[Weighted gene co-expression network analysis in biomedicine research].

PubMed

Liu, Wei; Li, Li; Ye, Hua; Tu, Wei

2017-11-25

High-throughput biological technologies are now widely applied in biology and medicine, allowing scientists to monitor thousands of parameters simultaneously in a specific sample. However, it is still an enormous challenge to mine useful information from high-throughput data. The emergence of network biology provides deeper insights into complex bio-system and reveals the modularity in tissue/cellular networks. Correlation networks are increasingly used in bioinformatics applications. Weighted gene co-expression network analysis (WGCNA) tool can detect clusters of highly correlated genes. Therefore, we systematically reviewed the application of WGCNA in the study of disease diagnosis, pathogenesis and other related fields. First, we introduced principle, workflow, advantages and disadvantages of WGCNA. Second, we presented the application of WGCNA in disease, physiology, drug, evolution and genome annotation. Then, we indicated the application of WGCNA in newly developed high-throughput methods. We hope this review will help to promote the application of WGCNA in biomedicine research.

A high-throughput screen for single gene activities: isolation of apoptosis inducers.

PubMed

Albayrak, Timur; Grimm, Stefan

2003-05-16

We describe a novel genetic screen that is performed by transfecting every individual clone of an expression library into a separate population of cells in a high-throughput mode. The screen allows one to achieve a hitherto unattained sensitivity in expression cloning which was exploited in a first read-out to clone apoptosis-inducing genes. This led to the isolation of several genes whose proteins induce distinct phenotypes of apoptosis in 293T cells. One of the isolated genes is the tumor suppressor cytochrome b(L) (cybL), a component of the respiratory chain complex II, that diminishes the activity of this complex for apoptosis induction. This gene is more efficient and specific for causing cell death than a drug with the same activity. These results suggest further applications, both of the isolated genes and the screen.

Characterization of three human cell line models for high-throughput neuronal cytotoxicity screening.

PubMed

Tong, Zhi-Bin; Hogberg, Helena; Kuo, David; Sakamuru, Srilatha; Xia, Menghang; Smirnova, Lena; Hartung, Thomas; Gerhold, David

2017-02-01

More than 75 000 man-made chemicals contaminate the environment; many of these have not been tested for toxicities. These chemicals demand quantitative high-throughput screening assays to assess them for causative roles in neurotoxicities, including Parkinson's disease and other neurodegenerative disorders. To facilitate high throughput screening for cytotoxicity to neurons, three human neuronal cellular models were compared: SH-SY5Y neuroblastoma cells, LUHMES conditionally-immortalized dopaminergic neurons, and Neural Stem Cells (NSC) derived from human fetal brain. These three cell lines were evaluated for rapidity and degree of differentiation, and sensitivity to 32 known or candidate neurotoxicants. First, expression of neural differentiation genes was assayed during a 7-day differentiation period. Of the three cell lines, LUHMES showed the highest gene expression of neuronal markers after differentiation. Both in the undifferentiated state and after 7 days of neuronal differentiation, LUHMES cells exhibited greater cytotoxic sensitivity to most of 32 suspected or known neurotoxicants than SH-SY5Y or NSCs. LUHMES cells were also unique in being more susceptible to several compounds in the differentiating state than in the undifferentiated state; including known neurotoxicants colchicine, methyl-mercury (II), and vincristine. Gene expression results suggest that differentiating LUHMES cells may be susceptible to apoptosis because they express low levels of anti-apoptotic genes BCL2 and BIRC5/survivin, whereas SH-SY5Y cells may be resistant to apoptosis because they express high levels of BCL2, BIRC5/survivin, and BIRC3 genes. Thus, LUHMES cells exhibited favorable characteristics for neuro-cytotoxicity screening: rapid differentiation into neurons that exhibit high level expression neuronal marker genes, and marked sensitivity of LUHMES cells to known neurotoxicants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

PubMed Central

Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher

2016-01-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

IAOseq: inferring abundance of overlapping genes using RNA-seq data.

PubMed

Sun, Hong; Yang, Shuang; Tun, Liangliang; Li, Yixue

2015-01-01

Overlapping transcription constitutes a common mechanism for regulating gene expression. A major limitation of the overlapping transcription assays is the lack of high throughput expression data. We developed a new tool (IAOseq) that is based on reads distributions along the transcribed regions to identify the expression levels of overlapping genes from standard RNA-seq data. Compared with five commonly used quantification methods, IAOseq showed better performance in the estimation accuracy of overlapping transcription levels. For the same strand overlapping transcription, currently existing high-throughput methods are rarely available to distinguish which strand was present in the original mRNA template. The IAOseq results showed that the commonly used methods gave an average of 1.6 fold overestimation of the expression levels of same strand overlapping genes. This work provides a useful tool for mining overlapping transcription levels from standard RNA-seq libraries. IAOseq could be used to help us understand the complex regulatory mechanism mediated by overlapping transcripts. IAOseq is freely available at http://lifecenter.sgst.cn/main/en/IAO_seq.jsp.

The Gene Expression Omnibus Database.

PubMed

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.

The Gene Expression Omnibus database

PubMed Central

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

A method for quantitative analysis of standard and high-throughput qPCR expression data based on input sample quantity.

PubMed

Adamski, Mateusz G; Gumann, Patryk; Baird, Alison E

2014-01-01

Over the past decade rapid advances have occurred in the understanding of RNA expression and its regulation. Quantitative polymerase chain reactions (qPCR) have become the gold standard for quantifying gene expression. Microfluidic next generation, high throughput qPCR now permits the detection of transcript copy number in thousands of reactions simultaneously, dramatically increasing the sensitivity over standard qPCR. Here we present a gene expression analysis method applicable to both standard polymerase chain reactions (qPCR) and high throughput qPCR. This technique is adjusted to the input sample quantity (e.g., the number of cells) and is independent of control gene expression. It is efficiency-corrected and with the use of a universal reference sample (commercial complementary DNA (cDNA)) permits the normalization of results between different batches and between different instruments--regardless of potential differences in transcript amplification efficiency. Modifications of the input quantity method include (1) the achievement of absolute quantification and (2) a non-efficiency corrected analysis. When compared to other commonly used algorithms the input quantity method proved to be valid. This method is of particular value for clinical studies of whole blood and circulating leukocytes where cell counts are readily available.

Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data

PubMed Central

Hassane, Duane C.; Guzman, Monica L.; Corbett, Cheryl; Li, Xiaojie; Abboud, Ramzi; Young, Fay; Liesveld, Jane L.; Carroll, Martin

2008-01-01

Increasing evidence indicates that malignant stem cells are important for the pathogenesis of acute myelogenous leukemia (AML) and represent a reservoir of cells that drive the development of AML and relapse. Therefore, new treatment regimens are necessary to prevent relapse and improve therapeutic outcomes. Previous studies have shown that the sesquiterpene lactone, parthenolide (PTL), ablates bulk, progenitor, and stem AML cells while causing no appreciable toxicity to normal hematopoietic cells. Thus, PTL must evoke cellular responses capable of mediating AML selective cell death. Given recent advances in chemical genomics such as gene expression-based high-throughput screening (GE-HTS) and the Connectivity Map, we hypothesized that the gene expression signature resulting from treatment of primary AML with PTL could be used to search for similar signatures in publicly available gene expression profiles deposited into the Gene Expression Omnibus (GEO). We therefore devised a broad in silico screen of the GEO database using the PTL gene expression signature as a template and discovered 2 new agents, celastrol and 4-hydroxy-2-nonenal, that effectively eradicate AML at the bulk, progenitor, and stem cell level. These findings suggest the use of multicenter collections of high-throughput data to facilitate discovery of leukemia drugs and drug targets. PMID:18305216

Pre-amplification in the context of high-throughput qPCR gene expression experiment.

PubMed

Korenková, Vlasta; Scott, Justin; Novosadová, Vendula; Jindřichová, Marie; Langerová, Lucie; Švec, David; Šídová, Monika; Sjöback, Robert

2015-03-11

With the introduction of the first high-throughput qPCR instrument on the market it became possible to perform thousands of reactions in a single run compared to the previous hundreds. In the high-throughput reaction, only limited volumes of highly concentrated cDNA or DNA samples can be added. This necessity can be solved by pre-amplification, which became a part of the high-throughput experimental workflow. Here, we focused our attention on the limits of the specific target pre-amplification reaction and propose the optimal, general setup for gene expression experiment using BioMark instrument (Fluidigm). For evaluating different pre-amplification factors following conditions were combined: four human blood samples from healthy donors and five transcripts having high to low expression levels; each cDNA sample was pre-amplified at four cycles (15, 18, 21, and 24) and five concentrations (equivalent to 0.078 ng, 0.32 ng, 1.25 ng, 5 ng, and 20 ng of total RNA). Factors identified as critical for a success of cDNA pre-amplification were cycle of pre-amplification, total RNA concentration, and type of gene. The selected pre-amplification reactions were further tested for optimal Cq distribution in a BioMark Array. The following concentrations combined with pre-amplification cycles were optimal for good quality samples: 20 ng of total RNA with 15 cycles of pre-amplification, 20x and 40x diluted; and 5 ng and 20 ng of total RNA with 18 cycles of pre-amplification, both 20x and 40x diluted. We set up upper limits for the bulk gene expression experiment using gene expression Dynamic Array and provided an easy-to-obtain tool for measuring of pre-amplification success. We also showed that variability of the pre-amplification, introduced into the experimental workflow of reverse transcription-qPCR, is lower than variability caused by the reverse transcription step.

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

Kolker, Eugene

Our project focused primarily on analysis of different types of data produced by global high-throughput technologies, data integration of gene annotation, and gene and protein expression information, as well as on getting a better functional annotation of Shewanella genes. Specifically, four of our numerous major activities and achievements include the development of: statistical models for identification and expression proteomics, superior to currently available approaches (including our own earlier ones); approaches to improve gene annotations on the whole-organism scale; standards for annotation, transcriptomics and proteomics approaches; and generalized approaches for data integration of gene annotation, gene and protein expression information.

A high-quality annotated transcriptome of swine peripheral blood

USDA-ARS?s Scientific Manuscript database

Background: High throughput gene expression profiling assays of peripheral blood are widely used in biomedicine, as well as in animal genetics and physiology research. Accurate, comprehensive, and precise interpretation of such high throughput assays relies on well-characterized reference genomes an...

Picking Cell Lines for High-Throughput Transcriptomic Toxicity Screening (SOT)

EPA Science Inventory

High throughput, whole genome transcriptomic profiling is a promising approach to comprehensively evaluate chemicals for potential biological effects. To be useful for in vitro toxicity screening, gene expression must be quantified in a set of representative cell types that captu...

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

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.

Design and construction of a first-generation high-throughput integrated robotic molecular biology platform for bioenergy applications.

PubMed

Hughes, Stephen R; Butt, Tauseef R; Bartolett, Scott; Riedmuller, Steven B; Farrelly, Philip

2011-08-01

The molecular biological techniques for plasmid-based assembly and cloning of gene open reading frames are essential for elucidating the function of the proteins encoded by the genes. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly clone and express heterologous gene open reading frames in bacteria and yeast and to screen large numbers of expressed proteins for optimized function are an important technology for improving microbial strains for biofuel production. The process involves the production of full-length complementary DNA libraries as a source of plasmid-based clones to express the desired proteins in active form for determination of their functions. Proteins that were identified by high-throughput screening as having desired characteristics are overexpressed in microbes to enable them to perform functions that will allow more cost-effective and sustainable production of biofuels. Because the plasmid libraries are composed of several thousand unique genes, automation of the process is essential. This review describes the design and implementation of an automated integrated programmable robotic workcell capable of producing complementary DNA libraries, colony picking, isolating plasmid DNA, transforming yeast and bacteria, expressing protein, and performing appropriate functional assays. These operations will allow tailoring microbial strains to use renewable feedstocks for production of biofuels, bioderived chemicals, fertilizers, and other coproducts for profitable and sustainable biorefineries. Published by Elsevier Inc.

Using Gene Expression Biomarkers to Identify Chemicals that Induce Key Events in Cancer and Endocrine Disruption AOPs: Androgen Receptor as an Example

EPA Science Inventory

High-throughput transcriptomic (HTTr) technologies are increasingly being used to screen environmental chemicals in vitro to provide mechanistic context for regulatory testing. The development of gene expression biomarkers that accurately predict molecular and toxicological effec...

A gene expression biomarker accurately predicts estrogen receptor α modulation in a human gene expression compendium

EPA Science Inventory

The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1...

Contributions to Statistical Problems Related to Microarray Data

ERIC Educational Resources Information Center

Hong, Feng

2009-01-01

Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

High-Throughput Cloning and Expression Library Creation for Functional Proteomics

PubMed Central

Festa, Fernanda; Steel, Jason; Bian, Xiaofang; Labaer, Joshua

2013-01-01

The study of protein function usually requires the use of a cloned version of the gene for protein expression and functional assays. This strategy is particular important when the information available regarding function is limited. The functional characterization of the thousands of newly identified proteins revealed by genomics requires faster methods than traditional single gene experiments, creating the need for fast, flexible and reliable cloning systems. These collections of open reading frame (ORF) clones can be coupled with high-throughput proteomics platforms, such as protein microarrays and cell-based assays, to answer biological questions. In this tutorial we provide the background for DNA cloning, discuss the major high-throughput cloning systems (Gateway® Technology, Flexi® Vector Systems, and Creator™ DNA Cloning System) and compare them side-by-side. We also report an example of high-throughput cloning study and its application in functional proteomics. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP12). Details can be found at http://www.proteomicstutorials.org. PMID:23457047

High-throughput cloning and expression library creation for functional proteomics.

PubMed

Festa, Fernanda; Steel, Jason; Bian, Xiaofang; Labaer, Joshua

2013-05-01

The study of protein function usually requires the use of a cloned version of the gene for protein expression and functional assays. This strategy is particularly important when the information available regarding function is limited. The functional characterization of the thousands of newly identified proteins revealed by genomics requires faster methods than traditional single-gene experiments, creating the need for fast, flexible, and reliable cloning systems. These collections of ORF clones can be coupled with high-throughput proteomics platforms, such as protein microarrays and cell-based assays, to answer biological questions. In this tutorial, we provide the background for DNA cloning, discuss the major high-throughput cloning systems (Gateway® Technology, Flexi® Vector Systems, and Creator(TM) DNA Cloning System) and compare them side-by-side. We also report an example of high-throughput cloning study and its application in functional proteomics. This tutorial is part of the International Proteomics Tutorial Programme (IPTP12). © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gene expression profiling of flax (Linum usitatissimum L.) under edaphic stress.

PubMed

Dmitriev, Alexey A; Kudryavtseva, Anna V; Krasnov, George S; Koroban, Nadezhda V; Speranskaya, Anna S; Krinitsina, Anastasia A; Belenikin, Maxim S; Snezhkina, Anastasiya V; Sadritdinova, Asiya F; Kishlyan, Natalya V; Rozhmina, Tatiana A; Yurkevich, Olga Yu; Muravenko, Olga V; Bolsheva, Nadezhda L; Melnikova, Nataliya V

2016-11-16

Cultivated flax (Linum usitatissimum L.) is widely used for production of textile, food, chemical and pharmaceutical products. However, various stresses decrease flax production. Search for genes, which are involved in stress response, is necessary for breeding of adaptive cultivars. Imbalanced concentration of nutrient elements in soil decrease flax yields and also results in heritable changes in some flax lines. The appearance of Linum Insertion Sequence 1 (LIS-1) is the most studied modification. However, LIS-1 function is still unclear. High-throughput sequencing of transcriptome of flax plants grown under normal (N), phosphate deficient (P), and nutrient excess (NPK) conditions was carried out using Illumina platform. The assembly of transcriptome was performed, and a total of 34924, 33797, and 33698 unique transcripts for N, P, and NPK sequencing libraries were identified, respectively. We have not revealed any LIS-1 derived mRNA in our sequencing data. The analysis of high-throughput sequencing data allowed us to identify genes with potentially differential expression under imbalanced nutrition. For further investigation with qPCR, 15 genes were chosen and their expression levels were evaluated in the extended sampling of 31 flax plants. Significant expression alterations were revealed for genes encoding WRKY and JAZ protein families under P and NPK conditions. Moreover, the alterations of WRKY family genes differed depending on LIS-1 presence in flax plant genome. Besides, we revealed slight and LIS-1 independent mRNA level changes of KRP2 and ING1 genes, which are adjacent to LIS-1, under nutrition stress. Differentially expressed genes were identified in flax plants, which were grown under phosphate deficiency and excess nutrition, on the basis of high-throughput sequencing and qPCR data. We showed that WRKY and JAS gene families participate in flax response to imbalanced nutrient content in soil. Besides, we have not identified any mRNA, which could be derived from LIS-1, in our transcriptome sequencing data. Expression of LIS-1 flanking genes, ING1 and KRP2, was suggested not to be nutrient stress-induced. Obtained results provide new insights into edaphic stress response in flax and the role of LIS-1 in these process.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium.

PubMed

Ryan, Natalia; Chorley, Brian; Tice, Raymond R; Judson, Richard; Corton, J Christopher

2016-05-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

Searching for resistance genes to Bursaphelenchus xylophilus using high throughput screening.

PubMed

Santos, Carla S; Pinheiro, Miguel; Silva, Ana I; Egas, Conceição; Vasconcelos, Marta W

2012-11-07

Pine wilt disease (PWD), caused by the pinewood nematode (PWN; Bursaphelenchus xylophilus), damages and kills pine trees and is causing serious economic damage worldwide. Although the ecological mechanism of infestation is well described, the plant's molecular response to the pathogen is not well known. This is due mainly to the lack of genomic information and the complexity of the disease. High throughput sequencing is now an efficient approach for detecting the expression of genes in non-model organisms, thus providing valuable information in spite of the lack of the genome sequence. In an attempt to unravel genes potentially involved in the pine defense against the pathogen, we hereby report the high throughput comparative sequence analysis of infested and non-infested stems of Pinus pinaster (very susceptible to PWN) and Pinus pinea (less susceptible to PWN). Four cDNA libraries from infested and non-infested stems of P. pinaster and P. pinea were sequenced in a full 454 GS FLX run, producing a total of 2,083,698 reads. The putative amino acid sequences encoded by the assembled transcripts were annotated according to Gene Ontology, to assign Pinus contigs into Biological Processes, Cellular Components and Molecular Functions categories. Most of the annotated transcripts corresponded to Picea genes-25.4-39.7%, whereas a smaller percentage, matched Pinus genes, 1.8-12.8%, probably a consequence of more public genomic information available for Picea than for Pinus. The comparative transcriptome analysis showed that when P. pinaster was infested with PWN, the genes malate dehydrogenase, ABA, water deficit stress related genes and PAR1 were highly expressed, while in PWN-infested P. pinea, the highly expressed genes were ricin B-related lectin, and genes belonging to the SNARE and high mobility group families. Quantitative PCR experiments confirmed the differential gene expression between the two pine species. Defense-related genes triggered by nematode infestation were detected in both P. pinaster and P. pinea transcriptomes utilizing 454 pyrosequencing technology. P. pinaster showed higher abundance of genes related to transcriptional regulation, terpenoid secondary metabolism (including some with nematicidal activity) and pathogen attack. P. pinea showed higher abundance of genes related to oxidative stress and higher levels of expression in general of stress responsive genes. This study provides essential information about the molecular defense mechanisms utilized by P. pinaster and P. pinea against PWN infestation and contributes to a better understanding of PWD.

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks

PubMed Central

Trapnell, Cole; Roberts, Adam; Goff, Loyal; Pertea, Geo; Kim, Daehwan; Kelley, David R; Pimentel, Harold; Salzberg, Steven L; Rinn, John L; Pachter, Lior

2012-01-01

Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ~1 h of hands-on time. PMID:22383036

Confident difference criterion: a new Bayesian differentially expressed gene selection algorithm with applications.

PubMed

Yu, Fang; Chen, Ming-Hui; Kuo, Lynn; Talbott, Heather; Davis, John S

2015-08-07

Recently, the Bayesian method becomes more popular for analyzing high dimensional gene expression data as it allows us to borrow information across different genes and provides powerful estimators for evaluating gene expression levels. It is crucial to develop a simple but efficient gene selection algorithm for detecting differentially expressed (DE) genes based on the Bayesian estimators. In this paper, by extending the two-criterion idea of Chen et al. (Chen M-H, Ibrahim JG, Chi Y-Y. A new class of mixture models for differential gene expression in DNA microarray data. J Stat Plan Inference. 2008;138:387-404), we propose two new gene selection algorithms for general Bayesian models and name these new methods as the confident difference criterion methods. One is based on the standardized differences between two mean expression values among genes; the other adds the differences between two variances to it. The proposed confident difference criterion methods first evaluate the posterior probability of a gene having different gene expressions between competitive samples and then declare a gene to be DE if the posterior probability is large. The theoretical connection between the proposed first method based on the means and the Bayes factor approach proposed by Yu et al. (Yu F, Chen M-H, Kuo L. Detecting differentially expressed genes using alibrated Bayes factors. Statistica Sinica. 2008;18:783-802) is established under the normal-normal-model with equal variances between two samples. The empirical performance of the proposed methods is examined and compared to those of several existing methods via several simulations. The results from these simulation studies show that the proposed confident difference criterion methods outperform the existing methods when comparing gene expressions across different conditions for both microarray studies and sequence-based high-throughput studies. A real dataset is used to further demonstrate the proposed methodology. In the real data application, the confident difference criterion methods successfully identified more clinically important DE genes than the other methods. The confident difference criterion method proposed in this paper provides a new efficient approach for both microarray studies and sequence-based high-throughput studies to identify differentially expressed genes.

Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data.

PubMed

Yang, Laurence; Tan, Justin; O'Brien, Edward J; Monk, Jonathan M; Kim, Donghyuk; Li, Howard J; Charusanti, Pep; Ebrahim, Ali; Lloyd, Colton J; Yurkovich, James T; Du, Bin; Dräger, Andreas; Thomas, Alex; Sun, Yuekai; Saunders, Michael A; Palsson, Bernhard O

2015-08-25

Finding the minimal set of gene functions needed to sustain life is of both fundamental and practical importance. Minimal gene lists have been proposed by using comparative genomics-based core proteome definitions. A definition of a core proteome that is supported by empirical data, is understood at the systems-level, and provides a basis for computing essential cell functions is lacking. Here, we use a systems biology-based genome-scale model of metabolism and expression to define a functional core proteome consisting of 356 gene products, accounting for 44% of the Escherichia coli proteome by mass based on proteomics data. This systems biology core proteome includes 212 genes not found in previous comparative genomics-based core proteome definitions, accounts for 65% of known essential genes in E. coli, and has 78% gene function overlap with minimal genomes (Buchnera aphidicola and Mycoplasma genitalium). Based on transcriptomics data across environmental and genetic backgrounds, the systems biology core proteome is significantly enriched in nondifferentially expressed genes and depleted in differentially expressed genes. Compared with the noncore, core gene expression levels are also similar across genetic backgrounds (two times higher Spearman rank correlation) and exhibit significantly more complex transcriptional and posttranscriptional regulatory features (40% more transcription start sites per gene, 22% longer 5'UTR). Thus, genome-scale systems biology approaches rigorously identify a functional core proteome needed to support growth. This framework, validated by using high-throughput datasets, facilitates a mechanistic understanding of systems-level core proteome function through in silico models; it de facto defines a paleome.

Systematic Analysis of Zn2Cys6 Transcription Factors Required for Development and Pathogenicity by High-Throughput Gene Knockout in the Rice Blast Fungus

PubMed Central

Huang, Pengyun; Lin, Fucheng

2014-01-01

Because of great challenges and workload in deleting genes on a large scale, the functions of most genes in pathogenic fungi are still unclear. In this study, we developed a high-throughput gene knockout system using a novel yeast-Escherichia-Agrobacterium shuttle vector, pKO1B, in the rice blast fungus Magnaporthe oryzae. Using this method, we deleted 104 fungal-specific Zn2Cys6 transcription factor (TF) genes in M. oryzae. We then analyzed the phenotypes of these mutants with regard to growth, asexual and infection-related development, pathogenesis, and 9 abiotic stresses. The resulting data provide new insights into how this rice pathogen of global significance regulates important traits in the infection cycle through Zn2Cys6TF genes. A large variation in biological functions of Zn2Cys6TF genes was observed under the conditions tested. Sixty-one of 104 Zn2Cys6 TF genes were found to be required for fungal development. In-depth analysis of TF genes revealed that TF genes involved in pathogenicity frequently tend to function in multiple development stages, and disclosed many highly conserved but unidentified functional TF genes of importance in the fungal kingdom. We further found that the virulence-required TF genes GPF1 and CNF2 have similar regulation mechanisms in the gene expression involved in pathogenicity. These experimental validations clearly demonstrated the value of a high-throughput gene knockout system in understanding the biological functions of genes on a genome scale in fungi, and provided a solid foundation for elucidating the gene expression network that regulates the development and pathogenicity of M. oryzae. PMID:25299517

Identification, Expression Analysis, and Target Prediction of Flax Genotroph MicroRNAs Under Normal and Nutrient Stress Conditions

PubMed Central

Melnikova, Nataliya V.; Dmitriev, Alexey A.; Belenikin, Maxim S.; Koroban, Nadezhda V.; Speranskaya, Anna S.; Krinitsina, Anastasia A.; Krasnov, George S.; Lakunina, Valentina A.; Snezhkina, Anastasiya V.; Sadritdinova, Asiya F.; Kishlyan, Natalya V.; Rozhmina, Tatiana A.; Klimina, Kseniya M.; Amosova, Alexandra V.; Zelenin, Alexander V.; Muravenko, Olga V.; Bolsheva, Nadezhda L.; Kudryavtseva, Anna V.

2016-01-01

Cultivated flax (Linum usitatissimum L.) is an important plant valuable for industry. Some flax lines can undergo heritable phenotypic and genotypic changes (LIS-1 insertion being the most common) in response to nutrient stress and are called plastic lines. Offspring of plastic lines, which stably inherit the changes, are called genotrophs. MicroRNAs (miRNAs) are involved in a crucial regulatory mechanism of gene expression. They have previously been assumed to take part in nutrient stress response and can, therefore, participate in genotroph formation. In the present study, we performed high-throughput sequencing of small RNAs (sRNAs) extracted from flax plants grown under normal, phosphate deficient and nutrient excess conditions to identify miRNAs and evaluate their expression. Our analysis revealed expression of 96 conserved miRNAs from 21 families in flax. Moreover, 475 novel potential miRNAs were identified for the first time, and their targets were predicted. However, none of the identified miRNAs were transcribed from LIS-1. Expression of seven miRNAs (miR168, miR169, miR395, miR398, miR399, miR408, and lus-miR-N1) with up- or down-regulation under nutrient stress (on the basis of high-throughput sequencing data) was evaluated on extended sampling using qPCR. Reference gene search identified ETIF3H and ETIF3E genes as most suitable for this purpose. Down-regulation of novel potential lus-miR-N1 and up-regulation of conserved miR399 were revealed under the phosphate deficient conditions. In addition, the negative correlation of expression of lus-miR-N1 and its predicted target, ubiquitin-activating enzyme E1 gene, as well as, miR399 and its predicted target, ubiquitin-conjugating enzyme E2 gene, was observed. Thus, in our study, miRNAs expressed in flax plastic lines and genotrophs were identified and their expression and expression of their targets was evaluated using high-throughput sequencing and qPCR for the first time. These data provide new insights into nutrient stress response regulation in plastic flax cultivars. PMID:27092149

Selecting the most appropriate time points to profile in high-throughput studies

PubMed Central

Kleyman, Michael; Sefer, Emre; Nicola, Teodora; Espinoza, Celia; Chhabra, Divya; Hagood, James S; Kaminski, Naftali; Ambalavanan, Namasivayam; Bar-Joseph, Ziv

2017-01-01

Biological systems are increasingly being studied by high throughput profiling of molecular data over time. Determining the set of time points to sample in studies that profile several different types of molecular data is still challenging. Here we present the Time Point Selection (TPS) method that solves this combinatorial problem in a principled and practical way. TPS utilizes expression data from a small set of genes sampled at a high rate. As we show by applying TPS to study mouse lung development, the points selected by TPS can be used to reconstruct an accurate representation for the expression values of the non selected points. Further, even though the selection is only based on gene expression, these points are also appropriate for representing a much larger set of protein, miRNA and DNA methylation changes over time. TPS can thus serve as a key design strategy for high throughput time series experiments. Supporting Website: www.sb.cs.cmu.edu/TPS DOI: http://dx.doi.org/10.7554/eLife.18541.001 PMID:28124972

High-Throughput Microfluidic Labyrinth for the Label-free Isolation of Circulating Tumor Cells.

PubMed

Lin, Eric; Rivera-Báez, Lianette; Fouladdel, Shamileh; Yoon, Hyeun Joong; Guthrie, Stephanie; Wieger, Jacob; Deol, Yadwinder; Keller, Evan; Sahai, Vaibhav; Simeone, Diane M; Burness, Monika L; Azizi, Ebrahim; Wicha, Max S; Nagrath, Sunitha

2017-09-27

We present "Labyrinth," a label-free microfluidic device to isolate circulating tumor cells (CTCs) using the combination of long loops and sharp corners to focus both CTCs and white blood cells (WBCs) at a high throughput of 2.5 mL/min. The high yield (>90%) and purity (600 WBCs/mL) of Labyrinth enabled us to profile gene expression in CTCs. As proof of principle, we used previously established cancer stem cell gene signatures to profile single cells isolated from the blood of breast cancer patients. We observed heterogeneous subpopulations of CTCs expressing genes for stem cells, epithelial cells, mesenchymal cells, and cells transitioning between epithelial and mesenchymal. Labyrinth offers a cell-surface marker-independent single-cell isolation platform to study heterogeneous CTC subpopulations. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of high-throughput biological data using their rank values.

PubMed

Dembélé, Doulaye

2018-01-01

High-throughput biological technologies are routinely used to generate gene expression profiling or cytogenetics data. To achieve high performance, methods available in the literature become more specialized and often require high computational resources. Here, we propose a new versatile method based on the data-ordering rank values. We use linear algebra, the Perron-Frobenius theorem and also extend a method presented earlier for searching differentially expressed genes for the detection of recurrent copy number aberration. A result derived from the proposed method is a one-sample Student's t-test based on rank values. The proposed method is to our knowledge the only that applies to gene expression profiling and to cytogenetics data sets. This new method is fast, deterministic, and requires a low computational load. Probabilities are associated with genes to allow a statistically significant subset selection in the data set. Stability scores are also introduced as quality parameters. The performance and comparative analyses were carried out using real data sets. The proposed method can be accessed through an R package available from the CRAN (Comprehensive R Archive Network) website: https://cran.r-project.org/web/packages/fcros .

Identification of in vivo regulators of the Vibrio cholerae xds gene using a high-throughput genetic selection

PubMed Central

McDonough, EmilyKate; Lazinski, David W.; Camilli, Andrew

2014-01-01

Summary Vibrio cholerae, the causative agent of cholera, remains a threat to public health in areas with inadequate sanitation. As a waterborne pathogen, V. cholerae moves between two dissimilar environments, aquatic reservoirs and the intestinal tract of humans. Accordingly, this pathogen undergoes adaptive shifts in gene expression throughout the different stages of its lifecycle. One particular gene, xds, encodes a secreted exonuclease that was previously identified as being induced during infection. Here we sought to identify regulators responsible for the in vivo-specific induction of xds. A transcriptional fusion of xds to two consecutive antibiotic resistance genes was used to select transposon mutants that had inserted within or adjacent to regulatory genes and thereby caused increased expression of the xds fusion under non-inducing conditions. Large pools of selected insertion sites were sequenced in a high throughput manner using Tn-seq to identify potential mechanisms of xds regulation. Our selection identified the two-component system PhoB/R as the dominant activator of xds expression. In vitro validation confirmed that PhoB, a protein which is only active during phosphate limitation, was responsible for xds activation. Using xds expression as a biosensor of the extracellular phosphate level, we observed that the mouse small intestine is a phosphate-limited environment. PMID:24673931

Ribosomal Binding Site Switching: An Effective Strategy for High-Throughput Cloning Constructions

PubMed Central

Li, Yunlong; Zhang, Yong; Lu, Pei; Rayner, Simon; Chen, Shiyun

2012-01-01

Direct cloning of PCR fragments by TA cloning or blunt end ligation are two simple methods which would greatly benefit high-throughput (HTP) cloning constructions if the efficiency can be improved. In this study, we have developed a ribosomal binding site (RBS) switching strategy for direct cloning of PCR fragments. RBS is an A/G rich region upstream of the translational start codon and is essential for gene expression. Change from A/G to T/C in the RBS blocks its activity and thereby abolishes gene expression. Based on this property, we introduced an inactive RBS upstream of a selectable marker gene, and designed a fragment insertion site within this inactive RBS. Forward and reverse insertions of specifically tailed fragments will respectively form an active and inactive RBS, thus all background from vector self-ligation and fragment reverse insertions will be eliminated due to the non-expression of the marker gene. The effectiveness of our strategy for TA cloning and blunt end ligation are confirmed. Application of this strategy to gene over-expression, a bacterial two-hybrid system, a bacterial one-hybrid system, and promoter bank construction are also verified. The advantages of this simple procedure, together with its low cost and high efficiency, makes our strategy extremely useful in HTP cloning constructions. PMID:23185557

Discovering causal signaling pathways through gene-expression patterns

PubMed Central

Parikh, Jignesh R.; Klinger, Bertram; Xia, Yu; Marto, Jarrod A.; Blüthgen, Nils

2010-01-01

High-throughput gene-expression studies result in lists of differentially expressed genes. Most current meta-analyses of these gene lists include searching for significant membership of the translated proteins in various signaling pathways. However, such membership enrichment algorithms do not provide insight into which pathways caused the genes to be differentially expressed in the first place. Here, we present an intuitive approach for discovering upstream signaling pathways responsible for regulating these differentially expressed genes. We identify consistently regulated signature genes specific for signal transduction pathways from a panel of single-pathway perturbation experiments. An algorithm that detects overrepresentation of these signature genes in a gene group of interest is used to infer the signaling pathway responsible for regulation. We expose our novel resource and algorithm through a web server called SPEED: Signaling Pathway Enrichment using Experimental Data sets. SPEED can be freely accessed at http://speed.sys-bio.net/. PMID:20494976

Identification of two integration sites in favor of transgene expression in Trichoderma reesei.

PubMed

Qin, Lina; Jiang, Xianzhang; Dong, Zhiyang; Huang, Jianzhong; Chen, Xiuzhen

2018-01-01

The ascomycete fungus Trichoderma reesei was widely used as a biotechnological workhorse for production of cellulases and recombinant proteins due to its large capacity of protein secretion. Transgenesis by random integration of a gene of interest (GOI) into the genome of T. reesei can generate series of strains that express different levels of the indicated transgene. The insertion site of the GOI plays an important role in the ultimate production of the targeted proteins. However, so far no systematic studies have been made to identify transgene integration loci for optimal expression of the GOI in T. reesei . Currently, only the locus of exocellobiohydrolases I encoding gene ( cbh1) is widely used as a promising integration site to lead to high expression level of the GOI. No additional sites associated with efficient gene expression have been characterized. To search for gene integration sites that benefit for the secreted expression of GOI, the food-and-mouth disease virus 2A protein was applied for co-expression of an Aspergillus niger lipA gene and Discosoma sp. DsRed1 gene in T. reesei, by random integration of the expression cassette into the genome. We demonstrated that the fluorescent intensity of RFP (red fluorescent protein) inside of the cell was well correlated with the secreted lipase yields, based on which, we successfully developed a high-throughput screening method to screen strains with relatively higher secreted expression of the GOI (in this study, lipase). The copy number and the insertion sites of the transgene were investigated among the selected highly expressed strains. Eventually, in addition to cbh1 gene locus, two other genome insertion loci that efficiently facilitate gene expression in T. reesei were identified. We have successfully developed a high-throughput screening method to screen strains with optimal expression of the indicated secreted proteins in T. reesei . Moreover, we identified two optimal genome loci for transgene expression, which could provide new approach to modulate gene expression levels while retaining the indicated promoter and culture conditions.

Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism.

PubMed

Nemenman, Ilya; Escola, G Sean; Hlavacek, William S; Unkefer, Pat J; Unkefer, Clifford J; Wall, Michael E

2007-12-01

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For benchmarking purposes, we generate synthetic metabolic profiles based on a well-established model for red blood cell metabolism. A variety of data sets are generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We use ARACNE, a mainstream algorithm for reverse engineering of transcriptional regulatory networks from gene expression data, to predict metabolic interactions from these data sets. We find that the performance of ARACNE on metabolic data is comparable to that on gene expression data.

Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells.

PubMed

Gatto, Sole; Puri, Pier Lorenzo; Malecova, Barbora

2017-01-01

Single cell gene expression profiling is a fundamental tool for studying the heterogeneity of a cell population by addressing the phenotypic and functional characteristics of each cell. Technological advances that have coupled microfluidic technologies with high-throughput quantitative RT-PCR analyses have enabled detailed analyses of single cells in various biological contexts. In this chapter, we describe the procedure for isolating the skeletal muscle interstitial cells termed Fibro-Adipogenic Progenitors (FAPs ) and their gene expression profiling at the single cell level. Moreover, we accompany our bench protocol with bioinformatics analysis designed to process raw data as well as to visualize single cell gene expression data. Single cell gene expression profiling is therefore a useful tool in the investigation of FAPs heterogeneity and their contribution to muscle homeostasis.

Identification and consequences of miRNA-target interactions--beyond repression of gene expression.

PubMed

Hausser, Jean; Zavolan, Mihaela

2014-09-01

Comparative genomics analyses and high-throughput experimental studies indicate that a microRNA (miRNA) binds to hundreds of sites across the transcriptome. Although the knockout of components of the miRNA biogenesis pathway has profound phenotypic consequences, most predicted miRNA targets undergo small changes at the mRNA and protein levels when the expression of the miRNA is perturbed. Alternatively, miRNAs can establish thresholds in and increase the coherence of the expression of their target genes, as well as reduce the cell-to-cell variability in target gene expression. Here, we review the recent progress in identifying miRNA targets and the emerging paradigms of how miRNAs shape the dynamics of target gene expression.

MINER: exploratory analysis of gene interaction networks by machine learning from expression data.

PubMed

Kadupitige, Sidath Randeni; Leung, Kin Chun; Sellmeier, Julia; Sivieng, Jane; Catchpoole, Daniel R; Bain, Michael E; Gaëta, Bruno A

2009-12-03

The reconstruction of gene regulatory networks from high-throughput "omics" data has become a major goal in the modelling of living systems. Numerous approaches have been proposed, most of which attempt only "one-shot" reconstruction of the whole network with no intervention from the user, or offer only simple correlation analysis to infer gene dependencies. We have developed MINER (Microarray Interactive Network Exploration and Representation), an application that combines multivariate non-linear tree learning of individual gene regulatory dependencies, visualisation of these dependencies as both trees and networks, and representation of known biological relationships based on common Gene Ontology annotations. MINER allows biologists to explore the dependencies influencing the expression of individual genes in a gene expression data set in the form of decision, model or regression trees, using their domain knowledge to guide the exploration and formulate hypotheses. Multiple trees can then be summarised in the form of a gene network diagram. MINER is being adopted by several of our collaborators and has already led to the discovery of a new significant regulatory relationship with subsequent experimental validation. Unlike most gene regulatory network inference methods, MINER allows the user to start from genes of interest and build the network gene-by-gene, incorporating domain expertise in the process. This approach has been used successfully with RNA microarray data but is applicable to other quantitative data produced by high-throughput technologies such as proteomics and "next generation" DNA sequencing.

Widespread Enhancer Activity from Core Promoters.

PubMed

Medina-Rivera, Alejandra; Santiago-Algarra, David; Puthier, Denis; Spicuglia, Salvatore

2018-06-01

Gene expression in higher eukaryotes is precisely regulated in time and space through the interplay between promoters and gene-distal regulatory regions, known as enhancers. The original definition of enhancers implies the ability to activate gene expression remotely, while promoters entail the capability to locally induce gene expression. Despite the conventional distinction between them, promoters and enhancers share many genomic and epigenomic features. One intriguing finding in the gene regulation field comes from the observation that many core promoter regions display enhancer activity. Recent high-throughput reporter assays along with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-related approaches have indicated that this phenomenon is common and might have a strong impact on our global understanding of genome organisation and gene expression regulation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Object-location training elicits an overlapping but temporally distinct transcriptional profile from contextual fear conditioning.

PubMed

Poplawski, Shane G; Schoch, Hannah; Wimmer, Mathieu; Hawk, Joshua D; Walsh, Jennifer L; Giese, Karl P; Abel, Ted

2014-12-01

Hippocampus-dependent learning is known to induce changes in gene expression, but information on gene expression differences between different learning paradigms that require the hippocampus is limited. The bulk of studies investigating RNA expression after learning use the contextual fear conditioning task, which couples a novel environment with a footshock. Although contextual fear conditioning has been useful in discovering gene targets, gene expression after spatial memory tasks has received less attention. In this study, we used the object-location memory task and studied gene expression at two time points after learning in a high-throughput manner using a microfluidic qPCR approach. We found that expression of the classic immediate-early genes changes after object-location training in a fashion similar to that observed after contextual fear conditioning. However, the temporal dynamics of gene expression are different between the two tasks, with object-location memory producing gene expression changes that last at least 2 hours. Our findings indicate that different training paradigms may give rise to distinct temporal dynamics of gene expression after learning. Copyright © 2014 Elsevier Inc. All rights reserved.

Object-Location Training Elicits an Overlapping but Temporally Distinct Transcriptional Profile from Contextual Fear Conditioning

PubMed Central

Wimmer, Mathieu; Hawk, Joshua D.; Walsh, Jennifer L.; Giese, Karl P.; Abel, Ted

2014-01-01

Hippocampus-dependent learning is known to induce changes in gene expression, but information on gene expression differences between different learning paradigms that require the hippocampus is limited. The bulk of studies investigating RNA expression after learning use the contextual fear conditioning task, which couples a novel environment with a footshock. Although contextual fear conditioning has been useful in discovering gene targets, gene expression after spatial memory tasks has received less attention. In this study, we used the object-location memory task and studied gene expression at two time points after learning in a high-throughput manner using a microfluidic qPCR approach. We found that expression of the classic immediate-early genes changes after object-location training in a fashion similar to that observed after contextual fear conditioning. However, the temporal dynamics of gene expression are different between the two tasks, with object-location memory producing gene expression changes that last at least 2 hours. Our findings indicate that different training paradigms may give rise to distinct temporal dynamics of gene expression after learning. PMID:25242102

Searching for resistance genes to Bursaphelenchus xylophilus using high throughput screening

PubMed Central

2012-01-01

Background Pine wilt disease (PWD), caused by the pinewood nematode (PWN; Bursaphelenchus xylophilus), damages and kills pine trees and is causing serious economic damage worldwide. Although the ecological mechanism of infestation is well described, the plant’s molecular response to the pathogen is not well known. This is due mainly to the lack of genomic information and the complexity of the disease. High throughput sequencing is now an efficient approach for detecting the expression of genes in non-model organisms, thus providing valuable information in spite of the lack of the genome sequence. In an attempt to unravel genes potentially involved in the pine defense against the pathogen, we hereby report the high throughput comparative sequence analysis of infested and non-infested stems of Pinus pinaster (very susceptible to PWN) and Pinus pinea (less susceptible to PWN). Results Four cDNA libraries from infested and non-infested stems of P. pinaster and P. pinea were sequenced in a full 454 GS FLX run, producing a total of 2,083,698 reads. The putative amino acid sequences encoded by the assembled transcripts were annotated according to Gene Ontology, to assign Pinus contigs into Biological Processes, Cellular Components and Molecular Functions categories. Most of the annotated transcripts corresponded to Picea genes-25.4-39.7%, whereas a smaller percentage, matched Pinus genes, 1.8-12.8%, probably a consequence of more public genomic information available for Picea than for Pinus. The comparative transcriptome analysis showed that when P. pinaster was infested with PWN, the genes malate dehydrogenase, ABA, water deficit stress related genes and PAR1 were highly expressed, while in PWN-infested P. pinea, the highly expressed genes were ricin B-related lectin, and genes belonging to the SNARE and high mobility group families. Quantitative PCR experiments confirmed the differential gene expression between the two pine species. Conclusions Defense-related genes triggered by nematode infestation were detected in both P. pinaster and P. pinea transcriptomes utilizing 454 pyrosequencing technology. P. pinaster showed higher abundance of genes related to transcriptional regulation, terpenoid secondary metabolism (including some with nematicidal activity) and pathogen attack. P. pinea showed higher abundance of genes related to oxidative stress and higher levels of expression in general of stress responsive genes. This study provides essential information about the molecular defense mechanisms utilized by P. pinaster and P. pinea against PWN infestation and contributes to a better understanding of PWD. PMID:23134679

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

Prediction of in vivo hepatotoxicity effects using in vitro transcriptomics data (SOT)

EPA Science Inventory

High-throughput in vitro transcriptomics data support molecular understanding of chemical-induced toxicity. Here, we evaluated the utility of such data to predict liver toxicity. First, in vitro gene expression data for 93 genes was generated following exposure of metabolically c...

Automated solid-phase subcloning based on beads brought into proximity by magnetic force.

PubMed

Hudson, Elton P; Nikoshkov, Andrej; Uhlen, Mathias; Rockberg, Johan

2012-01-01

In the fields of proteomics, metabolic engineering and synthetic biology there is a need for high-throughput and reliable cloning methods to facilitate construction of expression vectors and genetic pathways. Here, we describe a new approach for solid-phase cloning in which both the vector and the gene are immobilized to separate paramagnetic beads and brought into proximity by magnetic force. Ligation events were directly evaluated using fluorescent-based microscopy and flow cytometry. The highest ligation efficiencies were obtained when gene- and vector-coated beads were brought into close contact by application of a magnet during the ligation step. An automated procedure was developed using a laboratory workstation to transfer genes into various expression vectors and more than 95% correct clones were obtained in a number of various applications. The method presented here is suitable for efficient subcloning in an automated manner to rapidly generate a large number of gene constructs in various vectors intended for high throughput applications.

Automated Solid-Phase Subcloning Based on Beads Brought into Proximity by Magnetic Force

PubMed Central

Hudson, Elton P.; Nikoshkov, Andrej; Uhlen, Mathias; Rockberg, Johan

2012-01-01

In the fields of proteomics, metabolic engineering and synthetic biology there is a need for high-throughput and reliable cloning methods to facilitate construction of expression vectors and genetic pathways. Here, we describe a new approach for solid-phase cloning in which both the vector and the gene are immobilized to separate paramagnetic beads and brought into proximity by magnetic force. Ligation events were directly evaluated using fluorescent-based microscopy and flow cytometry. The highest ligation efficiencies were obtained when gene- and vector-coated beads were brought into close contact by application of a magnet during the ligation step. An automated procedure was developed using a laboratory workstation to transfer genes into various expression vectors and more than 95% correct clones were obtained in a number of various applications. The method presented here is suitable for efficient subcloning in an automated manner to rapidly generate a large number of gene constructs in various vectors intended for high throughput applications. PMID:22624028

Gene-Expression Biomarkers for Application to High-Throughput Radiation Biodosimetry

DTIC Science & Technology

2005-01-01

nuclear disaster . Even with the delayed onset of symptoms, sometimes several days after exposure, gene-expression biomarkers can identify these exposed individuals very early after exposure, allowing for prompt medical intervention. This early assessment of a radiation dose after exposure would enhance the operational commander’s situational awareness of the radiation exposure status of deployed units and increase the prospect of reduced morbidity and mortality through early medical intervention. Candidate gene targets were selected from microarray studies of ex

High-throughput cell-based screening reveals a role for ZNF131 as a repressor of ERalpha signaling

PubMed Central

Han, Xiao; Guo, Jinhai; Deng, Weiwei; Zhang, Chenying; Du, Peige; Shi, Taiping; Ma, Dalong

2008-01-01

Background Estrogen receptor α (ERα) is a transcription factor whose activity is affected by multiple regulatory cofactors. In an effort to identify the human genes involved in the regulation of ERα, we constructed a high-throughput, cell-based, functional screening platform by linking a response element (ERE) with a reporter gene. This allowed the cellular activity of ERα, in cells cotransfected with the candidate gene, to be quantified in the presence or absence of its cognate ligand E2. Results From a library of 570 human cDNA clones, we identified zinc finger protein 131 (ZNF131) as a repressor of ERα mediated transactivation. ZNF131 is a typical member of the BTB/POZ family of transcription factors, and shows both ubiquitous expression and a high degree of sequence conservation. The luciferase reporter gene assay revealed that ZNF131 inhibits ligand-dependent transactivation by ERα in a dose-dependent manner. Electrophoretic mobility shift assay clearly demonstrated that the interaction between ZNF131 and ERα interrupts or prevents ERα binding to the estrogen response element (ERE). In addition, ZNF131 was able to suppress the expression of pS2, an ERα target gene. Conclusion We suggest that the functional screening platform we constructed can be applied for high-throughput genomic screening candidate ERα-related genes. This in turn may provide new insights into the underlying molecular mechanisms of ERα regulation in mammalian cells. PMID:18847501

Strain Library Imaging Protocol for high-throughput, automated single-cell microscopy of large bacterial collections arrayed on multiwell plates.

PubMed

Shi, Handuo; Colavin, Alexandre; Lee, Timothy K; Huang, Kerwyn Casey

2017-02-01

Single-cell microscopy is a powerful tool for studying gene functions using strain libraries, but it suffers from throughput limitations. Here we describe the Strain Library Imaging Protocol (SLIP), which is a high-throughput, automated microscopy workflow for large strain collections that requires minimal user involvement. SLIP involves transferring arrayed bacterial cultures from multiwell plates onto large agar pads using inexpensive replicator pins and automatically imaging the resulting single cells. The acquired images are subsequently reviewed and analyzed by custom MATLAB scripts that segment single-cell contours and extract quantitative metrics. SLIP yields rich data sets on cell morphology and gene expression that illustrate the function of certain genes and the connections among strains in a library. For a library arrayed on 96-well plates, image acquisition can be completed within 4 min per plate.

Evaluating between-pathway models with expression data.

PubMed

Hescott, B J; Leiserson, M D M; Cowen, L J; Slonim, D K

2010-03-01

Between-pathway models (BPMs) are network motifs consisting of pairs of putative redundant pathways. In this article, we show how adding another source of high-throughput data--microarray gene expression data from knockout experiments--allows us to identify a compensatory functional relationship between genes from the two BPM pathways. We evaluate the quality of the BPMs from four different studies, and we describe how our methods might be extended to refine pathways.

Identification of in vivo regulators of the Vibrio cholerae xds gene using a high-throughput genetic selection.

PubMed

McDonough, Emilykate; Lazinski, David W; Camilli, Andrew

2014-04-01

Vibrio cholerae, the causative agent of cholera, remains a threat to public health in areas with inadequate sanitation. As a waterborne pathogen, V. cholerae moves between two dissimilar environments, aquatic reservoirs and the intestinal tract of humans. Accordingly, this pathogen undergoes adaptive shifts in gene expression throughout the different stages of its lifecycle. One particular gene, xds, encodes a secreted exonuclease that was previously identified as being induced during infection. Here we sought to identify regulators responsible for the in vivo-specific induction of xds. A transcriptional fusion of xds to two consecutive antibiotic resistance genes was used to select transposon mutants that had inserted within or adjacent to regulatory genes and thereby caused increased expression of the xds fusion under non-inducing conditions. Large pools of selected insertion sites were sequenced in a high throughput manner using Tn-seq to identify potential mechanisms of xds regulation. Our selection identified the two-component system PhoB/R as the dominant activator of xds expression. In vitro validation confirmed that PhoB, a protein which is only active during phosphate limitation, was responsible for xds activation. Using xds expression as a biosensor of the extracellular phosphate level, we observed that the mouse small intestine is a phosphate-limited environment. © 2014 John Wiley & Sons Ltd.

Discovery of sex-related genes through high-throughput transcriptome sequencing from the salmon louse Caligus rogercresseyi.

PubMed

Farlora, Rodolfo; Araya-Garay, José; Gallardo-Escárate, Cristian

2014-06-01

Understanding the molecular underpinnings involved in the reproduction of the salmon louse is critical for designing novel strategies of pest management for this ectoparasite. However, genomic information on sex-related genes is still limited. In the present work, sex-specific gene transcription was revealed in the salmon louse Caligus rogercresseyi using high-throughput Illumina sequencing. A total of 30,191,914 and 32,292,250 high quality reads were generated for females and males, and these were de novo assembled into 32,173 and 38,177 contigs, respectively. Gene ontology analysis showed a pattern of higher expression in the female as compared to the male transcriptome. Based on our sequence analysis and known sex-related proteins, several genes putatively involved in sex differentiation, including Dmrt3, FOXL2, VASA, and FEM1, and other potentially significant candidate genes in C. rogercresseyi, were identified for the first time. In addition, the occurrence of SNPs in several differentially expressed contigs annotating for sex-related genes was found. This transcriptome dataset provides a useful resource for future functional analyses, opening new opportunities for sea lice pest control. Copyright © 2014 Elsevier B.V. All rights reserved.

TGMI: an efficient algorithm for identifying pathway regulators through evaluation of triple-gene mutual interaction

PubMed Central

Gunasekara, Chathura; Zhang, Kui; Deng, Wenping; Brown, Laura

2018-01-01

Abstract Despite their important roles, the regulators for most metabolic pathways and biological processes remain elusive. Presently, the methods for identifying metabolic pathway and biological process regulators are intensively sought after. We developed a novel algorithm called triple-gene mutual interaction (TGMI) for identifying these regulators using high-throughput gene expression data. It first calculated the regulatory interactions among triple gene blocks (two pathway genes and one transcription factor (TF)), using conditional mutual information, and then identifies significantly interacted triple genes using a newly identified novel mutual interaction measure (MIM), which was substantiated to reflect strengths of regulatory interactions within each triple gene block. The TGMI calculated the MIM for each triple gene block and then examined its statistical significance using bootstrap. Finally, the frequencies of all TFs present in all significantly interacted triple gene blocks were calculated and ranked. We showed that the TFs with higher frequencies were usually genuine pathway regulators upon evaluating multiple pathways in plants, animals and yeast. Comparison of TGMI with several other algorithms demonstrated its higher accuracy. Therefore, TGMI will be a valuable tool that can help biologists to identify regulators of metabolic pathways and biological processes from the exploded high-throughput gene expression data in public repositories. PMID:29579312

Prediction of epigenetically regulated genes in breast cancer cell lines.

PubMed

Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen; Nautiyal, Shivani; Flaucher, Diane; Carlton, Victoria E H; Moorhead, Martin; Lu, Yontao; Gray, Joe W; Faham, Malek; Spellman, Paul; Parvin, Bahram

2010-06-04

Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profiles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profiles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fixed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically significant negative correlation between methylation profiles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identified 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.

NCBI GEO: archive for functional genomics data sets--10 years on.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Holko, Michelle; Ayanbule, Oluwabukunmi; Yefanov, Andrey; Soboleva, Alexandra

2011-01-01

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20,000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Independent and high-level dual-gene expression in adult stem-progenitor cells from a single lentiviral vector.

PubMed

Tian, J; Andreadis, S T

2009-07-01

Expression of multiple genes from the same target cell is required in several technological and therapeutic applications such as quantitative measurements of promoter activity or in vivo tracking of stem cells. In spite of such need, reaching independent and high-level dual-gene expression cannot be reliably accomplished by current gene transfer vehicles. To address this issue, we designed a lentiviral vector carrying two transcriptional units separated by polyadenylation, terminator and insulator sequences. With this design, the expression level of both genes was as high as that yielded from lentiviral vectors containing only a single transcriptional unit. Similar results were observed with several promoters and cell types including epidermal keratinocytes, bone marrow mesenchymal stem cells and hair follicle stem cells. Notably, we demonstrated quantitative dynamic monitoring of gene expression in primary cells with no need for selection protocols suggesting that this optimized lentivirus may be useful in high-throughput gene expression profiling studies.

A plug-and-play pathway refactoring workflow for natural product research in Escherichia coli and Saccharomyces cerevisiae.

PubMed

Ren, Hengqian; Hu, Pingfan; Zhao, Huimin

2017-08-01

Pathway refactoring serves as an invaluable synthetic biology tool for natural product discovery, characterization, and engineering. However, the complicated and laborious molecular biology techniques largely hinder its application in natural product research, especially in a high-throughput manner. Here we report a plug-and-play pathway refactoring workflow for high-throughput, flexible pathway construction, and expression in both Escherichia coli and Saccharomyces cerevisiae. Biosynthetic genes were firstly cloned into pre-assembled helper plasmids with promoters and terminators, resulting in a series of expression cassettes. These expression cassettes were further assembled using Golden Gate reaction to generate fully refactored pathways. The inclusion of spacer plasmids in this system would not only increase the flexibility for refactoring pathways with different number of genes, but also facilitate gene deletion and replacement. As proof of concept, a total of 96 pathways for combinatorial carotenoid biosynthesis were built successfully. This workflow should be generally applicable to different classes of natural products produced by various organisms. Biotechnol. Bioeng. 2017;114: 1847-1854. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Population transcriptomics with single-cell resolution: a new field made possible by microfluidics: a technology for high throughput transcript counting and data-driven definition of cell types.

PubMed

Plessy, Charles; Desbois, Linda; Fujii, Teruo; Carninci, Piero

2013-02-01

Tissues contain complex populations of cells. Like countries, which are comprised of mixed populations of people, tissues are not homogeneous. Gene expression studies that analyze entire populations of cells from tissues as a mixture are blind to this diversity. Thus, critical information is lost when studying samples rich in specialized but diverse cells such as tumors, iPS colonies, or brain tissue. High throughput methods are needed to address, model and understand the constitutive and stochastic differences between individual cells. Here, we describe microfluidics technologies that utilize a combination of molecular biology and miniaturized labs on chips to study gene expression at the single cell level. We discuss how the characterization of the transcriptome of each cell in a sample will open a new field in gene expression analysis, population transcriptomics, that will change the academic and biomedical analysis of complex samples by defining them as quantified populations of single cells. Copyright © 2013 WILEY Periodicals, Inc.

A high-throughput quantitative expression analysis of cancer-related genes in human HepG2 cells in response to limonene, a potential anticancer agent.

PubMed

Hafidh, Rand R; Hussein, Saba Z; MalAllah, Mohammed Q; Abdulamir, Ahmed S; Abu Bakar, Fatimah

2017-11-14

Citrus bioactive compounds, as active anticancer agent, have been under focus by several studies worldwide. However, the underlying genes responsible for the anticancer potential have not been sufficiently highlighted. The current study investigated the gene expression profile of hepatocellular carcinoma, HepG2, cells after treatment with Limonene. The concentration that killed 50% of HepG2 cells was used to elucidate the genetic mechanisms of limonene anticancer activity. The apoptotic induction was detected by flow cytometry and confocal fluorescence microscope. Two of pro-apoptotic events, caspase-3 activation and phosphatidylserine translocation were manifested by confocal fluorescence microscopy. High-throughput real-time PCR was used to profile 1023 cancer-related genes in 16 different gene families related to the cancer development. In comparison to untreated cells, limonene increased the percentage of apoptotic cells up to 89.61%, by flow cytometry, and 48.2% by fluorescence microscopy. There was a significant limonene-driven differential gene expression of HepG2 cells in 15 different gene families. Limonene was shown to significantly (>2log) up-regulate and down-regulate 14 and 59 genes, respectively. The affected gene families, from most to least affected, were apoptosis induction, signal transduction, cancer genes augmentation, alteration in kinases expression, inflammation, DNA damage repair, and cell cycle proteins. The current study reveals that limonene could be a promising, cheap, and effective anticancer compound. The broad spectrum of limonene anticancer activity is interesting for anticancer drug development. Further research is needed to confirm the current findings and to examine the anticancer potential of limonene along with underlying mechanisms on different cell lines. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

High-Throughput RT-PCR for small-molecule screening assays

PubMed Central

Bittker, Joshua A.

2012-01-01

Quantitative measurement of the levels of mRNA expression using real-time reverse transcription polymerase chain reaction (RT-PCR) has long been used for analyzing expression differences in tissue or cell lines of interest. This method has been used somewhat less frequently to measure the changes in gene expression due to perturbagens such as small molecules or siRNA. The availability of new instrumentation for liquid handling and real-time PCR analysis as well as the commercial availability of start-to-finish kits for RT-PCR has enabled the use of this method for high-throughput small-molecule screening on a scale comparable to traditional high-throughput screening (HTS) assays. This protocol focuses on the special considerations necessary for using quantitative RT-PCR as a primary small-molecule screening assay, including the different methods available for mRNA isolation and analysis. PMID:23487248

GermOnline 4.0 is a genomics gateway for germline development, meiosis and the mitotic cell cycle.

PubMed

Lardenois, Aurélie; Gattiker, Alexandre; Collin, Olivier; Chalmel, Frédéric; Primig, Michael

2010-01-01

GermOnline 4.0 is a cross-species database portal focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. It is thus a source of information for life scientists as well as clinicians who are interested in gene expression and regulatory networks. The GermOnline gateway provides unlimited access to information produced with high-density oligonucleotide microarrays (3'-UTR GeneChips), genome-wide protein-DNA binding assays and protein-protein interaction studies in the context of Ensembl genome annotation. Samples used to produce high-throughput expression data and to carry out genome-wide in vivo DNA binding assays are annotated via the MIAME-compliant Multiomics Information Management and Annotation System (MIMAS 3.0). Furthermore, the Saccharomyces Genomics Viewer (SGV) was developed and integrated into the gateway. SGV is a visualization tool that outputs genome annotation and DNA-strand specific expression data produced with high-density oligonucleotide tiling microarrays (Sc_tlg GeneChips) which cover the complete budding yeast genome on both DNA strands. It facilitates the interpretation of expression levels and transcript structures determined for various cell types cultured under different growth and differentiation conditions. Database URL: www.germonline.org/

GermOnline 4.0 is a genomics gateway for germline development, meiosis and the mitotic cell cycle

PubMed Central

Lardenois, Aurélie; Gattiker, Alexandre; Collin, Olivier; Chalmel, Frédéric; Primig, Michael

2010-01-01

GermOnline 4.0 is a cross-species database portal focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. It is thus a source of information for life scientists as well as clinicians who are interested in gene expression and regulatory networks. The GermOnline gateway provides unlimited access to information produced with high-density oligonucleotide microarrays (3′-UTR GeneChips), genome-wide protein–DNA binding assays and protein–protein interaction studies in the context of Ensembl genome annotation. Samples used to produce high-throughput expression data and to carry out genome-wide in vivo DNA binding assays are annotated via the MIAME-compliant Multiomics Information Management and Annotation System (MIMAS 3.0). Furthermore, the Saccharomyces Genomics Viewer (SGV) was developed and integrated into the gateway. SGV is a visualization tool that outputs genome annotation and DNA-strand specific expression data produced with high-density oligonucleotide tiling microarrays (Sc_tlg GeneChips) which cover the complete budding yeast genome on both DNA strands. It facilitates the interpretation of expression levels and transcript structures determined for various cell types cultured under different growth and differentiation conditions. Database URL: www.germonline.org/ PMID:21149299

Evaluating Between-Pathway Models with Expression Data

PubMed Central

Leiserson, M.D.M.; Cowen, L.J.; Slonim, D.K.

2010-01-01

Abstract Between-pathway models (BPMs) are network motifs consisting of pairs of putative redundant pathways. In this article, we show how adding another source of high-throughput data—microarray gene expression data from knockout experiments—allows us to identify a compensatory functional relationship between genes from the two BPM pathways. We evaluate the quality of the BPMs from four different studies, and we describe how our methods might be extended to refine pathways. PMID:20377458

MicroRNA from Moringa oleifera: Identification by High Throughput Sequencing and Their Potential Contribution to Plant Medicinal Value.

PubMed

Pirrò, Stefano; Zanella, Letizia; Kenzo, Maurice; Montesano, Carla; Minutolo, Antonella; Potestà, Marina; Sobze, Martin Sanou; Canini, Antonella; Cirilli, Marco; Muleo, Rosario; Colizzi, Vittorio; Galgani, Andrea

2016-01-01

Moringa oleifera is a widespread plant with substantial nutritional and medicinal value. We postulated that microRNAs (miRNAs), which are endogenous, noncoding small RNAs regulating gene expression at the post-transcriptional level, might contribute to the medicinal properties of plants of this species after ingestion into human body, regulating human gene expression. However, the knowledge is scarce about miRNA in Moringa. Furthermore, in order to test the hypothesis on the pharmacological potential properties of miRNA, we conducted a high-throughput sequencing analysis using the Illumina platform. A total of 31,290,964 raw reads were produced from a library of small RNA isolated from M. oleifera seeds. We identified 94 conserved and two novel miRNAs that were validated by qRT-PCR assays. Results from qRT-PCR trials conducted on the expression of 20 Moringa miRNA showed that are conserved across multiple plant species as determined by their detection in tissue of other common crop plants. In silico analyses predicted target genes for the conserved miRNA that in turn allowed to relate the miRNAs to the regulation of physiological processes. Some of the predicted plant miRNAs have functional homology to their mammalian counterparts and regulated human genes when they were transfected into cell lines. To our knowledge, this is the first report of discovering M. oleifera miRNAs based on high-throughput sequencing and bioinformatics analysis and we provided new insight into a potential cross-species control of human gene expression. The widespread cultivation and consumption of M. oleifera, for nutritional and medicinal purposes, brings humans into close contact with products and extracts of this plant species. The potential for miRNA transfer should be evaluated as one possible mechanism of action to account for beneficial properties of this valuable species.

A Perspective on the Future of High-Throughput RNAi Screening: Will CRISPR Cut Out the Competition or Can RNAi Help Guide the Way?

PubMed

Taylor, Jessica; Woodcock, Simon

2015-09-01

For more than a decade, RNA interference (RNAi) has brought about an entirely new approach to functional genomics screening. Enabling high-throughput loss-of-function (LOF) screens against the human genome, identifying new drug targets, and significantly advancing experimental biology, RNAi is a fast, flexible technology that is compatible with existing high-throughput systems and processes; however, the recent advent of clustered regularly interspaced palindromic repeats (CRISPR)-Cas, a powerful new precise genome-editing (PGE) technology, has opened up vast possibilities for functional genomics. CRISPR-Cas is novel in its simplicity: one piece of easily engineered guide RNA (gRNA) is used to target a gene sequence, and Cas9 expression is required in the cells. The targeted double-strand break introduced by the gRNA-Cas9 complex is highly effective at removing gene expression compared to RNAi. Together with the reduced cost and complexity of CRISPR-Cas, there is the realistic opportunity to use PGE to screen for phenotypic effects in a total gene knockout background. This review summarizes the exciting development of CRISPR-Cas as a high-throughput screening tool, comparing its future potential to that of well-established RNAi screening techniques, and highlighting future challenges and opportunities within these disciplines. We conclude that the two technologies actually complement rather than compete with each other, enabling greater understanding of the genome in relation to drug discovery. © 2015 Society for Laboratory Automation and Screening.

Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review.

PubMed

Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

2017-09-01

High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

Generation of SNCA Cell Models Using Zinc Finger Nuclease (ZFN) Technology for Efficient High-Throughput Drug Screening.

PubMed

Dansithong, Warunee; Paul, Sharan; Scoles, Daniel R; Pulst, Stefan M; Huynh, Duong P

2015-01-01

Parkinson's disease (PD) is a progressive neurodegenerative disorder caused by loss of dopaminergic neurons of the substantia nigra. The hallmark of PD is the appearance of neuronal protein aggregations known as Lewy bodies and Lewy neurites, of which α-synuclein forms a major component. Familial PD is rare and is associated with missense mutations of the SNCA gene or increases in gene copy number resulting in SNCA overexpression. This suggests that lowering SNCA expression could be therapeutic for PD. Supporting this hypothesis, SNCA reduction was neuroprotective in cell line and rodent PD models. We developed novel cell lines expressing SNCA fused to the reporter genes luciferase (luc) or GFP with the objective to enable high-throughput compound screening (HTS) for small molecules that can lower SNCA expression. Because SNCA expression is likely regulated by far-upstream elements (including the NACP-REP1 located at 8852 bp upstream of the transcription site), we employed zinc finger nuclease (ZFN) genome editing to insert reporter genes in-frame downstream of the SNCA gene in order to retain native SNCA expression control. This ensured full retention of known and unknown up- and downstream genetic elements controlling SNCA expression. Treatment of cells with the histone deacetylase inhibitor valproic acid (VPA) resulted in significantly increased SNCA-luc and SNCA-GFP expression supporting the use of our cell lines for identifying small molecules altering complex modes of expression control. Cells expressing SNCA-luc treated with a luciferase inhibitor or SNCA siRNA resulted in Z'-scores ≥ 0.75, suggesting the suitability of these cell lines for use in HTS. This study presents a novel use of genome editing for the creation of cell lines expressing α-synuclein fusion constructs entirely under native expression control. These cell lines are well suited for HTS for compounds that lower SNCA expression directly or by acting at long-range sites to the SNCA promoter and 5'-UTR.

Concurrent host-pathogen gene expression in the lungs of pigs challenged with Actinobacillus pleuropneumoniae.

PubMed

Brogaard, Louise; Klitgaard, Kirstine; Heegaard, Peter M H; Hansen, Mette Sif; Jensen, Tim Kåre; Skovgaard, Kerstin

2015-05-28

Actinobacillus pleuropneumoniae causes pleuropneumonia in pigs, a disease which is associated with high morbidity and mortality, as well as impaired animal welfare. To obtain in-depth understanding of this infection, the interplay between virulence factors of the pathogen and defense mechanisms of the porcine host needs to be elucidated. However, research has traditionally focused on either bacteriology or immunology; an unbiased picture of the transcriptional responses can be obtained by investigating both organisms in the same biological sample. Host and pathogen responses in pigs experimentally infected with A. pleuropneumoniae were analyzed by high-throughput RT-qPCR. This approach allowed concurrent analysis of selected genes encoding proteins known or hypothesized to be important in the acute phase of this infection. The expression of 17 bacterial and 31 porcine genes was quantified in lung samples obtained within the first 48 hours of infection. This provided novel insight into the early time course of bacterial genes involved in synthesis of pathogen-associated molecular patterns (lipopolysaccharide, peptidoglycan, lipoprotein) and genes involved in pattern recognition (TLR4, CD14, MD2, LBP, MYD88) in response to A. pleuropneumoniae. Significant up-regulation of proinflammatory cytokines such as IL1B, IL6, and IL8 was observed, correlating with protein levels, infection status and histopathological findings. Host genes encoding proteins involved in iron metabolism, as well as bacterial genes encoding exotoxins, proteins involved in adhesion, and iron acquisition were found to be differentially expressed according to disease progression. By applying laser capture microdissection, porcine expression of selected genes could be confirmed in the immediate surroundings of the invading pathogen. Microbial pathogenesis is the product of interactions between host and pathogen. Our results demonstrate the applicability of high-throughput RT-qPCR for the elucidation of dual-organism gene expression analysis during infection. We showed differential expression of 12 bacterial and 24 porcine genes during infection and significant correlation of porcine and bacterial gene expression. This is the first study investigating the concurrent transcriptional response of both bacteria and host at the site of infection during porcine respiratory infection.

Genome-wide characterization of mammalian promoters with distal enhancer functions.

PubMed

Dao, Lan T M; Galindo-Albarrán, Ariel O; Castro-Mondragon, Jaime A; Andrieu-Soler, Charlotte; Medina-Rivera, Alejandra; Souaid, Charbel; Charbonnier, Guillaume; Griffon, Aurélien; Vanhille, Laurent; Stephen, Tharshana; Alomairi, Jaafar; Martin, David; Torres, Magali; Fernandez, Nicolas; Soler, Eric; van Helden, Jacques; Puthier, Denis; Spicuglia, Salvatore

2017-07-01

Gene expression in mammals is precisely regulated by the combination of promoters and gene-distal regulatory regions, known as enhancers. Several studies have suggested that some promoters might have enhancer functions. However, the extent of this type of promoters and whether they actually function to regulate the expression of distal genes have remained elusive. Here, by exploiting a high-throughput enhancer reporter assay, we unravel a set of mammalian promoters displaying enhancer activity. These promoters have distinct genomic and epigenomic features and frequently interact with other gene promoters. Extensive CRISPR-Cas9 genomic manipulation demonstrated the involvement of these promoters in the cis regulation of expression of distal genes in their natural loci. Our results have important implications for the understanding of complex gene regulation in normal development and disease.

GEOGLE: context mining tool for the correlation between gene expression and the phenotypic distinction.

PubMed

Yu, Yao; Tu, Kang; Zheng, Siyuan; Li, Yun; Ding, Guohui; Ping, Jie; Hao, Pei; Li, Yixue

2009-08-25

In the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches. In our work, we integrated gene expression information from Gene Expression Omnibus (GEO), biomedical ontology from Medical Subject Headings (MeSH) and signaling pathway knowledge from sigPathway entries to develop a context mining tool for gene expression analysis - GEOGLE. GEOGLE offers a rapid and convenient way for searching relevant experimental datasets, pathways and biological terms according to multiple types of queries: including biomedical vocabularies, GDS IDs, gene IDs, pathway names and signature list. Moreover, GEOGLE summarizes the signature genes from a subset of GDSes and estimates the correlation between gene expression and the phenotypic distinction with an integrated p value. This approach performing global searching of expression data may expand the traditional way of collecting heterogeneous gene expression experiment data. GEOGLE is a novel tool that provides researchers a quantitative way to understand the correlation between gene expression and phenotypic distinction through meta-analysis of gene expression datasets from different experiments, as well as the biological meaning behind. The web site and user guide of GEOGLE are available at: http://omics.biosino.org:14000/kweb/workflow.jsp?id=00020.

Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data

PubMed Central

Liu, Zhi-Ping

2015-01-01

Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented. PMID:25937810

From Saccharomyces cerevisiae to human: The important gene co-expression modules.

PubMed

Liu, Wei; Li, Li; Ye, Hua; Chen, Haiwei; Shen, Weibiao; Zhong, Yuexian; Tian, Tian; He, Huaqin

2017-08-01

Network-based systems biology has become an important method for analyzing high-throughput gene expression data and gene function mining. Yeast has long been a popular model organism for biomedical research. In the current study, a weighted gene co-expression network analysis algorithm was applied to construct a gene co-expression network in Saccharomyces cerevisiae . Seventeen stable gene co-expression modules were detected from 2,814 S. cerevisiae microarray data. Further characterization of these modules with the Database for Annotation, Visualization and Integrated Discovery tool indicated that these modules were associated with certain biological processes, such as heat response, cell cycle, translational regulation, mitochondrion oxidative phosphorylation, amino acid metabolism and autophagy. Hub genes were also screened by intra-modular connectivity. Finally, the module conservation was evaluated in a human disease microarray dataset. Functional modules were identified in budding yeast, some of which are associated with patient survival. The current study provided a paradigm for single cell microorganisms and potentially other organisms.

Validation of high-throughput single cell analysis methodology.

PubMed

Devonshire, Alison S; Baradez, Marc-Olivier; Morley, Gary; Marshall, Damian; Foy, Carole A

2014-05-01

High-throughput quantitative polymerase chain reaction (qPCR) approaches enable profiling of multiple genes in single cells, bringing new insights to complex biological processes and offering opportunities for single cell-based monitoring of cancer cells and stem cell-based therapies. However, workflows with well-defined sources of variation are required for clinical diagnostics and testing of tissue-engineered products. In a study of neural stem cell lines, we investigated the performance of lysis, reverse transcription (RT), preamplification (PA), and nanofluidic qPCR steps at the single cell level in terms of efficiency, precision, and limit of detection. We compared protocols using a separate lysis buffer with cell capture directly in RT-PA reagent. The two methods were found to have similar lysis efficiencies, whereas the direct RT-PA approach showed improved precision. Digital PCR was used to relate preamplified template copy numbers to Cq values and reveal where low-quality signals may affect the analysis. We investigated the impact of calibration and data normalization strategies as a means of minimizing the impact of inter-experimental variation on gene expression values and found that both approaches can improve data comparability. This study provides validation and guidance for the application of high-throughput qPCR workflows for gene expression profiling of single cells. Copyright © 2014 Elsevier Inc. All rights reserved.

Analytical workflow profiling gene expression in murine macrophages

PubMed Central

Nixon, Scott E.; González-Peña, Dianelys; Lawson, Marcus A.; McCusker, Robert H.; Hernandez, Alvaro G.; O’Connor, Jason C.; Dantzer, Robert; Kelley, Keith W.

2015-01-01

Comprehensive and simultaneous analysis of all genes in a biological sample is a capability of RNA-Seq technology. Analysis of the entire transcriptome benefits from summarization of genes at the functional level. As a cellular response of interest not previously explored with RNA-Seq, peritoneal macrophages from mice under two conditions (control and immunologically challenged) were analyzed for gene expression differences. Quantification of individual transcripts modeled RNA-Seq read distribution and uncertainty (using a Beta Negative Binomial distribution), then tested for differential transcript expression (False Discovery Rate-adjusted p-value < 0.05). Enrichment of functional categories utilized the list of differentially expressed genes. A total of 2079 differentially expressed transcripts representing 1884 genes were detected. Enrichment of 92 categories from Gene Ontology Biological Processes and Molecular Functions, and KEGG pathways were grouped into 6 clusters. Clusters included defense and inflammatory response (Enrichment Score = 11.24) and ribosomal activity (Enrichment Score = 17.89). Our work provides a context to the fine detail of individual gene expression differences in murine peritoneal macrophages during immunological challenge with high throughput RNA-Seq. PMID:25708305

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.

Identifying potential maternal genes of Bombyx mori using digital gene expression profiling

PubMed Central

Xu, Pingzhen

2018-01-01

Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

Pathway analyses and understanding disease associations

PubMed Central

Liu, Yu; Chance, Mark R

2013-01-01

High throughput technologies have been applied to investigate the underlying mechanisms of complex diseases, identify disease-associations and help to improve treatment. However it is challenging to derive biological insight from conventional single gene based analysis of “omics” data from high throughput experiments due to sample and patient heterogeneity. To address these challenges, many novel pathway and network based approaches were developed to integrate various “omics” data, such as gene expression, copy number alteration, Genome Wide Association Studies, and interaction data. This review will cover recent methodological developments in pathway analysis for the detection of dysregulated interactions and disease-associated subnetworks, prioritization of candidate disease genes, and disease classifications. For each application, we will also discuss the associated challenges and potential future directions. PMID:24319650

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

Genome-scale deletion screening of human long non-coding RNAs using a paired-guide RNA CRISPR library

PubMed Central

Zhu, Shiyou; Li, Wei; Liu, Jingze; Chen, Chen-Hao; Liao, Qi; Xu, Ping; Xu, Han; Xiao, Tengfei; Cao, Zhongzheng; Peng, Jingyu; Yuan, Pengfei; Brown, Myles; Liu, Xiaole Shirley; Wei, Wensheng

2017-01-01

CRISPR/Cas9 screens have been widely adopted to analyse coding gene functions, but high throughput screening of non-coding elements using this method is more challenging, because indels caused by a single cut in non-coding regions are unlikely to produce a functional knockout. A high-throughput method to produce deletions of non-coding DNA is needed. Herein, we report a high throughput genomic deletion strategy to screen for functional long non-coding RNAs (lncRNAs) that is based on a lentiviral paired-guide RNA (pgRNA) library. Applying our screening method, we identified 51 lncRNAs that can positively or negatively regulate human cancer cell growth. We individually validated 9 lncRNAs using CRISPR/Cas9-mediated genomic deletion and functional rescue, CRISPR activation or inhibition, and gene expression profiling. Our high-throughput pgRNA genome deletion method should enable rapid identification of functional mammalian non-coding elements. PMID:27798563

Domain selection combined with improved cloning strategy for high throughput expression of higher eukaryotic proteins

PubMed Central

Chen, Yunjia; Qiu, Shihong; Luan, Chi-Hao; Luo, Ming

2007-01-01

Background Expression of higher eukaryotic genes as soluble, stable recombinant proteins is still a bottleneck step in biochemical and structural studies of novel proteins today. Correct identification of stable domains/fragments within the open reading frame (ORF), combined with proper cloning strategies, can greatly enhance the success rate when higher eukaryotic proteins are expressed as these domains/fragments. Furthermore, a HTP cloning pipeline incorporated with bioinformatics domain/fragment selection methods will be beneficial to studies of structure and function genomics/proteomics. Results With bioinformatics tools, we developed a domain/domain boundary prediction (DDBP) method, which was trained by available experimental data. Combined with an improved cloning strategy, DDBP had been applied to 57 proteins from C. elegans. Expression and purification results showed there was a 10-fold increase in terms of obtaining purified proteins. Based on the DDBP method, the improved GATEWAY cloning strategy and a robotic platform, we constructed a high throughput (HTP) cloning pipeline, including PCR primer design, PCR, BP reaction, transformation, plating, colony picking and entry clones extraction, which have been successfully applied to 90 C. elegans genes, 88 Brucella genes, and 188 human genes. More than 97% of the targeted genes were obtained as entry clones. This pipeline has a modular design and can adopt different operations for a variety of cloning/expression strategies. Conclusion The DDBP method and improved cloning strategy were satisfactory. The cloning pipeline, combined with our recombinant protein HTP expression pipeline and the crystal screening robots, constitutes a complete platform for structure genomics/proteomics. This platform will increase the success rate of purification and crystallization dramatically and promote the further advancement of structure genomics/proteomics. PMID:17663785

Effects of TCDD on the Expression of Nuclear Encoded Mitochondrial Genes

PubMed Central

Forgacs, Agnes L.; Burgoon, Lyle D.; Lynn, Scott G.; LaPres, John J.; Zacharewski, Timothy

2014-01-01

Generation of mitochondrial reactive oxygen species (ROS) can be perturbed following exposure to environmental chemicals such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Reports indicate that the aryl hydrocarbon receptor (AhR) mediates TCDD-induced sustained hepatic oxidative stress by decreasing hepatic ATP levels and through hyperpolarization of the inner mitochondrial membrane. To further elucidate the effects of TCDD on the mitochondria, high-throughput quantitative real-time PCR (HTP-QRTPCR) was used to evaluate the expression of 90 genes encoding mitochondrial proteins involved in electron transport, oxidative phosphorylation, uncoupling, and associated chaperones. HTP-QRTPCR analysis of time course (30 μg/kg TCDD at 2, 4, 8, 12, 18, 24, 72, and 168 hrs) liver samples obtained from orally gavaged immature, ovariectomized C57BL/6 mice identified 54 differentially expressed genes (|fold change|>1.5 and P-value <0.1). Of these, 8 exhibited a dose response (0.03 to 300 μg/kg TCDD) at 4, 24 or 72 hrs. Dose responsive genes encoded proteins associated with electron transport chain (ETC) complex I (NADH dehydrogenase), III (cytochrome c reductase), IV (cytochrome c oxidase), and V (ATP synthase) and could be generally categorized as having proton gradient, ATP synthesis, and chaperone activities. In contrast, transcript levels of ETC complex II, succinate dehydrogenase, remained unchanged. Putative dioxin response elements were computationally found in the promoter regions of the 8 dose-responsive genes. This high-throughput approach suggests that TCDD alters the expression of genes associated with mitochondrial function which may contribute to TCDD-elicited mitochondrial toxicity. PMID:20399798

Sort-Seq Approach to Engineering a Formaldehyde-Inducible Promoter for Dynamically Regulated Escherichia coli Growth on Methanol

PubMed Central

2017-01-01

Tight and tunable control of gene expression is a highly desirable goal in synthetic biology for constructing predictable gene circuits and achieving preferred phenotypes. Elucidating the sequence–function relationship of promoters is crucial for manipulating gene expression at the transcriptional level, particularly for inducible systems dependent on transcriptional regulators. Sort-seq methods employing fluorescence-activated cell sorting (FACS) and high-throughput sequencing allow for the quantitative analysis of sequence–function relationships in a robust and rapid way. Here we utilized a massively parallel sort-seq approach to analyze the formaldehyde-inducible Escherichia coli promoter (Pfrm) with single-nucleotide resolution. A library of mutated formaldehyde-inducible promoters was cloned upstream of gfp on a plasmid. The library was partitioned into bins via FACS on the basis of green fluorescent protein (GFP) expression level, and mutated promoters falling into each expression bin were identified with high-throughput sequencing. The resulting analysis identified two 19 base pair repressor binding sites, one upstream of the −35 RNA polymerase (RNAP) binding site and one overlapping with the −10 site, and assessed the relative importance of each position and base therein. Key mutations were identified for tuning expression levels and were used to engineer formaldehyde-inducible promoters with predictable activities. Engineered variants demonstrated up to 14-fold lower basal expression, 13-fold higher induced expression, and a 3.6-fold stronger response as indicated by relative dynamic range. Finally, an engineered formaldehyde-inducible promoter was employed to drive the expression of heterologous methanol assimilation genes and achieved increased biomass levels on methanol, a non-native substrate of E. coli. PMID:28463494

NCBI GEO: archive for functional genomics data sets—10 years on

PubMed Central

Barrett, Tanya; Troup, Dennis B.; Wilhite, Stephen E.; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F.; Tomashevsky, Maxim; Marshall, Kimberly A.; Phillippy, Katherine H.; Sherman, Patti M.; Muertter, Rolf N.; Holko, Michelle; Ayanbule, Oluwabukunmi; Yefanov, Andrey; Soboleva, Alexandra

2011-01-01

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20 000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/. PMID:21097893

Prediction of epigenetically regulated genes in breast cancer cell lines

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

Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen

Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines,more » which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fxed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically signifcant negative correlation between methylation profles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identifed 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.« less

Characterization of transformation related genes in oral cancer cells.

PubMed

Chang, D D; Park, N H; Denny, C T; Nelson, S F; Pe, M

1998-04-16

A cDNA representational difference analysis (cDNA-RDA) and an arrayed filter technique were used to characterize transformation-related genes in oral cancer. From an initial comparison of normal oral epithelial cells and a human papilloma virus (HPV)-immortalized oral epithelial cell line, we obtained 384 differentially expressed gene fragments and arrayed them on a filter. Two hundred and twelve redundant clones were identified by three rounds of back hybridization. Sequence analysis of the remaining clones revealed 99 unique clones corresponding to 69 genes. The expression of these transformation related gene fragments in three nontumorigenic HPV-immortalized oral epithelial cell lines and three oral cancer cell lines were simultaneously monitored using a cDNA array hybridization. Although there was a considerable cell line-to-cell line variability in the expression of these clones, a reliable prediction of their expression could be made from the cDNA array hybridization. Our study demonstrates the utility of combining cDNA-RDA and arrayed filters in high-throughput gene expression difference analysis. The differentially expressed genes identified in this study should be informative in studying oral epithelial cell carcinogenesis.

Technical variables in high-throughput miRNA expression profiling: much work remains to be done.

PubMed

Nelson, Peter T; Wang, Wang-Xia; Wilfred, Bernard R; Tang, Guiliang

2008-11-01

MicroRNA (miRNA) gene expression profiling has provided important insights into plant and animal biology. However, there has not been ample published work about pitfalls associated with technical parameters in miRNA gene expression profiling. One source of pertinent information about technical variables in gene expression profiling is the separate and more well-established literature regarding mRNA expression profiling. However, many aspects of miRNA biochemistry are unique. For example, the cellular processing and compartmentation of miRNAs, the differential stability of specific miRNAs, and aspects of global miRNA expression regulation require specific consideration. Additional possible sources of systematic bias in miRNA expression studies include the differential impact of pre-analytical variables, substrate specificity of nucleic acid processing enzymes used in labeling and amplification, and issues regarding new miRNA discovery and annotation. We conclude that greater focus on technical parameters is required to bolster the validity, reliability, and cultural credibility of miRNA gene expression profiling studies.

ImpulseDE: detection of differentially expressed genes in time series data using impulse models.

PubMed

Sander, Jil; Schultze, Joachim L; Yosef, Nir

2017-03-01

Perturbations in the environment lead to distinctive gene expression changes within a cell. Observed over time, those variations can be characterized by single impulse-like progression patterns. ImpulseDE is an R package suited to capture these patterns in high throughput time series datasets. By fitting a representative impulse model to each gene, it reports differentially expressed genes across time points from a single or between two time courses from two experiments. To optimize running time, the code uses clustering and multi-threading. By applying ImpulseDE , we demonstrate its power to represent underlying biology of gene expression in microarray and RNA-Seq data. ImpulseDE is available on Bioconductor ( https://bioconductor.org/packages/ImpulseDE/ ). niryosef@berkeley.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Rose Scent

PubMed Central

Guterman, Inna; Shalit, Moshe; Menda, Naama; Piestun, Dan; Dafny-Yelin, Mery; Shalev, Gil; Bar, Einat; Davydov, Olga; Ovadis, Mariana; Emanuel, Michal; Wang, Jihong; Adam, Zach; Pichersky, Eran; Lewinsohn, Efraim; Zamir, Dani; Vainstein, Alexander; Weiss, David

2002-01-01

For centuries, rose has been the most important crop in the floriculture industry; its economic importance also lies in the use of its petals as a source of natural fragrances. Here, we used genomics approaches to identify novel scent-related genes, using rose flowers from tetraploid scented and nonscented cultivars. An annotated petal EST database of ∼2100 unique genes from both cultivars was created, and DNA chips were prepared and used for expression analyses of selected clones. Detailed chemical analysis of volatile composition in the two cultivars, together with the identification of secondary metabolism–related genes whose expression coincides with scent production, led to the discovery of several novel flower scent–related candidate genes. The function of some of these genes, including a germacrene D synthase, was biochemically determined using an Escherichia coli expression system. This work demonstrates the advantages of using the high-throughput approaches of genomics to detail traits of interest expressed in a cultivar-specific manner in nonmodel plants. PMID:12368489

Identifying and engineering promoters for high level and sustainable therapeutic recombinant protein production in cultured mammalian cells.

PubMed

Ho, Steven C L; Yang, Yuansheng

2014-08-01

Promoters are essential on plasmid vectors to initiate transcription of the transgenes when generating therapeutic recombinant proteins expressing mammalian cell lines. High and sustained levels of gene expression are desired during therapeutic protein production while gene expression is useful for cell engineering. As many finely controlled promoters exhibit cell and product specificity, new promoters need to be identified, optimized and carefully evaluated before use. Suitable promoters can be identified using techniques ranging from simple molecular biology methods to modern high-throughput omics screenings. Promoter engineering is often required after identification to either obtain high and sustained expression or to provide a wider range of gene expression. This review discusses some of the available methods to identify and engineer promoters for therapeutic recombinant protein expression in mammalian cells.

Understanding regulation of microRNAs on intestine regeneration in the sea cucumber Apostichopus japonicus using high-throughput sequencing.

PubMed

Sun, Lina; Sun, Jingchun; Li, Xiaoni; Zhang, Libin; Yang, Hongsheng; Wang, Qing

2017-06-01

The sea cucumber, as a member of the Echinodermata, has the capacity to restore damaged organs and body parts, which has always been a key scientific issue. MicroRNAs (miRNAs), a class of short noncoding RNAs, play important roles in regulating gene expression. In the present study, we applied high-throughput sequencing to investigate alterations of miRNA expression in regenerative intestine compared to normal intestine. A total of 73 differentially expressed miRNAs were obtained, including 59 up-regulated miRNAs and 14 down-regulated miRNAs. Among these molecules, Aja-miR-1715-5p, Aja-miR-153, Aja-miR-252a, Aja-miR-153-5p, Aja-miR-252b, Aja-miR-2001, Aja-miR-64d-3p, and Aja-miR-252-5p were differentially expressed over 10-fold at 3days post-evisceration (dpe). Notably, real-time PCR revealed that Aja-miR-1715-5p was up-regulated 1390-fold at 3dpe. Moreover, putative target gene co-expression analyses, gene ontology, and pathway analyses suggest that these miRNAs play important roles in specific cellular events (cell proliferation, migration, and apoptosis), metabolic regulation, and energy redistribution. These results will provide a basis for future studies of miRNA regulation in sea cucumber regeneration. Copyright © 2017 Elsevier Inc. All rights reserved.

Gene Expression Analysis of Copper Tolerance and Wood Decay in the Brown Rot Fungus Fibroporia radiculosa

Treesearch

J. D. Tang; L. A. Parker; A. D. Perkins; T. S. Sonstegard; S. G. Schroeder; D. D. Nicholas; S. V. Diehl

2013-01-01

High-throughput transcriptomics was used to identify Fibroporia radiculosa genes that were differentially regulated during colonization of wood treated with a copper-based preservative. The transcriptome was profiled at two time points while the fungus was growing on wood treated with micronized copper quat (MCQ). A total of 917 transcripts were...

Identification of differentially expressed lncRNAs involved in transient regeneration of the neonatal C57BL/6J mouse heart by next-generation high-throughput RNA sequencing.

PubMed

Chen, Yu-Mei; Li, Hua; Fan, Yi; Zhang, Qi-Jun; Li, Xing; Wu, Li-Jie; Chen, Zi-Jie; Zhu, Chun; Qian, Ling-Mei

2017-04-25

Previous studies have shown that mammalian cardiac tissue has a regenerative capacity. Remarkably, neonatal mice can regenerate their cardiac tissue for up to 6 days after birth, but this capacity is lost by day 7. In this study, we aimed to explore the expression pattern of long noncoding RNA (lncRNA) during this period and examine the mechanisms underlying this process. We found that 685 lncRNAs and 1833 mRNAs were differentially expressed at P1 and P7 by the next-generation high-throughput RNA sequencing. The coding genes associated with differentially expressed lncRNAs were mainly involved in metabolic processes and cell proliferation, and also were potentially associated with several key regeneration signalling pathways, including PI3K-Akt, MAPK, Hippo and Wnt. In addition, we identified some correlated targets of highly-dysregulated lncRNAs such as Igfbp3, Trnp1, Itgb6, and Pim3 by the coding-noncoding gene co-expression network. These data may offer a reference resource for further investigation about the mechanisms by which lncRNAs regulate cardiac regeneration.

A Triple-Fluorophore-Labeled Nucleic Acid pH Nanosensor to Investigate Non-viral Gene Delivery.

PubMed

Wilson, David R; Routkevitch, Denis; Rui, Yuan; Mosenia, Arman; Wahlin, Karl J; Quinones-Hinojosa, Alfredo; Zack, Donald J; Green, Jordan J

2017-07-05

There is a need for new tools to better quantify intracellular delivery barriers in high-throughput and high-content ways. Here, we synthesized a triple-fluorophore-labeled nucleic acid pH nanosensor for measuring intracellular pH of exogenous DNA at specific time points in a high-throughput manner by flow cytometry following non-viral transfection. By including two pH-sensitive fluorophores and one pH-insensitive fluorophore in the nanosensor, detection of pH was possible over the full physiological range. We further assessed possible correlation between intracellular pH of delivered DNA, cellular uptake of DNA, and DNA reporter gene expression at 24 hr post-transfection for poly-L-lysine and branched polyethylenimine polyplex nanoparticles. While successful transfection was shown to clearly depend on median cellular pH of delivered DNA at the cell population level, surprisingly, on an individual cell basis, there was no significant correlation between intracellular pH and transfection efficacy. To our knowledge, this is the first reported instance of high-throughput single-cell analysis between cellular uptake of DNA, intracellular pH of delivered DNA, and gene expression of the delivered DNA. Using the nanosensor, we demonstrate that the ability of polymeric nanoparticles to avoid an acidic environment is necessary, but not sufficient, for successful transfection. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

MethylMix 2.0: an R package for identifying DNA methylation genes. | Office of Cancer Genomics

Cancer.gov

DNA methylation is an important mechanism regulating gene transcription, and its role in carcinogenesis has been extensively studied. Hyper and hypomethylation of genes is a major mechanism of gene expression deregulation in a wide range of diseases. At the same time, high-throughput DNA methylation assays have been developed generating vast amounts of genome wide DNA methylation measurements. We developed MethylMix, an algorithm implemented in R to identify disease specific hyper and hypomethylated genes.

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.

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/.

OptSSeq: High-throughput sequencing readout of growth enrichment defines optimal gene expression elements for homoethanologenesis

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

Ghosh, Indro Neil; Landick, Robert

The optimization of synthetic pathways is a central challenge in metabolic engineering. OptSSeq (Optimization by Selection and Sequencing) is one approach to this challenge. OptSSeq couples selection of optimal enzyme expression levels linked to cell growth rate with high-throughput sequencing to track enrichment of gene expression elements (promoters and ribosomebinding sites) from a combinatorial library. OptSSeq yields information on both optimal and suboptimal enzyme levels, and helps identify constraints that limit maximal product formation. Here we report a proof-of-concept implementation of OptSSeq using homoethanologenesis, a two-step pathway consisting of pyruvate decarboxylase (Pdc) and alcohol dehydrogenase (Adh) that converts pyruvate tomore » ethanol and is naturally optimized in the bacterium Zymomonas mobilis. We used OptSSeq to determine optimal gene expression elements and enzyme levels for Z. mobilis Pdc, AdhA, and AdhB expressed in Escherichia coli. By varying both expression signals and gene order, we identified an optimal solution using only Pdc and AdhB. We resolved current uncertainty about the functions of the Fe 2+-dependent AdhB and Zn 2+- dependent AdhA by showing that AdhB is preferred over AdhA for rapid growth in both E. coli and Z. mobilis. Finally, by comparing predictions of growth-linked metabolic flux to enzyme synthesis costs, we established that optimal E. coli homoethanologenesis was achieved by our best pdc-adhB expression cassette and that the remaining constraints lie in the E. coli metabolic network or inefficient Pdc or AdhB function in E. coli. Furthermore, OptSSeq is a general tool for synthetic biology to tune enzyme levels in any pathway whose optimal function can be linked to cell growth or survival.« less

OptSSeq: High-throughput sequencing readout of growth enrichment defines optimal gene expression elements for homoethanologenesis

DOE PAGES

Ghosh, Indro Neil; Landick, Robert

2016-07-16

The optimization of synthetic pathways is a central challenge in metabolic engineering. OptSSeq (Optimization by Selection and Sequencing) is one approach to this challenge. OptSSeq couples selection of optimal enzyme expression levels linked to cell growth rate with high-throughput sequencing to track enrichment of gene expression elements (promoters and ribosomebinding sites) from a combinatorial library. OptSSeq yields information on both optimal and suboptimal enzyme levels, and helps identify constraints that limit maximal product formation. Here we report a proof-of-concept implementation of OptSSeq using homoethanologenesis, a two-step pathway consisting of pyruvate decarboxylase (Pdc) and alcohol dehydrogenase (Adh) that converts pyruvate tomore » ethanol and is naturally optimized in the bacterium Zymomonas mobilis. We used OptSSeq to determine optimal gene expression elements and enzyme levels for Z. mobilis Pdc, AdhA, and AdhB expressed in Escherichia coli. By varying both expression signals and gene order, we identified an optimal solution using only Pdc and AdhB. We resolved current uncertainty about the functions of the Fe 2+-dependent AdhB and Zn 2+- dependent AdhA by showing that AdhB is preferred over AdhA for rapid growth in both E. coli and Z. mobilis. Finally, by comparing predictions of growth-linked metabolic flux to enzyme synthesis costs, we established that optimal E. coli homoethanologenesis was achieved by our best pdc-adhB expression cassette and that the remaining constraints lie in the E. coli metabolic network or inefficient Pdc or AdhB function in E. coli. Furthermore, OptSSeq is a general tool for synthetic biology to tune enzyme levels in any pathway whose optimal function can be linked to cell growth or survival.« less

From genes to protein mechanics on a chip.

PubMed

Otten, Marcus; Ott, Wolfgang; Jobst, Markus A; Milles, Lukas F; Verdorfer, Tobias; Pippig, Diana A; Nash, Michael A; Gaub, Hermann E

2014-11-01

Single-molecule force spectroscopy enables mechanical testing of individual proteins, but low experimental throughput limits the ability to screen constructs in parallel. We describe a microfluidic platform for on-chip expression, covalent surface attachment and measurement of single-molecule protein mechanical properties. A dockerin tag on each protein molecule allowed us to perform thousands of pulling cycles using a single cohesin-modified cantilever. The ability to synthesize and mechanically probe protein libraries enables high-throughput mechanical phenotyping.

Identification of Reference Genes for RT-qPCR Data Normalization in Cannabis sativa Stem Tissues.

PubMed

Mangeot-Peter, Lauralie; Legay, Sylvain; Hausman, Jean-Francois; Esposito, Sergio; Guerriero, Gea

2016-09-15

Gene expression profiling via quantitative real-time PCR is a robust technique widely used in the life sciences to compare gene expression patterns in, e.g., different tissues, growth conditions, or after specific treatments. In the field of plant science, real-time PCR is the gold standard to study the dynamics of gene expression and is used to validate the results generated with high throughput techniques, e.g., RNA-Seq. An accurate relative quantification of gene expression relies on the identification of appropriate reference genes, that need to be determined for each experimental set-up used and plant tissue studied. Here, we identify suitable reference genes for expression profiling in stems of textile hemp (Cannabis sativa L.), whose tissues (isolated bast fibres and core) are characterized by remarkable differences in cell wall composition. We additionally validate the reference genes by analysing the expression of putative candidates involved in the non-oxidative phase of the pentose phosphate pathway and in the first step of the shikimate pathway. The goal is to describe the possible regulation pattern of some genes involved in the provision of the precursors needed for lignin biosynthesis in the different hemp stem tissues. The results here shown are useful to design future studies focused on gene expression analyses in hemp.

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

Identification of differentially expressed genes in cucumber (Cucumis sativus L.) root under waterlogging stress by digital gene expression profile.

PubMed

Qi, Xiao-Hua; Xu, Xue-Wen; Lin, Xiao-Jian; Zhang, Wen-Jie; Chen, Xue-Hao

2012-03-01

High-throughput tag-sequencing (Tag-seq) analysis based on the Solexa Genome Analyzer platform was applied to analyze the gene expression profiling of cucumber plant at 5 time points over a 24h period of waterlogging treatment. Approximately 5.8 million total clean sequence tags per library were obtained with 143013 distinct clean tag sequences. Approximately 23.69%-29.61% of the distinct clean tags were mapped unambiguously to the unigene database, and 53.78%-60.66% of the distinct clean tags were mapped to the cucumber genome database. Analysis of the differentially expressed genes revealed that most of the genes were down-regulated in the waterlogging stages, and the differentially expressed genes mainly linked to carbon metabolism, photosynthesis, reactive oxygen species generation/scavenging, and hormone synthesis/signaling. Finally, quantitative real-time polymerase chain reaction using nine genes independently verified the tag-mapped results. This present study reveals the comprehensive mechanisms of waterlogging-responsive transcription in cucumber. Copyright © 2011 Elsevier Inc. All rights reserved.

A versatile toolkit for high throughput functional genomics with Trichoderma reesei

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

Schuster, Andre; Bruno, Kenneth S.; Collett, James R.

2012-01-02

The ascomycete fungus, Trichoderma reesei (anamorph of Hypocrea jecorina), represents a biotechnological workhorse and is currently one of the most proficient cellulase producers. While strain improvement was traditionally accomplished by random mutagenesis, a detailed understanding of cellulase regulation can only be gained using recombinant technologies. RESULTS: Aiming at high efficiency and high throughput methods, we present here a construction kit for gene knock out in T. reesei. We provide a primer database for gene deletion using the pyr4, amdS and hph selection markers. For high throughput generation of gene knock outs, we constructed vectors using yeast mediated recombination and thenmore » transformed a T. reesei strain deficient in non-homologous end joining (NHEJ) by spore electroporation. This NHEJ-defect was subsequently removed by crossing of mutants with a sexually competent strain derived from the parental strain, QM9414.CONCLUSIONS:Using this strategy and the materials provided, high throughput gene deletion in T. reesei becomes feasible. Moreover, with the application of sexual development, the NHEJ-defect can be removed efficiently and without the need for additional selection markers. The same advantages apply for the construction of multiple mutants by crossing of strains with different gene deletions, which is now possible with considerably less hands-on time and minimal screening effort compared to a transformation approach. Consequently this toolkit can considerably boost research towards efficient exploitation of the resources of T. reesei for cellulase expression and hence second generation biofuel production.« less

Natural products that reduce rotavirus infectivity identified by a cell-based moderate-throughput screening assay.

PubMed

Shaneyfelt, Mark E; Burke, Anna D; Graff, Joel W; Jutila, Mark A; Hardy, Michele E

2006-09-01

There is widespread interest in the use of innate immune modulators as a defense strategy against infectious pathogens. Using rotavirus as a model system, we developed a cell-based, moderate-throughput screening (MTS) assay to identify compounds that reduce rotavirus infectivity in vitro, toward a long-term goal of discovering immunomodulatory agents that enhance innate responses to viral infection. A natural product library consisting of 280 compounds was screened in the assay and 15 compounds that significantly reduced infectivity without cytotoxicity were identified. Time course analysis of four compounds with previously characterized effects on inflammatory gene expression inhibited replication with pre-treatment times as minimal as 2 hours. Two of these four compounds, alpha-mangostin and 18-beta-glycyrrhetinic acid, activated NFkappaB and induced IL-8 secretion. The assay is adaptable to other virus systems, and amenable to full automation and adaptation to a high-throughput format. Identification of several compounds with known effects on inflammatory and antiviral gene expression that confer resistance to rotavirus infection in vitro suggests the assay is an appropriate platform for discovery of compounds with potential to amplify innate antiviral responses.

Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data.

PubMed

Ryall, Karen A; Shin, Jimin; Yoo, Minjae; Hinz, Trista K; Kim, Jihye; Kang, Jaewoo; Heasley, Lynn E; Tan, Aik Choon

2015-12-01

Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make results difficult to interpret. We developed Kinase Addiction Ranker (KAR), an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells. We applied KAR to predict kinase dependency of 21 lung cancer cell lines and 151 leukemia patient samples using published datasets. We experimentally validated KAR predictions of FGFR and MTOR dependence in lung cancer cell line H1581, showing synergistic reduction in proliferation after combining ponatinib and AZD8055. KAR can be downloaded as a Python function or a MATLAB script along with example inputs and outputs at: http://tanlab.ucdenver.edu/KAR/. aikchoon.tan@ucdenver.edu. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

High-throughput screening of a CRISPR/Cas9 library for functional genomics in human cells.

PubMed

Zhou, Yuexin; Zhu, Shiyou; Cai, Changzu; Yuan, Pengfei; Li, Chunmei; Huang, Yanyi; Wei, Wensheng

2014-05-22

Targeted genome editing technologies are powerful tools for studying biology and disease, and have a broad range of research applications. In contrast to the rapid development of toolkits to manipulate individual genes, large-scale screening methods based on the complete loss of gene expression are only now beginning to be developed. Here we report the development of a focused CRISPR/Cas-based (clustered regularly interspaced short palindromic repeats/CRISPR-associated) lentiviral library in human cells and a method of gene identification based on functional screening and high-throughput sequencing analysis. Using knockout library screens, we successfully identified the host genes essential for the intoxication of cells by anthrax and diphtheria toxins, which were confirmed by functional validation. The broad application of this powerful genetic screening strategy will not only facilitate the rapid identification of genes important for bacterial toxicity but will also enable the discovery of genes that participate in other biological processes.

High-Throughput Sequencing of microRNAs in Glucocorticoid Sensitive Paediatric Inflammatory Bowel Disease Patients.

PubMed

De Iudicibus, Sara; Lucafò, Marianna; Vitulo, Nicola; Martelossi, Stefano; Zimbello, Rosanna; De Pascale, Fabio; Forcato, Claudio; Naviglio, Samuele; Di Silvestre, Alessia; Gerdol, Marco; Stocco, Gabriele; Valle, Giorgio; Ventura, Alessandro; Bramuzzo, Matteo; Decorti, Giuliana

2018-05-08

The aim of this research was the identification of novel pharmacogenomic biomarkers for better understanding the complex gene regulation mechanisms underpinning glucocorticoid (GC) action in paediatric inflammatory bowel disease (IBD). This goal was achieved by evaluating high-throughput microRNA (miRNA) profiles during GC treatment, integrated with the assessment of expression changes in GC receptor (GR) heterocomplex genes. Furthermore, we tested the hypothesis that differentially expressed miRNAs could be directly regulated by GCs through investigating the presence of GC responsive elements (GREs) in their gene promoters. Ten IBD paediatric patients responding to GCs were enrolled. Peripheral blood was obtained at diagnosis (T0) and after four weeks of steroid treatment (T4). MicroRNA profiles were analyzed using next generation sequencing, and selected significantly differentially expressed miRNAs were validated by quantitative reverse transcription-polymerase chain reaction. In detail, 18 miRNAs were differentially expressed from T0 to T4, 16 of which were upregulated and 2 of which were downregulated. Out of these, three miRNAs (miR-144, miR-142, and miR-96) could putatively recognize the 3’UTR of the GR gene and three miRNAs (miR-363, miR-96, miR-142) contained GREs sequences, thereby potentially enabling direct regulation by the GR. In conclusion, we identified miRNAs differently expressed during GC treatment and miRNAs which could be directly regulated by GCs in blood cells of young IBD patients. These results could represent a first step towards their translation as pharmacogenomic biomarkers.

Gene expression profile change and growth inhibition in Drosophila larvae treated with azadirachtin.

PubMed

Lai, Duo; Jin, Xiaoyong; Wang, Hao; Yuan, Mei; Xu, Hanhong

2014-09-20

Azadirachtin is a botanical insecticide that affects various biological processes. The effects of azadirachtin on the digital gene expression profile and growth inhibition in Drosophila larvae have not been investigated. In this study, we applied high-throughput sequencing technology to detect the differentially expressed genes of Drosophila larvae regulated by azadirachtin. A total of 15,322 genes were detected, and 28 genes were found to be significantly regulated by azadirachtin. Biological process and pathway analysis showed that azadirachtin affected starch and sucrose metabolism, defense response, signal transduction, instar larval or pupal development, and chemosensory behavior processes. The genes regulated by azadirachtin were mainly enriched in starch and sucrose metabolism. This study provided a general digital gene expression profile of dysregulated genes in response to azadirachtin and showed that azadirachtin provoked potent growth inhibitory effects in Drosophila larvae by regulating the genes of cuticular protein, amylase, and odorant-binding protein. Finally, we propose a potential mechanism underlying the dysregulation of the insulin/insulin-like growth factor signaling pathway by azadirachtin. Copyright © 2014 Elsevier B.V. All rights reserved.

Brain in situ hybridization maps as a source for reverse-engineering transcriptional regulatory networks: Alzheimer's disease insights

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

Acquaah-Mensah, George K.; Taylor, Ronald C.

Microarray data have been a valuable resource for identifying transcriptional regulatory relationships among genes. As an example, brain region-specific transcriptional regulatory events have the potential of providing etiological insights into Alzheimer Disease (AD). However, there is often a paucity of suitable brain-region specific expression data obtained via microarrays or other high throughput means. The Allen Brain Atlas in situ hybridization (ISH) data sets (Jones et al., 2009) represent a potentially valuable alternative source of high-throughput brain region-specific gene expression data for such purposes. In this study, Allen BrainAtlasmouse ISH data in the hippocampal fields were extracted, focusing on 508 genesmore » relevant to neurodegeneration. Transcriptional regulatory networkswere learned using three high-performing network inference algorithms. Only 17% of regulatory edges from a network reverse-engineered based on brain region-specific ISH data were also found in a network constructed upon gene expression correlations inmousewhole brain microarrays, thus showing the specificity of gene expression within brain sub-regions. Furthermore, the ISH data-based networks were used to identify instructive transcriptional regulatory relationships. Ncor2, Sp3 and Usf2 form a unique three-party regulatory motif, potentially affecting memory formation pathways. Nfe2l1, Egr1 and Usf2 emerge among regulators of genes involved in AD (e.g. Dhcr24, Aplp2, Tia1, Pdrx1, Vdac1, andSyn2). Further, Nfe2l1, Egr1 and Usf2 are sensitive to dietary factors and could be among links between dietary influences and genes in the AD etiology. Thus, this approach of harnessing brain region-specific ISH data represents a rare opportunity for gleaning unique etiological insights for diseases such as AD.« less

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering.

PubMed

Groen, Nathalie; Guvendiren, Murat; Rabitz, Herschel; Welsh, William J; Kohn, Joachim; de Boer, Jan

2016-04-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. Copyright © 2016. Published by Elsevier Ltd.

OncoBinder facilitates interpretation of proteomic interaction data by capturing coactivation pairs in cancer.

PubMed

Van Coillie, Samya; Liang, Lunxi; Zhang, Yao; Wang, Huanbin; Fang, Jing-Yuan; Xu, Jie

2016-04-05

High-throughput methods such as co-immunoprecipitationmass spectrometry (coIP-MS) and yeast 2 hybridization (Y2H) have suggested a broad range of unannotated protein-protein interactions (PPIs), and interpretation of these PPIs remains a challenging task. The advancements in cancer genomic researches allow for the inference of "coactivation pairs" in cancer, which may facilitate the identification of PPIs involved in cancer. Here we present OncoBinder as a tool for the assessment of proteomic interaction data based on the functional synergy of oncoproteins in cancer. This decision tree-based method combines gene mutation, copy number and mRNA expression information to infer the functional status of protein-coding genes. We applied OncoBinder to evaluate the potential binders of EGFR and ERK2 proteins based on the gastric cancer dataset of The Cancer Genome Atlas (TCGA). As a result, OncoBinder identified high confidence interactions (annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) or validated by low-throughput assays) more efficiently than co-expression based method. Taken together, our results suggest that evaluation of gene functional synergy in cancer may facilitate the interpretation of proteomic interaction data. The OncoBinder toolbox for Matlab is freely accessible online.

Droplet-based microfluidic analysis and screening of single plant cells.

PubMed

Yu, Ziyi; Boehm, Christian R; Hibberd, Julian M; Abell, Chris; Haseloff, Jim; Burgess, Steven J; Reyna-Llorens, Ivan

2018-01-01

Droplet-based microfluidics has been used to facilitate high-throughput analysis of individual prokaryote and mammalian cells. However, there is a scarcity of similar workflows applicable to rapid phenotyping of plant systems where phenotyping analyses typically are time-consuming and low-throughput. We report on-chip encapsulation and analysis of protoplasts isolated from the emergent plant model Marchantia polymorpha at processing rates of >100,000 cells per hour. We use our microfluidic system to quantify the stochastic properties of a heat-inducible promoter across a population of transgenic protoplasts to demonstrate its potential for assessing gene expression activity in response to environmental conditions. We further demonstrate on-chip sorting of droplets containing YFP-expressing protoplasts from wild type cells using dielectrophoresis force. This work opens the door to droplet-based microfluidic analysis of plant cells for applications ranging from high-throughput characterisation of DNA parts to single-cell genomics to selection of rare plant phenotypes.

Transcriptomic features associated with energy production in the muscles of Pacific bluefin tuna and Pacific cod.

PubMed

Shibata, Mami; Mekuchi, Miyuki; Mori, Kazuki; Muta, Shigeru; Chowdhury, Vishwajit Sur; Nakamura, Yoji; Ojima, Nobuhiko; Saitoh, Kenji; Kobayashi, Takanori; Wada, Tokio; Inouye, Kiyoshi; Kuhara, Satoru; Tashiro, Kosuke

2016-06-01

Bluefin tuna are high-performance swimmers and top predators in the open ocean. Their swimming is grounded by unique features including an exceptional glycolytic potential in white muscle, which is supported by high enzymatic activities. Here we performed high-throughput RNA sequencing (RNA-Seq) in muscles of the Pacific bluefin tuna (Thunnus orientalis) and Pacific cod (Gadus macrocephalus) and conducted a comparative transcriptomic analysis of genes related to energy production. We found that the total expression of glycolytic genes was much higher in the white muscle of tuna than in the other muscles, and that the expression of only six genes for glycolytic enzymes accounted for 83.4% of the total. These expression patterns were in good agreement with the patterns of enzyme activity previously reported. The findings suggest that the mRNA expression of glycolytic genes may contribute directly to the enzymatic activities in the muscles of tuna.

Identification and validation of vesicant therapeutic targets using a high, throughput siRNA screening approach

DTIC Science & Technology

2014-12-24

toxlet.2011.04.007 Rogers JV, Choi YW, Kiser RC et al (2004) Microarray analysis of gene expression in murine skin exposed to sulfur mustard. J Bio...Chemotactic factors released in culture by intact developing and healing skin lesions produced in rabbits by the irritant sulfur mustard. Inflam- mation 21(2...Project ID Number CBM.CUTOC.04.10. RC 00114. ABSTRACT See reprint. 15. SUBJECT TERMS sulfur mustard, cutaneous injury, siRNA, high-throughput screening

Identification of Potential Chemical Carcinogens in Compendia of Gene Expression Profiles

EPA Science Inventory

Chemicals induce cancer through partially characterized adverse outcome pathways (AOPs) that include molecular initiating events (MIEs) and downstream key events (KEs). Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput form...

Final technical report

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

Edward DeLong

2011-10-07

Our overarching goals in this project were to: Develop and improve high-throughput sequencing methods and analytical approaches for quantitative analyses of microbial gene expression at the Hawaii Ocean Time Series Station and the Bermuda Atlantic Time Series Station; Conduct field analyses following gene expression patterns in picoplankton microbial communities in general, and Prochlorococcus flow sorted from that community, as they respond to different environmental variables (light, macronutrients, dissolved organic carbon), that are predicted to influence activity, productivity, and carbon cycling; Use the expression analyses of flow sorted Prochlorococcus to identify horizontally transferred genes and gene products, in particular those thatmore » are located in genomic islands and likely to confer habitat-specific fitness advantages; Use the microbial community gene expression data that we generate to gain insights, and test hypotheses, about the variability, genomic context, activity and function of as yet uncharacterized gene products, that appear highly expressed in the environment. We achieved the above goals, and even more over the course of the project. This includes a number of novel methodological developments, as well as the standardization of microbial community gene expression analyses in both field surveys, and experimental modalities. The availability of these methods, tools and approaches is changing current practice in microbial community analyses.« less

In silico gene expression profiling in Cannabis sativa.

PubMed

Massimino, Luca

2017-01-01

The cannabis plant and its active ingredients (i.e., cannabinoids and terpenoids) have been socially stigmatized for half a century. Luckily, with more than 430,000 published scientific papers and about 600 ongoing and completed clinical trials, nowadays cannabis is employed for the treatment of many different medical conditions. Nevertheless, even if a large amount of high-throughput functional genomic data exists, most researchers feature a strong background in molecular biology but lack advanced bioinformatics skills. In this work, publicly available gene expression datasets have been analyzed giving rise to a total of 40,224 gene expression profiles taken from cannabis plant tissue at different developmental stages. The resource presented here will provide researchers with a starting point for future investigations with Cannabis sativa .

Customized Molecular Phenotyping by Quantitative Gene Expression and Pattern Recognition Analysis

PubMed Central

Akilesh, Shreeram; Shaffer, Daniel J.; Roopenian, Derry

2003-01-01

Description of the molecular phenotypes of pathobiological processes in vivo is a pressing need in genomic biology. We have implemented a high-throughput real-time PCR strategy to establish quantitative expression profiles of a customized set of target genes. It enables rapid, reproducible data acquisition from limited quantities of RNA, permitting serial sampling of mouse blood during disease progression. We developed an easy to use statistical algorithm—Global Pattern Recognition—to readily identify genes whose expression has changed significantly from healthy baseline profiles. This approach provides unique molecular signatures for rheumatoid arthritis, systemic lupus erythematosus, and graft versus host disease, and can also be applied to defining the molecular phenotype of a variety of other normal and pathological processes. PMID:12840047

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

PubMed Central

2010-01-01

Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

PubMed

Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

2010-01-18

The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

An integrated PCR colony hybridization approach to screen cDNA libraries for full-length coding sequences.

PubMed

Pollier, Jacob; González-Guzmán, Miguel; Ardiles-Diaz, Wilson; Geelen, Danny; Goossens, Alain

2011-01-01

cDNA-Amplified Fragment Length Polymorphism (cDNA-AFLP) is a commonly used technique for genome-wide expression analysis that does not require prior sequence knowledge. Typically, quantitative expression data and sequence information are obtained for a large number of differentially expressed gene tags. However, most of the gene tags do not correspond to full-length (FL) coding sequences, which is a prerequisite for subsequent functional analysis. A medium-throughput screening strategy, based on integration of polymerase chain reaction (PCR) and colony hybridization, was developed that allows in parallel screening of a cDNA library for FL clones corresponding to incomplete cDNAs. The method was applied to screen for the FL open reading frames of a selection of 163 cDNA-AFLP tags from three different medicinal plants, leading to the identification of 109 (67%) FL clones. Furthermore, the protocol allows for the use of multiple probes in a single hybridization event, thus significantly increasing the throughput when screening for rare transcripts. The presented strategy offers an efficient method for the conversion of incomplete expressed sequence tags (ESTs), such as cDNA-AFLP tags, to FL-coding sequences.

Applications of Replicating-Competent Reporter-Expressing Viruses in Diagnostic and Molecular Virology.

PubMed

Li, Yongfeng; Li, Lian-Feng; Yu, Shaoxiong; Wang, Xiao; Zhang, Lingkai; Yu, Jiahui; Xie, Libao; Li, Weike; Ali, Razim; Qiu, Hua-Ji

2016-05-06

Commonly used tests based on wild-type viruses, such as immunostaining, cannot meet the demands for rapid detection of viral replication, high-throughput screening for antivirals, as well as for tracking viral proteins or virus transport in real time. Notably, the development of replicating-competent reporter-expressing viruses (RCREVs) has provided an excellent option to detect directly viral replication without the use of secondary labeling, which represents a significant advance in virology. This article reviews the applications of RCREVs in diagnostic and molecular virology, including rapid neutralization tests, high-throughput screening systems, identification of viral receptors and virus-host interactions, dynamics of viral infections in vitro and in vivo, vaccination approaches and others. However, there remain various challenges associated with RCREVs, including pathogenicity alterations due to the insertion of a reporter gene, instability or loss of the reporter gene expression, or attenuation of reporter signals in vivo. Despite all these limitations, RCREVs have become powerful tools for both basic and applied virology with the development of new technologies for generating RCREVs, the inventions of novel reporters and the better understanding of regulation of viral replication.

Principles of gene microarray data analysis.

PubMed

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

Missing data and technical variability in single-cell RNA-sequencing experiments.

PubMed

Hicks, Stephanie C; Townes, F William; Teng, Mingxiang; Irizarry, Rafael A

2017-11-06

Until recently, high-throughput gene expression technology, such as RNA-Sequencing (RNA-seq) required hundreds of thousands of cells to produce reliable measurements. Recent technical advances permit genome-wide gene expression measurement at the single-cell level. Single-cell RNA-Seq (scRNA-seq) is the most widely used and numerous publications are based on data produced with this technology. However, RNA-seq and scRNA-seq data are markedly different. In particular, unlike RNA-seq, the majority of reported expression levels in scRNA-seq are zeros, which could be either biologically-driven, genes not expressing RNA at the time of measurement, or technically-driven, genes expressing RNA, but not at a sufficient level to be detected by sequencing technology. Another difference is that the proportion of genes reporting the expression level to be zero varies substantially across single cells compared to RNA-seq samples. However, it remains unclear to what extent this cell-to-cell variation is being driven by technical rather than biological variation. Furthermore, while systematic errors, including batch effects, have been widely reported as a major challenge in high-throughput technologies, these issues have received minimal attention in published studies based on scRNA-seq technology. Here, we use an assessment experiment to examine data from published studies and demonstrate that systematic errors can explain a substantial percentage of observed cell-to-cell expression variability. Specifically, we present evidence that some of these reported zeros are driven by technical variation by demonstrating that scRNA-seq produces more zeros than expected and that this bias is greater for lower expressed genes. In addition, this missing data problem is exacerbated by the fact that this technical variation varies cell-to-cell. Then, we show how this technical cell-to-cell variability can be confused with novel biological results. Finally, we demonstrate and discuss how batch-effects and confounded experiments can intensify the problem. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

tCRISPRi: tunable and reversible, one-step control of gene expression

NASA Astrophysics Data System (ADS)

Li, Xin-Tian; Jun, Yonggun; Erickstad, Michael J.; Brown, Steven D.; Parks, Adam; Court, Donald L.; Jun, Suckjoon

2016-12-01

The ability to control the level of gene expression is a major quest in biology. A widely used approach employs deletion of a nonessential gene of interest (knockout), or multi-step recombineering to move a gene of interest under a repressible promoter (knockdown). However, these genetic methods are laborious, and limited for quantitative study. Here, we report a tunable CRISPR-cas system, “tCRISPRi”, for precise and continuous titration of gene expression by more than 30-fold. Our tCRISPRi system employs various previous advancements into a single strain: (1) We constructed a new strain containing a tunable arabinose operon promoter PBAD to quantitatively control the expression of CRISPR-(d)Cas protein over two orders of magnitude in a plasmid-free system. (2) tCRISPRi is reversible, and gene expression is repressed under knockdown conditions. (3) tCRISPRi shows significantly less than 10% leaky expression. (4) Most important from a practical perspective, construction of tCRISPRi to target a new gene requires only one-step of oligo recombineering. Our results show that tCRISPRi, in combination with recombineering, provides a simple and easy-to-implement tool for gene expression control, and is ideally suited for construction of both individual strains and high-throughput tunable knockdown libraries.

Simulation Modeling to Compare High-Throughput, Low-Iteration Optimization Strategies for Metabolic Engineering

PubMed Central

Heinsch, Stephen C.; Das, Siba R.; Smanski, Michael J.

2018-01-01

Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems. PMID:29535690

Cloning, annotation and expression analysis of mycoparasitism-related genes in Trichoderma harzianum 88.

PubMed

Yao, Lin; Yang, Qian; Song, Jinzhu; Tan, Chong; Guo, Changhong; Wang, Li; Qu, Lianhai; Wang, Yun

2013-04-01

Trichoderma harzianum 88, a filamentous soil fungus, is an effective biocontrol agent against several plant pathogens. High-throughput sequencing was used here to study the mycoparasitism mechanisms of T. harzianum 88. Plate confrontation tests of T. harzianum 88 against plant pathogens were conducted, and a cDNA library was constructed from T. harzianum 88 mycelia in the presence of plant pathogen cell walls. Randomly selected transcripts from the cDNA library were compared with eukaryotic plant and fungal genomes. Of the 1,386 transcripts sequenced, the most abundant Gene Ontology (GO) classification group was "physiological process". Differential expression of 19 genes was confirmed by real-time RT-PCR at different mycoparasitism stages against plant pathogens. Gene expression analysis revealed the transcription of various genes involved in mycoparasitism of T. harzianum 88. Our study provides helpful insights into the mechanisms of T. harzianum 88-plant pathogen interactions.

Integrated analysis of gene expression and methylation profiles of 48 candidate genes in breast cancer patients.

PubMed

Li, Zibo; Heng, Jianfu; Yan, Jinhua; Guo, Xinwu; Tang, Lili; Chen, Ming; Peng, Limin; Wu, Yepeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Wang, Jun

2016-11-01

Gene-specific methylation and expression have shown biological and clinical importance for breast cancer diagnosis and prognosis. Integrated analysis of gene methylation and gene expression may identify genes associated with biology mechanism and clinical outcome of breast cancer and aid in clinical management. Using high-throughput microfluidic quantitative PCR, we analyzed the expression profiles of 48 candidate genes in 96 Chinese breast cancer patients and investigated their correlation with gene methylation and associations with breast cancer clinical parameters. Breast cancer-specific gene expression alternation was found in 25 genes with significant expression difference between paired tumor and normal tissues. A total of 9 genes (CCND2, EGFR, GSTP1, PGR, PTGS2, RECK, SOX17, TNFRSF10D, and WIF1) showed significant negative correlation between methylation and gene expression, which were validated in the TCGA database. Total 23 genes (ACADL, APC, BRCA2, CADM1, CAV1, CCND2, CST6, EGFR, ESR2, GSTP1, ICAM5, NPY, PGR, PTGS2, RECK, RUNX3, SFRP1, SOX17, SYK, TGFBR2, TNFRSF10D, WIF1, and WRN) annotated with potential TFBSs in the promoter regions showed negative correlation between methylation and expression. In logistics regression analysis, 31 of the 48 genes showed improved performance in disease prediction with combination of methylation and expression coefficient. Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.

Expression of Innate Immune Response Genes in Liver and Three Types of Adipose Tissue in Cloned Pigs

PubMed Central

Rødgaard, Tina; Skovgaard, Kerstin; Stagsted, Jan

2012-01-01

Abstract The pig has been proposed as a relevant model for human obesity-induced inflammation, and cloning may improve the applicability of this model. We tested the assumptions that cloning would reduce interindividual variation in gene expression of innate immune factors and that their expression would remain unaffected by the cloning process. We investigated the expression of 40 innate immune factors by high-throughput quantitative real-time PCR in samples from liver, abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and neck SAT in cloned pigs compared to normal outbred pigs. The variation in gene expression was found to be similar for the two groups, and the expression of a small number of genes was significantly affected by cloning. In the VAT and abdominal SAT, six out of seven significantly differentially expressed genes were downregulated in the clones. In contrast, most differently expressed genes in both liver and neck SAT were upregulated (seven out of eight). Remarkably, acute phase proteins (APPs) dominated the upregulated genes in the liver, whereas APP expression was either unchanged or downregulated in abdominal SAT and VAT. The general conclusion from this work is that cloning leads to subtle changes in specific subsets of innate immune genes. Such changes, even if minor, may have phenotypic effects over time, e.g., in models of long-term inflammation related to obesity. PMID:22928970

Near-isogenic cotton germplasm lines that differ in fiber-bundle strength have temporal differences in fiber gene expression patterns as revealed by comparative high-throughput profiling.

PubMed

Hinchliffe, Doug J; Meredith, William R; Yeater, Kathleen M; Kim, Hee Jin; Woodward, Andrew W; Chen, Z Jeffrey; Triplett, Barbara A

2010-05-01

Gene expression profiles of developing cotton (Gossypium hirsutum L.) fibers from two near-isogenic lines (NILs) that differ in fiber-bundle strength, short-fiber content, and in fewer than two genetic loci were compared using an oligonucleotide microarray. Fiber gene expression was compared at five time points spanning fiber elongation and secondary cell wall (SCW) biosynthesis. Fiber samples were collected from field plots in a randomized, complete block design, with three spatially distinct biological replications for each NIL at each time point. Microarray hybridizations were performed in a loop experimental design that allowed comparisons of fiber gene expression profiles as a function of time between the two NILs. Overall, developmental expression patterns revealed by the microarray experiment agreed with previously reported cotton fiber gene expression patterns for specific genes. Additionally, genes expressed coordinately with the onset of SCW biosynthesis in cotton fiber correlated with gene expression patterns of other SCW-producing plant tissues. Functional classification and enrichment analysis of differentially expressed genes between the two NILs revealed that genes associated with SCW biosynthesis were significantly up-regulated in fibers of the high-fiber quality line at the transition stage of cotton fiber development. For independent corroboration of the microarray results, 15 genes were selected for quantitative reverse transcription PCR analysis of fiber gene expression. These analyses, conducted over multiple field years, confirmed the temporal difference in fiber gene expression between the two NILs. We hypothesize that the loci conferring temporal differences in fiber gene expression between the NILs are important regulatory sequences that offer the potential for more targeted manipulation of cotton fiber quality.

Gene Expression Omnibus (GEO): Microarray data storage, submission, retrieval, and analysis

PubMed Central

Barrett, Tanya

2006-01-01

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely distributes high-throughput molecular abundance data, predominantly gene expression data generated by DNA microarray technology. The database has a flexible design that can handle diverse styles of both unprocessed and processed data in a MIAME- (Minimum Information About a Microarray Experiment) supportive infrastructure that promotes fully annotated submissions. GEO currently stores about a billion individual gene expression measurements, derived from over 100 organisms, submitted by over 1,500 laboratories, addressing a wide range of biological phenomena. To maximize the utility of these data, several user-friendly Web-based interfaces and applications have been implemented that enable effective exploration, query, and visualization of these data, at the level of individual genes or entire studies. This chapter describes how the data are stored, submission procedures, and mechanisms for data retrieval and query. GEO is publicly accessible at http://www.ncbi.nlm.nih.gov/projects/geo/. PMID:16939800

Genomics for the identification of novel antimicrobials

USDA-ARS?s Scientific Manuscript database

There is a critical need in animal agriculture for developing novel antimicrobials and alternative strategies to reduce the use of antibiotics and address the challenges of antimicrobial resistance. High-throughput gene expression analysis is providing new tools that are enabling the discovery of h...

Analysis, annotation, and profiling of the oat seed transcriptome

USDA-ARS?s Scientific Manuscript database

Novel high-throughput next generation sequencing (NGS) technologies are providing opportunities to explore genomes and transcriptomes in a cost-effective manner. To construct a gene expression atlas of developing oat (Avena sativa) seeds, two software packages specifically designed for RNA-seq (Trin...

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR.

PubMed

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch.

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR

PubMed Central

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch. PMID:21917859

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

Engineering synthetic TALE and CRISPR/Cas9 transcription factors for regulating gene expression.

PubMed

Kabadi, Ami M; Gersbach, Charles A

2014-09-01

Engineered DNA-binding proteins that can be targeted to specific sites in the genome to manipulate gene expression have enabled many advances in biomedical research. This includes generating tools to study fundamental aspects of gene regulation and the development of a new class of gene therapies that alter the expression of endogenous genes. Designed transcription factors have entered clinical trials for the treatment of human diseases and others are in preclinical development. High-throughput and user-friendly platforms for designing synthetic DNA-binding proteins present innovative methods for deciphering cell biology and designing custom synthetic gene circuits. We review two platforms for designing synthetic transcription factors for manipulating gene expression: Transcription activator-like effectors (TALEs) and the RNA-guided clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system. We present an overview of each technology and a guide for designing and assembling custom TALE- and CRISPR/Cas9-based transcription factors. We also discuss characteristics of each platform that are best suited for different applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Identification of microRNAs in PCV2 subclinically infected pigs by high throughput sequencing.

PubMed

Núñez-Hernández, Fernando; Pérez, Lester J; Muñoz, Marta; Vera, Gonzalo; Tomás, Anna; Egea, Raquel; Córdoba, Sarai; Segalés, Joaquim; Sánchez, Armand; Núñez, José I

2015-03-03

Porcine circovirus type 2 (PCV2) is the essential etiological infectious agent of PCV2-systemic disease and has been associated with other swine diseases, all of them collectively known as porcine circovirus diseases. MicroRNAs (miRNAs) are a new class of small non-coding RNAs that regulate gene expression post-transcriptionally. miRNAs play an increasing role in many biological processes. The study of miRNA-mediated host-pathogen interactions has emerged in the last decade due to the important role that miRNAs play in antiviral defense. The objective of this study was to identify the miRNA expression pattern in PCV2 subclinically infected and non-infected pigs. For this purpose an experimental PCV2 infection was carried out and small-RNA libraries were constructed from tonsil and mediastinal lymph node (MLN) of infected and non-infected pigs. High throughput sequencing determined differences in miRNA expression in MLN between infected and non-infected while, in tonsil, a very conserved pattern was observed. In MLN, miRNA 126-3p, miRNA 126-5p, let-7d-3p, mir-129a and mir-let-7b-3p were up-regulated whereas mir-193a-5p, mir-574-5p and mir-34a down-regulated. Prediction of functional analysis showed that these miRNAs can be involved in pathways related to immune system and in processes related to the pathogenesis of PCV2, although functional assays are needed to support these predictions. This is the first study on miRNA gene expression in pigs infected with PCV2 using a high throughput sequencing approach in which several host miRNAs were differentially expressed in response to PCV2 infection.

Identification of functional modules using network topology and high-throughput data.

PubMed

Ulitsky, Igor; Shamir, Ron

2007-01-26

With the advent of systems biology, biological knowledge is often represented today by networks. These include regulatory and metabolic networks, protein-protein interaction networks, and many others. At the same time, high-throughput genomics and proteomics techniques generate very large data sets, which require sophisticated computational analysis. Usually, separate and different analysis methodologies are applied to each of the two data types. An integrated investigation of network and high-throughput information together can improve the quality of the analysis by accounting simultaneously for topological network properties alongside intrinsic features of the high-throughput data. We describe a novel algorithmic framework for this challenge. We first transform the high-throughput data into similarity values, (e.g., by computing pairwise similarity of gene expression patterns from microarray data). Then, given a network of genes or proteins and similarity values between some of them, we seek connected sub-networks (or modules) that manifest high similarity. We develop algorithms for this problem and evaluate their performance on the osmotic shock response network in S. cerevisiae and on the human cell cycle network. We demonstrate that focused, biologically meaningful and relevant functional modules are obtained. In comparison with extant algorithms, our approach has higher sensitivity and higher specificity. We have demonstrated that our method can accurately identify functional modules. Hence, it carries the promise to be highly useful in analysis of high throughput data.

Caste-Specific and Sex-Specific Expression of Chemoreceptor Genes in a Termite

PubMed Central

Mikheyev, Alexander; Tin, Mandy M. Y.; Watanabe, Yutaka; Matsuura, Kenji

2016-01-01

The sophisticated colony organization of eusocial insects is primarily maintained through the utilization of pheromones. The regulation of these complex social interactions requires intricate chemoreception systems. The recent publication of the genome of Zootermopsis nevadensis opened a new avenue to study molecular basis of termite caste systems. Although there has been a growing interest in the termite chemoreception system that regulates their sophisticated caste system, the relationship between division of labor and expression of chemoreceptor genes remains to be explored. Using high-throughput mRNA sequencing (RNA-seq), we found several chemoreceptors that are differentially expressed among castes and between sexes in a subterranean termite Reticulitermes speratus. In total, 53 chemoreception-related genes were annotated, including 22 odorant receptors, 7 gustatory receptors, 12 ionotropic receptors, 9 odorant-binding proteins, and 3 chemosensory proteins. Most of the chemoreception-related genes had caste-related and sex-related expression patterns; in particular, some chemoreception genes showed king-biased or queen-biased expression patterns. Moreover, more than half of the genes showed significant age-dependent differences in their expression in female and/or male reproductives. These results reveal a strong relationship between the evolution of the division of labor and the regulation of chemoreceptor gene expression, thereby demonstrating the chemical communication and underlining chemoreception mechanism in social insects. PMID:26760975

Caste-Specific and Sex-Specific Expression of Chemoreceptor Genes in a Termite.

PubMed

Mitaka, Yuki; Kobayashi, Kazuya; Mikheyev, Alexander; Tin, Mandy M Y; Watanabe, Yutaka; Matsuura, Kenji

2016-01-01

The sophisticated colony organization of eusocial insects is primarily maintained through the utilization of pheromones. The regulation of these complex social interactions requires intricate chemoreception systems. The recent publication of the genome of Zootermopsis nevadensis opened a new avenue to study molecular basis of termite caste systems. Although there has been a growing interest in the termite chemoreception system that regulates their sophisticated caste system, the relationship between division of labor and expression of chemoreceptor genes remains to be explored. Using high-throughput mRNA sequencing (RNA-seq), we found several chemoreceptors that are differentially expressed among castes and between sexes in a subterranean termite Reticulitermes speratus. In total, 53 chemoreception-related genes were annotated, including 22 odorant receptors, 7 gustatory receptors, 12 ionotropic receptors, 9 odorant-binding proteins, and 3 chemosensory proteins. Most of the chemoreception-related genes had caste-related and sex-related expression patterns; in particular, some chemoreception genes showed king-biased or queen-biased expression patterns. Moreover, more than half of the genes showed significant age-dependent differences in their expression in female and/or male reproductives. These results reveal a strong relationship between the evolution of the division of labor and the regulation of chemoreceptor gene expression, thereby demonstrating the chemical communication and underlining chemoreception mechanism in social insects.

Automated Purification of Recombinant Proteins: Combining High-throughput with High Yield

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

Lin, Chiann Tso; Moore, Priscilla A.; Auberry, Deanna L.

2006-05-01

Protein crystallography, mapping protein interactions and other approaches of current functional genomics require not only purifying large numbers of proteins but also obtaining sufficient yield and homogeneity for downstream high-throughput applications. There is a need for the development of robust automated high-throughput protein expression and purification processes to meet these requirements. We developed and compared two alternative workflows for automated purification of recombinant proteins based on expression of bacterial genes in Escherichia coli: First - a filtration separation protocol based on expression of 800 ml E. coli cultures followed by filtration purification using Ni2+-NTATM Agarose (Qiagen). Second - a smallermore » scale magnetic separation method based on expression in 25 ml cultures of E.coli followed by 96-well purification on MagneHisTM Ni2+ Agarose (Promega). Both workflows provided comparable average yields of proteins about 8 ug of purified protein per unit of OD at 600 nm of bacterial culture. We discuss advantages and limitations of the automated workflows that can provide proteins more than 90 % pure in the range of 100 ug – 45 mg per purification run as well as strategies for optimization of these protocols.« less

Quantification of differential gene expression by multiplexed targeted resequencing of cDNA

PubMed Central

Arts, Peer; van der Raadt, Jori; van Gestel, Sebastianus H.C.; Steehouwer, Marloes; Shendure, Jay; Hoischen, Alexander; Albers, Cornelis A.

2017-01-01

Whole-transcriptome or RNA sequencing (RNA-Seq) is a powerful and versatile tool for functional analysis of different types of RNA molecules, but sample reagent and sequencing cost can be prohibitive for hypothesis-driven studies where the aim is to quantify differential expression of a limited number of genes. Here we present an approach for quantification of differential mRNA expression by targeted resequencing of complementary DNA using single-molecule molecular inversion probes (cDNA-smMIPs) that enable highly multiplexed resequencing of cDNA target regions of ∼100 nucleotides and counting of individual molecules. We show that accurate estimates of differential expression can be obtained from molecule counts for hundreds of smMIPs per reaction and that smMIPs are also suitable for quantification of relative gene expression and allele-specific expression. Compared with low-coverage RNA-Seq and a hybridization-based targeted RNA-Seq method, cDNA-smMIPs are a cost-effective high-throughput tool for hypothesis-driven expression analysis in large numbers of genes (10 to 500) and samples (hundreds to thousands). PMID:28474677

Use of high-throughput mass spectrometry to elucidate host pathogen interactions in Salmonella

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

Rodland, Karin D.; Adkins, Joshua N.; Ansong, Charles

Capabilities in mass spectrometry are evolving rapidly, with recent improvements in sensitivity, data analysis, and most important, from the standpoint of this review, much higher throughput allowing analysis of many samples in a single day. This short review describes how these improvements in mass spectrometry can be used to dissect host-pathogen interactions using Salmonella as a model system. This approach enabled direct identification of the majority of annotated Salmonella proteins, quantitation of expression changes under various in vitro growth conditions, and new insights into virulence and expression of Salmonella proteins within host cell cells. One of the most significant findingsmore » is that a very high percentage of the all annotated genes (>20%) in Salmonella are regulated post-transcriptionally. In addition, new and unexpected interactions have been identified for several Salmonella virulence regulators that involve protein-protein interactions, suggesting additional functions of these regulators in coordinating virulence expression. Overall high throughput mass spectrometry provides a new view of pathogen-host interactions emphasizing the protein products and defining how protein interactions determine the outcome of infection.« less

Novel Inducers of Fetal Globin Identified through High Throughput Screening (HTS) Are Active In Vivo in Anemic Baboons and Transgenic Mice.

PubMed

Boosalis, Michael S; Sangerman, Jose I; White, Gary L; Wolf, Roman F; Shen, Ling; Dai, Yan; White, Emily; Makala, Levi H; Li, Biaoru; Pace, Betty S; Nouraie, Mehdi; Faller, Douglas V; Perrine, Susan P

2015-01-01

High-level fetal (γ) globin expression ameliorates clinical severity of the beta (β) hemoglobinopathies, and safe, orally-bioavailable γ-globin inducing agents would benefit many patients. We adapted a LCR-γ-globin promoter-GFP reporter assay to a high-throughput robotic system to evaluate five diverse chemical libraries for this activity. Multiple structurally- and functionally-diverse compounds were identified which activate the γ-globin gene promoter at nanomolar concentrations, including some therapeutics approved for other conditions. Three candidates with established safety profiles were further evaluated in erythroid progenitors, anemic baboons and transgenic mice, with significant induction of γ-globin expression observed in vivo. A lead candidate, Benserazide, emerged which demonstrated > 20-fold induction of γ-globin mRNA expression in anemic baboons and increased F-cell proportions by 3.5-fold in transgenic mice. Benserazide has been used chronically to inhibit amino acid decarboxylase to enhance plasma levels of L-dopa. These studies confirm the utility of high-throughput screening and identify previously unrecognized fetal globin inducing candidates which can be developed expediently for treatment of hemoglobinopathies.

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.

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

Prediction of gene expression in embryonic structures of Drosophila melanogaster.

PubMed

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-07-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms.

Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster

PubMed Central

Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

2007-01-01

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms. PMID:17658945

High-throughput transformation of Saccharomyces cerevisiae using liquid handling robots.

PubMed

Liu, Guangbo; Lanham, Clayton; Buchan, J Ross; Kaplan, Matthew E

2017-01-01

Saccharomyces cerevisiae (budding yeast) is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc) transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids) or genome mutation (e.g., gene mutation, deletion, epitope tagging) is a useful and long established method. However, a reliable and optimized high throughput transformation protocol that runs almost no risk of human error has not been described in the literature. Here, we describe such a method that is broadly transferable to most liquid handling high-throughput robotic platforms, which are now commonplace in academic and industry settings. Using our optimized method, we are able to comfortably transform approximately 1200 individual strains per day, allowing complete transformation of typical genomic yeast libraries within 6 days. In addition, use of our protocol for gene knockout purposes also provides a potentially quicker, easier and more cost-effective approach to generating collections of double mutants than the popular and elegant synthetic genetic array methodology. In summary, our methodology will be of significant use to anyone interested in high throughput molecular and/or genetic analysis of yeast.

Selection of Reference Genes for Expression Studies of Xenobiotic Adaptation in Tetranychus urticae.

PubMed

Morales, Mariany Ashanty; Mendoza, Bianca Marie; Lavine, Laura Corley; Lavine, Mark Daniel; Walsh, Douglas Bruce; Zhu, Fang

2016-01-01

Quantitative real-time PCR (qRT-PCR) is an extensively used, high-throughput method to analyze transcriptional expression of genes of interest. An appropriate normalization strategy with reliable reference genes is required for calculating gene expression across diverse experimental conditions. In this study, we aim to identify the most stable reference genes for expression studies of xenobiotic adaptation in Tetranychus urticae, an extremely polyphagous herbivore causing significant yield reduction of agriculture. We chose eight commonly used housekeeping genes as candidates. The qRT-PCR expression data for these genes were evaluated from seven populations: a susceptible and three acaricide resistant populations feeding on lima beans, and three other susceptible populations which had been shifted host from lima beans to three other plant species. The stability of the candidate reference genes was then assessed using four different algorithms (comparative ΔCt method, geNorm, NormFinder, and BestKeeper). Additionally, we used an online web-based tool (RefFinder) to assign an overall final rank for each candidate gene. Our study found that CycA and Rp49 are best for investigating gene expression in acaricide susceptible and resistant populations. GAPDH, Rp49, and Rpl18 are best for host plant shift studies. And GAPDH and Rp49 were the most stable reference genes when investigating gene expression under changes in both experimental conditions. These results will facilitate research in revealing molecular mechanisms underlying the xenobiotic adaptation of this notorious agricultural pest.

Selection of Reference Genes for Expression Studies of Xenobiotic Adaptation in Tetranychus urticae

PubMed Central

Morales, Mariany Ashanty; Mendoza, Bianca Marie; Lavine, Laura Corley; Lavine, Mark Daniel; Walsh, Douglas Bruce; Zhu, Fang

2016-01-01

Quantitative real-time PCR (qRT-PCR) is an extensively used, high-throughput method to analyze transcriptional expression of genes of interest. An appropriate normalization strategy with reliable reference genes is required for calculating gene expression across diverse experimental conditions. In this study, we aim to identify the most stable reference genes for expression studies of xenobiotic adaptation in Tetranychus urticae, an extremely polyphagous herbivore causing significant yield reduction of agriculture. We chose eight commonly used housekeeping genes as candidates. The qRT-PCR expression data for these genes were evaluated from seven populations: a susceptible and three acaricide resistant populations feeding on lima beans, and three other susceptible populations which had been shifted host from lima beans to three other plant species. The stability of the candidate reference genes was then assessed using four different algorithms (comparative ΔCt method, geNorm, NormFinder, and BestKeeper). Additionally, we used an online web-based tool (RefFinder) to assign an overall final rank for each candidate gene. Our study found that CycA and Rp49 are best for investigating gene expression in acaricide susceptible and resistant populations. GAPDH, Rp49, and Rpl18 are best for host plant shift studies. And GAPDH and Rp49 were the most stable reference genes when investigating gene expression under changes in both experimental conditions. These results will facilitate research in revealing molecular mechanisms underlying the xenobiotic adaptation of this notorious agricultural pest. PMID:27570487

Effects of Gene Duplication, Positive Selection, and Shifts in Gene Expression on the Evolution of the Venom Gland Transcriptome in Widow Spiders

PubMed Central

Haney, Robert A.; Clarke, Thomas H.; Gadgil, Rujuta; Fitzpatrick, Ryan; Hayashi, Cheryl Y.; Ayoub, Nadia A.; Garb, Jessica E.

2016-01-01

Gene duplication and positive selection can be important determinants of the evolution of venom, a protein-rich secretion used in prey capture and defense. In a typical model of venom evolution, gene duplicates switch to venom gland expression and change function under the action of positive selection, which together with further duplication produces large gene families encoding diverse toxins. Although these processes have been demonstrated for individual toxin families, high-throughput multitissue sequencing of closely related venomous species can provide insights into evolutionary dynamics at the scale of the entire venom gland transcriptome. By assembling and analyzing multitissue transcriptomes from the Western black widow spider and two closely related species with distinct venom toxicity phenotypes, we do not find that gene duplication and duplicate retention is greater in gene families with venom gland biased expression in comparison with broadly expressed families. Positive selection has acted on some venom toxin families, but does not appear to be in excess for families with venom gland biased expression. Moreover, we find 309 distinct gene families that have single transcripts with venom gland biased expression, suggesting that the switching of genes to venom gland expression in numerous unrelated gene families has been a dominant mode of evolution. We also find ample variation in protein sequences of venom gland–specific transcripts, lineage-specific family sizes, and ortholog expression among species. This variation might contribute to the variable venom toxicity of these species. PMID:26733576

High-Throughput Screening to Identify Compounds That Increase Fragile X Mental Retardation Protein Expression in Neural Stem Cells Differentiated From Fragile X Syndrome Patient-Derived Induced Pluripotent Stem Cells.

PubMed

Kumari, Daman; Swaroop, Manju; Southall, Noel; Huang, Wenwei; Zheng, Wei; Usdin, Karen

2015-07-01

: Fragile X syndrome (FXS), the most common form of inherited cognitive disability, is caused by a deficiency of the fragile X mental retardation protein (FMRP). In most patients, the absence of FMRP is due to an aberrant transcriptional silencing of the fragile X mental retardation 1 (FMR1) gene. FXS has no cure, and the available treatments only provide symptomatic relief. Given that FMR1 gene silencing in FXS patient cells can be partially reversed by treatment with compounds that target repressive epigenetic marks, restoring FMRP expression could be one approach for the treatment of FXS. We describe a homogeneous and highly sensitive time-resolved fluorescence resonance energy transfer assay for FMRP detection in a 1,536-well plate format. Using neural stem cells differentiated from an FXS patient-derived induced pluripotent stem cell (iPSC) line that does not express any FMRP, we screened a collection of approximately 5,000 known tool compounds and approved drugs using this FMRP assay and identified 6 compounds that modestly increase FMR1 gene expression in FXS patient cells. Although none of these compounds resulted in clinically relevant levels of FMR1 mRNA, our data provide proof of principle that this assay combined with FXS patient-derived neural stem cells can be used in a high-throughput format to identify better lead compounds for FXS drug development. In this study, a specific and sensitive fluorescence resonance energy transfer-based assay for fragile X mental retardation protein detection was developed and optimized for high-throughput screening (HTS) of compound libraries using fragile X syndrome (FXS) patient-derived neural stem cells. The data suggest that this HTS format will be useful for the identification of better lead compounds for developing new therapeutics for FXS. This assay can also be adapted for FMRP detection in clinical and research settings. ©AlphaMed Press.

Superior Cross-Species Reference Genes: A Blueberry Case Study

PubMed Central

Die, Jose V.; Rowland, Lisa J.

2013-01-01

The advent of affordable Next Generation Sequencing technologies has had major impact on studies of many crop species, where access to genomic technologies and genome-scale data sets has been extremely limited until now. The recent development of genomic resources in blueberry will enable the application of high throughput gene expression approaches that should relatively quickly increase our understanding of blueberry physiology. These studies, however, require a highly accurate and robust workflow and make necessary the identification of reference genes with high expression stability for correct target gene normalization. To create a set of superior reference genes for blueberry expression analyses, we mined a publicly available transcriptome data set from blueberry for orthologs to a set of Arabidopsis genes that showed the most stable expression in a developmental series. In total, the expression stability of 13 putative reference genes was evaluated by qPCR and a set of new references with high stability values across a developmental series in fruits and floral buds of blueberry were identified. We also demonstrated the need to use at least two, preferably three, reference genes to avoid inconsistencies in results, even when superior reference genes are used. The new references identified here provide a valuable resource for accurate normalization of gene expression in Vaccinium spp. and may be useful for other members of the Ericaceae family as well. PMID:24058469

Analysis of differentially expressed genes between fluoride-sensitive and fluoride-endurable individuals in midgut of silkworm, Bombyx mori.

PubMed

Qian, Heying; Li, Gang; He, Qingling; Zhang, Huaguang; Xu, Anying

2016-08-15

Fluoride tolerance is an economically important trait of silkworm. Near-isogenic lines (NILs) of the dominant endurance to fluoride (Def) gene in Bombyx mori has been constructed before. Here, we analyzed the gene expression profiles of midgut of fluoride-sensitive and fluoride-endurable individuals of Def NILs by using high-throughput Illumina sequencing technology and bioinformatics tools, and identified differentially expressed genes between these individuals. A total of 3,612,399 and 3,567,631 clean tags for the libraries of fluoride-endurable and fluoride-sensitive individuals were obtained, which corresponded to 32,933 and 43,976 distinct clean tags, respectively. Analysis of differentially expressed genes indicates that 241 genes are differentially expressed between the two libraries. Among the 241 genes, 30 are up-regulated and 211 are down-regulated in fluoride-endurable individuals. Pathway enrichment analysis demonstrates that genes related to ribosomes, pancreatic secretion, steroid biosynthesis, glutathione metabolism, steroid biosynthesis, and glycerolipid metabolism are down-regulated in fluoride-endurable individuals. qRT-PCR was conducted to confirm the results of the DGE. The present study analyzed differential expression of related genes and tried to find out whether the crucial genes were related to fluoride detoxification which might elucidate fluoride effect and provide a new way in the fluorosis research. Copyright © 2016 Elsevier B.V. All rights reserved.

Exploring the key genes and pathways in enchondromas using a gene expression microarray.

PubMed

Shi, Zhongju; Zhou, Hengxing; Pan, Bin; Lu, Lu; Kang, Yi; Liu, Lu; Wei, Zhijian; Feng, Shiqing

2017-07-04

Enchondromas are the most common primary benign osseous neoplasms that occur in the medullary bone; they can undergo malignant transformation into chondrosarcoma. However, enchondromas are always undetected in patients, and the molecular mechanism is unclear. To identify key genes and pathways associated with the occurrence and development of enchondromas, we downloaded the gene expression dataset GSE22855 and obtained the differentially expressed genes (DEGs) by analyzing high-throughput gene expression in enchondromas. In total, 635 genes were identified as DEGs. Of these, 225 genes (35.43%) were up-regulated, and the remaining 410 genes (64.57%) were down-regulated. We identified the predominant gene ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were significantly over-represented in the enchondromas samples compared with the control samples. Subsequently the top 10 core genes were identified from the protein-protein interaction (PPI) network. The enrichment analyses of the genes mainly involved in two significant modules showed that the DEGs were principally related to ribosomes, protein digestion and absorption, ECM-receptor interaction, focal adhesion, amoebiasis and the PI3K-Akt signaling pathway.Together, these data elucidate the molecular mechanisms underlying the occurrence and development of enchondromas and provide promising candidates for therapeutic intervention and prognostic evaluation. However, further experimental studies are needed to confirm these results.

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

Digital gene expression for non-model organisms

PubMed Central

Hong, Lewis Z.; Li, Jun; Schmidt-Küntzel, Anne; Warren, Wesley C.; Barsh, Gregory S.

2011-01-01

Next-generation sequencing technologies offer new approaches for global measurements of gene expression but are mostly limited to organisms for which a high-quality assembled reference genome sequence is available. We present a method for gene expression profiling called EDGE, or EcoP15I-tagged Digital Gene Expression, based on ultra-high-throughput sequencing of 27-bp cDNA fragments that uniquely tag the corresponding gene, thereby allowing direct quantification of transcript abundance. We show that EDGE is capable of assaying for expression in >99% of genes in the genome and achieves saturation after 6–8 million reads. EDGE exhibits very little technical noise, reveals a large (106) dynamic range of gene expression, and is particularly suited for quantification of transcript abundance in non-model organisms where a high-quality annotated genome is not available. In a direct comparison with RNA-seq, both methods provide similar assessments of relative transcript abundance, but EDGE does better at detecting gene expression differences for poorly expressed genes and does not exhibit transcript length bias. Applying EDGE to laboratory mice, we show that a loss-of-function mutation in the melanocortin 1 receptor (Mc1r), recognized as a Mendelian determinant of yellow hair color in many different mammals, also causes reduced expression of genes involved in the interferon response. To illustrate the application of EDGE to a non-model organism, we examine skin biopsy samples from a cheetah (Acinonyx jubatus) and identify genes likely to control differences in the color of spotted versus non-spotted regions. PMID:21844123

Evaluating reproducibility of differential expression discoveries in microarray studies by considering correlated molecular changes.

PubMed

Zhang, Min; Zhang, Lin; Zou, Jinfeng; Yao, Chen; Xiao, Hui; Liu, Qing; Wang, Jing; Wang, Dong; Wang, Chenguang; Guo, Zheng

2009-07-01

According to current consistency metrics such as percentage of overlapping genes (POG), lists of differentially expressed genes (DEGs) detected from different microarray studies for a complex disease are often highly inconsistent. This irreproducibility problem also exists in other high-throughput post-genomic areas such as proteomics and metabolism. A complex disease is often characterized with many coordinated molecular changes, which should be considered when evaluating the reproducibility of discovery lists from different studies. We proposed metrics percentage of overlapping genes-related (POGR) and normalized POGR (nPOGR) to evaluate the consistency between two DEG lists for a complex disease, considering correlated molecular changes rather than only counting gene overlaps between the lists. Based on microarray datasets of three diseases, we showed that though the POG scores for DEG lists from different studies for each disease are extremely low, the POGR and nPOGR scores can be rather high, suggesting that the apparently inconsistent DEG lists may be highly reproducible in the sense that they are actually significantly correlated. Observing different discovery results for a disease by the POGR and nPOGR scores will obviously reduce the uncertainty of the microarray studies. The proposed metrics could also be applicable in many other high-throughput post-genomic areas.

The putative protein methyltransferase LAE1 controls cellulase gene expression in Trichoderma reesei

PubMed Central

Seiboth, Bernhard; Karimi, Razieh Aghcheh; Phatale, Pallavi A; Linke, Rita; Hartl, Lukas; Sauer, Dominik G; Smith, Kristina M; Baker, Scott E; Freitag, Michael; Kubicek, Christian P

2012-01-01

Summary Trichoderma reesei is an industrial producer of enzymes that degrade lignocellulosic polysaccharides to soluble monomers, which can be fermented to biofuels. Here we show that the expression of genes for lignocellulose degradation are controlled by the orthologous T. reesei protein methyltransferase LAE1. In a lae1 deletion mutant we observed a complete loss of expression of all seven cellulases, auxiliary factors for cellulose degradation, β-glucosidases and xylanases were no longer expressed. Conversely, enhanced expression of lae1 resulted in significantly increased cellulase gene transcription. Lae1-modulated cellulase gene expression was dependent on the function of the general cellulase regulator XYR1, but also xyr1 expression was LAE1-dependent. LAE1 was also essential for conidiation of T. reesei. Chromatin immunoprecipitation followed by high-throughput sequencing (‘ChIP-seq’) showed that lae1 expression was not obviously correlated with H3K4 di- or trimethylation (indicative of active transcription) or H3K9 trimethylation (typical for heterochromatin regions) in CAZyme coding regions, suggesting that LAE1 does not affect CAZyme gene expression by directly modulating H3K4 or H3K9 methylation. Our data demonstrate that the putative protein methyltransferase LAE1 is essential for cellulase gene expression in T. reesei through mechanisms that remain to be identified. PMID:22554051

A Bootstrap Based Measure Robust to the Choice of Normalization Methods for Detecting Rhythmic Features in High Dimensional Data.

PubMed

Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A; Peddada, Shyamal D

2018-01-01

Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available in the literature. Based on our experience, in the context of oscillatory systems, such as cell-cycle, circadian clock, etc., the choice of the normalization method may substantially impact the determination of a gene to be rhythmic. Thus rhythmicity of a gene can purely be an artifact of how the data were normalized. Since the determination of rhythmic genes is an important component of modern toxicological and pharmacological studies, it is important to determine truly rhythmic genes that are robust to the choice of a normalization method. Results: In this paper we introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes in an oscillatory system. Although the proposed methodology can be used for any high-throughput gene expression data, in this paper we illustrate the proposed methodology using several publicly available circadian clock microarray gene-expression datasets. We demonstrate that the choice of normalization method has very little effect on the proposed methodology. Specifically, for any pair of normalization methods considered in this paper, the resulting values of the rhythmicity measure are highly correlated. Thus it suggests that the proposed measure is robust to the choice of a normalization method. Consequently, the rhythmicity of a gene is potentially not a mere artifact of the normalization method used. Lastly, as demonstrated in the paper, the proposed bootstrap methodology can also be used for simulating data for genes participating in an oscillatory system using a reference dataset. Availability: A user friendly code implemented in R language can be downloaded from http://www.eio.uva.es/~miguel/robustdetectionprocedure.html.

A Bootstrap Based Measure Robust to the Choice of Normalization Methods for Detecting Rhythmic Features in High Dimensional Data

PubMed Central

Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A.; Peddada, Shyamal D.

2018-01-01

Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available in the literature. Based on our experience, in the context of oscillatory systems, such as cell-cycle, circadian clock, etc., the choice of the normalization method may substantially impact the determination of a gene to be rhythmic. Thus rhythmicity of a gene can purely be an artifact of how the data were normalized. Since the determination of rhythmic genes is an important component of modern toxicological and pharmacological studies, it is important to determine truly rhythmic genes that are robust to the choice of a normalization method. Results: In this paper we introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes in an oscillatory system. Although the proposed methodology can be used for any high-throughput gene expression data, in this paper we illustrate the proposed methodology using several publicly available circadian clock microarray gene-expression datasets. We demonstrate that the choice of normalization method has very little effect on the proposed methodology. Specifically, for any pair of normalization methods considered in this paper, the resulting values of the rhythmicity measure are highly correlated. Thus it suggests that the proposed measure is robust to the choice of a normalization method. Consequently, the rhythmicity of a gene is potentially not a mere artifact of the normalization method used. Lastly, as demonstrated in the paper, the proposed bootstrap methodology can also be used for simulating data for genes participating in an oscillatory system using a reference dataset. Availability: A user friendly code implemented in R language can be downloaded from http://www.eio.uva.es/~miguel/robustdetectionprocedure.html PMID:29456555

From Genes to Protein Mechanics on a Chip

PubMed Central

Milles, Lukas F.; Verdorfer, Tobias; Pippig, Diana A.; Nash, Michael A.; Gaub, Hermann E.

2014-01-01

Single-molecule force spectroscopy enables mechanical testing of individual proteins, however low experimental throughput limits the ability to screen constructs in parallel. We describe a microfluidic platform for on-chip protein expression and measurement of single-molecule mechanical properties. We constructed microarrays of proteins covalently attached to a chip surface, and found that a single cohesin-modified cantilever that bound to the terminal dockerin-tag of each protein remained stable over thousands of pulling cycles. The ability to synthesize and mechanically probe protein libraries presents new opportunities for high-throughput mechanical phenotyping. PMID:25194847

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.

High-Throughput Sequencing Identifies MicroRNAs from Posterior Intestine of Loach (Misgurnus anguillicaudatus) and Their Response to Intestinal Air-Breathing Inhibition.

PubMed

Huang, Songqian; Cao, Xiaojuan; Tian, Xianchang; Wang, Weimin

2016-01-01

MicroRNAs (miRNAs) exert important roles in animal growth, immunity, and development, and regulate gene expression at the post-transcriptional level. Knowledges about the diversities of miRNAs and their roles in accessory air-breathing organs (ABOs) of fish remain unknown. In this work, we used high-throughput sequencing to identify known and novel miRNAs from the posterior intestine, an important ABO, in loach (Misgurnus anguillicaudatus) under normal and intestinal air-breathing inhibited conditions. A total of 204 known and 84 novel miRNAs were identified, while 47 miRNAs were differentially expressed between the two small RNA libraries (i.e. between the normal and intestinal air-breathing inhibited group). Potential miRNA target genes were predicted by combining our transcriptome data of the posterior intestine of the loach under the same conditions, and then annotated using COG, GO, KEGG, Swissprot and Nr databases. The regulatory networks of miRNAs and their target genes were analyzed. The abundances of nine known miRNAs were validated by qRT-PCR. The relative expression profiles of six known miRNAs and their eight corresponding target genes, and two novel potential miRNAs were also detected. Histological characteristics of the posterior intestines in both normal and air-breathing inhibited group were further analyzed. This study contributes to our understanding on the functions and molecular regulatory mechanisms of miRNAs in accessory air-breathing organs of fish.

High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes

PubMed Central

Hidalgo, Marta R.; Cubuk, Cankut; Amadoz, Alicia; Salavert, Francisco; Carbonell-Caballero, José; Dopazo, Joaquin

2017-01-01

Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is a main challenge for precision medicine. Here we propose a new method that models cell signaling using biological knowledge on signal transduction. The method recodes individual gene expression values (and/or gene mutations) into accurate measurements of changes in the activity of signaling circuits, which ultimately constitute high-throughput estimations of cell functionalities caused by gene activity within the pathway. Moreover, such estimations can be obtained either at cohort-level, in case/control comparisons, or personalized for individual patients. The accuracy of the method is demonstrated in an extensive analysis involving 5640 patients from 12 different cancer types. Circuit activity measurements not only have a high diagnostic value but also can be related to relevant disease outcomes such as survival, and can be used to assess therapeutic interventions. PMID:28042959

Identification of FGF-dependent genes in the Drosophila tracheal system.

PubMed

Stahl, Markus; Schuh, Reinhard; Adryan, Boris

2007-01-01

The embryonic development of the tracheal system of the fruit fly Drosophila provides a paradigm for genetic studies of branching morphogenesis. Efforts of many laboratories have identified Branchless (Bnl, a fibroblast growth factor homologue) and Breathless (Btl, the receptor homologue) as crucial factors at many stages of tracheal system development. The downstream targets of the Bnl/Btl signalling cascade, however, remain mostly unknown. Misexpression of the bnl gene results in specific tracheal phenotypes that lead to larval death. We characterised the transcriptional profiles of targeted over-expression of bnl in the embryonic trachea and of loss-of-function bnl(P1) mutant embryos. Gene expression data was mapped to high-throughput in situ hybridisation based ImaGO-annotation. Thus, we identified and confirmed by quantitative PCR 13 Bnl-dependent genes that are expressed in cells within and outside of the tracheal system.

Laminar and dorsoventral molecular organization of the medial entorhinal cortex revealed by large-scale anatomical analysis of gene expression.

PubMed

Ramsden, Helen L; Sürmeli, Gülşen; McDonagh, Steven G; Nolan, Matthew F

2015-01-01

Neural circuits in the medial entorhinal cortex (MEC) encode an animal's position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH) images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. We propose a new molecular basis for distinguishing the deep layers of the MEC and show that their similarity to corresponding layers of neocortex is greater than that of superficial layers. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. We also reveal laminar organization of genes related to disease pathology and suggest that a high metabolic demand predisposes layer II to neurodegenerative pathology. In principle, our computational pipeline can be applied to high-throughput analysis of many forms of neuroanatomical data. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations.

Laminar and Dorsoventral Molecular Organization of the Medial Entorhinal Cortex Revealed by Large-scale Anatomical Analysis of Gene Expression

PubMed Central

Ramsden, Helen L.; Sürmeli, Gülşen; McDonagh, Steven G.; Nolan, Matthew F.

2015-01-01

Neural circuits in the medial entorhinal cortex (MEC) encode an animal’s position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH) images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. We propose a new molecular basis for distinguishing the deep layers of the MEC and show that their similarity to corresponding layers of neocortex is greater than that of superficial layers. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. We also reveal laminar organization of genes related to disease pathology and suggest that a high metabolic demand predisposes layer II to neurodegenerative pathology. In principle, our computational pipeline can be applied to high-throughput analysis of many forms of neuroanatomical data. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations. PMID:25615592

High throughput sequencing identifies chilling responsive genes in sweetpotato (Ipomoea batatas Lam.) during storage.

PubMed

Xie, Zeyi; Zhou, Zhilin; Li, Hongmin; Yu, Jingjing; Jiang, Jiaojiao; Tang, Zhonghou; Ma, Daifu; Zhang, Baohong; Han, Yonghua; Li, Zongyun

2018-05-21

Sweetpotato (Ipomoea batatas L.) is a globally important economic food crop. It belongs to Convolvulaceae family and origins in the tropics; however, sweetpotato is sensitive to cold stress during storage. In this study, we performed transcriptome sequencing to investigate the sweetpotato response to chilling stress during storage. A total of 110,110 unigenes were generated via high-throughput sequencing. Differentially expressed genes (DEGs) analysis showed that 18,681 genes were up-regulated and 21,983 genes were down-regulated in low temperature condition. Many DEGs were related to the cell membrane system, antioxidant enzymes, carbohydrate metabolism, and hormone metabolism, which are potentially associated with sweetpotato resistance to low temperature. The existence of DEGs suggests a molecular basis for the biochemical and physiological consequences of sweetpotato in low temperature storage conditions. Our analysis will provide a new target for enhancement of sweetpotato cold stress tolerance in postharvest storage through genetic manipulation. Copyright © 2018. Published by Elsevier Inc.

Design and engineering of intracellular-metabolite-sensing/regulation gene circuits in Saccharomyces cerevisiae.

PubMed

Wang, Meng; Li, Sijin; Zhao, Huimin

2016-01-01

The development of high-throughput phenotyping tools is lagging far behind the rapid advances of genotype generation methods. To bridge this gap, we report a new strategy for design, construction, and fine-tuning of intracellular-metabolite-sensing/regulation gene circuits by repurposing bacterial transcription factors and eukaryotic promoters. As proof of concept, we systematically investigated the design and engineering of bacterial repressor-based xylose-sensing/regulation gene circuits in Saccharomyces cerevisiae. We demonstrated that numerous properties, such as induction ratio and dose-response curve, can be fine-tuned at three different nodes, including repressor expression level, operator position, and operator sequence. By applying these gene circuits, we developed a cell sorting based, rapid and robust high-throughput screening method for xylose transporter engineering and obtained a sugar transporter HXT14 mutant with 6.5-fold improvement in xylose transportation capacity. This strategy should be generally applicable and highly useful for evolutionary engineering of proteins, pathways, and genomes in S. cerevisiae. © 2015 Wiley Periodicals, Inc.

The genomic response of skeletal muscle to methylprednisolone using microarrays: tailoring data mining to the structure of the pharmacogenomic time series

PubMed Central

DuBois, Debra C; Piel, William H; Jusko, William J

2008-01-01

High-throughput data collection using gene microarrays has great potential as a method for addressing the pharmacogenomics of complex biological systems. Similarly, mechanism-based pharmacokinetic/pharmacodynamic modeling provides a tool for formulating quantitative testable hypotheses concerning the responses of complex biological systems. As the response of such systems to drugs generally entails cascades of molecular events in time, a time series design provides the best approach to capturing the full scope of drug effects. A major problem in using microarrays for high-throughput data collection is sorting through the massive amount of data in order to identify probe sets and genes of interest. Due to its inherent redundancy, a rich time series containing many time points and multiple samples per time point allows for the use of less stringent criteria of expression, expression change and data quality for initial filtering of unwanted probe sets. The remaining probe sets can then become the focus of more intense scrutiny by other methods, including temporal clustering, functional clustering and pharmacokinetic/pharmacodynamic modeling, which provide additional ways of identifying the probes and genes of pharmacological interest. PMID:15212590

Comprehensive circular RNA expression profile in radiation-treated HeLa cells and analysis of radioresistance-related circRNAs.

PubMed

Yu, Duo; Li, Yunfeng; Ming, Zhihui; Wang, Hongyong; Dong, Zhuo; Qiu, Ling; Wang, Tiejun

2018-01-01

Cervical cancer is one of the most common cancers in women worldwide. Malignant tumors develop resistance mechanisms and are less sensitive to or do not respond to irradiation. With the development of high-throughput sequencing technologies, circular RNA (circRNA) has been identified in an increasing number of diseases, especially cancers. It has been reported that circRNA can compete with microRNAs (miRNAs) to change the stability or translation of target RNAs, thus regulating gene expression at the transcriptional level. However, the role of circRNAs in cervical cancer and the radioresistance mechanisms of HeLa cells are unknown. The objective of this study is to investigate the role of circRNAs in radioresistance in HeLa cells. High-throughput sequencing and bioinformatics analysis of irradiated and sham-irradiated HeLa cells. The reliability of high-throughput RNA sequencing was validated using quantitative real-time polymerase chain reaction. The most significant circRNA functions and pathways were selected by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A circRNA-miRNA-target gene interaction network was used to find circRNAs associated with radioresistance. Moreover, a protein-protein interaction network was constructed to identify radioresistance-related hub proteins. High-throughput sequencing allowed the identification of 16,893 circRNAs involved in the response of HeLa cells to radiation. Compared with the control group, there were 153 differentially expressed circRNAs, of which 76 were up-regulated and 77 were down-regulated. GO covered three domains: biological process (BP), cellular component (CC) and molecular function (MF). The terms assigned to the BP domain were peptidyl-tyrosine dephosphorylation and regulation of cell migration. The identified CC terms were cell-cell adherens junction, nucleoplasm and cytosol, and the identified MF terms were protein binding and protein tyrosine phosphatase activity. The top five KEGG pathways were MAPK signaling pathway, endocytosis, axon guidance, neurotrophin signaling pathway, and SNARE interactions in vesicular transport. The protein-protein interaction analysis indicated that 19 proteins might be hub proteins. CircRNAs may play a major role in the response to radiation. These findings may improve our understanding of the role of circRNAs in radioresistance in HeLa cells and allow the development of novel therapeutic approaches.

A gene expression resource generated by genome-wide lacZ profiling in the mouse

PubMed Central

Tuck, Elizabeth; Estabel, Jeanne; Oellrich, Anika; Maguire, Anna Karin; Adissu, Hibret A.; Souter, Luke; Siragher, Emma; Lillistone, Charlotte; Green, Angela L.; Wardle-Jones, Hannah; Carragher, Damian M.; Karp, Natasha A.; Smedley, Damian; Adams, Niels C.; Bussell, James N.; Adams, David J.; Ramírez-Solis, Ramiro; Steel, Karen P.; Galli, Antonella; White, Jacqueline K.

2015-01-01

ABSTRACT Knowledge of the expression profile of a gene is a critical piece of information required to build an understanding of the normal and essential functions of that gene and any role it may play in the development or progression of disease. High-throughput, large-scale efforts are on-going internationally to characterise reporter-tagged knockout mouse lines. As part of that effort, we report an open access adult mouse expression resource, in which the expression profile of 424 genes has been assessed in up to 47 different organs, tissues and sub-structures using a lacZ reporter gene. Many specific and informative expression patterns were noted. Expression was most commonly observed in the testis and brain and was most restricted in white adipose tissue and mammary gland. Over half of the assessed genes presented with an absent or localised expression pattern (categorised as 0-10 positive structures). A link between complexity of expression profile and viability of homozygous null animals was observed; inactivation of genes expressed in ≥21 structures was more likely to result in reduced viability by postnatal day 14 compared with more restricted expression profiles. For validation purposes, this mouse expression resource was compared with Bgee, a federated composite of RNA-based expression data sets. Strong agreement was observed, indicating a high degree of specificity in our data. Furthermore, there were 1207 observations of expression of a particular gene in an anatomical structure where Bgee had no data, indicating a large amount of novelty in our data set. Examples of expression data corroborating and extending genotype-phenotype associations and supporting disease gene candidacy are presented to demonstrate the potential of this powerful resource. PMID:26398943

NCBI GEO: mining millions of expression profiles--database and tools.

PubMed

Barrett, Tanya; Suzek, Tugba O; Troup, Dennis B; Wilhite, Stephen E; Ngau, Wing-Chi; Ledoux, Pierre; Rudnev, Dmitry; Lash, Alex E; Fujibuchi, Wataru; Edgar, Ron

2005-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30,000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

Natural Antisense Transcripts: Molecular Mechanisms and Implications in Breast Cancers

PubMed Central

Latgé, Guillaume; Poulet, Christophe; Bours, Vincent; Jerusalem, Guy

2018-01-01

Natural antisense transcripts are RNA sequences that can be transcribed from both DNA strands at the same locus but in the opposite direction from the gene transcript. Because strand-specific high-throughput sequencing of the antisense transcriptome has only been available for less than a decade, many natural antisense transcripts were first described as long non-coding RNAs. Although the precise biological roles of natural antisense transcripts are not known yet, an increasing number of studies report their implication in gene expression regulation. Their expression levels are altered in many physiological and pathological conditions, including breast cancers. Among the potential clinical utilities of the natural antisense transcripts, the non-coding|coding transcript pairs are of high interest for treatment. Indeed, these pairs can be targeted by antisense oligonucleotides to specifically tune the expression of the coding-gene. Here, we describe the current knowledge about natural antisense transcripts, their varying molecular mechanisms as gene expression regulators, and their potential as prognostic or predictive biomarkers in breast cancers. PMID:29301303

Natural Antisense Transcripts: Molecular Mechanisms and Implications in Breast Cancers.

PubMed

Latgé, Guillaume; Poulet, Christophe; Bours, Vincent; Josse, Claire; Jerusalem, Guy

2018-01-02

Natural antisense transcripts are RNA sequences that can be transcribed from both DNA strands at the same locus but in the opposite direction from the gene transcript. Because strand-specific high-throughput sequencing of the antisense transcriptome has only been available for less than a decade, many natural antisense transcripts were first described as long non-coding RNAs. Although the precise biological roles of natural antisense transcripts are not known yet, an increasing number of studies report their implication in gene expression regulation. Their expression levels are altered in many physiological and pathological conditions, including breast cancers. Among the potential clinical utilities of the natural antisense transcripts, the non-coding|coding transcript pairs are of high interest for treatment. Indeed, these pairs can be targeted by antisense oligonucleotides to specifically tune the expression of the coding-gene. Here, we describe the current knowledge about natural antisense transcripts, their varying molecular mechanisms as gene expression regulators, and their potential as prognostic or predictive biomarkers in breast cancers.

iGC-an integrated analysis package of gene expression and copy number alteration.

PubMed

Lai, Yi-Pin; Wang, Liang-Bo; Wang, Wei-An; Lai, Liang-Chuan; Tsai, Mong-Hsun; Lu, Tzu-Pin; Chuang, Eric Y

2017-01-14

With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual. We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance. The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .

Development of a keratinocyte-based screening model for antipsoriatic drugs using green fluorescent protein under the control of an endogenous promoter.

PubMed

Pol, Arno; van Ruissen, Fred; Schalkwijk, Joost

2002-08-01

Inflamed epidermis (psoriasis, wound healing, ultraviolet-irradiated skin) harbors keratinocytes that are hyperproliferative and display an abnormal differentiation program. A distinct feature of this so-called regenerative maturation pathway is the expression of proteins such as the cytokeratins CK6, CK16, and CK17 and the antiinflammatory protein SKALP/elafin. These proteins are absent in normal skin but highly induced in lesional psoriatic skin. Expression of these genes can be used as a surrogate marker for psoriasis in drug-screening procedures of large compound libraries. The aim of this study was to develop a keratinocyte cell line that contained a reporter gene under the control of a psoriasis-associated endogenous promoter and demonstrate its use in an assay suitable for screening. We generated a stably transfected keratinocyte cell line that expresses enhanced green fluorescent protein (EGFP), under the control of a 0.8-kb fragment derived from the promoter of the SKALP/elafin gene, which confers high levels of tissue-specific expression at the mRNA level. Induction of the SKALP promoter by tumor necrosis factor-alpha resulted in increased expression levels of the secreted SKALP-EGFP fusion protein as assessed by direct readout of fluorescence and fluorescence polarization in 96-well cell culture plates. The fold stimulation of the reporter gene was comparable to that of the endogenous SKALP gene as assessed by enzyme-linked immunosorbent assay. Although the dynamic range of the screening system is limited, the small standard deviation yields a Z factor of 0.49. This indicates that the assay is suitable as a high-throughput screen, and provides proof of the concept that a secreted EGFP fusion protein under the control of a physiologically relevant endogenous promoter can be used as a fluorescence-based high-throughput screen for differentiation-modifying or antiinflammatory compounds that act via the keratinocyte.

Gene expression profiling reveals underlying molecular mechanisms of the early stages of tamoxifen-induced rat hepatocarcinogenesis

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

Pogribny, Igor P.; Bagnyukova, Tetyana V.; Tryndyak, Volodymyr P.

2007-11-15

Tamoxifen is a widely used anti-estrogenic drug for chemotherapy and, more recently, for the chemoprevention of breast cancer. Despite the indisputable benefits of tamoxifen in preventing the occurrence and re-occurrence of breast cancer, the use of tamoxifen has been shown to induce non-alcoholic steatohepatitis, which is a life-threatening fatty liver disease with a risk of progression to cirrhosis and hepatocellular carcinoma. In recent years, the high-throughput microarray technology for large-scale analysis of gene expression has become a powerful tool for increasing the understanding of the molecular mechanisms of carcinogenesis and for identifying new biomarkers with diagnostic and predictive values. Inmore » the present study, we used the high-throughput microarray technology to determine the gene expression profiles in the liver during early stages of tamoxifen-induced rat hepatocarcinogenesis. Female Fisher 344 rats were fed a 420 ppm tamoxifen containing diet for 12 or 24 weeks, and gene expression profiles were determined in liver of control and tamoxifen-exposed rats. The results indicate that early stages of tamoxifen-induced liver carcinogenesis are characterized by alterations in several major cellular pathways, specifically those involved in the tamoxifen metabolism, lipid metabolism, cell cycle signaling, and apoptosis/cell proliferation control. One of the most prominent changes during early stages of tamoxifen-induced hepatocarcinogenesis is dysregulation of signaling pathways in cell cycle progression from the G{sub 1} to S phase, evidenced by the progressive and sustained increase in expression of the Pdgfc, Calb3, Ets1, and Ccnd1 genes accompanied by the elevated level of the PI3K, p-PI3K, Akt1/2, Akt3, and cyclin B, D1, and D3 proteins. The early appearance of these alterations suggests their importance in the mechanism of neoplastic cell transformation induced by tamoxifen.« less

High-throughput sequencing of small RNAs and analysis of differentially expressed microRNAs associated with pistil development in Japanese apricot

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are a class of endogenous, small, non-coding RNAs that regulate gene expression by mediating gene silencing at transcriptional and post-transcriptional levels in high plants. However, the diversity of miRNAs and their roles in floral development in Japanese apricot (Prunus mume Sieb. et Zucc) remains largely unexplored. Imperfect flowers with pistil abortion seriously decrease production yields. To understand the role of miRNAs in pistil development, pistil development-related miRNAs were identified by Solexa sequencing in Japanese apricot. Results Solexa sequencing was used to identify and quantitatively profile small RNAs from perfect and imperfect flower buds of Japanese apricot. A total of 22,561,972 and 24,952,690 reads were sequenced from two small RNA libraries constructed from perfect and imperfect flower buds, respectively. Sixty-one known miRNAs, belonging to 24 families, were identified. Comparative profiling revealed that seven known miRNAs exhibited significant differential expression between perfect and imperfect flower buds. A total of 61 potentially novel miRNAs/new members of known miRNA families were also identified by the presence of mature miRNAs and corresponding miRNA*s in the sRNA libraries. Comparative analysis showed that six potentially novel miRNAs were differentially expressed between perfect and imperfect flower buds. Target predictions of the 13 differentially expressed miRNAs resulted in 212 target genes. Gene ontology (GO) annotation revealed that high-ranking miRNA target genes are those implicated in the developmental process, the regulation of transcription and response to stress. Conclusions This study represents the first comparative identification of miRNAomes between perfect and imperfect Japanese apricot flowers. Seven known miRNAs and six potentially novel miRNAs associated with pistil development were identified, using high-throughput sequencing of small RNAs. The findings, both computationally and experimentally, provide valuable information for further functional characterisation of miRNAs associated with pistil development in plants. PMID:22863067

High Throughput, High Content Screening for Novel Pigmentation Regulators Using a Keratinocyte/Melanocyte Co-culture System

PubMed Central

Lee, Ju Hee; Chen, Hongxiang; Kolev, Vihren; Aull, Katherine H.; Jung, Inhee; Wang, Jun; Miyamoto, Shoko; Hosoi, Junichi; Mandinova, Anna; Fisher, David E.

2014-01-01

Skin pigmentation is a complex process including melanogenesis within melanocytes and melanin transfer to the keratinocytes. To develop a comprehensive screening method for novel pigmentation regulators, we used immortalized melanocytes and keratinocytes in co-culture to screen large numbers of compounds. High-throughput screening plates were subjected to digital automated microscopy to quantify the pigmentation via brightfield microscopy. Compounds with pigment suppression were secondarily tested for their effects on expression of MITF and several pigment regulatory genes, and further validated in terms of non-toxicity to keratinocytes/melanocytes and dose dependent activity. The results demonstrate a high-throughput, high-content screening approach, which is applicable to the analysis of large chemical libraries using a co-culture system. We identified candidate pigmentation inhibitors from 4,000 screened compounds including zoxazolamine, 3-methoxycatechol, and alpha-mangostin, which were also shown to modulate expression of MITF and several key pigmentation factors, and are worthy of further evaluation for potential translation to clinical use. PMID:24438532

Global gene expression analysis using RNA-seq uncovered a new role for SR1/CAMTA3 transcription factor in salt stress

PubMed Central

Prasad, Kasavajhala V. S. K.; Abdel-Hameed, Amira A. E.; Xing, Denghui; Reddy, Anireddy S. N.

2016-01-01

Abiotic and biotic stresses cause significant yield losses in all crops. Acquisition of stress tolerance in plants requires rapid reprogramming of gene expression. SR1/CAMTA3, a member of signal responsive transcription factors (TFs), functions both as a positive and a negative regulator of biotic stress responses and as a positive regulator of cold stress-induced gene expression. Using high throughput RNA-seq, we identified ~3000 SR1-regulated genes. Promoters of about 60% of the differentially expressed genes have a known DNA binding site for SR1, suggesting that they are likely direct targets. Gene ontology analysis of SR1-regulated genes confirmed previously known functions of SR1 and uncovered a potential role for this TF in salt stress. Our results showed that SR1 mutant is more tolerant to salt stress than the wild type and complemented line. Improved tolerance of sr1 seedlings to salt is accompanied with the induction of salt-responsive genes. Furthermore, ChIP-PCR results showed that SR1 binds to promoters of several salt-responsive genes. These results suggest that SR1 acts as a negative regulator of salt tolerance by directly repressing the expression of salt-responsive genes. Overall, this study identified SR1-regulated genes globally and uncovered a previously uncharacterized role for SR1 in salt stress response. PMID:27251464

Functional Genome Mining for Metabolites Encoded by Large Gene Clusters through Heterologous Expression of a Whole-Genome Bacterial Artificial Chromosome Library in Streptomyces spp.

PubMed Central

Xu, Min; Wang, Yemin; Zhao, Zhilong; Gao, Guixi; Huang, Sheng-Xiong; Kang, Qianjin; He, Xinyi; Lin, Shuangjun; Pang, Xiuhua; Deng, Zixin

2016-01-01

ABSTRACT Genome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries in Streptomyces spp. We demonstrate mining from a strain of Streptomyces rochei, which is known to produce streptothricins and borrelidin, by expressing its BAC library in the surrogate host Streptomyces lividans SBT5, and screening for antimicrobial activity. In addition to the successful capture of the streptothricin and borrelidin biosynthetic gene clusters, we discovered two novel linear lipopeptides and their corresponding biosynthetic gene cluster, as well as a novel cryptic gene cluster for an unknown antibiotic from S. rochei. This high-throughput functional genome mining approach can be easily applied to other streptomycetes, and it is very suitable for the large-scale screening of genomic BAC libraries for bioactive natural products and the corresponding biosynthetic pathways. IMPORTANCE Microbial genomes encode numerous cryptic biosynthetic gene clusters for unknown small metabolites with potential biological activities. Several genome mining approaches have been developed to activate and bring these cryptic metabolites to biological tests for future drug discovery. Previous sequence-guided procedures relied on bioinformatic analysis to predict potentially interesting biosynthetic gene clusters. In this study, we describe an efficient approach based on heterologous expression and functional screening of a whole-genome library for the mining of bioactive metabolites from Streptomyces. The usefulness of this function-driven approach was demonstrated by the capture of four large biosynthetic gene clusters for metabolites of various chemical types, including streptothricins, borrelidin, two novel lipopeptides, and one unknown antibiotic from Streptomyces rochei Sal35. The transfer, expression, and screening of the library were all performed in a high-throughput way, so that this approach is scalable and adaptable to industrial automation for next-generation antibiotic discovery. PMID:27451447

Novel Approaches to Preventing Urinary Tract Infection in Women

DTIC Science & Technology

1999-09-01

throughput analysis of differential gene expression of in vitro urothelium exposed to uropathogenic Escherichia colj pDC-1. Program and abstracts of...chip" analysis of in vitro urothelium exposed to uropathogenic Escherichia coli pDC-1. Presented at the annual meeting of the American Academy of

Comparison of L1000 and Affymetrix Microarray for In Vitro Concentration-Response Gene Expression Profiling (SOT)

EPA Science Inventory

Advances in high-throughput screening technologies and in vitro systems have opened doors for cost-efficient evaluation of chemical effects on a diversity of biological endpoints. However, toxicogenomics platforms remain too costly to evaluate large libraries of chemicals in conc...

High-throughput SuperSAGE for gene expression analysis of Nicotiana tabacum - Rhizoctonia solani interaction

USDA-ARS?s Scientific Manuscript database

Plants are under continuous threat of infection by pathogens endowed with diverse strategies to colonize their host. Knowledge of plant susceptibility factors and the molecular processes involved in the infection process are critical for understanding plant-pathogen interactions. We used SuperSAGE t...

A reduced transcriptome approach to assess environmental toxicants using zebrafish embryo tests

EPA Science Inventory

This paper reports on the pilot testing of a new bioassay platform that monitors expression of 1600 genes in zebrafish embryos exposed to either single chemicals or complex water samples. The method provides a more cost effective, high throughput means to broadly evaluate the pot...

Identification of immunohistochemical markers for distinguishing lung adenocarcinoma from squamous cell carcinoma

PubMed Central

Zhan, Cheng; Yan, Li; Wang, Lin; Sun, Yang; Wang, Xingxing; Lin, Zongwu; Zhang, Yongxing; Wang, Qun

2015-01-01

Background Immunohistochemical staining has been widely used in distinguishing lung adenocarcinoma (LUAD) from lung squamous cell carcinoma (LUSC), which is of vital importance for the diagnosis and treatment of lung cancer. Due to the lack of a comprehensive analysis of different lung cancer subtypes, there may still be undiscovered markers with higher diagnostic accuracy. Methods Herein first, we systematically analyzed high-throughput data obtained from The Cancer Genome Atlas (TCGA) database. Combining differently expressed gene screening and receiver operating characteristic (ROC) curve analysis, we attempted to identify the genes which might be suitable as immunohistochemical markers in distinguishing LUAD from LUSC. Then we detected the expression of six of these genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in lung cancer sections using immunohistochemical staining. Results A number of genes were identified as candidate immunohistochemical markers with high sensitivity and specificity in distinguishing LUAD from LUSC. Then the staining results confirmed the potentials of the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in distinguishing LUAD from LUSC, and their sensitivity and specificity were not less than many commonly used markers. Conclusions The results revealed that the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) might be suitable markers in distinguishing LUAD from LUSC, and also validated the feasibility of our methods for identification of candidate markers from high-throughput data. PMID:26380766

Cloning, over-expression and purification of Pseudomonas aeruginosa murC encoding uridine diphosphate N-acetylmuramate: L-alanine ligase.

PubMed

El Zoeiby, A; Sanschagrin, F; Lamoureux, J; Darveau, A; Levesque, R C

2000-02-15

We cloned and sequenced the murC gene from Pseudomonas aeruginosa encoding a protein of 53 kDa. Multiple alignments with 20 MurC peptide sequences from different bacteria confirmed the presence of highly conserved regions having sequence identities ranging from 22-97% including conserved motifs for ATP-binding and the active site of the enzyme. Genetic complementation was done in Escherichia coli (murCts) suppressing the lethal phenotype. The murC gene was subcloned into the expression vector pET30a and overexpressed in E. coli BL21(lambdaDE3). Three PCR cloning strategies were used to obtain the three recombinant plasmids for expression of the native MurC, MurC His-tagged at N-terminal and at C-terminal, respectively. MurC His-tagged at C-terminal was chosen for large scale production and protein purification in the soluble form. The purification was done in a single chromatographic step on an affinity nickel column and obtained in mg quantities at 95% homogeneity. MurC protein was used to produce monoclonal antibodies for epitope mapping and for assay development in high throughput screenings. Detailed studies of MurC and other genes of the bacterial cell cycle will provide the reagents and strain constructs for high throughput screening and for design of novel antibacterials.

Sexually Dimorphic Gene Expression Associated with Growth and Reproduction of Tongue Sole (Cynoglossus semilaevis) Revealed by Brain Transcriptome Analysis.

PubMed

Wang, Pingping; Zheng, Min; Liu, Jian; Liu, Yongzhuang; Lu, Jianguo; Sun, Xiaowen

2016-08-26

In this study, we performed a comprehensive analysis of the transcriptome of one- and two-year-old male and female brains of Cynoglossus semilaevis by high-throughput Illumina sequencing. A total of 77,066 transcripts, corresponding to 21,475 unigenes, were obtained with a N50 value of 4349 bp. Of these unigenes, 33 genes were found to have significant differential expression and potentially associated with growth, from which 18 genes were down-regulated and 12 genes were up-regulated in two-year-old males, most of these genes had no significant differences in expression among one-year-old males and females and two-year-old females. A similar analysis was conducted to look for genes associated with reproduction; 25 genes were identified, among them, five genes were found to be down regulated and 20 genes up regulated in two-year-old males, again, most of the genes had no significant expression differences among the other three. The performance of up regulated genes in Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was significantly different between two-year-old males and females. Males had a high gene expression in genetic information processing, while female's highly expressed genes were mainly enriched on organismal systems. Our work identified a set of sex-biased genes potentially associated with growth and reproduction that might be the candidate factors affecting sexual dimorphism of tongue sole, laying the foundation to understand the complex process of sex determination of this economic valuable species.

Multiplex enrichment quantitative PCR (ME-qPCR): a high-throughput, highly sensitive detection method for GMO identification.

PubMed

Fu, Wei; Zhu, Pengyu; Wei, Shuang; Zhixin, Du; Wang, Chenguang; Wu, Xiyang; Li, Feiwu; Zhu, Shuifang

2017-04-01

Among all of the high-throughput detection methods, PCR-based methodologies are regarded as the most cost-efficient and feasible methodologies compared with the next-generation sequencing or ChIP-based methods. However, the PCR-based methods can only achieve multiplex detection up to 15-plex due to limitations imposed by the multiplex primer interactions. The detection throughput cannot meet the demands of high-throughput detection, such as SNP or gene expression analysis. Therefore, in our study, we have developed a new high-throughput PCR-based detection method, multiplex enrichment quantitative PCR (ME-qPCR), which is a combination of qPCR and nested PCR. The GMO content detection results in our study showed that ME-qPCR could achieve high-throughput detection up to 26-plex. Compared to the original qPCR, the Ct values of ME-qPCR were lower for the same group, which showed that ME-qPCR sensitivity is higher than the original qPCR. The absolute limit of detection for ME-qPCR could achieve levels as low as a single copy of the plant genome. Moreover, the specificity results showed that no cross-amplification occurred for irrelevant GMO events. After evaluation of all of the parameters, a practical evaluation was performed with different foods. The more stable amplification results, compared to qPCR, showed that ME-qPCR was suitable for GMO detection in foods. In conclusion, ME-qPCR achieved sensitive, high-throughput GMO detection in complex substrates, such as crops or food samples. In the future, ME-qPCR-based GMO content identification may positively impact SNP analysis or multiplex gene expression of food or agricultural samples. Graphical abstract For the first-step amplification, four primers (A, B, C, and D) have been added into the reaction volume. In this manner, four kinds of amplicons have been generated. All of these four amplicons could be regarded as the target of second-step PCR. For the second-step amplification, three parallels have been taken for the final evaluation. After the second evaluation, the final amplification curves and melting curves have been achieved.

Comparative Transcriptomics to Identify Novel Genes and Pathways in Dinoflagellates

NASA Astrophysics Data System (ADS)

Ryan, D.

2016-02-01

The unarmored dinoflagellate Karenia brevis is among the most prominent harmful, bloom-forming phytoplankton species in the Gulf of Mexico. During blooms, the polyketides PbTx-1 and PbTx-2 (brevetoxins) are produced by K. brevis. Brevetoxins negatively impact human health and the Gulf shellfish harvest. However, the genes underlying brevetoxin synthesis are currently unknown. Because the K. brevis genome is extremely large ( 1 × 1011 base pairs long), and with a high proportion of repetitive, non-coding DNA, it has not been sequenced. In fact, large, repetitive genomes are common among the dinoflagellate group. High-throughput RNA sequencing technology enabled us to assemble Karenia transcriptomes de novo and investigate potential genes in the brevetoxin pathway through comparative transcriptomics. The brevetoxin profile varies among K. brevis clonal cultures. For example, well-documented Wilson-CCFWC268 typically produces 8-10 pg PbTx per cell, whereas SP1 produces < 2 pg PbTx/cell, and the mutant low-toxin Wilson clone produces undetectable to low (<0.05 pg/cell) amounts. Further, PbTx-2 has been measured in Karenia papilionacea but not Karenia mikimotoi. We compared the transcriptomes of four K. brevis clones (Wilson-CCFWC268, SP3, SP1, and mutant low-toxin Wilson) with K. papilionacea and K. mikimotoi to investigate nucleotide-level genetic variations and differences in gene expression. Of the 85,000 transcripts in the K. brevis transcriptome, 4,600 transcripts, including novel unannotated orthologs and putative polyketide synthases (PKSs), were only expressed by brevetoxin-producing K. brevis and K. papilionacea, not K. mikimotoi. Examination of gene expression between the typical- and low-toxin Wilson clones identified about 3,500 genes with significantly different expression levels, including 2 putative PKSs. One of the 2 PKSs was only found in the brevetoxin-producing Karenia species. These transcriptomes could not have been characterized without high-throughput RNA sequencing.

An interspecific fungal hybrid reveals cross-kingdom rules for allopolyploid gene expression patterns.

PubMed

Cox, Murray P; Dong, Ting; Shen, Genggeng; Dalvi, Yogesh; Scott, D Barry; Ganley, Austen R D

2014-03-01

Polyploidy, a state in which the chromosome complement has undergone an increase, is a major force in evolution. Understanding the consequences of polyploidy has received much attention, and allopolyploids, which result from the union of two different parental genomes, are of particular interest because they must overcome a suite of biological responses to this merger, known as "genome shock." A key question is what happens to gene expression of the two gene copies following allopolyploidization, but until recently the tools to answer this question on a genome-wide basis were lacking. Here we utilize high throughput transcriptome sequencing to produce the first genome-wide picture of gene expression response to allopolyploidy in fungi. A novel pipeline for assigning sequence reads to the gene copies was used to quantify their expression in a fungal allopolyploid. We find that the transcriptional response to allopolyploidy is predominantly conservative: both copies of most genes are retained; over half the genes inherit parental gene expression patterns; and parental differential expression is often lost in the allopolyploid. Strikingly, the patterns of gene expression change are highly concordant with the genome-wide expression results of a cotton allopolyploid. The very different nature of these two allopolyploids implies a conserved, eukaryote-wide transcriptional response to genome merger. We provide evidence that the transcriptional responses we observe are mostly driven by intrinsic differences between the regulatory systems in the parent species, and from this propose a mechanistic model in which the cross-kingdom conservation in transcriptional response reflects conservation of the mutational processes underlying eukaryotic gene regulatory evolution. This work provides a platform to develop a universal understanding of gene expression response to allopolyploidy and suggests that allopolyploids are an exceptional system to investigate gene regulatory changes that have evolved in the parental species prior to allopolyploidization.

Efficient expression systems for cysteine proteases of malaria parasites

PubMed Central

Sarduy, Emir Salas; de los A. Chávez Planes, María

2013-01-01

Papain-like cysteine proteases of malaria parasites are considered important chemotherapeutic targets or valuable models for the evaluation of drug candidates. Consequently, many of these enzymes have been cloned and expressed in Escherichia coli for their biochemical characterization. However, their expression has been problematic, showing low yield and leading to the formation of insoluble aggregates. Given that highly-productive expression systems are required for the high-throughput evaluation of inhibitors, we analyzed the existing expression systems to identify the causes of such apparent issues. We found that significant divergences in codon and nucleotide composition from host genes are the most probable cause of expression failure, and propose several strategies to overcome these limitations. Finally we predict that yeast hosts Saccharomyces cerevisiae and Pichia pastoris may be better suited than E. coli for the efficient expression of plasmodial genes, presumably leading to soluble and active products reproducing structural and functional characteristics of the natural enzymes. PMID:23018863

A Knock-in Reporter for a Novel AR-Targeted Therapy

DTIC Science & Technology

2016-05-01

of this research is to explore a possibility whether the CRISPR -Cas9 technology, an emerging genome-editing approach, could be applied to develop a...in this report that the CRISPR -Cas9 system could indeed mediate high-efficient insertion of a selection gene into a site immediately downstream of...inhibitory for AR expression. 15. SUBJECT TERMS Androgen receptor, high-throughput drug screening assay, reporter gene assay, CRISPR -Cas9, genome editing

Targeted and genome-scale methylomics reveals gene body signatures in human cell lines

PubMed Central

Ball, Madeleine Price; Li, Jin Billy; Gao, Yuan; Lee, Je-Hyuk; LeProust, Emily; Park, In-Hyun; Xie, Bin; Daley, George Q.; Church, George M.

2012-01-01

Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions. PMID:19329998

Estimation of Dynamic Systems for Gene Regulatory Networks from Dependent Time-Course Data.

PubMed

Kim, Yoonji; Kim, Jaejik

2018-06-15

Dynamic system consisting of ordinary differential equations (ODEs) is a well-known tool for describing dynamic nature of gene regulatory networks (GRNs), and the dynamic features of GRNs are usually captured through time-course gene expression data. Owing to high-throughput technologies, time-course gene expression data have complex structures such as heteroscedasticity, correlations between genes, and time dependence. Since gene experiments typically yield highly noisy data with small sample size, for a more accurate prediction of the dynamics, the complex structures should be taken into account in ODE models. Hence, this study proposes an ODE model considering such data structures and a fast and stable estimation method for the ODE parameters based on the generalized profiling approach with data smoothing techniques. The proposed method also provides statistical inference for the ODE estimator and it is applied to a zebrafish retina cell network.

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

PubMed

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

2015-01-01

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

Cardiogenic Genes Expressed in Cardiac Fibroblasts Contribute to Heart Development and Repair

PubMed Central

Furtado, Milena B.; Costa, Mauro W.; Pranoto, Edward Adi; Salimova, Ekaterina; Pinto, Alex; Lam, Nicholas T.; Park, Anthony; Snider, Paige; Chandran, Anjana; Harvey, Richard P.; Boyd, Richard; Conway, Simon J.; Pearson, James; Kaye, David M.; Rosenthal, Nadia A.

2014-01-01

Rationale Cardiac fibroblasts are critical to proper heart function through multiple interactions with the myocardial compartment but appreciation of their contribution has suffered from incomplete characterization and lack of cell-specific markers. Objective To generate an unbiased comparative gene expression profile of the cardiac fibroblast pool, identify and characterize the role of key genes in cardiac fibroblast function, and determine their contribution to myocardial development and regeneration. Methods and Results High-throughput cell surface and intracellular profiling of cardiac and tail fibroblasts identified canonical MSC and a surprising number of cardiogenic genes, some expressed at higher levels than in whole heart. Whilst genetically marked fibroblasts contributed heterogeneously to interstitial but not cardiomyocyte compartments in infarcted hearts, fibroblast-restricted depletion of one highly expressed cardiogenic marker, Tbx20, caused marked myocardial dysmorphology and perturbations in scar formation upon myocardial infarction. Conclusions The surprising transcriptional identity of cardiac fibroblasts, the adoption of cardiogenic gene programs and direct contribution to cardiac development and repair provokes alternative interpretations for studies on more specialized cardiac progenitors, offering a novel perspective for reinterpreting cardiac regenerative therapies. PMID:24650916

Analysis of porcine adipose tissue transcriptome reveals differences in de novo fatty acid synthesis in pigs with divergent muscle fatty acid composition.

PubMed

Corominas, Jordi; Ramayo-Caldas, Yuliaxis; Puig-Oliveras, Anna; Estellé, Jordi; Castelló, Anna; Alves, Estefania; Pena, Ramona N; Ballester, Maria; Folch, Josep M

2013-12-01

In pigs, adipose tissue is one of the principal organs involved in the regulation of lipid metabolism. It is particularly involved in the overall fatty acid synthesis with consequences in other lipid-target organs such as muscles and the liver. With this in mind, we have used massive, parallel high-throughput sequencing technologies to characterize the porcine adipose tissue transcriptome architecture in six Iberian x Landrace crossbred pigs showing extreme phenotypes for intramuscular fatty acid composition (three per group). High-throughput RNA sequencing was used to generate a whole characterization of adipose tissue (backfat) transcriptome. A total of 4,130 putative unannotated protein-coding sequences were identified in the 20% of reads which mapped in intergenic regions. Furthermore, 36% of the unmapped reads were represented by interspersed repeats, SINEs being the most abundant elements. Differential expression analyses identified 396 candidate genes among divergent animals for intramuscular fatty acid composition. Sixty-two percent of these genes (247/396) presented higher expression in the group of pigs with higher content of intramuscular SFA and MUFA, while the remaining 149 showed higher expression in the group with higher content of PUFA. Pathway analysis related these genes to biological functions and canonical pathways controlling lipid and fatty acid metabolisms. In concordance with the phenotypic classification of animals, the major metabolic pathway differentially modulated between groups was de novo lipogenesis, the group with more PUFA being the one that showed lower expression of lipogenic genes. These results will help in the identification of genetic variants at loci that affect fatty acid composition traits. The implications of these results range from the improvement of porcine meat quality traits to the application of the pig as an animal model of human metabolic diseases.

Detection of rearrangements and transcriptional up-regulation of ALK in FFPE lung cancer specimens using a novel, sensitive, quantitative reverse transcription polymerase chain reaction assay.

PubMed

Gruber, Kim; Horn, Heike; Kalla, Jörg; Fritz, Peter; Rosenwald, Andreas; Kohlhäufl, Martin; Friedel, Godehard; Schwab, Matthias; Ott, German; Kalla, Claudia

2014-03-01

The approved dual-color fluorescence in situ hybridization (FISH) test for the detection of anaplastic lymphoma receptor tyrosine kinase (ALK) gene rearrangements in non-small-cell lung cancer (NSCLC) is complex and represents a low-throughput assay difficult to use in daily diagnostic practice. We devised a sensitive and robust routine diagnostic test for the detection of rearrangements and transcriptional up-regulation of ALK. We developed a quantitative reverse transcription polymerase chain reaction (qRT-PCR) assay adapted to RNA isolated from routine formalin-fixed, paraffin-embedded material and applied it to 652 NSCLC specimens. The reliability of this technique to detect ALK dysregulation was shown by comparison with FISH and immunohistochemistry. qRT-PCR analysis detected unbalanced ALK expression indicative of a gene rearrangement in 24 (4.6%) and full-length ALK transcript expression in six (1.1%) of 523 interpretable tumors. Among 182 tumors simultaneously analyzed by FISH and qRT-PCR, the latter accurately typed 97% of 19 rearranged and 158 nonrearranged tumors and identified ALK deregulation in two cases with insufficient FISH. Six tumors expressing full-length ALK transcripts did not show rearrangements of the gene. Immunohistochemistry detected ALK protein overexpression in tumors with gene fusions and transcriptional up-regulation, but did not distinguish between the two. One case with full-length ALK expression carried a heterozygous point mutation (S1220Y) within the kinase domain potentially interfering with kinase activity and/or inhibitor binding. Our qRT-PCR assay reliably identifies and distinguishes ALK rearrangements and full-length transcript expression in formalin-fixed, paraffin-embedded material. It is an easy-to-perform, cost-effective, and high-throughput tool for the diagnosis of ALK activation. The expression of full-length ALK transcripts may be relevant for ALK inhibitor therapy in NSCLC.

Selection of reference genes for quantitative real-time PCR normalization in Panax ginseng at different stages of growth and in different organs.

PubMed

Liu, Jing; Wang, Qun; Sun, Minying; Zhu, Linlin; Yang, Michael; Zhao, Yu

2014-01-01

Quantitative real-time reverse transcription PCR (qRT-PCR) has become a widely used method for gene expression analysis; however, its data interpretation largely depends on the stability of reference genes. The transcriptomics of Panax ginseng, one of the most popular and traditional ingredients used in Chinese medicines, is increasingly being studied. Furthermore, it is vital to establish a series of reliable reference genes when qRT-PCR is used to assess the gene expression profile of ginseng. In this study, we screened out candidate reference genes for ginseng using gene expression data generated by a high-throughput sequencing platform. Based on the statistical tests, 20 reference genes (10 traditional housekeeping genes and 10 novel genes) were selected. These genes were tested for the normalization of expression levels in five growth stages and three distinct plant organs of ginseng by qPCR. These genes were subsequently ranked and compared according to the stability of their expressions using geNorm, NormFinder, and BestKeeper computational programs. Although the best reference genes were found to vary across different samples, CYP and EF-1α were the most stable genes amongst all samples. GAPDH/30S RPS20, CYP/60S RPL13 and CYP/QCR were the optimum pair of reference genes in the roots, stems, and leaves. CYP/60S RPL13, CYP/eIF-5A, aTUB/V-ATP, eIF-5A/SAR1, and aTUB/pol IIa were the most stably expressed combinations in each of the five developmental stages. Our study serves as a foundation for developing an accurate method of qRT-PCR and will benefit future studies on gene expression profiles of Panax Ginseng.

Regulation of miRNA Processing and miRNA Mediated Gene Repression in Cancer

PubMed Central

Bajan, Sarah; Hutvagner, Gyorgy

2014-01-01

The majority of human protein-coding genes are predicted to be targets of miRNA-mediated post-transcriptional regulation. The widespread influence of miRNAs is illustrated by their essential roles in all biological processes. Regulated miRNA expression is essential for maintaining cellular differentiation; therefore alterations in miRNA expression patterns are associated with several diseases, including various cancers. High-throughput sequencing technologies revealed low level expressing miRNA isoforms, termed isomiRs. IsomiRs may differ in sequence, length, target preference and expression patterns from their parental miRNA and can arise from differences in miRNA biosynthesis, RNA editing, or SNPs inherent to the miRNA gene. The association between isomiR expression and disease progression is largely unknown. Misregulated miRNA expression is thought to contribute to the formation and/or progression of cancer. However, due to the diversity of targeted transcripts, miRNAs can function as both tumor-suppressor genes and oncogenes as defined by cellular context. Despite this, miRNA profiling studies concluded that the differential expression of particular miRNAs in diseased tissue could aid the diagnosis and treatment of some cancers. PMID:25069508

A High-throughput Assay for mRNA Silencing in Primary Cortical Neurons in vitro with Oligonucleotide Therapeutics.

PubMed

Alterman, Julia F; Coles, Andrew H; Hall, Lauren M; Aronin, Neil; Khvorova, Anastasia; Didiot, Marie-Cécile

2017-08-20

Primary neurons represent an ideal cellular system for the identification of therapeutic oligonucleotides for the treatment of neurodegenerative diseases. However, due to the sensitive nature of primary cells, the transfection of small interfering RNAs (siRNA) using classical methods is laborious and often shows low efficiency. Recent progress in oligonucleotide chemistry has enabled the development of stabilized and hydrophobically modified small interfering RNAs (hsiRNAs). This new class of oligonucleotide therapeutics shows extremely efficient self-delivery properties and supports potent and durable effects in vitro and in vivo . We have developed a high-throughput in vitro assay to identify and test hsiRNAs in primary neuronal cultures. To simply, rapidly, and accurately quantify the mRNA silencing of hundreds of hsiRNAs, we use the QuantiGene 2.0 quantitative gene expression assay. This high-throughput, 96-well plate-based assay can quantify mRNA levels directly from sample lysate. Here, we describe a method to prepare short-term cultures of mouse primary cortical neurons in a 96-well plate format for high-throughput testing of oligonucleotide therapeutics. This method supports the testing of hsiRNA libraries and the identification of potential therapeutics within just two weeks. We detail methodologies of our high throughput assay workflow from primary neuron preparation to data analysis. This method can help identify oligonucleotide therapeutics for treatment of various neurological diseases.

Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations

PubMed Central

Gurunathan, Rajalakshmi; Van Emden, Bernard; Panchanathan, Sethuraman; Kumar, Sudhir

2004-01-01

Background Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. Results The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. Conclusions We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns. PMID:15603586

Novel Inducers of Fetal Globin Identified through High Throughput Screening (HTS) Are Active In Vivo in Anemic Baboons and Transgenic Mice

PubMed Central

Boosalis, Michael S.; Sangerman, Jose I.; White, Gary L.; Wolf, Roman F.; Shen, Ling; Dai, Yan; White, Emily; Makala, Levi H.; Li, Biaoru; Pace, Betty S.; Nouraie, Mehdi; Faller, Douglas V.; Perrine, Susan P.

2015-01-01

High-level fetal (γ) globin expression ameliorates clinical severity of the beta (β) hemoglobinopathies, and safe, orally-bioavailable γ-globin inducing agents would benefit many patients. We adapted a LCR-γ-globin promoter-GFP reporter assay to a high-throughput robotic system to evaluate five diverse chemical libraries for this activity. Multiple structurally- and functionally-diverse compounds were identified which activate the γ-globin gene promoter at nanomolar concentrations, including some therapeutics approved for other conditions. Three candidates with established safety profiles were further evaluated in erythroid progenitors, anemic baboons and transgenic mice, with significant induction of γ-globin expression observed in vivo. A lead candidate, Benserazide, emerged which demonstrated > 20-fold induction of γ-globin mRNA expression in anemic baboons and increased F-cell proportions by 3.5-fold in transgenic mice. Benserazide has been used chronically to inhibit amino acid decarboxylase to enhance plasma levels of L-dopa. These studies confirm the utility of high-throughput screening and identify previously unrecognized fetal globin inducing candidates which can be developed expediently for treatment of hemoglobinopathies. PMID:26713848

Transcriptomic Profiling Analysis of Arabidopsis thaliana Treated with Exogenous Myo-Inositol

PubMed Central

Ye, Wenxing; Ren, Weibo; Kong, Lingqi; Zhang, Wanjun; Wang, Tao

2016-01-01

Myo-insositol (MI) is a crucial substance in the growth and developmental processes in plants. It is commonly added to the culture medium to promote adventitious shoot development. In our previous work, MI was found in influencing Agrobacterium-mediated transformation. In this report, a high-throughput RNA sequencing technique (RNA-Seq) was used to investigate differently expressed genes in one-month-old Arabidopsis seedling grown on MI free or MI supplemented culture medium. The results showed that 21,288 and 21,299 genes were detected with and without MI treatment, respectively. The detected genes included 184 new genes that were not annotated in the Arabidopsis thaliana reference genome. Additionally, 183 differentially expressed genes were identified (DEGs, FDR ≤0.05, log2 FC≥1), including 93 up-regulated genes and 90 down-regulated genes. The DEGs were involved in multiple pathways, such as cell wall biosynthesis, biotic and abiotic stress response, chromosome modification, and substrate transportation. Some significantly differently expressed genes provided us with valuable information for exploring the functions of exogenous MI. RNA-Seq results showed that exogenous MI could alter gene expression and signaling transduction in plant cells. These results provided a systematic understanding of the functions of exogenous MI in detail and provided a foundation for future studies. PMID:27603208

Gene coexpression measures in large heterogeneous samples using count statistics.

PubMed

Wang, Y X Rachel; Waterman, Michael S; Huang, Haiyan

2014-11-18

With the advent of high-throughput technologies making large-scale gene expression data readily available, developing appropriate computational tools to process these data and distill insights into systems biology has been an important part of the "big data" challenge. Gene coexpression is one of the earliest techniques developed that is still widely in use for functional annotation, pathway analysis, and, most importantly, the reconstruction of gene regulatory networks, based on gene expression data. However, most coexpression measures do not specifically account for local features in expression profiles. For example, it is very likely that the patterns of gene association may change or only exist in a subset of the samples, especially when the samples are pooled from a range of experiments. We propose two new gene coexpression statistics based on counting local patterns of gene expression ranks to take into account the potentially diverse nature of gene interactions. In particular, one of our statistics is designed for time-course data with local dependence structures, such as time series coupled over a subregion of the time domain. We provide asymptotic analysis of their distributions and power, and evaluate their performance against a wide range of existing coexpression measures on simulated and real data. Our new statistics are fast to compute, robust against outliers, and show comparable and often better general performance.

oPOSSUM-3: Advanced Analysis of Regulatory Motif Over-Representation Across Genes or ChIP-Seq Datasets

PubMed Central

Kwon, Andrew T.; Arenillas, David J.; Hunt, Rebecca Worsley; Wasserman, Wyeth W.

2012-01-01

oPOSSUM-3 is a web-accessible software system for identification of over-represented transcription factor binding sites (TFBS) and TFBS families in either DNA sequences of co-expressed genes or sequences generated from high-throughput methods, such as ChIP-Seq. Validation of the system with known sets of co-regulated genes and published ChIP-Seq data demonstrates the capacity for oPOSSUM-3 to identify mediating transcription factors (TF) for co-regulated genes or co-recovered sequences. oPOSSUM-3 is available at http://opossum.cisreg.ca. PMID:22973536

oPOSSUM-3: advanced analysis of regulatory motif over-representation across genes or ChIP-Seq datasets.

PubMed

Kwon, Andrew T; Arenillas, David J; Worsley Hunt, Rebecca; Wasserman, Wyeth W

2012-09-01

oPOSSUM-3 is a web-accessible software system for identification of over-represented transcription factor binding sites (TFBS) and TFBS families in either DNA sequences of co-expressed genes or sequences generated from high-throughput methods, such as ChIP-Seq. Validation of the system with known sets of co-regulated genes and published ChIP-Seq data demonstrates the capacity for oPOSSUM-3 to identify mediating transcription factors (TF) for co-regulated genes or co-recovered sequences. oPOSSUM-3 is available at http://opossum.cisreg.ca.

Fidelity and enhanced sensitivity of differential transcription profiles following linear amplification of nanogram amounts of endothelial mRNA

NASA Technical Reports Server (NTRS)

Polacek, Denise C.; Passerini, Anthony G.; Shi, Congzhu; Francesco, Nadeene M.; Manduchi, Elisabetta; Grant, Gregory R.; Powell, Steven; Bischof, Helen; Winkler, Hans; Stoeckert, Christian J Jr;

MultiSite Gateway-Compatible Cell Type-Specific Gene-Inducible System for Plants1[OPEN

PubMed Central

Siligato, Riccardo; Wang, Xin; Yadav, Shri Ram; Lehesranta, Satu; Ma, Guojie; Ursache, Robertas; Sevilem, Iris; Zhang, Jing; Gorte, Maartje; Prasad, Kalika; Heidstra, Renze

2016-01-01

A powerful method to study gene function is expression or overexpression in an inducible, cell type-specific system followed by observation of consequent phenotypic changes and visualization of linked reporters in the target tissue. Multiple inducible gene overexpression systems have been developed for plants, but very few of these combine plant selection markers, control of expression domains, access to multiple promoters and protein fusion reporters, chemical induction, and high-throughput cloning capabilities. Here, we introduce a MultiSite Gateway-compatible inducible system for Arabidopsis (Arabidopsis thaliana) plants that provides the capability to generate such constructs in a single cloning step. The system is based on the tightly controlled, estrogen-inducible XVE system. We demonstrate that the transformants generated with this system exhibit the expected cell type-specific expression, similar to what is observed with constitutively expressed native promoters. With this new system, cloning of inducible constructs is no longer limited to a few special cases but can be used as a standard approach when gene function is studied. In addition, we present a set of entry clones consisting of histochemical and fluorescent reporter variants designed for gene and promoter expression studies. PMID:26644504

A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data.

PubMed

Zhang, L; Liu, X J

2016-06-03

With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.

Hereditary mixed polyposis syndrome is caused by a 40-kb upstream duplication that leads to increased and ectopic expression of the BMP antagonist GREM1.

PubMed

Jaeger, Emma; Leedham, Simon; Lewis, Annabelle; Segditsas, Stefania; Becker, Martin; Cuadrado, Pedro Rodenas; Davis, Hayley; Kaur, Kulvinder; Heinimann, Karl; Howarth, Kimberley; East, James; Taylor, Jenny; Thomas, Huw; Tomlinson, Ian

2012-05-06

Hereditary mixed polyposis syndrome (HMPS) is characterized by apparent autosomal dominant inheritance of multiple types of colorectal polyp, with colorectal carcinoma occurring in a high proportion of affected individuals. Here, we use genetic mapping, copy-number analysis, exclusion of mutations by high-throughput sequencing, gene expression analysis and functional assays to show that HMPS is caused by a duplication spanning the 3' end of the SCG5 gene and a region upstream of the GREM1 locus. This unusual mutation is associated with increased allele-specific GREM1 expression. Whereas GREM1 is expressed in intestinal subepithelial myofibroblasts in controls, GREM1 is predominantly expressed in the epithelium of the large bowel in individuals with HMPS. The HMPS duplication contains predicted enhancer elements; some of these interact with the GREM1 promoter and can drive gene expression in vitro. Increased GREM1 expression is predicted to cause reduced bone morphogenetic protein (BMP) pathway activity, a mechanism that also underlies tumorigenesis in juvenile polyposis of the large bowel.

Predicting Response to Histone Deacetylase Inhibitors Using High-Throughput Genomics.

PubMed

Geeleher, Paul; Loboda, Andrey; Lenkala, Divya; Wang, Fan; LaCroix, Bonnie; Karovic, Sanja; Wang, Jacqueline; Nebozhyn, Michael; Chisamore, Michael; Hardwick, James; Maitland, Michael L; Huang, R Stephanie

2015-11-01

Many disparate biomarkers have been proposed as predictors of response to histone deacetylase inhibitors (HDI); however, all have failed when applied clinically. Rather than this being entirely an issue of reproducibility, response to the HDI vorinostat may be determined by the additive effect of multiple molecular factors, many of which have previously been demonstrated. We conducted a large-scale gene expression analysis using the Cancer Genome Project for discovery and generated another large independent cancer cell line dataset across different cancers for validation. We compared different approaches in terms of how accurately vorinostat response can be predicted on an independent out-of-batch set of samples and applied the polygenic marker prediction principles in a clinical trial. Using machine learning, the small effects that aggregate, resulting in sensitivity or resistance, can be recovered from gene expression data in a large panel of cancer cell lines.This approach can predict vorinostat response accurately, whereas single gene or pathway markers cannot. Our analyses recapitulated and contextualized many previous findings and suggest an important role for processes such as chromatin remodeling, autophagy, and apoptosis. As a proof of concept, we also discovered a novel causative role for CHD4, a helicase involved in the histone deacetylase complex that is associated with poor clinical outcome. As a clinical validation, we demonstrated that a common dose-limiting toxicity of vorinostat, thrombocytopenia, can be predicted (r = 0.55, P = .004) several days before it is detected clinically. Our work suggests a paradigm shift from single-gene/pathway evaluation to simultaneously evaluating multiple independent high-throughput gene expression datasets, which can be easily extended to other investigational compounds where similar issues are hampering clinical adoption. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis

PubMed Central

2013-01-01

Background Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions. Results We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/. Conclusions Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods. PMID:24373308

A high-throughput pipeline for the production of synthetic antibodies for analysis of ribonucleoprotein complexes

PubMed Central

Na, Hong; Laver, John D.; Jeon, Jouhyun; Singh, Fateh; Ancevicius, Kristin; Fan, Yujie; Cao, Wen Xi; Nie, Kun; Yang, Zhenglin; Luo, Hua; Wang, Miranda; Rissland, Olivia; Westwood, J. Timothy; Kim, Philip M.; Smibert, Craig A.; Lipshitz, Howard D.; Sidhu, Sachdev S.

2016-01-01

Post-transcriptional regulation of mRNAs plays an essential role in the control of gene expression. mRNAs are regulated in ribonucleoprotein (RNP) complexes by RNA-binding proteins (RBPs) along with associated protein and noncoding RNA (ncRNA) cofactors. A global understanding of post-transcriptional control in any cell type requires identification of the components of all of its RNP complexes. We have previously shown that these complexes can be purified by immunoprecipitation using anti-RBP synthetic antibodies produced by phage display. To develop the large number of synthetic antibodies required for a global analysis of RNP complex composition, we have established a pipeline that combines (i) a computationally aided strategy for design of antigens located outside of annotated domains, (ii) high-throughput antigen expression and purification in Escherichia coli, and (iii) high-throughput antibody selection and screening. Using this pipeline, we have produced 279 antibodies against 61 different protein components of Drosophila melanogaster RNPs. Together with those produced in our low-throughput efforts, we have a panel of 311 antibodies for 67 RNP complex proteins. Tests of a subset of our antibodies demonstrated that 89% immunoprecipitate their endogenous target from embryo lysate. This panel of antibodies will serve as a resource for global studies of RNP complexes in Drosophila. Furthermore, our high-throughput pipeline permits efficient production of synthetic antibodies against any large set of proteins. PMID:26847261

Transcriptome analysis by strand-specific sequencing of complementary DNA

PubMed Central

Parkhomchuk, Dmitri; Borodina, Tatiana; Amstislavskiy, Vyacheslav; Banaru, Maria; Hallen, Linda; Krobitsch, Sylvia; Lehrach, Hans; Soldatov, Alexey

2009-01-01

High-throughput complementary DNA sequencing (RNA-Seq) is a powerful tool for whole-transcriptome analysis, supplying information about a transcript's expression level and structure. However, it is difficult to determine the polarity of transcripts, and therefore identify which strand is transcribed. Here, we present a simple cDNA sequencing protocol that preserves information about a transcript's direction. Using Saccharomyces cerevisiae and mouse brain transcriptomes as models, we demonstrate that knowing the transcript's orientation allows more accurate determination of the structure and expression of genes. It also helps to identify new genes and enables studying promoter-associated and antisense transcription. The transcriptional landscapes we obtained are available online. PMID:19620212

Transcriptome analysis by strand-specific sequencing of complementary DNA.

PubMed

Parkhomchuk, Dmitri; Borodina, Tatiana; Amstislavskiy, Vyacheslav; Banaru, Maria; Hallen, Linda; Krobitsch, Sylvia; Lehrach, Hans; Soldatov, Alexey

2009-10-01

High-throughput complementary DNA sequencing (RNA-Seq) is a powerful tool for whole-transcriptome analysis, supplying information about a transcript's expression level and structure. However, it is difficult to determine the polarity of transcripts, and therefore identify which strand is transcribed. Here, we present a simple cDNA sequencing protocol that preserves information about a transcript's direction. Using Saccharomyces cerevisiae and mouse brain transcriptomes as models, we demonstrate that knowing the transcript's orientation allows more accurate determination of the structure and expression of genes. It also helps to identify new genes and enables studying promoter-associated and antisense transcription. The transcriptional landscapes we obtained are available online.

Metatranscriptomics of Soil Eukaryotic Communities.

PubMed

Yadav, Rajiv K; Bragalini, Claudia; Fraissinet-Tachet, Laurence; Marmeisse, Roland; Luis, Patricia

2016-01-01

Functions expressed by eukaryotic organisms in soil can be specifically studied by analyzing the pool of eukaryotic-specific polyadenylated mRNA directly extracted from environmental samples. In this chapter, we describe two alternative protocols for the extraction of high-quality RNA from soil samples. Total soil RNA or mRNA can be converted to cDNA for direct high-throughput sequencing. Polyadenylated mRNA-derived full-length cDNAs can also be cloned in expression plasmid vectors to constitute soil cDNA libraries, which can be subsequently screened for functional gene categories. Alternatively, the diversity of specific gene families can also be explored following cDNA sequence capture using exploratory oligonucleotide probes.

Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

PubMed Central

Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando

2008-01-01

Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433

Non-coding-regulatory regions of human brain genes delineated by bacterial artificial chromosome knock-in mice.

PubMed

Schmouth, Jean-François; Castellarin, Mauro; Laprise, Stéphanie; Banks, Kathleen G; Bonaguro, Russell J; McInerny, Simone C; Borretta, Lisa; Amirabbasi, Mahsa; Korecki, Andrea J; Portales-Casamar, Elodie; Wilson, Gary; Dreolini, Lisa; Jones, Steven J M; Wasserman, Wyeth W; Goldowitz, Daniel; Holt, Robert A; Simpson, Elizabeth M

2013-10-14

The next big challenge in human genetics is understanding the 98% of the genome that comprises non-coding DNA. Hidden in this DNA are sequences critical for gene regulation, and new experimental strategies are needed to understand the functional role of gene-regulation sequences in health and disease. In this study, we build upon our HuGX ('high-throughput human genes on the X chromosome') strategy to expand our understanding of human gene regulation in vivo. In all, ten human genes known to express in therapeutically important brain regions were chosen for study. For eight of these genes, human bacterial artificial chromosome clones were identified, retrofitted with a reporter, knocked single-copy into the Hprt locus in mouse embryonic stem cells, and mouse strains derived. Five of these human genes expressed in mouse, and all expressed in the adult brain region for which they were chosen. This defined the boundaries of the genomic DNA sufficient for brain expression, and refined our knowledge regarding the complexity of gene regulation. We also characterized for the first time the expression of human MAOA and NR2F2, two genes for which the mouse homologs have been extensively studied in the central nervous system (CNS), and AMOTL1 and NOV, for which roles in CNS have been unclear. We have demonstrated the use of the HuGX strategy to functionally delineate non-coding-regulatory regions of therapeutically important human brain genes. Our results also show that a careful investigation, using publicly available resources and bioinformatics, can lead to accurate predictions of gene expression.

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.

Identifying Environmental Chemicals as Agonists of the Androgen Receptor by Applying a Quantitative High-throughput Screening Platform

EPA Science Inventory

Background: The androgen receptor (AR, NR3C4) is a nuclear receptor whose main function is acting as a transcription factor regulating gene expression for male sexual development and maintaining accessory sexual organ function. It is also a necessary component of female fertility...

Genome-wide identification of microRNAs in pomegranate (Punica granatum L.) by high-throughput sequencing

USDA-ARS?s Scientific Manuscript database

Background: MicroRNAs (miRNAs), a class of small non-coding endogenous RNAs that regulate gene expression post-transcriptionally, play multiple key roles in plant growth and development and in biotic and abiotic stress response. Knowledge and roles of miRNAs in pomegranate fruit development have not...

Modeling Bi-modality Improves Characterization of Cell Cycle on Gene Expression in Single Cells

PubMed Central

Danaher, Patrick; Finak, Greg; Krouse, Michael; Wang, Alice; Webster, Philippa; Beechem, Joseph; Gottardo, Raphael

2014-01-01

Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%–17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome. PMID:25032992

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

Development of a High-Throughput Gene Expression Screen for Modulators of RAS-MAPK Signaling in a Mutant RAS Cellular Context.

PubMed

Severyn, Bryan; Nguyen, Thi; Altman, Michael D; Li, Lixia; Nagashima, Kumiko; Naumov, George N; Sathyanarayanan, Sriram; Cook, Erica; Morris, Erick; Ferrer, Marc; Arthur, Bill; Benita, Yair; Watters, Jim; Loboda, Andrey; Hermes, Jeff; Gilliland, D Gary; Cleary, Michelle A; Carroll, Pamela M; Strack, Peter; Tudor, Matt; Andersen, Jannik N

2016-10-01

The RAS-MAPK pathway controls many cellular programs, including cell proliferation, differentiation, and apoptosis. In colorectal cancers, recurrent mutations in this pathway often lead to increased cell signaling that may contribute to the development of neoplasms, thereby making this pathway attractive for therapeutic intervention. To this end, we developed a 26-member gene signature of RAS-MAPK pathway activity utilizing the Affymetrix QuantiGene Plex 2.0 reagent system and performed both primary and confirmatory gene expression-based high-throughput screens (GE-HTSs) using KRAS mutant colon cancer cells (SW837) and leveraging a highly annotated chemical library. The screen achieved a hit rate of 1.4% and was able to enrich for hit compounds that target RAS-MAPK pathway members such as MEK and EGFR. Sensitivity and selectivity performance measurements were 0.84 and 1.00, respectively, indicating high true-positive and true-negative rates. Active compounds from the primary screen were confirmed in a dose-response GE-HTS assay, a GE-HTS assay using 14 additional cancer cell lines, and an in vitro colony formation assay. Altogether, our data suggest that this GE-HTS assay will be useful for larger unbiased chemical screens to identify novel compounds and mechanisms that may modulate the RAS-MAPK pathway. © 2016 Society for Laboratory Automation and Screening.

Development of a high-throughput microfluidic integrated microarray for the detection of chimeric bioweapons.

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

Sheppod, Timothy; Satterfield, Brent; Hukari, Kyle W.

2006-10-01

The advancement of DNA cloning has significantly augmented the potential threat of a focused bioweapon assault, such as a terrorist attack. With current DNA cloning techniques, toxin genes from the most dangerous (but environmentally labile) bacterial or viral organism can now be selected and inserted into robust organism to produce an infinite number of deadly chimeric bioweapons. In order to neutralize such a threat, accurate detection of the expressed toxin genes, rather than classification on strain or genealogical decent of these organisms, is critical. The development of a high-throughput microarray approach will enable the detection of unknowns chimeric bioweapons. Themore » development of a high-throughput microarray approach will enable the detection of unknown bioweapons. We have developed a unique microfluidic approach to capture and concentrate these threat genes (mRNA's) upto a 30 fold concentration. These captured oligonucleotides can then be used to synthesize in situ oligonucleotide copies (cDNA probes) of the captured genes. An integrated microfluidic architecture will enable us to control flows of reagents, perform clean-up steps and finally elute nanoliter volumes of synthesized oligonucleotides probes. The integrated approach has enabled a process where chimeric or conventional bioweapons can rapidly be identified based on their toxic function, rather than being restricted to information that may not identify the critical nature of the threat.« less

A high-throughput screening system for barley/powdery mildew interactions based on automated analysis of light micrographs.

PubMed

Ihlow, Alexander; Schweizer, Patrick; Seiffert, Udo

2008-01-23

To find candidate genes that potentially influence the susceptibility or resistance of crop plants to powdery mildew fungi, an assay system based on transient-induced gene silencing (TIGS) as well as transient over-expression in single epidermal cells of barley has been developed. However, this system relies on quantitative microscopic analysis of the barley/powdery mildew interaction and will only become a high-throughput tool of phenomics upon automation of the most time-consuming steps. We have developed a high-throughput screening system based on a motorized microscope which evaluates the specimens fully automatically. A large-scale double-blind verification of the system showed an excellent agreement of manual and automated analysis and proved the system to work dependably. Furthermore, in a series of bombardment experiments an RNAi construct targeting the Mlo gene was included, which is expected to phenocopy resistance mediated by recessive loss-of-function alleles such as mlo5. In most cases, the automated analysis system recorded a shift towards resistance upon RNAi of Mlo, thus providing proof of concept for its usefulness in detecting gene-target effects. Besides saving labor and enabling a screening of thousands of candidate genes, this system offers continuous operation of expensive laboratory equipment and provides a less subjective analysis as well as a complete and enduring documentation of the experimental raw data in terms of digital images. In general, it proves the concept of enabling available microscope hardware to handle challenging screening tasks fully automatically.

Genome wide transcriptome profiling reveals differential gene expression in secondary metabolite pathway of Cymbopogon winterianus.

PubMed

Devi, Kamalakshi; Mishra, Surajit K; Sahu, Jagajjit; Panda, Debashis; Modi, Mahendra K; Sen, Priyabrata

2016-02-15

Advances in transcriptome sequencing provide fast, cost-effective and reliable approach to generate large expression datasets especially suitable for non-model species to identify putative genes, key pathway and regulatory mechanism. Citronella (Cymbopogon winterianus) is an aromatic medicinal grass used for anti-tumoral, antibacterial, anti-fungal, antiviral, detoxifying and natural insect repellent properties. Despite of having number of utilities, the genes involved in terpenes biosynthetic pathway is not yet clearly elucidated. The present study is a pioneering attempt to generate an exhaustive molecular information of secondary metabolite pathway and to increase genomic resources in Citronella. Using high-throughput RNA-Seq technology, root and leaf transcriptome was analysed at an unprecedented depth (11.7 Gb). Targeted searches identified majority of the genes associated with metabolic pathway and other natural product pathway viz. antibiotics synthesis along with many novel genes. Terpenoid biosynthesis genes comparative expression results were validated for 15 unigenes by RT-PCR and qRT-PCR. Thus the coverage of these transcriptome is comprehensive enough to discover all known genes of major metabolic pathways. This transcriptome dataset can serve as important public information for gene expression, genomics and function genomics studies in Citronella and shall act as a benchmark for future improvement of the crop.

Pervasive Effects of Aging on Gene Expression in Wild Wolves

PubMed Central

Charruau, Pauline; Johnston, Rachel A.; Stahler, Daniel R.; Lea, Amanda; Snyder-Mackler, Noah; Smith, Douglas W.; vonHoldt, Bridgett M.; Cole, Steven W.; Tung, Jenny; Wayne, Robert K.

2016-01-01

Abstract Gene expression levels change as an individual ages and responds to environmental conditions. With the exception of humans, such patterns have principally been studied under controlled conditions, overlooking the array of developmental and environmental influences that organisms encounter under conditions in which natural selection operates. We used high-throughput RNA sequencing (RNA-Seq) of whole blood to assess the relative impacts of social status, age, disease, and sex on gene expression levels in a natural population of gray wolves (Canis lupus). Our findings suggest that age is broadly associated with gene expression levels, whereas other examined factors have minimal effects on gene expression patterns. Further, our results reveal evolutionarily conserved signatures of senescence, such as immunosenescence and metabolic aging, between wolves and humans despite major differences in life history and environment. The effects of aging on gene expression levels in wolves exhibit conservation with humans, but the more rapid expression differences observed in aging wolves is evolutionarily appropriate given the species’ high level of extrinsic mortality due to intraspecific aggression. Some expression changes that occur with age can facilitate physical age-related changes that may enhance fitness in older wolves. However, the expression of these ancestral patterns of aging in descendant modern dogs living in highly modified domestic environments may be maladaptive and cause disease. This work provides evolutionary insight into aging patterns observed in domestic dogs and demonstrates the applicability of studying natural populations to investigate the mechanisms of aging. PMID:27189566

The changes of gene expression profiling between segmental vitiligo, generalized vitiligo and healthy individual.

PubMed

Wang, Ping; Li, Yong; Nie, Huiqiong; Zhang, Xiaoyan; Shao, Qiongyan; Hou, Xiuli; Xu, Wen; Hong, Weisong; Xu, Aie

2016-10-01

Vitiligo is a common acquired depigmentation skin disease characterized by loss or dysfunction of melanocytes within the skin lesion, but its pathologenesis is far from lucid. The gene expression profiling of segmental vitiligo (SV) and generalized vitiligo (GV) need further investigation. To better understanding the common and distinct factors, especially in the view of gene expression profile, which were involved in the diseases development and maintenance of segmental vitiligo (SV) and generalized vitiligo (GV). Peripheral bloods were collected from SV, GV and healthy individual (HI), followed by leukocytes separation and total RNA extraction. The high-throughput whole genome expression microarrays were used to assay the gene expression profiles between HI, SV and GV. Bioinformatics tools were employed to annotated the biological function of differently expressed genes. Quantitative PCR assay was used to validate the gene expression of array. Compared to HI, 239 over-expressed genes and 175 down-expressed genes detected in SV, 688 over-expressed genes and 560 down-expressed genes were found in GV, following the criteria of log2 (fold change)≥0.585 and P value<0.05. In these differently expressed genes, 60 over-expressed genes and 60 down-expressed genes had similar tendency in SV and GV. Compared to SV, 223 genes were up regulated and 129 genes were down regulated in GV. In the SV with HI as control, the differently expressed genes were mainly involved in the adaptive immune response, cytokine-cytokine receptor interaction, chemokine signaling, focal adhesion and sphingolipid metabolism. The differently expressed genes between GV and HI were mainly involved in the innate immune, autophagy, apoptosis, melanocyte biology, ubiquitin mediated proteolysis and tyrosine metabolism, which was different from SV. While the differently expressed genes between SV and GV were mainly involved in the metabolism pathway of purine, pyrimidine, glycolysis and sphingolipid. Above results suggested that they not only shared part bio-process and signal pathway, but more important, they utilized different biological mechanism in their pathogenesis and maintenance. Our results provide a comprehensive view on the gene expression profiling change between SV and GV especially in the side of leukocytes, and may facilitate the future study on their molecular mechanism and theraputic targets. Copyright © 2016 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.

Genomic Imprinting Was Evolutionarily Conserved during Wheat Polyploidization[OPEN

PubMed Central

Yang, Guanghui; Liu, Zhenshan; Gao, Lulu; Yu, Kuohai; Feng, Man; Peng, Huiru; Sun, Qixin; Ni, Zhongfu

2018-01-01

Genomic imprinting is an epigenetic phenomenon that causes genes to be differentially expressed depending on their parent of origin. To evaluate the evolutionary conservation of genomic imprinting and the effects of ploidy on this process, we investigated parent-of-origin-specific gene expression patterns in the endosperm of diploid (Aegilops spp), tetraploid, and hexaploid wheat (Triticum spp) at various stages of development via high-throughput transcriptome sequencing. We identified 91, 135, and 146 maternally or paternally expressed genes (MEGs or PEGs, respectively) in diploid, tetraploid, and hexaploid wheat, respectively, 52.7% of which exhibited dynamic expression patterns at different developmental stages. Gene Ontology enrichment analysis suggested that MEGs and PEGs were involved in metabolic processes and DNA-dependent transcription, respectively. Nearly half of the imprinted genes exhibited conserved expression patterns during wheat hexaploidization. In addition, 40% of the homoeolog pairs originating from whole-genome duplication were consistently maternally or paternally biased in the different subgenomes of hexaploid wheat. Furthermore, imprinted expression was found for 41.2% and 50.0% of homolog pairs that evolved by tandem duplication after genome duplication in tetraploid and hexaploid wheat, respectively. These results suggest that genomic imprinting was evolutionarily conserved between closely related Triticum and Aegilops species and in the face of polyploid hybridization between species in these genera. PMID:29298834

Complete Dosage Compensation and Sex-Biased Gene Expression in the Moth Manduca sexta

PubMed Central

Smith, Gilbert; Chen, Yun-Ru; Blissard, Gary W.; Briscoe, Adriana D.

2014-01-01

Sex chromosome dosage compensation balances homogametic sex chromosome expression with autosomal expression in the heterogametic sex, leading to sex chromosome expression parity between the sexes. If compensation is incomplete, this can lead to expression imbalance and sex-biased gene expression. Recent work has uncovered an intriguing and variable pattern of dosage compensation across species that includes a lack of complete dosage compensation in ZW species compared with XY species. This has led to the hypothesis that ZW species do not require complete compensation or that complete compensation would negatively affect their fitness. To date, only one study, a study of the moth Bombyx mori, has discovered evidence for complete dosage compensation in a ZW species. We examined another moth species, Manduca sexta, using high-throughput sequencing to survey gene expression in the head tissue of males and females. We found dosage compensation to be complete in M. sexta with average expression between the Z chromosome in males and females being equal. When genes expressed at very low levels are removed by filtering, we found that average autosome expression was highly similar to average Z expression, suggesting that the majority of genes in M. sexta are completely dosage compensated. Further, this compensation was accompanied by sex-specific gene expression associated with important sexually dimorphic traits. We suggest that complete dosage compensation in ZW species might be more common than previously appreciated and linked to additional selective processes, such as sexual selection. More ZW and lepidopteran species should now be examined in a phylogenetic framework, to understand the evolution of dosage compensation. PMID:24558255

Immuno-Navigator, a batch-corrected coexpression database, reveals cell type-specific gene networks in the immune system

PubMed Central

Vandenbon, Alexis; Dinh, Viet H.; Mikami, Norihisa; Kitagawa, Yohko; Teraguchi, Shunsuke; Ohkura, Naganari; Sakaguchi, Shimon

2016-01-01

High-throughput gene expression data are one of the primary resources for exploring complex intracellular dynamics in modern biology. The integration of large amounts of public data may allow us to examine general dynamical relationships between regulators and target genes. However, obstacles for such analyses are study-specific biases or batch effects in the original data. Here we present Immuno-Navigator, a batch-corrected gene expression and coexpression database for 24 cell types of the mouse immune system. We systematically removed batch effects from the underlying gene expression data and showed that this removal considerably improved the consistency between inferred correlations and prior knowledge. The data revealed widespread cell type-specific correlation of expression. Integrated analysis tools allow users to use this correlation of expression for the generation of hypotheses about biological networks and candidate regulators in specific cell types. We show several applications of Immuno-Navigator as examples. In one application we successfully predicted known regulators of importance in naturally occurring Treg cells from their expression correlation with a set of Treg-specific genes. For one high-scoring gene, integrin β8 (Itgb8), we confirmed an association between Itgb8 expression in forkhead box P3 (Foxp3)-positive T cells and Treg-specific epigenetic remodeling. Our results also suggest that the regulation of Treg-specific genes within Treg cells is relatively independent of Foxp3 expression, supporting recent results pointing to a Foxp3-independent component in the development of Treg cells. PMID:27078110

Cell-Free Optogenetic Gene Expression System.

PubMed

Jayaraman, Premkumar; Yeoh, Jing Wui; Jayaraman, Sudhaghar; Teh, Ai Ying; Zhang, Jingyun; Poh, Chueh Loo

2018-04-20

Optogenetic tools provide a new and efficient way to dynamically program gene expression with unmatched spatiotemporal precision. To date, their vast potential remains untapped in the field of cell-free synthetic biology, largely due to the lack of simple and efficient light-switchable systems. Here, to bridge the gap between cell-free systems and optogenetics, we studied our previously engineered one component-based blue light-inducible Escherichia coli promoter in a cell-free environment through experimental characterization and mathematical modeling. We achieved >10-fold dynamic expression and demonstrated rapid and reversible activation of the target gene to generate oscillatory response. The deterministic model developed was able to recapitulate the system behavior and helped to provide quantitative insights to optimize dynamic response. This in vitro optogenetic approach could be a powerful new high-throughput screening technology for rapid prototyping of complex biological networks in both space and time without the need for chemical induction.

High-throughput full-length single-cell mRNA-seq of rare cells.

PubMed

Ooi, Chin Chun; Mantalas, Gary L; Koh, Winston; Neff, Norma F; Fuchigami, Teruaki; Wong, Dawson J; Wilson, Robert J; Park, Seung-Min; Gambhir, Sanjiv S; Quake, Stephen R; Wang, Shan X

2017-01-01

Single-cell characterization techniques, such as mRNA-seq, have been applied to a diverse range of applications in cancer biology, yielding great insight into mechanisms leading to therapy resistance and tumor clonality. While single-cell techniques can yield a wealth of information, a common bottleneck is the lack of throughput, with many current processing methods being limited to the analysis of small volumes of single cell suspensions with cell densities on the order of 107 per mL. In this work, we present a high-throughput full-length mRNA-seq protocol incorporating a magnetic sifter and magnetic nanoparticle-antibody conjugates for rare cell enrichment, and Smart-seq2 chemistry for sequencing. We evaluate the efficiency and quality of this protocol with a simulated circulating tumor cell system, whereby non-small-cell lung cancer cell lines (NCI-H1650 and NCI-H1975) are spiked into whole blood, before being enriched for single-cell mRNA-seq by EpCAM-functionalized magnetic nanoparticles and the magnetic sifter. We obtain high efficiency (> 90%) capture and release of these simulated rare cells via the magnetic sifter, with reproducible transcriptome data. In addition, while mRNA-seq data is typically only used for gene expression analysis of transcriptomic data, we demonstrate the use of full-length mRNA-seq chemistries like Smart-seq2 to facilitate variant analysis of expressed genes. This enables the use of mRNA-seq data for differentiating cells in a heterogeneous population by both their phenotypic and variant profile. In a simulated heterogeneous mixture of circulating tumor cells in whole blood, we utilize this high-throughput protocol to differentiate these heterogeneous cells by both their phenotype (lung cancer versus white blood cells), and mutational profile (H1650 versus H1975 cells), in a single sequencing run. This high-throughput method can help facilitate single-cell analysis of rare cell populations, such as circulating tumor or endothelial cells, with demonstrably high-quality transcriptomic data.

Screening and identification of gastric adenocarcinoma metastasis-related genes by using cDNA microarray coupled to FDD-PCR.

PubMed

Wang, Jian-Hua; Chen, Shi-Shu

2002-07-01

To clone gastric adenocarcinoma metastasis related genes, RF-1 cell line (primary tumor of a gastric adenocarcinoma patient ) and RF-48 cell line (its metastatic counterpart) were used as a model for studying the molecular mechanism of tumor metastasis. Two fluorescent cDNA probes, labeled with Cy3 and Cy5 dyes, were prepared from RF-1 and RF-48 mRNA samples by reverse transcription method. The two color probes were then mixed and hybridized to the cDNA chip constructed by double-dots of 4 096 human genes, and scanned at two wavelengths. The experiment was repeated for 2 times. Differential expression genes from the above two cells were analyzed using the computer. 138 in all genes (3.4%) revealed differential expression in RF-48 cells compared with RF-1 cells: 81(2.1%) genes revealed apparent up-regulation, and 56(1.3%) genes revealed down-regulation. 45 genes involved in gastric adenocarcinoma metastasis were cloned using fluorescent differential display-PCR (FDD-PCR), including 3 novel genes. There were 7 differential expression genes that agreed with each other in two detection methods. The possible roles of some differential expressed genes, which maybe involved in the mechanism of tumor metastasis, were discussed. cDNA chip was used to analyze gene expression in a high-throughput and large scale manner, in combination with FDD-PCR for cloning unknown novel genes. In conclusion, some genes related to metastasis were preliminarily scanned, which would contribute to disclose the molecular mechanism of gastric adenocarcinoma metastasis.

APG: an Active Protein-Gene network model to quantify regulatory signals in complex biological systems.

PubMed

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information.

APG: an Active Protein-Gene Network Model to Quantify Regulatory Signals in Complex Biological Systems

PubMed Central

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information. PMID:23346354

High-throughput multiplex HLA-typing by ligase detection reaction (LDR) and universal array (UA) approach.

PubMed

Consolandi, Clarissa

2009-01-01

One major goal of genetic research is to understand the role of genetic variation in living systems. In humans, by far the most common type of such variation involves differences in single DNA nucleotides, and is thus termed single nucleotide polymorphism (SNP). The need for improvement in throughput and reliability of traditional techniques makes it necessary to develop new technologies. Thus the past few years have witnessed an extraordinary surge of interest in DNA microarray technology. This new technology offers the first great hope for providing a systematic way to explore the genome. It permits a very rapid analysis of thousands genes for the purpose of gene discovery, sequencing, mapping, expression, and polymorphism detection. We generated a series of analytical tools to address the manufacturing, detection and data analysis components of a microarray experiment. In particular, we set up a universal array approach in combination with a PCR-LDR (polymerase chain reaction-ligation detection reaction) strategy for allele identification in the HLA gene.

CRISPR-enabled tools for engineering microbial genomes and phenotypes.

PubMed

Tarasava, Katia; Oh, Eun Joong; Eckert, Carrie A; Gill, Ryan T

2018-06-19

In recent years CRISPR-Cas technologies have revolutionized microbial engineering approaches. Genome editing and non-editing applications of various CRISPR-Cas systems have expanded the throughput and scale of engineering efforts, as well as opened up new avenues for manipulating genomes of non-model organisms. As we expand the range of organisms used for biotechnological applications, we need to develop better, more versatile tools for manipulation of these systems. Here we summarize the current advances in microbial gene editing using CRISPR-Cas based tools, and highlight state-of-the-art methods for high-throughput, efficient genome-scale engineering in model organisms Escherichia coli and Saccharomyces cerevisiae. We also review non-editing CRISPR-Cas applications available for gene expression manipulation, epigenetic remodeling, RNA editing, labeling and synthetic gene circuit design. Finally, we point out the areas of research that need further development in order to expand the range of applications and increase the utility of these new methods. This article is protected by copyright. All rights reserved.

Identification of miRNAs Involved in Stolon Formation in Tulipa edulis by High-Throughput Sequencing

PubMed Central

Zhu, Zaibiao; Miao, Yuanyuan; Guo, Qiaosheng; Zhu, Yunhao; Yang, Xiaohua; Sun, Yuan

2016-01-01

MicroRNAs (miRNAs) are a class of endogenous, non-coding small RNAs that play an important role in transcriptional and post-transcriptional gene regulation. However, the sequence information and functions of miRNAs are still unexplored in Tulipa edulis. In this study, high-throughput sequencing was used to identify small RNAs in stolon formation stages (stage 1, 2, and 3) in T. edulis. A total of 12,890,912, 12,182,122, and 12,061,434 clean reads were obtained from stage 1, 2, and 3, respectively. Among the reads, 88 conserved miRNAs and 70 novel miRNAs were identified. Target prediction of 122 miRNAs resulted in 531 potential target genes. Nr, Swiss-Prot, GO, COG, and KEGG annotations revealed that these target genes participate in many biologic and metabolic processes. Moreover, qRT-PCR was performed to analyze the expression levels of the miRNAs and target genes in stolon formation. The results revealed that miRNAs play a key role in T. edulis stolon formation. PMID:27446103

Identification of miRNAs Involved in Stolon Formation in Tulipa edulis by High-Throughput Sequencing.

PubMed

Zhu, Zaibiao; Miao, Yuanyuan; Guo, Qiaosheng; Zhu, Yunhao; Yang, Xiaohua; Sun, Yuan

2016-01-01

MicroRNAs (miRNAs) are a class of endogenous, non-coding small RNAs that play an important role in transcriptional and post-transcriptional gene regulation. However, the sequence information and functions of miRNAs are still unexplored in Tulipa edulis. In this study, high-throughput sequencing was used to identify small RNAs in stolon formation stages (stage 1, 2, and 3) in T. edulis. A total of 12,890,912, 12,182,122, and 12,061,434 clean reads were obtained from stage 1, 2, and 3, respectively. Among the reads, 88 conserved miRNAs and 70 novel miRNAs were identified. Target prediction of 122 miRNAs resulted in 531 potential target genes. Nr, Swiss-Prot, GO, COG, and KEGG annotations revealed that these target genes participate in many biologic and metabolic processes. Moreover, qRT-PCR was performed to analyze the expression levels of the miRNAs and target genes in stolon formation. The results revealed that miRNAs play a key role in T. edulis stolon formation.

BubbleGUM: automatic extraction of phenotype molecular signatures and comprehensive visualization of multiple Gene Set Enrichment Analyses.

PubMed

Spinelli, Lionel; Carpentier, Sabrina; Montañana Sanchis, Frédéric; Dalod, Marc; Vu Manh, Thien-Phong

2015-10-19

Recent advances in the analysis of high-throughput expression data have led to the development of tools that scaled-up their focus from single-gene to gene set level. For example, the popular Gene Set Enrichment Analysis (GSEA) algorithm can detect moderate but coordinated expression changes of groups of presumably related genes between pairs of experimental conditions. This considerably improves extraction of information from high-throughput gene expression data. However, although many gene sets covering a large panel of biological fields are available in public databases, the ability to generate home-made gene sets relevant to one's biological question is crucial but remains a substantial challenge to most biologists lacking statistic or bioinformatic expertise. This is all the more the case when attempting to define a gene set specific of one condition compared to many other ones. Thus, there is a crucial need for an easy-to-use software for generation of relevant home-made gene sets from complex datasets, their use in GSEA, and the correction of the results when applied to multiple comparisons of many experimental conditions. We developed BubbleGUM (GSEA Unlimited Map), a tool that allows to automatically extract molecular signatures from transcriptomic data and perform exhaustive GSEA with multiple testing correction. One original feature of BubbleGUM notably resides in its capacity to integrate and compare numerous GSEA results into an easy-to-grasp graphical representation. We applied our method to generate transcriptomic fingerprints for murine cell types and to assess their enrichments in human cell types. This analysis allowed us to confirm homologies between mouse and human immunocytes. BubbleGUM is an open-source software that allows to automatically generate molecular signatures out of complex expression datasets and to assess directly their enrichment by GSEA on independent datasets. Enrichments are displayed in a graphical output that helps interpreting the results. This innovative methodology has recently been used to answer important questions in functional genomics, such as the degree of similarities between microarray datasets from different laboratories or with different experimental models or clinical cohorts. BubbleGUM is executable through an intuitive interface so that both bioinformaticians and biologists can use it. It is available at http://www.ciml.univ-mrs.fr/applications/BubbleGUM/index.html .

A Machine Learned Classifier That Uses Gene Expression Data to Accurately Predict Estrogen Receptor Status

PubMed Central

Bastani, Meysam; Vos, Larissa; Asgarian, Nasimeh; Deschenes, Jean; Graham, Kathryn; Mackey, John; Greiner, Russell

2013-01-01

Background Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER) status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. Methods To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. Results This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. Conclusions Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions. PMID:24312637

Global Screening of Antiviral Genes that Suppress Baculovirus Transgene Expression in Mammalian Cells.

PubMed

Wang, Chia-Hung; Naik, Nenavath Gopal; Liao, Lin-Li; Wei, Sung-Chan; Chao, Yu-Chan

2017-09-15

Although baculovirus has been used as a safe and convenient gene delivery vector in mammalian cells, baculovirus-mediated transgene expression is less effective in various mammalian cell lines. Identification of the negative regulators in host cells is necessary to improve baculovirus-based expression systems. Here, we performed high-throughput shRNA library screening, targeting 176 antiviral innate immune genes, and identified 43 host restriction factor genes in a human A549 lung carcinoma cell line. Among them, suppression of receptor interaction protein kinase 1 (RIP1, also known as RIPK1) significantly increased baculoviral transgene expression without resulting in significant cell death. Silencing of RIP1 did not affect viral entry or cell viability, but it did inhibit nuclear translocation of the IRF3 and NF-κB transcription factors. Also, activation of downstream signaling mediators (such as TBK1 and IRF7) was affected, and subsequent interferon and cytokine gene expression levels were abolished. Further, Necrostatin-1 (Nec-1)-an inhibitor of RIP1 kinase activity-dramatically increased baculoviral transgene expression in RIP1-silenced cells. Using baculovirus as a model system, this study presents an initial investigation of large numbers of human cell antiviral innate immune response factors against a "nonadaptive virus." In addition, our study has made baculovirus a more efficient gene transfer vector for some of the most frequently used mammalian cell systems.

Induction of anti-aging gene klotho with a small chemical compound that demethylates CpG islands

PubMed Central

Jung, Dongju; Xu, Yuechi; Sun, Zhongjie

2017-01-01

Klotho (KL) is described as an anti-aging gene because mutation of Kl gene leads to multiple pre-mature aging phenotypes and shortens lifespan in mice. Growing evidence suggests that an increase in KL expression may be beneficial for age-related diseases such as arteriosclerosis and diabetes. It remains largely unknown, however, how Kl expression could be induced. Here we discovered novel molecular mechanism for induction of Kl expression with a small molecule ‘Compound H’, N-(2-chlorophenyl)-1H-indole-3-caboxamide. Compound H was originally identified through a high-throughput screening of small molecules for identifying Kl inducers. However, how Compound H induces Kl expression has never been investigated. We found that Compound H increased Kl expression via demethylation in CpG islands of the Kl gene. The demethylation was accomplished by activating demethylases rather than inhibiting methylases. Due to demethylation, Compound H enhanced binding of transcription factors, Pax4 and Kid3, to the promoter of the Kl gene. Pax4 and Kid3 regulated Kl promoter activity positively and negatively, respectively. Thus, our results show that demethylation is an important molecular mechanism that mediates Compound H-induced Kl expression. Further investigation is warranted to determine whether Compound H demethylates the Kl gene in vivo and whether it can serve as a therapeutic agent for repressing or delaying the onset of age-related diseases. PMID:28657902

Comparison of Leaf Sheath Transcriptome Profiles with Physiological Traits of Bread Wheat Cultivars under Salinity Stress

PubMed Central

Trittermann, Christine; Berger, Bettina; Roy, Stuart J.; Seki, Motoaki; Shinozaki, Kazuo; Tester, Mark

2015-01-01

Salinity stress has significant negative effects on plant biomass production and crop yield. Salinity tolerance is controlled by complex systems of gene expression and ion transport. The relationship between specific features of mild salinity stress adaptation and gene expression was analyzed using four commercial varieties of bread wheat (Triticum aestivum) that have different levels of salinity tolerance. The high-throughput phenotyping system in The Plant Accelerator at the Australian Plant Phenomics Facility revealed variation in shoot relative growth rate and salinity tolerance among the four cultivars. Comparative analysis of gene expression in the leaf sheaths identified genes whose functions are potentially linked to shoot biomass development and salinity tolerance. Early responses to mild salinity stress through changes in gene expression have an influence on the acquisition of stress tolerance and improvement in biomass accumulation during the early “osmotic” phase of salinity stress. In addition, results revealed transcript profiles for the wheat cultivars that were different from those of usual stress-inducible genes, but were related to those of plant growth. These findings suggest that, in the process of breeding, selection of specific traits with various salinity stress-inducible genes in commercial bread wheat has led to adaptation to mild salinity conditions. PMID:26244554

Transcriptomics of mRNA and egg quality in farmed fish: Some recent developments and future directions.

PubMed

Sullivan, Craig V; Chapman, Robert W; Reading, Benjamin J; Anderson, Paul E

2015-09-15

Maternal mRNA transcripts deposited in growing oocytes regulate early development and are under intensive investigation as determinants of egg quality. The research has evolved from single gene studies to microarray and now RNA-Seq analyses in which mRNA expression by virtually every gene can be assessed and related to gamete quality. Such studies have mainly focused on genes changing two- to several-fold in expression between biological states, and have identified scores of candidate genes and a few gene networks whose functioning is related to successful development. However, ever-increasing yields of information from high throughput methods for detecting transcript abundance have far outpaced progress in methods for analyzing the massive quantities of gene expression data, and especially for meaningful relation of whole transcriptome profiles to gamete quality. We have developed a new approach to this problem employing artificial neural networks and supervised machine learning with other novel bioinformatics procedures to discover a previously unknown level of ovarian transcriptome function at which minute changes in expression of a few hundred genes is highly predictive of egg quality. In this paper, we briefly review the progress in transcriptomics of fish egg quality and discuss some future directions for this field of study. Copyright © 2015 Elsevier Inc. All rights reserved.

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

A High-Throughput Data Mining of Single Nucleotide Polymorphisms in Coffea Species Expressed Sequence Tags Suggests Differential Homeologous Gene Expression in the Allotetraploid Coffea arabica1[W

PubMed Central

Vidal, Ramon Oliveira; Mondego, Jorge Maurício Costa; Pot, David; Ambrósio, Alinne Batista; Andrade, Alan Carvalho; Pereira, Luiz Filipe Protasio; Colombo, Carlos Augusto; Vieira, Luiz Gonzaga Esteves; Carazzolle, Marcelo Falsarella; Pereira, Gonçalo Amarante Guimarães

2010-01-01

Polyploidization constitutes a common mode of evolution in flowering plants. This event provides the raw material for the divergence of function in homeologous genes, leading to phenotypic novelty that can contribute to the success of polyploids in nature or their selection for use in agriculture. Mounting evidence underlined the existence of homeologous expression biases in polyploid genomes; however, strategies to analyze such transcriptome regulation remained scarce. Important factors regarding homeologous expression biases remain to be explored, such as whether this phenomenon influences specific genes, how paralogs are affected by genome doubling, and what is the importance of the variability of homeologous expression bias to genotype differences. This study reports the expressed sequence tag assembly of the allopolyploid Coffea arabica and one of its direct ancestors, Coffea canephora. The assembly was used for the discovery of single nucleotide polymorphisms through the identification of high-quality discrepancies in overlapped expressed sequence tags and for gene expression information indirectly estimated by the transcript redundancy. Sequence diversity profiles were evaluated within C. arabica (Ca) and C. canephora (Cc) and used to deduce the transcript contribution of the Coffea eugenioides (Ce) ancestor. The assignment of the C. arabica haplotypes to the C. canephora (CaCc) or C. eugenioides (CaCe) ancestral genomes allowed us to analyze gene expression contributions of each subgenome in C. arabica. In silico data were validated by the quantitative polymerase chain reaction and allele-specific combination TaqMAMA-based method. The presence of differential expression of C. arabica homeologous genes and its implications in coffee gene expression, ontology, and physiology are discussed. PMID:20864545

Defining the Human Macula Transcriptome and Candidate Retinal Disease Genes UsingEyeSAGE

PubMed Central

Rickman, Catherine Bowes; Ebright, Jessica N.; Zavodni, Zachary J.; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P.; Wistow, Graeme; Boon, Kathy; Hauser, Michael A.

2009-01-01

Purpose To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Methods Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Results Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. Conclusions The EyeSAGE database, combining three different gene-profiling platforms including the authors’ multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions. PMID:16723438

Defining the human macula transcriptome and candidate retinal disease genes using EyeSAGE.

PubMed

Bowes Rickman, Catherine; Ebright, Jessica N; Zavodni, Zachary J; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P; Wistow, Graeme; Boon, Kathy; Hauser, Michael A

2006-06-01

To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. The EyeSAGE database, combining three different gene-profiling platforms including the authors' multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions.

Genome-wide identification, phylogeny and expression analyses of SCARECROW-LIKE(SCL) genes in millet (Setaria italica).

PubMed

Liu, Hongyun; Qin, Jiajia; Fan, Hui; Cheng, Jinjin; Li, Lin; Liu, Zheng

2017-07-01

As a member of the GRAS gene family, SCARECROW - LIKE ( SCL ) genes encode transcriptional regulators that are involved in plant information transmission and signal transduction. In this study, 44 SCL genes including two SCARECROW genes in millet were identified to be distributed on eight chromosomes, except chromosome 6. All the millet genes contain motifs 6-8, indicating that these motifs are conserved during the evolution. SCL genes of millet were divided into eight groups based on the phylogenetic relationship and classification of Arabidopsis SCL genes. Several putative millet orthologous genes in Arabidopsis , maize and rice were identified. High throughput RNA sequencing revealed that the expressions of millet SCL genes in root, stem, leaf, spica, and along leaf gradient varied greatly. Analyses combining the gene expression patterns, gene structures, motif compositions, promoter cis -elements identification, alternative splicing of transcripts and phylogenetic relationship of SCL genes indicate that the these genes may play diverse functions. Functionally characterized SCL genes in maize, rice and Arabidopsis would provide us some clues for future characterization of their homologues in millet. To the best of our knowledge, this is the first study of millet SCL genes at the genome wide level. Our work provides a useful platform for functional analysis of SCL genes in millet, a model crop for C 4 photosynthesis and bioenergy studies.

Gene expression and splicing alterations analyzed by high throughput RNA sequencing of chronic lymphocytic leukemia specimens.

PubMed

Liao, Wei; Jordaan, Gwen; Nham, Phillipp; Phan, Ryan T; Pelegrini, Matteo; Sharma, Sanjai

2015-10-16

To determine differentially expressed and spliced RNA transcripts in chronic lymphocytic leukemia specimens a high throughput RNA-sequencing (HTS RNA-seq) analysis was performed. Ten CLL specimens and five normal peripheral blood CD19+ B cells were analyzed by HTS RNA-seq. The library preparation was performed with Illumina TrueSeq RNA kit and analyzed by Illumina HiSeq 2000 sequencing system. An average of 48.5 million reads for B cells, and 50.6 million reads for CLL specimens were obtained with 10396 and 10448 assembled transcripts for normal B cells and primary CLL specimens respectively. With the Cuffdiff analysis, 2091 differentially expressed genes (DEG) between B cells and CLL specimens based on FPKM (fragments per kilobase of transcript per million reads and false discovery rate, FDR q < 0.05, fold change >2) were identified. Expression of selected DEGs (n = 32) with up regulated and down regulated expression in CLL from RNA-seq data were also analyzed by qRT-PCR in a test cohort of CLL specimens. Even though there was a variation in fold expression of DEG genes between RNA-seq and qRT-PCR; more than 90 % of analyzed genes were validated by qRT-PCR analysis. Analysis of RNA-seq data for splicing alterations in CLL and B cells was performed by Multivariate Analysis of Transcript Splicing (MATS analysis). Skipped exon was the most frequent splicing alteration in CLL specimens with 128 significant events (P-value <0.05, minimum inclusion level difference >0.1). The RNA-seq analysis of CLL specimens identifies novel DEG and alternatively spliced genes that are potential prognostic markers and therapeutic targets. High level of validation by qRT-PCR for a number of DEG genes supports the accuracy of this analysis. Global comparison of transcriptomes of B cells, IGVH non-mutated CLL (U-CLL) and mutated CLL specimens (M-CLL) with multidimensional scaling analysis was able to segregate CLL and B cell transcriptomes but the M-CLL and U-CLL transcriptomes were indistinguishable. The analysis of HTS RNA-seq data to identify alternative splicing events and other genetic abnormalities specific to CLL is an added advantage of RNA-seq that is not feasible with other genome wide analysis.

The Spatial and Temporal Transcriptomic Landscapes of Ginseng, Panax ginseng C. A. Meyer.

PubMed

Wang, Kangyu; Jiang, Shicui; Sun, Chunyu; Lin, Yanping; Yin, Rui; Wang, Yi; Zhang, Meiping

2015-12-11

Ginseng, including Asian ginseng (Panax ginseng C. A. Meyer) and American ginseng (P. quinquefolius L.), is one of the most important medicinal herbs in Asia and North America, but significantly understudied. This study sequenced and characterized the transcriptomes and expression profiles of genes expressed in 14 tissues and four different aged roots of Asian ginseng. A total of 265.2 million 100-bp clean reads were generated using the high-throughput sequencing platform HiSeq 2000, representing >8.3x of the 3.2-Gb ginseng genome. From the sequences, 248,993 unigenes were assembled for whole plant, 61,912-113,456 unigenes for each tissue and 54,444-65,412 unigenes for different year-old roots. We comprehensively analyzed the unigene sets and gene expression profiles. We found that the number of genes allocated to each functional category is stable across tissues or developmental stages, while the expression profiles of different genes of a gene family or involved in ginsenoside biosynthesis dramatically diversified spatially and temporally. These results provide an overall insight into the spatial and temporal transcriptome dynamics and landscapes of Asian ginseng, and comprehensive resources for advanced research and breeding of ginseng and related species.

Development of a Universal RNA Beacon for Exogenous Gene Detection

PubMed Central

Guo, Yuanjian; Lu, Zhongju; Cohen, Ira Stephen

2015-01-01

Stem cell therapy requires a nontoxic and high-throughput method to achieve a pure cell population to prevent teratomas that can occur if even one cell in the implant has not been transformed. A promising method to detect and separate cells expressing a particular gene is RNA beacon technology. However, developing a successful, specific beacon to a particular transfected gene can take months to develop and in some cases is impossible. Here, we report on an off-the-shelf universal beacon that decreases the time and cost of applying beacon technology to select any living cell population transfected with an exogenous gene. PMID:25769653

Development of a universal RNA beacon for exogenous gene detection.

PubMed

Guo, Yuanjian; Lu, Zhongju; Cohen, Ira Stephen; Scarlata, Suzanne

2015-05-01

Stem cell therapy requires a nontoxic and high-throughput method to achieve a pure cell population to prevent teratomas that can occur if even one cell in the implant has not been transformed. A promising method to detect and separate cells expressing a particular gene is RNA beacon technology. However, developing a successful, specific beacon to a particular transfected gene can take months to develop and in some cases is impossible. Here, we report on an off-the-shelf universal beacon that decreases the time and cost of applying beacon technology to select any living cell population transfected with an exogenous gene. ©AlphaMed Press.

Gene Expression Profile Change and Associated Physiological and Pathological Effects in Mouse Liver Induced by Fasting and Refeeding

PubMed Central

Zhang, Fang; Xu, Xiang; Zhou, Ben; He, Zhishui; Zhai, Qiwei

2011-01-01

Food availability regulates basal metabolism and progression of many diseases, and liver plays an important role in these processes. The effects of food availability on digital gene expression profile, physiological and pathological functions in liver are yet to be further elucidated. In this study, we applied high-throughput sequencing technology to detect digital gene expression profile of mouse liver in fed, fasted and refed states. Totally 12162 genes were detected, and 2305 genes were significantly regulated by food availability. Biological process and pathway analysis showed that fasting mainly affected lipid and carboxylic acid metabolic processes in liver. Moreover, the genes regulated by fasting and refeeding in liver were mainly enriched in lipid metabolic process or fatty acid metabolism. Network analysis demonstrated that fasting mainly regulated Drug Metabolism, Small Molecule Biochemistry and Endocrine System Development and Function, and the networks including Lipid Metabolism, Small Molecule Biochemistry and Gene Expression were affected by refeeding. In addition, FunDo analysis showed that liver cancer and diabetes mellitus were most likely to be affected by food availability. This study provides the digital gene expression profile of mouse liver regulated by food availability, and demonstrates the main biological processes, pathways, gene networks and potential hepatic diseases regulated by fasting and refeeding. These results show that food availability mainly regulates hepatic lipid metabolism and is highly correlated with liver-related diseases including liver cancer and diabetes. PMID:22096593

Gene expression profile change and associated physiological and pathological effects in mouse liver induced by fasting and refeeding.

PubMed

Zhang, Fang; Xu, Xiang; Zhou, Ben; He, Zhishui; Zhai, Qiwei

2011-01-01

Food availability regulates basal metabolism and progression of many diseases, and liver plays an important role in these processes. The effects of food availability on digital gene expression profile, physiological and pathological functions in liver are yet to be further elucidated. In this study, we applied high-throughput sequencing technology to detect digital gene expression profile of mouse liver in fed, fasted and refed states. Totally 12162 genes were detected, and 2305 genes were significantly regulated by food availability. Biological process and pathway analysis showed that fasting mainly affected lipid and carboxylic acid metabolic processes in liver. Moreover, the genes regulated by fasting and refeeding in liver were mainly enriched in lipid metabolic process or fatty acid metabolism. Network analysis demonstrated that fasting mainly regulated Drug Metabolism, Small Molecule Biochemistry and Endocrine System Development and Function, and the networks including Lipid Metabolism, Small Molecule Biochemistry and Gene Expression were affected by refeeding. In addition, FunDo analysis showed that liver cancer and diabetes mellitus were most likely to be affected by food availability. This study provides the digital gene expression profile of mouse liver regulated by food availability, and demonstrates the main biological processes, pathways, gene networks and potential hepatic diseases regulated by fasting and refeeding. These results show that food availability mainly regulates hepatic lipid metabolism and is highly correlated with liver-related diseases including liver cancer and diabetes.

Quantifying whole transcriptome size, a prerequisite for understanding transcriptome evolution across species: an example from a plant allopolyploid.

PubMed

Coate, Jeremy E; Doyle, Jeff J

2010-01-01

Evolutionary biologists are increasingly comparing gene expression patterns across species. Due to the way in which expression assays are normalized, such studies provide no direct information about expression per gene copy (dosage responses) or per cell and can give a misleading picture of genes that are differentially expressed. We describe an assay for estimating relative expression per cell. When used in conjunction with transcript profiling data, it is possible to compare the sizes of whole transcriptomes, which in turn makes it possible to compare expression per cell for each gene in the transcript profiling data set. We applied this approach, using quantitative reverse transcriptase-polymerase chain reaction and high throughput RNA sequencing, to a recently formed allopolyploid and showed that its leaf transcriptome was approximately 1.4-fold larger than either progenitor transcriptome (70% of the sum of the progenitor transcriptomes). In contrast, the allopolyploid genome is 94.3% as large as the sum of its progenitor genomes and retains > or =93.5% of the sum of its progenitor gene complements. Thus, "transcriptome downsizing" is greater than genome downsizing. Using this transcriptome size estimate, we inferred dosage responses for several thousand genes and showed that the majority exhibit partial dosage compensation. Homoeologue silencing is nonrandomly distributed across dosage responses, with genes showing extreme responses in either direction significantly more likely to have a silent homoeologue. This experimental approach will add value to transcript profiling experiments involving interspecies and interploidy comparisons by converting expression per transcriptome to expression per genome, eliminating the need for assumptions about transcriptome size.

A high-throughput RNA extraction for sprouted single-seed malting barley (Hordeum vulgare L.) rich in polysaccharides

USDA-ARS?s Scientific Manuscript database

Germinated seed from cereal crops including barley (Hordeum vulgare L.) is an important tissue to extract RNA and analyze expression levels of genes that control aspects of germination. These tissues are rich in polysaccharides and most methods for RNA extraction are not suitable to handle the exces...

Estimating differential expression from multiple indicators

PubMed Central

Ilmjärv, Sten; Hundahl, Christian Ansgar; Reimets, Riin; Niitsoo, Margus; Kolde, Raivo; Vilo, Jaak; Vasar, Eero; Luuk, Hendrik

2014-01-01

Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR. PMID:24586062

Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.

PubMed

Vallat, Laurent; Kemper, Corey A; Jung, Nicolas; Maumy-Bertrand, Myriam; Bertrand, Frédéric; Meyer, Nicolas; Pocheville, Arnaud; Fisher, John W; Gribben, John G; Bahram, Seiamak

2013-01-08

Cellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions--notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program.

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

PubMed

Feltus, F Alex

2014-06-01

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Characterization of gonadal transcriptomes from the turbot (Scophthalmus maximus).

PubMed

Hu, Yulong; Huang, Meng; Wang, Weiji; Guan, Jiantao; Kong, Jie

2016-01-01

The mechanisms underlying sexual reproduction and sex ratio determination remains unclear in turbot, a flatfish of great commercial value. And there is limited information in the turbot database regarding genes related to the reproductive system. Here, we conducted high-throughput transcriptome profiling of turbot gonad tissues to better understand their reproductive functions and to supply essential gene sequence information for marker-assisted selection programs in the turbot industry. In this study, two gonad libraries representing sex differences in Scophthalmus maximus yielded 453 818 high-quality reads that were assembled into 24 611 contigs and 33 713 singletons by using 454 pyrosequencing, 13 936 contigs and singletons (CS) of which were annotated using BLASTx. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses revealed that various biological functions and processes were associated with many of the annotated CS. Expression analyses showed that 510 genes were differentially expressed in males versus females; 80% of these genes were annotated. In addition, 6484 and 6036 single nucleotide polymorphisms (SNPs) were identified in male and female libraries, respectively. This transcriptome resource will serve as the foundation for cDNA or SNP microarray construction, gene expression characterization, and sex-specific linkage mapping in turbot.

Different Metabolic Pathways Are Involved in Response of Saccharomyces cerevisiae to L-A and M Viruses

PubMed Central

Lukša, Juliana; Ravoitytė, Bazilė; Konovalovas, Aleksandras; Aitmanaitė, Lina; Butenko, Anzhelika; Serva, Saulius; Servienė, Elena

2017-01-01

Competitive and naturally occurring yeast killer phenotype is governed by coinfection with dsRNA viruses. Long-term relationship between the host cell and viruses appear to be beneficial and co-adaptive; however, the impact of viral dsRNA on the host gene expression has barely been investigated. Here, we determined the transcriptomic profiles of the host Saccharomyces cerevisiae upon the loss of the M-2 dsRNA alone and the M-2 along with the L-A-lus dsRNAs. We provide a comprehensive study based on the high-throughput RNA-Seq data, Gene Ontology and the analysis of the interaction networks. We identified 486 genes differentially expressed after curing yeast cells of the M-2 dsRNA and 715 genes affected by the elimination of both M-2 and L-A-lus dsRNAs. We report that most of the transcriptional responses induced by viral dsRNAs are moderate. Differently expressed genes are related to ribosome biogenesis, mitochondrial functions, stress response, biosynthesis of lipids and amino acids. Our study also provided insight into the virus–host and virus–virus interplays. PMID:28757599

Different Metabolic Pathways Are Involved in Response of Saccharomyces cerevisiae to L-A and M Viruses.

PubMed

Lukša, Juliana; Ravoitytė, Bazilė; Konovalovas, Aleksandras; Aitmanaitė, Lina; Butenko, Anzhelika; Yurchenko, Vyacheslav; Serva, Saulius; Servienė, Elena

2017-07-25

Competitive and naturally occurring yeast killer phenotype is governed by coinfection with dsRNA viruses. Long-term relationship between the host cell and viruses appear to be beneficial and co-adaptive; however, the impact of viral dsRNA on the host gene expression has barely been investigated. Here, we determined the transcriptomic profiles of the host Saccharomyces cerevisiae upon the loss of the M-2 dsRNA alone and the M-2 along with the L-A-lus dsRNAs. We provide a comprehensive study based on the high-throughput RNA-Seq data, Gene Ontology and the analysis of the interaction networks. We identified 486 genes differentially expressed after curing yeast cells of the M-2 dsRNA and 715 genes affected by the elimination of both M-2 and L-A-lus dsRNAs. We report that most of the transcriptional responses induced by viral dsRNAs are moderate. Differently expressed genes are related to ribosome biogenesis, mitochondrial functions, stress response, biosynthesis of lipids and amino acids. Our study also provided insight into the virus-host and virus-virus interplays.

Construction of siRNA/miRNA expression vectors based on a one-step PCR process

PubMed Central

Xu, Jun; Zeng, Jie Qiong; Wan, Gang; Hu, Gui Bin; Yan, Hong; Ma, Li Xin

2009-01-01

Background RNA interference (RNAi) has become a powerful means for silencing target gene expression in mammalian cells and is envisioned to be useful in therapeutic approaches to human disease. In recent years, high-throughput, genome-wide screening of siRNA/miRNA libraries has emerged as a desirable approach. Current methods for constructing siRNA/miRNA expression vectors require the synthesis of long oligonucleotides, which is costly and suffers from mutation problems. Results Here we report an ingenious method to solve traditional problems associated with construction of siRNA/miRNA expression vectors. We synthesized shorter primers (< 50 nucleotides) to generate a linear expression structure by PCR. The PCR products were directly transformed into chemically competent E. coli and converted to functional vectors in vivo via homologous recombination. The positive clones could be easily screened under UV light. Using this method we successfully constructed over 500 functional siRNA/miRNA expression vectors. Sequencing of the vectors confirmed a high accuracy rate. Conclusion This novel, convenient, low-cost and highly efficient approach may be useful for high-throughput assays of RNAi libraries. PMID:19490634

Profiling of drought-responsive microRNA and mRNA in tomato using high-throughput sequencing.

PubMed

Liu, Minmin; Yu, Huiyang; Zhao, Gangjun; Huang, Qiufeng; Lu, Yongen; Ouyang, Bo

2017-06-26

Abiotic stresses cause severe loss of crop production. Among them, drought is one of the most frequent environmental stresses, which limits crop growth, development and productivity. Plant drought tolerance is fine-tuned by a complex gene regulatory network. Understanding the molecular regulation of this polygenic trait is crucial for the eventual success to improve plant yield and quality. Recent studies have demonstrated that microRNAs play critical roles in plant drought tolerance. However, little is known about the microRNA in drought response of the model plant tomato. Here, we described the profiling of drought-responsive microRNA and mRNA in tomato using high-throughput next-generation sequencing. Drought stress was applied on the seedlings of M82, a drought-sensitive cultivated tomato genotype, and IL9-1, a drought-tolerant introgression line derived from the stress-resistant wild species Solanum pennellii LA0716 and M82. Under drought, IL9-1 performed superior than M82 regarding survival rate, H 2 O 2 elimination and leaf turgor maintenance. A total of four small RNA and eight mRNA libraries were constructed and sequenced using Illumina sequencing technology. 105 conserved and 179 novel microRNAs were identified, among them, 54 and 98 were differentially expressed upon drought stress, respectively. The majority of the differentially-expressed conserved microRNAs was up-regulated in IL9-1 whereas down-regulated in M82. Under drought stress, 2714 and 1161 genes were found to be differentially expressed in M82 and IL9-1, respectively, and many of their homologues are involved in plant stress, such as genes encoding transcription factor and protein kinase. Various pathways involved in abiotic stress were revealed by Gene Ontology and pathway analysis. The mRNA sequencing results indicated that most of the target genes were regulated by their corresponding microRNAs, which suggested that microRNAs may play essential roles in the drought tolerance of tomato. In this study, numerous microRNAs and mRNAs involved in the drought response of tomato were identified using high-throughput sequencing, which will provide new insights into the complex regulatory network of plant adaption to drought stress. This work will also help to exploit new players functioning in plant drought-stress tolerance.

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

[Knockdown of dopamine receptor D2 upregulates the expression of adiogenic genes in mouse primary mesencephalic neurons].

PubMed

Ding, Jiaqi; Chen, Xiaoli; Lin, Jiaji; Zhu, Junling; Li, Zhuyi

2018-01-01

Objective To study the effects of dopamine receptor D2 (DRD2) on the adipogenesis genes in mouse primary mesencephalic neurons. Methods The lentiviral vectors which expressed specific shRNA targeting DRD2 were constructed to decrease DRD2 expression in mouse primary mesencephalic neurons. High throughput sequencing (HTS) analysis was used to investigate gene expression changes between the DRD2 knock-down group and the negative control group. Real-time quantitative PCR (qRT-PCR) and Western blot analysis were applied to verify the differently expressed genes. Fatty acids were measured by fatty acid detection kit. Results DRD2 expression was effectively down-regulated in mouse primary mesencephalic neurons by lentiviral vectors. HTS revealed adipogenesis genes were significantly up-regulated after DRD2 down-regulation, mainly including delta(14)-sterol reductase, acetyl-coenzyme A synthetase, insulin-induced gene 1 protein and especially stearoyl-coenzyme A desaturase 1 (SCD1, 4-fold upregulated). The qRT-PCR and Western blot analysis verified that SCD1 was upregulated 2.6 folds and 2 folds respectively by lentiviral DRD2-shRNA vectors. Moreover, the SCD1-related free fatty acids were significantly more increased than the negative control group. Conclusion DRD2 in primary mesencephalic neurons had a significant regulative effect on the adipogenesis genes. The up-regulation of SCD1 can accelerate the conversion of saturated fatty acids to monounsaturated fatty acids and prevent the damage of lipid toxicity to cells.

Integrated analysis of miRNAs and transcriptomes in Aedes albopictus midgut reveals the differential expression profiles of immune-related genes during dengue virus serotype-2 infection.

PubMed

Liu, Yan-Xia; Li, Fen-Xiang; Liu, Zhuan-Zhuan; Jia, Zhi-Rong; Zhou, Yan-He; Zhang, Hao; Yan, Hui; Zhou, Xian-Qiang; Chen, Xiao-Guang

2016-06-01

Mosquito microRNAs (miRNAs) are involved in host-virus interaction, and have been reported to be altered by dengue virus (DENV) infection in Aedes albopictus (Diptera: Culicidae). However, little is known about the molecular mechanisms of Aedes albopictus midgut-the first organ to interact with DENV-involved in its resistance to DENV. Here we used high-throughput sequencing to characterize miRNA and messenger RNA (mRNA) expression patterns in Aedes albopictus midgut in response to dengue virus serotype 2. A total of three miRNAs and 777 mRNAs were identified to be differentially expressed upon DENV infection. For the mRNAs, we identified 198 immune-related genes and 31 of them were differentially expressed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses also showed that the differentially expressed immune-related genes were involved in immune response. Then the differential expression patterns of six immune-related genes and three miRNAs were confirmed by real-time reverse transcription polymerase chain reaction. Furthermore, seven known miRNA-mRNA interaction pairs were identified by aligning our two datasets. These analyses of miRNA and mRNA transcriptomes provide valuable information for uncovering the DENV response genes and provide a basis for future study of the resistance mechanisms in Aedes albopictus midgut. © 2016 Institute of Zoology, Chinese Academy of Sciences.

Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

PubMed

Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

2015-01-01

Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

Defining the limits of physiological plasticity: how gene expression can assess and predict the consequences of ocean change

PubMed Central

Evans, Tyler G.; Hofmann, Gretchen E.

2012-01-01

Anthropogenic stressors, such as climate change, are driving fundamental shifts in the abiotic characteristics of marine ecosystems. As the environmental aspects of our world's oceans deviate from evolved norms, of major concern is whether extant marine species possess the capacity to cope with such rapid change. In what many scientists consider the post-genomic era, tools that exploit the availability of DNA sequence information are being increasingly recognized as relevant to questions surrounding ocean change and marine conservation. In this review, we highlight the application of high-throughput gene-expression profiling, primarily transcriptomics, to the field of marine conservation physiology. Through the use of case studies, we illustrate how gene expression can be used to standardize metrics of sub-lethal stress, track organism condition in natural environments and bypass phylogenetic barriers that hinder the application of other physiological techniques to conservation. When coupled with fine-scale monitoring of environmental variables, gene-expression profiling provides a powerful approach to conservation capable of informing diverse issues related to ocean change, from coral bleaching to the spread of invasive species. Integrating novel approaches capable of improving existing conservation strategies, including gene-expression profiling, will be critical to ensuring the ecological and economic health of the global ocean. PMID:22566679

De novo transcriptomic analysis during Lentinula edodes fruiting body growth.

PubMed

Wang, Yingzhu; Zeng, Xianlu; Liu, Wenguang

2018-01-30

The fruiting body of Lentinula edodes is a popular edible mushroom, and extracts from the mycelium and the fruiting body of this species have diverse therapeutic potential. To gain insights into the molecular mechanisms underlying the fruiting body growth of L. edodes from the early bud stage (EBS), through the intermediate developing stage (IDS), to the fully developed stage (FDS), we performed de novo transcriptomic analysis using high-throughput Illumina RNA-sequencing. First, we generated three cDNA libraries representative of the three respective stages. We then obtained 38,933,148, 44,594,472, and 37,905,646 high-quality reads from the respective libraries and assembled the reads into 25,104 transcriptional contigs, containing 15,199 unigenes. We found that only 9331 of the unigenes had been annotated in the NCBI non-redundant protein database, and we functionally annotated 4758 of them through Gene Ontology (GO) analysis and 2921 of them through Clusters of Orthologous Groups of proteins (COGs) analysis. We also assigned 3995 unigenes to metabolic pathways by using the Kyoto Encyclopedia of Genes and Genomes (KEGG). We further identified 399 differentially expressed genes (DEGs) between EBS and IDS, 1428 between IDS and FDS, and 1830 between EBS and FDS, uncovering 769 DEGs in multiple metabolic and signaling pathways. Interestingly, there were a limited number of DEGs whose expression was dramatically associated with FDS. Finally, genes, whose expression was either highly up-regulated in FDS or remained at a high level during fruiting body growth, were annotated specifically in the pathways of purine metabolism, unsaturated fatty acid metabolism and meiosis, suggesting that these key molecular events were actively occurring in the fruiting body. Our work is the first high-throughput transcriptome study on the growth of L. edodes fruiting bodies, and the results uncovered candidate genes for future gene identification and utilization of this commercially and medically important mushroom. Copyright © 2017 Elsevier B.V. All rights reserved.

MicroRNA-21 promotes proliferation of rat hepatocyte BRL-3A by targeting FASLG.

PubMed

Li, J J; Chan, W H; Leung, W Y; Wang, Y; Xu, C S

2015-04-27

Rat liver regeneration (RLR) induced by partial hepatectomy involves cell proliferation regulated by numerous factors, including microRNAs (miRNAs). miRNA high-throughput sequencing has been established and used to analyze miRNA expression profiles. This study showed that 39 miRNAs were related to RLR through the analysis of miRNA high-throughput sequencing. Their role toward rat normal hepatocyte line BRL-3A was studied by gain- and loss-of-function analyses, and one of them, microRNA-21 (miR-21), obviously upregulated and promoted BRL-3A cell proliferation. Using bioinformatics to search for miR-21 targets revealed that Fas ligand (FASLG) is one of miR-21's target genes. A dual-luciferase report assay and Western blot assay showed that miR-21 directly targeted the 3'-untranslated region of FASLG and inhibited the expression of FASLG, which suggests that miR-21 promoted BRL-3A cell proliferation by reducing FASLG expression.

Knowledge Driven Variable Selection (KDVS) – a new approach to enrichment analysis of gene signatures obtained from high–throughput data

PubMed Central

2013-01-01

Background High–throughput (HT) technologies provide huge amount of gene expression data that can be used to identify biomarkers useful in the clinical practice. The most frequently used approaches first select a set of genes (i.e. gene signature) able to characterize differences between two or more phenotypical conditions, and then provide a functional assessment of the selected genes with an a posteriori enrichment analysis, based on biological knowledge. However, this approach comes with some drawbacks. First, gene selection procedure often requires tunable parameters that affect the outcome, typically producing many false hits. Second, a posteriori enrichment analysis is based on mapping between biological concepts and gene expression measurements, which is hard to compute because of constant changes in biological knowledge and genome analysis. Third, such mapping is typically used in the assessment of the coverage of gene signature by biological concepts, that is either score–based or requires tunable parameters as well, limiting its power. Results We present Knowledge Driven Variable Selection (KDVS), a framework that uses a priori biological knowledge in HT data analysis. The expression data matrix is transformed, according to prior knowledge, into smaller matrices, easier to analyze and to interpret from both computational and biological viewpoints. Therefore KDVS, unlike most approaches, does not exclude a priori any function or process potentially relevant for the biological question under investigation. Differently from the standard approach where gene selection and functional assessment are applied independently, KDVS embeds these two steps into a unified statistical framework, decreasing the variability derived from the threshold–dependent selection, the mapping to the biological concepts, and the signature coverage. We present three case studies to assess the usefulness of the method. Conclusions We showed that KDVS not only enables the selection of known biological functionalities with accuracy, but also identification of new ones. An efficient implementation of KDVS was devised to obtain results in a fast and robust way. Computing time is drastically reduced by the effective use of distributed resources. Finally, integrated visualization techniques immediately increase the interpretability of results. Overall, KDVS approach can be considered as a viable alternative to enrichment–based approaches. PMID:23302187

Tackling the widespread and critical impact of batch effects in high-throughput data.

PubMed

Leek, Jeffrey T; Scharpf, Robert B; Bravo, Héctor Corrada; Simcha, David; Langmead, Benjamin; Johnson, W Evan; Geman, Donald; Baggerly, Keith; Irizarry, Rafael A

2010-10-01

High-throughput technologies are widely used, for example to assay genetic variants, gene and protein expression, and epigenetic modifications. One often overlooked complication with such studies is batch effects, which occur because measurements are affected by laboratory conditions, reagent lots and personnel differences. This becomes a major problem when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. Using both published studies and our own analyses, we argue that batch effects (as well as other technical and biological artefacts) are widespread and critical to address. We review experimental and computational approaches for doing so.

Transcriptome profiling and pathway analysis of hepatotoxicity induced by tris (2-ethylhexyl) trimellitate (TOTM) in mice.

PubMed

Chen, Xian-Hua; Ma, Li; Hu, Yi-Xiang; Wang, Dan-Xian; Fang, Li; Li, Xue-Lai; Zhao, Jin-Chuan; Yu, Hai-Rong; Ying, Hua-Zhong; Yu, Chen-Huan

2016-01-01

Tris (2-ethylhexyl) trimellitate (TOTM) is commonly used as an alternative plasticizer for medical devices. But very little information was available on its biological effects. In this study, we investigated toxicity effects of TOTM on hepatic differential gene expression analyzed by using high-throughput sequencing analysis for over-represented functions and phenotypically anchored to complementary histopathologic, and biochemical data in the liver of mice. Among 1668 candidate genes, 694 genes were up-regulated and 974 genes were down-regulated after TOTM exposure. Using Gene Ontology analysis, TOTM affected three processes: the cell cycle, metabolic process and oxidative activity. Furthermore, 11 key genes involved in the above processes were validated by real time PCR. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that these genes were involved in the cell cycle pathway, lipid metabolism and oxidative process. It revealed the transcriptome gene expression response to TOTM exposure in mouse, and these data could contribute to provide a clearer understanding of the molecular mechanisms of TOTM-induced hepatotoxicity in human. Copyright © 2015 Elsevier B.V. All rights reserved.

Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

PubMed

Wolen, Aaron R; Miles, Michael F

2012-01-01

For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

Protocol: high throughput silica-based purification of RNA from Arabidopsis seedlings in a 96-well format

PubMed Central

2011-01-01

The increasing popularity of systems-based approaches to plant research has resulted in a demand for high throughput (HTP) methods to be developed. RNA extraction from multiple samples in an experiment is a significant bottleneck in performing systems-level genomic studies. Therefore we have established a high throughput method of RNA extraction from Arabidopsis thaliana to facilitate gene expression studies in this widely used plant model. We present optimised manual and automated protocols for the extraction of total RNA from 9-day-old Arabidopsis seedlings in a 96 well plate format using silica membrane-based methodology. Consistent and reproducible yields of high quality RNA are isolated averaging 8.9 μg total RNA per sample (~20 mg plant tissue). The purified RNA is suitable for subsequent qPCR analysis of the expression of over 500 genes in triplicate from each sample. Using the automated procedure, 192 samples (2 × 96 well plates) can easily be fully processed (samples homogenised, RNA purified and quantified) in less than half a day. Additionally we demonstrate that plant samples can be stored in RNAlater at -20°C (but not 4°C) for 10 months prior to extraction with no significant effect on RNA yield or quality. Additionally, disrupted samples can be stored in the lysis buffer at -20°C for at least 6 months prior to completion of the extraction procedure providing a flexible sampling and storage scheme to facilitate complex time series experiments. PMID:22136293

Protocol: high throughput silica-based purification of RNA from Arabidopsis seedlings in a 96-well format.

PubMed

Salvo-Chirnside, Eliane; Kane, Steven; Kerr, Lorraine E

2011-12-02

The increasing popularity of systems-based approaches to plant research has resulted in a demand for high throughput (HTP) methods to be developed. RNA extraction from multiple samples in an experiment is a significant bottleneck in performing systems-level genomic studies. Therefore we have established a high throughput method of RNA extraction from Arabidopsis thaliana to facilitate gene expression studies in this widely used plant model. We present optimised manual and automated protocols for the extraction of total RNA from 9-day-old Arabidopsis seedlings in a 96 well plate format using silica membrane-based methodology. Consistent and reproducible yields of high quality RNA are isolated averaging 8.9 μg total RNA per sample (~20 mg plant tissue). The purified RNA is suitable for subsequent qPCR analysis of the expression of over 500 genes in triplicate from each sample. Using the automated procedure, 192 samples (2 × 96 well plates) can easily be fully processed (samples homogenised, RNA purified and quantified) in less than half a day. Additionally we demonstrate that plant samples can be stored in RNAlater at -20°C (but not 4°C) for 10 months prior to extraction with no significant effect on RNA yield or quality. Additionally, disrupted samples can be stored in the lysis buffer at -20°C for at least 6 months prior to completion of the extraction procedure providing a flexible sampling and storage scheme to facilitate complex time series experiments.

Profiling and bioinformatic analysis of circular RNA expression regulated by c-Myc.

PubMed

Gou, Qiheng; Wu, Ke; Zhou, Jian-Kang; Xie, Yuxin; Liu, Lunxu; Peng, Yong

2017-09-22

The c-Myc transcription factor is involved in cell proliferation, cell cycle and apoptosis by activating or repressing transcription of multiple genes. Circular RNAs (circRNAs) are widely expressed non-coding RNAs participating in the regulation of gene expression. Using a high-throughput microarray assay, we showed that Myc regulates the expression of certain circRNAs. A total of 309 up- and 252 down-regulated circRNAs were identified. Among them, randomly selected 8 circRNAs were confirmed by real-time PCR. Subsequently, Myc-binding sites were found to generally exist in the promoter regions of differentially expressed circRNAs. Based on miRNA sponge mechanism, we constructed circRNAs/miRNAs network regulated by Myc, suggesting that circRNAs may widely regulate protein expression through miRNA sponge mechanism. Lastly, we took advantage of Gene Ontology and KEGG analyses to point out that Myc-regulated circRNAs could impact cell proliferation through affecting Ras signaling pathway and pathways in cancer. Our study for the first time demonstrated that Myc transcription factor regulates the expression of circRNAs, adding a novel component of the Myc tumorigenic program and opening a window to investigate the function of certain circRNAs in tumorigenesis.

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

PubMed

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

2017-06-01

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

Adolescent mouse takes on an active transcriptomic expression during postnatal cerebral development.

PubMed

Xu, Wei; Xin, Chengqi; Lin, Qiang; Ding, Feng; Gong, Wei; Zhou, Yuanyuan; Yu, Jun; Cui, Peng; Hu, Songnian

2014-06-01

Postnatal cerebral development is a complicated biological process precisely controlled by multiple genes. To understand the molecular mechanism of cerebral development, we compared dynamics of mouse cerebrum transcriptome through three developmental stages using high-throughput RNA-seq technique. Three libraries were generated from the mouse cerebrum at infancy, adolescence and adulthood, respectively. Consequently, 44,557,729 (infancy), 59,257,530 (adolescence) and 72,729,636 (adulthood) reads were produced, which were assembled into 15,344, 16,048 and 15,775 genes, respectively. We found that the overall gene expression level increased from infancy to adolescence and decreased later on upon reaching adulthood. The adolescence cerebrum has the most active gene expression, with expression of a large number of regulatory genes up-regulated and some crucial pathways activated. Transcription factor (TF) analysis suggested the similar dynamics as expression profiling, especially those TFs functioning in neurogenesis differentiation, oligodendrocyte lineage determination and circadian rhythm regulation. Moreover, our data revealed a drastic increase in myelin basic protein (MBP)-coding gene expression in adolescence and adulthood, suggesting that the brain myelin may be generated since mouse adolescence. In addition, differential gene expression analysis indicated the activation of rhythmic pathway, suggesting the function of rhythmic movement since adolescence; Furthermore, during infancy and adolescence periods, gene expression related to axonrepulsion and attraction showed the opposite trends, indicating that axon repulsion was activated after birth, while axon attraction might be activated at the embryonic stage and declined during the postnatal development. Our results from the present study may shed light on the molecular mechanism underlying the postnatal development of the mammalian cerebrum. Copyright © 2014. Production and hosting by Elsevier Ltd.

Gene expression profiling via LongSAGE in a non-model plant species: a case study in seeds of Brassica napus

PubMed Central

Obermeier, Christian; Hosseini, Bashir; Friedt, Wolfgang; Snowdon, Rod

2009-01-01

Background Serial analysis of gene expression (LongSAGE) was applied for gene expression profiling in seeds of oilseed rape (Brassica napus ssp. napus). The usefulness of this technique for detailed expression profiling in a non-model organism was demonstrated for the highly complex, neither fully sequenced nor annotated genome of B. napus by applying a tag-to-gene matching strategy based on Brassica ESTs and the annotated proteome of the closely related model crucifer A. thaliana. Results Transcripts from 3,094 genes were detected at two time-points of seed development, 23 days and 35 days after pollination (DAP). Differential expression showed a shift from gene expression involved in diverse developmental processes including cell proliferation and seed coat formation at 23 DAP to more focussed metabolic processes including storage protein accumulation and lipid deposition at 35 DAP. The most abundant transcripts at 23 DAP were coding for diverse protease inhibitor proteins and proteases, including cysteine proteases involved in seed coat formation and a number of lipid transfer proteins involved in embryo pattern formation. At 35 DAP, transcripts encoding napin, cruciferin and oleosin storage proteins were most abundant. Over both time-points, 18.6% of the detected genes were matched by Brassica ESTs identified by LongSAGE tags in antisense orientation. This suggests a strong involvement of antisense transcript expression in regulatory processes during B. napus seed development. Conclusion This study underlines the potential of transcript tagging approaches for gene expression profiling in Brassica crop species via EST matching to annotated A. thaliana genes. Limits of tag detection for low-abundance transcripts can today be overcome by ultra-high throughput sequencing approaches, so that tag-based gene expression profiling may soon become the method of choice for global expression profiling in non-model species. PMID:19575793

Comparative expression profiling reveals gene functions in female meiosis and gametophyte development in Arabidopsis.

PubMed

Zhao, Lihua; He, Jiangman; Cai, Hanyang; Lin, Haiyan; Li, Yanqiang; Liu, Renyi; Yang, Zhenbiao; Qin, Yuan

2014-11-01

Megasporogenesis is essential for female fertility, and requires the accomplishment of meiosis and the formation of functional megaspores. The inaccessibility and low abundance of female meiocytes make it particularly difficult to elucidate the molecular basis underlying megasporogenesis. We used high-throughput tag-sequencing analysis to identify genes expressed in female meiocytes (FMs) by comparing gene expression profiles from wild-type ovules undergoing megasporogenesis with those from the spl mutant ovules, which lack megasporogenesis. A total of 862 genes were identified as FMs, with levels that are consistently reduced in spl ovules in two biological replicates. Fluorescence-assisted cell sorting followed by RNA-seq analysis of DMC1:GFP-labeled female meiocytes confirmed that 90% of the FMs are indeed detected in the female meiocyte protoplast profiling. We performed reverse genetic analysis of 120 candidate genes and identified four FM genes with a function in female meiosis progression in Arabidopsis. We further revealed that KLU, a putative cytochrome P450 monooxygenase, is involved in chromosome pairing during female meiosis, most likely by affecting the normal expression pattern of DMC1 in ovules during female meiosis. Our studies provide valuable information for functional genomic analyses of plant germline development as well as insights into meiosis. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

Using reporter gene assays to identify cis regulatory differences between humans and chimpanzees.

PubMed

Chabot, Adrien; Shrit, Ralla A; Blekhman, Ran; Gilad, Yoav

2007-08-01

Most phenotypic differences between human and chimpanzee are likely to result from differences in gene regulation, rather than changes to protein-coding regions. To date, however, only a handful of human-chimpanzee nucleotide differences leading to changes in gene regulation have been identified. To hone in on differences in regulatory elements between human and chimpanzee, we focused on 10 genes that were previously found to be differentially expressed between the two species. We then designed reporter gene assays for the putative human and chimpanzee promoters of the 10 genes. Of seven promoters that we found to be active in human liver cell lines, human and chimpanzee promoters had significantly different activity in four cases, three of which recapitulated the gene expression difference seen in the microarray experiment. For these three genes, we were therefore able to demonstrate that a change in cis influences expression differences between humans and chimpanzees. Moreover, using site-directed mutagenesis on one construct, the promoter for the DDA3 gene, we were able to identify three nucleotides that together lead to a cis regulatory difference between the species. High-throughput application of this approach can provide a map of regulatory element differences between humans and our close evolutionary relatives.

The gene expression profile of resistant and susceptible Bombyx mori strains reveals cypovirus-associated variations in host gene transcript levels.

PubMed

Guo, Rui; Wang, Simei; Xue, Renyu; Cao, Guangli; Hu, Xiaolong; Huang, Moli; Zhang, Yangqi; Lu, Yahong; Zhu, Liyuan; Chen, Fei; Liang, Zi; Kuang, Sulan; Gong, Chengliang

2015-06-01

High-throughput paired-end RNA sequencing (RNA-Seq) was performed to investigate the gene expression profile of a susceptible Bombyx mori strain, Lan5, and a resistant B. mori strain, Ou17, which were both orally infected with B. mori cypovirus (BmCPV) in the midgut. There were 330 and 218 up-regulated genes, while there were 147 and 260 down-regulated genes in the Lan5 and Ou17 strains, respectively. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment for differentially expressed genes (DEGs) were carried out. Moreover, gene interaction network (STRING) analyses were performed to analyze the relationships among the shared DEGs. Some of these genes were related and formed a large network, in which the genes for B. mori cuticular protein RR-2 motif 123 (BmCPR123) and the gene for B. mori DNA replication licensing factor Mcm2-like (BmMCM2) were key genes among the common up-regulated DEGs, whereas the gene for B. mori heat shock protein 20.1 (Bmhsp20.1) was the central gene among the shared down-regulated DEGs between Lan5 vs Lan5-CPV and Ou17 vs Ou17-CPV. These findings established a comprehensive database of genes that are differentially expressed in response to BmCPV infection between silkworm strains that differed in resistance to BmCPV and implied that these DEGs might be involved in B. mori immune responses against BmCPV infection.

A genome resource to address mechanisms of developmental programming: determination of the fetal sheep heart transcriptome.

PubMed

Cox, Laura A; Glenn, Jeremy P; Spradling, Kimberly D; Nijland, Mark J; Garcia, Roy; Nathanielsz, Peter W; Ford, Stephen P

2012-06-15

The pregnant sheep has provided seminal insights into reproduction related to animal and human development (ovarian function, fertility, implantation, fetal growth, parturition and lactation). Fetal sheep physiology has been extensively studied since 1950, contributing significantly to the basis for our understanding of many aspects of fetal development and behaviour that remain in use in clinical practice today. Understanding mechanisms requires the combination of systems approaches uniquely available in fetal sheep with the power of genomic studies. Absence of the full range of sheep genomic resources has limited the full realization of the power of this model, impeding progress in emerging areas of pregnancy biology such as developmental programming. We have examined the expressed fetal sheep heart transcriptome using high-throughput sequencing technologies. In so doing we identified 36,737 novel transcripts and describe genes, gene variants and pathways relevant to fundamental developmental mechanisms. Genes with the highest expression levels and with novel exons in the fetal heart transcriptome are known to play central roles in muscle development. We show that high-throughput sequencing methods can generate extensive transcriptome information in the absence of an assembled and annotated genome for that species. The gene sequence data obtained provide a unique genomic resource for sheep specific genetic technology development and, combined with the polymorphism data, augment annotation and assembly of the sheep genome. In addition, identification and pathway analysis of novel fetal sheep heart transcriptome splice variants is a first step towards revealing mechanisms of genetic variation and gene environment interactions during fetal heart development.

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

A genome resource to address mechanisms of developmental programming: determination of the fetal sheep heart transcriptome

PubMed Central

Cox, Laura A; Glenn, Jeremy P; Spradling, Kimberly D; Nijland, Mark J; Garcia, Roy; Nathanielsz, Peter W; Ford, Stephen P

2012-01-01

The pregnant sheep has provided seminal insights into reproduction related to animal and human development (ovarian function, fertility, implantation, fetal growth, parturition and lactation). Fetal sheep physiology has been extensively studied since 1950, contributing significantly to the basis for our understanding of many aspects of fetal development and behaviour that remain in use in clinical practice today. Understanding mechanisms requires the combination of systems approaches uniquely available in fetal sheep with the power of genomic studies. Absence of the full range of sheep genomic resources has limited the full realization of the power of this model, impeding progress in emerging areas of pregnancy biology such as developmental programming. We have examined the expressed fetal sheep heart transcriptome using high-throughput sequencing technologies. In so doing we identified 36,737 novel transcripts and describe genes, gene variants and pathways relevant to fundamental developmental mechanisms. Genes with the highest expression levels and with novel exons in the fetal heart transcriptome are known to play central roles in muscle development. We show that high-throughput sequencing methods can generate extensive transcriptome information in the absence of an assembled and annotated genome for that species. The gene sequence data obtained provide a unique genomic resource for sheep specific genetic technology development and, combined with the polymorphism data, augment annotation and assembly of the sheep genome. In addition, identification and pathway analysis of novel fetal sheep heart transcriptome splice variants is a first step towards revealing mechanisms of genetic variation and gene environment interactions during fetal heart development. PMID:22508961

Gene Expression (mRNA) Markers for Differentiating between Malignant and Benign Follicular Thyroid Tumours

PubMed Central

Wojtas, Bartosz; Pfeifer, Aleksandra; Oczko-Wojciechowska, Malgorzata; Krajewska, Jolanta; Czarniecka, Agnieszka; Kukulska, Aleksandra; Eszlinger, Markus; Musholt, Thomas; Stokowy, Tomasz; Swierniak, Michal; Stobiecka, Ewa; Chmielik, Ewa; Rusinek, Dagmara; Tyszkiewicz, Tomasz; Halczok, Monika; Hauptmann, Steffen; Lange, Dariusz; Jarzab, Michal; Paschke, Ralf; Jarzab, Barbara

2017-01-01

Distinguishing between follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA) constitutes a long-standing diagnostic problem resulting in equivocal histopathological diagnoses. There is therefore a need for additional molecular markers. To identify molecular differences between FTC and FTA, we analyzed the gene expression microarray data of 52 follicular neoplasms. We also performed a meta-analysis involving 14 studies employing high throughput methods (365 follicular neoplasms analyzed). Based on these two analyses, we selected 18 genes differentially expressed between FTA and FTC. We validated them by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent set of 71 follicular neoplasms from formaldehyde-fixed paraffin embedded (FFPE) tissue material. We confirmed differential expression for 7 genes (CPQ, PLVAP, TFF3, ACVRL1, ZFYVE21, FAM189A2, and CLEC3B). Finally, we created a classifier that distinguished between FTC and FTA with an accuracy of 78%, sensitivity of 76%, and specificity of 80%, based on the expression of 4 genes (CPQ, PLVAP, TFF3, ACVRL1). In our study, we have demonstrated that meta-analysis is a valuable method for selecting possible molecular markers. Based on our results, we conclude that there might exist a plausible limit of gene classifier accuracy of approximately 80%, when follicular tumors are discriminated based on formalin-fixed postoperative material. PMID:28574441

Gene Expression (mRNA) Markers for Differentiating between Malignant and Benign Follicular Thyroid Tumours.

PubMed

Wojtas, Bartosz; Pfeifer, Aleksandra; Oczko-Wojciechowska, Malgorzata; Krajewska, Jolanta; Czarniecka, Agnieszka; Kukulska, Aleksandra; Eszlinger, Markus; Musholt, Thomas; Stokowy, Tomasz; Swierniak, Michal; Stobiecka, Ewa; Chmielik, Ewa; Rusinek, Dagmara; Tyszkiewicz, Tomasz; Halczok, Monika; Hauptmann, Steffen; Lange, Dariusz; Jarzab, Michal; Paschke, Ralf; Jarzab, Barbara

2017-06-02

Distinguishing between follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA) constitutes a long-standing diagnostic problem resulting in equivocal histopathological diagnoses. There is therefore a need for additional molecular markers. To identify molecular differences between FTC and FTA, we analyzed the gene expression microarray data of 52 follicular neoplasms. We also performed a meta-analysis involving 14 studies employing high throughput methods (365 follicular neoplasms analyzed). Based on these two analyses, we selected 18 genes differentially expressed between FTA and FTC. We validated them by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent set of 71 follicular neoplasms from formaldehyde-fixed paraffin embedded (FFPE) tissue material. We confirmed differential expression for 7 genes ( CPQ , PLVAP , TFF3 , ACVRL1 , ZFYVE21 , FAM189A2 , and CLEC3B ). Finally, we created a classifier that distinguished between FTC and FTA with an accuracy of 78%, sensitivity of 76%, and specificity of 80%, based on the expression of 4 genes ( CPQ , PLVAP , TFF3 , ACVRL1 ). In our study, we have demonstrated that meta-analysis is a valuable method for selecting possible molecular markers. Based on our results, we conclude that there might exist a plausible limit of gene classifier accuracy of approximately 80%, when follicular tumors are discriminated based on formalin-fixed postoperative material.

Identification of Novel Pro-Migratory, Cancer-Associated Genes Using Quantitative, Microscopy-Based Screening

PubMed Central

Naffar-Abu-Amara, Suha; Shay, Tal; Galun, Meirav; Cohen, Naomi; Isakoff, Steven J.; Kam, Zvi; Geiger, Benjamin

2008-01-01

Background Cell migration is a highly complex process, regulated by multiple genes, signaling pathways and external stimuli. To discover genes or pharmacological agents that can modulate the migratory activity of cells, screening strategies that enable the monitoring of diverse migratory parameters in a large number of samples are necessary. Methodology In the present study, we describe the development of a quantitative, high-throughput cell migration assay, based on a modified phagokinetic tracks (PKT) procedure, and apply it for identifying novel pro-migratory genes in a cancer-related gene library. In brief, cells are seeded on fibronectin-coated 96-well plates, covered with a monolayer of carboxylated latex beads. Motile cells clear the beads, located along their migratory paths, forming tracks that are visualized using an automated, transmitted-light screening microscope. The tracks are then segmented and characterized by multi-parametric, morphometric analysis, resolving a variety of morphological and kinetic features. Conclusions In this screen we identified 4 novel genes derived from breast carcinoma related cDNA library, whose over-expression induces major alteration in the migration of the stationary MCF7 cells. This approach can serve for high throughput screening for novel ways to modulate cellular migration in pathological states such as tumor metastasis and invasion. PMID:18213366

rSeqNP: a non-parametric approach for detecting differential expression and splicing from RNA-Seq data.

PubMed

Shi, Yang; Chinnaiyan, Arul M; Jiang, Hui

2015-07-01

High-throughput sequencing of transcriptomes (RNA-Seq) has become a powerful tool to study gene expression. Here we present an R package, rSeqNP, which implements a non-parametric approach to test for differential expression and splicing from RNA-Seq data. rSeqNP uses permutation tests to access statistical significance and can be applied to a variety of experimental designs. By combining information across isoforms, rSeqNP is able to detect more differentially expressed or spliced genes from RNA-Seq data. The R package with its source code and documentation are freely available at http://www-personal.umich.edu/∼jianghui/rseqnp/. jianghui@umich.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

TMV-Gate vectors: Gateway compatible tobacco mosaic virus based expression vectors for functional analysis of proteins

PubMed Central

Kagale, Sateesh; Uzuhashi, Shihomi; Wigness, Merek; Bender, Tricia; Yang, Wen; Borhan, M. Hossein; Rozwadowski, Kevin

2012-01-01

Plant viral expression vectors are advantageous for high-throughput functional characterization studies of genes due to their capability for rapid, high-level transient expression of proteins. We have constructed a series of tobacco mosaic virus (TMV) based vectors that are compatible with Gateway technology to enable rapid assembly of expression constructs and exploitation of ORFeome collections. In addition to the potential of producing recombinant protein at grams per kilogram FW of leaf tissue, these vectors facilitate either N- or C-terminal fusions to a broad series of epitope tag(s) and fluorescent proteins. We demonstrate the utility of these vectors in affinity purification, immunodetection and subcellular localisation studies. We also apply the vectors to characterize protein-protein interactions and demonstrate their utility in screening plant pathogen effectors. Given its broad utility in defining protein properties, this vector series will serve as a useful resource to expedite gene characterization efforts. PMID:23166857

Genomic Imprinting Was Evolutionarily Conserved during Wheat Polyploidization.

PubMed

Yang, Guanghui; Liu, Zhenshan; Gao, Lulu; Yu, Kuohai; Feng, Man; Yao, Yingyin; Peng, Huiru; Hu, Zhaorong; Sun, Qixin; Ni, Zhongfu; Xin, Mingming

2018-01-01

Genomic imprinting is an epigenetic phenomenon that causes genes to be differentially expressed depending on their parent of origin. To evaluate the evolutionary conservation of genomic imprinting and the effects of ploidy on this process, we investigated parent-of-origin-specific gene expression patterns in the endosperm of diploid ( Aegilops spp), tetraploid, and hexaploid wheat ( Triticum spp) at various stages of development via high-throughput transcriptome sequencing. We identified 91, 135, and 146 maternally or paternally expressed genes (MEGs or PEGs, respectively) in diploid, tetraploid, and hexaploid wheat, respectively, 52.7% of which exhibited dynamic expression patterns at different developmental stages. Gene Ontology enrichment analysis suggested that MEGs and PEGs were involved in metabolic processes and DNA-dependent transcription, respectively. Nearly half of the imprinted genes exhibited conserved expression patterns during wheat hexaploidization. In addition, 40% of the homoeolog pairs originating from whole-genome duplication were consistently maternally or paternally biased in the different subgenomes of hexaploid wheat. Furthermore, imprinted expression was found for 41.2% and 50.0% of homolog pairs that evolved by tandem duplication after genome duplication in tetraploid and hexaploid wheat, respectively. These results suggest that genomic imprinting was evolutionarily conserved between closely related Triticum and Aegilops species and in the face of polyploid hybridization between species in these genera. © 2018 American Society of Plant Biologists. All rights reserved.

Genome engineering and gene expression control for bacterial strain development.

PubMed

Song, Chan Woo; Lee, Joungmin; Lee, Sang Yup

2015-01-01

In recent years, a number of techniques and tools have been developed for genome engineering and gene expression control to achieve desired phenotypes of various bacteria. Here we review and discuss the recent advances in bacterial genome manipulation and gene expression control techniques, and their actual uses with accompanying examples. Genome engineering has been commonly performed based on homologous recombination. During such genome manipulation, the counterselection systems employing SacB or nucleases have mainly been used for the efficient selection of desired engineered strains. The recombineering technology enables simple and more rapid manipulation of the bacterial genome. The group II intron-mediated genome engineering technology is another option for some bacteria that are difficult to be engineered by homologous recombination. Due to the increasing demands on high-throughput screening of bacterial strains having the desired phenotypes, several multiplex genome engineering techniques have recently been developed and validated in some bacteria. Another approach to achieve desired bacterial phenotypes is the repression of target gene expression without the modification of genome sequences. This can be performed by expressing antisense RNA, small regulatory RNA, or CRISPR RNA to repress target gene expression at the transcriptional or translational level. All of these techniques allow efficient and rapid development and screening of bacterial strains having desired phenotypes, and more advanced techniques are expected to be seen. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Human Endometrial DNA Methylome Is Cycle-Dependent and Is Associated With Gene Expression Regulation

PubMed Central

Houshdaran, Sahar; Zelenko, Zara; Irwin, Juan C.

2014-01-01

Human endometrium undergoes major gene expression changes, resulting in altered cellular functions in response to cyclic variations in circulating estradiol and progesterone, largely mediated by transcription factors and nuclear receptors. In addition to classic modulators, epigenetic mechanisms regulate gene expression during development in response to environmental factors and in some diseases and have roles in steroid hormone action. Herein, we tested the hypothesis that DNA methylation plays a role in gene expression regulation in human endometrium in different hormonal milieux. High throughput, genome-wide DNA methylation profiling of endometrial samples in proliferative, early secretory, and midsecretory phases revealed dynamic DNA methylation patterns with segregation of proliferative from secretory phase samples by unsupervised cluster analysis of differentially methylated genes. Changes involved different frequencies of gain and loss of methylation within or outside CpG islands. Comparison of changes in transcriptomes and corresponding DNA methylomes from the same samples revealed association of DNA methylation and gene expression in a number of loci, some important in endometrial biology. Human endometrial stromal fibroblasts treated in vitro with estradiol and progesterone exhibited DNA methylation changes in several genes observed in proliferative and secretory phase tissues, respectively. Taken together, the data support the observation that epigenetic mechanisms are involved in gene expression regulation in human endometrium in different hormonal milieux, adding endometrium to a small number of normal adult tissues exhibiting dynamic DNA methylation. The data also raise the possibility that the interplay between steroid hormone and methylome dynamics regulates normal endometrial functions and, if abnormal, may result in endometrial dysfunction and associated disorders. PMID:24877562

Identification of Epithelial-Mesenchymal Transition-related Target Genes Induced by the Mutation of Smad3 Linker Phosphorylation.

PubMed

Park, Sujin; Yang, Kyung-Min; Park, Yuna; Hong, Eunji; Hong, Chang Pyo; Park, Jinah; Pang, Kyoungwha; Lee, Jihee; Park, Bora; Lee, Siyoung; An, Haein; Kwak, Mi-Kyung; Kim, Junil; Kang, Jin Muk; Kim, Pyunggang; Xiao, Yang; Nie, Guangjun; Ooshima, Akira; Kim, Seong-Jin

2018-03-01

Smad3 linker phosphorylation plays essential roles in tumor progression and metastasis. We have previously reported that the mutation of Smad3 linker phosphorylation sites (Smad3-Erk/Pro-directed kinase site mutant constructs [EPSM]) markedly reduced the tumor progression while increasing the lung metastasis in breast cancer. We performed high-throughput RNA-Sequencing of the human prostate cancer cell lines infected with adenoviral Smad3-EPSM to identify the genes regulated by Smad3-EPSM. In this study, we identified genes which are differentially regulated in the presence of Smad3-EPSM. We first confirmed that Smad3-EPSM strongly enhanced a capability of cell motility and invasiveness as well as the expression of epithelial-mesenchymal transition marker genes, CDH2 , SNAI1 , and ZEB1 in response to TGF-β1 in human pancreatic and prostate cancer cell lines. We identified GADD45B , CTGF , and JUNB genes in the expression profiles associated with cell motility and invasiveness induced by the Smad3-EPSM. These results suggested that inhibition of Smad3 linker phosphorylation may enhance cell motility and invasiveness by inducing expression of GADD45B , CTGF , and JUNB genes in various cancers.

Drug-Path: a database for drug-induced pathways

PubMed Central

Zeng, Hui; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. Database URL: http://www.cuilab.cn/drugpath PMID:26130661

Drug-Path: a database for drug-induced pathways.

PubMed

Zeng, Hui; Qiu, Chengxiang; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. © The Author(s) 2015. Published by Oxford University Press.

X-ray irradiation has positive effects for the recovery of peripheral nerve injury maybe through the vascular smooth muscle contraction signaling pathway.

PubMed

Jiang, Bo; Zhang, Yong; She, Chang; Zhao, Jiaju; Zhou, Kailong; Zuo, Zhicheng; Zhou, Xiaozhong; Wang, Peiji; Dong, Qirong

2017-09-01

It is well known that moderate to high doses of ionizing radiation have a toxic effect on the organism. However, there are few experimental studies on the mechanisms of LDR ionizing radiation on nerve regeneration after peripheral nerve injury. We established the rats' peripheral nerve injury model via repaired Peripheral nerve injury nerve, vascular endothelial growth factor a and Growth associated protein-43 were detected from different treatment groups. We performed transcriptome sequencing focusing on investigating the differentially expressed genes and gene functions between the control group and 1Gy group. Sequencing was done by using high-throughput RNA-sequencing (RNA-seq) technologies. The results showed the 1Gy group to be the most effective promoting repair. RNA-sequencing identified 619 differently expressed genes between control and treated groups. A Gene Ontology analysis of the differentially expressed genes revealed enrichment in the functional pathways. Among them, candidate genes associated with nerve repair were identified. Pathways involved in cell-substrate adhesion, vascular smooth muscle contraction and cell adhesion molecule signaling may be involved in recovery from peripheral nerve injury. Copyright © 2017. Published by Elsevier B.V.

Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data.

PubMed

Nabavi, Sheida

2016-08-15

With advances in technologies, huge amounts of multiple types of high-throughput genomics data are available. These data have tremendous potential to identify new and clinically valuable biomarkers to guide the diagnosis, assessment of prognosis, and treatment of complex diseases, such as cancer. Integrating, analyzing, and interpreting big and noisy genomics data to obtain biologically meaningful results, however, remains highly challenging. Mining genomics datasets by utilizing advanced computational methods can help to address these issues. To facilitate the identification of a short list of biologically meaningful genes as candidate drivers of anti-cancer drug resistance from an enormous amount of heterogeneous data, we employed statistical machine-learning techniques and integrated genomics datasets. We developed a computational method that integrates gene expression, somatic mutation, and copy number aberration data of sensitive and resistant tumors. In this method, an integrative method based on module network analysis is applied to identify potential driver genes. This is followed by cross-validation and a comparison of the results of sensitive and resistance groups to obtain the final list of candidate biomarkers. We applied this method to the ovarian cancer data from the cancer genome atlas. The final result contains biologically relevant genes, such as COL11A1, which has been reported as a cis-platinum resistant biomarker for epithelial ovarian carcinoma in several recent studies. The described method yields a short list of aberrant genes that also control the expression of their co-regulated genes. The results suggest that the unbiased data driven computational method can identify biologically relevant candidate biomarkers. It can be utilized in a wide range of applications that compare two conditions with highly heterogeneous datasets.

Comparative transcriptome analysis reveals different molecular mechanisms of Bacillus coagulans 2-6 response to sodium lactate and calcium lactate during lactic acid production.

PubMed

Qin, Jiayang; Wang, Xiuwen; Wang, Landong; Zhu, Beibei; Zhang, Xiaohua; Yao, Qingshou; Xu, Ping

2015-01-01

Lactate production is enhanced by adding calcium carbonate or sodium hydroxide during fermentation. However, Bacillus coagulans 2-6 can produce more than 180 g/L L-lactic acid when calcium lactate is accumulated, but less than 120 g/L L-lactic acid when sodium lactate is formed. The molecular mechanisms by which B. coagulans responds to calcium lactate and sodium lactate remain unclear. In this study, comparative transcriptomic methods based on high-throughput RNA sequencing were applied to study gene expression changes in B. coagulans 2-6 cultured in non-stress, sodium lactate stress and calcium lactate stress conditions. Gene expression profiling identified 712 and 1213 significantly regulated genes in response to calcium lactate stress and sodium lactate stress, respectively. Gene ontology assignments of the differentially expressed genes were performed. KEGG pathway enrichment analysis revealed that 'ATP-binding cassette transporters' were significantly affected by calcium lactate stress, and 'amino sugar and nucleotide sugar metabolism' was significantly affected by sodium lactate stress. It was also found that lactate fermentation was less affected by calcium lactate stress than by sodium lactate stress. Sodium lactate stress had negative effect on the expression of 'glycolysis/gluconeogenesis' genes but positive effect on the expression of 'citrate cycle (TCA cycle)' genes. However, calcium lactate stress had positive influence on the expression of 'glycolysis/gluconeogenesis' genes and had minor influence on 'citrate cycle (TCA cycle)' genes. Thus, our findings offer new insights into the responses of B. coagulans to different lactate stresses. Notably, our RNA-seq dataset constitute a robust database for investigating the functions of genes induced by lactate stress in the future and identify potential targets for genetic engineering to further improve L-lactic acid production by B. coagulans.

Expression and phylogenetic analyses reveal paralogous lineages of putatively classical and non-classical MHC-I genes in three sparrow species (Passer).

PubMed

Drews, Anna; Strandh, Maria; Råberg, Lars; Westerdahl, Helena

2017-06-26

The Major Histocompatibility Complex (MHC) plays a central role in immunity and has been given considerable attention by evolutionary ecologists due to its associations with fitness-related traits. Songbirds have unusually high numbers of MHC class I (MHC-I) genes, but it is not known whether all are expressed and equally important for immune function. Classical MHC-I genes are highly expressed, polymorphic and present peptides to T-cells whereas non-classical MHC-I genes have lower expression, are more monomorphic and do not present peptides to T-cells. To get a better understanding of the highly duplicated MHC genes in songbirds, we studied gene expression in a phylogenetic framework in three species of sparrows (house sparrow, tree sparrow and Spanish sparrow), using high-throughput sequencing. We hypothesize that sparrows could have classical and non-classical genes, as previously indicated though never tested using gene expression. The phylogenetic analyses reveal two distinct types of MHC-I alleles among the three sparrow species, one with high and one with low level of polymorphism, thus resembling classical and non-classical genes, respectively. All individuals had both types of alleles, but there was copy number variation both within and among the sparrow species. However, the number of highly polymorphic alleles that were expressed did not vary between species, suggesting that the structural genomic variation is counterbalanced by conserved gene expression. Overall, 50% of the MHC-I alleles were expressed in sparrows. Expression of the highly polymorphic alleles was very variable, whereas the alleles with low polymorphism had uniformly low expression. Interestingly, within an individual only one or two alleles from the polymorphic genes were highly expressed, indicating that only a single copy of these is highly expressed. Taken together, the phylogenetic reconstruction and the analyses of expression suggest that sparrows have both classical and non-classical MHC-I genes, and that the evolutionary origin of these genes predate the split of the three investigated sparrow species 7 million years ago. Because only the classical MHC-I genes are involved in antigen presentation, the function of different MHC-I genes should be considered in future ecological and evolutionary studies of MHC-I in sparrows and other songbirds.

High-Throughput Analysis of Dynamic Gene Expression Associated with Sleep Deprivation and Recovery Sleep in the Mouse Brain

DTIC Science & Technology

2006-12-01

CONTRACTING ORGANIZATION : Allen Institute for Brain Science Seattle, WA 98103 REPORT DATE...5e. TASK NUMBER Email: edl@alleninstitute.org 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING... ORGANIZATION REPORT NUMBER Allen Institute for Brain Science Seattle, WA 98103 9. SPONSORING / MONITORING AGENCY NAME(S) AND

Flexible Measurement of Bioluminescent Reporters Using an Automated Longitudinal Luciferase Imaging Gas- and Temperature-optimized Recorder (ALLIGATOR).

PubMed

Crosby, Priya; Hoyle, Nathaniel P; O'Neill, John S

2017-12-13

Luciferase-based reporters of cellular gene expression are in widespread use for both longitudinal and end-point assays of biological activity. In circadian rhythms research, for example, clock gene fusions with firefly luciferase give rise to robust rhythms in cellular bioluminescence that persist over many days. Technical limitations associated with photomultiplier tubes (PMT) or conventional microscopy-based methods for bioluminescence quantification have typically demanded that cells and tissues be maintained under quite non-physiological conditions during recording, with a trade-off between sensitivity and throughput. Here, we report a refinement of prior methods that allows long-term bioluminescence imaging with high sensitivity and throughput which supports a broad range of culture conditions, including variable gas and humidity control, and that accepts many different tissue culture plates and dishes. This automated longitudinal luciferase imaging gas- and temperature-optimized recorder (ALLIGATOR) also allows the observation of spatial variations in luciferase expression across a cell monolayer or tissue, which cannot readily be observed by traditional methods. We highlight how the ALLIGATOR provides vastly increased flexibility for the detection of luciferase activity when compared with existing methods.

TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes.

PubMed

Jung, Inuk; Jo, Kyuri; Kang, Hyejin; Ahn, Hongryul; Yu, Youngjae; Kim, Sun

2017-12-01

Identifying biologically meaningful gene expression patterns from time series gene expression data is important to understand the underlying biological mechanisms. To identify significantly perturbed gene sets between different phenotypes, analysis of time series transcriptome data requires consideration of time and sample dimensions. Thus, the analysis of such time series data seeks to search gene sets that exhibit similar or different expression patterns between two or more sample conditions, constituting the three-dimensional data, i.e. gene-time-condition. Computational complexity for analyzing such data is very high, compared to the already difficult NP-hard two dimensional biclustering algorithms. Because of this challenge, traditional time series clustering algorithms are designed to capture co-expressed genes with similar expression pattern in two sample conditions. We present a triclustering algorithm, TimesVector, specifically designed for clustering three-dimensional time series data to capture distinctively similar or different gene expression patterns between two or more sample conditions. TimesVector identifies clusters with distinctive expression patterns in three steps: (i) dimension reduction and clustering of time-condition concatenated vectors, (ii) post-processing clusters for detecting similar and distinct expression patterns and (iii) rescuing genes from unclassified clusters. Using four sets of time series gene expression data, generated by both microarray and high throughput sequencing platforms, we demonstrated that TimesVector successfully detected biologically meaningful clusters of high quality. TimesVector improved the clustering quality compared to existing triclustering tools and only TimesVector detected clusters with differential expression patterns across conditions successfully. The TimesVector software is available at http://biohealth.snu.ac.kr/software/TimesVector/. sunkim.bioinfo@snu.ac.kr. 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

Efficient production of antibody Fab fragment by transient gene expression in insect cells.

PubMed

Mori, Keita; Hamada, Hirotsugu; Ogawa, Takafumi; Ohmuro-Matsuyama, Yuki; Katsuda, Tomohisa; Yamaji, Hideki

2017-08-01

Transient gene expression allows a rapid production of diverse recombinant proteins in early-stage preclinical and clinical developments of biologics. Insect cells have proven to be an excellent platform for the production of functional recombinant proteins. In the present study, the production of an antibody Fab fragment by transient gene expression in lepidopteran insect cells was investigated. The DNA fragments encoding heavy-chain (Hc; Fd fragment) and light-chain (Lc) genes of an Fab fragment were individually cloned into the plasmid vector pIHAneo, which contained the Bombyx mori actin promoter downstream of the B. mori nucleopolyhedrovirus (BmNPV) IE-1 transactivator and the BmNPV HR3 enhancer for high-level expression. Trichoplusia ni BTI-TN-5B1-4 (High Five) cells were co-transfected with the resultant plasmid vectors using linear polyethyleneimine. When the transfection efficiency was evaluated, a plasmid vector encoding an enhanced green fluorescent protein (EGFP) gene was also co-transfected. Transfection and culture conditions were optimized based on both the flow cytometry of the EGFP expression in transfected cells and the yield of the secreted Fab fragments determined by enzyme-linked immunosorbent assay (ELISA). Under optimal conditions, a yield of approximately 120 mg/L of Fab fragments was achieved in 5 days in a shake-flask culture. Transient gene expression in insect cells may offer a promising approach to the high-throughput production of recombinant proteins. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Finding gene clusters for a replicated time course study

PubMed Central

2014-01-01

Background Finding genes that share similar expression patterns across samples is an important question that is frequently asked in high-throughput microarray studies. Traditional clustering algorithms such as K-means clustering and hierarchical clustering base gene clustering directly on the observed measurements and do not take into account the specific experimental design under which the microarray data were collected. A new model-based clustering method, the clustering of regression models method, takes into account the specific design of the microarray study and bases the clustering on how genes are related to sample covariates. It can find useful gene clusters for studies from complicated study designs such as replicated time course studies. Findings In this paper, we applied the clustering of regression models method to data from a time course study of yeast on two genotypes, wild type and YOX1 mutant, each with two technical replicates, and compared the clustering results with K-means clustering. We identified gene clusters that have similar expression patterns in wild type yeast, two of which were missed by K-means clustering. We further identified gene clusters whose expression patterns were changed in YOX1 mutant yeast compared to wild type yeast. Conclusions The clustering of regression models method can be a valuable tool for identifying genes that are coordinately transcribed by a common mechanism. PMID:24460656

Selection and evaluation of reference genes for expression studies with quantitative PCR in the model fungus Neurospora crassa under different environmental conditions in continuous culture.

PubMed

Cusick, Kathleen D; Fitzgerald, Lisa A; Pirlo, Russell K; Cockrell, Allison L; Petersen, Emily R; Biffinger, Justin C

2014-01-01

Neurospora crassa has served as a model organism for studying circadian pathways and more recently has gained attention in the biofuel industry due to its enhanced capacity for cellulase production. However, in order to optimize N. crassa for biotechnological applications, metabolic pathways during growth under different environmental conditions must be addressed. Reverse-transcription quantitative PCR (RT-qPCR) is a technique that provides a high-throughput platform from which to measure the expression of a large set of genes over time. The selection of a suitable reference gene is critical for gene expression studies using relative quantification, as this strategy is based on normalization of target gene expression to a reference gene whose expression is stable under the experimental conditions. This study evaluated twelve candidate reference genes for use with N. crassa when grown in continuous culture bioreactors under different light and temperature conditions. Based on combined stability values from NormFinder and Best Keeper software packages, the following are the most appropriate reference genes under conditions of: (1) light/dark cycling: btl, asl, and vma1; (2) all-dark growth: btl, tbp, vma1, and vma2; (3) temperature flux: btl, vma1, act, and asl; (4) all conditions combined: vma1, vma2, tbp, and btl. Since N. crassa exists as different cell types (uni- or multi-nucleated), expression changes in a subset of the candidate genes was further assessed using absolute quantification. A strong negative correlation was found to exist between ratio and threshold cycle (CT) values, demonstrating that CT changes serve as a reliable reflection of transcript, and not gene copy number, fluctuations. The results of this study identified genes that are appropriate for use as reference genes in RT-qPCR studies with N. crassa and demonstrated that even with the presence of different cell types, relative quantification is an acceptable method for measuring gene expression changes during growth in bioreactors.

Genome-wide transcriptome and expression profile analysis of Phalaenopsis during explant browning.

PubMed

Xu, Chuanjun; Zeng, Biyu; Huang, Junmei; Huang, Wen; Liu, Yumei

2015-01-01

Explant browning presents a major problem for in vitro culture, and can lead to the death of the explant and failure of regeneration. Considerable work has examined the physiological mechanisms underlying Phalaenopsis leaf explant browning, but the molecular mechanisms of browning remain elusive. In this study, we used whole genome RNA sequencing to examine Phalaenopsis leaf explant browning at genome-wide level. We first used Illumina high-throughput technology to sequence the transcriptome of Phalaenopsis and then performed de novo transcriptome assembly. We assembled 79,434,350 clean reads into 31,708 isogenes and generated 26,565 annotated unigenes. We assigned Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations, and potential Pfam domains to each transcript. Using the transcriptome data as a reference, we next analyzed the differential gene expression of explants cultured for 0, 3, and 6 d, respectively. We then identified differentially expressed genes (DEGs) before and after Phalaenopsis explant browning. We also performed GO, KEGG functional enrichment and Pfam analysis of all DEGs. Finally, we selected 11 genes for quantitative real-time PCR (qPCR) analysis to confirm the expression profile analysis. Here, we report the first comprehensive analysis of transcriptome and expression profiles during Phalaenopsis explant browning. Our results suggest that Phalaenopsis explant browning may be due in part to gene expression changes that affect the secondary metabolism, such as: phenylpropanoid pathway and flavonoid biosynthesis. Genes involved in photosynthesis and ATPase activity have been found to be changed at transcription level; these changes may perturb energy metabolism and thus lead to the decay of plant cells and tissues. This study provides comprehensive gene expression data for Phalaenopsis browning. Our data constitute an important resource for further functional studies to prevent explant browning.

Genome-Wide Transcriptome and Expression Profile Analysis of Phalaenopsis during Explant Browning

PubMed Central

Xu, Chuanjun; Zeng, Biyu; Huang, Junmei; Huang, Wen; Liu, Yumei

2015-01-01

Background Explant browning presents a major problem for in vitro culture, and can lead to the death of the explant and failure of regeneration. Considerable work has examined the physiological mechanisms underlying Phalaenopsis leaf explant browning, but the molecular mechanisms of browning remain elusive. In this study, we used whole genome RNA sequencing to examine Phalaenopsis leaf explant browning at genome-wide level. Methodology/Principal Findings We first used Illumina high-throughput technology to sequence the transcriptome of Phalaenopsis and then performed de novo transcriptome assembly. We assembled 79,434,350 clean reads into 31,708 isogenes and generated 26,565 annotated unigenes. We assigned Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations, and potential Pfam domains to each transcript. Using the transcriptome data as a reference, we next analyzed the differential gene expression of explants cultured for 0, 3, and 6 d, respectively. We then identified differentially expressed genes (DEGs) before and after Phalaenopsis explant browning. We also performed GO, KEGG functional enrichment and Pfam analysis of all DEGs. Finally, we selected 11 genes for quantitative real-time PCR (qPCR) analysis to confirm the expression profile analysis. Conclusions/Significance Here, we report the first comprehensive analysis of transcriptome and expression profiles during Phalaenopsis explant browning. Our results suggest that Phalaenopsis explant browning may be due in part to gene expression changes that affect the secondary metabolism, such as: phenylpropanoid pathway and flavonoid biosynthesis. Genes involved in photosynthesis and ATPase activity have been found to be changed at transcription level; these changes may perturb energy metabolism and thus lead to the decay of plant cells and tissues. This study provides comprehensive gene expression data for Phalaenopsis browning. Our data constitute an important resource for further functional studies to prevent explant browning. PMID:25874455

Gene expression profiling of human breast tissue samples using SAGE-Seq.

PubMed

Wu, Zhenhua Jeremy; Meyer, Clifford A; Choudhury, Sibgat; Shipitsin, Michail; Maruyama, Reo; Bessarabova, Marina; Nikolskaya, Tatiana; Sukumar, Saraswati; Schwartzman, Armin; Liu, Jun S; Polyak, Kornelia; Liu, X Shirley

2010-12-01

We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.

Chimeras taking shape: Potential functions of proteins encoded by chimeric RNA transcripts

PubMed Central

Frenkel-Morgenstern, Milana; Lacroix, Vincent; Ezkurdia, Iakes; Levin, Yishai; Gabashvili, Alexandra; Prilusky, Jaime; del Pozo, Angela; Tress, Michael; Johnson, Rory; Guigo, Roderic; Valencia, Alfonso

2012-01-01

Chimeric RNAs comprise exons from two or more different genes and have the potential to encode novel proteins that alter cellular phenotypes. To date, numerous putative chimeric transcripts have been identified among the ESTs isolated from several organisms and using high throughput RNA sequencing. The few corresponding protein products that have been characterized mostly result from chromosomal translocations and are associated with cancer. Here, we systematically establish that some of the putative chimeric transcripts are genuinely expressed in human cells. Using high throughput RNA sequencing, mass spectrometry experimental data, and functional annotation, we studied 7424 putative human chimeric RNAs. We confirmed the expression of 175 chimeric RNAs in 16 human tissues, with an abundance varying from 0.06 to 17 RPKM (Reads Per Kilobase per Million mapped reads). We show that these chimeric RNAs are significantly more tissue-specific than non-chimeric transcripts. Moreover, we present evidence that chimeras tend to incorporate highly expressed genes. Despite the low expression level of most chimeric RNAs, we show that 12 novel chimeras are translated into proteins detectable in multiple shotgun mass spectrometry experiments. Furthermore, we confirm the expression of three novel chimeric proteins using targeted mass spectrometry. Finally, based on our functional annotation of exon organization and preserved domains, we discuss the potential features of chimeric proteins with illustrative examples and suggest that chimeras significantly exploit signal peptides and transmembrane domains, which can alter the cellular localization of cognate proteins. Taken together, these findings establish that some chimeric RNAs are translated into potentially functional proteins in humans. PMID:22588898

Global Gene Expression Patterns and Somatic Mutations in Sporadic Intracranial Aneurysms.

PubMed

Li, Zhili; Tan, Haibin; Shi, Yi; Huang, Guangfu; Wang, Zhenyu; Liu, Ling; Yin, Cheng; Wang, Qi

2017-04-01

High-throughput sequencing technologies can expand our understanding of the pathologic basis of intracranial aneurysms (IAs). Our study was aimed to decipher the gene expression signature and genetic factors associated with IAs. We determined the gene expression levels of 3 cases of IAs by RNA sequencing. Bioinformatics analysis was conducted to identify the differentially expressed genes (DEGs) and uncover their biological function. In addition, whole genome sequencing was performed on an additional 6 cases of IAs to detect the potential somatic alterations in DEGs. Compared with the normal arterial tissue, 1709 genes were differentially expressed in IAs arterial tissue. The most significantly up-regulated gene and down-regulated gene, H19 and HIST1H3J, may be essential for tumorigenesis of IAs. Hub protein of IKBKG in protein-protein interaction network was probably involved in the inflammation process in aneurysms. Another 2 hub proteins, ACTB and MKI67IP, as well as up-regulated genes, might be abnormally activated in aneurysms and involved in the pathogenesis of IAs. Further whole genome sequencing and filtering yielded 4 candidate somatic single nucleotide variants including MUC3B, and BLM may be involved in the pathogenesis of IAs. Even though, our results do not support the hypothesis of somatic mutations occurred in the DEGs. Two-dimensional genomic data from transcriptome and whole genome sequencing indicated that no somatic mutations occurred in DEGs. In addition, 3 DEGs (IKBKG, ACTB, and MKI67IP) and 2 mutant genes (MUC3B and BLM) were essential in IAs. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimal consistency in microRNA expression analysis using reference-gene-based normalization.

PubMed

Wang, Xi; Gardiner, Erin J; Cairns, Murray J

2015-05-01

Normalization of high-throughput molecular expression profiles secures differential expression analysis between samples of different phenotypes or biological conditions, and facilitates comparison between experimental batches. While the same general principles apply to microRNA (miRNA) normalization, there is mounting evidence that global shifts in their expression patterns occur in specific circumstances, which pose a challenge for normalizing miRNA expression data. As an alternative to global normalization, which has the propensity to flatten large trends, normalization against constitutively expressed reference genes presents an advantage through their relative independence. Here we investigated the performance of reference-gene-based (RGB) normalization for differential miRNA expression analysis of microarray expression data, and compared the results with other normalization methods, including: quantile, variance stabilization, robust spline, simple scaling, rank invariant, and Loess regression. The comparative analyses were executed using miRNA expression in tissue samples derived from subjects with schizophrenia and non-psychiatric controls. We proposed a consistency criterion for evaluating methods by examining the overlapping of differentially expressed miRNAs detected using different partitions of the whole data. Based on this criterion, we found that RGB normalization generally outperformed global normalization methods. Thus we recommend the application of RGB normalization for miRNA expression data sets, and believe that this will yield a more consistent and useful readout of differentially expressed miRNAs, particularly in biological conditions characterized by large shifts in miRNA expression.

Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation

PubMed Central

van Hijum, Sacha A. F. T.; Medema, Marnix H.; Kuipers, Oscar P.

2009-01-01

Summary: A major part of organismal complexity and versatility of prokaryotes resides in their ability to fine-tune gene expression to adequately respond to internal and external stimuli. Evolution has been very innovative in creating intricate mechanisms by which different regulatory signals operate and interact at promoters to drive gene expression. The regulation of target gene expression by transcription factors (TFs) is governed by control logic brought about by the interaction of regulators with TF binding sites (TFBSs) in cis-regulatory regions. A factor that in large part determines the strength of the response of a target to a given TF is motif stringency, the extent to which the TFBS fits the optimal TFBS sequence for a given TF. Advances in high-throughput technologies and computational genomics allow reconstruction of transcriptional regulatory networks in silico. To optimize the prediction of transcriptional regulatory networks, i.e., to separate direct regulation from indirect regulation, a thorough understanding of the control logic underlying the regulation of gene expression is required. This review summarizes the state of the art of the elements that determine the functionality of TFBSs by focusing on the molecular biological mechanisms and evolutionary origins of cis-regulatory regions. PMID:19721087

mRNA-Seq Analysis of the Pseudoperonospora cubensis Transcriptome During Cucumber (Cucumis sativus L.) Infection

PubMed Central

Hamilton, John P.; Vaillancourt, Brieanne; Buell, C. Robin; Day, Brad

2012-01-01

Pseudoperonospora cubensis, an oomycete, is the causal agent of cucurbit downy mildew, and is responsible for significant losses on cucurbit crops worldwide. While other oomycete plant pathogens have been extensively studied at the molecular level, Ps. cubensis and the molecular basis of its interaction with cucurbit hosts has not been well examined. Here, we present the first large-scale global gene expression analysis of Ps. cubensis infection of a susceptible Cucumis sativus cultivar, ‘Vlaspik’, and identification of genes with putative roles in infection, growth, and pathogenicity. Using high throughput whole transcriptome sequencing, we captured differential expression of 2383 Ps. cubensis genes in sporangia and at 1, 2, 3, 4, 6, and 8 days post-inoculation (dpi). Additionally, comparison of Ps. cubensis expression profiles with expression profiles from an infection time course of the oomycete pathogen Phytophthora infestans on Solanum tuberosum revealed similarities in expression patterns of 1,576–6,806 orthologous genes suggesting a substantial degree of overlap in molecular events in virulence between the biotrophic Ps. cubensis and the hemi-biotrophic P. infestans. Co-expression analyses identified distinct modules of Ps. cubensis genes that were representative of early, intermediate, and late infection stages. Collectively, these expression data have advanced our understanding of key molecular and genetic events in the virulence of Ps. cubensis and thus, provides a foundation for identifying mechanism(s) by which to engineer or effect resistance in the host. PMID:22545137

Identification of miRNA-Mediated Core Gene Module for Glioma Patient Prediction by Integrating High-Throughput miRNA, mRNA Expression and Pathway Structure

PubMed Central

Han, Junwei; Shang, Desi; Zhang, Yunpeng; Zhang, Wei; Yao, Qianlan; Han, Lei; Xu, Yanjun; Yan, Wei; Bao, Zhaoshi; You, Gan; Jiang, Tao; Kang, Chunsheng; Li, Xia

2014-01-01

The prognosis of glioma patients is usually poor, especially in patients with glioblastoma (World Health Organization (WHO) grade IV). The regulatory functions of microRNA (miRNA) on genes have important implications in glioma cell survival. However, there are not many studies that have investigated glioma survival by integrating miRNAs and genes while also considering pathway structure. In this study, we performed sample-matched miRNA and mRNA expression profilings to systematically analyze glioma patient survival. During this analytical process, we developed pathway-based random walk to identify a glioma core miRNA-gene module, simultaneously considering pathway structure information and multi-level involvement of miRNAs and genes. The core miRNA-gene module we identified was comprised of four apparent sub-modules; all four sub-modules displayed a significant correlation with patient survival in the testing set (P-values≤0.001). Notably, one sub-module that consisted of 6 miRNAs and 26 genes also correlated with survival time in the high-grade subgroup (WHO grade III and IV), P-value = 0.0062. Furthermore, the 26-gene expression signature from this sub-module had robust predictive power in four independent, publicly available glioma datasets. Our findings suggested that the expression signatures, which were identified by integration of miRNA and gene level, were closely associated with overall survival among the glioma patients with various grades. PMID:24809850

High resolution array CGH and gene expression profiling of alveolar soft part sarcoma

PubMed Central

Selvarajah, Shamini; Pyne, Saumyadipta; Chen, Eleanor; Sompallae, Ramakrishna; Ligon, Azra H.; Nielsen, Gunnlaugur P.; Dranoff, Glenn; Stack, Edward; Loda, Massimo; Flavin, Richard

2014-01-01

Purpose Alveolar soft part sarcoma (ASPS) is a soft tissue sarcoma with poor prognosis, and little molecular evidence for its origin, initiation and progression. The aim of this study was to elucidate candidate molecular pathways involved in tumor pathogenesis. Experimental Design We employed high-throughput array comparative genomic hybridization and cDNA-Mediated Annealing, Selection, Ligation, and Extension Assay to profile the genomic and expression signatures of primary and metastatic ASPS from 17 tumors derived from 11 patients. We used an integrative bioinformatics approach to elucidate the molecular pathways associated with ASPS progression. Fluorescence in situ hybridization was performed to validate the presence of the t(X;17)(p11.2;q25) ASPL-TFE3 fusion and hence confirm the aCGH observations. Results FISH analysis identified the ASPL-TFE3 fusion in all cases. ArrayCGH revealed a higher number of numerical aberrations in metastatic tumors relative to primaries, but failed to identify consistent alterations in either group. Gene expression analysis highlighted 1,063 genes which were differentially expressed between the two groups. Gene set enrichment analysis identified 16 enriched gene sets (p < 0.1) associated with differentially expressed genes. Notable among these were several stem cell gene expression signatures and pathways related to differentiation. In particular, the paired box transcription factor PAX6 was up-regulated in the primary tumors, along with several genes whose mouse orthologs have previously been implicated in Pax6-DNA binding during neural stem cell differentiation. Conclusion In addition to suggesting a tentative neural line of differentiation for ASPS, these results implicate transcriptional deregulation from fusion genes in the pathogenesis of ASPS. PMID:24493828

Gene Expression Dynamics Accompanying the Sponge Thermal Stress Response.

PubMed

Guzman, Christine; Conaco, Cecilia

2016-01-01

Marine sponges are important members of coral reef ecosystems. Thus, their responses to changes in ocean chemistry and environmental conditions, particularly to higher seawater temperatures, will have potential impacts on the future of these reefs. To better understand the sponge thermal stress response, we investigated gene expression dynamics in the shallow water sponge, Haliclona tubifera (order Haplosclerida, class Demospongiae), subjected to elevated temperature. Using high-throughput transcriptome sequencing, we show that these conditions result in the activation of various processes that interact to maintain cellular homeostasis. Short-term thermal stress resulted in the induction of heat shock proteins, antioxidants, and genes involved in signal transduction and innate immunity pathways. Prolonged exposure to thermal stress affected the expression of genes involved in cellular damage repair, apoptosis, signaling and transcription. Interestingly, exposure to sublethal temperatures may improve the ability of the sponge to mitigate cellular damage under more extreme stress conditions. These insights into the potential mechanisms of adaptation and resilience of sponges contribute to a better understanding of sponge conservation status and the prediction of ecosystem trajectories under future climate conditions.

Comparative Transcriptomic Analysis in Paddy Rice under Storage and Identification of Differentially Regulated Genes in Response to High Temperature and Humidity.

PubMed

Zhao, Chanjuan; Xie, Junqi; Li, Li; Cao, Chongjiang

2017-09-20

The transcriptomes of paddy rice in response to high temperature and humidity were studied using a high-throughput RNA sequencing approach. Effects of high temperature and humidity on the sucrose and starch contents and α/β-amylase activity were also investigated. Results showed that 6876 differentially expressed genes (DEGs) were identified in paddy rice under high temperature and humidity storage. Importantly, 12 DEGs that were downregulated fell into the "starch and sucrose pathway". The quantitative real-time polymerase chain reaction assays indicated that expression of these 12 DEGs was significantly decreased, which was in parallel with the reduced level of enzyme activities and the contents of sucrose and starch in paddy rice stored at high temperature and humidity conditions compared to the control group. Taken together, high temperature and humidity influence the quality of paddy rice at least partially by downregulating the expression of genes encoding sucrose transferases and hydrolases, which might result in the decrease of starch and sucrose contents.

SEURAT: visual analytics for the integrated analysis of microarray data.

PubMed

Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

2010-06-03

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

Genetic Network Inference: From Co-Expression Clustering to Reverse Engineering

NASA Technical Reports Server (NTRS)

Dhaeseleer, Patrik; Liang, Shoudan; Somogyi, Roland

2000-01-01

Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

Enhancement of SMN protein levels in a mouse model of spinal muscular atrophy using novel drug-like compounds

PubMed Central

Cherry, Jonathan J; Osman, Erkan Y; Evans, Matthew C; Choi, Sungwoon; Xing, Xuechao; Cuny, Gregory D; Glicksman, Marcie A; Lorson, Christian L; Androphy, Elliot J

2013-01-01

Spinal muscular atrophy (SMA) is a neurodegenerative disease that causes progressive muscle weakness, which primarily targets proximal muscles. About 95% of SMA cases are caused by the loss of both copies of the SMN1 gene. SMN2 is a nearly identical copy of SMN1, which expresses much less functional SMN protein. SMN2 is unable to fully compensate for the loss of SMN1 in motor neurons but does provide an excellent target for therapeutic intervention. Increased expression of functional full-length SMN protein from the endogenous SMN2 gene should lessen disease severity. We have developed and implemented a new high-throughput screening assay to identify small molecules that increase the expression of full-length SMN from a SMN2 reporter gene. Here, we characterize two novel compounds that increased SMN protein levels in both reporter cells and SMA fibroblasts and show that one increases lifespan, motor function, and SMN protein levels in a severe mouse model of SMA. PMID:23740718

Risk stratification in myelodysplastic syndromes: is there a role for gene expression profiling?

PubMed

Zeidan, Amer M; Prebet, Thomas; Saad Aldin, Ehab; Gore, Steven David

2014-04-01

Evaluation of: Pellagatti A, Benner A, Mills KI et al. Identification of gene expression-based prognostic markers in the hematopoietic stem cells of patients with myelodysplastic syndromes. J. Clin. Oncol. 31(28), 3557-3564 (2013). Patients with myelodysplastic syndromes (MDS) exhibit wide heterogeneity in clinical outcomes making accurate risk-stratification an integral part of the risk-adaptive management paradigm. Current prognostic schemes for MDS rely on clinicopathological parameters. Despite the increasing knowledge of the genetic landscape of MDS and the prognostic impact of many newly discovered molecular aberrations, none to date has been incorporated formally into the major risk models. Efforts are ongoing to use data generated from genome-wide high-throughput techniques to improve the 'individualized' outcome prediction for patients. We here discuss an important paper in which gene expression profiling (GEP) technology was applied to marrow CD34(+) cells from 125 MDS patients to generate and validate a standardized GEP-based prognostic signature.

Machine Learning Analysis Identifies Drosophila Grunge/Atrophin as an Important Learning and Memory Gene Required for Memory Retention and Social Learning.

PubMed

Kacsoh, Balint Z; Greene, Casey S; Bosco, Giovanni

2017-11-06

High-throughput experiments are becoming increasingly common, and scientists must balance hypothesis-driven experiments with genome-wide data acquisition. We sought to predict novel genes involved in Drosophila learning and long-term memory from existing public high-throughput data. We performed an analysis using PILGRM, which analyzes public gene expression compendia using machine learning. We evaluated the top prediction alongside genes involved in learning and memory in IMP, an interface for functional relationship networks. We identified Grunge/Atrophin ( Gug/Atro ), a transcriptional repressor, histone deacetylase, as our top candidate. We find, through multiple, distinct assays, that Gug has an active role as a modulator of memory retention in the fly and its function is required in the adult mushroom body. Depletion of Gug specifically in neurons of the adult mushroom body, after cell division and neuronal development is complete, suggests that Gug function is important for memory retention through regulation of neuronal activity, and not by altering neurodevelopment. Our study provides a previously uncharacterized role for Gug as a possible regulator of neuronal plasticity at the interface of memory retention and memory extinction. Copyright © 2017 Kacsoh et al.

Microarray Detection of Duplex and Triplex DNA Binders with DNA-Modified Gold Nanoparticles

PubMed Central

Lytton-Jean, Abigail K. R.; Han, Min Su; Mirkin, Chad A.

2008-01-01

We have designed a chip-based assay, using microarray technology, for determining the relative binding affinities of duplex and triplex DNA binders. This assay combines the high discrimination capabilities afforded by DNA-modified Au nanoparticles with the high-throughput capabilities of DNA microarrays. The detection and screening of duplex DNA binders are important because these molecules, in many cases, are potential anticancer agents as well as toxins. Triplex DNA binders are also promising drug candidates. These molecules, in conjunction with triplex forming oligonucleotides, could potentially be used to achieve control of gene expression by interfering with transcription factors that bind to DNA. Therefore, the ability to screen for these molecules in a high-throughput fashion could dramatically improve the drug screening process. The assay reported here provides excellent discrimination between strong, intermediate, and weak duplex and triplex DNA binders in a high-throughput fashion. PMID:17614366

Computational challenges, tools and resources for analyzing co- and post-transcriptional events in high throughput

PubMed Central

Bahrami-Samani, Emad; Vo, Dat T.; de Araujo, Patricia Rosa; Vogel, Christine; Smith, Andrew D.; Penalva, Luiz O. F.; Uren, Philip J.

2014-01-01

Co- and post-transcriptional regulation of gene expression is complex and multi-faceted, spanning the complete RNA lifecycle from genesis to decay. High-throughput profiling of the constituent events and processes is achieved through a range of technologies that continue to expand and evolve. Fully leveraging the resulting data is non-trivial, and requires the use of computational methods and tools carefully crafted for specific data sources and often intended to probe particular biological processes. Drawing upon databases of information pre-compiled by other researchers can further elevate analyses. Within this review, we describe the major co- and post-transcriptional events in the RNA lifecycle that are amenable to high-throughput profiling. We place specific emphasis on the analysis of the resulting data, in particular the computational tools and resources available, as well as looking towards future challenges that remain to be addressed. PMID:25515586

Evaluation and rational design of guide RNAs for efficient CRISPR/Cas9-mediated mutagenesis in Ciona

PubMed Central

Gandhi, Shashank; Haeussler, Maximilian; Razy-Krajka, Florian; Christiaen, Lionel; Stolfi, Alberto

2017-01-01

The CRISPR/Cas9 system has emerged as an important tool for various genome engineering applications. A current obstacle to high throughput applications of CRISPR/Cas9 is the imprecise prediction of highly active single guide RNAs (sgRNAs). We previously implemented the CRISPR/Cas9 system to induce tissue-specific mutations in the tunicate Ciona. In the present study, we designed and tested 83 single guide RNA (sgRNA) vectors targeting 23 genes expressed in the cardiopharyngeal progenitors and surrounding tissues of Ciona embryo. Using high-throughput sequencing of mutagenized alleles, we identified guide sequences that correlate with sgRNA mutagenesis activity and used this information for the rational design of all possible sgRNAs targeting the Ciona transcriptome. We also describe a one-step cloning-free protocol for the assembly of sgRNA expression cassettes. These cassettes can be directly electroporated as unpurified PCR products into Ciona embryos for sgRNA expression in vivo, resulting in high frequency of CRISPR/Cas9-mediated mutagenesis in somatic cells of electroporated embryos. We found a strong correlation between the frequency of an Ebf loss-of-function phenotype and the mutagenesis efficacies of individual Ebf-targeting sgRNAs tested using this method. We anticipate that our approach can be scaled up to systematically design and deliver highly efficient sgRNAs for the tissue-specific investigation of gene functions in Ciona. PMID:28341547

Exploration of jasmonate signalling via automated and standardized transient expression assays in tobacco cells.

PubMed

De Sutter, Valerie; Vanderhaeghen, Rudy; Tilleman, Sofie; Lammertyn, Freya; Vanhoutte, Isabelle; Karimi, Mansour; Inzé, Dirk; Goossens, Alain; Hilson, Pierre

2005-12-01

Although sequence information and genome annotation are improving at an impressive pace, functional ontology is still non-existent or rudimentary for most genes. In this regard, transient expression assays are very valuable for identification of short functional segments in particular pathways, because they can be performed rapidly and at a scale unattainable in stably transformed tissues. Vectors were constructed and protocols developed for systematic transient assays in plant protoplasts. To enhance throughput and reproducibility, protoplast treatments were performed entirely by a liquid-handling robot in multiwell plates, including polyethylene glycol/Ca2+ cell transfection with plasmid mixtures, washes and lysis. All transcriptional readouts were measured using a dual firefly/Renilla luciferase assay, in which the former was controlled by a reporter promoter and the latter by the 35S CaMV promoter, which served as internal normalization standard. The automated protocols were suitable for transient assays in protoplasts prepared from cell cultures of Nicotiana tabacum Bright Yellow-2 and Arabidopsis thaliana. They were implemented in a screen to discover potential regulators of genes coding for key enzymes in nicotine biosynthesis. Two novel tobacco transcription factors were found, NtORC1 and NtJAP1, that positively regulate the putrescine N-methyltransferase (PMT) promoter. In addition, combinatorial tests showed that these two factors act synergistically to induce PMT transcriptional activity. The development and use of high-throughput plant transient expression assays are discussed.

Identification of MicroRNAs and Their Targets Associated with Fruit-Bagging and Subsequent Sunlight Re-exposure in the “Granny Smith” Apple Exocarp Using High-Throughput Sequencing

PubMed Central

Qu, Dong; Yan, Fei; Meng, Rui; Jiang, Xiaobing; Yang, Huijuan; Gao, Ziyi; Dong, Yonghui; Yang, Yazhou; Zhao, Zhengyang

2016-01-01

Bagged fruits of green apple cultivar “Granny Smith” have been found to turn cardinal red after debagging during fruit-ripening in the Loess Plateau region of China. To understand this phenomenon at post-transcriptional level, we have investigated the roles of microRNAs (miRNAs) in response to debagging. Three small RNA libraries were primarily constructed from peels of “Granny Smith” apples subjected to bagging followed by sunlight re-exposure treatments (0, 6 h, 1 day) (debagging), and from peels of apples without any bagging treatments (0, 6 h, 1 day). 201 known miRNAs belonging to 43 miRNA families and 220 novel miRNAs were identified via high-throughput sequencing. Some miRNAs were found to be differentially expressed after debagging, which indicated that miRNAs affected anthocyanin accumulation through their target genes in mature apple. To further explore the effect of debagging on miRNAs regulating the expression of anthocyanin regulatory genes, four miRNAs and their target genes regulating anthocyanin accumulation, miR156, miR828, miR858, and miR5072, were compared between green cultivar “Granny Smith” and red cultivar “Starkrimson.” Results showed that mdm-miR828 and mdm-miR858 regulated anthocyanin contents in both apple cultivars, while mdm-miR156 only affected anthocyanin accumulation in “Granny Smith,” and miR5072 affected anthocyanin accumulation in “Starkrimson.” Additional analysis of gene ontology for the differentially expressed miRNAs after debagging treatments and their predicted target genes showed that they were involved in photo-protective response after debagging from 0 h to 1 day; they might play important roles in fruit development and adaptation to high light stress. PMID:26870053

Genome-Wide Tuning of Protein Expression Levels to Rapidly Engineer Microbial Traits.

PubMed

Freed, Emily F; Winkler, James D; Weiss, Sophie J; Garst, Andrew D; Mutalik, Vivek K; Arkin, Adam P; Knight, Rob; Gill, Ryan T

2015-11-20

The reliable engineering of biological systems requires quantitative mapping of predictable and context-independent expression over a broad range of protein expression levels. However, current techniques for modifying expression levels are cumbersome and are not amenable to high-throughput approaches. Here we present major improvements to current techniques through the design and construction of E. coli genome-wide libraries using synthetic DNA cassettes that can tune expression over a ∼10(4) range. The cassettes also contain molecular barcodes that are optimized for next-generation sequencing, enabling rapid and quantitative tracking of alleles that have the highest fitness advantage. We show these libraries can be used to determine which genes and expression levels confer greater fitness to E. coli under different growth conditions.

Integrated analysis of mRNA and miRNA expression profiling in rice backcrossed progenies (BC2F12) with different plant height

PubMed Central

Cao, Aqin; Jin, Jie; Li, Shaoqing

2017-01-01

Inter-specific hybridization and backcrossing commonly occur in plants. The use of progeny generated from inter-specific hybridization and backcrossing has been developed as a novel model system to explore gene expression divergence. The present study investigated the analysis of gene expression and miRNA regulation in backcrossed introgression lines constructed from cultivated and wild rice. High-throughput sequencing was used to compare gene and miRNA expression profiles in three progeny lines (L1710, L1817 and L1730), with different plant heights resulting from the backcrossing of introgression lines (BC2F12) and their parents (O. sativa and O. longistaminata). A total of 25,387 to 26,139 mRNAs and 379 to 419 miRNAs were obtained in these rice lines. More differentially expressed genes and miRNAs were detected in progeny/O. longistaminata comparison groups than in progeny/O. sativa comparison groups. Approximately 80% of the genes and miRNAs showed expression level dominance to O. sativa, indicating that three progeny lines were closer to the recurrent parent, which might be influenced by their parental genome dosage. Approximately 16% to 64% of the differentially expressed miRNAs possessing coherent target genes were predicted, and many of these miRNAs regulated multiple target genes. Most genes were up-regulated in progeny lines compared with their parents, but down-regulated in the higher plant height line in the comparison groups among the three progeny lines. Moreover, certain genes related to cell walls and plant hormones might play crucial roles in the plant height variations of the three progeny lines. Taken together, these results provided valuable information on the molecular mechanisms of hybrid backcrossing and plant height variations based on the gene and miRNA expression levels in the three progeny lines. PMID:28859136

Conceptualizing adverse outcome pathways for ...

EPA Pesticide Factsheets

Cyclooxygenase (COX) inhibition is of concern in fish because COX inhibitors (e.g., ibuprofen) are ubiquitous in aquatic systems/fish tissues, and can disrupt synthesis of prostaglandins that modulate a variety of essential biological functions (e.g., reproduction). This study utilized newly generated high content (transcriptomic and metabolomic) empirical data in combination with existing high throughput (ACTOR, epa.gov) toxicity data to facilitate development of adverse outcome pathways (AOPs) for molecular initiating event (MIE) of COX inhibition. We examined effects of a waterborne, 96h exposure to three COX inhibitors (indomethacin (IN; 100 µg/L), ibuprofen (IB; 200 µg/L) and celecoxib (CX; 20 µg/L) on the liver metabolome and ovarian gene expression (using oligonucleotide microarray 4 x15K platform) in sexually mature fathead minnows (n=8). Differentially expressed genes were identified (t-test, p < 0.01), and functional analyses performed to determine enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (p < 0.05). Principal component analysis indicated that liver metabolomics profiles of IN, IB and CX were not significantly different from control or one another. When compared to control, exposure to IB and CX resulted in differential expression of comparable numbers of genes (IB = 433, CX= 545). In contrast, 2558 genes were differentially expressed in IN-treated fish. KEGG pathway analyses show that IN had extensive effects on oocyte meios

NvERTx: a gene expression database to compare embryogenesis and regeneration in the sea anemone Nematostella vectensis.

PubMed

Warner, Jacob F; Guerlais, Vincent; Amiel, Aldine R; Johnston, Hereroa; Nedoncelle, Karine; Röttinger, Eric

2018-05-17

For over a century, researchers have been comparing embryogenesis and regeneration hoping that lessons learned from embryonic development will unlock hidden regenerative potential. This problem has historically been a difficult one to investigate because the best regenerative model systems are poor embryonic models and vice versa. Recently, however, there has been renewed interest in this question, as emerging models have allowed researchers to investigate these processes in the same organism. This interest has been further fueled by the advent of high-throughput transcriptomic analyses that provide virtual mountains of data. Here, we present N ematostella vectensis Embryogenesis and Regeneration Transcriptomics (NvERTx), a platform for comparing gene expression during embryogenesis and regeneration. NvERTx consists of close to 50 transcriptomic data sets spanning embryogenesis and regeneration in Nematostella These data were used to perform a robust de novo transcriptome assembly, with which users can search, conduct BLAST analyses, and plot the expression of multiple genes during these two developmental processes. The site is also home to the results of gene clustering analyses, to further mine the data and identify groups of co-expressed genes. The site can be accessed at http://nvertx.kahikai.org. © 2018. Published by The Company of Biologists Ltd.

Evolutionary origin and functional divergence of totipotent cell homeobox genes in eutherian mammals.

PubMed

Maeso, Ignacio; Dunwell, Thomas L; Wyatt, Chris D R; Marlétaz, Ferdinand; Vető, Borbála; Bernal, Juan A; Quah, Shan; Irimia, Manuel; Holland, Peter W H

2016-06-13

A central goal of evolutionary biology is to link genomic change to phenotypic evolution. The origin of new transcription factors is a special case of genomic evolution since it brings opportunities for novel regulatory interactions and potentially the emergence of new biological properties. We demonstrate that a group of four homeobox gene families (Argfx, Leutx, Dprx, Tprx), plus a gene newly described here (Pargfx), arose by tandem gene duplication from the retinal-expressed Crx gene, followed by asymmetric sequence evolution. We show these genes arose as part of repeated gene gain and loss events on a dynamic chromosomal region in the stem lineage of placental mammals, on the forerunner of human chromosome 19. The human orthologues of these genes are expressed specifically in early embryo totipotent cells, peaking from 8-cell to morula, prior to cell fate restrictions; cow orthologues have similar expression. To examine biological roles, we used ectopic gene expression in cultured human cells followed by high-throughput RNA-seq and uncovered extensive transcriptional remodelling driven by three of the genes. Comparison to transcriptional profiles of early human embryos suggest roles in activating and repressing a set of developmentally-important genes that spike at 8-cell to morula, rather than a general role in genome activation. We conclude that a dynamic chromosome region spawned a set of evolutionarily new homeobox genes, the ETCHbox genes, specifically in eutherian mammals. After these genes diverged from the parental Crx gene, we argue they were recruited for roles in the preimplantation embryo including activation of genes at the 8-cell stage and repression after morula. We propose these new homeobox gene roles permitted fine-tuning of cell fate decisions necessary for specification and function of embryonic and extra-embryonic tissues utilised in mammalian development and pregnancy.

Epigenetic Loss of MLH1 Expression in Normal Human Hematopoietic Stem Cell Clones is Defined by the Promoter CpG Methylation Pattern Observed by High-Throughput Methylation Specific Sequencing

PubMed Central

Kenyon, Jonathan; Nickel-Meester, Gabrielle; Qing, Yulan; Santos-Guasch, Gabriela; Drake, Ellen; PingfuFu; Sun, Shuying; Bai, Xiaodong; Wald, David; Arts, Eric; Gerson, Stanton L.

2016-01-01

Normal human hematopoietic stem and progenitor cells (HPC) lose expression of MLH1, an important mismatch repair (MMR) pathway gene, with age. Loss of MMR leads to replication dependent mutational events and microsatellite instability observed in secondary acute myelogenous leukemia and other hematologic malignancies. Epigenetic CpG methylation upstream of the MLH1 promoter is a contributing factor to acquired loss of MLH1 expression in tumors of the epithelia and proximal mucosa. Using single molecule high-throughput bisulfite sequencing we have characterized the CpG methylation landscape from −938 to −337 bp upstream of the MLH1 transcriptional start site (position +0), from 30 hematopoietic colony forming cell clones (CFC) either expressing or not expressing MLH1. We identify a correlation between MLH1 promoter methylation and loss of MLH1 expression. Additionally, using the CpG site methylation frequencies obtained in this study we were able to generate a classification algorithm capable of sorting the expressing and non-expressing CFC. Thus, as has been previously described for many tumor cell types, we report for the first time a correlation between the loss of MLH1 expression and increased MLH1 promoter methylation in CFC derived from CD34+ selected hematopoietic stem and progenitor cells. PMID:27570841

Epigenetic Loss of MLH1 Expression in Normal Human Hematopoietic Stem Cell Clones is Defined by the Promoter CpG Methylation Pattern Observed by High-Throughput Methylation Specific Sequencing.

PubMed

Kenyon, Jonathan; Nickel-Meester, Gabrielle; Qing, Yulan; Santos-Guasch, Gabriela; Drake, Ellen; PingfuFu; Sun, Shuying; Bai, Xiaodong; Wald, David; Arts, Eric; Gerson, Stanton L

Normal human hematopoietic stem and progenitor cells (HPC) lose expression of MLH1 , an important mismatch repair (MMR) pathway gene, with age. Loss of MMR leads to replication dependent mutational events and microsatellite instability observed in secondary acute myelogenous leukemia and other hematologic malignancies. Epigenetic CpG methylation upstream of the MLH1 promoter is a contributing factor to acquired loss of MLH1 expression in tumors of the epithelia and proximal mucosa. Using single molecule high-throughput bisulfite sequencing we have characterized the CpG methylation landscape from -938 to -337 bp upstream of the MLH1 transcriptional start site (position +0), from 30 hematopoietic colony forming cell clones (CFC) either expressing or not expressing MLH1 . We identify a correlation between MLH1 promoter methylation and loss of MLH1 expression. Additionally, using the CpG site methylation frequencies obtained in this study we were able to generate a classification algorithm capable of sorting the expressing and non-expressing CFC. Thus, as has been previously described for many tumor cell types, we report for the first time a correlation between the loss of MLH1 expression and increased MLH1 promoter methylation in CFC derived from CD34 + selected hematopoietic stem and progenitor cells.

Identification and comparative analysis of the microRNA transcriptome in roots of two contrasting tobacco genotypes in response to cadmium stress

NASA Astrophysics Data System (ADS)

He, Xiaoyan; Zheng, Weite; Cao, Fangbin; Wu, Feibo

2016-09-01

Tobacco (Nicotiana tabacum L.) is more acclimated to cadmium (Cd) uptake and preferentially enriches Cd in leaves than other crops. MicroRNAs (miRNAs) play crucial roles in regulating expression of various stress response genes in plants. However, genome-wide expression of miRNAs and their target genes in response to Cd stress in tobacco are still unknown. Here, miRNA high-throughput sequencing technology was performed using two contrasting tobacco genotypes Guiyan 1 and Yunyan 2 of Cd-sensitive and tolerance. Comprehensive analysis of miRNA expression profiles in control and Cd treated plants identified 72 known (27 families) and 14 novel differentially expressed miRNAs in the two genotypes. Among them, 28 known (14 families) and 5 novel miRNAs were considered as Cd tolerance associated miRNAs, which mainly involved in cell growth, ion homeostasis, stress defense, antioxidant and hormone signaling. Finally, a hypothetical model of Cd tolerance mechanism in Yunyan 2 was presented. Our findings suggest that some miRNAs and their target genes and pathways may play critical roles in Cd tolerance.

Pervasive Effects of Aging on Gene Expression in Wild Wolves.

PubMed

Charruau, Pauline; Johnston, Rachel A; Stahler, Daniel R; Lea, Amanda; Snyder-Mackler, Noah; Smith, Douglas W; vonHoldt, Bridgett M; Cole, Steven W; Tung, Jenny; Wayne, Robert K

2016-08-01

Gene expression levels change as an individual ages and responds to environmental conditions. With the exception of humans, such patterns have principally been studied under controlled conditions, overlooking the array of developmental and environmental influences that organisms encounter under conditions in which natural selection operates. We used high-throughput RNA sequencing (RNA-Seq) of whole blood to assess the relative impacts of social status, age, disease, and sex on gene expression levels in a natural population of gray wolves (Canis lupus). Our findings suggest that age is broadly associated with gene expression levels, whereas other examined factors have minimal effects on gene expression patterns. Further, our results reveal evolutionarily conserved signatures of senescence, such as immunosenescence and metabolic aging, between wolves and humans despite major differences in life history and environment. The effects of aging on gene expression levels in wolves exhibit conservation with humans, but the more rapid expression differences observed in aging wolves is evolutionarily appropriate given the species' high level of extrinsic mortality due to intraspecific aggression. Some expression changes that occur with age can facilitate physical age-related changes that may enhance fitness in older wolves. However, the expression of these ancestral patterns of aging in descendant modern dogs living in highly modified domestic environments may be maladaptive and cause disease. This work provides evolutionary insight into aging patterns observed in domestic dogs and demonstrates the applicability of studying natural populations to investigate the mechanisms of aging. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Discovering Protein-Coding Genes from the Environment: Time for the Eukaryotes?

PubMed

Marmeisse, Roland; Kellner, Harald; Fraissinet-Tachet, Laurence; Luis, Patricia

2017-09-01

Eukaryotic microorganisms from diverse environments encompass a large number of taxa, many of them still unknown to science. One strategy to mine these organisms for genes of biotechnological relevance is to use a pool of eukaryotic mRNA directly extracted from environmental samples. Recent reports demonstrate that the resulting metatranscriptomic cDNA libraries can be screened by expression in yeast for a wide range of genes and functions from many of the different eukaryotic taxa. In combination with novel emerging high-throughput technologies, we anticipate that this approach should contribute to exploring the functional diversity of the eukaryotic microbiota. Copyright © 2017 Elsevier Ltd. All rights reserved.

Strategies to explore functional genomics data sets in NCBI's GEO database.

PubMed

Wilhite, Stephen E; Barrett, Tanya

2012-01-01

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze, and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries.

Strategies to Explore Functional Genomics Data Sets in NCBI’s GEO Database

PubMed Central

Wilhite, Stephen E.; Barrett, Tanya

2012-01-01

The Gene Expression Omnibus (GEO) database is a major repository that stores high-throughput functional genomics data sets that are generated using both microarray-based and sequence-based technologies. Data sets are submitted to GEO primarily by researchers who are publishing their results in journals that require original data to be made freely available for review and analysis. In addition to serving as a public archive for these data, GEO has a suite of tools that allow users to identify, analyze and visualize data relevant to their specific interests. These tools include sample comparison applications, gene expression profile charts, data set clusters, genome browser tracks, and a powerful search engine that enables users to construct complex queries. PMID:22130872

A multi-strategy approach to informative gene identification from gene expression data.

PubMed

Liu, Ziying; Phan, Sieu; Famili, Fazel; Pan, Youlian; Lenferink, Anne E G; Cantin, Christiane; Collins, Catherine; O'Connor-McCourt, Maureen D

2010-02-01

An unsupervised multi-strategy approach has been developed to identify informative genes from high throughput genomic data. Several statistical methods have been used in the field to identify differentially expressed genes. Since different methods generate different lists of genes, it is very challenging to determine the most reliable gene list and the appropriate method. This paper presents a multi-strategy method, in which a combination of several data analysis techniques are applied to a given dataset and a confidence measure is established to select genes from the gene lists generated by these techniques to form the core of our final selection. The remainder of the genes that form the peripheral region are subject to exclusion or inclusion into the final selection. This paper demonstrates this methodology through its application to an in-house cancer genomics dataset and a public dataset. The results indicate that our method provides more reliable list of genes, which are validated using biological knowledge, biological experiments, and literature search. We further evaluated our multi-strategy method by consolidating two pairs of independent datasets, each pair is for the same disease, but generated by different labs using different platforms. The results showed that our method has produced far better results.

A gene expression signature associated with survival in metastatic melanoma

PubMed Central

Mandruzzato, Susanna; Callegaro, Andrea; Turcatel, Gianluca; Francescato, Samuela; Montesco, Maria C; Chiarion-Sileni, Vanna; Mocellin, Simone; Rossi, Carlo R; Bicciato, Silvio; Wang, Ena; Marincola, Francesco M; Zanovello, Paola

2006-01-01

Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells. PMID:17129373

Impact of Profiling Technologies in the Understanding of Recombinant Protein Production

NASA Astrophysics Data System (ADS)

Vijayendran, Chandran; Flaschel, Erwin

Since expression profiling methods have been available in a high throughput fashion, the implication of these technologies in the field of biotechnology has increased dramatically. Microarray technology is one such unique and efficient methodology for simultaneous exploration of expression levels of numerous genes. Likewise, two-dimensional gel electrophoresis or multidimensional liquid chromatography coupled with mass spectrometry are extensively utilised for studying expression levels of numerous proteins. In the field of biotechnology these highly parallel analytical methods have paved the way to study and understand various biological phenomena depending on expression patterns. The next phenomenological level is represented by the metabolome and the (metabolic) fluxome. However, this chapter reviews gene and protein profiling and their impact on understanding recombinant protein production. We focus on the computational methods utilised for the analyses of data obtained from these profiling technologies as well as prominent results focusing on recombinant protein expression with Escherichia coli. Owing to the knowledge accumulated with respect to cellular signals triggered during recombinant protein production, this field is on the way to design strategies for developing improved processes. Both gene and protein profiling have exhibited a handful of functional categories to concentrate on in order to identify target genes and proteins, respectively, involved in the signalling network with major impact on recombinant protein production.

Enrichment and isolation of neurons from adult mouse brain for ex vivo analysis.

PubMed

Berl, Sabina; Karram, Khalad; Scheller, Anja; Jungblut, Melanie; Kirchhoff, Frank; Waisman, Ari

2017-05-01

Isolation of neurons from the adult mouse CNS is important in order to study their gene expression during development or the course of different diseases. Here we present two different methods for the enrichment or isolation of neurons from adult mouse CNS. These methods: are either based on flow cytometry sorting of eYFP expressing neurons, or by depletion of non-neuronal cells by sorting with magnetic-beads. Enrichment by FACS sorting of eYFP positive neurons results in a population of 62.4% NeuN positive living neurons. qPCR data shows a 3-5fold upregulation of neuronal markers. The isolation of neurons based on depletion of non-neuronal cells using the Miltenyi Neuron Isolation Kit, reaches a purity of up to 86.5%. qPCR data of these isolated neurons shows an increase in neuronal markers and an absence of glial markers, proving pure neuronal RNA isolation. Former data related to neuronal gene expression are mainly based on histology, which does not allow for high-throughput transcriptome analysis to examine differential gene expression. These protocols can be used to study cell type specific gene expression of neurons to unravel their function in the process of damage to the CNS. Copyright © 2017 Elsevier B.V. All rights reserved.

Distinct Strains of Toxoplasma gondii Feature Divergent Transcriptomes Regardless of Developmental Stage

DOE PAGES

Croken, Matthew; Ma, Yan Fen; Markillie, Lye Meng; ...

2014-11-13

Using high through-put RNA sequencing, we assayed the transcriptomes of three different strains of Toxoplasma gondii representing three common genotypes under both in vitro tachyzoite and in vitro bradyzoite-inducing alkaline stress culture conditions. Strikingly, the differences in transcriptional profiles between the strains, RH, PLK, and CTG, is much greater than differences between tachyzoites and alkaline stressed in vitro bradyzoites. With an FDR of 10%, we identify 241 genes differentially expressed between CTG tachyzoites and in vitro bradyzoites, including 5 putative AP2 transcription factors. We also observe close association between cell cycle regulated genes and differentiation. By Gene Set Enrichment Analysismore » (GSEA), there are a number of KEGG pathways associated with the in vitro bradyzoite transcriptomes of PLK and CTG, including pyrimidine metabolism and DNA replication. These functions are likely associated with cell-cycle arrest. When comparing mRNA levels between strains, we identify 1,526 genes that are differentially expressed regardless of culture-condition as well as 846 differentially expressed only in bradyzoites and 542 differentially expressed only in tachyzoites between at least two strains. Using GSEA, we identify ribosomal proteins as being expressed at significantly higher levels in the CTG strain than in either the RH or PLK strains. This association holds true regardless of life cycle stage.« less

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

PubMed

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-06-01

Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

Dynamic Visualization of Co-expression in Systems Genetics Data

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

New, Joshua Ryan; Huang, Jian; Chesler, Elissa J

2008-01-01

Biologists hope to address grand scientific challenges by exploring the abundance of data made available through modern microarray technology and other high-throughput techniques. The impact of this data, however, is limited unless researchers can effectively assimilate such complex information and integrate it into their daily research; interactive visualization tools are called for to support the effort. Specifically, typical studies of gene co-expression require novel visualization tools that enable the dynamic formulation and fine-tuning of hypotheses to aid the process of evaluating sensitivity of key parameters. These tools should allow biologists to develop an intuitive understanding of the structure of biologicalmore » networks and discover genes which reside in critical positions in networks and pathways. By using a graph as a universal data representation of correlation in gene expression data, our novel visualization tool employs several techniques that when used in an integrated manner provide innovative analytical capabilities. Our tool for interacting with gene co-expression data integrates techniques such as: graph layout, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by querying an optimized b-tree, dynamic level-of-detail graph abstraction, and template-based fuzzy classification using neural networks. We demonstrate our system using a real-world workflow from a large-scale, systems genetics study of mammalian gene co-expression.« less

A High-Throughput Fluorescence-Based Assay System for Appetite-Regulating Gene and Drug Screening

PubMed Central

Shimada, Yasuhito; Hirano, Minoru; Nishimura, Yuhei; Tanaka, Toshio

2012-01-01

The increasing number of people suffering from metabolic syndrome and obesity is becoming a serious problem not only in developed countries, but also in developing countries. However, there are few agents currently approved for the treatment of obesity. Those that are available are mainly appetite suppressants and gastrointestinal fat blockers. We have developed a simple and rapid method for the measurement of the feeding volume of Danio rerio (zebrafish). This assay can be used to screen appetite suppressants and enhancers. In this study, zebrafish were fed viable paramecia that were fluorescently-labeled, and feeding volume was measured using a 96-well microplate reader. Gene expression analysis of brain-derived neurotrophic factor (bdnf), knockdown of appetite-regulating genes (neuropeptide Y, preproinsulin, melanocortin 4 receptor, agouti related protein, and cannabinoid receptor 1), and the administration of clinical appetite suppressants (fluoxetine, sibutramine, mazindol, phentermine, and rimonabant) revealed the similarity among mechanisms regulating appetite in zebrafish and mammals. In combination with behavioral analysis, we were able to evaluate adverse effects on locomotor activities from gene knockdown and chemical treatments. In conclusion, we have developed an assay that uses zebrafish, which can be applied to high-throughput screening and target gene discovery for appetite suppressants and enhancers. PMID:23300705

Whole-transcriptome, high-throughput RNA sequence analysis of the bovine macrophage response to Mycobacterium bovis infection in vitro.

PubMed

Nalpas, Nicolas C; Park, Stephen D E; Magee, David A; Taraktsoglou, Maria; Browne, John A; Conlon, Kevin M; Rue-Albrecht, Kévin; Killick, Kate E; Hokamp, Karsten; Lohan, Amanda J; Loftus, Brendan J; Gormley, Eamonn; Gordon, Stephen V; MacHugh, David E

2013-04-08

Mycobacterium bovis, the causative agent of bovine tuberculosis, is an intracellular pathogen that can persist inside host macrophages during infection via a diverse range of mechanisms that subvert the host immune response. In the current study, we have analysed and compared the transcriptomes of M. bovis-infected monocyte-derived macrophages (MDM) purified from six Holstein-Friesian females with the transcriptomes of non-infected control MDM from the same animals over a 24 h period using strand-specific RNA sequencing (RNA-seq). In addition, we compare gene expression profiles generated using RNA-seq with those previously generated by us using the high-density Affymetrix® GeneChip® Bovine Genome Array platform from the same MDM-extracted RNA. A mean of 7.2 million reads from each MDM sample mapped uniquely and unambiguously to single Bos taurus reference genome locations. Analysis of these mapped reads showed 2,584 genes (1,392 upregulated; 1,192 downregulated) and 757 putative natural antisense transcripts (558 upregulated; 119 downregulated) that were differentially expressed based on sense and antisense strand data, respectively (adjusted P-value ≤ 0.05). Of the differentially expressed genes, 694 were common to both the sense and antisense data sets, with the direction of expression (i.e. up- or downregulation) positively correlated for 693 genes and negatively correlated for the remaining gene. Gene ontology analysis of the differentially expressed genes revealed an enrichment of immune, apoptotic and cell signalling genes. Notably, the number of differentially expressed genes identified from RNA-seq sense strand analysis was greater than the number of differentially expressed genes detected from microarray analysis (2,584 genes versus 2,015 genes). Furthermore, our data reveal a greater dynamic range in the detection and quantification of gene transcripts for RNA-seq compared to microarray technology. This study highlights the value of RNA-seq in identifying novel immunomodulatory mechanisms that underlie host-mycobacterial pathogen interactions during infection, including possible complex post-transcriptional regulation of host gene expression involving antisense RNA.

GEO2Enrichr: browser extension and server app to extract gene sets from GEO and analyze them for biological functions.

PubMed

Gundersen, Gregory W; Jones, Matthew R; Rouillard, Andrew D; Kou, Yan; Monteiro, Caroline D; Feldmann, Axel S; Hu, Kevin S; Ma'ayan, Avi

2015-09-15

Identification of differentially expressed genes is an important step in extracting knowledge from gene expression profiling studies. The raw expression data from microarray and other high-throughput technologies is deposited into the Gene Expression Omnibus (GEO) and served as Simple Omnibus Format in Text (SOFT) files. However, to extract and analyze differentially expressed genes from GEO requires significant computational skills. Here we introduce GEO2Enrichr, a browser extension for extracting differentially expressed gene sets from GEO and analyzing those sets with Enrichr, an independent gene set enrichment analysis tool containing over 70 000 annotated gene sets organized into 75 gene-set libraries. GEO2Enrichr adds JavaScript code to GEO web-pages; this code scrapes user selected accession numbers and metadata, and then, with one click, users can submit this information to a web-server application that downloads the SOFT files, parses, cleans and normalizes the data, identifies the differentially expressed genes, and then pipes the resulting gene lists to Enrichr for downstream functional analysis. GEO2Enrichr opens a new avenue for adding functionality to major bioinformatics resources such GEO by integrating tools and resources without the need for a plug-in architecture. Importantly, GEO2Enrichr helps researchers to quickly explore hypotheses with little technical overhead, lowering the barrier of entry for biologists by automating data processing steps needed for knowledge extraction from the major repository GEO. GEO2Enrichr is an open source tool, freely available for installation as browser extensions at the Chrome Web Store and FireFox Add-ons. Documentation and a browser independent web application can be found at http://amp.pharm.mssm.edu/g2e/. avi.maayan@mssm.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Drug repositioning for orphan genetic diseases through Conserved Anticoexpressed Gene Clusters (CAGCs)

PubMed Central

2013-01-01

Background The development of new therapies for orphan genetic diseases represents an extremely important medical and social challenge. Drug repositioning, i.e. finding new indications for approved drugs, could be one of the most cost- and time-effective strategies to cope with this problem, at least in a subset of cases. Therefore, many computational approaches based on the analysis of high throughput gene expression data have so far been proposed to reposition available drugs. However, most of these methods require gene expression profiles directly relevant to the pathologic conditions under study, such as those obtained from patient cells and/or from suitable experimental models. In this work we have developed a new approach for drug repositioning, based on identifying known drug targets showing conserved anti-correlated expression profiles with human disease genes, which is completely independent from the availability of ‘ad hoc’ gene expression data-sets. Results By analyzing available data, we provide evidence that the genes displaying conserved anti-correlation with drug targets are antagonistically modulated in their expression by treatment with the relevant drugs. We then identified clusters of genes associated to similar phenotypes and showing conserved anticorrelation with drug targets. On this basis, we generated a list of potential candidate drug-disease associations. Importantly, we show that some of the proposed associations are already supported by independent experimental evidence. Conclusions Our results support the hypothesis that the identification of gene clusters showing conserved anticorrelation with drug targets can be an effective method for drug repositioning and provide a wide list of new potential drug-disease associations for experimental validation. PMID:24088245

Differential deposition of H2A.Z in rice seedling tissue during the day-night cycle.

PubMed

Zhang, Kang; Xu, Wenying; Wang, Chunchao; Yi, Xin; Su, Zhen

2017-03-04

Chromatin structure has an important role in modulating gene expression. The incorporation of histone variants into the nucleosome leads to important changes in the chromatin structure. The histone variant H2A.Z is highly conserved between different species of fungi, animals, and plants. However, dynamic changes to H2A.Z in rice have not been reported during the day-night cycle. In this study, we generated genome wide maps of H2A.Z for day and night time in harvested seedling tissues by combining chromatin immunoprecipitation and high-throughput sequencing. The analysis results for the H2A.Z data sets detected 7099 genes with higher depositions of H2A.Z in seedling tissues harvested at night compared with seedling tissues harvested during the day, whereas 4597 genes had higher H2A.Z depositions in seedlings harvested during the day. The gene expression profiles data suggested that H2A.Z probably negatively regulated gene expression during the day-night cycle and was involved in many important biologic processes. In general, our results indicated that H2A.Z may play an important role in plant responses to the diurnal oscillation process.

Comparative Transcriptomic Characterization of the Early Development in Pacific White Shrimp Litopenaeus vannamei

PubMed Central

Wei, Jiankai; Zhang, Xiaojun; Yu, Yang; Huang, Hao; Li, Fuhua; Xiang, Jianhai

2014-01-01

Penaeid shrimp has a distinctive metamorphosis stage during early development. Although morphological and biochemical studies about this ontogeny have been developed for decades, researches on gene expression level are still scarce. In this study, we have investigated the transcriptomes of five continuous developmental stages in Pacific white shrimp (Litopenaeus vannamei) with high throughput Illumina sequencing technology. The reads were assembled and clustered into 66,815 unigenes, of which 32,398 have putative homologues in nr database, 14,981 have been classified into diverse functional categories by Gene Ontology (GO) annotation and 26,257 have been associated with 255 pathways by KEGG pathway mapping. Meanwhile, the differentially expressed genes (DEGs) between adjacent developmental stages were identified and gene expression patterns were clustered. By GO term enrichment analysis, KEGG pathway enrichment analysis and functional gene profiling, the physiological changes during shrimp metamorphosis could be better understood, especially histogenesis, diet transition, muscle development and exoskeleton reconstruction. In conclusion, this is the first study that characterized the integrated transcriptomic profiles during early development of penaeid shrimp, and these findings will serve as significant references for shrimp developmental biology and aquaculture research. PMID:25197823

Transcriptome Sequencing of Gracilariopsis lemaneiformis to Analyze the Genes Related to Optically Active Phycoerythrin Synthesis.

PubMed

Huang, Xiaoyun; Zang, Xiaonan; Wu, Fei; Jin, Yuming; Wang, Haitao; Liu, Chang; Ding, Yating; He, Bangxiang; Xiao, Dongfang; Song, Xinwei; Liu, Zhu

2017-01-01

Gracilariopsis lemaneiformis (aka Gracilaria lemaneiformis) is a red macroalga rich in phycoerythrin, which can capture light efficiently and transfer it to photosystemⅡ. However, little is known about the synthesis of optically active phycoerythrinin in G. lemaneiformis at the molecular level. With the advent of high-throughput sequencing technology, analysis of genetic information for G. lemaneiformis by transcriptome sequencing is an effective means to get a deeper insight into the molecular mechanism of phycoerythrin synthesis. Illumina technology was employed to sequence the transcriptome of two strains of G. lemaneiformis- the wild type and a green-pigmented mutant. We obtained a total of 86915 assembled unigenes as a reference gene set, and 42884 unigenes were annotated in at least one public database. Taking the above transcriptome sequencing as a reference gene set, 4041 differentially expressed genes were screened to analyze and compare the gene expression profiles of the wild type and green mutant. By GO and KEGG pathway analysis, we concluded that three factors, including a reduction in the expression level of apo-phycoerythrin, an increase of chlorophyll light-harvesting complex synthesis, and reduction of phycoerythrobilin by competitive inhibition, caused the reduction of optically active phycoerythrin in the green-pigmented mutant.

NetMiner-an ensemble pipeline for building genome-wide and high-quality gene co-expression network using massive-scale RNA-seq samples.

PubMed

Yu, Hua; Jiao, Bingke; Lu, Lu; Wang, Pengfei; Chen, Shuangcheng; Liang, Chengzhi; Liu, Wei

2018-01-01

Accurately reconstructing gene co-expression network is of great importance for uncovering the genetic architecture underlying complex and various phenotypes. The recent availability of high-throughput RNA-seq sequencing has made genome-wide detecting and quantifying of the novel, rare and low-abundance transcripts practical. However, its potential merits in reconstructing gene co-expression network have still not been well explored. Using massive-scale RNA-seq samples, we have designed an ensemble pipeline, called NetMiner, for building genome-scale and high-quality Gene Co-expression Network (GCN) by integrating three frequently used inference algorithms. We constructed a RNA-seq-based GCN in one species of monocot rice. The quality of network obtained by our method was verified and evaluated by the curated gene functional association data sets, which obviously outperformed each single method. In addition, the powerful capability of network for associating genes with functions and agronomic traits was shown by enrichment analysis and case studies. In particular, we demonstrated the potential value of our proposed method to predict the biological roles of unknown protein-coding genes, long non-coding RNA (lncRNA) genes and circular RNA (circRNA) genes. Our results provided a valuable and highly reliable data source to select key candidate genes for subsequent experimental validation. To facilitate identification of novel genes regulating important biological processes and phenotypes in other plants or animals, we have published the source code of NetMiner, making it freely available at https://github.com/czllab/NetMiner.

Transcriptome Characterization Analysis of Bactrocera minax and New Insights into Its Pupal Diapause Development with Gene Expression Analysis

PubMed Central

Dong, Yongcheng; Desneux, Nicolas; Lei, Chaoliang; Niu, Changying

2014-01-01

Bactrocera minax is a major citrus pest distributed in China, Bhutan and India. The long pupal diapause duration of this fly is a major bottleneck for artificial rearing and underlying mechanisms remain unknown. Genetic information on B. minax transcriptome and gene expression profiles are needed to understand its pupal diapause. High-throughput RNA-seq technology was used to characterize the B. minax transcriptome and to identify differentially expressed genes during pupal diapause development. A total number of 52,519,948 reads were generated and assembled into 47,217 unigenes. 26,843 unigenes matched to proteins in the NCBI database using the BLAST search. Four digital gene expression (DGE) libraries were constructed for pupae at early diapause, late diapause, post-diapause and diapause terminated developmental status. 4,355 unigenes showing the differences expressed across four libraries revealed major shifts in cellular functions of cell proliferation, protein processing and export, metabolism and stress response in pupal diapause. When diapause was terminated by 20-hydroxyecdysone (20E), many genes involved in ribosome and metabolism were differentially expressed which may mediate diapause transition. The gene sets involved in protein and energy metabolisms varied throughout early-, late- and post-diapause. A total of 15 genes were selected to verify the DGE results through quantitative real-time PCR (qRT-PCR); qRT-PCR expression levels strongly correlated with the DGE data. The results provided the extensive sequence resources available for B. minax and increased our knowledge on its pupal diapause development and they shed new light on the possible mechanisms involved in pupal diapause in this species. PMID:25285037

Molecular Structure-Based Large-Scale Prediction of Chemical-Induced Gene Expression Changes.

PubMed

Liu, Ruifeng; AbdulHameed, Mohamed Diwan M; Wallqvist, Anders

2017-09-25

The quantitative structure-activity relationship (QSAR) approach has been used to model a wide range of chemical-induced biological responses. However, it had not been utilized to model chemical-induced genomewide gene expression changes until very recently, owing to the complexity of training and evaluating a very large number of models. To address this issue, we examined the performance of a variable nearest neighbor (v-NN) method that uses information on near neighbors conforming to the principle that similar structures have similar activities. Using a data set of gene expression signatures of 13 150 compounds derived from cell-based measurements in the NIH Library of Integrated Network-based Cellular Signatures program, we were able to make predictions for 62% of the compounds in a 10-fold cross validation test, with a correlation coefficient of 0.61 between the predicted and experimentally derived signatures-a reproducibility rivaling that of high-throughput gene expression measurements. To evaluate the utility of the predicted gene expression signatures, we compared the predicted and experimentally derived signatures in their ability to identify drugs known to cause specific liver, kidney, and heart injuries. Overall, the predicted and experimentally derived signatures had similar receiver operating characteristics, whose areas under the curve ranged from 0.71 to 0.77 and 0.70 to 0.73, respectively, across the three organ injury models. However, detailed analyses of enrichment curves indicate that signatures predicted from multiple near neighbors outperformed those derived from experiments, suggesting that averaging information from near neighbors may help improve the signal from gene expression measurements. Our results demonstrate that the v-NN method can serve as a practical approach for modeling large-scale, genomewide, chemical-induced, gene expression changes.

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

CCR researchers identify pathway critical for preventing premature aging | Center for Cancer Research

Cancer.gov

Hutchinson-Gilford progeria syndrome (HGPS) is a rare, fatal disease in which patients age prematurely. To identify primary HGPS driver mechanisms, Nard Kubben, Ph.D., a Research Fellow in the laboratory of Tom Misteli, Ph.D., in CCR’s Laboratory of Receptor Biology and Gene Expression, and colleagues in the NCI High-throughput Imaging Facility developed an imaging-based

Gravity-regulated gene expression in Arabidopsis thaliana

NASA Astrophysics Data System (ADS)

Sederoff, Heike; Brown, Christopher S.; Heber, Steffen; Kajla, Jyoti D.; Kumar, Sandeep; Lomax, Terri L.; Wheeler, Benjamin; Yalamanchili, Roopa

Plant growth and development is regulated by changes in environmental signals. Plants sense environmental changes and respond to them by modifying gene expression programs to ad-just cell growth, differentiation, and metabolism. Functional expression of genes comprises many different processes including transcription, translation, post-transcriptional and post-translational modifications, as well as the degradation of RNA and proteins. Recently, it was discovered that small RNAs (sRNA, 18-24 nucleotides long), which are heritable and systemic, are key elements in regulating gene expression in response to biotic and abiotic changes. Sev-eral different classes of sRNAs have been identified that are part of a non-cell autonomous and phloem-mobile network of regulators affecting transcript stability, translational kinetics, and DNA methylation patterns responsible for heritable transcriptional silencing (epigenetics). Our research has focused on gene expression changes in response to gravistimulation of Arabidopsis roots. Using high-throughput technologies including microarrays and 454 sequencing, we iden-tified rapid changes in transcript abundance of genes as well as differential expression of small RNA in Arabidopsis root apices after minutes of reorientation. Some of the differentially regu-lated transcripts are encoded by genes that are important for the bending response. Functional mutants of those genes respond faster to reorientation than the respective wild type plants, indicating that these proteins are repressors of differential cell elongation. We compared the gravity responsive sRNAs to the changes in transcript abundances of their putative targets and identified several potential miRNA: target pairs. Currently, we are using mutant and transgenic Arabidopsis plants to characterize the function of those miRNAs and their putative targets in gravitropic and phototropic responses in Arabidopsis.

Bayesian inference with historical data-based informative priors improves detection of differentially expressed genes

PubMed Central

Li, Ben; Sun, Zhaonan; He, Qing; Zhu, Yu; Qin, Zhaohui S.

2016-01-01

Motivation: Modern high-throughput biotechnologies such as microarray are capable of producing a massive amount of information for each sample. However, in a typical high-throughput experiment, only limited number of samples were assayed, thus the classical ‘large p, small n’ problem. On the other hand, rapid propagation of these high-throughput technologies has resulted in a substantial collection of data, often carried out on the same platform and using the same protocol. It is highly desirable to utilize the existing data when performing analysis and inference on a new dataset. Results: Utilizing existing data can be carried out in a straightforward fashion under the Bayesian framework in which the repository of historical data can be exploited to build informative priors and used in new data analysis. In this work, using microarray data, we investigate the feasibility and effectiveness of deriving informative priors from historical data and using them in the problem of detecting differentially expressed genes. Through simulation and real data analysis, we show that the proposed strategy significantly outperforms existing methods including the popular and state-of-the-art Bayesian hierarchical model-based approaches. Our work illustrates the feasibility and benefits of exploiting the increasingly available genomics big data in statistical inference and presents a promising practical strategy for dealing with the ‘large p, small n’ problem. Availability and implementation: Our method is implemented in R package IPBT, which is freely available from https://github.com/benliemory/IPBT. Contact: yuzhu@purdue.edu; zhaohui.qin@emory.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26519502

Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

PubMed

Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

2013-09-22

High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

The role of Cdx2 as a lineage specific transcriptional repressor for pluripotent network during the first developmental cell lineage segregation.

PubMed

Huang, Daosheng; Guo, Guoji; Yuan, Ping; Ralston, Amy; Sun, Lingang; Huss, Mikael; Mistri, Tapan; Pinello, Luca; Ng, Huck Hui; Yuan, Guocheng; Ji, Junfeng; Rossant, Janet; Robson, Paul; Han, Xiaoping

2017-12-07

The first cellular differentiation event in mouse development leads to the formation of the blastocyst consisting of the inner cell mass (ICM) and trophectoderm (TE). The transcription factor CDX2 is required for proper TE specification, where it promotes expression of TE genes, and represses expression of Pou5f1 (OCT4). However its downstream network in the developing embryo is not fully characterized. Here, we performed high-throughput single embryo qPCR analysis in Cdx2 null embryos to identify CDX2-regulated targets in vivo. To identify genes likely to be regulated by CDX2 directly, we performed CDX2 ChIP-Seq on trophoblast stem (TS) cells. In addition, we examined the dynamics of gene expression changes using inducible CDX2 embryonic stem (ES) cells, so that we could predict which CDX2-bound genes are activated or repressed by CDX2 binding. By integrating these data with observations of chromatin modifications, we identify putative novel regulatory elements that repress gene expression in a lineage-specific manner. Interestingly, we found CDX2 binding sites within regulatory elements of key pluripotent genes such as Pou5f1 and Nanog, pointing to the existence of a novel mechanism by which CDX2 maintains repression of OCT4 in trophoblast. Our study proposes a general mechanism in regulating lineage segregation during mammalian development.

Integrating Microarray Data and GRNs.

PubMed

Koumakis, L; Potamias, G; Tsiknakis, M; Zervakis, M; Moustakis, V

2016-01-01

With the completion of the Human Genome Project and the emergence of high-throughput technologies, a vast amount of molecular and biological data are being produced. Two of the most important and significant data sources come from microarray gene-expression experiments and respective databanks (e,g., Gene Expression Omnibus-GEO (http://www.ncbi.nlm.nih.gov/geo)), and from molecular pathways and Gene Regulatory Networks (GRNs) stored and curated in public (e.g., Kyoto Encyclopedia of Genes and Genomes-KEGG (http://www.genome.jp/kegg/pathway.html), Reactome (http://www.reactome.org/ReactomeGWT/entrypoint.html)) as well as in commercial repositories (e.g., Ingenuity IPA (http://www.ingenuity.com/products/ipa)). The association of these two sources aims to give new insight in disease understanding and reveal new molecular targets in the treatment of specific phenotypes.Three major research lines and respective efforts that try to utilize and combine data from both of these sources could be identified, namely: (1) de novo reconstruction of GRNs, (2) identification of Gene-signatures, and (3) identification of differentially expressed GRN functional paths (i.e., sub-GRN paths that distinguish between different phenotypes). In this chapter, we give an overview of the existing methods that support the different types of gene-expression and GRN integration with a focus on methodologies that aim to identify phenotype-discriminant GRNs or subnetworks, and we also present our methodology.

The transcriptional response of Escherichia coli to recombinant protein insolubility.

PubMed

Smith, Harold E

2007-03-01

Bacterial production of recombinant proteins offers several advantages over alternative expression methods and remains the system of choice for many structural genomics projects. However, a large percentage of targets accumulate as insoluble inclusion bodies rather than soluble protein, creating a significant bottleneck in the protein production pipeline. Numerous strategies have been reported that can improve in vivo protein solubility, but most do not scale easily for high-throughput expression screening. To understand better the host cell response to the accumulation of insoluble protein, we determined genome-wide changes in bacterial gene expression upon induction of either soluble or insoluble target proteins. By comparing transcriptional profiles for multiple examples from the soluble or insoluble class, we identified a pattern of gene expression that correlates strongly with protein solubility. Direct targets of the sigma32 heat shock sigma factor, which includes genes involved in protein folding and degradation, were highly expressed in response to induction of insoluble protein. This same group of genes was also upregulated by insoluble protein accumulation under a different growth regime, indicating that sigma32-mediated gene expression is a general response to protein insolubility. This knowledge provides a starting point for the rational design of growth parameters and host strains with improved protein solubility characteristics. Summary Problems with protein solubility are frequently encountered when recombinant proteins are expressed in E. coli. The bacterial host responds to this problem by increasing expression of the protein folding machinery via the heat shock sigma factor sigma32. Manipulation of the sigma32 regulon might provide a general mechanism for improving recombinant protein solubility.

Identification of Mycoparasitism-Related Genes in Trichoderma atroviride ▿ † ‡

PubMed Central

Reithner, Barbara; Ibarra-Laclette, Enrique; Mach, Robert L.; Herrera-Estrella, Alfredo

2011-01-01

A high-throughput sequencing approach was utilized to carry out a comparative transcriptome analysis of Trichoderma atroviride IMI206040 during mycoparasitic interactions with the plant-pathogenic fungus Rhizoctonia solani. In this study, transcript fragments of 7,797 Trichoderma genes were sequenced, 175 of which were host responsive. According to the functional annotation of these genes by KOG (eukaryotic orthologous groups), the most abundant group during direct contact was “metabolism.” Quantitative reverse transcription (RT)-PCR confirmed the differential transcription of 13 genes (including swo1, encoding an expansin-like protein; axe1, coding for an acetyl xylan esterase; and homologs of genes encoding the aspartyl protease papA and a trypsin-like protease, pra1) in the presence of R. solani. An additional relative gene expression analysis of these genes, conducted at different stages of mycoparasitism against Botrytis cinerea and Phytophthora capsici, revealed a synergistic transcription of various genes involved in cell wall degradation. The similarities in expression patterns and the occurrence of regulatory binding sites in the corresponding promoter regions suggest a possible analog regulation of these genes during the mycoparasitism of T. atroviride. Furthermore, a chitin- and distance-dependent induction of pra1 was demonstrated. PMID:21531825

RNA-seq analysis of the gonadal transcriptome during Alligator mississippiensis temperature-dependent sex determination and differentiation.

PubMed

Yatsu, Ryohei; Miyagawa, Shinichi; Kohno, Satomi; Parrott, Benjamin B; Yamaguchi, Katsushi; Ogino, Yukiko; Miyakawa, Hitoshi; Lowers, Russell H; Shigenobu, Shuji; Guillette, Louis J; Iguchi, Taisen

2016-01-25

The American alligator (Alligator mississippiensis) displays temperature-dependent sex determination (TSD), in which incubation temperature during embryonic development determines the sexual fate of the individual. However, the molecular mechanisms governing this process remain a mystery, including the influence of initial environmental temperature on the comprehensive gonadal gene expression patterns occurring during TSD. Our characterization of transcriptomes during alligator TSD allowed us to identify novel candidate genes involved in TSD initiation. High-throughput RNA sequencing (RNA-seq) was performed on gonads collected from A. mississippiensis embryos incubated at both a male and a female producing temperature (33.5 °C and 30 °C, respectively) in a time series during sexual development. RNA-seq yielded 375.2 million paired-end reads, which were mapped and assembled, and used to characterize differential gene expression. Changes in the transcriptome occurring as a function of both development and sexual differentiation were extensively profiled. Forty-one differentially expressed genes were detected in response to incubation at male producing temperature, and included genes such as Wnt signaling factor WNT11, histone demethylase KDM6B, and transcription factor C/EBPA. Furthermore, comparative analysis of development- and sex-dependent differential gene expression revealed 230 candidate genes involved in alligator sex determination and differentiation, and early details of the suspected male-fate commitment were profiled. We also discovered sexually dimorphic expression of uncharacterized ncRNAs and other novel elements, such as unique expression patterns of HEMGN and ARX. Twenty-five of the differentially expressed genes identified in our analysis were putative transcriptional regulators, among which were MYBL2, MYCL, and HOXC10, in addition to conventional sex differentiation genes such as SOX9, and FOXL2. Inferred gene regulatory network was constructed, and the gene-gene and temperature-gene interactions were predicted. Gonadal global gene expression kinetics during sex determination has been extensively profiled for the first time in a TSD species. These findings provide insights into the genetic framework underlying TSD, and expand our current understanding of the developmental fate pathways during vertebrate sex determination.

Droplet-based microfluidic high-throughput screening of heterologous enzymes secreted by the yeast Yarrowia lipolytica.

PubMed

Beneyton, Thomas; Thomas, Stéphane; Griffiths, Andrew D; Nicaud, Jean-Marc; Drevelle, Antoine; Rossignol, Tristan

2017-01-31

Droplet-based microfluidics is becoming an increasingly attractive alternative to microtiter plate techniques for enzymatic high-throughput screening (HTS), especially for exploring large diversities with lower time and cost footprint. In this case, the assayed enzyme has to be accessible to the substrate within the water-in-oil droplet by being ideally extracellular or displayed at the cell surface. However, most of the enzymes screened to date are expressed within the cytoplasm of Escherichia coli cells, which means that a lysis step must take place inside the droplets for enzyme activity to be assayed. Here, we take advantage of the excellent secretion abilities of the yeast Yarrowia lipolytica to describe a highly efficient expression system particularly suitable for the droplet-based microfluidic HTS. Five hydrolytic genes from Aspergillus niger genome were chosen and the corresponding five Yarrowia lipolytica producing strains were constructed. Each enzyme (endo-β-1,4-xylanase B and C; 1,4-β-cellobiohydrolase A; endoglucanase A; aspartic protease) was successfully overexpressed and secreted in an active form in the crude supernatant. A droplet-based microfluidic HTS system was developed to (a) encapsulate single yeast cells; (b) grow yeast in droplets; (c) inject the relevant enzymatic substrate; (d) incubate droplets on chip; (e) detect enzymatic activity; and (f) sort droplets based on enzymatic activity. Combining this integrated microfluidic platform with gene expression in Y. lipolytica results in remarkably low variability in the enzymatic activity at the single cell level within a given monoclonal population (<5%). Xylanase, cellobiohydrolase and protease activities were successfully assayed using this system. We then used the system to screen for thermostable variants of endo-β-1,4-xylanase C in error-prone PCR libraries. Variants displaying higher thermostable xylanase activities compared to the wild-type were isolated (up to 4.7-fold improvement). Yarrowia lipolytica was used to express fungal genes encoding hydrolytic enzymes of interest. We developed a successful droplet-based microfluidic platform for the high-throughput screening (10 5 strains/h) of Y. lipolytica based on enzyme secretion and activity. This approach provides highly efficient tools for the HTS of recombinant enzymatic activities. This should be extremely useful for discovering new biocatalysts via directed evolution or protein engineering approaches and should lead to major advances in microbial cell factory development.

MicroRNA expression profiling in alveolar macrophages of indigenous Chinese Tongcheng pigs infected with PRRSV in vivo.

PubMed

Zhou, Xiang; Michal, Jennifer J; Jiang, Zhihua; Liu, Bang

2017-11-01

Porcine respiratory and reproductive syndrome (PRRS), caused by PRRS virus (PRRSV), is one of the most serious infectious diseases in the swine industry worldwide. Indigenous Chinese Tongcheng (TC) pigs reportedly show strong resistance to PRRSV infection. The miRNA expression profiles of porcine alveolar macrophages (PAMs) of control TC pigs and those infected with PRRSV in vivo were analyzed by high-throughput sequencing to explore changes induced by infection. A total of 182 known miRNAs including 101 miRNA-5p and 81 miRNA-3p were identified with 23 up-regulated differentially expressed miRNAs (DEmiRNAs) and 25 down-regulated DEmiRNAs. Gene Ontology analysis showed that predicted target genes for the DEmiRNAs were enriched in immune response, transcription regulation, and cell death. The integrative analysis of mRNA and miRNA expression revealed that down-regulated methylation-related genes (DNMT1 and DNMT3b) were targeted by five up-regulated DEmiRNAs. Furthermore, 35 pairs of miRNAs (70 miRNAs) were co-expressed after PRRSV infection and six pairs were co-expressed differently. Our results describe miRNA expression profiles of TC pigs in response to PRRSV infection and lay a strong foundation for developing novel therapies to control PRRS in pigs.

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.

Characterization and Expression Patterns of microRNAs Involved in Rice Grain Filling

PubMed Central

Du, Yanxiu; Zhang, Jing; Li, Junzhou; Liu, Yanxia; Zhao, Yafan; Zhao, Quanzhi

2013-01-01

MicroRNAs (miRNAs) are upstream gene regulators of plant development and hormone homeostasis through their directed cleavage or translational repression of the target mRNAs, which may play crucial roles in rice grain filling and determining the final grain weight and yield. In this study, high-throughput sequencing was performed to survey the dynamic expressions of miRNAs and their corresponding target genes at five distinct developmental stages of grain filling. In total, 445 known miRNAs and 45 novel miRNAs were detected with most of them expressed in a developmental stage dependent manner, and the majority of known miRNAs, which increased gradually with rice grain filling, showed negatively related to the grain filling rate. Detailed expressional comparisons revealed a clear negative correlation between most miRNAs and their target genes. It was found that specific miRNA cohorts are expressed in a developmental stage dependent manner during grain filling and the known functions of these miRNAs are involved in plant hormone homeostasis and starch accumulation, indicating that the expression dynamics of these miRNAs might play key roles in regulating rice grain filling. PMID:23365650

High-throughput transcriptome analysis of barley (Hordeum vulgare) exposed to excessive boron.

PubMed

Tombuloglu, Guzin; Tombuloglu, Huseyin; Sakcali, M Serdal; Unver, Turgay

2015-02-15

Boron (B) is an essential micronutrient for optimum plant growth. However, above certain threshold B is toxic and causes yield loss in agricultural lands. While a number of studies were conducted to understand B tolerance mechanism, a transcriptome-wide approach for B tolerant barley is performed here for the first time. A high-throughput RNA-Seq (cDNA) sequencing technology (Illumina) was used with barley (Hordeum vulgare), yielding 208 million clean reads. In total, 256,874 unigenes were generated and assigned to known peptide databases: Gene Ontology (GO) (99,043), Swiss-Prot (38,266), Clusters of Orthologous Groups (COG) (26,250), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) (36,860), as determined by BLASTx search. According to the digital gene expression (DGE) analyses, 16% and 17% of the transcripts were found to be differentially regulated in root and leaf tissues, respectively. Most of them were involved in cell wall, stress response, membrane, protein kinase and transporter mechanisms. Some of the genes detected as highly expressed in root tissue are phospholipases, predicted divalent heavy-metal cation transporters, formin-like proteins and calmodulin/Ca(2+)-binding proteins. In addition, chitin-binding lectin precursor, ubiquitin carboxyl-terminal hydrolase, and serine/threonine-protein kinase AFC2 genes were indicated to be highly regulated in leaf tissue upon excess B treatment. Some pathways, such as the Ca(2+)-calmodulin system, are activated in response to B toxicity. The differential regulation of 10 transcripts was confirmed by qRT-PCR, revealing the tissue-specific responses against B toxicity and their putative function in B-tolerance mechanisms. Copyright © 2014. Published by Elsevier B.V.

Expression patterns of the aquaporin gene family during renal development: influence of genetic variability.

PubMed

Parreira, Kleber S; Debaix, Huguette; Cnops, Yvette; Geffers, Lars; Devuyst, Olivier

2009-08-01

High-throughput analyses have shown that aquaporins (AQPs) belong to a cluster of genes that are differentially expressed during kidney organogenesis. However, the spatiotemporal expression patterns of the AQP gene family during tubular maturation and the potential influence of genetic variation on these patterns and on water handling remain unknown. We investigated the expression patterns of all AQP isoforms in fetal (E13.5 to E18.5), postnatal (P1 to P28), and adult (9 weeks) kidneys of inbred (C57BL/6J) and outbred (CD-1) mice. Using quantitative polymerase chain reaction (PCR), we evidenced two mRNA patterns during tubular maturation in C57 mice. The AQPs 1-7-11 showed an early (from E14.5) and progressive increase to adult levels, similar to the mRNA pattern observed for proximal tubule markers (Megalin, NaPi-IIa, OAT1) and reflecting the continuous increase in renal cortical structures during development. By contrast, AQPs 2-3-4 showed a later (E15.5) and more abrupt increase, with transient postnatal overexpression. Most AQP genes were expressed earlier and/or stronger in maturing CD-1 kidneys. Furthermore, adult CD-1 kidneys expressed more AQP2 in the collecting ducts, which was reflected by a significant delay in excreting a water load. The expression patterns of proximal vs. distal AQPs and the earlier expression in the CD-1 strain were confirmed by immunoblotting and immunostaining. These data (1) substantiate the clustering of important genes during tubular maturation and (2) demonstrate that genetic variability influences the regulation of the AQP gene family during tubular maturation and water handling by the mature kidney.

Screening and identification of gastric adenocarcinoma metastasis-related genes using cDNA microarray coupled to FDD-PCR.

PubMed

Wang, Jianhua; Chen, Shishu

2002-10-01

To identify certain gastric adenocarcinoma metastasis-related genes, an RF-1 cell line (primary tumor from a gastric adenocarcinoma patient) and an RF-48 cell line (its metastatic counterpart) were used as a model for studying the molecular mechanism of tumor metastasis. Two fluorescent cDNA probes, labeled with Cy3 and Cy5 dyes, were prepared from RF-1 and RF-48 mRNA samples by the reverse transcription method. The two color probes were then mixed and hybridized to a cDNA chip constructed with double-dots from 4,096 human genes, and scanned at two wavelengths. The experiment was repeated twice. Differentially expressedn genes from the above two cells were analyzed by use of computer. Of the total genes, 138 (3.4%) revealed differential expression in RF-48 cells compared with RF-1 cells: 81 (2.1%) genes revealed apparent up-regulation, and 56 (1.3%) genes revealed down-regulation. Forty-five genes involved in gastric adenocarcinoma metastasis were cloned using fluorescent differential display-PCR (FDD-PCR), including three novel genes. There were seven differentially expressed genes that presented the same behaviour under both detection methods. The possible roles of some differentially expressed genes, which may be involved in the mechanism of tumor metastasis, were discussed. cDNA chip was used to analyze gene expression in a high-throughput and large-scale manner in combination with FDD-PCR for cloning unknown novel genes. Some genes related to metastasis were preliminarily scanned, which would contribute to disclose the molecular mechanism of gastric adenocarcinoma metastasis and provide new targets for therapeutic intervention.

Issues with RNA-seq analysis in non-model organisms: A salmonid example.

PubMed

Sundaram, Arvind; Tengs, Torstein; Grimholt, Unni

2017-10-01

High throughput sequencing (HTS) is useful for many purposes as exemplified by the other topics included in this special issue. The purpose of this paper is to look into the unique challenges of using this technology in non-model organisms where resources such as genomes, functional genome annotations or genome complexity provide obstacles not met in model organisms. To describe these challenges, we narrow our scope to RNA sequencing used to study differential gene expression in response to pathogen challenge. As a demonstration species we chose Atlantic salmon, which has a sequenced genome with poor annotation and an added complexity due to many duplicated genes. We find that our RNA-seq analysis pipeline deciphers between duplicates despite high sequence identity. However, annotation issues provide problems in linking differentially expressed genes to pathways. Also, comparing results between approaches and species are complicated due to lack of standardized annotation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transcriptome sequencing and annotation of the halophytic microalga Dunaliella salina * #

PubMed Central

Hong, Ling; Liu, Jun-li; Midoun, Samira Z.; Miller, Philip C.

2017-01-01

The unicellular green alga Dunaliella salina is well adapted to salt stress and contains compounds (including β-carotene and vitamins) with potential commercial value. A large transcriptome database of D. salina during the adjustment, exponential and stationary growth phases was generated using a high throughput sequencing platform. We characterized the metabolic processes in D. salina with a focus on valuable metabolites, with the aim of manipulating D. salina to achieve greater economic value in large-scale production through a bioengineering strategy. Gene expression profiles under salt stress verified using quantitative polymerase chain reaction (qPCR) implied that salt can regulate the expression of key genes. This study generated a substantial fraction of D. salina transcriptional sequences for the entire growth cycle, providing a basis for the discovery of novel genes. This first full-scale transcriptome study of D. salina establishes a foundation for further comparative genomic studies. PMID:28990374

Molecular Screening Tools to Study Arabidopsis Transcription Factors

PubMed Central

Wehner, Nora; Weiste, Christoph; Dröge-Laser, Wolfgang

2011-01-01

In the model plant Arabidopsis thaliana, more than 2000 genes are estimated to encode transcription factors (TFs), which clearly emphasizes the importance of transcriptional control. Although genomic approaches have generated large TF open reading frame (ORF) collections, only a limited number of these genes is functionally characterized, yet. This review evaluates strategies and methods to identify TF functions. In particular, we focus on two recently developed TF screening platforms, which make use of publically available GATEWAY®-compatible ORF collections. (1) The Arabidopsis thaliana TF ORF over-Expression (AtTORF-Ex) library provides pooled collections of transgenic lines over-expressing HA-tagged TF genes, which are suited for screening approaches to define TF functions in stress defense and development. (2) A high-throughput microtiter plate based protoplast trans activation (PTA) system has been established to screen for TFs which are regulating a given promoter:Luciferase construct in planta. PMID:22645547

Overview Article: Identifying transcriptional cis-regulatory modules in animal genomes

PubMed Central

Suryamohan, Kushal; Halfon, Marc S.

2014-01-01

Gene expression is regulated through the activity of transcription factors and chromatin modifying proteins acting on specific DNA sequences, referred to as cis-regulatory elements. These include promoters, located at the transcription initiation sites of genes, and a variety of distal cis-regulatory modules (CRMs), the most common of which are transcriptional enhancers. Because regulated gene expression is fundamental to cell differentiation and acquisition of new cell fates, identifying, characterizing, and understanding the mechanisms of action of CRMs is critical for understanding development. CRM discovery has historically been challenging, as CRMs can be located far from the genes they regulate, have few readily-identifiable sequence characteristics, and for many years were not amenable to high-throughput discovery methods. However, the recent availability of complete genome sequences and the development of next-generation sequencing methods has led to an explosion of both computational and empirical methods for CRM discovery in model and non-model organisms alike. Experimentally, CRMs can be identified through chromatin immunoprecipitation directed against transcription factors or histone post-translational modifications, identification of nucleosome-depleted “open” chromatin regions, or sequencing-based high-throughput functional screening. Computational methods include comparative genomics, clustering of known or predicted transcription factor binding sites, and supervised machine-learning approaches trained on known CRMs. All of these methods have proven effective for CRM discovery, but each has its own considerations and limitations, and each is subject to a greater or lesser number of false-positive identifications. Experimental confirmation of predictions is essential, although shortcomings in current methods suggest that additional means of validation need to be developed. PMID:25704908

Analyses of Brucella Pathogenesis, Host Immunity, and Vaccine Targets using Systems Biology and Bioinformatics

PubMed Central

He, Yongqun

2011-01-01

Brucella is a Gram-negative, facultative intracellular bacterium that causes zoonotic brucellosis in humans and various animals. Out of 10 classified Brucella species, B. melitensis, B. abortus, B. suis, and B. canis are pathogenic to humans. In the past decade, the mechanisms of Brucella pathogenesis and host immunity have been extensively investigated using the cutting edge systems biology and bioinformatics approaches. This article provides a comprehensive review of the applications of Omics (including genomics, transcriptomics, and proteomics) and bioinformatics technologies for the analysis of Brucella pathogenesis, host immune responses, and vaccine targets. Based on more than 30 sequenced Brucella genomes, comparative genomics is able to identify gene variations among Brucella strains that help to explain host specificity and virulence differences among Brucella species. Diverse transcriptomics and proteomics gene expression studies have been conducted to analyze gene expression profiles of wild type Brucella strains and mutants under different laboratory conditions. High throughput Omics analyses of host responses to infections with virulent or attenuated Brucella strains have been focused on responses by mouse and cattle macrophages, bovine trophoblastic cells, mouse and boar splenocytes, and ram buffy coat. Differential serum responses in humans and rams to Brucella infections have been analyzed using high throughput serum antibody screening technology. The Vaxign reverse vaccinology has been used to predict many Brucella vaccine targets. More than 180 Brucella virulence factors and their gene interaction networks have been identified using advanced literature mining methods. The recent development of community-based Vaccine Ontology and Brucellosis Ontology provides an efficient way for Brucella data integration, exchange, and computer-assisted automated reasoning. PMID:22919594

Analyses of Brucella pathogenesis, host immunity, and vaccine targets using systems biology and bioinformatics.

PubMed

He, Yongqun

2012-01-01

Brucella is a Gram-negative, facultative intracellular bacterium that causes zoonotic brucellosis in humans and various animals. Out of 10 classified Brucella species, B. melitensis, B. abortus, B. suis, and B. canis are pathogenic to humans. In the past decade, the mechanisms of Brucella pathogenesis and host immunity have been extensively investigated using the cutting edge systems biology and bioinformatics approaches. This article provides a comprehensive review of the applications of Omics (including genomics, transcriptomics, and proteomics) and bioinformatics technologies for the analysis of Brucella pathogenesis, host immune responses, and vaccine targets. Based on more than 30 sequenced Brucella genomes, comparative genomics is able to identify gene variations among Brucella strains that help to explain host specificity and virulence differences among Brucella species. Diverse transcriptomics and proteomics gene expression studies have been conducted to analyze gene expression profiles of wild type Brucella strains and mutants under different laboratory conditions. High throughput Omics analyses of host responses to infections with virulent or attenuated Brucella strains have been focused on responses by mouse and cattle macrophages, bovine trophoblastic cells, mouse and boar splenocytes, and ram buffy coat. Differential serum responses in humans and rams to Brucella infections have been analyzed using high throughput serum antibody screening technology. The Vaxign reverse vaccinology has been used to predict many Brucella vaccine targets. More than 180 Brucella virulence factors and their gene interaction networks have been identified using advanced literature mining methods. The recent development of community-based Vaccine Ontology and Brucellosis Ontology provides an efficient way for Brucella data integration, exchange, and computer-assisted automated reasoning.

Long non-coding RNA expression patterns in lung tissues of chronic cigarette smoke induced COPD mouse model.

PubMed

Zhang, Haiyun; Sun, Dejun; Li, Defu; Zheng, Zeguang; Xu, Jingyi; Liang, Xue; Zhang, Chenting; Wang, Sheng; Wang, Jian; Lu, Wenju

2018-05-15

Long non-coding RNAs (lncRNAs) have critical regulatory roles in protein-coding gene expression. Aberrant expression profiles of lncRNAs have been observed in various human diseases. In this study, we investigated transcriptome profiles in lung tissues of chronic cigarette smoke (CS)-induced COPD mouse model. We found that 109 lncRNAs and 260 mRNAs were significantly differential expressed in lungs of chronic CS-induced COPD mouse model compared with control animals. GO and KEGG analyses indicated that differentially expressed lncRNAs associated protein-coding genes were mainly involved in protein processing of endoplasmic reticulum pathway, and taurine and hypotaurine metabolism pathway. The combination of high throughput data analysis and the results of qRT-PCR validation in lungs of chronic CS-induced COPD mouse model, 16HBE cells with CSE treatment and PBMC from patients with COPD revealed that NR_102714 and its associated protein-coding gene UCHL1 might be involved in the development of COPD both in mouse and human. In conclusion, our study demonstrated that aberrant expression profiles of lncRNAs and mRNAs existed in lungs of chronic CS-induced COPD mouse model. From animal models perspective, these results might provide further clues to investigate biological functions of lncRNAs and their potential target protein-coding genes in the pathogenesis of COPD.

Inference of developmental gene regulatory networks beyond classical model systems: new approaches in the post-genomic era.

PubMed

Fernandez-Valverde, Selene L; Aguilera, Felipe; Ramos-Díaz, René Alexander

2018-06-18

The advent of high-throughput sequencing technologies has revolutionized the way we understand the transformation of genetic information into morphological traits. Elucidating the network of interactions between genes that govern cell differentiation through development is one of the core challenges in genome research. These networks are known as developmental gene regulatory networks (dGRNs) and consist largely of the functional linkage between developmental control genes, cis-regulatory modules and differentiation genes, which generate spatially and temporally refined patterns of gene expression. Over the last 20 years, great advances have been made in determining these gene interactions mainly in classical model systems, including human, mouse, sea urchin, fruit fly, and worm. This has brought about a radical transformation in the fields of developmental biology and evolutionary biology, allowing the generation of high-resolution gene regulatory maps to analyse cell differentiation during animal development. Such maps have enabled the identification of gene regulatory circuits and have led to the development of network inference methods that can recapitulate the differentiation of specific cell-types or developmental stages. In contrast, dGRN research in non-classical model systems has been limited to the identification of developmental control genes via the candidate gene approach and the characterization of their spatiotemporal expression patterns, as well as to the discovery of cis-regulatory modules via patterns of sequence conservation and/or predicted transcription-factor binding sites. However, thanks to the continuous advances in high-throughput sequencing technologies, this scenario is rapidly changing. Here, we give a historical overview on the architecture and elucidation of the dGRNs. Subsequently, we summarize the approaches available to unravel these regulatory networks, highlighting the vast range of possibilities of integrating multiple technical advances and theoretical approaches to expand our understanding on the global of gene regulation during animal development in non-classical model systems. Such new knowledge will not only lead to greater insights into the evolution of molecular mechanisms underlying cell identity and animal body plans, but also into the evolution of morphological key innovations in animals.

High-throughput discovery of novel developmental phenotypes.

PubMed

Dickinson, Mary E; Flenniken, Ann M; Ji, Xiao; Teboul, Lydia; Wong, Michael D; White, Jacqueline K; Meehan, Terrence F; Weninger, Wolfgang J; Westerberg, Henrik; Adissu, Hibret; Baker, Candice N; Bower, Lynette; Brown, James M; Caddle, L Brianna; Chiani, Francesco; Clary, Dave; Cleak, James; Daly, Mark J; Denegre, James M; Doe, Brendan; Dolan, Mary E; Edie, Sarah M; Fuchs, Helmut; Gailus-Durner, Valerie; Galli, Antonella; Gambadoro, Alessia; Gallegos, Juan; Guo, Shiying; Horner, Neil R; Hsu, Chih-Wei; Johnson, Sara J; Kalaga, Sowmya; Keith, Lance C; Lanoue, Louise; Lawson, Thomas N; Lek, Monkol; Mark, Manuel; Marschall, Susan; Mason, Jeremy; McElwee, Melissa L; Newbigging, Susan; Nutter, Lauryl M J; Peterson, Kevin A; Ramirez-Solis, Ramiro; Rowland, Douglas J; Ryder, Edward; Samocha, Kaitlin E; Seavitt, John R; Selloum, Mohammed; Szoke-Kovacs, Zsombor; Tamura, Masaru; Trainor, Amanda G; Tudose, Ilinca; Wakana, Shigeharu; Warren, Jonathan; Wendling, Olivia; West, David B; Wong, Leeyean; Yoshiki, Atsushi; MacArthur, Daniel G; Tocchini-Valentini, Glauco P; Gao, Xiang; Flicek, Paul; Bradley, Allan; Skarnes, William C; Justice, Monica J; Parkinson, Helen E; Moore, Mark; Wells, Sara; Braun, Robert E; Svenson, Karen L; de Angelis, Martin Hrabe; Herault, Yann; Mohun, Tim; Mallon, Ann-Marie; Henkelman, R Mark; Brown, Steve D M; Adams, David J; Lloyd, K C Kent; McKerlie, Colin; Beaudet, Arthur L; Bućan, Maja; Murray, Stephen A

2016-09-22

Approximately one-third of all mammalian genes are essential for life. Phenotypes resulting from knockouts of these genes in mice have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5,000 knockout mouse lines, here we identify 410 lethal genes during the production of the first 1,751 unique gene knockouts. Using a standardized phenotyping platform that incorporates high-resolution 3D imaging, we identify phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes, thus providing a dataset that facilitates the prioritization and validation of mutations identified in clinical sequencing efforts.

High-throughput discovery of novel developmental phenotypes

PubMed Central

Dickinson, Mary E.; Flenniken, Ann M.; Ji, Xiao; Teboul, Lydia; Wong, Michael D.; White, Jacqueline K.; Meehan, Terrence F.; Weninger, Wolfgang J.; Westerberg, Henrik; Adissu, Hibret; Baker, Candice N.; Bower, Lynette; Brown, James M.; Caddle, L. Brianna; Chiani, Francesco; Clary, Dave; Cleak, James; Daly, Mark J.; Denegre, James M.; Doe, Brendan; Dolan, Mary E.; Edie, Sarah M.; Fuchs, Helmut; Gailus-Durner, Valerie; Galli, Antonella; Gambadoro, Alessia; Gallegos, Juan; Guo, Shiying; Horner, Neil R.; Hsu, Chih-wei; Johnson, Sara J.; Kalaga, Sowmya; Keith, Lance C.; Lanoue, Louise; Lawson, Thomas N.; Lek, Monkol; Mark, Manuel; Marschall, Susan; Mason, Jeremy; McElwee, Melissa L.; Newbigging, Susan; Nutter, Lauryl M.J.; Peterson, Kevin A.; Ramirez-Solis, Ramiro; Rowland, Douglas J.; Ryder, Edward; Samocha, Kaitlin E.; Seavitt, John R.; Selloum, Mohammed; Szoke-Kovacs, Zsombor; Tamura, Masaru; Trainor, Amanda G; Tudose, Ilinca; Wakana, Shigeharu; Warren, Jonathan; Wendling, Olivia; West, David B.; Wong, Leeyean; Yoshiki, Atsushi; MacArthur, Daniel G.; Tocchini-Valentini, Glauco P.; Gao, Xiang; Flicek, Paul; Bradley, Allan; Skarnes, William C.; Justice, Monica J.; Parkinson, Helen E.; Moore, Mark; Wells, Sara; Braun, Robert E.; Svenson, Karen L.; de Angelis, Martin Hrabe; Herault, Yann; Mohun, Tim; Mallon, Ann-Marie; Henkelman, R. Mark; Brown, Steve D.M.; Adams, David J.; Lloyd, K.C. Kent; McKerlie, Colin; Beaudet, Arthur L.; Bucan, Maja; Murray, Stephen A.

2016-01-01

Approximately one third of all mammalian genes are essential for life. Phenotypes resulting from mouse knockouts of these genes have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5000 knockout mouse lines, we have identified 410 lethal genes during the production of the first 1751 unique gene knockouts. Using a standardised phenotyping platform that incorporates high-resolution 3D imaging, we identified novel phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes identified in our screen, thus providing a novel dataset that facilitates prioritization and validation of mutations identified in clinical sequencing efforts. PMID:27626380

Combinatorial codon scrambling enables scalable gene synthesis and amplification of repetitive proteins

NASA Astrophysics Data System (ADS)

Tang, Nicholas C.; Chilkoti, Ashutosh

2016-04-01

Most genes are synthesized using seamless assembly methods that rely on the polymerase chain reaction (PCR). However, PCR of genes encoding repetitive proteins either fails or generates nonspecific products. Motivated by the need to efficiently generate new protein polymers through high-throughput gene synthesis, here we report a codon-scrambling algorithm that enables the PCR-based gene synthesis of repetitive proteins by exploiting the codon redundancy of amino acids and finding the least-repetitive synonymous gene sequence. We also show that the codon-scrambling problem is analogous to the well-known travelling salesman problem, and obtain an exact solution to it by using De Bruijn graphs and a modern mixed integer linear programme solver. As experimental proof of the utility of this approach, we use it to optimize the synthetic genes for 19 repetitive proteins, and show that the gene fragments are amenable to PCR-based gene assembly and recombinant expression.

Molecular Pathways: Extracting Medical Knowledge from High Throughput Genomic Data

PubMed Central

Goldstein, Theodore; Paull, Evan O.; Ellis, Matthew J.; Stuart, Joshua M.

2013-01-01

High-throughput genomic data that measures RNA expression, DNA copy number, mutation status and protein levels provide us with insights into the molecular pathway structure of cancer. Genomic lesions (amplifications, deletions, mutations) and epigenetic modifications disrupt biochemical cellular pathways. While the number of possible lesions is vast, different genomic alterations may result in concordant expression and pathway activities, producing common tumor subtypes that share similar phenotypic outcomes. How can these data be translated into medical knowledge that provides prognostic and predictive information? First generation mRNA expression signatures such as Genomic Health's Oncotype DX already provide prognostic information, but do not provide therapeutic guidance beyond the current standard of care – which is often inadequate in high-risk patients. Rather than building molecular signatures based on gene expression levels, evidence is growing that signatures based on higher-level quantities such as from genetic pathways may provide important prognostic and diagnostic cues. We provide examples of how activities for molecular entities can be predicted from pathway analysis and how the composite of all such activities, referred to here as the “activitome,” help connect genomic events to clinical factors in order to predict the drivers of poor outcome. PMID:23430023

Identifying Stable Reference Genes for qRT-PCR Normalisation in Gene Expression Studies of Narrow-Leafed Lupin (Lupinus angustifolius L.).

PubMed

Taylor, Candy M; Jost, Ricarda; Erskine, William; Nelson, Matthew N

2016-01-01

Quantitative Reverse Transcription PCR (qRT-PCR) is currently one of the most popular, high-throughput and sensitive technologies available for quantifying gene expression. Its accurate application depends heavily upon normalisation of gene-of-interest data with reference genes that are uniformly expressed under experimental conditions. The aim of this study was to provide the first validation of reference genes for Lupinus angustifolius (narrow-leafed lupin, a significant grain legume crop) using a selection of seven genes previously trialed as reference genes for the model legume, Medicago truncatula. In a preliminary evaluation, the seven candidate reference genes were assessed on the basis of primer specificity for their respective targeted region, PCR amplification efficiency, and ability to discriminate between cDNA and gDNA. Following this assessment, expression of the three most promising candidates [Ubiquitin C (UBC), Helicase (HEL), and Polypyrimidine tract-binding protein (PTB)] was evaluated using the NormFinder and RefFinder statistical algorithms in two narrow-leafed lupin lines, both with and without vernalisation treatment, and across seven organ types (cotyledons, stem, leaves, shoot apical meristem, flowers, pods and roots) encompassing three developmental stages. UBC was consistently identified as the most stable candidate and has sufficiently uniform expression that it may be used as a sole reference gene under the experimental conditions tested here. However, as organ type and developmental stage were associated with greater variability in relative expression, it is recommended using UBC and HEL as a pair to achieve optimal normalisation. These results highlight the importance of rigorously assessing candidate reference genes for each species across a diverse range of organs and developmental stages. With emerging technologies, such as RNAseq, and the completion of valuable transcriptome data sets, it is possible that other potentially more suitable reference genes will be identified for this species in future.

Identifying Stable Reference Genes for qRT-PCR Normalisation in Gene Expression Studies of Narrow-Leafed Lupin (Lupinus angustifolius L.)

PubMed Central

Erskine, William; Nelson, Matthew N.

2016-01-01

Quantitative Reverse Transcription PCR (qRT-PCR) is currently one of the most popular, high-throughput and sensitive technologies available for quantifying gene expression. Its accurate application depends heavily upon normalisation of gene-of-interest data with reference genes that are uniformly expressed under experimental conditions. The aim of this study was to provide the first validation of reference genes for Lupinus angustifolius (narrow-leafed lupin, a significant grain legume crop) using a selection of seven genes previously trialed as reference genes for the model legume, Medicago truncatula. In a preliminary evaluation, the seven candidate reference genes were assessed on the basis of primer specificity for their respective targeted region, PCR amplification efficiency, and ability to discriminate between cDNA and gDNA. Following this assessment, expression of the three most promising candidates [Ubiquitin C (UBC), Helicase (HEL), and Polypyrimidine tract-binding protein (PTB)] was evaluated using the NormFinder and RefFinder statistical algorithms in two narrow-leafed lupin lines, both with and without vernalisation treatment, and across seven organ types (cotyledons, stem, leaves, shoot apical meristem, flowers, pods and roots) encompassing three developmental stages. UBC was consistently identified as the most stable candidate and has sufficiently uniform expression that it may be used as a sole reference gene under the experimental conditions tested here. However, as organ type and developmental stage were associated with greater variability in relative expression, it is recommended using UBC and HEL as a pair to achieve optimal normalisation. These results highlight the importance of rigorously assessing candidate reference genes for each species across a diverse range of organs and developmental stages. With emerging technologies, such as RNAseq, and the completion of valuable transcriptome data sets, it is possible that other potentially more suitable reference genes will be identified for this species in future. PMID:26872362

SVAw - a web-based application tool for automated surrogate variable analysis of gene expression studies

PubMed Central

2013-01-01

Background Surrogate variable analysis (SVA) is a powerful method to identify, estimate, and utilize the components of gene expression heterogeneity due to unknown and/or unmeasured technical, genetic, environmental, or demographic factors. These sources of heterogeneity are common in gene expression studies, and failing to incorporate them into the analysis can obscure results. Using SVA increases the biological accuracy and reproducibility of gene expression studies by identifying these sources of heterogeneity and correctly accounting for them in the analysis. Results Here we have developed a web application called SVAw (Surrogate variable analysis Web app) that provides a user friendly interface for SVA analyses of genome-wide expression studies. The software has been developed based on open source bioconductor SVA package. In our software, we have extended the SVA program functionality in three aspects: (i) the SVAw performs a fully automated and user friendly analysis workflow; (ii) It calculates probe/gene Statistics for both pre and post SVA analysis and provides a table of results for the regression of gene expression on the primary variable of interest before and after correcting for surrogate variables; and (iii) it generates a comprehensive report file, including graphical comparison of the outcome for the user. Conclusions SVAw is a web server freely accessible solution for the surrogate variant analysis of high-throughput datasets and facilitates removing all unwanted and unknown sources of variation. It is freely available for use at http://psychiatry.igm.jhmi.edu/sva. The executable packages for both web and standalone application and the instruction for installation can be downloaded from our web site. PMID:23497726

NCBI GEO: mining tens of millions of expression profiles--database and tools update.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Rudnev, Dmitry; Evangelista, Carlos; Kim, Irene F; Soboleva, Alexandra; Tomashevsky, Maxim; Edgar, Ron

2007-01-01

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely disseminates microarray and other forms of high-throughput data generated by the scientific community. The database has a minimum information about a microarray experiment (MIAME)-compliant infrastructure that captures fully annotated raw and processed data. Several data deposit options and formats are supported, including web forms, spreadsheets, XML and Simple Omnibus Format in Text (SOFT). In addition to data storage, a collection of user-friendly web-based interfaces and applications are available to help users effectively explore, visualize and download the thousands of experiments and tens of millions of gene expression patterns stored in GEO. This paper provides a summary of the GEO database structure and user facilities, and describes recent enhancements to database design, performance, submission format options, data query and retrieval utilities. GEO is accessible at http://www.ncbi.nlm.nih.gov/geo/

Gene identification for risk of relapse in stage I lung adenocarcinoma patients: a combined methodology of gene expression profiling and computational gene network analysis.

PubMed

Ludovini, Vienna; Bianconi, Fortunato; Siggillino, Annamaria; Piobbico, Danilo; Vannucci, Jacopo; Metro, Giulio; Chiari, Rita; Bellezza, Guido; Puma, Francesco; Della Fazia, Maria Agnese; Servillo, Giuseppe; Crinò, Lucio

2016-05-24

Risk assessment and treatment choice remains a challenge in early non-small-cell lung cancer (NSCLC). The aim of this study was to identify novel genes involved in the risk of early relapse (ER) compared to no relapse (NR) in resected lung adenocarcinoma (AD) patients using a combination of high throughput technology and computational analysis. We identified 18 patients (n.13 NR and n.5 ER) with stage I AD. Frozen samples of patients in ER, NR and corresponding normal lung (NL) were subjected to Microarray technology and quantitative-PCR (Q-PCR). A gene network computational analysis was performed to select predictive genes. An independent set of 79 ADs stage I samples was used to validate selected genes by Q-PCR.From microarray analysis we selected 50 genes, using the fold change ratio of ER versus NR. They were validated both in pool and individually in patient samples (ER and NR) by Q-PCR. Fourteen increased and 25 decreased genes showed a concordance between two methods. They were used to perform a computational gene network analysis that identified 4 increased (HOXA10, CLCA2, AKR1B10, FABP3) and 6 decreased (SCGB1A1, PGC, TFF1, PSCA, SPRR1B and PRSS1) genes. Moreover, in an independent dataset of ADs samples, we showed that both high FABP3 expression and low SCGB1A1 expression was associated with a worse disease-free survival (DFS).Our results indicate that it is possible to define, through gene expression and computational analysis, a characteristic gene profiling of patients with an increased risk of relapse that may become a tool for patient selection for adjuvant therapy.

Phage phenomics: Physiological approaches to characterize novel viral proteins

ScienceCinema

Sanchez, Savannah E. [San Diego State Univ., San Diego, CA (United States); Cuevas, Daniel A. [San Diego State Univ., San Diego, CA (United States); Rostron, Jason E. [San Diego State Univ., San Diego, CA (United States); Liang, Tiffany Y. [San Diego State Univ., San Diego, CA (United States); Pivaroff, Cullen G. [San Diego State Univ., San Diego, CA (United States); Haynes, Matthew R. [San Diego State Univ., San Diego, CA (United States); Nulton, Jim [San Diego State Univ., San Diego, CA (United States); Felts, Ben [San Diego State Univ., San Diego, CA (United States); Bailey, Barbara A. [San Diego State Univ., San Diego, CA (United States); Salamon, Peter [San Diego State Univ., San Diego, CA (United States); Edwards, Robert A. [San Diego State Univ., San Diego, CA (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Burgin, Alex B. [Broad Institute, Cambridge, MA (United States); Segall, Anca M. [San Diego State Univ., San Diego, CA (United States); Rohwer, Forest [San Diego State Univ., San Diego, CA (United States)

2018-06-21

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Thus, representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.

Evaluation of Bias-Variance Trade-Off for Commonly Used Post-Summarizing Normalization Procedures in Large-Scale Gene Expression Studies

PubMed Central

Qiu, Xing; Hu, Rui; Wu, Zhixin

2014-01-01

Normalization procedures are widely used in high-throughput genomic data analyses to remove various technological noise and variations. They are known to have profound impact to the subsequent gene differential expression analysis. Although there has been some research in evaluating different normalization procedures, few attempts have been made to systematically evaluate the gene detection performances of normalization procedures from the bias-variance trade-off point of view, especially with strong gene differentiation effects and large sample size. In this paper, we conduct a thorough study to evaluate the effects of normalization procedures combined with several commonly used statistical tests and MTPs under different configurations of effect size and sample size. We conduct theoretical evaluation based on a random effect model, as well as simulation and biological data analyses to verify the results. Based on our findings, we provide some practical guidance for selecting a suitable normalization procedure under different scenarios. PMID:24941114

Genome-wide recessive genetic screening in mammalian cells with a lentiviral CRISPR-guide RNA library.

PubMed

Koike-Yusa, Hiroko; Li, Yilong; Tan, E-Pien; Velasco-Herrera, Martin Del Castillo; Yusa, Kosuke

2014-03-01

Identification of genes influencing a phenotype of interest is frequently achieved through genetic screening by RNA interference (RNAi) or knockouts. However, RNAi may only achieve partial depletion of gene activity, and knockout-based screens are difficult in diploid mammalian cells. Here we took advantage of the efficiency and high throughput of genome editing based on type II, clustered, regularly interspaced, short palindromic repeats (CRISPR)-CRISPR-associated (Cas) systems to introduce genome-wide targeted mutations in mouse embryonic stem cells (ESCs). We designed 87,897 guide RNAs (gRNAs) targeting 19,150 mouse protein-coding genes and used a lentiviral vector to express these gRNAs in ESCs that constitutively express Cas9. Screening the resulting ESC mutant libraries for resistance to either Clostridium septicum alpha-toxin or 6-thioguanine identified 27 known and 4 previously unknown genes implicated in these phenotypes. Our results demonstrate the potential for efficient loss-of-function screening using the CRISPR-Cas9 system.

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

Sanchez, Savannah E.; Cuevas, Daniel A.; Rostron, Jason E.

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysismore » by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Thus, representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.« less

Identification of Epithelial-Mesenchymal Transition-related Target Genes Induced by the Mutation of Smad3 Linker Phosphorylation

PubMed Central

Park, Sujin; Yang, Kyung-Min; Park, Yuna; Hong, Eunji; Hong, Chang Pyo; Park, Jinah; Pang, Kyoungwha; Lee, Jihee; Park, Bora; Lee, Siyoung; An, Haein; Kwak, Mi-Kyung; Kim, Junil; Kang, Jin Muk; Kim, Pyunggang; Xiao, Yang; Nie, Guangjun; Ooshima, Akira

2018-01-01

Background Smad3 linker phosphorylation plays essential roles in tumor progression and metastasis. We have previously reported that the mutation of Smad3 linker phosphorylation sites (Smad3-Erk/Pro-directed kinase site mutant constructs [EPSM]) markedly reduced the tumor progression while increasing the lung metastasis in breast cancer. Methods We performed high-throughput RNA-Sequencing of the human prostate cancer cell lines infected with adenoviral Smad3-EPSM to identify the genes regulated by Smad3-EPSM. Results In this study, we identified genes which are differentially regulated in the presence of Smad3-EPSM. We first confirmed that Smad3-EPSM strongly enhanced a capability of cell motility and invasiveness as well as the expression of epithelial-mesenchymal transition marker genes, CDH2, SNAI1, and ZEB1 in response to TGF-β1 in human pancreatic and prostate cancer cell lines. We identified GADD45B, CTGF, and JUNB genes in the expression profiles associated with cell motility and invasiveness induced by the Smad3-EPSM. Conclusions These results suggested that inhibition of Smad3 linker phosphorylation may enhance cell motility and invasiveness by inducing expression of GADD45B, CTGF, and JUNB genes in various cancers. PMID:29629343

Gene expression differences between Noccaea caerulescens ecotypes help to identify candidate genes for metal phytoremediation.

PubMed

Halimaa, Pauliina; Lin, Ya-Fen; Ahonen, Viivi H; Blande, Daniel; Clemens, Stephan; Gyenesei, Attila; Häikiö, Elina; Kärenlampi, Sirpa O; Laiho, Asta; Aarts, Mark G M; Pursiheimo, Juha-Pekka; Schat, Henk; Schmidt, Holger; Tuomainen, Marjo H; Tervahauta, Arja I

2014-03-18

Populations of Noccaea caerulescens show tremendous differences in their capacity to hyperaccumulate and hypertolerate metals. To explore the differences that could contribute to these traits, we undertook SOLiD high-throughput sequencing of the root transcriptomes of three phenotypically well-characterized N. caerulescens accessions, i.e., Ganges, La Calamine, and Monte Prinzera. Genes with possible contribution to zinc, cadmium, and nickel hyperaccumulation and hypertolerance were predicted. The most significant differences between the accessions were related to metal ion (di-, trivalent inorganic cation) transmembrane transporter activity, iron and calcium ion binding, (inorganic) anion transmembrane transporter activity, and antioxidant activity. Analysis of correlation between the expression profile of each gene and the metal-related characteristics of the accessions disclosed both previously characterized (HMA4, HMA3) and new candidate genes (e.g., for nickel IRT1, ZIP10, and PDF2.3) as possible contributors to the hyperaccumulation/tolerance phenotype. A number of unknown Noccaea-specific transcripts also showed correlation with Zn(2+), Cd(2+), or Ni(2+) hyperaccumulation/tolerance. This study shows that N. caerulescens populations have evolved great diversity in the expression of metal-related genes, facilitating adaptation to various metalliferous soils. The information will be helpful in the development of improved plants for metal phytoremediation.

Assessing the potential for AAV vector genotoxicity in a murine model

PubMed Central

Li, Hojun; Malani, Nirav; Hamilton, Shari R.; Schlachterman, Alexander; Bussadori, Giulio; Edmonson, Shyrie E.; Shah, Rachel; Arruda, Valder R.; Mingozzi, Federico; Fraser Wright, J.; Bushman, Frederic D.

2011-01-01

Gene transfer using adeno-associated virus (AAV) vectors has great potential for treating human disease. Recently, questions have arisen about the safety of AAV vectors, specifically, whether integration of vector DNA in transduced cell genomes promotes tumor formation. This study addresses these questions with high-dose liver-directed AAV-mediated gene transfer in the adult mouse as a model (80 AAV-injected mice and 52 controls). After 18 months of follow-up, AAV-injected mice did not show a significantly higher rate of hepatocellular carcinoma compared with controls. Tumors in mice treated with AAV vectors did not have significantly different amounts of vector DNA compared with adjacent normal tissue. A novel high-throughput method for identifying AAV vector integration sites was developed and used to clone 1029 integrants. Integration patterns in tumor tissue and adjacent normal tissue were similar to each other, showing preferences for active genes, cytosine-phosphate-guanosine islands, and guanosine/cysteine-rich regions. Gene expression data showed that genes near integration sites did not show significant changes in expression patterns compared with genes more distal to integration sites. No integration events were identified as causing increased oncogene expression. Thus, we did not find evidence that AAV vectors cause insertional activation of oncogenes and subsequent tumor formation. PMID:21106988

Genome-Wide Characterization and Expression Profiling of the AUXIN RESPONSE FACTOR (ARF) Gene Family in Eucalyptus grandis

PubMed Central

Yu, Hong; Soler, Marçal; Mila, Isabelle; San Clemente, Hélène; Savelli, Bruno; Dunand, Christophe; Paiva, Jorge A. P.; Myburg, Alexander A.; Bouzayen, Mondher; Grima-Pettenati, Jacqueline; Cassan-Wang, Hua

2014-01-01

Auxin is a central hormone involved in a wide range of developmental processes including the specification of vascular stem cells. Auxin Response Factors (ARF) are important actors of the auxin signalling pathway, regulating the transcription of auxin-responsive genes through direct binding to their promoters. The recent availability of the Eucalyptus grandis genome sequence allowed us to examine the characteristics and evolutionary history of this gene family in a woody plant of high economic importance. With 17 members, the E. grandis ARF gene family is slightly contracted, as compared to those of most angiosperms studied hitherto, lacking traces of duplication events. In silico analysis of alternative transcripts and gene truncation suggested that these two mechanisms were preeminent in shaping the functional diversity of the ARF family in Eucalyptus. Comparative phylogenetic analyses with genomes of other taxonomic lineages revealed the presence of a new ARF clade found preferentially in woody and/or perennial plants. High-throughput expression profiling among different organs and tissues and in response to environmental cues highlighted genes expressed in vascular cambium and/or developing xylem, responding dynamically to various environmental stimuli. Finally, this study allowed identification of three ARF candidates potentially involved in the auxin-regulated transcriptional program underlying wood formation. PMID:25269088

Comparative transcriptomics of Pleurotus eryngii reveals blue-light regulation of carbohydrate-active enzymes (CAZymes) expression at primordium differentiated into fruiting body stage.

PubMed

Xie, Chunliang; Gong, Wenbing; Zhu, Zuohua; Yan, Li; Hu, Zhenxiu; Peng, Yuande

2018-05-01

Blue light is an important environmental factor which could induce mushroom primordium differentiation and fruiting body development. However, the mechanisms of Pleurotus eryngii primordium differentiation and development induced by blue light are still unclear. The CAZymes (carbohydrate-active enzymes) play important roles in degradation of renewable lignocelluloses to provide carbohydrates for fungal growth, development and reproduction. In the present research, the expression profiles of genes were measured by comparison between the Pleurotus eryngii at primordium differentiated into fruiting body stage after blue light stimulation and dark using high-throughput sequencing approach. After assembly and compared to the Pleurotus eryngii reference genome, 11,343 unigenes were identified. 539 differentially expressed genes including white collar 2 type of transcription factor gene, A mating type protein gene, MAP kinase gene, oxidative phosphorylation associated genes, CAZymes genes and other metabolism related genes were identified during primordium differentiated into fruiting body stage after blue light stimulation. KEGG results showed that carbon metabolism, glycolysis/gluconeogenesis and biosynthesis of amino acids pathways were affected during blue light inducing primordia formation. Most importantly, 319 differentially expressed CAZymes participated in carbon metabolism were identified. The expression patterns of six representative CAZymes and laccase genes were further confirmed by qRT-PCR. Enzyme activity results indicated that the activities of CAZymes and laccase were affected in primordium differentiated into fruiting body under blue light stimulation. In conclusion, the comprehensive transcriptome and CAZymes of Pleurotus eryngii at primordium differentiated into fruiting body stage after blue light stimulation were obtained. The biological insights gained from this integrative system represent a valuable resource for future genomic studies on this commercially important mushroom. Copyright © 2017. Published by Elsevier Inc.

Methylation and microRNA-mediated epigenetic regulation of SOCS3

PubMed Central

Boosani, Chandra S.; Agrawal, Devendra K.

2017-01-01

Epigenetic gene silencing of several genes causes different pathological conditions in humans, and DNA methylation has been identified as one of the key mechanisms that underlie this evolutionarily conserved phenomenon associated with developmental and pathological gene regulation. Recent advances in the miRNA technology with high throughput analysis of gene regulation further increased our understanding on the role of miRNAs regulating multiple gene expression. There is increasing evidence supporting that the miRNAs not only regulate gene expression but they also are involved in the hypermethylation of promoter sequences, which cumulatively contributes to the epigenetic gene silencing. Here, we critically evaluated the recent progress on the transcriptional regulation of an important suppressor protein that inhibits cytokine-mediated signaling, SOCS3, whose expression is directly regulated both by promoter methylation and also by microRNAs, affecting its vital cell regulating functions. SOCS3 was identified as a potent inhibitor of Jak/STAT signaling pathway which is frequently upregulated in several pathologies, including cardiovascular disease, cancer, diabetes, viral infections, and the expression of SOCS3 was inhibited or greatly reduced due to hypermethylation of the CpG islands in its promoter region or suppression of its expression by different microRNAs. Additionally, we discuss key intracellular signaling pathways regulated by SOCS3 involving cellular events, including cell proliferation, cell growth, cell migration and apoptosis. Identification of the pathway intermediates as specific targets would not only aid in the development of novel therapeutic drugs, but, would also assist in developing new treatment strategies that could successfully be employed in combination therapy to target multiple signaling pathways. PMID:25682267

RNA-sequencing analysis reveals abundant developmental stage-specific and immunity-related genes in the pollen beetle Meligethes aeneus.

PubMed

Vogel, H; Badapanda, C; Knorr, E; Vilcinskas, A

2014-02-01

The pollen beetle (Meligethes aeneus) is a major pest of oilseed rape (Brassica napus) and other cruciferous crops in Europe. Pesticide-resistant pollen beetle populations are emerging, increasing the economic impact of this species. We isolated total RNA from the larval and adult stages, the latter either naïve or immunized by injection with bacteria and yeast. High-throughput RNA sequencing (RNA-Seq) was carried out to establish a comprehensive transcriptome catalogue and to screen for developmental stage-specific and immunity-related transcripts. We assembled the transcriptome de novo by combining sequence tags from all developmental stages and treatments. Gene expression data based on normalized read counts revealed several functional gene categories that were differentially expressed between larvae and adults, particularly genes associated with digestion and detoxification that were induced in larvae, and genes associated with reproduction and environmental signalling that were induced in adults. We also identified many genes associated with microbe recognition, immunity-related signalling and defence effectors, such as antimicrobial peptides (AMPs) and lysozymes. Digital gene expression analysis revealed significant differences in the profile of AMPs expressed in larvae, naïve adults and immune-challenged adults, providing insight into the steady-state differences between developmental stages and the complex transcriptional remodelling that occurs following the induction of immunity. Our data provide insight into the adaptive mechanisms used by phytophagous insects and could lead to the development of more effective control strategies for insect pests. © 2013 The Royal Entomological Society.

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

Expression profiling during arabidopsis/downy mildew interaction reveals a highly-expressed effector that attenuates responses to salicylic acid.

PubMed

Asai, Shuta; Rallapalli, Ghanasyam; Piquerez, Sophie J M; Caillaud, Marie-Cécile; Furzer, Oliver J; Ishaque, Naveed; Wirthmueller, Lennart; Fabro, Georgina; Shirasu, Ken; Jones, Jonathan D G

2014-10-01

Plants have evolved strong innate immunity mechanisms, but successful pathogens evade or suppress plant immunity via effectors delivered into the plant cell. Hyaloperonospora arabidopsidis (Hpa) causes downy mildew on Arabidopsis thaliana, and a genome sequence is available for isolate Emoy2. Here, we exploit the availability of genome sequences for Hpa and Arabidopsis to measure gene-expression changes in both Hpa and Arabidopsis simultaneously during infection. Using a high-throughput cDNA tag sequencing method, we reveal expression patterns of Hpa predicted effectors and Arabidopsis genes in compatible and incompatible interactions, and promoter elements associated with Hpa genes expressed during infection. By resequencing Hpa isolate Waco9, we found it evades Arabidopsis resistance gene RPP1 through deletion of the cognate recognized effector ATR1. Arabidopsis salicylic acid (SA)-responsive genes including PR1 were activated not only at early time points in the incompatible interaction but also at late time points in the compatible interaction. By histochemical analysis, we found that Hpa suppresses SA-inducible PR1 expression, specifically in the haustoriated cells into which host-translocated effectors are delivered, but not in non-haustoriated adjacent cells. Finally, we found a highly-expressed Hpa effector candidate that suppresses responsiveness to SA. As this approach can be easily applied to host-pathogen interactions for which both host and pathogen genome sequences are available, this work opens the door towards transcriptome studies in infection biology that should help unravel pathogen infection strategies and the mechanisms by which host defense responses are overcome.

High-throughput tool to discriminate effects of NMs (Cu-NPs, Cu-nanowires, CuNO3, and Cu salt aged): transcriptomics in Enchytraeus crypticus.

PubMed

Gomes, Susana I L; Roca, Carlos P; Pegoraro, Natália; Trindade, Tito; Scott-Fordsmand, Janeck J; Amorim, Mónica J B

2018-05-01

The current testing of nanomaterials (NMs) via standard toxicity tests does not cover many of the NMs specificities. One of the recommendations lays on understanding the mechanisms of action, as these can help predicting long-term effects and safe-by-design production. In the present study, we used the high-throughput gene expression tool, developed for Enchytraeus crypticus (4 × 44k Agilent microarray), to study the effects of exposure to several copper (Cu) forms. The Cu treatments included two NMs (spherical and wires) and two copper-salt treatments (CuNO 3 spiked and Cu salt field historical contamination). To relate gene expression with higher effect level, testing was done with reproduction effect concentrations (EC 20 , EC 50 ), using 3 and 7 days as exposure periods. Results showed that time plays a major role in the transcriptomic response, most of it occurring after 3 days. Analysis of gene expression profiles showed that Cu-salt-aged and Cu-nanowires (Nwires) differed from CuNO 3 and Cu-nanoparticles (NPs). Functional analysis revealed specific mechanisms: Cu-NPs uniquely affected senescence and cuticle pattern formation, which can result from the contact of the NPs with the worms' tegument. Cu-Nwires affected reproduction via male gamete generation and hermaphrodite genitalia development. CuNO 3 affected neurotransmission and locomotory behavior, both of which can be related with avoidance response. Cu salt-aged uniquely affected phagocytosis and reproductive system development (via different mechanisms than Cu-Nwires). For the first time for Cu (nano)materials, the adverse outcome pathways (AOPs) drafted here provide an overview for common and unique effects per material and linkage with apical effects.

High-throughput sequencing of the chloroplast and mitochondrion of Chlamydomonas reinhardtii to generate improved de novo assemblies, analyze expression patterns and transcript speciation, and evaluate diversity among laboratory strains and wild isolates

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

Gallaher, Sean D.; Fitz-Gibbon, Sorel T.; Strenkert, Daniela

Chlamydomonas reinhardtii is a unicellular chlorophyte alga that is widely studied as a reference organism for understanding photosynthesis, sensory and motile cilia, and for development of an algal-based platform for producing biofuels and bio-products. Its highly repetitive, ~205-kbp circular chloroplast genome and ~15.8-kbp linear mitochondrial genome were sequenced prior to the advent of high-throughput sequencing technologies. Here, high coverage shotgun sequencing was used to assemble both organellar genomes de novo. These new genomes correct dozens of errors in the prior genome sequences and annotations. Gen-ome sequencing coverage indicates that each cell contains on average 83 copies of the chloroplast genomemore » and 130 copies of the mitochondrial genome. Using protocols and analyses optimized for organellar tran-scripts, RNA-Seq was used to quantify their relative abundances across 12 different growth conditions. Forty-six percent of total cellular mRNA is attributable to high expression from a few dozen chloroplast genes. RNA-Seq data were used to guide gene annotation, to demonstrate polycistronic gene expression, and to quantify splicing of psaA and psbA introns. In contrast to a conclusion from a recent study, we found that chloroplast transcripts are not edited. Unexpectedly, cytosine-rich polynucleotide tails were observed at the 3’-end of all mitochondrial transcripts. A comparative genomics analysis of eight laboratory strains and 11 wild isolates of C. reinhardtii identified 2658 variants in the organellargenomes, which is 1/10th as much genetic diversity as is found in the nucleus.« less

The Prediction of Drug-Disease Correlation Based on Gene Expression Data.

PubMed

Cui, Hui; Zhang, Menghuan; Yang, Qingmin; Li, Xiangyi; Liebman, Michael; Yu, Ying; Xie, Lu

2018-01-01

The explosive growth of high-throughput experimental methods and resulting data yields both opportunity and challenge for selecting the correct drug to treat both a specific patient and their individual disease. Ideally, it would be useful and efficient if computational approaches could be applied to help achieve optimal drug-patient-disease matching but current efforts have met with limited success. Current approaches have primarily utilized the measureable effect of a specific drug on target tissue or cell lines to identify the potential biological effect of such treatment. While these efforts have met with some level of success, there exists much opportunity for improvement. This specifically follows the observation that, for many diseases in light of actual patient response, there is increasing need for treatment with combinations of drugs rather than single drug therapies. Only a few previous studies have yielded computational approaches for predicting the synergy of drug combinations by analyzing high-throughput molecular datasets. However, these computational approaches focused on the characteristics of the drug itself, without fully accounting for disease factors. Here, we propose an algorithm to specifically predict synergistic effects of drug combinations on various diseases, by integrating the data characteristics of disease-related gene expression profiles with drug-treated gene expression profiles. We have demonstrated utility through its application to transcriptome data, including microarray and RNASeq data, and the drug-disease prediction results were validated using existing publications and drug databases. It is also applicable to other quantitative profiling data such as proteomics data. We also provide an interactive web interface to allow our Prediction of Drug-Disease method to be readily applied to user data. While our studies represent a preliminary exploration of this critical problem, we believe that the algorithm can provide the basis for further refinement towards addressing a large clinical need.

Integrative ChIP-seq/Microarray Analysis Identifies a CTNNB1 Target Signature Enriched in Intestinal Stem Cells and Colon Cancer

PubMed Central

Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L.; Roberts, Brian S.; Arthur, William T.; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

2014-01-01

Background Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. Results We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Conclusion Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells. PMID:24651522

Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

PubMed

Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

2014-01-01

Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

Cancer biomarker discovery: the entropic hallmark.

PubMed

Berretta, Regina; Moscato, Pablo

2010-08-18

It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases.

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.

Apple ring rot-responsive putative microRNAs revealed by high-throughput sequencing in Malus × domestica Borkh.

PubMed

Yu, Xin-Yi; Du, Bei-Bei; Gao, Zhi-Hong; Zhang, Shi-Jie; Tu, Xu-Tong; Chen, Xiao-Yun; Zhang, Zhen; Qu, Shen-Chun

2014-08-01

MicroRNAs (miRNAs) are small non-coding RNAs, which silence target mRNA via cleavage or translational inhibition to function in regulating gene expression. MiRNAs act as important regulators of plant development and stress response. For understanding the role of miRNAs responsive to apple ring rot stress, we identified disease-responsive miRNAs using high-throughput sequencing in Malus × domestica Borkh.. Four small RNA libraries were constructed from two control strains in M. domestica, crabapple (CKHu) and Fuji Naga-fu No. 6 (CKFu), and two disease stress strains, crabapple (DSHu) and Fuji Naga-fu No. 6 (DSFu). A total of 59 miRNA families were identified and five miRNAs might be responsive to apple ring rot infection and validated via qRT-PCR. Furthermore, we predicted 76 target genes which were regulated by conserved miRNAs potentially. Our study demonstrated that miRNAs was responsive to apple ring rot infection and may have important implications on apple disease resistance.

High-throughput microfluidics to control and measure signaling dynamics in single yeast cells

PubMed Central

Hansen, Anders S.; Hao, Nan; O'Shea, Erin K.

2015-01-01

Microfluidics coupled to quantitative time-lapse fluorescence microscopy is transforming our ability to control, measure, and understand signaling dynamics in single living cells. Here we describe a pipeline that incorporates multiplexed microfluidic cell culture, automated programmable fluid handling for cell perturbation, quantitative time-lapse microscopy, and computational analysis of time-lapse movies. We illustrate how this setup can be used to control the nuclear localization of the budding yeast transcription factor Msn2. Using this protocol, we generate oscillations of Msn2 localization and measure the dynamic gene expression response of individual genes in single cells. The protocol allows a single researcher to perform up to 20 different experiments in a single day, whilst collecting data for thousands of single cells. Compared to other protocols, the present protocol is relatively easy to adopt and higher-throughput. The protocol can be widely used to control and monitor single-cell signaling dynamics in other signal transduction systems in microorganisms. PMID:26158443

New Era of Studying RNA Secondary Structure and Its Influence on Gene Regulation in Plants.

PubMed

Yang, Xiaofei; Yang, Minglei; Deng, Hongjing; Ding, Yiliang

2018-01-01

The dynamic structure of RNA plays a central role in post-transcriptional regulation of gene expression such as RNA maturation, degradation, and translation. With the rise of next-generation sequencing, the study of RNA structure has been transformed from in vitro low-throughput RNA structure probing methods to in vivo high-throughput RNA structure profiling. The development of these methods enables incremental studies on the function of RNA structure to be performed, revealing new insights of novel regulatory mechanisms of RNA structure in plants. Genome-wide scale RNA structure profiling allows us to investigate general RNA structural features over 10s of 1000s of mRNAs and to compare RNA structuromes between plant species. Here, we provide a comprehensive and up-to-date overview of: (i) RNA structure probing methods; (ii) the biological functions of RNA structure; (iii) genome-wide RNA structural features corresponding to their regulatory mechanisms; and (iv) RNA structurome evolution in plants.

Sensitive and quantitative measurement of gene expression directly from a small amount of whole blood.

PubMed

Zheng, Zhi; Luo, Yuling; McMaster, Gary K

2006-07-01

Accurate and precise quantification of mRNA in whole blood is made difficult by gene expression changes during blood processing, and by variations and biases introduced by sample preparations. We sought to develop a quantitative whole-blood mRNA assay that eliminates blood purification, RNA isolation, reverse transcription, and target amplification while providing high-quality data in an easy assay format. We performed single- and multiplex gene expression analysis with multiple hybridization probes to capture mRNA directly from blood lysate and used branched DNA to amplify the signal. The 96-well plate singleplex assay uses chemiluminescence detection, and the multiplex assay combines Luminex-encoded beads with fluorescent detection. The single- and multiplex assays could quantitatively measure as few as 6000 and 24,000 mRNA target molecules (0.01 and 0.04 amoles), respectively, in up to 25 microL of whole blood. Both formats had CVs < 10% and dynamic ranges of 3-4 logs. Assay sensitivities allowed quantitative measurement of gene expression in the minority of cells in whole blood. The signals from whole-blood lysate correlated well with signals from purified RNA of the same sample, and absolute mRNA quantification results from the assay were similar to those obtained by quantitative reverse transcription-PCR. Both single- and multiplex assay formats were compatible with common anticoagulants and PAXgene-treated samples; however, PAXgene preparations induced expression of known antiapoptotic genes in whole blood. Both the singleplex and the multiplex branched DNA assays can quantitatively measure mRNA expression directly from small volumes of whole blood. The assay offers an alternative to current technologies that depend on RNA isolation and is amenable to high-throughput gene expression analysis of whole blood.

Applying Genomic and Genetic Tools to Understand and Mitigate Damage from Exposure to Toxins

DTIC Science & Technology

2011-10-01

Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Use of the pyridostigmine bromide during the 1991 Gulf War has been implicated as a contributing...2 EXECUTIVE SUMMARY Treatment of soldiers of the 1991 Gulf War with the drug pyridostigmine bromide for pretreatment against nerve agents has...organism for the characterization of the effects of pyridostigmine bromide (PB) on gene expression using unbiased, high-throughput techniques, specifically

Single-cell multimodal profiling reveals cellular epigenetic heterogeneity.

PubMed

Cheow, Lih Feng; Courtois, Elise T; Tan, Yuliana; Viswanathan, Ramya; Xing, Qiaorui; Tan, Rui Zhen; Tan, Daniel S W; Robson, Paul; Loh, Yuin-Han; Quake, Stephen R; Burkholder, William F

2016-10-01

Sample heterogeneity often masks DNA methylation signatures in subpopulations of cells. Here, we present a method to genotype single cells while simultaneously interrogating gene expression and DNA methylation at multiple loci. We used this targeted multimodal approach, implemented on an automated, high-throughput microfluidic platform, to assess primary lung adenocarcinomas and human fibroblasts undergoing reprogramming by profiling epigenetic variation among cell types identified through genotyping and transcriptional analysis.

cDNA Clones with Rare and Recurrent Mutations Found in Cancers | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at UT- MD Anderson Cancer Center has developed High-Throughput Mutagenesis and Molecular Barcoding (HiTMMoB)1,2 pipeline to construct mutant alleles open reading frame expression clones that are either recurrent or rare in cancers. These barcoded genes can be used for context-specific functional validation, detection of novel biomarkers (pathway activation) and targets (drug sensitivity).

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

Quantitative High-Throughput Identification of Drugs as Modulators of Human Constitutive Androstane Receptor

PubMed Central

Lynch, Caitlin; Zhao, Jinghua; Huang, Ruili; Xiao, Jingwei; Li, Linhao; Heyward, Scott; Xia, Menghang; Wang, Hongbing

2015-01-01

The constitutive androstane receptor (CAR, NR1I3) plays a key role in governing the transcription of numerous hepatic genes that involve xenobiotic metabolism/clearance, energy homeostasis, and cell proliferation. Thus, identification of novel human CAR (hCAR) modulators may not only enhance early prediction of drug-drug interactions but also offer potentially novel therapeutics for diseases such as metabolic disorders and cancer. In this study, we have generated a double stable cell line expressing both hCAR and a CYP2B6-driven luciferase reporter for quantitative high-throughput screening (qHTS) of hCAR modulators. Approximately 2800 compounds from the NIH Chemical Genomics Center Pharmaceutical Collection were screened employing both the activation and deactivation modes of the qHTS. Activators (115) and deactivators (152) of hCAR were identified from the primary qHTS, among which 10 agonists and 10 antagonists were further validated in the physiologically relevant human primary hepatocytes for compound-mediated hCAR nuclear translocation and target gene expression. Collectively, our results reveal that hCAR modulators can be efficiently identified through this newly established qHTS assay. Profiling drug collections for hCAR activity would facilitate the prediction of metabolism-based drug-drug interactions, and may lead to the identification of potential novel therapeutics. PMID:25993555

A Mixture Modeling Framework for Differential Analysis of High-Throughput Data

PubMed Central

Taslim, Cenny; Lin, Shili

2014-01-01

The inventions of microarray and next generation sequencing technologies have revolutionized research in genomics; platforms have led to massive amount of data in gene expression, methylation, and protein-DNA interactions. A common theme among a number of biological problems using high-throughput technologies is differential analysis. Despite the common theme, different data types have their own unique features, creating a “moving target” scenario. As such, methods specifically designed for one data type may not lead to satisfactory results when applied to another data type. To meet this challenge so that not only currently existing data types but also data from future problems, platforms, or experiments can be analyzed, we propose a mixture modeling framework that is flexible enough to automatically adapt to any moving target. More specifically, the approach considers several classes of mixture models and essentially provides a model-based procedure whose model is adaptive to the particular data being analyzed. We demonstrate the utility of the methodology by applying it to three types of real data: gene expression, methylation, and ChIP-seq. We also carried out simulations to gauge the performance and showed that the approach can be more efficient than any individual model without inflating type I error. PMID:25057284

The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens.

PubMed

Hutz, Janna E; Nelson, Thomas; Wu, Hua; McAllister, Gregory; Moutsatsos, Ioannis; Jaeger, Savina A; Bandyopadhyay, Somnath; Nigsch, Florian; Cornett, Ben; Jenkins, Jeremy L; Selinger, Douglas W

2013-04-01

Screens using high-throughput, information-rich technologies such as microarrays, high-content screening (HCS), and next-generation sequencing (NGS) have become increasingly widespread. Compared with single-readout assays, these methods produce a more comprehensive picture of the effects of screened treatments. However, interpreting such multidimensional readouts is challenging. Univariate statistics such as t-tests and Z-factors cannot easily be applied to multidimensional profiles, leaving no obvious way to answer common screening questions such as "Is treatment X active in this assay?" and "Is treatment X different from (or equivalent to) treatment Y?" We have developed a simple, straightforward metric, the multidimensional perturbation value (mp-value), which can be used to answer these questions. Here, we demonstrate application of the mp-value to three data sets: a multiplexed gene expression screen of compounds and genomic reagents, a microarray-based gene expression screen of compounds, and an HCS compound screen. In all data sets, active treatments were successfully identified using the mp-value, and simulations and follow-up analyses supported the mp-value's statistical and biological validity. We believe the mp-value represents a promising way to simplify the analysis of multidimensional data while taking full advantage of its richness.

High-throughput screening for modulators of ACVR1 transcription: discovery of potential therapeutics for fibrodysplasia ossificans progressiva

PubMed Central

Cappato, Serena; Tonachini, Laura; Giacopelli, Francesca; Tirone, Mario; Galietta, Luis J. V.; Sormani, Martina; Giovenzana, Anna; Spinelli, Antonello E.; Canciani, Barbara; Brunelli, Silvia; Ravazzolo, Roberto

2016-01-01

ABSTRACT The ACVR1 gene encodes a type I receptor of bone morphogenetic proteins (BMPs). Activating mutations in ACVR1 are responsible for fibrodysplasia ossificans progressiva (FOP), a rare disease characterized by congenital toe malformation and progressive heterotopic endochondral ossification leading to severe and cumulative disability. Until now, no therapy has been available to prevent soft-tissue swelling (flare-ups) that trigger the ossification process. With the aim of finding a new therapeutic strategy for FOP, we developed a high-throughput screening (HTS) assay to identify inhibitors of ACVR1 gene expression among drugs already approved for the therapy of other diseases. The screening, based on an ACVR1 promoter assay, was followed by an in vitro and in vivo test to validate and characterize candidate molecules. Among compounds that modulate the ACVR1 promoter activity, we selected the one showing the highest inhibitory effect, dipyridamole, a drug that is currently used as a platelet anti-aggregant. The inhibitory effect was detectable on ACVR1 gene expression, on the whole Smad-dependent BMP signaling pathway, and on chondrogenic and osteogenic differentiation processes by in vitro cellular assays. Moreover, dipyridamole reduced the process of heterotopic bone formation in vivo. Our drug repositioning strategy has led to the identification of dipyridamole as a possible therapeutic tool for the treatment of FOP. Furthermore, our study has also defined a pipeline of assays that will be useful for the evaluation of other pharmacological inhibitors of heterotopic ossification. PMID:27125279

Macromolecule exchange in Cuscuta-host plant interactions.

PubMed

Kim, Gunjune; Westwood, James H

2015-08-01

Cuscuta species (dodders) are parasitic plants that are able to grow on many different host plants and can be destructive to crops. The connections between Cuscuta and its hosts allow movement of not only water and small nutrients, but also macromolecules including mRNA, proteins and viruses. Recent studies show that RNAs move bidirectionally between hosts and parasites and involve a large number of different genes. Although the function of mobile mRNAs has not been demonstrated in this system, small RNAs are also transmitted and a silencing construct expressed in hosts is able to affect expression of the target gene in the parasite. High throughput sequencing of host-parasite associations has the potential to greatly accelerate understanding of this remarkable interaction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Correlation analysis of the mRNA and miRNA expression profiles in the nascent synthetic allotetraploid Raphanobrassica

PubMed Central

Ye, Bingyuan; Wang, Ruihua; Wang, Jianbo

2016-01-01

Raphanobrassica is an allopolyploid species derived from inter-generic hybridization that combines the R genome from R. sativus and the C genome from B. oleracea var. alboglabra. In the present study, we used a high-throughput sequencing method to identify the mRNA and miRNA profiles in Raphanobrassica and its parents. A total of 33,561 mRNAs and 283 miRNAs were detected, 9,209 mRNAs and 134 miRNAs were differentially expressed respectively, 7,633 mRNAs and 39 miRNAs showed ELD expression, 5,219 mRNAs and 57 miRNAs were non-additively expressed in Raphanobrassica. Remarkably, differentially expressed genes (DEGs) were up-regulated and maternal bias was detected in Raphanobrassica. In addition, a miRNA-mRNA interaction network was constructed based on reverse regulated miRNA-mRNAs, which included 75 miRNAs and 178 mRNAs, 31 miRNAs were non-additively expressed target by 13 miRNAs. The related target genes were significantly enriched in the GO term ‘metabolic processes’. Non-additive related target genes regulation is involved in a range of biological pathways, like providing a driving force for variation and adaption in this allopolyploid. The integrative analysis of mRNA and miRNA profiling provides more information to elucidate gene expression mechanism and may supply a comprehensive and corresponding method to study genetic and transcription variation of allopolyploid. PMID:27874043

Microaspiration of esophageal gland cells and cDNA library construction for identifying parasitism genes of plant-parasitic nematodes.

PubMed

Hussey, Richard S; Huang, Guozhong; Allen, Rex

2011-01-01

Identifying parasitism genes encoding proteins secreted from a plant-parasitic nematode's esophageal gland cells and injected through its stylet into plant tissue is the key to understanding the molecular basis of nematode parasitism of plants. Parasitism genes have been cloned by directly microaspirating the cytoplasm from the esophageal gland cells of different parasitic stages of cyst or root-knot nematodes to provide mRNA to create a gland cell-specific cDNA library by long-distance reverse-transcriptase polymerase chain reaction. cDNA clones are sequenced and deduced protein sequences with a signal peptide for secretion are identified for high-throughput in situ hybridization to confirm gland-specific expression.

Molecular Cloning of Secreted Luciferases from Marine Planktonic Copepods.

PubMed

Takenaka, Yasuhiro; Ikeo, Kazuho; Shigeri, Yasushi

2016-01-01

Secreted luciferases isolated from copepod crustaceans are frequently used for nondisruptive reporter-gene assays, such as the continuous, automated and/or high-throughput monitoring of gene expression in living cells. All known copepod luciferases share highly conserved amino acid residues in two similar, repeated domains in the sequence. The similarity in the domains are ideal nature for designing PCR primers to amplify cDNA fragments of unidentified copepod luciferases from bioluminescent copepod crustaceans. Here, we introduce how to establish a cDNA encoding novel copepod luciferases from a copepod specimen by PCR with degenerated primers.

Sorting Out Antibiotics' Mechanisms of Action: a Double Fluorescent Protein Reporter for High-Throughput Screening of Ribosome and DNA Biosynthesis Inhibitors

PubMed Central

Osterman, Ilya A.; Komarova, Ekaterina S.; Shiryaev, Dmitry I.; Korniltsev, Ilya A.; Khven, Irina M.; Lukyanov, Dmitry A.; Tashlitsky, Vadim N.; Serebryakova, Marina V.; Efremenkova, Olga V.; Ivanenkov, Yan A.; Bogdanov, Alexey A.; Dontsova, Olga A.

2016-01-01

In order to accelerate drug discovery, a simple, reliable, and cost-effective system for high-throughput identification of a potential antibiotic mechanism of action is required. To facilitate such screening of new antibiotics, we created a double-reporter system for not only antimicrobial activity detection but also simultaneous sorting of potential antimicrobials into those that cause ribosome stalling and those that induce the SOS response due to DNA damage. In this reporter system, the red fluorescent protein gene rfp was placed under the control of the SOS-inducible sulA promoter. The gene of the far-red fluorescent protein, katushka2S, was inserted downstream of the tryptophan attenuator in which two tryptophan codons were replaced by alanine codons, with simultaneous replacement of the complementary part of the attenuator to preserve the ability to form secondary structures that influence transcription termination. This genetically modified attenuator makes possible Katushka2S expression only upon exposure to ribosome-stalling compounds. The application of red and far-red fluorescent proteins provides a high signal-to-background ratio without any need of enzymatic substrates for detection of the reporter activity. This reporter was shown to be efficient in high-throughput screening of both synthetic and natural chemicals. PMID:27736765

A paper-based microbial fuel cell array for rapid and high-throughput screening of electricity-producing bacteria.

PubMed

Choi, Gihoon; Hassett, Daniel J; Choi, Seokheun

2015-06-21

There is a large global effort to improve microbial fuel cell (MFC) techniques and advance their translational potential toward practical, real-world applications. Significant boosts in MFC performance can be achieved with the development of new techniques in synthetic biology that can regulate microbial metabolic pathways or control their gene expression. For these new directions, a high-throughput and rapid screening tool for microbial biopower production is needed. In this work, a 48-well, paper-based sensing platform was developed for the high-throughput and rapid characterization of the electricity-producing capability of microbes. 48 spatially distinct wells of a sensor array were prepared by patterning 48 hydrophilic reservoirs on paper with hydrophobic wax boundaries. This paper-based platform exploited the ability of paper to quickly wick fluid and promoted bacterial attachment to the anode pads, resulting in instant current generation upon loading of the bacterial inoculum. We validated the utility of our MFC array by studying how strategic genetic modifications impacted the electrochemical activity of various Pseudomonas aeruginosa mutant strains. Within just 20 minutes, we successfully determined the electricity generation capacity of eight isogenic mutants of P. aeruginosa. These efforts demonstrate that our MFC array displays highly comparable performance characteristics and identifies genes in P. aeruginosa that can trigger a higher power density.

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.

DEEP--a tool for differential expression effector prediction.

PubMed

Degenhardt, Jost; Haubrock, Martin; Dönitz, Jürgen; Wingender, Edgar; Crass, Torsten

2007-07-01

High-throughput methods for measuring transcript abundance, like SAGE or microarrays, are widely used for determining differences in gene expression between different tissue types, dignities (normal/malignant) or time points. Further analysis of such data frequently aims at the identification of gene interaction networks that form the causal basis for the observed properties of the systems under examination. To this end, it is usually not sufficient to rely on the measured gene expression levels alone; rather, additional biological knowledge has to be taken into account in order to generate useful hypotheses about the molecular mechanism leading to the realization of a certain phenotype. We present a method that combines gene expression data with biological expert knowledge on molecular interaction networks, as described by the TRANSPATH database on signal transduction, to predict additional--and not necessarily differentially expressed--genes or gene products which might participate in processes specific for either of the examined tissues or conditions. In a first step, significance values for over-expression in tissue/condition A or B are assigned to all genes in the expression data set. Genes with a significance value exceeding a certain threshold are used as starting points for the reconstruction of a graph with signaling components as nodes and signaling events as edges. In a subsequent graph traversal process, again starting from the previously identified differentially expressed genes, all encountered nodes 'inherit' all their starting nodes' significance values. In a final step, the graph is visualized, the nodes being colored according to a weighted average of their inherited significance values. Each node's, or sub-network's, predominant color, ranging from green (significant for tissue/condition A) over yellow (not significant for either tissue/condition) to red (significant for tissue/condition B), thus gives an immediate visual clue on which molecules--differentially expressed or not--may play pivotal roles in the tissues or conditions under examination. The described method has been implemented in Java as a client/server application and a web interface called DEEP (Differential Expression Effector Prediction). The client, which features an easy-to-use graphical interface, can freely be downloaded from the following URL: http://deep.bioinf.med.uni-goettingen.de.

Printing Proteins as Microarrays for High-Throughput Function Determination

NASA Astrophysics Data System (ADS)

MacBeath, Gavin; Schreiber, Stuart L.

2000-09-01

Systematic efforts are currently under way to construct defined sets of cloned genes for high-throughput expression and purification of recombinant proteins. To facilitate subsequent studies of protein function, we have developed miniaturized assays that accommodate extremely low sample volumes and enable the rapid, simultaneous processing of thousands of proteins. A high-precision robot designed to manufacture complementary DNA microarrays was used to spot proteins onto chemically derivatized glass slides at extremely high spatial densities. The proteins attached covalently to the slide surface yet retained their ability to interact specifically with other proteins, or with small molecules, in solution. Three applications for protein microarrays were demonstrated: screening for protein-protein interactions, identifying the substrates of protein kinases, and identifying the protein targets of small molecules.

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods

PubMed Central

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-01-01

Background Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. Objectives The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. Materials and Methods In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman’s rank correlation coefficient and Blomqvist’s measure, and compared them with Pearson’s correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson’s correlation, Spearman’s rank correlation, and Blomqvist’s coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Results Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist’s coefficient was not confirmed by visual methods. Conclusions Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data. PMID:27621916

Engineering customized TALE nucleases (TALENs) and TALE transcription factors by fast ligation-based automatable solid-phase high-throughput (FLASH) assembly.

PubMed

Reyon, Deepak; Maeder, Morgan L; Khayter, Cyd; Tsai, Shengdar Q; Foley, Jonathan E; Sander, Jeffry D; Joung, J Keith

2013-07-01

Customized DNA-binding domains made using transcription activator-like effector (TALE) repeats are rapidly growing in importance as widely applicable research tools. TALE nucleases (TALENs), composed of an engineered array of TALE repeats fused to the FokI nuclease domain, have been used successfully for directed genome editing in various organisms and cell types. TALE transcription factors (TALE-TFs), consisting of engineered TALE repeat arrays linked to a transcriptional regulatory domain, have been used to up- or downregulate expression of endogenous genes in human cells and plants. This unit describes a detailed protocol for the recently described fast ligation-based automatable solid-phase high-throughput (FLASH) assembly method. FLASH enables automated high-throughput construction of engineered TALE repeats using an automated liquid handling robot or manually using a multichannel pipet. Using the automated approach, a single researcher can construct up to 96 DNA fragments encoding TALE repeat arrays of various lengths in a single day, and then clone these to construct sequence-verified TALEN or TALE-TF expression plasmids in a week or less. Plasmids required for FLASH are available by request from the Joung lab (http://eGenome.org). This unit also describes improvements to the Zinc Finger and TALE Targeter (ZiFiT Targeter) web server (http://ZiFiT.partners.org) that facilitate the design and construction of FLASH TALE repeat arrays in high throughput. © 2013 by John Wiley & Sons, Inc.

Engineering Customized TALE Nucleases (TALENs) and TALE Transcription Factors by Fast Ligation-based Automatable Solid-phase High-throughput (FLASH) Assembly

PubMed Central

Reyon, Deepak; Maeder, Morgan L.; Khayter, Cyd; Tsai, Shengdar Q.; Foley, Jonathan E.; Sander, Jeffry D.; Joung, J. Keith

2013-01-01

Customized DNA-binding domains made using Transcription Activator-Like Effector (TALE) repeats are rapidly growing in importance as widely applicable research tools. TALE nucleases (TALENs), composed of an engineered array of TALE repeats fused to the FokI nuclease domain, have been used successfully for directed genome editing in multiple different organisms and cell types. TALE transcription factors (TALE-TFs), consisting of engineered TALE repeat arrays linked to a transcriptional regulatory domain, have been used to up- or down-regulate expression of endogenous genes in human cells and plants. Here we describe a detailed protocol for practicing the recently described Fast Ligation-based Automatable Solid-phase High-throughput (FLASH) assembly method. FLASH enables automated high-throughput construction of engineered TALE repeats using an automated liquid handling robot or manually using a multi-channel pipet. With the automated version of FLASH, a single researcher can construct up to 96 DNA fragments encoding various length TALE repeat arrays in one day and then clone these to construct sequence-verified TALEN or TALE-TF expression plasmids in one week or less. Plas-mids required to practice FLASH are available by request from the Joung Lab (http://www.jounglab.org/). We also describe here improvements to the Zinc Finger and TALE Targeter (ZiFiT Targeter) webserver (http://ZiFiTBeta.partners.org) that facilitate the design and construction of FLASH TALE repeat arrays in high-throughput. PMID:23821439

Transcriptome and gene expression analysis of DHA producer Aurantiochytrium under low temperature conditions

PubMed Central

Ma, Zengxin; Tan, Yanzhen; Cui, Guzhen; Feng, Yingang; Cui, Qiu; Song, Xiaojin

2015-01-01

Aurantiochytrium is a promising docosahexaenoic acid (DHA) production candidate due to its fast growth rate and high proportions of lipid and DHA content. In this study, high-throughput RNA sequencing technology was employed to explore the acclimatization of this DHA producer under cold stress at the transcriptional level. The overall de novo assembly of the cDNA sequence data generated 29,783 unigenes, with an average length of 1,200 bp. In total, 13,245 unigenes were annotated in at least one database. A comparative genomic analysis between normal conditions and cold stress revealed that 2,013 genes were differentially expressed during the growth stage, while 2,071 genes were differentially expressed during the lipid accumulation stage. Further functional categorization and analyses showed some differentially expressed genes were involved in processes crucial to cold acclimation, such as signal transduction, cellular component biogenesis, and carbohydrate and lipid metabolism. A brief survey of the transcripts obtained in response to cold stress underlines the survival strategy of Aurantiochytrium; of these transcripts, many directly or indirectly influence the lipid composition. This is the first study to perform a transcriptomic analysis of the Aurantiochytrium under low temperature conditions. Our results will help to enhance DHA production by Aurantiochytrium in the future. PMID:26403200

Transcriptome and gene expression analysis of DHA producer Aurantiochytrium under low temperature conditions.

PubMed

Ma, Zengxin; Tan, Yanzhen; Cui, Guzhen; Feng, Yingang; Cui, Qiu; Song, Xiaojin

2015-09-25

Aurantiochytrium is a promising docosahexaenoic acid (DHA) production candidate due to its fast growth rate and high proportions of lipid and DHA content. In this study, high-throughput RNA sequencing technology was employed to explore the acclimatization of this DHA producer under cold stress at the transcriptional level. The overall de novo assembly of the cDNA sequence data generated 29,783 unigenes, with an average length of 1,200 bp. In total, 13,245 unigenes were annotated in at least one database. A comparative genomic analysis between normal conditions and cold stress revealed that 2,013 genes were differentially expressed during the growth stage, while 2,071 genes were differentially expressed during the lipid accumulation stage. Further functional categorization and analyses showed some differentially expressed genes were involved in processes crucial to cold acclimation, such as signal transduction, cellular component biogenesis, and carbohydrate and lipid metabolism. A brief survey of the transcripts obtained in response to cold stress underlines the survival strategy of Aurantiochytrium; of these transcripts, many directly or indirectly influence the lipid composition. This is the first study to perform a transcriptomic analysis of the Aurantiochytrium under low temperature conditions. Our results will help to enhance DHA production by Aurantiochytrium in the future.

Step-by-Step Construction of Gene Co-expression Networks from High-Throughput Arabidopsis RNA Sequencing Data.

PubMed

Contreras-López, Orlando; Moyano, Tomás C; Soto, Daniela C; Gutiérrez, Rodrigo A

2018-01-01

The rapid increase in the availability of transcriptomics data generated by RNA sequencing represents both a challenge and an opportunity for biologists without bioinformatics training. The challenge is handling, integrating, and interpreting these data sets. The opportunity is to use this information to generate testable hypothesis to understand molecular mechanisms controlling gene expression and biological processes (Fig. 1). A successful strategy to generate tractable hypotheses from transcriptomics data has been to build undirected network graphs based on patterns of gene co-expression. Many examples of new hypothesis derived from network analyses can be found in the literature, spanning different organisms including plants and specific fields such as root developmental biology.In order to make the process of constructing a gene co-expression network more accessible to biologists, here we provide step-by-step instructions using published RNA-seq experimental data obtained from a public database. Similar strategies have been used in previous studies to advance root developmental biology. This guide includes basic instructions for the operation of widely used open source platforms such as Bio-Linux, R, and Cytoscape. Even though the data we used in this example was obtained from Arabidopsis thaliana, the workflow developed in this guide can be easily adapted to work with RNA-seq data from any organism.

Transcriptomic analysis of Crassostrea sikamea × Crassostrea angulata hybrids in response to low salinity stress.

PubMed

Yan, Lulu; Su, Jiaqi; Wang, Zhaoping; Yan, Xiwu; Yu, Ruihai; Ma, Peizhen; Li, Yangchun; Du, Junpeng

2017-01-01

Hybrid oysters often show heterosis in growth rate, weight, survival and adaptability to extremes of salinity. Oysters have also been used as model organisms to study the evolution of host-defense system. To gain comprehensive knowledge about various physiological processes in hybrid oysters under low salinity stress, we performed transcriptomic analysis of gill tissue of Crassostrea sikamea ♀ × Crassostrea angulata♂ hybrid using the deep-sequencing platform Illumina HiSeq. We exploited the high-throughput technique to delineate differentially expressed genes (DEGs) in oysters maintained in hypotonic conditions. A total of 199,391 high quality unigenes, with average length of 644 bp, were generated. Of these 35 and 31 genes showed up- and down-regulation, respectively. Functional categorization and pathway analysis of these DEGs revealed enrichment for immune mechanism, apoptosis, energy metabolism and osmoregulation under low salinity stress. The expression patterns of 41 DEGs in hybrids and their parental species were further analyzed by quantitative real-time PCR (qRT-PCR). This study will serve as a platform for subsequent gene expression analysis regarding environmental stress. Our findings will also provide valuable information about gene expression to better understand the immune mechanism, apoptosis, energy metabolism and osmoregulation in hybrid oysters under low salinity stress.

Transcriptomic analysis of Crassostrea sikamea × Crassostrea angulata hybrids in response to low salinity stress

PubMed Central

Yan, Lulu; Su, Jiaqi; Wang, Zhaoping; Yan, Xiwu; Yu, Ruihai; Ma, Peizhen; Li, Yangchun; Du, Junpeng

2017-01-01

Hybrid oysters often show heterosis in growth rate, weight, survival and adaptability to extremes of salinity. Oysters have also been used as model organisms to study the evolution of host-defense system. To gain comprehensive knowledge about various physiological processes in hybrid oysters under low salinity stress, we performed transcriptomic analysis of gill tissue of Crassostrea sikamea ♀ × Crassostrea angulata♂ hybrid using the deep-sequencing platform Illumina HiSeq. We exploited the high-throughput technique to delineate differentially expressed genes (DEGs) in oysters maintained in hypotonic conditions. A total of 199,391 high quality unigenes, with average length of 644 bp, were generated. Of these 35 and 31 genes showed up- and down-regulation, respectively. Functional categorization and pathway analysis of these DEGs revealed enrichment for immune mechanism, apoptosis, energy metabolism and osmoregulation under low salinity stress. The expression patterns of 41 DEGs in hybrids and their parental species were further analyzed by quantitative real-time PCR (qRT-PCR). This study will serve as a platform for subsequent gene expression analysis regarding environmental stress. Our findings will also provide valuable information about gene expression to better understand the immune mechanism, apoptosis, energy metabolism and osmoregulation in hybrid oysters under low salinity stress. PMID:28182701

Optimized Sleeping Beauty transposons rapidly generate stable transgenic cell lines.

PubMed

Kowarz, Eric; Löscher, Denise; Marschalek, Rolf

2015-04-01

Stable gene expression in mammalian cells is a prerequisite for many in vitro and in vivo experiments. However, either the integration of plasmids into mammalian genomes or the use of retro-/lentiviral systems have intrinsic limitations. The use of transposable elements, e.g. the Sleeping Beauty system (SB), circumvents most of these drawbacks (integration sites, size limitations) and allows the quick generation of stable cell lines. The integration process of SB is catalyzed by a transposase and the handling of this gene transfer system is easy, fast and safe. Here, we report our improvements made to the existing SB vector system and present two new vector types for robust constitutive or inducible expression of any gene of interest. Both types are available in 16 variants with different selection marker (puromycin, hygromycin, blasticidin, neomycin) and fluorescent protein expression (GFP, RFP, BFP) to fit most experimental requirements. With this system it is possible to generate cell lines from stable transfected cells quickly and reliably in a medium-throughput setting (three to five days). Cell lines robustly express any gene-of-interest, either constitutively or tightly regulated by doxycycline. This allows many laboratory experiments to speed up generation of data in a rapid and robust manner. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

NF-κB dynamics show digital activation and analog information processing in cells

NASA Astrophysics Data System (ADS)

Tay, Savas; Hughey, Jake; Lee, Timothy; Lipniacki, Tomasz; Covert, Markus; Quake, Stephen

2010-03-01

Cells operate in ever changing environments using extraordinary communication capabilities. Cell-to-cell communication is mediated by signaling molecules that form spatiotemporal concentration gradients, which requires cells to respond to a wide range of signal intensities. We used high-throughput microfluidic cell culture, quantitative gene expression analysis and mathematical modeling to investigate how single mammalian cells respond to different concentrations of the signaling molecule TNF-α via the transcription factor NF-κB. We measured NF-κB activity in thousands of live cells under TNF-α doses covering four orders of magnitude. In contrast to population studies, the activation is a stochastic, switch-like process at the single cell level with fewer cells responding at lower doses. The activated cells respond fully and express early genes independent of the TNF-α concentration, while only high dose stimulation results in the expression of late genes. Cells also encode a set of analog parameters such as the NF-κB peak intensity, response time and number of oscillations to modulate the outcome. We developed a stochastic model that reproduces both the digital and analog dynamics as well as the gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-α induced NF-κB signaling in various types of cells.

Expression profiling of cardiovascular disease

PubMed Central

2004-01-01

Cardiovascular disease is the most important cause of morbidity and mortality in developed countries, causing twice as many deaths as cancer in the USA. The major cardiovascular diseases, including coronary artery disease (CAD), myocardial infarction (MI), congestive heart failure (CHF) and common congenital heart disease (CHD), are caused by multiple genetic and environmental factors, as well as the interactions between them. The underlying molecular pathogenic mechanisms for these disorders are still largely unknown, but gene expression may play a central role in the development and progression of cardiovascular disease. Microarrays are high-throughput genomic tools that allow the comparison of global expression changes in thousands of genes between normal and diseased cells/tissues. Microarrays have recently been applied to CAD/MI, CHF and CHD to profile changes in gene expression patterns in diseased and non-diseased patients. This same technology has also been used to characterise endothelial cells, vascular smooth muscle cells and inflammatory cells, with or without various treatments that mimic disease processes involved in CAD/MI. These studies have led to the identification of unique subsets of genes associated with specific diseases and disease processes. Ongoing microarray studies in the field will provide insights into the molecular mechanism of cardiovascular disease and may generate new diagnostic and therapeutic markers. PMID:15588496

GC-Content Normalization for RNA-Seq Data

PubMed Central

2011-01-01

Background Transcriptome sequencing (RNA-Seq) has become the assay of choice for high-throughput studies of gene expression. However, as is the case with microarrays, major technology-related artifacts and biases affect the resulting expression measures. Normalization is therefore essential to ensure accurate inference of expression levels and subsequent analyses thereof. Results We focus on biases related to GC-content and demonstrate the existence of strong sample-specific GC-content effects on RNA-Seq read counts, which can substantially bias differential expression analysis. We propose three simple within-lane gene-level GC-content normalization approaches and assess their performance on two different RNA-Seq datasets, involving different species and experimental designs. Our methods are compared to state-of-the-art normalization procedures in terms of bias and mean squared error for expression fold-change estimation and in terms of Type I error and p-value distributions for tests of differential expression. The exploratory data analysis and normalization methods proposed in this article are implemented in the open-source Bioconductor R package EDASeq. Conclusions Our within-lane normalization procedures, followed by between-lane normalization, reduce GC-content bias and lead to more accurate estimates of expression fold-changes and tests of differential expression. Such results are crucial for the biological interpretation of RNA-Seq experiments, where downstream analyses can be sensitive to the supplied lists of genes. PMID:22177264

Characterization of transcriptome in the Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) and gene expression analysis during developmental stages.

PubMed

Tang, Pei-An; Wu, Hai-Jing; Xue, Hao; Ju, Xing-Rong; Song, Wei; Zhang, Qi-Lin; Yuan, Ming-Long

2017-07-30

The Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) is a worldwide pest that causes serious damage to stored foods. Although many efforts have been conducted on this species due to its economic importance, the study of genetic basis of development, behavior and insecticide resistance has been greatly hampered due to lack of genomic information. In this study, we used high throughput sequencing platform to perform a de novo transcriptome assembly and tag-based digital gene expression profiling (DGE) analyses across four different developmental stages of P. interpunctella (egg, third-instar larvae, pupae and adult). We obtained approximate 9gigabyte (GB) of clean data and recovered 84,938 unigenes, including 37,602 clusters and 47,336 singletons. These unigenes were annotated using BLAST against the non-redundant protein databases and then functionally classified based on Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes databases (KEGG). A large number of differentially expressed genes were identified by pairwise comparisons among different developmental stages. Gene expression profiles dramatically changed between developmental stage transitions. Some of these differentially expressed genes were related to digestion and cuticularization. Quantitative real-time PCR results of six randomly selected genes conformed the findings in the DGEs. Furthermore, we identified over 8000 microsatellite markers and 97,648 single nucleotide polymorphisms which will be useful for population genetics studies of P. interpunctella. This transcriptomic information provided insight into the developmental basis of P. interpunctella and will be helpful for establishing integrated management strategies and developing new targets of insecticides for this serious pest. Copyright © 2017 Elsevier B.V. All rights reserved.

RNA-Seq analysis and annotation of a draft blueberry genome assembly identifies candidate genes involved in fruit ripening, biosynthesis of bioactive compounds, and stage-specific alternative splicing.

PubMed

Gupta, Vikas; Estrada, April D; Blakley, Ivory; Reid, Rob; Patel, Ketan; Meyer, Mason D; Andersen, Stig Uggerhøj; Brown, Allan F; Lila, Mary Ann; Loraine, Ann E

2015-01-01

Blueberries are a rich source of antioxidants and other beneficial compounds that can protect against disease. Identifying genes involved in synthesis of bioactive compounds could enable the breeding of berry varieties with enhanced health benefits. Toward this end, we annotated a previously sequenced draft blueberry genome assembly using RNA-Seq data from five stages of berry fruit development and ripening. Genome-guided assembly of RNA-Seq read alignments combined with output from ab initio gene finders produced around 60,000 gene models, of which more than half were similar to proteins from other species, typically the grape Vitis vinifera. Comparison of gene models to the PlantCyc database of metabolic pathway enzymes identified candidate genes involved in synthesis of bioactive compounds, including bixin, an apocarotenoid with potential disease-fighting properties, and defense-related cyanogenic glycosides, which are toxic. Cyanogenic glycoside (CG) biosynthetic enzymes were highly expressed in green fruit, and a candidate CG detoxification enzyme was up-regulated during fruit ripening. Candidate genes for ethylene, anthocyanin, and 400 other biosynthetic pathways were also identified. Homology-based annotation using Blast2GO and InterPro assigned Gene Ontology terms to around 15,000 genes. RNA-Seq expression profiling showed that blueberry growth, maturation, and ripening involve dynamic gene expression changes, including coordinated up- and down-regulation of metabolic pathway enzymes and transcriptional regulators. Analysis of RNA-seq alignments identified developmentally regulated alternative splicing, promoter use, and 3' end formation. We report genome sequence, gene models, functional annotations, and RNA-Seq expression data that provide an important new resource enabling high throughput studies in blueberry.

Digital gene expression approach over multiple RNA-Seq data sets to detect neoblast transcriptional changes in Schmidtea mediterranea.

PubMed

Rodríguez-Esteban, Gustavo; González-Sastre, Alejandro; Rojo-Laguna, José Ignacio; Saló, Emili; Abril, Josep F

2015-05-08

The freshwater planarian Schmidtea mediterranea is recognised as a valuable model for research into adult stem cells and regeneration. With the advent of the high-throughput sequencing technologies, it has become feasible to undertake detailed transcriptional analysis of its unique stem cell population, the neoblasts. Nonetheless, a reliable reference for this type of studies is still lacking. Taking advantage of digital gene expression (DGE) sequencing technology we compare all the available transcriptomes for S. mediterranea and improve their annotation. These results are accessible via web for the community of researchers. Using the quantitative nature of DGE, we describe the transcriptional profile of neoblasts and present 42 new neoblast genes, including several cancer-related genes and transcription factors. Furthermore, we describe in detail the Smed-meis-like gene and the three Nuclear Factor Y subunits Smed-nf-YA, Smed-nf-YB-2 and Smed-nf-YC. DGE is a valuable tool for gene discovery, quantification and annotation. The application of DGE in S. mediterranea confirms the planarian stem cells or neoblasts as a complex population of pluripotent and multipotent cells regulated by a mixture of transcription factors and cancer-related genes.

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.

GO-Bayes: Gene Ontology-based overrepresentation analysis using a Bayesian approach.

PubMed

Zhang, Song; Cao, Jing; Kong, Y Megan; Scheuermann, Richard H

2010-04-01

A typical approach for the interpretation of high-throughput experiments, such as gene expression microarrays, is to produce groups of genes based on certain criteria (e.g. genes that are differentially expressed). To gain more mechanistic insights into the underlying biology, overrepresentation analysis (ORA) is often conducted to investigate whether gene sets associated with particular biological functions, for example, as represented by Gene Ontology (GO) annotations, are statistically overrepresented in the identified gene groups. However, the standard ORA, which is based on the hypergeometric test, analyzes each GO term in isolation and does not take into account the dependence structure of the GO-term hierarchy. We have developed a Bayesian approach (GO-Bayes) to measure overrepresentation of GO terms that incorporates the GO dependence structure by taking into account evidence not only from individual GO terms, but also from their related terms (i.e. parents, children, siblings, etc.). The Bayesian framework borrows information across related GO terms to strengthen the detection of overrepresentation signals. As a result, this method tends to identify sets of closely related GO terms rather than individual isolated GO terms. The advantage of the GO-Bayes approach is demonstrated with a simulation study and an application example.

Evaluation and rational design of guide RNAs for efficient CRISPR/Cas9-mediated mutagenesis in Ciona.

PubMed

Gandhi, Shashank; Haeussler, Maximilian; Razy-Krajka, Florian; Christiaen, Lionel; Stolfi, Alberto

2017-05-01

The CRISPR/Cas9 system has emerged as an important tool for various genome engineering applications. A current obstacle to high throughput applications of CRISPR/Cas9 is the imprecise prediction of highly active single guide RNAs (sgRNAs). We previously implemented the CRISPR/Cas9 system to induce tissue-specific mutations in the tunicate Ciona. In the present study, we designed and tested 83 single guide RNA (sgRNA) vectors targeting 23 genes expressed in the cardiopharyngeal progenitors and surrounding tissues of Ciona embryo. Using high-throughput sequencing of mutagenized alleles, we identified guide sequences that correlate with sgRNA mutagenesis activity and used this information for the rational design of all possible sgRNAs targeting the Ciona transcriptome. We also describe a one-step cloning-free protocol for the assembly of sgRNA expression cassettes. These cassettes can be directly electroporated as unpurified PCR products into Ciona embryos for sgRNA expression in vivo, resulting in high frequency of CRISPR/Cas9-mediated mutagenesis in somatic cells of electroporated embryos. We found a strong correlation between the frequency of an Ebf loss-of-function phenotype and the mutagenesis efficacies of individual Ebf-targeting sgRNAs tested using this method. We anticipate that our approach can be scaled up to systematically design and deliver highly efficient sgRNAs for the tissue-specific investigation of gene functions in Ciona. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparative Transcriptome Analysis Reveals Different Molecular Mechanisms of Bacillus coagulans 2-6 Response to Sodium Lactate and Calcium Lactate during Lactic Acid Production

PubMed Central

Qin, Jiayang; Wang, Xiuwen; Wang, Landong; Zhu, Beibei; Zhang, Xiaohua; Yao, Qingshou; Xu, Ping

2015-01-01

Lactate production is enhanced by adding calcium carbonate or sodium hydroxide during fermentation. However, Bacillus coagulans 2-6 can produce more than 180 g/L L-lactic acid when calcium lactate is accumulated, but less than 120 g/L L-lactic acid when sodium lactate is formed. The molecular mechanisms by which B. coagulans responds to calcium lactate and sodium lactate remain unclear. In this study, comparative transcriptomic methods based on high-throughput RNA sequencing were applied to study gene expression changes in B. coagulans 2-6 cultured in non-stress, sodium lactate stress and calcium lactate stress conditions. Gene expression profiling identified 712 and 1213 significantly regulated genes in response to calcium lactate stress and sodium lactate stress, respectively. Gene ontology assignments of the differentially expressed genes were performed. KEGG pathway enrichment analysis revealed that ‘ATP-binding cassette transporters’ were significantly affected by calcium lactate stress, and ‘amino sugar and nucleotide sugar metabolism’ was significantly affected by sodium lactate stress. It was also found that lactate fermentation was less affected by calcium lactate stress than by sodium lactate stress. Sodium lactate stress had negative effect on the expression of ‘glycolysis/gluconeogenesis’ genes but positive effect on the expression of ‘citrate cycle (TCA cycle)’ genes. However, calcium lactate stress had positive influence on the expression of ‘glycolysis/gluconeogenesis’ genes and had minor influence on ‘citrate cycle (TCA cycle)’ genes. Thus, our findings offer new insights into the responses of B. coagulans to different lactate stresses. Notably, our RNA-seq dataset constitute a robust database for investigating the functions of genes induced by lactate stress in the future and identify potential targets for genetic engineering to further improve L-lactic acid production by B. coagulans. PMID:25875592

Live-cell monitoring of periodic gene expression in synchronous human cells identifies Forkhead genes involved in cell cycle control

PubMed Central

Grant, Gavin D.; Gamsby, Joshua; Martyanov, Viktor; Brooks, Lionel; George, Lacy K.; Mahoney, J. Matthew; Loros, Jennifer J.; Dunlap, Jay C.; Whitfield, Michael L.

2012-01-01

We developed a system to monitor periodic luciferase activity from cell cycle–regulated promoters in synchronous cells. Reporters were driven by a minimal human E2F1 promoter with peak expression in G1/S or a basal promoter with six Forkhead DNA-binding sites with peak expression at G2/M. After cell cycle synchronization, luciferase activity was measured in live cells at 10-min intervals across three to four synchronous cell cycles, allowing unprecedented resolution of cell cycle–regulated gene expression. We used this assay to screen Forkhead transcription factors for control of periodic gene expression. We confirmed a role for FOXM1 and identified two novel cell cycle regulators, FOXJ3 and FOXK1. Knockdown of FOXJ3 and FOXK1 eliminated cell cycle–dependent oscillations and resulted in decreased cell proliferation rates. Analysis of genes regulated by FOXJ3 and FOXK1 showed that FOXJ3 may regulate a network of zinc finger proteins and that FOXK1 binds to the promoter and regulates DHFR, TYMS, GSDMD, and the E2F binding partner TFDP1. Chromatin immunoprecipitation followed by high-throughput sequencing analysis identified 4329 genomic loci bound by FOXK1, 83% of which contained a FOXK1-binding motif. We verified that a subset of these loci are activated by wild-type FOXK1 but not by a FOXK1 (H355A) DNA-binding mutant. PMID:22740631

Comparison of normalization methods for differential gene expression analysis in RNA-Seq experiments

PubMed Central

Maza, Elie; Frasse, Pierre; Senin, Pavel; Bouzayen, Mondher; Zouine, Mohamed

2013-01-01

In recent years, RNA-Seq technologies became a powerful tool for transcriptome studies. However, computational methods dedicated to the analysis of high-throughput sequencing data are yet to be standardized. In particular, it is known that the choice of a normalization procedure leads to a great variability in results of differential gene expression analysis. The present study compares the most widespread normalization procedures and proposes a novel one aiming at removing an inherent bias of studied transcriptomes related to their relative size. Comparisons of the normalization procedures are performed on real and simulated data sets. Real RNA-Seq data sets analyses, performed with all the different normalization methods, show that only 50% of significantly differentially expressed genes are common. This result highlights the influence of the normalization step on the differential expression analysis. Real and simulated data sets analyses give similar results showing 3 different groups of procedures having the same behavior. The group including the novel method named “Median Ratio Normalization” (MRN) gives the lower number of false discoveries. Within this group the MRN method is less sensitive to the modification of parameters related to the relative size of transcriptomes such as the number of down- and upregulated genes and the gene expression levels. The newly proposed MRN method efficiently deals with intrinsic bias resulting from relative size of studied transcriptomes. Validation with real and simulated data sets confirmed that MRN is more consistent and robust than existing methods. PMID:26442135

Transcriptomic variation of eyestalk reveals the genes and biological processes associated with molting in Portunus trituberculatus

PubMed Central

Zhang, Longtao; Liu, Ping; Li, Jian

2017-01-01

Background Molting is an essential biological process throughout the life history of crustaceans, which is regulated by many neuropeptide hormones expressed in the eyestalk. To better understand the molting mechanism in Portunus trituberculatus, we used digital gene expression (DGE) to analyze single eyestalk samples during the molting cycle by high-throughput sequencing. Results We obtained 14,387,942, 12,631,508 and 13,060,062 clean sequence reads from inter-molt (InM), pre-molt (PrM) and post-molt (PoM) cDNA libraries, respectively. A total of 1,394 molt-related differentially expressed genes (DEGs) were identified. GO and KEGG enrichment analysis identified some important processes and pathways with key roles in molting regulation, such as chitin metabolism, peptidase inhibitor activity, and the ribosome. We first observed a pattern associated with the neuromodulator-related pathways during the molting cycle, which were up-regulated in PrM and down-regulated in PoM. Four categories of important molting-related transcripts were clustered and most of them had similar expression patterns, which suggests that there is a connection between these genes throughout the molt cycle. Conclusion Our work is the first molt-related investigation of P. trituberculatus focusing on the eyestalk at the whole transcriptome level. Together, our results, including DEGs, identification of molting-related biological processes and pathways, and observed expression patterns of important genes, provide a novel insight into the function of the eyestalk in molting regulation. PMID:28394948

Guanylate-binding protein-1 is a potential new therapeutic target for triple-negative breast cancer.

PubMed

Quintero, Melissa; Adamoski, Douglas; Reis, Larissa Menezes Dos; Ascenção, Carolline Fernanda Rodrigues; Oliveira, Krishina Ratna Sousa de; Gonçalves, Kaliandra de Almeida; Dias, Marília Meira; Carazzolle, Marcelo Falsarella; Dias, Sandra Martha Gomes

2017-11-07

Triple-negative breast cancer (TNBC) is characterized by a lack of estrogen and progesterone receptor expression (ESR and PGR, respectively) and an absence of human epithelial growth factor receptor (ERBB2) amplification. Approximately 15-20% of breast malignancies are TNBC. Patients with TNBC often have an unfavorable prognosis. In addition, TNBC represents an important clinical challenge since it does not respond to hormone therapy. In this work, we integrated high-throughput mRNA sequencing (RNA-Seq) data from normal and tumor tissues (obtained from The Cancer Genome Atlas, TCGA) and cell lines obtained through in-house sequencing or available from the Gene Expression Omnibus (GEO) to generate a unified list of differentially expressed (DE) genes. Methylome and proteomic data were integrated to our analysis to give further support to our findings. Genes that were overexpressed in TNBC were then curated to retain new potentially druggable targets based on in silico analysis. Knocking-down was used to assess gene importance for TNBC cell proliferation. Our pipeline analysis generated a list of 243 potential new targets for treating TNBC. We finally demonstrated that knock-down of Guanylate-Binding Protein 1 (GBP1 ), one of the candidate genes, selectively affected the growth of TNBC cell lines. Moreover, we showed that GBP1 expression was controlled by epidermal growth factor receptor (EGFR) in breast cancer cell lines. We propose that GBP1 is a new potential druggable therapeutic target for treating TNBC with enhanced EGFR expression.

Comprehensive gene and microRNA expression profiling on cardiovascular system in zebrafish co-exposured of SiNPs and MeHg.

PubMed

Hu, Hejing; Shi, Yanfeng; Zhang, Yannan; Wu, Jing; Asweto, Collins Otieno; Feng, Lin; Yang, Xiaozhe; Duan, Junchao; Sun, Zhiwei

2017-12-31

Air pollution has been shown to increase cardiovascular diseases. However, little attention has been paid to the combined effects of PM and air pollutants on the cardiovascular system. To explore this, a high-throughput sequencing technology was used to determine combined effects of silica nanoparticles (SiNPs) and MeHg in zebrafish. Our study demonstrated that SiNPs and MeHg co-exposure could cause significant changes in mRNA and miRNA expression patterns in zebrafish. The differentially expressed (DE) genes in profiles 17 and 26 of STC analysis suggest that SiNPs and MeHg co-exposure had more proinflammatory and cardiovascular toxicity in zebrafish than single exposure. Major gene functions associated with cardiovascular system in the co-exposed zebrafish were discerned from the dynamic-gene-network, including stxbp1a, celf4, ahr1b and bai2. In addition, the prominently expressed pathway of cardiac muscle contraction was targeted by 3 DE miRNAs identified by the miRNA-pathway-network (dre-miR-7147, dre-miR-26a and dre-miR-375), which included 23 DE genes. This study presents a global view of the combined SiNPs and MeHg toxicity on the dynamic expression of both mRNAs and miRNAs in zebrafish, and could serve as fundamental research clues for future studies, especially on cardiovascular system toxicity. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating gene and protein expression data with genome-scale metabolic networks to infer functional pathways.

PubMed

Pey, Jon; Valgepea, Kaspar; Rubio, Angel; Beasley, John E; Planes, Francisco J

2013-12-08

The study of cellular metabolism in the context of high-throughput -omics data has allowed us to decipher novel mechanisms of importance in biotechnology and health. To continue with this progress, it is essential to efficiently integrate experimental data into metabolic modeling. We present here an in-silico framework to infer relevant metabolic pathways for a particular phenotype under study based on its gene/protein expression data. This framework is based on the Carbon Flux Path (CFP) approach, a mixed-integer linear program that expands classical path finding techniques by considering additional biophysical constraints. In particular, the objective function of the CFP approach is amended to account for gene/protein expression data and influence obtained paths. This approach is termed integrative Carbon Flux Path (iCFP). We show that gene/protein expression data also influences the stoichiometric balancing of CFPs, which provides a more accurate picture of active metabolic pathways. This is illustrated in both a theoretical and real scenario. Finally, we apply this approach to find novel pathways relevant in the regulation of acetate overflow metabolism in Escherichia coli. As a result, several targets which could be relevant for better understanding of the phenomenon leading to impaired acetate overflow are proposed. A novel mathematical framework that determines functional pathways based on gene/protein expression data is presented and validated. We show that our approach is able to provide new insights into complex biological scenarios such as acetate overflow in Escherichia coli.

Digoxin reveals a functional connection between HIV-1 integration preference and T-cell activation.

PubMed

Zhyvoloup, Alexander; Melamed, Anat; Anderson, Ian; Planas, Delphine; Lee, Chen-Hsuin; Kriston-Vizi, Janos; Ketteler, Robin; Merritt, Andy; Routy, Jean-Pierre; Ancuta, Petronela; Bangham, Charles R M; Fassati, Ariberto

2017-07-01

HIV-1 integrates more frequently into transcribed genes, however the biological significance of HIV-1 integration targeting has remained elusive. Using a selective high-throughput chemical screen, we discovered that the cardiac glycoside digoxin inhibits wild-type HIV-1 infection more potently than HIV-1 bearing a single point mutation (N74D) in the capsid protein. We confirmed that digoxin repressed viral gene expression by targeting the cellular Na+/K+ ATPase, but this did not explain its selectivity. Parallel RNAseq and integration mapping in infected cells demonstrated that digoxin inhibited expression of genes involved in T-cell activation and cell metabolism. Analysis of >400,000 unique integration sites showed that WT virus integrated more frequently than N74D mutant within or near genes susceptible to repression by digoxin and involved in T-cell activation and cell metabolism. Two main gene networks down-regulated by the drug were CD40L and CD38. Blocking CD40L by neutralizing antibodies selectively inhibited WT virus infection, phenocopying digoxin. Thus the selectivity of digoxin depends on a combination of integration targeting and repression of specific gene networks. The drug unmasked a functional connection between HIV-1 integration and T-cell activation. Our results suggest that HIV-1 evolved integration site selection to couple its early gene expression with the status of target CD4+ T-cells, which may affect latency and viral reactivation.

On the Molecular Basis of Division of Labor in Solenopsis invicta (Hymenoptera: Formicidae) Workers: RNA-seq Analysis.

PubMed

Qiu, Hua-Long; Zhao, Cheng-Yin; He, Yu-Rong

2017-01-01

The fire ant Solenopsis invicta Buren is an important invasive pest. Among S. invicta workers behavioral changes depend on age where younger ants are nurses and older ants foragers. To identify potential genes associated with this division of labor, we compared gene expression between foragers and nurses by high-throughput sequencing. In total, we identified 1,618 genes significantly differently expressed between nurses and foragers, of which 542 were upregulated in foragers and 1,076 were upregulated in nurses. Several pathways related to metabolism were significantly enriched, such as lipid storage and fatty acid biosynthesis, which might contribute to the division of labor in S. invicta. Several genes involved in DNA methylation, transcription, and olfactory responses as well as resistance to stress were differentially expressed between nurses and foragers workers. Finally, a comparison between previously published microarray data and our RNA-seq data in S. invicta shows 116 genes overlap, and the GO term myofibril assembly (GO: 0030239) were simultaneously significantly enriched. These results advance knowledge of potentially important genes and molecular pathways associated with worker division of labor in S. invicta. We hope our dataset will provide . candidate target genes to disrupt organization in S. invicta as a control strategy against this invasive pest. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America.

BioVLAB-mCpG-SNP-EXPRESS: A system for multi-level and multi-perspective analysis and exploration of DNA methylation, sequence variation (SNPs), and gene expression from multi-omics data.

PubMed

Chae, Heejoon; Lee, Sangseon; Seo, Seokjun; Jung, Daekyoung; Chang, Hyeonsook; Nephew, Kenneth P; Kim, Sun

2016-12-01

Measuring gene expression, DNA sequence variation, and DNA methylation status is routinely done using high throughput sequencing technologies. To analyze such multi-omics data and explore relationships, reliable bioinformatics systems are much needed. Existing systems are either for exploring curated data or for processing omics data in the form of a library such as R. Thus scientists have much difficulty in investigating relationships among gene expression, DNA sequence variation, and DNA methylation using multi-omics data. In this study, we report a system called BioVLAB-mCpG-SNP-EXPRESS for the integrated analysis of DNA methylation, sequence variation (SNPs), and gene expression for distinguishing cellular phenotypes at the pairwise and multiple phenotype levels. The system can be deployed on either the Amazon cloud or a publicly available high-performance computing node, and the data analysis and exploration of the analysis result can be conveniently done using a web-based interface. In order to alleviate analysis complexity, all the process are fully automated, and graphical workflow system is integrated to represent real-time analysis progression. The BioVLAB-mCpG-SNP-EXPRESS system works in three stages. First, it processes and analyzes multi-omics data as input in the form of the raw data, i.e., FastQ files. Second, various integrated analyses such as methylation vs. gene expression and mutation vs. methylation are performed. Finally, the analysis result can be explored in a number of ways through a web interface for the multi-level, multi-perspective exploration. Multi-level interpretation can be done by either gene, gene set, pathway or network level and multi-perspective exploration can be explored from either gene expression, DNA methylation, sequence variation, or their relationship perspective. The utility of the system is demonstrated by performing analysis of phenotypically distinct 30 breast cancer cell line data set. BioVLAB-mCpG-SNP-EXPRESS is available at http://biohealth.snu.ac.kr/software/biovlab_mcpg_snp_express/. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Identification of microRNAs and their targets in Finger millet by high throughput sequencing.

PubMed

Usha, S; Jyothi, M N; Sharadamma, N; Dixit, Rekha; Devaraj, V R; Nagesh Babu, R

2015-12-15

MicroRNAs are short non-coding RNAs which play an important role in regulating gene expression by mRNA cleavage or by translational repression. The majority of identified miRNAs were evolutionarily conserved; however, others expressed in a species-specific manner. Finger millet is an important cereal crop; nonetheless, no practical information is available on microRNAs to date. In this study, we have identified 95 conserved microRNAs belonging to 39 families and 3 novel microRNAs by high throughput sequencing. For the identified conserved and novel miRNAs a total of 507 targets were predicted. 11 miRNAs were validated and tissue specificity was determined by stem loop RT-qPCR, Northern blot. GO analyses revealed targets of miRNA were involved in wide range of regulatory functions. This study implies large number of known and novel miRNAs found in Finger millet which may play important role in growth and development. Copyright © 2015 Elsevier B.V. All rights reserved.