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

Science.gov (United States)

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

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

National Research Council Canada - National Science Library

Grace, M. B; Salter, C. A; Bullard, J. R; Prasanna, P. G; Manglapus, G. L; Blakely, W. F

2005-01-01

.... 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...

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

Science.gov (United States)

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.

Determination of gene expression patterns using high-throughput RNA in situ hybridizaion to whole-mount Drosophila embryos

Energy Technology Data Exchange (ETDEWEB)

Weiszmann, R.; Hammonds, A.S.; Celniker, S.E.

2009-04-09

We describe a high-throughput protocol for RNA in situ hybridization (ISH) to Drosophila embryos in a 96-well format. cDNA or genomic DNA templates are amplified by PCR and then digoxigenin-labeled ribonucleotides are incorporated into antisense RNA probes by in vitro transcription. The quality of each probe is evaluated before ISH using a RNA probe quantification (dot blot) assay. RNA probes are hybridized to fixed, mixed-staged Drosophila embryos in 96-well plates. The resulting stained embryos can be examined and photographed immediately or stored at 4oC for later analysis. Starting with fixed, staged embryos, the protocol takes 6 d from probe template production through hybridization. Preparation of fixed embryos requires a minimum of 2 weeks to collect embryos representing all stages. The method has been used to determine the expression patterns of over 6,000 genes throughout embryogenesis.

Emory University: High-Throughput Protein-Protein Interaction Dataset for Lung Cancer-Associated Genes | Office of Cancer Genomics

Science.gov (United States)

To discover novel PPI signaling hubs for lung cancer, CTD2 Center at Emory utilized large-scale genomics datasets and literature to compile a set of lung cancer-associated genes. A library of expression vectors were generated for these genes and utilized for detecting pairwise PPIs with cell lysate-based TR-FRET assays in high-throughput screening format. Read the abstract.

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

Alexey A. Dmitriev

2016-11-01

Full Text Available Abstract Background 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. Results 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. Conclusions 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

MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer.

LENUS (Irish Health Repository)

Chang, Kah Hoong

2010-01-01

BACKGROUND: Advances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to quantify gene expression. Appropriate normalisation of RT-qPCR data using stably expressed reference genes is critical to ensure accurate and reliable results. Mi(cro)RNA expression profiles have been shown to be more accurate in disease classification than mRNA expression profiles. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in miRNA RT-qPCR studies. METHODS: We adopt and report a systematic approach to identify the most stable reference genes for miRNA expression studies by RT-qPCR in colorectal cancer (CRC). High-throughput miRNA profiling was performed on ten pairs of CRC and normal tissues. By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation. As such the stability of a panel of miRNAs was examined on 35 tumour and 39 normal tissues. The effects of normalisers on the relative quantity of established oncogenic (miR-21 and miR-31) and tumour suppressor (miR-143 and miR-145) target miRNAs were assessed. RESULTS: In the array experiment, miR-26a, miR-345, miR-425 and miR-454 were identified as having expression profiles closest to the global mean. From a panel of six miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) and two small nucleolar RNA genes (RNU48 and Z30), miR-16 and miR-345 were identified as the most stably expressed reference genes. The combined use of miR-16 and miR-345 to normalise expression data enabled detection of a significant dysregulation of all four target miRNAs between tumour and normal colorectal tissue. CONCLUSIONS: Our study demonstrates that the top six most

MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer

LENUS (Irish Health Repository)

Chang, Kah Hoong

2010-04-29

Abstract Background Advances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to quantify gene expression. Appropriate normalisation of RT-qPCR data using stably expressed reference genes is critical to ensure accurate and reliable results. Mi(cro)RNA expression profiles have been shown to be more accurate in disease classification than mRNA expression profiles. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in miRNA RT-qPCR studies. Methods We adopt and report a systematic approach to identify the most stable reference genes for miRNA expression studies by RT-qPCR in colorectal cancer (CRC). High-throughput miRNA profiling was performed on ten pairs of CRC and normal tissues. By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation. As such the stability of a panel of miRNAs was examined on 35 tumour and 39 normal tissues. The effects of normalisers on the relative quantity of established oncogenic (miR-21 and miR-31) and tumour suppressor (miR-143 and miR-145) target miRNAs were assessed. Results In the array experiment, miR-26a, miR-345, miR-425 and miR-454 were identified as having expression profiles closest to the global mean. From a panel of six miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) and two small nucleolar RNA genes (RNU48 and Z30), miR-16 and miR-345 were identified as the most stably expressed reference genes. The combined use of miR-16 and miR-345 to normalise expression data enabled detection of a significant dysregulation of all four target miRNAs between tumour and normal colorectal tissue. Conclusions Our study demonstrates that the top six most

Population and sex differences in Drosophila melanogaster brain gene expression

Directory of Open Access Journals (Sweden)

Catalán Ana

2012-11-01

Full Text Available Abstract Background Changes in gene regulation are thought to be crucial for the adaptation of organisms to their environment. Transcriptome analyses can be used to identify candidate genes for ecological adaptation, but can be complicated by variation in gene expression between tissues, sexes, or individuals. Here we use high-throughput RNA sequencing of a single Drosophila melanogaster tissue to detect brain-specific differences in gene expression between the sexes and between two populations, one from the ancestral species range in sub-Saharan Africa and one from the recently colonized species range in Europe. Results Relatively few genes (Cyp6g1 and CHKov1. Conclusions Analysis of the brain transcriptome revealed many genes differing in expression between populations that were not detected in previous studies using whole flies. There was little evidence for sex-specific regulatory adaptation in the brain, as most expression differences between populations were observed in both males and females. The enrichment of genes with sexually dimorphic expression on the X chromosome is consistent with dosage compensation mechanisms affecting sex-biased expression in somatic tissues.

A community resource for high-throughput quantitative RT-PCR analysis of transcription factor gene expression in Medicago truncatula

Directory of Open Access Journals (Sweden)

Redman Julia C

2008-07-01

Full Text Available Abstract Background Medicago truncatula is a model legume species that is currently the focus of an international genome sequencing effort. Although several different oligonucleotide and cDNA arrays have been produced for genome-wide transcript analysis of this species, intrinsic limitations in the sensitivity of hybridization-based technologies mean that transcripts of genes expressed at low-levels cannot be measured accurately with these tools. Amongst such genes are many encoding transcription factors (TFs, which are arguably the most important class of regulatory proteins. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR is the most sensitive method currently available for transcript quantification, and one that can be scaled up to analyze transcripts of thousands of genes in parallel. Thus, qRT-PCR is an ideal method to tackle the problem of TF transcript quantification in Medicago and other plants. Results We established a bioinformatics pipeline to identify putative TF genes in Medicago truncatula and to design gene-specific oligonucleotide primers for qRT-PCR analysis of TF transcripts. We validated the efficacy and gene-specificity of over 1000 TF primer pairs and utilized these to identify sets of organ-enhanced TF genes that may play important roles in organ development or differentiation in this species. This community resource will be developed further as more genome sequence becomes available, with the ultimate goal of producing validated, gene-specific primers for all Medicago TF genes. Conclusion High-throughput qRT-PCR using a 384-well plate format enables rapid, flexible, and sensitive quantification of all predicted Medicago transcription factor mRNAs. This resource has been utilized recently by several groups in Europe, Australia, and the USA, and we expect that it will become the 'gold-standard' for TF transcript profiling in Medicago truncatula.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

Mateusz G Adamski

Full Text Available 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.

Regional differences in gene expression and promoter usage in aged human brains

KAUST Repository

Pardo, Luba M.

2013-02-19

To characterize the promoterome of caudate and putamen regions (striatum), frontal and temporal cortices, and hippocampi from aged human brains, we used high-throughput cap analysis of gene expression to profile the transcription start sites and to quantify the differences in gene expression across the 5 brain regions. We also analyzed the extent to which methylation influenced the observed expression profiles. We sequenced more than 71 million cap analysis of gene expression tags corresponding to 70,202 promoter regions and 16,888 genes. More than 7000 transcripts were differentially expressed, mainly because of differential alternative promoter usage. Unexpectedly, 7% of differentially expressed genes were neurodevelopmental transcription factors. Functional pathway analysis on the differentially expressed genes revealed an overrepresentation of several signaling pathways (e.g., fibroblast growth factor and wnt signaling) in hippocampus and striatum. We also found that although 73% of methylation signals mapped within genes, the influence of methylation on the expression profile was small. Our study underscores alternative promoter usage as an important mechanism for determining the regional differences in gene expression at old age.

Building gene co-expression networks using transcriptomics data for systems biology investigations

DEFF Research Database (Denmark)

Kadarmideen, Haja; Watson-Haigh, Nathan S.

2012-01-01

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four......) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT...... (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended....

High-throughput identification of ionizing radiation-sensitive plant genes and development of radiation indicator plant and radiation sensing Genechip

International Nuclear Information System (INIS)

Kim, Dong Sub; Kim, Jinbaek; Ha, Bokeun; Kim, Sang Hoon; Kim, Sunhee

2013-05-01

Physiological analysis of monocot model plant (rice) in response to ionizing radiation (cosmic-ray, gamma-ray, Ion beam). - Identification of antioxidant characters through cytochemical analysis. - Comparison of antioxidant activities in response to ionizing irradiation. - Evaluation of anthocyanin quantity in response to ionizing irradiation. Ionization energy response gene family analysis via bioinformatic validation. - Expression analysis of monocot and dicot gene families. - In silico and bioinformatic approach to elucidate gene function. Characterization and functional analysis of genes specifically expressed in response to ionizing irradiation (cosmic-ray, gamma-ray, Ion beam). - High throughput trancriptomic analysis of plants under ionizing radiation using microarray. - Promotor and cis-element analysis of genes specifically expressed in response to ionizing radiation. - Validation and function analysis of candidate genes. - Elucidation of plant mechanism of sensing and response to ionization energy. Development of bioindicator plants detecting ionization energy. - Cloning and identification of 'Radio marker genes (RMG)'. - Development of Over-expression (O/E) or Knock-out (K/O) plant using RMG. Development of Genechip as an ionization energy detector. - Expression profiling analysis of genes specifically expression in response to ionization energy. - Prepare high-conserved gene specific oligomer. - Development of ionization energy monitoring Genechip and application

High-throughput identification of ionizing radiation-sensitive plant genes and development of radiation indicator plant and radiation sensing Genechip

Energy Technology Data Exchange (ETDEWEB)

Kim, Dong Sub; Kim, Jinbaek; Ha, Bokeun; Kim, Sang Hoon; Kim, Sunhee

2013-05-15

Physiological analysis of monocot model plant (rice) in response to ionizing radiation (cosmic-ray, gamma-ray, Ion beam). - Identification of antioxidant characters through cytochemical analysis. - Comparison of antioxidant activities in response to ionizing irradiation. - Evaluation of anthocyanin quantity in response to ionizing irradiation. Ionization energy response gene family analysis via bioinformatic validation. - Expression analysis of monocot and dicot gene families. - In silico and bioinformatic approach to elucidate gene function. Characterization and functional analysis of genes specifically expressed in response to ionizing irradiation (cosmic-ray, gamma-ray, Ion beam). - High throughput trancriptomic analysis of plants under ionizing radiation using microarray. - Promotor and cis-element analysis of genes specifically expressed in response to ionizing radiation. - Validation and function analysis of candidate genes. - Elucidation of plant mechanism of sensing and response to ionization energy. Development of bioindicator plants detecting ionization energy. - Cloning and identification of 'Radio marker genes (RMG)'. - Development of Over-expression (O/E) or Knock-out (K/O) plant using RMG. Development of Genechip as an ionization energy detector. - Expression profiling analysis of genes specifically expression in response to ionization energy. - Prepare high-conserved gene specific oligomer. - Development of ionization energy monitoring Genechip and application.

Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

Science.gov (United States)

The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

Regional differences in gene expression and promoter usage in aged human brains

KAUST Repository

Pardo, Luba M.; Rizzu, Patrizia; Francescatto, Margherita; Vitezic, Morana; Leday, Gwenaë l G.R.; Sanchez, Javier Simon; Khamis, Abdullah M.; Takahashi, Hazuki; van de Berg, Wilma D.J.; Medvedeva, Yulia A.; van de Wiel, Mark A.; Daub, Carsten O.; Carninci, Piero; Heutink, Peter

2013-01-01

To characterize the promoterome of caudate and putamen regions (striatum), frontal and temporal cortices, and hippocampi from aged human brains, we used high-throughput cap analysis of gene expression to profile the transcription start sites

DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis

Directory of Open Access Journals (Sweden)

Baseler Michael W

2007-11-01

Full Text Available Abstract Background Due to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes one of the bottlenecks, particularly for the analytic task associated with a large gene list. Thus, a highly centralized and ready-to-use gene-annotation knowledgebase is in demand for high throughput gene functional analysis. Description The DAVID Knowledgebase is built around the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of gene/protein identifiers from a variety of public genomic resources into DAVID gene clusters. The grouping of such identifiers improves the cross-reference capability, particularly across NCBI and UniProt systems, enabling more than 40 publicly available functional annotation sources to be comprehensively integrated and centralized by the DAVID gene clusters. The simple, pair-wise, text format files which make up the DAVID Knowledgebase are freely downloadable for various data analysis uses. In addition, a well organized web interface allows users to query different types of heterogeneous annotations in a high-throughput manner. Conclusion The DAVID Knowledgebase is designed to facilitate high throughput gene functional analysis. For a given gene list, it not only provides the quick accessibility to a wide range of heterogeneous annotation data in a centralized location, but also enriches the level of biological information for an individual gene. Moreover, the entire DAVID Knowledgebase is freely downloadable or searchable at http://david.abcc.ncifcrf.gov/knowledgebase/.

VESPUCCI: exploring patterns of gene expression in grapevine

Directory of Open Access Journals (Sweden)

Marco eMoretto

2016-05-01

Full Text Available Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult.In this paper we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI, a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.

Identification of sparsely distributed clusters of cis-regulatory elements in sets of co-expressed genes

OpenAIRE

Kreiman, Gabriel

2004-01-01

Sequence information and high‐throughput methods to measure gene expression levels open the door to explore transcriptional regulation using computational tools. Combinatorial regulation and sparseness of regulatory elements throughout the genome allow organisms to control the spatial and temporal patterns of gene expression. Here we study the organization of cis‐regulatory elements in sets of co‐regulated genes. We build an algorithm to search for combinations of transcription factor binding...

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

Science.gov (United States)

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.

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

Fujii, Chisato; Kuwahara, Hiroyuki; Yu, Ge; Guo, Lili; Gao, Xin

2016-01-01

An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

Learning gene regulatory networks from gene expression data using weighted consensus

KAUST Repository

Fujii, Chisato

2016-08-25

An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

A family of E. coli expression vectors for laboratory scale and high throughput soluble protein production

Directory of Open Access Journals (Sweden)

Bottomley Stephen P

2006-03-01

Full Text Available Abstract Background In the past few years, both automated and manual high-throughput protein expression and purification has become an accessible means to rapidly screen and produce soluble proteins for structural and functional studies. However, many of the commercial vectors encoding different solubility tags require different cloning and purification steps for each vector, considerably slowing down expression screening. We have developed a set of E. coli expression vectors with different solubility tags that allow for parallel cloning from a single PCR product and can be purified using the same protocol. Results The set of E. coli expression vectors, encode for either a hexa-histidine tag or the three most commonly used solubility tags (GST, MBP, NusA and all with an N-terminal hexa-histidine sequence. The result is two-fold: the His-tag facilitates purification by immobilised metal affinity chromatography, whilst the fusion domains act primarily as solubility aids during expression, in addition to providing an optional purification step. We have also incorporated a TEV recognition sequence following the solubility tag domain, which allows for highly specific cleavage (using TEV protease of the fusion protein to yield native protein. These vectors are also designed for ligation-independent cloning and they possess a high-level expressing T7 promoter, which is suitable for auto-induction. To validate our vector system, we have cloned four different genes and also one gene into all four vectors and used small-scale expression and purification techniques. We demonstrate that the vectors are capable of high levels of expression and that efficient screening of new proteins can be readily achieved at the laboratory level. Conclusion The result is a set of four rationally designed vectors, which can be used for streamlined cloning, expression and purification of target proteins in the laboratory and have the potential for being adaptable to a high-throughput

High throughput 16S rRNA gene amplicon sequencing

DEFF Research Database (Denmark)

Nierychlo, Marta; Larsen, Poul; Jørgensen, Mads Koustrup

S rRNA gene amplicon sequencing has been developed over the past few years and is now ready to use for more comprehensive studies related to plant operation and optimization thanks to short analysis time, low cost, high throughput, and high taxonomic resolution. In this study we show how 16S r......RNA gene amplicon sequencing can be used to reveal factors of importance for the operation of full-scale nutrient removal plants related to settling problems and floc properties. Using optimized DNA extraction protocols, indexed primers and our in-house Illumina platform, we prepared multiple samples...... be correlated to the presence of the species that are regarded as “strong” and “weak” floc formers. In conclusion, 16S rRNA gene amplicon sequencing provides a high throughput approach for a rapid and cheap community profiling of activated sludge that in combination with multivariate statistics can be used...

In silico gene expression profiling in Cannabis sativa.

Science.gov (United States)

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 .

Gravity-regulated gene expression in Arabidopsis thaliana

Science.gov (United States)

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.

Enzyme free cloning for high throughput gene cloning and expression

NARCIS (Netherlands)

de Jong, R.N.; Daniëls, M.; Kaptein, R.; Folkers, G.E.

2006-01-01

Structural and functional genomics initiatives significantly improved cloning methods over the past few years. Although recombinational cloning is highly efficient, its costs urged us to search for an alternative high throughput (HTP) cloning method. We implemented a modified Enzyme Free Cloning

Sensitivity and fidelity of DNA microarray improved with integration of Amplified Differential Gene Expression (ADGE

Directory of Open Access Journals (Sweden)

Ile Kristina E

2003-07-01

Full Text Available Abstract Background The ADGE technique is a method designed to magnify the ratios of gene expression before detection. It improves the detection sensitivity to small change of gene expression and requires small amount of starting material. However, the throughput of ADGE is low. We integrated ADGE with DNA microarray (ADGE microarray and compared it with regular microarray. Results When ADGE was integrated with DNA microarray, a quantitative relationship of a power function between detected and input ratios was found. Because of ratio magnification, ADGE microarray was better able to detect small changes in gene expression in a drug resistant model cell line system. The PCR amplification of templates and efficient labeling reduced the requirement of starting material to as little as 125 ng of total RNA for one slide hybridization and enhanced the signal intensity. Integration of ratio magnification, template amplification and efficient labeling in ADGE microarray reduced artifacts in microarray data and improved detection fidelity. The results of ADGE microarray were less variable and more reproducible than those of regular microarray. A gene expression profile generated with ADGE microarray characterized the drug resistant phenotype, particularly with reference to glutathione, proliferation and kinase pathways. Conclusion ADGE microarray magnified the ratios of differential gene expression in a power function, improved the detection sensitivity and fidelity and reduced the requirement for starting material while maintaining high throughput. ADGE microarray generated a more informative expression pattern than regular microarray.

Effects of TCDD on the expression of nuclear encoded mitochondrial genes

International Nuclear Information System (INIS)

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

2010-01-01

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 nuclear 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 h) 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 sigmoidal or exponential dose-response profile (0.03 to 300 μg/kg TCDD) at 4, 24 or 72 h. Dose-responsive genes encoded proteins associated with electron transport chain (ETC) complexes 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 all 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.

Hierarchical information representation and efficient classification of gene expression microarray data

OpenAIRE

Bosio, Mattia

2014-01-01

In the field of computational biology, microarryas are used to measure the activity of thousands of genes at once and create a global picture of cellular function. Microarrays allow scientists to analyze expression of many genes in a single experiment quickly and eficiently. Even if microarrays are a consolidated research technology nowadays and the trends in high-throughput data analysis are shifting towards new technologies like Next Generation Sequencing (NGS), an optimum method for sample...

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

Science.gov (United States)

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.

Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue

Directory of Open Access Journals (Sweden)

Usadel Björn

2007-05-01

Full Text Available Abstract Background Micro- and macroarray technologies help acquire thousands of gene expression patterns covering important biological processes during plant ontogeny. Particularly, faithful visualization methods are beneficial for revealing interesting gene expression patterns and functional relationships of coexpressed genes. Such screening helps to gain deeper insights into regulatory behavior and cellular responses, as will be discussed for expression data of developing barley endosperm tissue. For that purpose, high-throughput multidimensional scaling (HiT-MDS, a recent method for similarity-preserving data embedding, is substantially refined and used for (a assessing the quality and reliability of centroid gene expression patterns, and for (b derivation of functional relationships of coexpressed genes of endosperm tissue during barley grain development (0–26 days after flowering. Results Temporal expression profiles of 4824 genes at 14 time points are faithfully embedded into two-dimensional displays. Thereby, similar shapes of coexpressed genes get closely grouped by a correlation-based similarity measure. As a main result, by using power transformation of correlation terms, a characteristic cloud of points with bipolar sandglass shape is obtained that is inherently connected to expression patterns of pre-storage, intermediate and storage phase of endosperm development. Conclusion The new HiT-MDS-2 method helps to create global views of expression patterns and to validate centroids obtained from clustering programs. Furthermore, functional gene annotation for developing endosperm barley tissue is successfully mapped to the visualization, making easy localization of major centroids of enriched functional categories possible.

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

Directory of Open Access Journals (Sweden)

Sivieng Jane

2009-12-01

Full Text Available Abstract Background 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. Results 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. Conclusion 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.

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

Science.gov (United States)

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.

Application of four dyes in gene expression analyses by microarrays

Directory of Open Access Journals (Sweden)

van Schooten Frederik J

2005-07-01

Full Text Available Abstract Background DNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. Results Following tests for cross-talk of fluorescence signals, Alexa 488, Alexa 594, Cyanine 3 and Cyanine 5 were selected for hybridizations. For self-hybridizations, a single RNA sample was labelled with all dyes and hybridized on commercial cDNA arrays or on in-house spotted oligonucleotide arrays. Correlation coefficients for all combinations of dyes were above 0.9 on the cDNA array. On the oligonucleotide array they were above 0.8, except combinations with Alexa 488, which were approximately 0.5. Standard deviation of expression differences for replicate spots were similar on the cDNA array for all dye combinations, but on the oligonucleotide array combinations with Alexa 488 showed a higher variation. Conclusion In conclusion, the four dyes can be used simultaneously for gene expression experiments on the tested cDNA array, but only three dyes can be used on the tested oligonucleotide array. This was confirmed by hybridizations of control with test samples, as all combinations returned similar numbers of differentially expressed genes with comparable effects on gene expression.

Candidate Genes for Testicular Cancer Evaluated by In Situ Protein Expression Analyses on Tissue Microarrays

Directory of Open Access Journals (Sweden)

Rolf I. Skotheim

2003-09-01

Full Text Available By the use of high-throughput molecular technologies, the number of genes and proteins potentially relevant to testicular germ cell tumor (TGCT and other diseases will increase rapidly. In a recent transcriptional profiling, we demonstrated the overexpression of GRB7 and JUP in TGCTs, confirmed the reported overexpression of CCND2. We also have recent evidences for frequent genetic alterations of FHIT and epigenetic alterations of MGMT. To evaluate whether the expression of these genes is related to any clinicopathological variables, we constructed a tissue microarray with 510 testicular tissue cores from 279 patients diagnosed with TGCT, covering various histological subgroups and clinical stages. By immunohistochemistry, we found that JUP, GRB7, CCND2 proteins were rarely present in normal testis, but frequently expressed at high levels in TGCT. Additionally, all premalignant intratubular germ cell neoplasias were JUP-immunopositive. MGMT and FHIT were expressed by normal testicular tissues, but at significantly lower frequencies in TGCT. Except for CCND2, the expressions of all markers were significantly associated with various TGCT subtypes. In summary, we have developed a high-throughput tool for the evaluation of TGCT markers, utilized this to validate five candidate genes whose protein expressions were indeed deregulated in TGCT.

Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

Directory of Open Access Journals (Sweden)

Hu Xiaohua

2011-07-01

Full Text Available Abstract Background The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets. Methods Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA and nonnegative matrix factorization (NMF are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles. Results In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and

Pervasive Effects of Aging on Gene Expression in Wild Wolves

Science.gov (United States)

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

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

Science.gov (United States)

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.

Machine learning in computational biology to accelerate high-throughput protein expression.

Science.gov (United States)

Sastry, Anand; Monk, Jonathan; Tegel, Hanna; Uhlen, Mathias; Palsson, Bernhard O; Rockberg, Johan; Brunk, Elizabeth

2017-08-15

The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. ebrunk@ucsd.edu or johanr@biotech.kth.se. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Transcriptional analysis of heterologous gene expression using the endogenous sD promoter from Bacillus halodurans

CSIR Research Space (South Africa)

Crampton, Michael C

2010-07-01

Full Text Available This presentation focused on the transcriptional analysis of heterologous gene expression using the endogenous sD promoter from Bacillus halodurans. It concludes to a successful implementation of a high throughput mRNA sandwich hybridisation...

Development of multitissue microfluidic dynamic array for assessing changes in gene expression associated with channel catfish appetite, growth, metabolism, and intestinal health

Science.gov (United States)

Large-scale, gene expression methods allow for high throughput analysis of physiological pathways at a fraction of the cost of individual gene expression analysis. Systems, such as the Fluidigm quantitative PCR array described here, can provide powerful assessments of the effects of diet, environme...

Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection

KAUST Repository

Dhavala, Soma S.

2010-09-01

Massively Parallel Signature Sequencing (MPSS) is a high-throughput, counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different strains of Salmonella obtained using the MPSS technology. In this article, we develop an exact ANOVA type model for this count data using a zero-inflatedPoisson distribution, different from existing methods that assume continuous densities. We adopt two Bayesian hierarchical models-one parametric and the other semiparametric with a Dirichlet process prior that has the ability to "borrow strength" across related signatures, where a signature is a specific arrangement of the nucleotides, usually 16-21 base pairs long. We utilize the discreteness of Dirichlet process prior to cluster signatures that exhibit similar differential expression profiles. Tests for differential expression are carried out using nonparametric approaches, while controlling the false discovery rate. We identify several differentially expressed genes that have important biological significance and conclude with a summary of the biological discoveries. This article has supplementary materials online. © 2010 American Statistical Association.

Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection

KAUST Repository

Dhavala, Soma S.; Datta, Sujay; Mallick, Bani K.; Carroll, Raymond J.; Khare, Sangeeta; Lawhon, Sara D.; Adams, L. Garry

2010-01-01

Massively Parallel Signature Sequencing (MPSS) is a high-throughput, counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different strains of Salmonella obtained using the MPSS technology. In this article, we develop an exact ANOVA type model for this count data using a zero-inflatedPoisson distribution, different from existing methods that assume continuous densities. We adopt two Bayesian hierarchical models-one parametric and the other semiparametric with a Dirichlet process prior that has the ability to "borrow strength" across related signatures, where a signature is a specific arrangement of the nucleotides, usually 16-21 base pairs long. We utilize the discreteness of Dirichlet process prior to cluster signatures that exhibit similar differential expression profiles. Tests for differential expression are carried out using nonparametric approaches, while controlling the false discovery rate. We identify several differentially expressed genes that have important biological significance and conclude with a summary of the biological discoveries. This article has supplementary materials online. © 2010 American Statistical Association.

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

Science.gov (United States)

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.

Radioactive cDNA microarrys for gene expression profiles in antidepressant therapy

International Nuclear Information System (INIS)

Lee, M. S.; Han, B. J.; Cha, J. H.; Ryu, Y. M.; Shin, E. K.; Park, J. H.; Park, Y. H.; Kim, M. K.

2002-01-01

Using radioactive cDNA microarray, we investigated a pattern of gene regulation under treatment of antidepressant on patients of depressive disoder. Basic microarray technology was performed as previously described in our research. The bioinformatic selection of human cDNAs, which is specifically designed for psychiatry, neurology, and signal transduction, were arrayed on nylon membranes. Using with 33P-labeled probes, this method provided highly sensitive gene expression profiles of our interest including brain receptors, drug metabolism, and cellular signalings. Gene expression profiles were also classified into several categories in accordance with the gene-regulation of antidepressant. The gene profiles of our interest were significantly up- (16 genes, >2.0 of Z-ratio) or down- (24 genes, <-2.0 of Z ratio) regulated when compared the good responsed group with the bad-responsed one. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology

Bulk segregant analysis by high-throughput sequencing reveals a novel xylose utilization gene from Saccharomyces cerevisiae.

Directory of Open Access Journals (Sweden)

Jared W Wenger

2010-05-01

Full Text Available Fermentation of xylose is a fundamental requirement for the efficient production of ethanol from lignocellulosic biomass sources. Although they aggressively ferment hexoses, it has long been thought that native Saccharomyces cerevisiae strains cannot grow fermentatively or non-fermentatively on xylose. Population surveys have uncovered a few naturally occurring strains that are weakly xylose-positive, and some S. cerevisiae have been genetically engineered to ferment xylose, but no strain, either natural or engineered, has yet been reported to ferment xylose as efficiently as glucose. Here, we used a medium-throughput screen to identify Saccharomyces strains that can increase in optical density when xylose is presented as the sole carbon source. We identified 38 strains that have this xylose utilization phenotype, including strains of S. cerevisiae, other sensu stricto members, and hybrids between them. All the S. cerevisiae xylose-utilizing strains we identified are wine yeasts, and for those that could produce meiotic progeny, the xylose phenotype segregates as a single gene trait. We mapped this gene by Bulk Segregant Analysis (BSA using tiling microarrays and high-throughput sequencing. The gene is a putative xylitol dehydrogenase, which we name XDH1, and is located in the subtelomeric region of the right end of chromosome XV in a region not present in the S288c reference genome. We further characterized the xylose phenotype by performing gene expression microarrays and by genetically dissecting the endogenous Saccharomyces xylose pathway. We have demonstrated that natural S. cerevisiae yeasts are capable of utilizing xylose as the sole carbon source, characterized the genetic basis for this trait as well as the endogenous xylose utilization pathway, and demonstrated the feasibility of BSA using high-throughput sequencing.

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

Science.gov (United States)

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.

Quantification of differential gene expression by multiplexed targeted resequencing of cDNA

Science.gov (United States)

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

A pipeline to determine RT-QPCR control genes for evolutionary studies: application to primate gene expression across multiple tissues.

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Olivier Fedrigo

Full Text Available Because many species-specific phenotypic differences are assumed to be caused by differential regulation of gene expression, many recent investigations have focused on measuring transcript abundance. Despite the availability of high-throughput platforms, quantitative real-time polymerase chain reaction (RT-QPCR is often the method of choice because of its low cost and wider dynamic range. However, the accuracy of this technique heavily relies on the use of multiple valid control genes for normalization. We created a pipeline for choosing genes potentially useful as RT-QPCR control genes for measuring expression between human and chimpanzee samples across multiple tissues, using published microarrays and a measure of tissue-specificity. We identified 13 genes from the pipeline and from commonly used control genes: ACTB, USP49, ARGHGEF2, GSK3A, TBP, SDHA, EIF2B2, GPDH, YWHAZ, HPTR1, RPL13A, HMBS, and EEF2. We then tested these candidate genes and validated their expression stability across species. We established the rank order of the most preferable set of genes for single and combined tissues. Our results suggest that for at least three tissues (cerebral cortex, liver, and skeletal muscle, EIF2B2, EEF2, HMBS, and SDHA are useful genes for normalizing human and chimpanzee expression using RT-QPCR. Interestingly, other commonly used control genes, including TBP, GAPDH, and, especially ACTB do not perform as well. This pipeline could be easily adapted to other species for which expression data exist, providing taxonomically appropriate control genes for comparisons of gene expression among species.

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

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Yuki Mitaka

Full Text Available 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.

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

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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.

A novel mean-centering method for normalizing microRNA expression from high-throughput RT-qPCR data

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Wylie Dennis

2011-12-01

Full Text Available Abstract Background Normalization is critical for accurate gene expression analysis. A significant challenge in the quantitation of gene expression from biofluids samples is the inability to quantify RNA concentration prior to analysis, underscoring the need for robust normalization tools for this sample type. In this investigation, we evaluated various methods of normalization to determine the optimal approach for quantifying microRNA (miRNA expression from biofluids and tissue samples when using the TaqMan® Megaplex™ high-throughput RT-qPCR platform with low RNA inputs. Findings We compared seven normalization methods in the analysis of variation of miRNA expression from biofluid and tissue samples. We developed a novel variant of the common mean-centering normalization strategy, herein referred to as mean-centering restricted (MCR normalization, which is adapted to the TaqMan Megaplex RT-qPCR platform, but is likely applicable to other high-throughput RT-qPCR-based platforms. Our results indicate that MCR normalization performs comparable to or better than both standard mean-centering and other normalization methods. We also propose an extension of this method to be used when migrating biomarker signatures from Megaplex to singleplex RT-qPCR platforms, based on the identification of a small number of normalizer miRNAs that closely track the mean of expressed miRNAs. Conclusions We developed the MCR method for normalizing miRNA expression from biofluids samples when using the TaqMan Megaplex RT-qPCR platform. Our results suggest that normalization based on the mean of all fully observed (fully detected miRNAs minimizes technical variance in normalized expression values, and that a small number of normalizer miRNAs can be selected when migrating from Megaplex to singleplex assays. In our study, we find that normalization methods that focus on a restricted set of miRNAs tend to perform better than methods that focus on all miRNAs, including

A CRISPR CASe for High-Throughput Silencing

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Jacob eHeintze

2013-10-01

Full Text Available Manipulation of gene expression on a genome-wide level is one of the most important systematic tools in the post-genome era. Such manipulations have largely been enabled by expression cloning approaches using sequence-verified cDNA libraries, large-scale RNA interference libraries (shRNA or siRNA and zinc finger nuclease technologies. More recently, the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated (Cas9-mediated gene editing technology has been described that holds great promise for future use of this technology in genomic manipulation. It was suggested that the CRISPR system has the potential to be used in high-throughput, large-scale loss of function screening. Here we discuss some of the challenges in engineering of CRISPR/Cas genomic libraries and some of the aspects that need to be addressed in order to use this technology on a high-throughput scale.

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

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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.

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

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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

Gene Expression Dynamics Accompanying the Sponge Thermal Stress Response.

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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.

Modeling insertional mutagenesis using gene length and expression in murine embryonic stem cells.

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Alex S Nord

2007-07-01

Full Text Available High-throughput mutagenesis of the mammalian genome is a powerful means to facilitate analysis of gene function. Gene trapping in embryonic stem cells (ESCs is the most widely used form of insertional mutagenesis in mammals. However, the rules governing its efficiency are not fully understood, and the effects of vector design on the likelihood of gene-trapping events have not been tested on a genome-wide scale.In this study, we used public gene-trap data to model gene-trap likelihood. Using the association of gene length and gene expression with gene-trap likelihood, we constructed spline-based regression models that characterize which genes are susceptible and which genes are resistant to gene-trapping techniques. We report results for three classes of gene-trap vectors, showing that both length and expression are significant determinants of trap likelihood for all vectors. Using our models, we also quantitatively identified hotspots of gene-trap activity, which represent loci where the high likelihood of vector insertion is controlled by factors other than length and expression. These formalized statistical models describe a high proportion of the variance in the likelihood of a gene being trapped by expression-dependent vectors and a lower, but still significant, proportion of the variance for vectors that are predicted to be independent of endogenous gene expression.The findings of significant expression and length effects reported here further the understanding of the determinants of vector insertion. Results from this analysis can be applied to help identify other important determinants of this important biological phenomenon and could assist planning of large-scale mutagenesis efforts.

Gene expression and gene therapy imaging

International Nuclear Information System (INIS)

Rome, Claire; Couillaud, Franck; Moonen, Chrit T.W.

2007-01-01

The fast growing field of molecular imaging has achieved major advances in imaging gene expression, an important element of gene therapy. Gene expression imaging is based on specific probes or contrast agents that allow either direct or indirect spatio-temporal evaluation of gene expression. Direct evaluation is possible with, for example, contrast agents that bind directly to a specific target (e.g., receptor). Indirect evaluation may be achieved by using specific substrate probes for a target enzyme. The use of marker genes, also called reporter genes, is an essential element of MI approaches for gene expression in gene therapy. The marker gene may not have a therapeutic role itself, but by coupling the marker gene to a therapeutic gene, expression of the marker gene reports on the expression of the therapeutic gene. Nuclear medicine and optical approaches are highly sensitive (detection of probes in the picomolar range), whereas MRI and ultrasound imaging are less sensitive and require amplification techniques and/or accumulation of contrast agents in enlarged contrast particles. Recently developed MI techniques are particularly relevant for gene therapy. Amongst these are the possibility to track gene therapy vectors such as stem cells, and the techniques that allow spatiotemporal control of gene expression by non-invasive heating (with MRI guided focused ultrasound) and the use of temperature sensitive promoters. (orig.)

High-throughput Cloning and Expression of Integral Membrane Proteins in Escherichia coli

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Bruni, Renato

2014-01-01

Recently, several structural genomics centers have been established and a remarkable number of three-dimensional structures of soluble proteins have been solved. For membrane proteins, the number of structures solved has been significantly trailing those for their soluble counterparts, not least because over-expression and purification of membrane proteins is a much more arduous process. By using high throughput technologies, a large number of membrane protein targets can be screened simultaneously and a greater number of expression and purification conditions can be employed, leading to a higher probability of successfully determining the structure of membrane proteins. This unit describes the cloning, expression and screening of membrane proteins using high throughput methodologies developed in our laboratory. Basic Protocol 1 deals with the cloning of inserts into expression vectors by ligation-independent cloning. Basic Protocol 2 describes the expression and purification of the target proteins on a miniscale. Lastly, for the targets that express at the miniscale, basic protocols 3 and 4 outline the methods employed for the expression and purification of targets at the midi-scale, as well as a procedure for detergent screening and identification of detergent(s) in which the target protein is stable. PMID:24510647

Exploring gene expression changes in the amphioxus gill after poly(I:C) challenge using digital expression profiling.

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Zhang, Qi-Lin; Qiu, Han-Yue; Liang, Ming-Zhong; Luo, Bang; Wang, Xiu-Qiang; Chen, Jun-Yuan

2017-11-01

Amphioxus, a cephalochordate, is a key model animal for studying the evolution of vertebrate immunity. Recently, studies have revealed that microRNA (miRNA) expression profiles change significantly in the amphioxus gill after immune stimulation, but it remains largely unknown how gene expression responds to immune stress. Elucidating gene expression changes in the amphioxus gill will provide a deeper understanding of the evolution of gill immunity in vertebrates. Here, we used high-throughput RNA sequencing technology (RNA-seq) to conduct tag-based digital gene expression profiling (DGE) analyses of the gills of control Branchiostoma belcheri and of those exposed to the viral mimic, poly(I:C) (pIC). Six libraries were created for the control and treatment groups including three biological replicates per group. A total of 1999 differently expressed genes (DEGs) were obtained, with 571 and 1428 DEGs showing up- or down-regulation, respectively, in the treatment group. Enrichment analysis of gene ontology (GO) terms and pathways revealed that the DEGs were primarily related to immune and defense response, apoptosis, human disease, cancer, protein metabolism, enzyme activity, and regulatory processes. In addition, eight DEGs were randomly selected to validate the RNA-seq data using real-time quantitative PCR (qRT-PCR), and the results confirmed the accuracy of the RNA-seq approach. Next, we screened eight key responding genes to examine the dynamic changes in expression levels at different time points in more detail. The results indicated that expressions of TRADD, MARCH, RNF31, NF-κb, CYP450, TNFRSF6B, IFI and LECT1 were induced to participate in the antiviral response against pIC. This study provides a valuable resource for understanding the role of the amphioxus gill in antiviral immunity and the evolution of gill immunity in vertebrates. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

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Murray P Cox

2014-03-01

Full Text Available 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

Machine learning in computational biology to accelerate high-throughput protein expression

DEFF Research Database (Denmark)

Sastry, Anand; Monk, Jonathan M.; Tegel, Hanna

2017-01-01

and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide...... the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. Availability and implementation: We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template...

A gene expression signature associated with survival in metastatic melanoma

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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

A gene expression signature associated with survival in metastatic melanoma

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Rossi Carlo R

2006-11-01

Full Text Available Abstract 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.

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

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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.

Gene expression

International Nuclear Information System (INIS)

Hildebrand, C.E.; Crawford, B.D.; Walters, R.A.; Enger, M.D.

1983-01-01

We prepared probes for isolating functional pieces of the metallothionein locus. The probes enabled a variety of experiments, eventually revealing two mechanisms for metallothionein gene expression, the order of the DNA coding units at the locus, and the location of the gene site in its chromosome. Once the switch regulating metallothionein synthesis was located, it could be joined by recombinant DNA methods to other, unrelated genes, then reintroduced into cells by gene-transfer techniques. The expression of these recombinant genes could then be induced by exposing the cells to Zn 2+ or Cd 2+ . We would thus take advantage of the clearly defined switching properties of the metallothionein gene to manipulate the expression of other, perhaps normally constitutive, genes. Already, despite an incomplete understanding of how the regulatory switch of the metallothionein locus operates, such experiments have been performed successfully

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

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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 .

A comparison of digital gene expression profiling and methyl DNA immunoprecipitation as methods for gene discovery in honeybee (Apis mellifera behavioural genomic analyses.

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Cui Guan

Full Text Available The honey bee has a well-organized system of division of labour among workers. Workers typically progress through a series of discrete behavioural castes as they age, and this has become an important case study for exploring how dynamic changes in gene expression can influence behaviour. Here we applied both digital gene expression analysis and methyl DNA immunoprecipitation analysis to nurse, forager and reverted nurse bees (nurses that have returned to the nursing state after a period spent foraging from the same colony in order to compare the outcomes of these different forms of genomic analysis. A total of 874 and 710 significantly differentially expressed genes were identified in forager/nurse and reverted nurse/forager comparisons respectively. Of these, 229 genes exhibited reversed directions of gene expression differences between the forager/nurse and reverted nurse/forager comparisons. Using methyl-DNA immunoprecipitation combined with high-throughput sequencing (MeDIP-seq we identified 366 and 442 significantly differentially methylated genes in forager/nurse and reverted nurse/forager comparisons respectively. Of these, 165 genes were identified as differentially methylated in both comparisons. However, very few genes were identified as both differentially expressed and differentially methylated in our comparisons of nurses and foragers. These findings confirm that changes in both gene expression and DNA methylation are involved in the nurse and forager behavioural castes, but the different analytical methods reveal quite distinct sets of candidate genes.

Zebrafish Expression Ontology of Gene Sets (ZEOGS): A Tool to Analyze Enrichment of Zebrafish Anatomical Terms in Large Gene Sets

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Marsico, Annalisa

2013-01-01

Abstract The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene

Zebrafish Expression Ontology of Gene Sets (ZEOGS): a tool to analyze enrichment of zebrafish anatomical terms in large gene sets.

Science.gov (United States)

Prykhozhij, Sergey V; Marsico, Annalisa; Meijsing, Sebastiaan H

2013-09-01

The zebrafish (Danio rerio) is an established model organism for developmental and biomedical research. It is frequently used for high-throughput functional genomics experiments, such as genome-wide gene expression measurements, to systematically analyze molecular mechanisms. However, the use of whole embryos or larvae in such experiments leads to a loss of the spatial information. To address this problem, we have developed a tool called Zebrafish Expression Ontology of Gene Sets (ZEOGS) to assess the enrichment of anatomical terms in large gene sets. ZEOGS uses gene expression pattern data from several sources: first, in situ hybridization experiments from the Zebrafish Model Organism Database (ZFIN); second, it uses the Zebrafish Anatomical Ontology, a controlled vocabulary that describes connected anatomical structures; and third, the available connections between expression patterns and anatomical terms contained in ZFIN. Upon input of a gene set, ZEOGS determines which anatomical structures are overrepresented in the input gene set. ZEOGS allows one for the first time to look at groups of genes and to describe them in terms of shared anatomical structures. To establish ZEOGS, we first tested it on random gene selections and on two public microarray datasets with known tissue-specific gene expression changes. These tests showed that ZEOGS could reliably identify the tissues affected, whereas only very few enriched terms to none were found in the random gene sets. Next we applied ZEOGS to microarray datasets of 24 and 72 h postfertilization zebrafish embryos treated with beclomethasone, a potent glucocorticoid. This analysis resulted in the identification of several anatomical terms related to glucocorticoid-responsive tissues, some of which were stage-specific. Our studies highlight the ability of ZEOGS to extract spatial information from datasets derived from whole embryos, indicating that ZEOGS could be a useful tool to automatically analyze gene expression

Neighboring Genes Show Correlated Evolution in Gene Expression

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Ghanbarian, Avazeh T.; Hurst, Laurence D.

2015-01-01

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

Gene Expression Commons: an open platform for absolute gene expression profiling.

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Jun Seita

Full Text Available Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000 of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/ which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.

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

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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.

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

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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.

Gene expression differences between Noccaea caerulescens ecotypes help to identify candidate genes for metal phytoremediation.

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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.

High-throughput sequencing of microRNA transcriptome and expression assay in the sturgeon, Acipenser schrenckii.

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Lihong Yuan

Full Text Available Sturgeons are considered as living fossils and have very high evolutionary, economical and conservation values. The multiploidy of sturgeon that has been caused by chromosome duplication may lead to the emergence of new microRNAs (miRNAs involved in the ploidy and physiological processes. In the present study, we performed the first sturgeon miRNAs analysis by RNA-seq high-throughput sequencing combined with expression assay of microarray and real-time PCR, and aimed to discover the sturgeon-specific miRNAs, confirm the expressed pattern of miRNAs and illustrate the potential role of miRNAs-targets on sturgeon biological processes. A total of 103 miRNAs were identified, including 58 miRNAs with strongly detected signals (signal >500 and P≤0.01, which were detected by microarray. Real-time PCR assay supported the expression pattern obtained by microarray. Moreover, co-expression of 21 miRNAs in all five tissues and tissue-specific expression of 16 miRNAs implied the crucial and particular function of them in sturgeon physiological processes. Target gene prediction, especially the enriched functional gene groups (369 GO terms and pathways (37 KEGG regulated by 58 miRNAs (P<0.05, illustrated the interaction of miRNAs and putative mRNAs, and also the potential mechanism involved in these biological processes. Our new findings of sturgeon miRNAs expand the public database of transcriptome information for this species, contribute to our understanding of sturgeon biology, and also provide invaluable data that may be applied in sturgeon breeding.

High-throughput sequencing of microRNA transcriptome and expression assay in the sturgeon, Acipenser schrenckii.

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Yuan, Lihong; Zhang, Xiujuan; Li, Linmiao; Jiang, Haiying; Chen, Jinping

2014-01-01

Sturgeons are considered as living fossils and have very high evolutionary, economical and conservation values. The multiploidy of sturgeon that has been caused by chromosome duplication may lead to the emergence of new microRNAs (miRNAs) involved in the ploidy and physiological processes. In the present study, we performed the first sturgeon miRNAs analysis by RNA-seq high-throughput sequencing combined with expression assay of microarray and real-time PCR, and aimed to discover the sturgeon-specific miRNAs, confirm the expressed pattern of miRNAs and illustrate the potential role of miRNAs-targets on sturgeon biological processes. A total of 103 miRNAs were identified, including 58 miRNAs with strongly detected signals (signal >500 and P≤0.01), which were detected by microarray. Real-time PCR assay supported the expression pattern obtained by microarray. Moreover, co-expression of 21 miRNAs in all five tissues and tissue-specific expression of 16 miRNAs implied the crucial and particular function of them in sturgeon physiological processes. Target gene prediction, especially the enriched functional gene groups (369 GO terms) and pathways (37 KEGG) regulated by 58 miRNAs (P<0.05), illustrated the interaction of miRNAs and putative mRNAs, and also the potential mechanism involved in these biological processes. Our new findings of sturgeon miRNAs expand the public database of transcriptome information for this species, contribute to our understanding of sturgeon biology, and also provide invaluable data that may be applied in sturgeon breeding.

Gateway-compatible vectors for high-throughput protein expression in pro- and eukaryotic cell-free systems.

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Gagoski, Dejan; Mureev, Sergey; Giles, Nichole; Johnston, Wayne; Dahmer-Heath, Mareike; Škalamera, Dubravka; Gonda, Thomas J; Alexandrov, Kirill

2015-02-10

Although numerous techniques for protein expression and production are available the pace of genome sequencing outstrips our ability to analyze the encoded proteins. To address this bottleneck, we have established a system for parallelized cloning, DNA production and cell-free expression of large numbers of proteins. This system is based on a suite of pCellFree Gateway destination vectors that utilize a Species Independent Translation Initiation Sequence (SITS) that mediates recombinant protein expression in any in vitro translation system. These vectors introduce C or N terminal EGFP and mCherry fluorescent and affinity tags, enabling direct analysis and purification of the expressed proteins. To maximize throughput and minimize the cost of protein production we combined Gateway cloning with Rolling Circle DNA Amplification. We demonstrate that as little as 0.1 ng of plasmid DNA is sufficient for template amplification and production of recombinant human protein in Leishmania tarentolae and Escherichia coli cell-free expression systems. Our experiments indicate that this approach can be applied to large gene libraries as it can be reliably performed in multi-well plates. The resulting protein expression pipeline provides a valuable new tool for applications of the post genomic era. Copyright © 2014 Elsevier B.V. All rights reserved.

Meta Analysis of Gene Expression Data within and Across Species.

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Fierro, Ana C; Vandenbussche, Filip; Engelen, Kristof; Van de Peer, Yves; Marchal, Kathleen

2008-12-01

Since the second half of the 1990s, a large number of genome-wide analyses have been described that study gene expression at the transcript level. To this end, two major strategies have been adopted, a first one relying on hybridization techniques such as microarrays, and a second one based on sequencing techniques such as serial analysis of gene expression (SAGE), cDNA-AFLP, and analysis based on expressed sequence tags (ESTs). Despite both types of profiling experiments becoming routine techniques in many research groups, their application remains costly and laborious. As a result, the number of conditions profiled in individual studies is still relatively small and usually varies from only two to few hundreds of samples for the largest experiments. More and more, scientific journals require the deposit of these high throughput experiments in public databases upon publication. Mining the information present in these databases offers molecular biologists the possibility to view their own small-scale analysis in the light of what is already available. However, so far, the richness of the public information remains largely unexploited. Several obstacles such as the correct association between ESTs and microarray probes with the corresponding gene transcript, the incompleteness and inconsistency in the annotation of experimental conditions, and the lack of standardized experimental protocols to generate gene expression data, all impede the successful mining of these data. Here, we review the potential and difficulties of combining publicly available expression data from respectively EST analyses and microarray experiments. With examples from literature, we show how meta-analysis of expression profiling experiments can be used to study expression behavior in a single organism or between organisms, across a wide range of experimental conditions. We also provide an overview of the methods and tools that can aid molecular biologists in exploiting these public data.

High-Throughput Screening of a Luciferase Reporter of Gene Silencing on the Inactive X Chromosome.

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Keegan, Alissa; Plath, Kathrin; Damoiseaux, Robert

2018-01-01

Assays of luciferase gene activity are a sensitive and quantitative reporter system suited to high-throughput screening. We adapted a luciferase assay to a screening strategy for identifying factors that reactivate epigenetically silenced genes. This epigenetic luciferase reporter is subject to endogenous gene silencing mechanisms on the inactive X chromosome (Xi) in primary mouse cells and thus captures the multilayered nature of chromatin silencing in development. Here, we describe the optimization of an Xi-linked luciferase reactivation assay in 384-well format and adaptation of the assay for high-throughput siRNA and chemical screening. Xi-luciferase reactivation screening has applications in stem cell biology and cancer therapy. We have used the approach described here to identify chromatin-modifying proteins and to identify drug combinations that enhance the gene reactivation activity of the DNA demethylating drug 5-aza-2'-deoxycytidine.

A high-throughput fluorescence-based assay system for appetite-regulating gene and drug screening.

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Yasuhito Shimada

Full Text Available 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.

Step-by-Step Construction of Gene Co-expression Networks from High-Throughput Arabidopsis RNA Sequencing Data.

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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.

Imaging gene expression in gene therapy

International Nuclear Information System (INIS)

Wiebe, Leonard I.

1997-01-01

Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on 'suicide gene therapy' of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k + ) has been use for 'suicide' in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k + gene expression where the H S V-1 t k + gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([ 18 F]F H P G; [ 18 F]-A C V), and pyrimidine- ([ 123 / 131 I]I V R F U; [ 124 / 131I ]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [ 123 / 131I ]I V R F U imaging with the H S V-1 t k + reporter gene will be presented

Specific gene expression responses to parasite genotypes reveal redundancy of innate immunity in vertebrates.

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David Haase

Full Text Available Vertebrate innate immunity is the first line of defense against an invading pathogen and has long been assumed to be largely unspecific with respect to parasite/pathogen species. However, recent phenotypic evidence suggests that immunogenetic variation, i.e. allelic variability in genes associated with the immune system, results in host-parasite genotype-by-genotype interactions and thus specific innate immune responses. Immunogenetic variation is common in all vertebrate taxa and this reflects an effective immunological function in complex environments. However, the underlying variability in host gene expression patterns as response of innate immunity to within-species genetic diversity of macroparasites in vertebrates is unknown. We hypothesized that intra-specific variation among parasite genotypes must be reflected in host gene expression patterns. Here we used high-throughput RNA-sequencing to examine the effect of parasite genotypes on gene expression patterns of a vertebrate host, the three-spined stickleback (Gasterosteus aculeatus. By infecting naïve fish with distinct trematode genotypes of the species Diplostomum pseudospathaceum we show that gene activity of innate immunity in three-spined sticklebacks depended on the identity of an infecting macroparasite genotype. In addition to a suite of genes indicative for a general response against the trematode we also find parasite-strain specific gene expression, in particular in the complement system genes, despite similar infection rates of single clone treatments. The observed discrepancy between infection rates and gene expression indicates the presence of alternative pathways which execute similar functions. This suggests that the innate immune system can induce redundant responses specific to parasite genotypes.

Imaging gene expression in gene therapy

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Wiebe, Leonard I. [Alberta Univ., Edmonton (Canada). Noujaim Institute for Pharmaceutical Oncology Research

1997-12-31

Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on `suicide gene therapy` of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k{sup +}) has been use for `suicide` in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k{sup +} gene expression where the H S V-1 t k{sup +} gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([{sup 18} F]F H P G; [{sup 18} F]-A C V), and pyrimidine- ([{sup 123}/{sup 131} I]I V R F U; [{sup 124}/{sup 131I}]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [{sup 123}/{sup 131I}]I V R F U imaging with the H S V-1 t k{sup +} reporter gene will be presented

Identifying Stable Reference Genes for qRT-PCR Normalisation in Gene Expression Studies of Narrow-Leafed Lupin (Lupinus angustifolius L..

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Candy M Taylor

Full Text Available 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

Identification of differentially expressed genes in sunflower (Helianthus annuus) leaves and roots under drought stress by RNA sequencing.

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Liang, Chunbo; Wang, Wenjun; Wang, Jing; Ma, Jun; Li, Cen; Zhou, Fei; Zhang, Shuquan; Yu, Ying; Zhang, Liguo; Li, Weizhong; Huang, Xutang

2017-10-25

Sunflower is recognized as one of the most important oil plants with strong tolerance to drought in the world. In order to study the response mechanisms of sunflower plants to drought stress, gene expression profiling using high throughput sequencing was performed for seedling leaves and roots (sunflower inbred line R5) after 24 h of drought stress (15% PEG 6000). The transcriptome assembled using sequences of 12 samples was used as a reference. 805 and 198 genes were identified that were differentially expressed in leaves and roots, respectively. Another 71 genes were differentially expressed in both organs, in which more genes were up-regulated than down-regulated. In agreement with results obtained for other crops or from previous sunflower studies, we also observed that nine genes may be associated with the response of sunflower to drought. The results of this study may provide new information regarding the sunflower drought response, as well as add to the number of known genes associated with drought tolerance.

PamR, a new MarR-like regulator affecting prophages and metabolic genes expression in Bacillus subtilis.

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Alba De San Eustaquio-Campillo

Full Text Available B. subtilis adapts to changing environments by reprogramming its genetic expression through a variety of transcriptional regulators from the global transition state regulators that allow a complete resetting of the cell genetic expression, to stress specific regulators controlling only a limited number of key genes required for optimal adaptation. Among them, MarR-type transcriptional regulators are known to respond to a variety of stresses including antibiotics or oxidative stress, and to control catabolic or virulence gene expression. Here we report the characterization of the ydcFGH operon of B. subtilis, containing a putative MarR-type transcriptional regulator. Using a combination of molecular genetics and high-throughput approaches, we show that this regulator, renamed PamR, controls directly its own expression and influence the expression of large sets of prophage-related and metabolic genes. The extent of the regulon impacted by PamR suggests that this regulator reprograms the metabolic landscape of B. subtilis in response to a yet unknown signal.

Assessing a new gene expression analysis technique for radiation biodosimetry applications

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Manning, Grainne; Kabacik, Sylwia; Finnon, Paul; Paillier, Francois; Bouffler, Simon [Cancer Genetics and Cytogenetics, Biological Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Health Protection Agency, Chilton, Didcot, Oxfordshire OX11 ORQ (United Kingdom); Badie, Christophe, E-mail: christophe.badie@hpa.org.uk [Cancer Genetics and Cytogenetics, Biological Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Health Protection Agency, Chilton, Didcot, Oxfordshire OX11 ORQ (United Kingdom)

2011-09-15

The response to any radiation accident or incident involving actual or potential ionising radiation exposure requires accurate and rapid assessment of the doses received by individuals. The techniques available today for biodosimetry purposes are not fully adapted to rapid high-throughput measurements of exposures in large numbers of individuals. A recently emerging technique is based on gene expression analysis, as there are a number of genes which are radiation responsive in a dose-dependent manner. The present work aimed to assess a new technique which allows the detection of the level of expression of up to 800 genes without need of enzymatic reactions. In order to do so, human peripheral blood was exposed ex vivo to a range of x-ray doses from 5 mGy to 4 Gy of x-rays and the transcriptional expression of five radiation-responsive genes PHPT1, PUMA, CCNG1, DDB2 and MDM2 was studied by both the nCounter Digital Analyzer and Multiplex Quantitative Real-Time Polymerase Chain Reaction (MQRT-PCR) as the benchmark technology. Results from both techniques showed good correlation for all genes with R{sup 2} values ranging between 0.8160 and 0.9754. The reproducibility of the nCounter Digital Analyzer was also assessed in independent biological replicates and proved to be good. Although the slopes of the correlation of results obtained by the techniques suggest that MQRT-PCR is more sensitive than the nCounter Digital Analyzer, the nCounter Digital Analyzer provides sensitive and reliable data on modifications in gene expression in human blood exposed to radiation without enzymatic amplification of RNA prior to analysis.

A Microchip for Integrated Single-Cell Gene Expression Profiling and Genotoxicity Detection

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Hui Dong

2016-09-01

Full Text Available Microfluidics-based single-cell study is an emerging approach in personalized treatment or precision medicine studies. Single-cell gene expression holds a potential to provide treatment selections with maximized efficacy to help cancer patients based on a genetic understanding of their disease. This work presents a multi-layer microchip for single-cell multiplexed gene expression profiling and genotoxicity detection. Treated by three drug reagents (i.e., methyl methanesulfonate, docetaxel and colchicine with varied concentrations and time lengths, individual human cancer cells (MDA-MB-231 are lysed on-chip, and the released mRNA templates are captured and reversely transcribed into single strand DNA. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH, cyclin-dependent kinase inhibitor 1A (CDKN1A, and aurora kinase A (AURKA genes from single cells are amplified and real-time quantified through multiplex polymerase chain reaction. The microchip is capable of integrating all steps of single-cell multiplexed gene expression profiling, and providing precision detection of drug induced genotoxic stress. Throughput has been set to be 18, and can be further increased following the same approach. Numerical simulation of on-chip single cell trapping and heat transfer has been employed to evaluate the chip design and operation.

Expression stabilities of candidate reference genes for RT-qPCR under different stress conditions in soybean.

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Shuhua Ma

Full Text Available Due to its accuracy, sensitivity and high throughput, real time quantitative PCR (RT-qPCR has been widely used in analysing gene expression. The quality of data from such analyses is affected by the quality of reference genes used. Expression stabilities for nine candidate reference genes widely used in soybean were evaluated under different stresses in this study. Our results showed that EF1A and ACT11 were the best under salinity stress, TUB4, TUA5 and EF1A were the best under drought stress, ACT11 and UKN2 were the best under dark treatment, and EF1B and UKN2 were the best under virus infection. EF1B and UKN2 were the top two genes which can be reliably used in all of the stress conditions assessed.

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

OpenAIRE

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

2015-01-01

Background: 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. Methods: 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 bioinform...

High throughput analysis reveals dissociable gene expression profiles in two independent neural systems involved in the regulation of social behavior

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Stevenson Tyler J

2012-10-01

Full Text Available Abstract Background Production of contextually appropriate social behaviors involves integrated activity across many brain regions. Many songbird species produce complex vocalizations called ‘songs’ that serve to attract potential mates, defend territories, and/or maintain flock cohesion. There are a series of discrete interconnect brain regions that are essential for the successful production of song. The probability and intensity of singing behavior is influenced by the reproductive state. The objectives of this study were to examine the broad changes in gene expression in brain regions that control song production with a brain region that governs the reproductive state. Results We show using microarray cDNA analysis that two discrete brain systems that are both involved in governing singing behavior show markedly different gene expression profiles. We found that cortical and basal ganglia-like brain regions that control the socio-motor production of song in birds exhibit a categorical switch in gene expression that was dependent on their reproductive state. This pattern is in stark contrast to the pattern of expression observed in a hypothalamic brain region that governs the neuroendocrine control of reproduction. Subsequent gene ontology analysis revealed marked variation in the functional categories of active genes dependent on reproductive state and anatomical localization. HVC, one cortical-like structure, displayed significant gene expression changes associated with microtubule and neurofilament cytoskeleton organization, MAP kinase activity, and steroid hormone receptor complex activity. The transitions observed in the preoptic area, a nucleus that governs the motivation to engage in singing, exhibited variation in functional categories that included thyroid hormone receptor activity, epigenetic and angiogenetic processes. Conclusions These findings highlight the importance of considering the temporal patterns of gene expression

High-throughput screening of effective siRNAs using luciferase-linked chimeric mRNA.

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Shen Pang

Full Text Available The use of siRNAs to knock down gene expression can potentially be an approach to treat various diseases. To avoid siRNA toxicity the less transcriptionally active H1 pol III promoter, rather than the U6 promoter, was proposed for siRNA expression. To identify highly efficacious siRNA sequences, extensive screening is required, since current computer programs may not render ideal results. Here, we used CCR5 gene silencing as a model to investigate a rapid and efficient screening approach. We constructed a chimeric luciferase-CCR5 gene for high-throughput screening of siRNA libraries. After screening approximately 900 shRNA clones, 12 siRNA sequences were identified. Sequence analysis demonstrated that most (11 of the 12 sequences of these siRNAs did not match those identified by available siRNA prediction algorithms. Significant inhibition of CCR5 in a T-lymphocyte cell line and primary T cells by these identified siRNAs was confirmed using the siRNA lentiviral vectors to infect these cells. The inhibition of CCR5 expression significantly protected cells from R5 HIV-1JRCSF infection. These results indicated that the high-throughput screening method allows efficient identification of siRNA sequences to inhibit the target genes at low levels of expression.

GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments

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Kohlbacher Oliver

2008-12-01

Full Text Available Abstract Background High-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical processes. While the noisiness of the data necessitates an extensive pre-processing of the raw data, the high dimensionality requires effective statistical analysis methods that facilitate the identification of crucial biological features and relations. For these reasons, the evaluation and interpretation of expression data is a complex, labor-intensive multi-step process. While a variety of tools for normalizing, analysing, or visualizing expression profiles has been developed in the last years, most of these tools offer only functionality for accomplishing certain steps of the evaluation pipeline. Results Here, we present a web-based toolbox that provides rich functionality for all steps of the evaluation pipeline. Our tool GeneTrailExpress offers besides standard normalization procedures powerful statistical analysis methods for studying a large variety of biological categories and pathways. Furthermore, an integrated graph visualization tool, BiNA, enables the user to draw the relevant biological pathways applying cutting-edge graph-layout algorithms. Conclusion Our gene expression toolbox with its interactive visualization of the pathways and the expression values projected onto the nodes will simplify the analysis and interpretation of biochemical pathways considerably.

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

International Nuclear Information System (INIS)

Pogribny, Igor P.; Bagnyukova, Tetyana V.; Tryndyak, Volodymyr P.; Muskhelishvili, Levan; Rodriguez-Juarez, Rocio; Kovalchuk, Olga; Han Tao; Fuscoe, James C.; Ross, Sharon A.; Beland, Frederick A.

2007-01-01

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. In 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 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

Genome-Wide Constitutively Expressed Gene Analysis and New Reference Gene Selection Based on Transcriptome Data: A Case Study from Poplar/Canker Disease Interaction

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Jiaping Zhao

2017-10-01

Full Text Available A number of transcriptome datasets for differential expression (DE genes have been widely used for understanding organismal biology, but these datasets also contain untapped information that can be used to develop more precise analytical tools. With the use of transcriptome data generated from poplar/canker disease interaction system, we describe a methodology to identify candidate reference genes from high-throughput sequencing data. This methodology will improve the accuracy of RT-qPCR and will lead to better standards for the normalization of expression data. Expression stability analysis from xylem and phloem of Populus bejingensis inoculated with the fungal canker pathogen Botryosphaeria dothidea revealed that 729 poplar transcripts (1.11% were stably expressed, at a threshold level of coefficient of variance (CV of FPKM < 20% and maximum fold change (MFC of FPKM < 2.0. Expression stability and bioinformatics analysis suggested that commonly used house-keeping (HK genes were not the most appropriate internal controls: 70 of the 72 commonly used HK genes were not stably expressed, 45 of the 72 produced multiple isoform transcripts, and some of their reported primers produced unspecific amplicons in PCR amplification. RT-qPCR analysis to compare and evaluate the expression stability of 10 commonly used poplar HK genes and 20 of the 729 newly-identified stably expressed transcripts showed that some of the newly-identified genes (such as SSU_S8e, LSU_L5e, and 20S_PSU had higher stability ranking than most of commonly used HK genes. Based on these results, we recommend a pipeline for deriving reference genes from transcriptome data. An appropriate candidate gene should have a unique transcript, constitutive expression, CV value of expression < 20% (or possibly 30% and MFC value of expression <2, and an expression level of 50–1,000 units. Lastly, when four of the newly identified HK genes were used in the normalization of expression data for 20

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Optimal consistency in microRNA expression analysis using reference-gene-based normalization.

Science.gov (United States)

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.

Expression of Root Genes in Arabidopsis Seedlings Grown by Standard and Improved Growing Methods.

Science.gov (United States)

Qu, Yanli; Liu, Shuai; Bao, Wenlong; Xue, Xian; Ma, Zhengwen; Yokawa, Ken; Baluška, František; Wan, Yinglang

2017-05-03

Roots of Arabidopsis thaliana seedlings grown in the laboratory using the traditional plant-growing culture system (TPG) were covered to maintain them in darkness. This new method is based on a dark chamber and is named the improved plant-growing method (IPG). We measured the light conditions in dark chambers, and found that the highest light intensity was dramatically reduced deeper in the dark chamber. In the bottom and side parts of dark chambers, roots were almost completely shaded. Using the high-throughput RNA sequencing method on the whole RNA extraction from roots, we compared the global gene expression levels in roots of seedlings from these two conditions and identified 141 differently expressed genes (DEGs) between them. According to the KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment, the flavone and flavonol biosynthesis and flavonoid biosynthesis pathways were most affected among all annotated pathways. Surprisingly, no genes of known plant photoreceptors were identified as DEGs by this method. Considering that the light intensity was decreased in the IPG system, we collected four sections (1.5 cm for each) of Arabidopsis roots grown in TPG and IPG conditions, and the spatial-related differential gene expression levels of plant photoreceptors and polar auxin transporters, including CRY1 , CRY2 , PHYA , PHYB , PHOT1 , PHOT2 , and UVR8 were analyzed by qRT-PCR. Using these results, we generated a map of the spatial-related expression patterns of these genes under IPG and TPG conditions. The expression levels of light-related genes in roots is highly sensitive to illumination and it provides a background reference for selecting an improved culture method for laboratory-maintained Arabidopsis seedlings.

Weighted Gene Co-expression Network Analysis of the Dioscin Rich Medicinal Plant Dioscorea nipponica

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Wei Sun

2017-06-01

Full Text Available Dioscorea contains critically important species which can be used as staple foods or sources of bioactive substances, including Dioscorea nipponica, which has been used to develop highly successful drugs to treat cardiovascular disease. Its major active ingredients are thought to be sterol compounds such as diosgenin, which has been called “medicinal gold” because of its valuable properties. However, reliance on naturally growing plants as a production system limits the potential use of D. nipponica, raising interest in engineering metabolic pathways to enhance the production of secondary metabolites. However, the biosynthetic pathway of diosgenin is still poorly understood, and D. nipponica is poorly characterized at a molecular level, hindering in-depth investigation. In the present work, the RNAs from five organs and seven methyl jasmonate treated D. nipponica rhizomes were sequenced using the Illumina high-throughput sequencing platform, yielding 52 gigabases of data, which were pooled and assembled into a reference transcriptome. Four hundred and eighty two genes were found to be highly expressed in the rhizomes, and these genes are mainly involved in stress response and transcriptional regulation. Based on their expression patterns, 36 genes were selected for further investigation as candidate genes involved in dioscin biosynthesis. Constructing co-expression networks based on significant changes in gene expression revealed 15 gene modules. Of these, four modules with properties correlating to dioscin regulation and biosynthesis, consisting of 4,665 genes in total, were selected for further functional investigation. These results improve our understanding of dioscin biosynthesis in this important medicinal plant and will help guide more intensive investigations.

Expression patterns of the aquaporin gene family during renal development: influence of genetic variability.

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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.

Gene expression profiling in cervical cancer: identification of novel markers for disease diagnosis and therapy.

LENUS (Irish Health Repository)

Martin, Cara M

2012-02-01

Cervical cancer, a potentially preventable disease, remains the second most common malignancy in women worldwide. Human papillomavirus is the single most important etiological agent in cervical cancer. HPV contributes to neoplastic progression through the action of two viral oncoproteins E6 and E7, which interfere with critical cell cycle pathways, p53, and retinoblastoma. However, evidence suggests that HPV infection alone is insufficient to induce malignant changes and other host genetic variations are important in the development of cervical cancer. Advances in molecular biology and high throughput gene expression profiling technologies have heralded a new era in biomarker discovery and identification of molecular targets related to carcinogenesis. These advancements have improved our understanding of carcinogenesis and will facilitate screening, early detection, management, and personalised targeted therapy. In this chapter, we have described the use of high density microarrays to assess gene expression profiles in cervical cancer. Using this approach we have identified a number of novel genes which are differentially expressed in cervical cancer, including several genes involved in cell cycle regulation. These include p16ink4a, MCM 3 and 5, CDC6, Geminin, Cyclins A-D, TOPO2A, CDCA1, and BIRC5. We have validated expression of mRNA using real-time PCR and protein by immunohistochemistry.

ESPRIT: A Method for Defining Soluble Expression Constructs in Poorly Understood Gene Sequences.

Science.gov (United States)

Mas, Philippe J; Hart, Darren J

2017-01-01

Production of soluble, purifiable domains or multi-domain fragments of proteins is a prerequisite for structural biology and other applications. When target sequences are poorly annotated, or when there are few similar sequences available for alignments, identification of domains can be problematic. A method called expression of soluble proteins by random incremental truncation (ESPRIT) addresses this problem by high-throughput automated screening of tens of thousands of enzymatically truncated gene fragments. Rare soluble constructs are identified by experimental screening, and the boundaries revealed by DNA sequencing.

FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data

DEFF Research Database (Denmark)

Manijak, Mieszko P.; Nielsen, Henrik Bjørn

2011-01-01

circumvented by instead matching gene expression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700...... Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/....

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

Science.gov (United States)

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.

Digital gene expression analysis of gene expression differences within Brassica diploids and allopolyploids.

Science.gov (United States)

Jiang, Jinjin; Wang, Yue; Zhu, Bao; Fang, Tingting; Fang, Yujie; Wang, Youping

2015-01-27

Brassica includes many successfully cultivated crop species of polyploid origin, either by ancestral genome triplication or by hybridization between two diploid progenitors, displaying complex repetitive sequences and transposons. The U's triangle, which consists of three diploids and three amphidiploids, is optimal for the analysis of complicated genomes after polyploidization. Next-generation sequencing enables the transcriptome profiling of polyploids on a global scale. We examined the gene expression patterns of three diploids (Brassica rapa, B. nigra, and B. oleracea) and three amphidiploids (B. napus, B. juncea, and B. carinata) via digital gene expression analysis. In total, the libraries generated between 5.7 and 6.1 million raw reads, and the clean tags of each library were mapped to 18547-21995 genes of B. rapa genome. The unambiguous tag-mapped genes in the libraries were compared. Moreover, the majority of differentially expressed genes (DEGs) were explored among diploids as well as between diploids and amphidiploids. Gene ontological analysis was performed to functionally categorize these DEGs into different classes. The Kyoto Encyclopedia of Genes and Genomes analysis was performed to assign these DEGs into approximately 120 pathways, among which the metabolic pathway, biosynthesis of secondary metabolites, and peroxisomal pathway were enriched. The non-additive genes in Brassica amphidiploids were analyzed, and the results indicated that orthologous genes in polyploids are frequently expressed in a non-additive pattern. Methyltransferase genes showed differential expression pattern in Brassica species. Our results provided an understanding of the transcriptome complexity of natural Brassica species. The gene expression changes in diploids and allopolyploids may help elucidate the morphological and physiological differences among Brassica species.

Identification of imprinted genes subject to parent-of-origin specific expression in Arabidopsis thaliana seeds

LENUS (Irish Health Repository)

McKeown, Peter C

2011-08-12

Abstract Background Epigenetic regulation of gene dosage by genomic imprinting of some autosomal genes facilitates normal reproductive development in both mammals and flowering plants. While many imprinted genes have been identified and intensively studied in mammals, smaller numbers have been characterized in flowering plants, mostly in Arabidopsis thaliana. Identification of additional imprinted loci in flowering plants by genome-wide screening for parent-of-origin specific uniparental expression in seed tissues will facilitate our understanding of the origins and functions of imprinted genes in flowering plants. Results cDNA-AFLP can detect allele-specific expression that is parent-of-origin dependent for expressed genes in which restriction site polymorphisms exist in the transcripts derived from each allele. Using a genome-wide cDNA-AFLP screen surveying allele-specific expression of 4500 transcript-derived fragments, we report the identification of 52 maternally expressed genes (MEGs) displaying parent-of-origin dependent expression patterns in Arabidopsis siliques containing F1 hybrid seeds (3, 4 and 5 days after pollination). We identified these MEGs by developing a bioinformatics tool (GenFrag) which can directly determine the identities of transcript-derived fragments from (i) their size and (ii) which selective nucleotides were added to the primers used to generate them. Hence, GenFrag facilitates increased throughput for genome-wide cDNA-AFLP fragment analyses. The 52 MEGs we identified were further filtered for high expression levels in the endosperm relative to the seed coat to identify the candidate genes most likely representing novel imprinted genes expressed in the endosperm of Arabidopsis thaliana. Expression in seed tissues of the three top-ranked candidate genes, ATCDC48, PDE120 and MS5-like, was confirmed by Laser-Capture Microdissection and qRT-PCR analysis. Maternal-specific expression of these genes in Arabidopsis thaliana F1 seeds was

Identification of imprinted genes subject to parent-of-origin specific expression in Arabidopsis thaliana seeds

Directory of Open Access Journals (Sweden)

Wennblom Trevor J

2011-08-01

Full Text Available Abstract Background Epigenetic regulation of gene dosage by genomic imprinting of some autosomal genes facilitates normal reproductive development in both mammals and flowering plants. While many imprinted genes have been identified and intensively studied in mammals, smaller numbers have been characterized in flowering plants, mostly in Arabidopsis thaliana. Identification of additional imprinted loci in flowering plants by genome-wide screening for parent-of-origin specific uniparental expression in seed tissues will facilitate our understanding of the origins and functions of imprinted genes in flowering plants. Results cDNA-AFLP can detect allele-specific expression that is parent-of-origin dependent for expressed genes in which restriction site polymorphisms exist in the transcripts derived from each allele. Using a genome-wide cDNA-AFLP screen surveying allele-specific expression of 4500 transcript-derived fragments, we report the identification of 52 maternally expressed genes (MEGs displaying parent-of-origin dependent expression patterns in Arabidopsis siliques containing F1 hybrid seeds (3, 4 and 5 days after pollination. We identified these MEGs by developing a bioinformatics tool (GenFrag which can directly determine the identities of transcript-derived fragments from (i their size and (ii which selective nucleotides were added to the primers used to generate them. Hence, GenFrag facilitates increased throughput for genome-wide cDNA-AFLP fragment analyses. The 52 MEGs we identified were further filtered for high expression levels in the endosperm relative to the seed coat to identify the candidate genes most likely representing novel imprinted genes expressed in the endosperm of Arabidopsis thaliana. Expression in seed tissues of the three top-ranked candidate genes, ATCDC48, PDE120 and MS5-like, was confirmed by Laser-Capture Microdissection and qRT-PCR analysis. Maternal-specific expression of these genes in Arabidopsis thaliana F1

Real-Time Gene Expression Profiling of Live Shewanella Oneidensis Cells

Energy Technology Data Exchange (ETDEWEB)

Xiaoliang Sunney Xie

2009-03-30

The overall objective of this proposal is to make real-time observations of gene expression in live Shewanella oneidensis cells with high sensitivity and high throughput. Gene expression, a central process to all life, is stochastic because most genes often exist in one or two copies per cell. Although the central dogma of molecular biology has been proven beyond doubt, due to insufficient sensitivity, stochastic protein production has not been visualized in real time in an individual cell at the single-molecule level. We report the first direct observation of single protein molecules as they are generated, one at a time in a single live E. coli cell, yielding quantitative information about gene expression [Science 2006; 311: 1600-1603]. We demonstrated a general strategy for live-cell single-molecule measurements: detection by localization. It is difficult to detect single fluorescence protein molecules inside cytoplasm - their fluorescence is spread by fast diffusion to the entire cell and overwhelmed by the strong autofluorescence. We achieved single-molecule sensitivity by immobilizing the fluorescence protein on the cell membrane, where the diffusion is much slowed. We learned that under the repressed condition protein molecules are produced in bursts, with each burst originating from a stochastically-transcribed single messenger RNA molecule, and that protein copy numbers in the bursts follow a geometric distribution. We also simultaneously published a paper reporting a different method using β-glactosidase as a reporter [Nature 440, 358 (2006)]. Many important proteins are expressed at low levels, inaccessible by previous proteomic techniques. Both papers allowed quantification of protein expression with unprecedented sensitivity and received overwhelming acclaim from the scientific community. The Nature paper has been identified as one of the most-cited papers in the past year [http://esi-topics.com/]. We have also an analytical framework describing the

Potential translational targets revealed by linking mouse grooming behavioral phenotypes to gene expression using public databases.

Science.gov (United States)

Roth, Andrew; Kyzar, Evan J; Cachat, Jonathan; Stewart, Adam Michael; Green, Jeremy; Gaikwad, Siddharth; O'Leary, Timothy P; Tabakoff, Boris; Brown, Richard E; Kalueff, Allan V

2013-01-10

Rodent self-grooming is an important, evolutionarily conserved behavior, highly sensitive to pharmacological and genetic manipulations. Mice with aberrant grooming phenotypes are currently used to model various human disorders. Therefore, it is critical to understand the biology of grooming behavior, and to assess its translational validity to humans. The present in-silico study used publicly available gene expression and behavioral data obtained from several inbred mouse strains in the open-field, light-dark box, elevated plus- and elevated zero-maze tests. As grooming duration differed between strains, our analysis revealed several candidate genes with significant correlations between gene expression in the brain and grooming duration. The Allen Brain Atlas, STRING, GoMiner and Mouse Genome Informatics databases were used to functionally map and analyze these candidate mouse genes against their human orthologs, assessing the strain ranking of their expression and the regional distribution of expression in the mouse brain. This allowed us to identify an interconnected network of candidate genes (which have expression levels that correlate with grooming behavior), display altered patterns of expression in key brain areas related to grooming, and underlie important functions in the brain. Collectively, our results demonstrate the utility of large-scale, high-throughput data-mining and in-silico modeling for linking genomic and behavioral data, as well as their potential to identify novel neural targets for complex neurobehavioral phenotypes, including grooming. Copyright © 2012 Elsevier Inc. All rights reserved.

High throughput generated micro-aggregates of chondrocytes stimulate cartilage formation in vitro and in vivo

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LS Moreira Teixeira

2012-06-01

Full Text Available Cell-based cartilage repair strategies such as matrix-induced autologous chondrocyte implantation (MACI could be improved by enhancing cell performance. We hypothesised that micro-aggregates of chondrocytes generated in high-throughput prior to implantation in a defect could stimulate cartilaginous matrix deposition and remodelling. To address this issue, we designed a micro-mould to enable controlled high-throughput formation of micro-aggregates. Morphology, stability, gene expression profiles and chondrogenic potential of micro-aggregates of human and bovine chondrocytes were evaluated and compared to single-cells cultured in micro-wells and in 3D after encapsulation in Dextran-Tyramine (Dex-TA hydrogels in vitro and in vivo. We successfully formed micro-aggregates of human and bovine chondrocytes with highly controlled size, stability and viability within 24 hours. Micro-aggregates of 100 cells presented a superior balance in Collagen type I and Collagen type II gene expression over single cells and micro-aggregates of 50 and 200 cells. Matrix metalloproteinases 1, 9 and 13 mRNA levels were decreased in micro-aggregates compared to single-cells. Histological and biochemical analysis demonstrated enhanced matrix deposition in constructs seeded with micro-aggregates cultured in vitro and in vivo, compared to single-cell seeded constructs. Whole genome microarray analysis and single gene expression profiles using human chondrocytes confirmed increased expression of cartilage-related genes when chondrocytes were cultured in micro-aggregates. In conclusion, we succeeded in controlled high-throughput formation of micro-aggregates of chondrocytes. Compared to single cell-seeded constructs, seeding of constructs with micro-aggregates greatly improved neo-cartilage formation. Therefore, micro-aggregation prior to chondrocyte implantation in current MACI procedures, may effectively accelerate hyaline cartilage formation.

High throughput generated micro-aggregates of chondrocytes stimulate cartilage formation in vitro and in vivo.

Science.gov (United States)

Moreira Teixeira, L S; Leijten, J C H; Sobral, J; Jin, R; van Apeldoorn, A A; Feijen, J; van Blitterswijk, C; Dijkstra, P J; Karperien, M

2012-06-05

Cell-based cartilage repair strategies such as matrix-induced autologous chondrocyte implantation (MACI) could be improved by enhancing cell performance. We hypothesised that micro-aggregates of chondrocytes generated in high-throughput prior to implantation in a defect could stimulate cartilaginous matrix deposition and remodelling. To address this issue, we designed a micro-mould to enable controlled high-throughput formation of micro-aggregates. Morphology, stability, gene expression profiles and chondrogenic potential of micro-aggregates of human and bovine chondrocytes were evaluated and compared to single-cells cultured in micro-wells and in 3D after encapsulation in Dextran-Tyramine (Dex-TA) hydrogels in vitro and in vivo. We successfully formed micro-aggregates of human and bovine chondrocytes with highly controlled size, stability and viability within 24 hours. Micro-aggregates of 100 cells presented a superior balance in Collagen type I and Collagen type II gene expression over single cells and micro-aggregates of 50 and 200 cells. Matrix metalloproteinases 1, 9 and 13 mRNA levels were decreased in micro-aggregates compared to single-cells. Histological and biochemical analysis demonstrated enhanced matrix deposition in constructs seeded with micro-aggregates cultured in vitro and in vivo, compared to single-cell seeded constructs. Whole genome microarray analysis and single gene expression profiles using human chondrocytes confirmed increased expression of cartilage-related genes when chondrocytes were cultured in micro-aggregates. In conclusion, we succeeded in controlled high-throughput formation of micro-aggregates of chondrocytes. Compared to single cell-seeded constructs, seeding of constructs with micro-aggregates greatly improved neo-cartilage formation. Therefore, micro-aggregation prior to chondrocyte implantation in current MACI procedures, may effectively accelerate hyaline cartilage formation.

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

International Nuclear Information System (INIS)

Gur-Dedeoglu, Bala; Konu, Ozlen; Kir, Serkan; Ozturk, Ahmet Rasit; Bozkurt, Betul; Ergul, Gulusan; Yulug, Isik G

2008-01-01

Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results. The

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

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Ergul Gulusan

2008-12-01

Full Text Available Abstract Background Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. Methods A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC, and invasive lobular carcinoma (ILC samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. Results The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively. The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real

Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

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Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

2014-05-01

Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Using interpolation to estimate system uncertainty in gene expression experiments.

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Lee J Falin

Full Text Available The widespread use of high-throughput experimental assays designed to measure the entire complement of a cell's genes or gene products has led to vast stores of data that are extremely plentiful in terms of the number of items they can measure in a single sample, yet often sparse in the number of samples per experiment due to their high cost. This often leads to datasets where the number of treatment levels or time points sampled is limited, or where there are very small numbers of technical and/or biological replicates. Here we introduce a novel algorithm to quantify the uncertainty in the unmeasured intervals between biological measurements taken across a set of quantitative treatments. The algorithm provides a probabilistic distribution of possible gene expression values within unmeasured intervals, based on a plausible biological constraint. We show how quantification of this uncertainty can be used to guide researchers in further data collection by identifying which samples would likely add the most information to the system under study. Although the context for developing the algorithm was gene expression measurements taken over a time series, the approach can be readily applied to any set of quantitative systems biology measurements taken following quantitative (i.e. non-categorical treatments. In principle, the method could also be applied to combinations of treatments, in which case it could greatly simplify the task of exploring the large combinatorial space of future possible measurements.

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

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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.

Gene expression profiling of human breast tissue samples using SAGE-Seq.

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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.

Differential Expression and Functional Analysis of High-Throughput -Omics Data Using Open Source Tools.

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Kebschull, Moritz; Fittler, Melanie Julia; Demmer, Ryan T; Papapanou, Panos N

2017-01-01

Today, -omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ, or tissue sample, allow for an unbiased, comprehensive genome-level analysis of complex diseases, offering a large advantage over earlier "candidate" gene or pathway analyses. A primary goal in the analysis of these high-throughput assays is the detection of those features among several thousand that differ between different groups of samples. In the context of oral biology, our group has successfully utilized -omics technology to identify key molecules and pathways in different diagnostic entities of periodontal disease.A major issue when inferring biological information from high-throughput -omics studies is the fact that the sheer volume of high-dimensional data generated by contemporary technology is not appropriately analyzed using common statistical methods employed in the biomedical sciences.In this chapter, we outline a robust and well-accepted bioinformatics workflow for the initial analysis of -omics data generated using microarrays or next-generation sequencing technology using open-source tools. Starting with quality control measures and necessary preprocessing steps for data originating from different -omics technologies, we next outline a differential expression analysis pipeline that can be used for data from both microarray and sequencing experiments, and offers the possibility to account for random or fixed effects. Finally, we present an overview of the possibilities for a functional analysis of the obtained data.

Risk stratification in myelodysplastic syndromes: is there a role for gene expression profiling?

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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.

Large scale gene expression meta-analysis reveals tissue-specific, sex-biased gene expression in humans

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Benjamin Mayne

2016-10-01

Full Text Available The severity and prevalence of many diseases are known to differ between the sexes. Organ specific sex-biased gene expression may underpin these and other sexually dimorphic traits. To further our understanding of sex differences in transcriptional regulation, we performed meta-analyses of sex biased gene expression in multiple human tissues. We analysed 22 publicly available human gene expression microarray data sets including over 2500 samples from 15 different tissues and 9 different organs. Briefly, by using an inverse-variance method we determined the effect size difference of gene expression between males and females. We found the greatest sex differences in gene expression in the brain, specifically in the anterior cingulate cortex, (1818 genes, followed by the heart (375 genes, kidney (224 genes, colon (218 genes and thyroid (163 genes. More interestingly, we found different parts of the brain with varying numbers and identity of sex-biased genes, indicating that specific cortical regions may influence sexually dimorphic traits. The majority of sex-biased genes in other tissues such as the bladder, liver, lungs and pancreas were on the sex chromosomes or involved in sex hormone production. On average in each tissue, 32% of autosomal genes that were expressed in a sex-biased fashion contained androgen or estrogen hormone response elements. Interestingly, across all tissues, we found approximately two-thirds of autosomal genes that were sex-biased were not under direct influence of sex hormones. To our knowledge this is the largest analysis of sex-biased gene expression in human tissues to date. We identified many sex-biased genes that were not under the direct influence of sex chromosome genes or sex hormones. These may provide targets for future development of sex-specific treatments for diseases.

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

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Microarray profiling of chemical-induced effects is being increasingly used in medium and high-throughput formats. In this study, we describe computational methods to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), ...

Reconstructing Generalized Logical Networks of Transcriptional Regulation in Mouse Brain from Temporal Gene Expression Data

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Song, Mingzhou (Joe) [New Mexico State University, Las Cruces; Lewis, Chris K. [New Mexico State University, Las Cruces; Lance, Eric [New Mexico State University, Las Cruces; Chesler, Elissa J [ORNL; Kirova, Roumyana [Bristol-Myers Squibb Pharmaceutical Research & Development, NJ; Langston, Michael A [University of Tennessee, Knoxville (UTK); Bergeson, Susan [Texas Tech University, Lubbock

2009-01-01

The problem of reconstructing generalized logical networks to account for temporal dependencies among genes and environmental stimuli from high-throughput transcriptomic data is addressed. A network reconstruction algorithm was developed that uses the statistical significance as a criterion for network selection to avoid false-positive interactions arising from pure chance. Using temporal gene expression data collected from the brains of alcohol-treated mice in an analysis of the molecular response to alcohol, this algorithm identified genes from a major neuronal pathway as putative components of the alcohol response mechanism. Three of these genes have known associations with alcohol in the literature. Several other potentially relevant genes, highlighted and agreeing with independent results from literature mining, may play a role in the response to alcohol. Additional, previously-unknown gene interactions were discovered that, subject to biological verification, may offer new clues in the search for the elusive molecular mechanisms of alcoholism.

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

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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.

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

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Pingping Wang

2016-08-01

Full Text Available 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.

Radioactive cDNA microarray (II): Gene expression profiling of antidepressant treatment by human cDNA microarray

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Lee, Ji Hye; Kang, Rhee Hun; Ham, Byung Joo; Lee, Min Su; Shin, Kyung Ho; Choe, Jae Gol; Kim, Meyoung Kon [College of Medicine, Univ. of Korea, Seoul (Korea, Republic of)

2003-07-01

Major depressive disorder is a prevalent psychiatric disorder in primary care, associated with impaired patient functioning and well-being. Fluoxetine is a selective serotonin-reuptake inhibitors (SSRIs) and is a commonly prescribed antidepressant compound. Its action is primarily attributed to selective inhibition of the reuptake of serotonin (5-hydroxytryptamine) in the central nervous system. Objectives ; the aims of this study were two-fold: (1) to determine the usefulness for investigation of the transcription profiles in depression patients, and (2) to assess the differences in gene expression profiles between positive response group and negative response groups by fluoxetine treatment. This study included 53 patients with major depression (26 in positive response group with antidepressant treatment, 27 in negative response group with antidepressant treatment), and 53 healthy controls. To examine the difference of gene expression profile in depression patients, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 genes in total. Using 33p-labeled probes, this method provided highly sensitive gene expression profiles including brain receptors, drug metabolism, and cellular signaling. Gene transcription profiles were classified into several categories in accordance with the antidepressant gene-regulation. The gene profiles were significantly up-(22 genes) and down-(16 genes) regulated in the positive response group when compared to the control group. Also, in the negative response group, 35 genes were up-regulated and 8 genes were down-regulated when compared to the control group. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology.

Radioactive cDNA microarray (II): Gene expression profiling of antidepressant treatment by human cDNA microarray

International Nuclear Information System (INIS)

Lee, Ji Hye; Kang, Rhee Hun; Ham, Byung Joo; Lee, Min Su; Shin, Kyung Ho; Choe, Jae Gol; Kim, Meyoung Kon

2003-01-01

Major depressive disorder is a prevalent psychiatric disorder in primary care, associated with impaired patient functioning and well-being. Fluoxetine is a selective serotonin-reuptake inhibitors (SSRIs) and is a commonly prescribed antidepressant compound. Its action is primarily attributed to selective inhibition of the reuptake of serotonin (5-hydroxytryptamine) in the central nervous system. Objectives ; the aims of this study were two-fold: (1) to determine the usefulness for investigation of the transcription profiles in depression patients, and (2) to assess the differences in gene expression profiles between positive response group and negative response groups by fluoxetine treatment. This study included 53 patients with major depression (26 in positive response group with antidepressant treatment, 27 in negative response group with antidepressant treatment), and 53 healthy controls. To examine the difference of gene expression profile in depression patients, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 genes in total. Using 33p-labeled probes, this method provided highly sensitive gene expression profiles including brain receptors, drug metabolism, and cellular signaling. Gene transcription profiles were classified into several categories in accordance with the antidepressant gene-regulation. The gene profiles were significantly up-(22 genes) and down-(16 genes) regulated in the positive response group when compared to the control group. Also, in the negative response group, 35 genes were up-regulated and 8 genes were down-regulated when compared to the control group. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology

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

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Guangbo Liu

Full Text Available 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.

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

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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.

Differential Gene Expression and Aging

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Laurent Seroude

2002-01-01

Full Text Available It has been established that an intricate program of gene expression controls progression through the different stages in development. The equally complex biological phenomenon known as aging is genetically determined and environmentally modulated. This review focuses on the genetic component of aging, with a special emphasis on differential gene expression. At least two genetic pathways regulating organism longevity act by modifying gene expression. Many genes are also subjected to age-dependent transcriptional regulation. Some age-related gene expression changes are prevented by caloric restriction, the most robust intervention that slows down the aging process. Manipulating the expression of some age-regulated genes can extend an organism's life span. Remarkably, the activity of many transcription regulatory elements is linked to physiological age as opposed to chronological age, indicating that orderly and tightly controlled regulatory pathways are active during aging.

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

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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.

Polycistronic gene expression in Aspergillus niger.

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Schuetze, Tabea; Meyer, Vera

2017-09-25

Genome mining approaches predict dozens of biosynthetic gene clusters in each of the filamentous fungal genomes sequenced so far. However, the majority of these gene clusters still remain cryptic because they are not expressed in their natural host. Simultaneous expression of all genes belonging to a biosynthetic pathway in a heterologous host is one approach to activate biosynthetic gene clusters and to screen the metabolites produced for bioactivities. Polycistronic expression of all pathway genes under control of a single and tunable promoter would be the method of choice, as this does not only simplify cloning procedures, but also offers control on timing and strength of expression. However, polycistronic gene expression is a feature not commonly found in eukaryotic host systems, such as Aspergillus niger. In this study, we tested the suitability of the viral P2A peptide for co-expression of three genes in A. niger. Two genes descend from Fusarium oxysporum and are essential to produce the secondary metabolite enniatin (esyn1, ekivR). The third gene (luc) encodes the reporter luciferase which was included to study position effects. Expression of the polycistronic gene cassette was put under control of the Tet-On system to ensure tunable gene expression in A. niger. In total, three polycistronic expression cassettes which differed in the position of luc were constructed and targeted to the pyrG locus in A. niger. This allowed direct comparison of the luciferase activity based on the position of the luciferase gene. Doxycycline-mediated induction of the Tet-On expression cassettes resulted in the production of one long polycistronic mRNA as proven by Northern analyses, and ensured comparable production of enniatin in all three strains. Notably, gene position within the polycistronic expression cassette matters, as, luciferase activity was lowest at position one and had a comparable activity at positions two and three. The P2A peptide can be used to express at

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

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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.

GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.

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Kwon, Minseok; Leem, Sangseob; Yoon, Joon; Park, Taesung

2018-03-19

With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X.

A hemocyte gene expression signature correlated with predictive capacity of oysters to survive Vibrio infections

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Rosa Rafael

2012-06-01

Full Text Available Abstract Background The complex balance between environmental and host factors is an important determinant of susceptibility to infection. Disturbances of this equilibrium may result in multifactorial diseases as illustrated by the summer mortality syndrome, a worldwide and complex phenomenon that affects the oysters, Crassostrea gigas. The summer mortality syndrome reveals a physiological intolerance making this oyster species susceptible to diseases. Exploration of genetic basis governing the oyster resistance or susceptibility to infections is thus a major goal for understanding field mortality events. In this context, we used high-throughput genomic approaches to identify genetic traits that may characterize inherent survival capacities in C. gigas. Results Using digital gene expression (DGE, we analyzed the transcriptomes of hemocytes (immunocompetent cells of oysters able or not able to survive infections by Vibrio species shown to be involved in summer mortalities. Hemocytes were nonlethally collected from oysters before Vibrio experimental infection, and two DGE libraries were generated from individuals that survived or did not survive. Exploration of DGE data and microfluidic qPCR analyses at individual level showed an extraordinary polymorphism in gene expressions, but also a set of hemocyte-expressed genes whose basal mRNA levels discriminate oyster capacity to survive infections by the pathogenic V. splendidus LGP32. Finally, we identified a signature of 14 genes that predicted oyster survival capacity. Their expressions are likely driven by distinct transcriptional regulation processes associated or not associated to gene copy number variation (CNV. Conclusions We provide here for the first time in oyster a gene expression survival signature that represents a useful tool for understanding mortality events and for assessing genetic traits of interest for disease resistance selection programs.

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

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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.

Characteristic Changes in Decidual Gene Expression Signature in Spontaneous Term Parturition

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Haidy El-Azzamy

2017-05-01

Full Text Available Background The decidua has been implicated in the “terminal pathway” of human term parturition, which is characterized by the activation of pro-inflammatory pathways in gestational tissues. However, the transcriptomic changes in the decidua leading to terminal pathway activation have not been systematically explored. This study aimed to compare the decidual expression of developmental signaling and inflammation-related genes before and after spontaneous term labor in order to reveal their involvement in this process. Methods Chorioamniotic membranes were obtained from normal pregnant women who delivered at term with spontaneous labor (TIL, n = 14 or without labor (TNL, n = 15. Decidual cells were isolated from snap-frozen chorioamniotic membranes with laser microdissection. The expression of 46 genes involved in decidual development, sex steroid and prostaglandin signaling, as well as pro- and anti-inflammatory pathways, was analyzed using high-throughput quantitative real-time polymerase chain reaction (qRT-PCR. Chorioamniotic membrane sections were immunostained and then semi-quantified for five proteins, and immunoassays for three chemokines were performed on maternal plasma samples. Results The genes with the highest expression in the decidua at term gestation included insulin-like growth factor-binding protein 1 (IGFBP1, galectin-1 (LGALS1, and progestogen-associated endometrial protein (PAEP; the expression of estrogen receptor 1 (ESR1, homeobox A11 (HOXA11, interleukin 1β (IL1B, IL8, progesterone receptor membrane component 2 (PGRMC2, and prostaglandin E synthase (PTGES was higher in TIL than in TNL cases; the expression of chemokine C-C motif ligand 2 (CCL2, CCL5, LGALS1, LGALS3, and PAEP was lower in TIL than in TNL cases; immunostaining confirmed qRT-PCR data for IL-8, CCL2, galectin-1, galectin-3, and PAEP; and no correlations between the decidual gene expression and the maternal plasma protein concentrations of CCL2, CCL5, and

Gene expression inference with deep learning.

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Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

2016-06-15

Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.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.

Homologous high-throughput expression and purification of highly conserved E coli proteins

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Duchmann Rainer

2007-06-01

Full Text Available Abstract Background Genetic factors and a dysregulated immune response towards commensal bacteria contribute to the pathogenesis of Inflammatory Bowel Disease (IBD. Animal models demonstrated that the normal intestinal flora is crucial for the development of intestinal inflammation. However, due to the complexity of the intestinal flora, it has been difficult to design experiments for detection of proinflammatory bacterial antigen(s involved in the pathogenesis of the disease. Several studies indicated a potential association of E. coli with IBD. In addition, T cell clones of IBD patients were shown to cross react towards antigens from different enteric bacterial species and thus likely responded to conserved bacterial antigens. We therefore chose highly conserved E. coli proteins as candidate antigens for abnormal T cell responses in IBD and used high-throughput techniques for cloning, expression and purification under native conditions of a set of 271 conserved E. coli proteins for downstream immunologic studies. Results As a standardized procedure, genes were PCR amplified and cloned into the expression vector pQTEV2 in order to express proteins N-terminally fused to a seven-histidine-tag. Initial small-scale expression and purification under native conditions by metal chelate affinity chromatography indicated that the vast majority of target proteins were purified in high yields. Targets that revealed low yields after purification probably due to weak solubility were shuttled into Gateway (Invitrogen destination vectors in order to enhance solubility by N-terminal fusion of maltose binding protein (MBP, N-utilizing substance A (NusA, or glutathione S-transferase (GST to the target protein. In addition, recombinant proteins were treated with polymyxin B coated magnetic beads in order to remove lipopolysaccharide (LPS. Thus, 73% of the targeted proteins could be expressed and purified in large-scale to give soluble proteins in the range of 500

Establishment of IL-7 Expression Reporter Human Cell Lines, and Their Feasibility for High-Throughput Screening of IL-7-Upregulating Chemicals.

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Yeon Sook Cho

Full Text Available Interleukin-7 (IL-7 is a cytokine essential for T cell homeostasis, and is clinically important. However, the regulatory mechanism of IL-7 gene expression is not well known, and a systematic approach to screen chemicals that regulate IL-7 expression has not yet been developed. In this study, we attempted to develop human reporter cell lines using CRISPR/Cas9-mediated genome editing technology. For this purpose, we designed donor DNA that contains an enhanced green fluorescent protein (eGFP gene, drug selection cassette, and modified homologous arms which are considered to enhance the translation of the eGFP reporter transcript, and also a highly efficient single-guide RNA with a minimal off-target effect to target the IL-7 start codon region. By applying this system, we established IL-7 eGFP reporter cell lines that could report IL-7 gene transcription based on the eGFP protein signal. Furthermore, we utilized the cells to run a pilot screen campaign for IL-7-upregulating chemicals in a high-throughput format, and identified a chemical that can up-regulate IL-7 gene transcription. Collectively, these results suggest that our IL-7 reporter system can be utilized in large-scale chemical library screening to reveal novel IL-7 regulatory pathways and to identify potential drugs for development of new treatments in immunodeficiency disease.

Gene expression program of regeneration in Eisenia fetida: a transcriptomics study

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Aksheev Bhambri

2017-10-01

Full Text Available Annelids form a connecting link between segmented and non-segmented organisms.  In other words, phylogenetically, the segmented body pattern starts from Annelida, a phylum that consists of thousands of species, including marine worms, freshwater leeches and earthworms that inhabit deep layers of soil to environmental niches in forests and cultivated land. We are using Eisenia fetida (Indian isolate a top dwelling, vermicomposting worm due to its ability to regenerate its posterior after damage, injury or complete removal. On average, Eisenia fetida has 100-110 segments. We separated the anterior (upto 55-60th segment and posterior of the worm, and allowed it to regenerate.  In this model, only the posterior could be regenerated after injury.  We isolated RNA from the regenerated tissue and the immediate adjacent old tissue at 15 days, 20 days and 30 days during regeneration. We carried out transcriptome sequencing and analysis. With the aim of identifying specific factors which promote nerve regeneration, we have annotated the differentially expressed genes. In all organisms which possess a segmented body, the expression pattern of the Hox cluster is conserved. Hox gene expression, a conserved developmental phenomenon in establishment of body plan has been studied by comparative genomics of other annelids like the marine worm Capitella telleta, the leech Helobdella robusta.  We have used a combination of high-throughput sequencing based techniques and validation through cell and molecular biology to identify key aspects of the gene expression program of regeneration in this worm. Besides the transcriptome, we have also done whole genome sequencing, miRnome and metagenome sequencing of this terrestrial annelid.

Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia.

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Badea, Liviu; Herlea, Vlad; Dima, Simona Olimpia; Dumitrascu, Traian; Popescu, Irinel

2008-01-01

The precise details of pancreatic ductal adenocarcinoma (PDAC) pathogenesis are still insufficiently known, requiring the use of high-throughput methods. However, PDAC is especially difficult to study using microarrays due to its strong desmoplastic reaction, which involves a hyperproliferating stroma that effectively "masks" the contribution of the minoritary neoplastic epithelial cells. Thus it is not clear which of the genes that have been found differentially expressed between normal and whole tumor tissues are due to the tumor epithelia and which simply reflect the differences in cellular composition. To address this problem, laser microdissection studies have been performed, but these have to deal with much smaller tissue sample quantities and therefore have significantly higher experimental noise. In this paper we combine our own large sample whole-tissue study with a previously published smaller sample microdissection study by Grützmann et al. to identify the genes that are specifically overexpressed in PDAC tumor epithelia. The overlap of this list of genes with other microarray studies of pancreatic cancer as well as with the published literature is impressive. Moreover, we find a number of genes whose over-expression appears to be inversely correlated with patient survival: keratin 7, laminin gamma 2, stratifin, platelet phosphofructokinase, annexin A2, MAP4K4 and OACT2 (MBOAT2), which are all specifically upregulated in the neoplastic epithelia, rather than the tumor stroma. We improve on other microarray studies of PDAC by putting together the higher statistical power due to a larger number of samples with information about cell-type specific expression and patient survival.

Fine mapping of a Phytophthora-resistance gene RpsWY in soybean (Glycine max L.) by high-throughput genome-wide sequencing.

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Cheng, Yanbo; Ma, Qibin; Ren, Hailong; Xia, Qiuju; Song, Enliang; Tan, Zhiyuan; Li, Shuxian; Zhang, Gengyun; Nian, Hai

2017-05-01

Using a combination of phenotypic screening, genetic and statistical analyses, and high-throughput genome-wide sequencing, we have finely mapped a dominant Phytophthora resistance gene in soybean cultivar Wayao. Phytophthora root rot (PRR) caused by Phytophthora sojae is one of the most important soil-borne diseases in many soybean-production regions in the world. Identification of resistant gene(s) and incorporating them into elite varieties are an effective way for breeding to prevent soybean from being harmed by this disease. Two soybean populations of 191 F 2 individuals and 196 F 7:8 recombinant inbred lines (RILs) were developed to map Rps gene by crossing a susceptible cultivar Huachun 2 with the resistant cultivar Wayao. Genetic analysis of the F 2 population indicated that PRR resistance in Wayao was controlled by a single dominant gene, temporarily named RpsWY, which was mapped on chromosome 3. A high-density genetic linkage bin map was constructed using 3469 recombination bins of the RILs to explore the candidate genes by the high-throughput genome-wide sequencing. The results of genotypic analysis showed that the RpsWY gene was located in bin 401 between 4466230 and 4502773 bp on chromosome 3 through line 71 and 100 of the RILs. Four predicted genes (Glyma03g04350, Glyma03g04360, Glyma03g04370, and Glyma03g04380) were found at the narrowed region of 36.5 kb in bin 401. These results suggest that the high-throughput genome-wide resequencing is an effective method to fine map PRR candidate genes.

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

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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

New developments of RNAi in Paracoccidioides brasiliensis: prospects for high-throughput, genome-wide, functional genomics.

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Tercio Goes

2014-10-01

Full Text Available The Fungal Genome Initiative of the Broad Institute, in partnership with the Paracoccidioides research community, has recently sequenced the genome of representative isolates of this human-pathogen dimorphic fungus: Pb18 (S1, Pb03 (PS2 and Pb01. The accomplishment of future high-throughput, genome-wide, functional genomics will rely upon appropriate molecular tools and straightforward techniques to streamline the generation of stable loss-of-function phenotypes. In the past decades, RNAi has emerged as the most robust genetic technique to modulate or to suppress gene expression in diverse eukaryotes, including fungi. These molecular tools and techniques, adapted for RNAi, were up until now unavailable for P. brasiliensis.In this paper, we report Agrobacterium tumefaciens mediated transformation of yeast cells for high-throughput applications with which higher transformation frequencies of 150±24 yeast cell transformants per 1×106 viable yeast cells were obtained. Our approach is based on a bifunctional selective marker fusion protein consisted of the Streptoalloteichus hindustanus bleomycin-resistance gene (Shble and the intrinsically fluorescent monomeric protein mCherry which was codon-optimized for heterologous expression in P. brasiliensis. We also report successful GP43 gene knock-down through the expression of intron-containing hairpin RNA (ihpRNA from a Gateway-adapted cassette (cALf which was purpose-built for gene silencing in a high-throughput manner. Gp43 transcript levels were reduced by 73.1±22.9% with this approach.We have a firm conviction that the genetic transformation technique and the molecular tools herein described will have a relevant contribution in future Paracoccidioides spp. functional genomics research.

Scaling of gene expression data allowing the comparison of different gene expression platforms

NARCIS (Netherlands)

van Ruissen, Fred; Schaaf, Gerben J.; Kool, Marcel; Baas, Frank; Ruijter, Jan M.

2008-01-01

Serial analysis of gene expression (SAGE) and microarrays have found a widespread application, but much ambiguity exists regarding the amalgamation of the data resulting from these technologies. Cross-platform utilization of gene expression data from the SAGE and microarray technology could reduce

cis sequence effects on gene expression

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Jacobs Kevin

2007-08-01

Full Text Available Abstract Background Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and gene expression variation (genetical genomics provides insight into the role of linked sequence variation in the regulation of gene expression. We investigated the role of sequence variation in cis on gene expression (cis sequence effects in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. We estimated the proportion of genes exhibiting cis sequence effects and the proportion of gene expression variation explained by cis sequence effects using three different analytical approaches, and compared our results to the literature. Results We generated gene expression profiling data at N = 697 candidate genes from N = 30 lymphoblastoid cell lines for this study and used available candidate gene resequencing data at N = 552 candidate genes to identify N = 30 candidate genes with sufficient variance in both datasets for the investigation of cis sequence effects. We used two additive models and the haplotype phylogeny scanning approach of Templeton (Tree Scanning to evaluate association between individual SNPs, all SNPs at a gene, and diplotypes, with log-transformed gene expression. SNPs and diplotypes at eight candidate genes exhibited statistically significant (p cis sequence effects in our study, respectively. Conclusion Based on analysis of our results and the extant literature, one in four genes exhibits significant cis sequence effects, and for these genes, about 30% of gene expression variation is accounted for by cis sequence variation. Despite diverse experimental approaches, the presence or absence of significant cis sequence effects is largely supported by previously published studies.

Automated cleaning and pre-processing of immunoglobulin gene sequences from high-throughput sequencing

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Miri eMichaeli

2012-12-01

Full Text Available High throughput sequencing (HTS yields tens of thousands to millions of sequences that require a large amount of pre-processing work to clean various artifacts. Such cleaning cannot be performed manually. Existing programs are not suitable for immunoglobulin (Ig genes, which are variable and often highly mutated. This paper describes Ig-HTS-Cleaner (Ig High Throughput Sequencing Cleaner, a program containing a simple cleaning procedure that successfully deals with pre-processing of Ig sequences derived from HTS, and Ig-Indel-Identifier (Ig Insertion – Deletion Identifier, a program for identifying legitimate and artifact insertions and/or deletions (indels. Our programs were designed for analyzing Ig gene sequences obtained by 454 sequencing, but they are applicable to all types of sequences and sequencing platforms. Ig-HTS-Cleaner and Ig-Indel-Identifier have been implemented in Java and saved as executable JAR files, supported on Linux and MS Windows. No special requirements are needed in order to run the programs, except for correctly constructing the input files as explained in the text. The programs' performance has been tested and validated on real and simulated data sets.

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

OpenAIRE

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

2011-01-01

Abstract 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 p...

Global analysis of transcriptome responses and gene expression profiles to cold stress of Jatropha curcas L.

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Wang, Haibo; Zou, Zhurong; Wang, Shasha; Gong, Ming

2013-01-01

Jatropha curcas L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, J. curcas confers an inherent but undesirable characteristic (low cold resistance) that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE) are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in J. curcas. In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the J. curcas transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs) were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C) for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis. This study provides a global view of transcriptome response and gene expression profiling of J. curcas in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of crucial genes for genetically enhancing cold resistance

Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

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Paules Richard S

2007-11-01

Full Text Available Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

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Tholouli, Eleni [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); MacDermott, Sarah [The Medical School, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Hoyland, Judith [School of Biomedicine, Faculty of Medical and Human Sciences, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Yin, John Liu [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); Byers, Richard, E-mail: richard.byers@cmft.nhs.uk [School of Cancer and Enabling Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, M13 9PT Manchester (United Kingdom)

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

A robust approach to identifying tissue-specific gene expression regulatory variants using personalized human induced pluripotent stem cells.

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Je-Hyuk Lee

2009-11-01

Full Text Available Normal variation in gene expression due to regulatory polymorphisms is often masked by biological and experimental noise. In addition, some regulatory polymorphisms may become apparent only in specific tissues. We derived human induced pluripotent stem (iPS cells from adult skin primary fibroblasts and attempted to detect tissue-specific cis-regulatory variants using in vitro cell differentiation. We used padlock probes and high-throughput sequencing for digital RNA allelotyping and measured allele-specific gene expression in primary fibroblasts, lymphoblastoid cells, iPS cells, and their differentiated derivatives. We show that allele-specific expression is both cell type and genotype-dependent, but the majority of detectable allele-specific expression loci remains consistent despite large changes in the cell type or the experimental condition following iPS reprogramming, except on the X-chromosome. We show that our approach to mapping cis-regulatory variants reduces in vitro experimental noise and reveals additional tissue-specific variants using skin-derived human iPS cells.

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

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Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

Science.gov (United States)

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

Modulation of gene expression made easy

DEFF Research Database (Denmark)

Solem, Christian; Jensen, Peter Ruhdal

2002-01-01

A new approach for modulating gene expression, based on randomization of promoter (spacer) sequences, was developed. The method was applied to chromosomal genes in Lactococcus lactis and shown to generate libraries of clones with broad ranges of expression levels of target genes. In one example...... that the method can be applied to modulating the expression of native genes on the chromosome. We constructed a series of strains in which the expression of the las operon, containing the genes pfk, pyk, and ldh, was modulated by integrating a truncated copy of the pfk gene. Importantly, the modulation affected...

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

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

2012-07-15

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

Using gene expression noise to understand gene regulation

NARCIS (Netherlands)

Munsky, B.; Neuert, G.; van Oudenaarden, A.

2012-01-01

Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic gene expression, or gene expression "noise," has been suggested as a

The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations

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Parmigiani Giovanni

2009-08-01

Full Text Available Abstract Background A major challenge in computational biology is to extract knowledge about the genetic nature of disease from high-throughput data. However, an important obstacle to both biological understanding and clinical applications is the "black box" nature of the decision rules provided by most machine learning approaches, which usually involve many genes combined in a highly complex fashion. Achieving biologically relevant results argues for a different strategy. A promising alternative is to base prediction entirely upon the relative expression ordering of a small number of genes. Results We present a three-gene version of "relative expression analysis" (RXA, a rigorous and systematic comparison with earlier approaches in a variety of cancer studies, a clinically relevant application to predicting germline BRCA1 mutations in breast cancer and a cross-study validation for predicting ER status. In the BRCA1 study, RXA yields high accuracy with a simple decision rule: in tumors carrying mutations, the expression of a "reference gene" falls between the expression of two differentially expressed genes, PPP1CB and RNF14. An analysis of the protein-protein interactions among the triplet of genes and BRCA1 suggests that the classifier has a biological foundation. Conclusion RXA has the potential to identify genomic "marker interactions" with plausible biological interpretation and direct clinical applicability. It provides a general framework for understanding the roles of the genes involved in decision rules, as illustrated for the difficult and clinically relevant problem of identifying BRCA1 mutation carriers.

High-throughput expression of animal venom toxins in Escherichia coli to generate a large library of oxidized disulphide-reticulated peptides for drug discovery.

Science.gov (United States)

Turchetto, Jeremy; Sequeira, Ana Filipa; Ramond, Laurie; Peysson, Fanny; Brás, Joana L A; Saez, Natalie J; Duhoo, Yoan; Blémont, Marilyne; Guerreiro, Catarina I P D; Quinton, Loic; De Pauw, Edwin; Gilles, Nicolas; Darbon, Hervé; Fontes, Carlos M G A; Vincentelli, Renaud

2017-01-17

Animal venoms are complex molecular cocktails containing a wide range of biologically active disulphide-reticulated peptides that target, with high selectivity and efficacy, a variety of membrane receptors. Disulphide-reticulated peptides have evolved to display improved specificity, low immunogenicity and to show much higher resistance to degradation than linear peptides. These properties make venom peptides attractive candidates for drug development. However, recombinant expression of reticulated peptides containing disulphide bonds is challenging, especially when associated with the production of large libraries of bioactive molecules for drug screening. To date, as an alternative to artificial synthetic chemical libraries, no comprehensive recombinant libraries of natural venom peptides are accessible for high-throughput screening to identify novel therapeutics. In the accompanying paper an efficient system for the expression and purification of oxidized disulphide-reticulated venom peptides in Escherichia coli is described. Here we report the development of a high-throughput automated platform, that could be adapted to the production of other families, to generate the largest ever library of recombinant venom peptides. The peptides were produced in the periplasm of E. coli using redox-active DsbC as a fusion tag, thus allowing the efficient formation of correctly folded disulphide bridges. TEV protease was used to remove fusion tags and recover the animal venom peptides in the native state. Globally, within nine months, out of a total of 4992 synthetic genes encoding a representative diversity of venom peptides, a library containing 2736 recombinant disulphide-reticulated peptides was generated. The data revealed that the animal venom peptides produced in the bacterial host were natively folded and, thus, are putatively biologically active. Overall this study reveals that high-throughput expression of animal venom peptides in E. coli can generate large

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

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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

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

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Friedt Wolfgang

2009-07-01

Full Text Available Abstract 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.

Testing candidate genes for attention-deficit/hyperactivity disorder in fruit flies using a high throughput assay for complex behavior

DEFF Research Database (Denmark)

Rohde, Palle Duun; Madsen, Lisbeth Strøm; Arvidson, Sandra Marie Neumann

2016-01-01

Fruit flies are important model organisms for functional testing of candidate genes in multiple disciplines, including the study of human diseases. Here we use a high-throughput locomotor activity assay to test the response on activity behavior of gene disruption in Drosophila melanogaster. The aim...

Molecular Link between Leaf Coloration and Gene Expression of Flavonoid and Carotenoid Biosynthesis in Camellia sinensis Cultivar ‘Huangjinya’

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Lubin Song

2017-05-01

Full Text Available ‘Huangjinya’ is an excellent albino tea germplasm cultivated in China because of its bright color and high amino acid content. It is light sensitive, with yellow leaves under intense light while green leaves under weak light. As well, the flavonoid and carotenoid levels increased after moderate shading treatment. However, the mechanism underlying this interesting phenomenon remains unclear. In this study, the transcriptome of ‘Huangjinya’ plants exposed to sunlight and shade were analyzed by high-throughput sequencing followed by de novo assembly. Shading ‘Huangjinya’ made its leaf color turn green. De novo assembly showed that the transcriptome of ‘Huangjinya’ leaves comprises of 127,253 unigenes, with an average length of 914 nt. Among the 81,128 functionally annotated unigenes, 207 differentially expressed genes were identified, including 110 up-regulated and 97 down-regulated genes under moderate shading compared to full light. Gene ontology (GO indicated that the differentially expressed genes are mainly involved in protein and ion binding and oxidoreductase activity. Antioxidation-related pathways, including flavonoid and carotenoid biosynthesis, were highly enriched in these functions. Shading inhibited the expression of flavonoid biosynthesis-associated genes and induced carotenoid biosynthesis-related genes. This would suggest that decreased flavonoid biosynthetic gene expression coincides with increased flavonoids (e.g., catechin content upon moderate shading, while carotenoid levels and biosynthetic gene expression are positively correlated in ‘Huangjinya.’ In conclusion, the leaf color changes in ‘Huangjinya’ are largely determined by the combined effects of flavonoid and carotenoid biosynthesis.

Functional analysis of human hematopoietic stem cell gene expression using zebrafish.

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2005-08-01

Full Text Available Although several reports have characterized the hematopoietic stem cell (HSC transcriptome, the roles of HSC-specific genes in hematopoiesis remain elusive. To identify candidate regulators of HSC fate decisions, we compared the transcriptome of human umbilical cord blood and bone marrow (CD34+(CD33-(CD38-Rho(lo(c-kit+ cells, enriched for hematopoietic stem/progenitor cells with (CD34+(CD33-(CD38-Rho(hi cells, enriched in committed progenitors. We identified 277 differentially expressed transcripts conserved in these ontogenically distinct cell sources. We next performed a morpholino antisense oligonucleotide (MO-based functional screen in zebrafish to determine the hematopoietic function of 61 genes that had no previously known function in HSC biology and for which a likely zebrafish ortholog could be identified. MO knock down of 14/61 (23% of the differentially expressed transcripts resulted in hematopoietic defects in developing zebrafish embryos, as demonstrated by altered levels of circulating blood cells at 30 and 48 h postfertilization and subsequently confirmed by quantitative RT-PCR for erythroid-specific hbae1 and myeloid-specific lcp1 transcripts. Recapitulating the knockdown phenotype using a second MO of independent sequence, absence of the phenotype using a mismatched MO sequence, and rescue of the phenotype by cDNA-based overexpression of the targeted transcript for zebrafish spry4 confirmed the specificity of MO targeting in this system. Further characterization of the spry4-deficient zebrafish embryos demonstrated that hematopoietic defects were not due to more widespread defects in the mesodermal development, and therefore represented primary defects in HSC specification, proliferation, and/or differentiation. Overall, this high-throughput screen for the functional validation of differentially expressed genes using a zebrafish model of hematopoiesis represents a major step toward obtaining meaningful information from global

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

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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.

Regulation of eucaryotic gene expression

Energy Technology Data Exchange (ETDEWEB)

Brent, R.; Ptashne, M.S

1989-05-23

This patent describes a method of regulating the expression of a gene in a eucaryotic cell. The method consists of: providing in the eucaryotic cell, a peptide, derived from or substantially similar to a peptide of a procaryotic cell able to bind to DNA upstream from or within the gene, the amount of the peptide being sufficient to bind to the gene and thereby control expression of the gene.

Integrated automation for continuous high-throughput synthetic chromosome assembly and transformation to identify improved yeast strains for industrial production of peptide sweetener brazzein

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Production and recycling of recombinant sweetener peptides in industrial biorefineries involves the evaluation of large numbers of genes and proteins. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly synthesize, clone, and express heterologous gene ope...

Transcriptome profiling and digital gene expression by deep sequencing in early somatic embryogenesis of endangered medicinal Eleutherococcus senticosus Maxim.

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Tao, Lei; Zhao, Yue; Wu, Ying; Wang, Qiuyu; Yuan, Hongmei; Zhao, Lijuan; Guo, Wendong; You, Xiangling

2016-03-01

Somatic embryogenesis (SE) has been studied as a model system to understand molecular events in physiology, biochemistry, and cytology during plant embryo development. In particular, it is exceedingly difficult to access the morphological and early regulatory events in zygotic embryos. To understand the molecular mechanisms regulating early SE in Eleutherococcus senticosus Maxim., we used high-throughput RNA-Seq technology to investigate its transcriptome. We obtained 58,327,688 reads, which were assembled into 75,803 unique unigenes. To better understand their functions, the unigenes were annotated using the Clusters of Orthologous Groups, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes databases. Digital gene expression libraries revealed differences in gene expression profiles at different developmental stages (embryogenic callus, yellow embryogenic callus, global embryo). We obtained a sequencing depth of >5.6 million tags per sample and identified many differentially expressed genes at various stages of SE. The initiation of SE affected gene expression in many KEGG pathways, but predominantly that in metabolic pathways, biosynthesis of secondary metabolites, and plant hormone signal transduction. This information on the changes in the multiple pathways related to SE induction in E. senticosus Maxim. embryogenic tissue will contribute to a more comprehensive understanding of the mechanisms involved in early SE. Additionally, the differentially expressed genes may act as molecular markers and could play very important roles in the early stage of SE. The results are a comprehensive molecular biology resource for investigating SE of E. senticosus Maxim. Copyright © 2015 Elsevier B.V. All rights reserved.

Inferring gene expression dynamics via functional regression analysis

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Leng Xiaoyan

2008-01-01

Full Text Available Abstract Background Temporal gene expression profiles characterize the time-dynamics of expression of specific genes and are increasingly collected in current gene expression experiments. In the analysis of experiments where gene expression is obtained over the life cycle, it is of interest to relate temporal patterns of gene expression associated with different developmental stages to each other to study patterns of long-term developmental gene regulation. We use tools from functional data analysis to study dynamic changes by relating temporal gene expression profiles of different developmental stages to each other. Results We demonstrate that functional regression methodology can pinpoint relationships that exist between temporary gene expression profiles for different life cycle phases and incorporates dimension reduction as needed for these high-dimensional data. By applying these tools, gene expression profiles for pupa and adult phases are found to be strongly related to the profiles of the same genes obtained during the embryo phase. Moreover, one can distinguish between gene groups that exhibit relationships with positive and others with negative associations between later life and embryonal expression profiles. Specifically, we find a positive relationship in expression for muscle development related genes, and a negative relationship for strictly maternal genes for Drosophila, using temporal gene expression profiles. Conclusion Our findings point to specific reactivation patterns of gene expression during the Drosophila life cycle which differ in characteristic ways between various gene groups. Functional regression emerges as a useful tool for relating gene expression patterns from different developmental stages, and avoids the problems with large numbers of parameters and multiple testing that affect alternative approaches.

Synthetic promoter libraries- tuning of gene expression

DEFF Research Database (Denmark)

Hammer, Karin; Mijakovic, Ivan; Jensen, Peter Ruhdal

2006-01-01

knockout and strong overexpression. However, applications such as metabolic optimization and control analysis necessitate a continuous set of expression levels with only slight increments in strength to cover a specific window around the wildtype expression level of the studied gene; this requirement can......The study of gene function often requires changing the expression of a gene and evaluating the consequences. In principle, the expression of any given gene can be modulated in a quasi-continuum of discrete expression levels but the traditional approaches are usually limited to two extremes: gene...

DNA methylation alters transcriptional rates of differentially expressed genes and contributes to pathophysiology in mice fed a high fat diet

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Pili Zhang

2017-04-01

Full Text Available Objective: Overnutrition can alter gene expression patterns through epigenetic mechanisms that may persist through generations. However, it is less clear if overnutrition, for example a high fat diet, modifies epigenetic control of gene expression in adults, or by what molecular mechanisms, or if such mechanisms contribute to the pathology of the metabolic syndrome. Here we test the hypothesis that a high fat diet alters hepatic DNA methylation, transcription and gene expression patterns, and explore the contribution of such changes to the pathophysiology of obesity. Methods: RNA-seq and targeted high-throughput bisulfite DNA sequencing were used to undertake a systematic analysis of the hepatic response to a high fat diet. RT-PCR, chromatin immunoprecipitation and in vivo knockdown of an identified driver gene, Phlda1, were used to validate the results. Results: A high fat diet resulted in the hypermethylation and decreased transcription and expression of Phlda1 and several other genes. A subnetwork of genes associated with Phlda1 was identified from an existing Bayesian gene network that contained numerous hepatic regulatory genes involved in lipid and body weight homeostasis. Hepatic-specific depletion of Phlda1 in mice decreased expression of the genes in the subnetwork, and led to increased oil droplet size in standard chow-fed mice, an early indicator of steatosis, validating the contribution of this gene to the phenotype. Conclusions: We conclude that a high fat diet alters the epigenetics and transcriptional activity of key hepatic genes controlling lipid homeostasis, contributing to the pathophysiology of obesity. Author Video: Author Video Watch what authors say about their articles Keywords: DNA methylation, RNA-seq, Transcription, High fat diet, Liver, Phlda1

Adaptive Evolution of Gene Expression in Drosophila.

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Nourmohammad, Armita; Rambeau, Joachim; Held, Torsten; Kovacova, Viera; Berg, Johannes; Lässig, Michael

2017-08-08

Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Adaptive Evolution of Gene Expression in Drosophila

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Armita Nourmohammad

2017-08-01

Full Text Available Gene expression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of gene expression remain controversial. Here, we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of gene expression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive gene expression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis.

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

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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

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

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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 .

Global analysis of transcriptome responses and gene expression profiles to cold stress of Jatropha curcas L.

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Haibo Wang

Full Text Available BACKGROUND: Jatropha curcas L., also called the Physic nut, is an oil-rich shrub with multiple uses, including biodiesel production, and is currently exploited as a renewable energy resource in many countries. Nevertheless, because of its origin from the tropical MidAmerican zone, J. curcas confers an inherent but undesirable characteristic (low cold resistance that may seriously restrict its large-scale popularization. This adaptive flaw can be genetically improved by elucidating the mechanisms underlying plant tolerance to cold temperatures. The newly developed Illumina Hiseq™ 2000 RNA-seq and Digital Gene Expression (DGE are deep high-throughput approaches for gene expression analysis at the transcriptome level, using which we carefully investigated the gene expression profiles in response to cold stress to gain insight into the molecular mechanisms of cold response in J. curcas. RESULTS: In total, 45,251 unigenes were obtained by assembly of clean data generated by RNA-seq analysis of the J. curcas transcriptome. A total of 33,363 and 912 complete or partial coding sequences (CDSs were determined by protein database alignments and ESTScan prediction, respectively. Among these unigenes, more than 41.52% were involved in approximately 128 known metabolic or signaling pathways, and 4,185 were possibly associated with cold resistance. DGE analysis was used to assess the changes in gene expression when exposed to cold condition (12°C for 12, 24, and 48 h. The results showed that 3,178 genes were significantly upregulated and 1,244 were downregulated under cold stress. These genes were then functionally annotated based on the transcriptome data from RNA-seq analysis. CONCLUSIONS: This study provides a global view of transcriptome response and gene expression profiling of J. curcas in response to cold stress. The results can help improve our current understanding of the mechanisms underlying plant cold resistance and favor the screening of

Thalidomide induced early gene expression perturbations indicative of human embryopathy in mouse embryonic stem cells

International Nuclear Information System (INIS)

Gao, Xiugong; Sprando, Robert L.; Yourick, Jeffrey J.

2015-01-01

Developmental toxicity testing has traditionally relied on animal models which are costly, time consuming, and require the sacrifice of large numbers of animals. In addition, there are significant disparities between human beings and animals in their responses to chemicals. Thalidomide is a species-specific developmental toxicant that causes severe limb malformations in humans but not in mice. Here, we used microarrays to study transcriptomic changes induced by thalidomide in an in vitro model based on differentiation of mouse embryonic stem cells (mESCs). C57BL/6 mESCs were allowed to differentiate spontaneously and RNA was collected at 24, 48, and 72 h after exposure to 0.25 mM thalidomide. Global gene expression analysis using microarrays revealed hundreds of differentially expressed genes upon thalidomide exposure that were enriched in gene ontology (GO) terms and canonical pathways associated with embryonic development and differentiation. In addition, many genes were found to be involved in small GTPases-mediated signal transduction, heart development, and inflammatory responses, which coincide with clinical evidences and may represent critical embryotoxicities of thalidomide. These results demonstrate that transcriptomics in combination with mouse embryonic stem cell differentiation is a promising alternative model for developmental toxicity assessment. - Highlights: • Studied genomic changes in mouse embryonic stem cells upon thalidomide exposure • Identified gene expression changes that may represent thalidomide embryotoxicity • The toxicogenomic changes coincide well with known thalidomide clinical outcomes. • The mouse embryonic stem cell model is suitable for developmental toxicity testing. • The model has the potential for high-throughput screening of a multitude of compounds

Thalidomide induced early gene expression perturbations indicative of human embryopathy in mouse embryonic stem cells

Energy Technology Data Exchange (ETDEWEB)

Gao, Xiugong, E-mail: xiugong.gao@fda.hhs.gov; Sprando, Robert L.; Yourick, Jeffrey J.

2015-08-15

Developmental toxicity testing has traditionally relied on animal models which are costly, time consuming, and require the sacrifice of large numbers of animals. In addition, there are significant disparities between human beings and animals in their responses to chemicals. Thalidomide is a species-specific developmental toxicant that causes severe limb malformations in humans but not in mice. Here, we used microarrays to study transcriptomic changes induced by thalidomide in an in vitro model based on differentiation of mouse embryonic stem cells (mESCs). C57BL/6 mESCs were allowed to differentiate spontaneously and RNA was collected at 24, 48, and 72 h after exposure to 0.25 mM thalidomide. Global gene expression analysis using microarrays revealed hundreds of differentially expressed genes upon thalidomide exposure that were enriched in gene ontology (GO) terms and canonical pathways associated with embryonic development and differentiation. In addition, many genes were found to be involved in small GTPases-mediated signal transduction, heart development, and inflammatory responses, which coincide with clinical evidences and may represent critical embryotoxicities of thalidomide. These results demonstrate that transcriptomics in combination with mouse embryonic stem cell differentiation is a promising alternative model for developmental toxicity assessment. - Highlights: • Studied genomic changes in mouse embryonic stem cells upon thalidomide exposure • Identified gene expression changes that may represent thalidomide embryotoxicity • The toxicogenomic changes coincide well with known thalidomide clinical outcomes. • The mouse embryonic stem cell model is suitable for developmental toxicity testing. • The model has the potential for high-throughput screening of a multitude of compounds.

A machine learned classifier that uses gene expression data to accurately predict estrogen receptor status.

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Meysam Bastani

Full Text Available 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.

Differential Gene Expression Profiling of Dystrophic Dog Muscle after MuStem Cell Transplantation.

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Robriquet, Florence; Lardenois, Aurélie; Babarit, Candice; Larcher, Thibaut; Dubreil, Laurence; Leroux, Isabelle; Zuber, Céline; Ledevin, Mireille; Deschamps, Jack-Yves; Fromes, Yves; Cherel, Yan; Guevel, Laetitia; Rouger, Karl

2015-01-01

Several adult stem cell populations exhibit myogenic regenerative potential, thus representing attractive candidates for therapeutic approaches of neuromuscular diseases such as Duchenne Muscular Dystrophy (DMD). We have recently shown that systemic delivery of MuStem cells, skeletal muscle-resident stem cells isolated in healthy dog, generates the remodelling of muscle tissue and gives rise to striking clinical benefits in Golden Retriever Muscular Dystrophy (GRMD) dog. This global effect, which is observed in the clinically relevant DMD animal model, leads us to question here the molecular pathways that are impacted by MuStem cell transplantation. To address this issue, we compare the global gene expression profile between healthy, GRMD and MuStem cell treated GRMD dog muscle, four months after allogenic MuStem cell transplantation. In the dystrophic context of the GRMD dog, disease-related deregulation is observed in the case of 282 genes related to various processes such as inflammatory response, regeneration, calcium ion binding, extracellular matrix organization, metabolism and apoptosis regulation. Importantly, we reveal the impact of MuStem cell transplantation on several molecular and cellular pathways based on a selection of 31 genes displaying signals specifically modulated by the treatment. Concomitant with a diffuse dystrophin expression, a histological remodelling and a stabilization of GRMD dog clinical status, we show that cell delivery is associated with an up-regulation of genes reflecting a sustained enhancement of muscle regeneration. We also identify a decreased mRNA expression of a set of genes having metabolic functions associated with lipid homeostasis and energy. Interestingly, ubiquitin-mediated protein degradation is highly enhanced in GRMD dog muscle after systemic delivery of MuStem cells. Overall, our results provide the first high-throughput characterization of GRMD dog muscle and throw new light on the complex molecular

Differential Gene Expression Profiling of Dystrophic Dog Muscle after MuStem Cell Transplantation.

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Florence Robriquet

Full Text Available Several adult stem cell populations exhibit myogenic regenerative potential, thus representing attractive candidates for therapeutic approaches of neuromuscular diseases such as Duchenne Muscular Dystrophy (DMD. We have recently shown that systemic delivery of MuStem cells, skeletal muscle-resident stem cells isolated in healthy dog, generates the remodelling of muscle tissue and gives rise to striking clinical benefits in Golden Retriever Muscular Dystrophy (GRMD dog. This global effect, which is observed in the clinically relevant DMD animal model, leads us to question here the molecular pathways that are impacted by MuStem cell transplantation. To address this issue, we compare the global gene expression profile between healthy, GRMD and MuStem cell treated GRMD dog muscle, four months after allogenic MuStem cell transplantation.In the dystrophic context of the GRMD dog, disease-related deregulation is observed in the case of 282 genes related to various processes such as inflammatory response, regeneration, calcium ion binding, extracellular matrix organization, metabolism and apoptosis regulation. Importantly, we reveal the impact of MuStem cell transplantation on several molecular and cellular pathways based on a selection of 31 genes displaying signals specifically modulated by the treatment. Concomitant with a diffuse dystrophin expression, a histological remodelling and a stabilization of GRMD dog clinical status, we show that cell delivery is associated with an up-regulation of genes reflecting a sustained enhancement of muscle regeneration. We also identify a decreased mRNA expression of a set of genes having metabolic functions associated with lipid homeostasis and energy. Interestingly, ubiquitin-mediated protein degradation is highly enhanced in GRMD dog muscle after systemic delivery of MuStem cells.Overall, our results provide the first high-throughput characterization of GRMD dog muscle and throw new light on the complex

Gene and protein expression following exposure to radiofrequency fields from mobile phones.

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Vanderstraeten, Jacques; Verschaeve, Luc

2008-09-01

Since 1999, several articles have been published on genome-wide and/or proteome-wide response after exposure to radiofrequency (RF) fields whose signal and intensities were similar to or typical of those of currently used mobile telephones. These studies were performed using powerful high-throughput screening techniques (HTSTs) of transcriptomics and/or proteomics, which allow for the simultaneous screening of the expression of thousands of genes or proteins. We reviewed these HTST-based studies and compared the results with currently accepted concepts about the effects of RF fields on gene expression. In this article we also discuss these last in light of the recent concept of microwave-assisted chemistry. To date, the results of HTST-based studies of transcriptomics and/or proteomics after exposure to RF fields relevant to human exposure are still inconclusive, as most of the positive reports are flawed by methodologic imperfections or shortcomings. In addition, when positive findings were reported, no precise response pattern could be identified in a reproducible way. In particular, results from HTST studies tend to exclude the role of a cell stressor for exposure to RF fields at nonthermal intensities. However, on the basis of lessons from microwave-assisted chemistry, we can assume that RF fields might affect heat-sensitive gene or protein expression to an extent larger than would be predicted from temperature change only. But in all likelihood, this would concern intensities higher than those relevant to usual human exposure. The precise role of transcriptomics and proteomics in the screening of bioeffects from exposure to RF fields from mobile phones is still uncertain in view of the lack of positively identified phenotypic change and the lack of theoretical, as well as experimental, arguments for specific gene and/or protein response patterns after this kind of exposure.

Time-Course Gene Set Analysis for Longitudinal Gene Expression Data.

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Boris P Hejblum

2015-06-01

Full Text Available Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estimates. It allows to use all available repeated measurements while dealing with unbalanced data due to missing at random (MAR measurements. TcGSA is a hypothesis driven method that identifies a priori defined gene sets with significant expression variations over time, taking into account the potential heterogeneity of expression within gene sets. When biological conditions are compared, the method indicates if the time patterns of gene sets significantly differ according to these conditions. The interest of the method is illustrated by its application to two real life datasets: an HIV therapeutic vaccine trial (DALIA-1 trial, and data from a recent study on influenza and pneumococcal vaccines. In the DALIA-1 trial TcGSA revealed a significant change in gene expression over time within 69 gene sets during vaccination, while a standard univariate individual gene analysis corrected for multiple testing as well as a standard a Gene Set Enrichment Analysis (GSEA for time series both failed to detect any significant pattern change over time. When applied to the second illustrative data set, TcGSA allowed the identification of 4 gene sets finally found to be linked with the influenza vaccine too although they were found to be associated to the pneumococcal vaccine only in previous analyses. In our simulation study TcGSA exhibits good statistical properties, and an increased power compared to other approaches for analyzing time-course expression patterns of gene sets. The method is made available for the community through an R package.

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

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Rodland, Karin D.; Adkins, Joshua N.; Ansong, Charles; Chowdhury, Saiful M.; Manes, Nathan P.; Shi, Liang; Yoon, Hyunjin; Smith, Richard D.; Heffron, Fred

2008-12-01

New improvements to mass spectrometry include increased sensitivity, improvements in analyzing the collected data, and most important, from the standpoint of this review, a much higher throughput allowing analysis of many samples in a single day. This short review describes how host-pathogen interactions can be dissected by mass spectrometry using Salmonella as a model system. The approach allowed direct identification of the majority of annotate Salmonella proteins, how expression changed under various in vitro growth conditions, and how this relates to virulence and expression within host cell cells. One of the most significant findings is that a very high percentage of the all annotated genes (>20%) 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 the regulator in coordinating virulence expression. Overall high throughput mass spectrometer provides a new view of pathogen-host interaction emphasizing the protein products and defining how protein interactions determine the outcome of infection.

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

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

2016-01-01

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

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.

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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.

Methods for efficient high-throughput screening of protein expression in recombinant Pichia pastoris strains.

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Camattari, Andrea; Weinhandl, Katrin; Gudiminchi, Rama K

2014-01-01

The methylotrophic yeast Pichia pastoris is becoming one of the favorite industrial workhorses for protein expression. Due to the widespread use of integration vectors, which generates significant clonal variability, screening methods allowing assaying hundreds of individual clones are of particular importance. Here we describe methods to detect and analyze protein expression, developed in a 96-well format for high-throughput screening of recombinant P. pastoris strains. The chapter covers essentially three common scenarios: (1) an enzymatic assay for proteins expressed in the cell cytoplasm, requiring cell lysis; (2) a whole-cell assay for a fungal cytochrome P450; and (3) a nonenzymatic assay for detection and quantification of tagged protein secreted into the supernatant.

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

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Helen L Ramsden

2015-01-01

Full Text Available 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.

Localisation of Abundant and Organ-Specific Genes Expressed in Rosa hybrida Leaves and Flower Buds by Direct In Situ RT-PCR

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Agata Jedrzejuk

2012-01-01

Full Text Available In situ PCR is a technique that allows specific nucleic acid sequences to be detected in individual cells and tissues. In situ PCR and IS-RT-PCR are elegant techniques that can increase both sensitivity and throughput, but they are, at best, only semiquantitative; therefore, it is desirable first to ascertain the expression pattern by conventional means to establish the suitable conditions for each probe. In plants, in situ RT-PCR is widely used in the expression localisation of specific genes, including MADS-box and other function-specific genes or housekeeping genes in floral buds and other organs. This method is especially useful in small organs or during early developmental stages when the separation of particular parts is impossible. In this paper, we compared three different labelling and immunodetection methods by using in situ RT-PCR in Rosa hybrida flower buds and leaves. As target genes, we used the abundant β-actin and RhFUL gene, which is expressed only in the leaves and petals/sepals of flower buds. We used digoxygenin-11-dUTP, biotin-11-dUTP, and fluorescein-12-dUTP-labelled nucleotides and antidig-AP/ streptavidin-fluorescein-labelled antibodies. All of the used methods gave strong, specific signal and all of them may be used in localization of gene expression on tissue level in rose organs.

The rules of gene expression in plants: Organ identity and gene body methylation are key factors for regulation of gene expression in Arabidopsis thaliana

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Gutiérrez Rodrigo A

2008-09-01

Full Text Available Abstract Background Microarray technology is a widely used approach for monitoring genome-wide gene expression. For Arabidopsis, there are over 1,800 microarray hybridizations representing many different experimental conditions on Affymetrix™ ATH1 gene chips alone. This huge amount of data offers a unique opportunity to infer the principles that govern the regulation of gene expression in plants. Results We used bioinformatics methods to analyze publicly available data obtained using the ATH1 chip from Affymetrix. A total of 1887 ATH1 hybridizations were normalized and filtered to eliminate low-quality hybridizations. We classified and compared control and treatment hybridizations and determined differential gene expression. The largest differences in gene expression were observed when comparing samples obtained from different organs. On average, ten-fold more genes were differentially expressed between organs as compared to any other experimental variable. We defined "gene responsiveness" as the number of comparisons in which a gene changed its expression significantly. We defined genes with the highest and lowest responsiveness levels as hypervariable and housekeeping genes, respectively. Remarkably, housekeeping genes were best distinguished from hypervariable genes by differences in methylation status in their transcribed regions. Moreover, methylation in the transcribed region was inversely correlated (R2 = 0.8 with gene responsiveness on a genome-wide scale. We provide an example of this negative relationship using genes encoding TCA cycle enzymes, by contrasting their regulatory responsiveness to nitrate and methylation status in their transcribed regions. Conclusion Our results indicate that the Arabidopsis transcriptome is largely established during development and is comparatively stable when faced with external perturbations. We suggest a novel functional role for DNA methylation in the transcribed region as a key determinant

Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection

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Gavin C. Bowick

2011-05-01

Full Text Available The continuing use of high-throughput assays to investigate cellular responses to infection is providing a large repository of information. Due to the large number of differentially expressed transcripts, often running into the thousands, the majority of these data have not been thoroughly investigated. Advances in techniques for the downstream analysis of high-throughput datasets are providing additional methods for the generation of additional hypotheses for further investigation. The large number of experimental observations, combined with databases that correlate particular genes and proteins with canonical pathways, functions and diseases, allows for the bioinformatic exploration of functional networks that may be implicated in replication or pathogenesis. Herein, we provide an example of how analysis of published high-throughput datasets of cellular responses to hemorrhagic fever virus infection can generate additional functional data. We describe enrichment of genes involved in metabolism, post-translational modification and cardiac damage; potential roles for specific transcription factors and a conserved involvement of a pathway based around cyclooxygenase-2. We believe that these types of analyses can provide virologists with additional hypotheses for continued investigation.

Thiol-linked alkylation of RNA to assess expression dynamics.

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Herzog, Veronika A; Reichholf, Brian; Neumann, Tobias; Rescheneder, Philipp; Bhat, Pooja; Burkard, Thomas R; Wlotzka, Wiebke; von Haeseler, Arndt; Zuber, Johannes; Ameres, Stefan L

2017-12-01

Gene expression profiling by high-throughput sequencing reveals qualitative and quantitative changes in RNA species at steady state but obscures the intracellular dynamics of RNA transcription, processing and decay. We developed thiol(SH)-linked alkylation for the metabolic sequencing of RNA (SLAM seq), an orthogonal-chemistry-based RNA sequencing technology that detects 4-thiouridine (s 4 U) incorporation in RNA species at single-nucleotide resolution. In combination with well-established metabolic RNA labeling protocols and coupled to standard, low-input, high-throughput RNA sequencing methods, SLAM seq enabled rapid access to RNA-polymerase-II-dependent gene expression dynamics in the context of total RNA. We validated the method in mouse embryonic stem cells by showing that the RNA-polymerase-II-dependent transcriptional output scaled with Oct4/Sox2/Nanog-defined enhancer activity, and we provide quantitative and mechanistic evidence for transcript-specific RNA turnover mediated by post-transcriptional gene regulatory pathways initiated by microRNAs and N 6 -methyladenosine. SLAM seq facilitates the dissection of fundamental mechanisms that control gene expression in an accessible, cost-effective and scalable manner.

The functional landscape of mouse gene expression

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Zhang Wen

2004-12-01

Full Text Available Abstract Background Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. Results We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. Conclusions We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.

Expression of Sox genes in tooth development.

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Kawasaki, Katsushige; Kawasaki, Maiko; Watanabe, Momoko; Idrus, Erik; Nagai, Takahiro; Oommen, Shelly; Maeda, Takeyasu; Hagiwara, Nobuko; Que, Jianwen; Sharpe, Paul T; Ohazama, Atsushi

2015-01-01

Members of the Sox gene family play roles in many biological processes including organogenesis. We carried out comparative in situ hybridization analysis of seventeen sox genes (Sox1-14, 17, 18, 21) during murine odontogenesis from the epithelial thickening to the cytodifferentiation stages. Localized expression of five Sox genes (Sox6, 9, 13, 14 and 21) was observed in tooth bud epithelium. Sox13 showed restricted expression in the primary enamel knots. At the early bell stage, three Sox genes (Sox8, 11, 17 and 21) were expressed in pre-ameloblasts, whereas two others (Sox5 and 18) showed expression in odontoblasts. Sox genes thus showed a dynamic spatio-temporal expression during tooth development.

Profiling Gene Expression in Germinating Brassica Roots.

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Park, Myoung Ryoul; Wang, Yi-Hong; Hasenstein, Karl H

2014-01-01

Based on previously developed solid-phase gene extraction (SPGE) we examined the mRNA profile in primary roots of Brassica rapa seedlings for highly expressed genes like ACT7 (actin7), TUB (tubulin1), UBQ (ubiquitin), and low expressed GLK (glucokinase) during the first day post-germination. The assessment was based on the mRNA load of the SPGE probe of about 2.1 ng. The number of copies of the investigated genes changed spatially along the length of primary roots. The expression level of all genes differed significantly at each sample position. Among the examined genes ACT7 expression was most even along the root. UBQ was highest at the tip and root-shoot junction (RS). TUB and GLK showed a basipetal gradient. The temporal expression of UBQ was highest in the MZ 9 h after primary root emergence and higher than at any other sample position. Expressions of GLK in EZ and RS increased gradually over time. SPGE extraction is the result of oligo-dT and oligo-dA hybridization and the results illustrate that SPGE can be used for gene expression profiling at high spatial and temporal resolution. SPGE needles can be used within two weeks when stored at 4 °C. Our data indicate that gene expression studies that are based on the entire root miss important differences in gene expression that SPGE is able to resolve for example growth adjustments during gravitropism.

Genome-Wide Characterization and Expression Profiling of the AUXIN RESPONSE FACTOR (ARF) Gene Family in Eucalyptus grandis

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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

Genome-wide characterization and expression profiling of the AUXIN RESPONSE FACTOR (ARF gene family in Eucalyptus grandis.

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Hong Yu

Full Text Available 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.

Unstable Expression of Commonly Used Reference Genes in Rat Pancreatic Islets Early after Isolation Affects Results of Gene Expression Studies.

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Lucie Kosinová

Full Text Available The use of RT-qPCR provides a powerful tool for gene expression studies; however, the proper interpretation of the obtained data is crucially dependent on accurate normalization based on stable reference genes. Recently, strong evidence has been shown indicating that the expression of many commonly used reference genes may vary significantly due to diverse experimental conditions. The isolation of pancreatic islets is a complicated procedure which creates severe mechanical and metabolic stress leading possibly to cellular damage and alteration of gene expression. Despite of this, freshly isolated islets frequently serve as a control in various gene expression and intervention studies. The aim of our study was to determine expression of 16 candidate reference genes and one gene of interest (F3 in isolated rat pancreatic islets during short-term cultivation in order to find a suitable endogenous control for gene expression studies. We compared the expression stability of the most commonly used reference genes and evaluated the reliability of relative and absolute quantification using RT-qPCR during 0-120 hrs after isolation. In freshly isolated islets, the expression of all tested genes was markedly depressed and it increased several times throughout the first 48 hrs of cultivation. We observed significant variability among samples at 0 and 24 hrs but substantial stabilization from 48 hrs onwards. During the first 48 hrs, relative quantification failed to reflect the real changes in respective mRNA concentrations while in the interval 48-120 hrs, the relative expression generally paralleled the results determined by absolute quantification. Thus, our data call into question the suitability of relative quantification for gene expression analysis in pancreatic islets during the first 48 hrs of cultivation, as the results may be significantly affected by unstable expression of reference genes. However, this method could provide reliable information

Comprehensive analysis of gene expression patterns of hedgehog-related genes

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Baillie David

2006-10-01

Full Text Available Abstract Background The Caenorhabditis elegans genome encodes ten proteins that share sequence similarity with the Hedgehog signaling molecule through their C-terminal autoprocessing Hint/Hog domain. These proteins contain novel N-terminal domains, and C. elegans encodes dozens of additional proteins containing only these N-terminal domains. These gene families are called warthog, groundhog, ground-like and quahog, collectively called hedgehog (hh-related genes. Previously, the expression pattern of seventeen genes was examined, which showed that they are primarily expressed in the ectoderm. Results With the completion of the C. elegans genome sequence in November 2002, we reexamined and identified 61 hh-related ORFs. Further, we identified 49 hh-related ORFs in C. briggsae. ORF analysis revealed that 30% of the genes still had errors in their predictions and we improved these predictions here. We performed a comprehensive expression analysis using GFP fusions of the putative intergenic regulatory sequence with one or two transgenic lines for most genes. The hh-related genes are expressed in one or a few of the following tissues: hypodermis, seam cells, excretory duct and pore cells, vulval epithelial cells, rectal epithelial cells, pharyngeal muscle or marginal cells, arcade cells, support cells of sensory organs, and neuronal cells. Using time-lapse recordings, we discovered that some hh-related genes are expressed in a cyclical fashion in phase with molting during larval development. We also generated several translational GFP fusions, but they did not show any subcellular localization. In addition, we also studied the expression patterns of two genes with similarity to Drosophila frizzled, T23D8.1 and F27E11.3A, and the ortholog of the Drosophila gene dally-like, gpn-1, which is a heparan sulfate proteoglycan. The two frizzled homologs are expressed in a few neurons in the head, and gpn-1 is expressed in the pharynx. Finally, we compare the

Development of new USER-based cloning vectors for multiple genes expression in Saccharomyces cerevisiae

DEFF Research Database (Denmark)

Kildegaard, Kanchana Rueksomtawin; Jensen, Niels Bjerg; Maury, Jerome

2013-01-01

auxotrophic and dominant markers for convenience of use. Our vector set also contains both integrating and multicopy vectors for stability of protein expression and high expression level. We will make the new vector system available to the yeast community and provide a comprehensive protocol for cloning...... the production strain with the proper phenotype and product yield. However, the sequential number of metabolic engineering is time-consuming. Furthermore, the number of available selectable markers is also limiting the number of genetic modifications. To overcome these limitations, we have developed a new set...... of shuttle vectors for convenience of use for high-throughput cloning and selectable marker recycling. The new USER-based cloning vectors consist of a unique USER site and a CRE-loxP-mediated marker recycling system. The USER site allows insertion of genes of interest along with a bidirectional promoter...

Simple Comparative Analyses of Differentially Expressed Gene Lists May Overestimate Gene Overlap.

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Lawhorn, Chelsea M; Schomaker, Rachel; Rowell, Jonathan T; Rueppell, Olav

2018-04-16

Comparing the overlap between sets of differentially expressed genes (DEGs) within or between transcriptome studies is regularly used to infer similarities between biological processes. Significant overlap between two sets of DEGs is usually determined by a simple test. The number of potentially overlapping genes is compared to the number of genes that actually occur in both lists, treating every gene as equal. However, gene expression is controlled by transcription factors that bind to a variable number of transcription factor binding sites, leading to variation among genes in general variability of their expression. Neglecting this variability could therefore lead to inflated estimates of significant overlap between DEG lists. With computer simulations, we demonstrate that such biases arise from variation in the control of gene expression. Significant overlap commonly arises between two lists of DEGs that are randomly generated, assuming that the control of gene expression is variable among genes but consistent between corresponding experiments. More overlap is observed when transcription factors are specific to their binding sites and when the number of genes is considerably higher than the number of different transcription factors. In contrast, overlap between two DEG lists is always lower than expected when the genetic architecture of expression is independent between the two experiments. Thus, the current methods for determining significant overlap between DEGs are potentially confounding biologically meaningful overlap with overlap that arises due to variability in control of expression among genes, and more sophisticated approaches are needed.

Methods for monitoring multiple gene expression

Energy Technology Data Exchange (ETDEWEB)

Berka, Randy [Davis, CA; Bachkirova, Elena [Davis, CA; Rey, Michael [Davis, CA

2012-05-01

The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

Methods for monitoring multiple gene expression

Energy Technology Data Exchange (ETDEWEB)

Berka, Randy; Bachkirova, Elena; Rey, Michael

2013-10-01

The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

Determinants of human adipose tissue gene expression

DEFF Research Database (Denmark)

Viguerie, Nathalie; Montastier, Emilie; Maoret, Jean-José

2012-01-01

weight maintenance diets. For 175 genes, opposite regulation was observed during calorie restriction and weight maintenance phases, independently of variations in body weight. Metabolism and immunity genes showed inverse profiles. During the dietary intervention, network-based analyses revealed strong...... interconnection between expression of genes involved in de novo lipogenesis and components of the metabolic syndrome. Sex had a marked influence on AT expression of 88 transcripts, which persisted during the entire dietary intervention and after control for fat mass. In women, the influence of body mass index...... on expression of a subset of genes persisted during the dietary intervention. Twenty-two genes revealed a metabolic syndrome signature common to men and women. Genetic control of AT gene expression by cis signals was observed for 46 genes. Dietary intervention, sex, and cis genetic variants independently...

LINE FUSION GENES: a database of LINE expression in human genes

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Park Hong-Seog

2006-06-01

Full Text Available Abstract Background Long Interspersed Nuclear Elements (LINEs are the most abundant retrotransposons in humans. About 79% of human genes are estimated to contain at least one segment of LINE per transcription unit. Recent studies have shown that LINE elements can affect protein sequences, splicing patterns and expression of human genes. Description We have developed a database, LINE FUSION GENES, for elucidating LINE expression throughout the human gene database. We searched the 28,171 genes listed in the NCBI database for LINE elements and analyzed their structures and expression patterns. The results show that the mRNA sequences of 1,329 genes were affected by LINE expression. The LINE expression types were classified on the basis of LINEs in the 5' UTR, exon or 3' UTR sequences of the mRNAs. Our database provides further information, such as the tissue distribution and chromosomal location of the genes, and the domain structure that is changed by LINE integration. We have linked all the accession numbers to the NCBI data bank to provide mRNA sequences for subsequent users. Conclusion We believe that our work will interest genome scientists and might help them to gain insight into the implications of LINE expression for human evolution and disease. Availability http://www.primate.or.kr/line

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

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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

Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes

KAUST Repository

Horiuchi, Youko

2015-12-23

Background Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on gene expression, without explicit discrimination between global expression differences and tissue specific expression differences. However, different types of gene expression alteration should have different effects on an organism, the evolutionary forces that act on them might be different, and different types of genes might show different types of differential expression between species. To confirm this, we studied differentially expressed (DE) genes among closely related groups that have extensive gene expression atlases, and clarified characteristics of different types of DE genes including the identification of regulating loci for differential expression using expression quantitative loci (eQTL) analysis data. Results We detected differentially expressed (DE) genes between rice subspecies in five homologous tissues that were verified using japonica and indica transcriptome atlases in public databases. Using the transcriptome atlases, we classified DE genes into two types, global DE genes and changed-tissues DE genes. Global type DE genes were not expressed in any tissues in the atlas of one subspecies, however changed-tissues type DE genes were expressed in both subspecies with different tissue specificity. For the five tissues in the two japonica-indica combinations, 4.6 ± 0.8 and 5.9 ± 1.5 % of highly expressed genes were global and changed-tissues DE genes, respectively. Changed-tissues DE genes varied in number between tissues, increasing linearly with the abundance of tissue specifically expressed genes in the tissue. Molecular evolution of global DE genes was rapid, unlike that of changed-tissues DE genes. Based on gene ontology, global and changed-tissues DE genes were different, having no common GO terms. Expression differences of most global DE genes were regulated by cis-eQTLs. Expression

Social Regulation of Gene Expression in Threespine Sticklebacks.

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Anna K Greenwood

Full Text Available Identifying genes that are differentially expressed in response to social interactions is informative for understanding the molecular basis of social behavior. To address this question, we described changes in gene expression as a result of differences in the extent of social interactions. We housed threespine stickleback (Gasterosteus aculeatus females in either group conditions or individually for one week, then measured levels of gene expression in three brain regions using RNA-sequencing. We found that numerous genes in the hindbrain/cerebellum had altered expression in response to group or individual housing. However, relatively few genes were differentially expressed in either the diencephalon or telencephalon. The list of genes upregulated in fish from social groups included many genes related to neural development and cell adhesion as well as genes with functions in sensory signaling, stress, and social and reproductive behavior. The list of genes expressed at higher levels in individually-housed fish included several genes previously identified as regulated by social interactions in other animals. The identified genes are interesting targets for future research on the molecular mechanisms of normal social interactions.

Lung cancer gene expression database analysis incorporating prior knowledge with support vector machine-based classification method

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Huang Desheng

2009-07-01

Full Text Available Abstract Background A reliable and precise classification is essential for successful diagnosis and treatment of cancer. Gene expression microarrays have provided the high-throughput platform to discover genomic biomarkers for cancer diagnosis and prognosis. Rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, only some studies have been aware of the importance of prior information in cancer classification. Methods Together with the application of support vector machine as the discriminant approach, we proposed one modified method that incorporated prior knowledge into cancer classification based on gene expression data to improve accuracy. A public well-known dataset, Malignant pleural mesothelioma and lung adenocarcinoma gene expression database, was used in this study. Prior knowledge is viewed here as a means of directing the classifier using known lung adenocarcinoma related genes. The procedures were performed by software R 2.80. Results The modified method performed better after incorporating prior knowledge. Accuracy of the modified method improved from 98.86% to 100% in training set and from 98.51% to 99.06% in test set. The standard deviations of the modified method decreased from 0.26% to 0 in training set and from 3.04% to 2.10% in test set. Conclusion The method that incorporates prior knowledge into discriminant analysis could effectively improve the capacity and reduce the impact of noise. This idea may have good future not only in practice but also in methodology.

Translating standards into practice - one Semantic Web API for Gene Expression.

Science.gov (United States)

Deus, Helena F; Prud'hommeaux, Eric; Miller, Michael; Zhao, Jun; Malone, James; Adamusiak, Tomasz; McCusker, Jim; Das, Sudeshna; Rocca Serra, Philippe; Fox, Ronan; Marshall, M Scott

2012-08-01

Sharing and describing experimental results unambiguously with sufficient detail to enable replication of results is a fundamental tenet of scientific research. In today's cluttered world of "-omics" sciences, data standards and standardized use of terminologies and ontologies for biomedical informatics play an important role in reporting high-throughput experiment results in formats that can be interpreted by both researchers and analytical tools. Increasing adoption of Semantic Web and Linked Data technologies for the integration of heterogeneous and distributed health care and life sciences (HCLSs) datasets has made the reuse of standards even more pressing; dynamic semantic query federation can be used for integrative bioinformatics when ontologies and identifiers are reused across data instances. We present here a methodology to integrate the results and experimental context of three different representations of microarray-based transcriptomic experiments: the Gene Expression Atlas, the W3C BioRDF task force approach to reporting Provenance of Microarray Experiments, and the HSCI blood genomics project. Our approach does not attempt to improve the expressivity of existing standards for genomics but, instead, to enable integration of existing datasets published from microarray-based transcriptomic experiments. SPARQL Construct is used to create a posteriori mappings of concepts and properties and linking rules that match entities based on query constraints. We discuss how our integrative approach can encourage reuse of the Experimental Factor Ontology (EFO) and the Ontology for Biomedical Investigations (OBIs) for the reporting of experimental context and results of gene expression studies. Copyright © 2012 Elsevier Inc. All rights reserved.

A constructive approach to gene expression dynamics

International Nuclear Information System (INIS)

Ochiai, T.; Nacher, J.C.; Akutsu, T.

2004-01-01

Recently, experiments on mRNA abundance (gene expression) have revealed that gene expression shows a stationary organization described by a scale-free distribution. Here we propose a constructive approach to gene expression dynamics which restores the scale-free exponent and describes the intermediate state dynamics. This approach requires only one assumption: Markov property

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

Science.gov (United States)

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

2016-01-01

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

Stably Expressed Genes Involved in Basic Cellular Functions.

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Kejian Wang

Full Text Available Stably Expressed Genes (SEGs whose expression varies within a narrow range may be involved in core cellular processes necessary for basic functions. To identify such genes, we re-analyzed existing RNA-Seq gene expression profiles across 11 organs at 4 developmental stages (from immature to old age in both sexes of F344 rats (n = 4/group; 320 samples. Expression changes (calculated as the maximum expression / minimum expression for each gene of >19000 genes across organs, ages, and sexes ranged from 2.35 to >109-fold, with a median of 165-fold. The expression of 278 SEGs was found to vary ≤4-fold and these genes were significantly involved in protein catabolism (proteasome and ubiquitination, RNA transport, protein processing, and the spliceosome. Such stability of expression was further validated in human samples where the expression variability of the homologous human SEGs was significantly lower than that of other genes in the human genome. It was also found that the homologous human SEGs were generally less subject to non-synonymous mutation than other genes, as would be expected of stably expressed genes. We also found that knockout of SEG homologs in mouse models was more likely to cause complete preweaning lethality than non-SEG homologs, corroborating the fundamental roles played by SEGs in biological development. Such stably expressed genes and pathways across life-stages suggest that tight control of these processes is important in basic cellular functions and that perturbation by endogenous (e.g., genetics or exogenous agents (e.g., drugs, environmental factors may cause serious adverse effects.

Lithium ions induce prestalk-associated gene expression and inhibit prespore gene expression in Dictyostelium discoideum

NARCIS (Netherlands)

Peters, Dorien J.M.; Lookeren Campagne, Michiel M. van; Haastert, Peter J.M. van; Spek, Wouter; Schaap, Pauline

1989-01-01

We investigated the effect of Li+ on two types of cyclic AMP-regulated gene expression and on basal and cyclic AMP-stimulated inositol 1,4,5-trisphosphate (Ins(1,4,5)P3) levels. Li+ effectively inhibits cyclic AMP-induced prespore gene expression, half-maximal inhibition occurring at about 2mM-LiCl.

Validation of commonly used reference genes for sleep-related gene expression studies

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Castro Rosa MRPS

2009-05-01

Full Text Available Abstract Background Sleep is a restorative process and is essential for maintenance of mental and physical health. In an attempt to understand the complexity of sleep, multidisciplinary strategies, including genetic approaches, have been applied to sleep research. Although quantitative real time PCR has been used in previous sleep-related gene expression studies, proper validation of reference genes is currently lacking. Thus, we examined the effect of total or paradoxical sleep deprivation (TSD or PSD on the expression stability of the following frequently used reference genes in brain and blood: beta-actin (b-actin, beta-2-microglobulin (B2M, glyceraldehyde-3-phosphate dehydrogenase (GAPDH, and hypoxanthine guanine phosphoribosyl transferase (HPRT. Results Neither TSD nor PSD affected the expression stability of all tested genes in both tissues indicating that b-actin, B2M, GAPDH and HPRT are appropriate reference genes for the sleep-related gene expression studies. In order to further verify these results, the relative expression of brain derived neurotrophic factor (BDNF and glycerol-3-phosphate dehydrogenase1 (GPD1 was evaluated in brain and blood, respectively. The normalization with each of four reference genes produced similar pattern of expression in control and sleep deprived rats, but subtle differences in the magnitude of expression fold change were observed which might affect the statistical significance. Conclusion This study demonstrated that sleep deprivation does not alter the expression stability of commonly used reference genes in brain and blood. Nonetheless, the use of multiple reference genes in quantitative RT-PCR is required for the accurate results.

LOX: Inferring level of expression from diverse methods of census sequencing

KAUST Repository

Zhang, Zhang

2010-06-10

Summary: We present LOX (Level Of eXpression) that estimates the Level Of gene eXpression from high-throughput-expressed sequence datasets with multiple treatments or samples. Unlike most analyses, LOX incorporates a gene bias model that facilitates integration of diverse transcriptomic sequencing data that arises when transcriptomic data have been produced using diverse experimental methodologies. LOX integrates overall sequence count tallies normalized by total expressed sequence count to provide expression levels for each gene relative to all treatments as well as Bayesian credible intervals. © The Author 2010. Published by Oxford University Press. All rights reserved.

LOX: Inferring level of expression from diverse methods of census sequencing

KAUST Repository

Zhang, Zhang; Ló pez-Girá ldez, Francesc Francisco; Townsend, Jeffrey P.

2010-01-01

Summary: We present LOX (Level Of eXpression) that estimates the Level Of gene eXpression from high-throughput-expressed sequence datasets with multiple treatments or samples. Unlike most analyses, LOX incorporates a gene bias model that facilitates integration of diverse transcriptomic sequencing data that arises when transcriptomic data have been produced using diverse experimental methodologies. LOX integrates overall sequence count tallies normalized by total expressed sequence count to provide expression levels for each gene relative to all treatments as well as Bayesian credible intervals. © The Author 2010. Published by Oxford University Press. All rights reserved.

Stochastic gene expression in Arabidopsis thaliana.

Science.gov (United States)

Araújo, Ilka Schultheiß; Pietsch, Jessica Magdalena; Keizer, Emma Mathilde; Greese, Bettina; Balkunde, Rachappa; Fleck, Christian; Hülskamp, Martin

2017-12-14

Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy gene expression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker gene expression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of gene expression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

Deriving Trading Rules Using Gene Expression Programming

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Adrian VISOIU

2011-01-01

Full Text Available This paper presents how buy and sell trading rules are generated using gene expression programming with special setup. Market concepts are presented and market analysis is discussed with emphasis on technical analysis and quantitative methods. The use of genetic algorithms in deriving trading rules is presented. Gene expression programming is applied in a form where multiple types of operators and operands are used. This gives birth to multiple gene contexts and references between genes in order to keep the linear structure of the gene expression programming chromosome. The setup of multiple gene contexts is presented. The case study shows how to use the proposed gene setup to derive trading rules encoded by Boolean expressions, using a dataset with the reference exchange rates between the Euro and the Romanian leu. The conclusions highlight the positive results obtained in deriving useful trading rules.

Using PCR to Target Misconceptions about Gene Expression

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Leslie K. Wright

2013-02-01

Full Text Available We present a PCR-based laboratory exercise that can be used with first- or second-year biology students to help overcome common misconceptions about gene expression. Biology students typically do not have a clear understanding of the difference between genes (DNA and gene expression (mRNA/protein and often believe that genes exist in an organism or cell only when they are expressed. This laboratory exercise allows students to carry out a PCR-based experiment designed to challenge their misunderstanding of the difference between genes and gene expression. Students first transform E. coli with an inducible GFP gene containing plasmid and observe induced and un-induced colonies. The following exercise creates cognitive dissonance when actual PCR results contradict their initial (incorrect predictions of the presence of the GFP gene in transformed cells. Field testing of this laboratory exercise resulted in learning gains on both knowledge and application questions on concepts related to genes and gene expression.

Differential gene expression during Trypanosoma cruzi metacyclogenesis

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Marco Aurelio Krieger

1999-09-01

Full Text Available The transformation of epimastigotes into metacyclic trypomastigotes involves changes in the pattern of expressed genes, resulting in important morphological and functional differences between these developmental forms of Trypanosoma cruzi. In order to identify and characterize genes involved in triggering the metacyclogenesis process and in conferring to metacyclic trypomastigotes their stage specific biological properties, we have developed a method allowing the isolation of genes specifically expressed when comparing two close related cell populations (representation of differential expression or RDE. The method is based on the PCR amplification of gene sequences selected by hybridizing and subtracting the populations in such a way that after some cycles of hybridization-amplification genes specific to a given population are highly enriched. The use of this method in the analysis of differential gene expression during T. cruzi metacyclogenesis (6 hr and 24 hr of differentiation and metacyclic trypomastigotes resulted in the isolation of several clones from each time point. Northern blot analysis showed that some genes are transiently expressed (6 hr and 24 hr differentiating cells, while others are present in differentiating cells and in metacyclic trypomastigotes. Nucleotide sequencing of six clones characterized so far showed that they do not display any homology to gene sequences available in the GeneBank.

Conditional gene expression in the mouse using a Sleeping Beauty gene-trap transposon

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Hackett Perry B

2006-06-01

Full Text Available Abstract Background Insertional mutagenesis techniques with transposable elements have been popular among geneticists studying model organisms from E. coli to Drosophila and, more recently, the mouse. One such element is the Sleeping Beauty (SB transposon that has been shown in several studies to be an effective insertional mutagen in the mouse germline. SB transposon vector studies have employed different functional elements and reporter molecules to disrupt and report the expression of endogenous mouse genes. We sought to generate a transposon system that would be capable of reporting the expression pattern of a mouse gene while allowing for conditional expression of a gene of interest in a tissue- or temporal-specific pattern. Results Here we report the systematic development and testing of a transposon-based gene-trap system incorporating the doxycycline-repressible Tet-Off (tTA system that is capable of activating the expression of genes under control of a Tet response element (TRE promoter. We demonstrate that the gene trap system is fully functional in vitro by introducing the "gene-trap tTA" vector into human cells by transposition and identifying clones that activate expression of a TRE-luciferase transgene in a doxycycline-dependent manner. In transgenic mice, we mobilize gene-trap tTA vectors, discover parameters that can affect germline mobilization rates, and identify candidate gene insertions to demonstrate the in vivo functionality of the vector system. We further demonstrate that the gene-trap can act as a reporter of endogenous gene expression and it can be coupled with bioluminescent imaging to identify genes with tissue-specific expression patterns. Conclusion Akin to the GAL4/UAS system used in the fly, we have made progress developing a tool for mutating and revealing the expression of mouse genes by generating the tTA transactivator in the presence of a secondary TRE-regulated reporter molecule. A vector like the gene

Analysis of multiplex gene expression maps obtained by voxelation

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Smith Desmond J

2009-04-01

Full Text Available Abstract Background Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. Results To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in

Analysis of multiplex gene expression maps obtained by voxelation.

Science.gov (United States)

An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

2009-04-29

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental

A comparative gene expression database for invertebrates

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Ormestad Mattias

2011-08-01

Full Text Available Abstract Background As whole genome and transcriptome sequencing gets cheaper and faster, a great number of 'exotic' animal models are emerging, rapidly adding valuable data to the ever-expanding Evo-Devo field. All these new organisms serve as a fantastic resource for the research community, but the sheer amount of data, some published, some not, makes detailed comparison of gene expression patterns very difficult to summarize - a problem sometimes even noticeable within a single lab. The need to merge existing data with new information in an organized manner that is publicly available to the research community is now more necessary than ever. Description In order to offer a homogenous way of storing and handling gene expression patterns from a variety of organisms, we have developed the first web-based comparative gene expression database for invertebrates that allows species-specific as well as cross-species gene expression comparisons. The database can be queried by gene name, developmental stage and/or expression domains. Conclusions This database provides a unique tool for the Evo-Devo research community that allows the retrieval, analysis and comparison of gene expression patterns within or among species. In addition, this database enables a quick identification of putative syn-expression groups that can be used to initiate, among other things, gene regulatory network (GRN projects.

Genetic Variants Contribute to Gene Expression Variability in Humans

Science.gov (United States)

Hulse, Amanda M.; Cai, James J.

2013-01-01

Expression quantitative trait loci (eQTL) studies have established convincing relationships between genetic variants and gene expression. Most of these studies focused on the mean of gene expression level, but not the variance of gene expression level (i.e., gene expression variability). In the present study, we systematically explore genome-wide association between genetic variants and gene expression variability in humans. We adapt the double generalized linear model (dglm) to simultaneously fit the means and the variances of gene expression among the three possible genotypes of a biallelic SNP. The genomic loci showing significant association between the variances of gene expression and the genotypes are termed expression variability QTL (evQTL). Using a data set of gene expression in lymphoblastoid cell lines (LCLs) derived from 210 HapMap individuals, we identify cis-acting evQTL involving 218 distinct genes, among which 8 genes, ADCY1, CTNNA2, DAAM2, FERMT2, IL6, PLOD2, SNX7, and TNFRSF11B, are cross-validated using an extra expression data set of the same LCLs. We also identify ∼300 trans-acting evQTL between >13,000 common SNPs and 500 randomly selected representative genes. We employ two distinct scenarios, emphasizing single-SNP and multiple-SNP effects on expression variability, to explain the formation of evQTL. We argue that detecting evQTL may represent a novel method for effectively screening for genetic interactions, especially when the multiple-SNP influence on expression variability is implied. The implication of our results for revealing genetic mechanisms of gene expression variability is discussed. PMID:23150607

Correction of gene expression data

DEFF Research Database (Denmark)

Darbani Shirvanehdeh, Behrooz; Stewart, C. Neal, Jr.; Noeparvar, Shahin

2014-01-01

This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies....... For maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce...

Gene expression in colorectal cancer

DEFF Research Database (Denmark)

Birkenkamp-Demtroder, Karin; Christensen, Lise Lotte; Olesen, Sanne Harder

2002-01-01

Understanding molecular alterations in colorectal cancer (CRC) is needed to define new biomarkers and treatment targets. We used oligonucleotide microarrays to monitor gene expression of about 6,800 known genes and 35,000 expressed sequence tags (ESTs) on five pools (four to six samples in each...... pool) of total RNA from left-sided sporadic colorectal carcinomas. We compared normal tissue to carcinoma tissue from Dukes' stages A-D (noninvasive to distant metastasis) and identified 908 known genes and 4,155 ESTs that changed remarkably from normal to tumor tissue. Based on intensive filtering 226...

Multiscale Embedded Gene Co-expression Network Analysis.

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Won-Min Song

2015-11-01

Full Text Available Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3, the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA by: i introducing quality control of co-expression similarities, ii parallelizing embedded network construction, and iii developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs. We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA. MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

Multiscale Embedded Gene Co-expression Network Analysis.

Science.gov (United States)

Song, Won-Min; Zhang, Bin

2015-11-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

Characterization of transcriptome in the Indian meal moth Plodia interpunctella (Lepidoptera: Pyralidae) and gene expression analysis during developmental stages.

Science.gov (United States)

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.

Maternal Diabetes Alters Expression of MicroRNAs that Regulate Genes Critical for Neural Tube Development

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Seshadri Ramya

2017-07-01

Full Text Available Maternal diabetes is known to cause neural tube defects (NTDs in embryos and neuropsychological deficits in infants. Several metabolic pathways and a plethora of genes have been identified to be deregulated in developing brain of embryos by maternal diabetes, although the exact mechanism remains unknown. Recently, miRNAs have been shown to regulate genes involved in brain development and maturation. Therefore, we hypothesized that maternal diabetes alters the expression of miRNAs that regulate genes involved in biological pathways critical for neural tube development and closure during embryogenesis. To address this, high throughput miRNA expression profiling in neural stem cells (NSCs isolated from the forebrain of embryos from normal or streptozotocin-induced diabetic pregnancy was carried out. It is known that maternal diabetes results in fetal hypoglycemia/hyperglycemia or hypoxia. Hence, NSCs from embryos of control pregnant mice were exposed to low or high glucose or hypoxia in vitro. miRNA pathway analysis revealed distinct deregulation of several biological pathways, including axon guidance pathway, which are critical for brain development in NSCs exposed to different treatments. Among the differentially expressed miRNAs, the miRNA-30 family members which are predicted to target genes involved in brain development was upregulated in NSCs from embryos of diabetic pregnancy when compared to control. miRNA-30b was found to be upregulated while its target gene Sirtuin 1 (Sirt1, as revealed by luciferase assay, was down regulated in NSCs from embryos of diabetic pregnancy. Further, overexpression of miRNA-30b in NSCs, resulted in decreased expression of Sirt1 protein, and altered the neuron/glia ratio. On the other hand, siRNA mediated knockdown of Sirt1 in NSCs promoted astrogenesis, indicating that miRNA-30b alters lineage specification via Sirt1. Overall, these results suggest that maternal diabetes alters the genes involved in neural tube

High-throughput profiling of antibiotic resistance genes in drinking water treatment plants and distribution systems.

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Xu, Like; Ouyang, Weiying; Qian, Yanyun; Su, Chao; Su, Jianqiang; Chen, Hong

2016-06-01

Antibiotic resistance genes (ARGs) are present in surface water and often cannot be completely eliminated by drinking water treatment plants (DWTPs). Improper elimination of the ARG-harboring microorganisms contaminates the water supply and would lead to animal and human disease. Therefore, it is of utmost importance to determine the most effective ways by which DWTPs can eliminate ARGs. Here, we tested water samples from two DWTPs and distribution systems and detected the presence of 285 ARGs, 8 transposases, and intI-1 by utilizing high-throughput qPCR. The prevalence of ARGs differed in the two DWTPs, one of which employed conventional water treatments while the other had advanced treatment processes. The relative abundance of ARGs increased significantly after the treatment with biological activated carbon (BAC), raising the number of detected ARGs from 76 to 150. Furthermore, the final chlorination step enhanced the relative abundance of ARGs in the finished water generated from both DWTPs. The total enrichment of ARGs varied from 6.4-to 109.2-fold in tap water compared to finished water, among which beta-lactam resistance genes displayed the highest enrichment. Six transposase genes were detected in tap water samples, with the transposase gene TnpA-04 showing the greatest enrichment (up to 124.9-fold). We observed significant positive correlations between ARGs and mobile genetic elements (MGEs) during the distribution systems, indicating that transposases and intI-1 may contribute to antibiotic resistance in drinking water. To our knowledge, this is the first study to investigate the diversity and abundance of ARGs in drinking water treatment systems utilizing high-throughput qPCR techniques in China. Copyright © 2016 Elsevier Ltd. All rights reserved.

Vascular Gene Expression: A Hypothesis

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Angélica Concepción eMartínez-Navarro

2013-07-01

Full Text Available The phloem is the conduit through which photoassimilates are distributed from autotrophic to heterotrophic tissues and is involved in the distribution of signaling molecules that coordinate plant growth and responses to the environment. Phloem function depends on the coordinate expression of a large array of genes. We have previously identified conserved motifs in upstream regions of the Arabidopsis genes, encoding the homologs of pumpkin phloem sap mRNAs, displaying expression in vascular tissues. This tissue-specific expression in Arabidopsis is predicted by the overrepresentation of GA/CT-rich motifs in gene promoters. In this work we have searched for common motifs in upstream regions of the homologous genes from plants considered to possess a primitive vascular tissue (a lycophyte, as well as from others that lack a true vascular tissue (a bryophyte, and finally from chlorophytes. Both lycophyte and bryophyte display motifs similar to those found in Arabidopsis with a significantly low E-value, while the chlorophytes showed either a different conserved motif or no conserved motif at all. These results suggest that these same genes are expressed coordinately in non- vascular plants; this coordinate expression may have been one of the prerequisites for the development of conducting tissues in plants. We have also analyzed the phylogeny of conserved proteins that may be involved in phloem function and development. The presence of CmPP16, APL, FT and YDA in chlorophytes suggests the recruitment of ancient regulatory networks for the development of the vascular tissue during evolution while OPS is a novel protein specific to vascular plants.

GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

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Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

2018-01-01

When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

The evolution of gene expression in primates

OpenAIRE

Tashakkori Ghanbarian, Avazeh

2015-01-01

The evolution of a gene’s expression profile is commonly assumed to be independent of its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between expression of neighboring genes in extant taxa. Indeed, in all eukaryotic genomes, genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their e...

MeSH key terms for validation and annotation of gene expression clusters

Energy Technology Data Exchange (ETDEWEB)

Rechtsteiner, A. (Andreas); Rocha, L. M. (Luis Mateus)

2004-01-01

Integration of different sources of information is a great challenge for the analysis of gene expression data, and for the field of Functional Genomics in general. As the availability of numerical data from high-throughput methods increases, so does the need for technologies that assist in the validation and evaluation of the biological significance of results extracted from these data. In mRNA assaying with microarrays, for example, numerical analysis often attempts to identify clusters of co-expressed genes. The important task to find the biological significance of the results and validate them has so far mostly fallen to the biological expert who had to perform this task manually. One of the most promising avenues to develop automated and integrative technology for such tasks lies in the application of modern Information Retrieval (IR) and Knowledge Management (KM) algorithms to databases with biomedical publications and data. Examples of databases available for the field are bibliographic databases c ntaining scientific publications (e.g. MEDLINE/PUBMED), databases containing sequence data (e.g. GenBank) and databases of semantic annotations (e.g. the Gene Ontology Consortium and Medical Subject Headings (MeSH)). We present here an approach that uses the MeSH terms and their concept hierarchies to validate and obtain functional information for gene expression clusters. The controlled and hierarchical MeSH vocabulary is used by the National Library of Medicine (NLM) to index all the articles cited in MEDLINE. Such indexing with a controlled vocabulary eliminates some of the ambiguity due to polysemy (terms that have multiple meanings) and synonymy (multiple terms have similar meaning) that would be encountered if terms would be extracted directly from the articles due to differing article contexts or author preferences and background. Further, the hierarchical organization of the MeSH terms can illustrate the conceptuallfunctional relationships of genes

Reduced expression of Autographa californica nucleopolyhedrovirus ORF34, an essential gene, enhances heterologous gene expression

International Nuclear Information System (INIS)

Salem, Tamer Z.; Zhang, Fengrui; Thiem, Suzanne M.

2013-01-01

Autographa californica multiple nucleopolyhedrovirus ORF34 is part of a transcriptional unit that includes ORF32, encoding a viral fibroblast growth factor (FGF) and ORF33. We identified ORF34 as a candidate for deletion to improve protein expression in the baculovirus expression system based on enhanced reporter gene expression in an RNAi screen of virus genes. However, ORF34 was shown to be an essential gene. To explore ORF34 function, deletion (KO34) and rescue bacmids were constructed and characterized. Infection did not spread from primary KO34 transfected cells and supernatants from KO34 transfected cells could not infect fresh Sf21 cells whereas the supernatant from the rescue bacmids transfection could recover the infection. In addition, budded viruses were not observed in KO34 transfected cells by electron microscopy, nor were viral proteins detected from the transfection supernatants by western blots. These demonstrate that ORF34 is an essential gene with a possible role in infectious virus production.

Reduced expression of Autographa californica nucleopolyhedrovirus ORF34, an essential gene, enhances heterologous gene expression

Energy Technology Data Exchange (ETDEWEB)

Salem, Tamer Z. [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Department of Microbial Molecular Biology, AGERI, Agricultural Research Center, Giza 12619 (Egypt); Division of Biomedical Sciences, Zewail University, Zewail City of Science and Technology, Giza 12588 (Egypt); Zhang, Fengrui [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Thiem, Suzanne M., E-mail: smthiem@msu.edu [Department of Entomology, Michigan State University, East Lansing, MI 48824 (United States); Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824 (United States)

2013-01-20

Autographa californica multiple nucleopolyhedrovirus ORF34 is part of a transcriptional unit that includes ORF32, encoding a viral fibroblast growth factor (FGF) and ORF33. We identified ORF34 as a candidate for deletion to improve protein expression in the baculovirus expression system based on enhanced reporter gene expression in an RNAi screen of virus genes. However, ORF34 was shown to be an essential gene. To explore ORF34 function, deletion (KO34) and rescue bacmids were constructed and characterized. Infection did not spread from primary KO34 transfected cells and supernatants from KO34 transfected cells could not infect fresh Sf21 cells whereas the supernatant from the rescue bacmids transfection could recover the infection. In addition, budded viruses were not observed in KO34 transfected cells by electron microscopy, nor were viral proteins detected from the transfection supernatants by western blots. These demonstrate that ORF34 is an essential gene with a possible role in infectious virus production.

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

Energy Technology Data Exchange (ETDEWEB)

Rodland, Karin D.; Adkins, Joshua N.; Ansong, Charles; Chowdhury, Saiful M.; Manes, Nathan P.; Shi, Liang; Yoon, Hyunjin; Smith, Richard D.; Heffron, Fred

2008-12-01

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 findings 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.

Widespread ectopic expression of olfactory receptor genes

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Yanai Itai

2006-05-01

Full Text Available Abstract Background Olfactory receptors (ORs are the largest gene family in the human genome. Although they are expected to be expressed specifically in olfactory tissues, some ectopic expression has been reported, with special emphasis on sperm and testis. The present study systematically explores the expression patterns of OR genes in a large number of tissues and assesses the potential functional implication of such ectopic expression. Results We analyzed the expression of hundreds of human and mouse OR transcripts, via EST and microarray data, in several dozens of human and mouse tissues. Different tissues had specific, relatively small OR gene subsets which had particularly high expression levels. In testis, average expression was not particularly high, and very few highly expressed genes were found, none corresponding to ORs previously implicated in sperm chemotaxis. Higher expression levels were more common for genes with a non-OR genomic neighbor. Importantly, no correlation in expression levels was detected for human-mouse orthologous pairs. Also, no significant difference in expression levels was seen between intact and pseudogenized ORs, except for the pseudogenes of subfamily 7E which has undergone a human-specific expansion. Conclusion The OR superfamily as a whole, show widespread, locus-dependent and heterogeneous expression, in agreement with a neutral or near neutral evolutionary model for transcription control. These results cannot reject the possibility that small OR subsets might play functional roles in different tissues, however considerable care should be exerted when offering a functional interpretation for ectopic OR expression based only on transcription information.

Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

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Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

2013-01-01

The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

Differential Gene Expression Profiling of Dystrophic Dog Muscle after MuStem Cell Transplantation

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Babarit, Candice; Larcher, Thibaut; Dubreil, Laurence; Leroux, Isabelle; Zuber, Céline; Ledevin, Mireille; Deschamps, Jack-Yves; Fromes, Yves; Cherel, Yan; Guevel, Laetitia; Rouger, Karl

2015-01-01

Background Several adult stem cell populations exhibit myogenic regenerative potential, thus representing attractive candidates for therapeutic approaches of neuromuscular diseases such as Duchenne Muscular Dystrophy (DMD). We have recently shown that systemic delivery of MuStem cells, skeletal muscle-resident stem cells isolated in healthy dog, generates the remodelling of muscle tissue and gives rise to striking clinical benefits in Golden Retriever Muscular Dystrophy (GRMD) dog. This global effect, which is observed in the clinically relevant DMD animal model, leads us to question here the molecular pathways that are impacted by MuStem cell transplantation. To address this issue, we compare the global gene expression profile between healthy, GRMD and MuStem cell treated GRMD dog muscle, four months after allogenic MuStem cell transplantation. Results In the dystrophic context of the GRMD dog, disease-related deregulation is observed in the case of 282 genes related to various processes such as inflammatory response, regeneration, calcium ion binding, extracellular matrix organization, metabolism and apoptosis regulation. Importantly, we reveal the impact of MuStem cell transplantation on several molecular and cellular pathways based on a selection of 31 genes displaying signals specifically modulated by the treatment. Concomitant with a diffuse dystrophin expression, a histological remodelling and a stabilization of GRMD dog clinical status, we show that cell delivery is associated with an up-regulation of genes reflecting a sustained enhancement of muscle regeneration. We also identify a decreased mRNA expression of a set of genes having metabolic functions associated with lipid homeostasis and energy. Interestingly, ubiquitin-mediated protein degradation is highly enhanced in GRMD dog muscle after systemic delivery of MuStem cells. Conclusions Overall, our results provide the first high-throughput characterization of GRMD dog muscle and throw new light on the

Dynamic association rules for gene expression data analysis.

Science.gov (United States)

Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

2015-10-14

The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed

Gene expression in periodontal tissues following treatment

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Eisenacher Martin

2008-07-01

Full Text Available Abstract Background In periodontitis, treatment aimed at controlling the periodontal biofilm infection results in a resolution of the clinical and histological signs of inflammation. Although the cell types found in periodontal tissues following treatment have been well described, information on gene expression is limited to few candidate genes. Therefore, the aim of the study was to determine the expression profiles of immune and inflammatory genes in periodontal tissues from sites with severe chronic periodontitis following periodontal therapy in order to identify genes involved in tissue homeostasis. Gingival biopsies from 12 patients with severe chronic periodontitis were taken six to eight weeks following non-surgical periodontal therapy, and from 11 healthy controls. As internal standard, RNA of an immortalized human keratinocyte line (HaCaT was used. Total RNA was subjected to gene expression profiling using a commercially available microarray system focusing on inflammation-related genes. Post-hoc confirmation of selected genes was done by Realtime-PCR. Results Out of the 136 genes analyzed, the 5% most strongly expressed genes compared to healthy controls were Interleukin-12A (IL-12A, Versican (CSPG-2, Matrixmetalloproteinase-1 (MMP-1, Down syndrome critical region protein-1 (DSCR-1, Macrophage inflammatory protein-2β (Cxcl-3, Inhibitor of apoptosis protein-1 (BIRC-1, Cluster of differentiation antigen 38 (CD38, Regulator of G-protein signalling-1 (RGS-1, and Finkel-Biskis-Jinkins murine osteosarcoma virus oncogene (C-FOS; the 5% least strongly expressed genes were Receptor-interacting Serine/Threonine Kinase-2 (RIP-2, Complement component 3 (C3, Prostaglandin-endoperoxide synthase-2 (COX-2, Interleukin-8 (IL-8, Endothelin-1 (EDN-1, Plasminogen activator inhibitor type-2 (PAI-2, Matrix-metalloproteinase-14 (MMP-14, and Interferon regulating factor-7 (IRF-7. Conclusion Gene expression profiles found in periodontal tissues following

Predicting Recurrence and Progression of Noninvasive Papillary Bladder Cancer at Initial Presentation Based on Quantitative Gene Expression Profiles

DEFF Research Database (Denmark)

Birkhahn, M.; Mitra, A.P.; Williams, Johan

2010-01-01

% specificity. Since this is a small retrospective study using medium-throughput profiling, larger confirmatory studies are needed. Conclusions: Gene expression profiling across relevant cancer pathways appears to be a promising approach for Ta bladder tumor outcome prediction at initial diagnosis......Background: Currently, tumor grade is the best predictor of outcome at first presentation of noninvasive papillary (Ta) bladder cancer. However, reliable predictors of Ta tumor recurrence and progression for individual patients, which could optimize treatment and follow-up schedules based...... on specific tumor biology, are yet to be identified. Objective: To identify genes predictive for recurrence and progression in Ta bladder cancer at first presentation using a quantitative, pathway-specific approach. Design, setting, and participants: Retrospective study of patients with Ta G2/3 bladder tumors...

Unveiling network-based functional features through integration of gene expression into protein networks.

Science.gov (United States)

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

Transcriptome analysis of paired primary colorectal carcinoma and liver metastases reveals fusion transcripts and similar gene expression profiles in primary carcinoma and liver metastases

International Nuclear Information System (INIS)

Lee, Ja-Rang; Kwon, Chae Hwa; Choi, Yuri; Park, Hye Ji; Kim, Hyun Sung; Jo, Hong-Jae; Oh, Nahmgun; Park, Do Youn

2016-01-01

Despite the clinical significance of liver metastases, the difference between molecular and cellular changes in primary colorectal cancers (CRC) and matched liver metastases is poorly understood. In order to compare gene expression patterns and identify fusion genes in these two types of tumors, we performed high-throughput transcriptome sequencing of five sets of quadruple-matched tissues (primary CRC, liver metastases, normal colon, and liver). The gene expression patterns in normal colon and liver were successfully distinguished from those in CRCs; however, RNA sequencing revealed that the gene expression between primary CRCs and their matched liver metastases is highly similar. We identified 1895 genes that were differentially expressed in the primary carcinoma and liver metastases, than that in the normal colon tissues. A major proportion of the transcripts, identified by gene expression profiling as significantly enriched in the primary carcinoma and metastases, belonged to gene ontology categories involved in the cell cycle, mitosis, and cell division. Furthermore, we identified gene fusion events in primary carcinoma and metastases, and the fusion transcripts were experimentally confirmed. Among these, a chimeric transcript resulting from the fusion of RNF43 and SUPT4H1 was found to occur frequently in primary colorectal carcinoma. In addition, knockdown of the expression of this RNF43-SUPT4H1 chimeric transcript was found to have a growth-inhibitory effect in colorectal cancer cells. The present study reports a high concordance of gene expression in the primary carcinoma and liver metastases, and reveals potential new targets, such as fusion genes, against primary and metastatic colorectal carcinoma. The online version of this article (doi:10.1186/s12885-016-2596-3) contains supplementary material, which is available to authorized users

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

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Du Peige

2008-10-01

Full Text Available Abstract 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.

Significant differences in gene expression and key genetic components associated with high growth vigor in populus section tacamahaca as revealed by comparative transcriptome analysis

International Nuclear Information System (INIS)

Cheng, S.; Chen, M.; Li, Y.; Wang, J.; Sun, X.; Wang, J.

2017-01-01

To identify genetic components involved in high growth vigor in F1 Populus section Tacamahaca hybrid plants, high and low vigor plants showing significant differences in apical dominance during a rapid growth period were selected. Apical bud transcriptomes of high and low-growth-vigor hybrids and their parents were analyzed using high-throughput RNA sequencing on an Illumina HiSeq 2000 platform. A total of 5,542 genes were differently expressed between high growth vigor hybrid and its parents, the genes were significantly enriched in pathways related to processes such as photosynthesis, pyrimidine ribonucleotide biosynthetic processes and nucleoside metabolic processes. There were 1410 differentially expressed genes between high and low growth vigor hybrid, the genes were mainly involved in photosynthesis, chlorophyll biosynthetic process, carbon fixation in photosynthetic organisms, porphyrin and chlorophyll metabolism and nitrogen metabolism. Moreover, a k-core of a gene co-expression network analysis was performed to identify the potential functions of genes related to high growth vigor. The functions of 8 selected candidate genes were associated mainly with circadian rhythm, water transport, cellulose catabolic processes, sucrose biosynthesis, pyrimidine ribonucleotide biosynthesis, purine nucleotide biosynthesis, meristem maintenance, and carbohydrate metabolism. Our results may contribute to a better understanding of the molecular basis of high growth vigor in hybrids and its regulation. (author)

Gene expression profiles in skeletal muscle after gene electrotransfer

DEFF Research Database (Denmark)

Hojman, Pernille; Zibert, John R; Gissel, Hanne

2007-01-01

BACKGROUND: Gene transfer by electroporation (DNA electrotransfer) to muscle results in high level long term transgenic expression, showing great promise for treatment of e.g. protein deficiency syndromes. However little is known about the effects of DNA electrotransfer on muscle fibres. We have...... caused down-regulation of structural proteins e.g. sarcospan and catalytic enzymes. Injection of DNA induced down-regulation of intracellular transport proteins e.g. sentrin. The effects on muscle fibres were transient as the expression profiles 3 weeks after treatment were closely related......) followed by a long low voltage pulse (LV, 100 V/cm, 400 ms); a pulse combination optimised for efficient and safe gene transfer. Muscles were transfected with green fluorescent protein (GFP) and excised at 4 hours, 48 hours or 3 weeks after treatment. RESULTS: Differentially expressed genes were...

Comparative gene expression between two yeast species

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Guan Yuanfang

2013-01-01

Full Text Available Abstract Background Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository. Results In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species gene expression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences. Conclusions Taken together, these analyses provide a global view of gene expression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.

Management of High-Throughput DNA Sequencing Projects: Alpheus.

Science.gov (United States)

Miller, Neil A; Kingsmore, Stephen F; Farmer, Andrew; Langley, Raymond J; Mudge, Joann; Crow, John A; Gonzalez, Alvaro J; Schilkey, Faye D; Kim, Ryan J; van Velkinburgh, Jennifer; May, Gregory D; Black, C Forrest; Myers, M Kathy; Utsey, John P; Frost, Nicholas S; Sugarbaker, David J; Bueno, Raphael; Gullans, Stephen R; Baxter, Susan M; Day, Steve W; Retzel, Ernest F

2008-12-26

High-throughput DNA sequencing has enabled systems biology to begin to address areas in health, agricultural and basic biological research. Concomitant with the opportunities is an absolute necessity to manage significant volumes of high-dimensional and inter-related data and analysis. Alpheus is an analysis pipeline, database and visualization software for use with massively parallel DNA sequencing technologies that feature multi-gigabase throughput characterized by relatively short reads, such as Illumina-Solexa (sequencing-by-synthesis), Roche-454 (pyrosequencing) and Applied Biosystem's SOLiD (sequencing-by-ligation). Alpheus enables alignment to reference sequence(s), detection of variants and enumeration of sequence abundance, including expression levels in transcriptome sequence. Alpheus is able to detect several types of variants, including non-synonymous and synonymous single nucleotide polymorphisms (SNPs), insertions/deletions (indels), premature stop codons, and splice isoforms. Variant detection is aided by the ability to filter variant calls based on consistency, expected allele frequency, sequence quality, coverage, and variant type in order to minimize false positives while maximizing the identification of true positives. Alpheus also enables comparisons of genes with variants between cases and controls or bulk segregant pools. Sequence-based differential expression comparisons can be developed, with data export to SAS JMP Genomics for statistical analysis.

Digital gene expression analysis based on integrated de novo transcriptome assembly of sweet potato [Ipomoea batatas (L. Lam].

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Xiang Tao

Full Text Available BACKGROUND: Sweet potato (Ipomoea batatas L. [Lam.] ranks among the top six most important food crops in the world. It is widely grown throughout the world with high and stable yield, strong adaptability, rich nutrient content, and multiple uses. However, little is known about the molecular biology of this important non-model organism due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to get a comprehensive and integrated genomic resource and better understanding of gene expression patterns in different tissues and at various developmental stages. METHODOLOGY/PRINCIPAL FINDINGS: Illumina paired-end (PE RNA-Sequencing was performed, and generated 48.7 million of 75 bp PE reads. These reads were de novo assembled into 128,052 transcripts (≥ 100 bp, which correspond to 41.1 million base pairs, by using a combined assembly strategy. Transcripts were annotated by Blast2GO and 51,763 transcripts got BLASTX hits, in which 39,677 transcripts have GO terms and 14,117 have ECs that are associated with 147 KEGG pathways. Furthermore, transcriptome differences of seven tissues were analyzed by using Illumina digital gene expression (DGE tag profiling and numerous differentially and specifically expressed transcripts were identified. Moreover, the expression characteristics of genes involved in viral genomes, starch metabolism and potential stress tolerance and insect resistance were also identified. CONCLUSIONS/SIGNIFICANCE: The combined de novo transcriptome assembly strategy can be applied to other organisms whose reference genomes are not available. The data provided here represent the most comprehensive and integrated genomic resources for cloning and identifying genes of interest in sweet potato. Characterization of sweet potato transcriptome provides an effective tool for better understanding the molecular mechanisms of cellular processes including development of leaves and storage roots

Interactive visualization of gene regulatory networks with associated gene expression time series data

NARCIS (Netherlands)

Westenberg, M.A.; Hijum, van S.A.F.T.; Lulko, A.T.; Kuipers, O.P.; Roerdink, J.B.T.M.; Linsen, L.; Hagen, H.; Hamann, B.

2008-01-01

We present GENeVis, an application to visualize gene expression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes,

Serial analysis of gene expression (SAGE)

NARCIS (Netherlands)

van Ruissen, Fred; Baas, Frank

2007-01-01

In 1995, serial analysis of gene expression (SAGE) was developed as a versatile tool for gene expression studies. SAGE technology does not require pre-existing knowledge of the genome that is being examined and therefore SAGE can be applied to many different model systems. In this chapter, the SAGE

An Interactive Database of Cocaine-Responsive Gene Expression

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Willard M. Freeman

2002-01-01

Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

CDX2 gene expression in acute lymphoblastic leukemia

International Nuclear Information System (INIS)

Arnaoaut, H.H.; Mokhtar, D.A.; Samy, R.M.; Omar, Sh.A.; Khames, S.A.

2014-01-01

CDX genes are classically known as regulators of axial elongation during early embryogenesis. An unsuspected role for CDX genes has been revealed during hematopoietic development. The CDX gene family member CDX2 belongs to the most frequent aberrantly expressed proto-oncogenes in human acute leukemias and is highly leukemogenic in experimental models. We used reversed transcriptase polymerase chain reaction (RT-PCR) to determine the expression level of CDX2 gene in 30 pediatric patients with acute lymphoblastic leukemia (ALL) at diagnosis and 30 healthy volunteers. ALL patients were followed up to detect minimal residual disease (MRD) on days 15 and 42 of induction. We found that CDX2 gene was expressed in 50% of patients and not expressed in controls. Associations between gene expression and different clinical and laboratory data of patients revealed no impact on different findings. With follow up, we could not confirm that CDX2 expression had a prognostic significance.

Identification of reference genes in human myelomonocytic cells for gene expression studies in altered gravity.

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Thiel, Cora S; Hauschild, Swantje; Tauber, Svantje; Paulsen, Katrin; Raig, Christiane; Raem, Arnold; Biskup, Josefine; Gutewort, Annett; Hürlimann, Eva; Unverdorben, Felix; Buttron, Isabell; Lauber, Beatrice; Philpot, Claudia; Lier, Hartwin; Engelmann, Frank; Layer, Liliana E; Ullrich, Oliver

2015-01-01

Gene expression studies are indispensable for investigation and elucidation of molecular mechanisms. For the process of normalization, reference genes ("housekeeping genes") are essential to verify gene expression analysis. Thus, it is assumed that these reference genes demonstrate similar expression levels over all experimental conditions. However, common recommendations about reference genes were established during 1 g conditions and therefore their applicability in studies with altered gravity has not been demonstrated yet. The microarray technology is frequently used to generate expression profiles under defined conditions and to determine the relative difference in expression levels between two or more different states. In our study, we searched for potential reference genes with stable expression during different gravitational conditions (microgravity, normogravity, and hypergravity) which are additionally not altered in different hardware systems. We were able to identify eight genes (ALB, B4GALT6, GAPDH, HMBS, YWHAZ, ABCA5, ABCA9, and ABCC1) which demonstrated no altered gene expression levels in all tested conditions and therefore represent good candidates for the standardization of gene expression studies in altered gravity.

Inferring gene networks from discrete expression data

KAUST Repository

Zhang, L.

2013-07-18

The modeling of gene networks from transcriptional expression data is an important tool in biomedical research to reveal signaling pathways and to identify treatment targets. Current gene network modeling is primarily based on the use of Gaussian graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which generate counts of mRNAtranscripts in cell samples.We propose a generalized linear model to fit the discrete gene expression data and assume that the log ratios of the mean expression levels follow a Gaussian distribution.We restrict the gene network structures to decomposable graphs and derive the graphs by selecting the covariance matrix of the Gaussian distribution with the hyper-inverse Wishart priors. Furthermore, we incorporate prior network models based on gene ontology information, which avails existing biological information on the genes of interest. We conduct simulation studies to examine the performance of our discrete graphical model and apply the method to two real datasets for gene network inference. © The Author 2013. Published by Oxford University Press. All rights reserved.

LncRNA Expression Profile of Human Thoracic Aortic Dissection by High-Throughput Sequencing.

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Sun, Jie; Chen, Guojun; Jing, Yuanwen; He, Xiang; Dong, Jianting; Zheng, Junmeng; Zou, Meisheng; Li, Hairui; Wang, Shifei; Sun, Yili; Liao, Wangjun; Liao, Yulin; Feng, Li; Bin, Jianping

2018-01-01

In this study, the long non-coding RNA (lncRNA) expression profile in human thoracic aortic dissection (TAD), a highly lethal cardiovascular disease, was investigated. Human TAD (n=3) and normal aortic tissues (NA) (n=3) were examined by high-throughput sequencing. Bioinformatics analyses were performed to predict the roles of aberrantly expressed lncRNAs. Quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the results. A total of 269 lncRNAs (159 up-regulated and 110 down-regulated) and 2, 255 mRNAs (1 294 up-regulated and 961 down-regulated) were aberrantly expressed in human TAD (fold-change> 1.5, PTAD than in NA. The predicted binding motifs of three up-regulated lncRNAs (ENSG00000248508, ENSG00000226530, and EG00000259719) were correlated with up-regulated RUNX1 (R=0.982, PTAD. These findings suggest that lncRNAs are novel potential therapeutic targets for human TAD. © 2018 The Author(s). Published by S. Karger AG, Basel.

Reference Gene Screening for Analyzing Gene Expression Across Goat Tissue

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Yu Zhang

2013-12-01

Full Text Available Real-time quantitative PCR (qRT-PCR is one of the important methods for investigating the changes in mRNA expression levels in cells and tissues. Selection of the proper reference genes is very important when calibrating the results of real-time quantitative PCR. Studies on the selection of reference genes in goat tissues are limited, despite the economic importance of their meat and dairy products. We used real-time quantitative PCR to detect the expression levels of eight reference gene candidates (18S, TBP, HMBS, YWHAZ, ACTB, HPRT1, GAPDH and EEF1A2 in ten tissues types sourced from Boer goats. The optimal reference gene combination was selected according to the results determined by geNorm, NormFinder and Bestkeeper software packages. The analyses showed that tissue is an important variability factor in genes expression stability. When all tissues were considered, 18S, TBP and HMBS is the optimal reference combination for calibrating quantitative PCR analysis of gene expression from goat tissues. Dividing data set by tissues, ACTB was the most stable in stomach, small intestine and ovary, 18S in heart and spleen, HMBS in uterus and lung, TBP in liver, HPRT1 in kidney and GAPDH in muscle. Overall, this study provided valuable information about the goat reference genes that can be used in order to perform a proper normalisation when relative quantification by qRT-PCR studies is undertaken.

Studying the Complex Expression Dependences between Sets of Coexpressed Genes

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Mario Huerta

2014-01-01

Full Text Available Organisms simplify the orchestration of gene expression by coregulating genes whose products function together in the cell. The use of clustering methods to obtain sets of coexpressed genes from expression arrays is very common; nevertheless there are no appropriate tools to study the expression networks among these sets of coexpressed genes. The aim of the developed tools is to allow studying the complex expression dependences that exist between sets of coexpressed genes. For this purpose, we start detecting the nonlinear expression relationships between pairs of genes, plus the coexpressed genes. Next, we form networks among sets of coexpressed genes that maintain nonlinear expression dependences between all of them. The expression relationship between the sets of coexpressed genes is defined by the expression relationship between the skeletons of these sets, where this skeleton represents the coexpressed genes with a well-defined nonlinear expression relationship with the skeleton of the other sets. As a result, we can study the nonlinear expression relationships between a target gene and other sets of coexpressed genes, or start the study from the skeleton of the sets, to study the complex relationships of activation and deactivation between the sets of coexpressed genes that carry out the different cellular processes present in the expression experiments.

Tackling heterogeneity: a leaf disc-based assay for the high-throughput screening of transient gene expression in tobacco.

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Natalia Piotrzkowski

Full Text Available Transient Agrobacterium-mediated gene expression assays for Nicotiana tabacum (N. tabacum are frequently used because they facilitate the comparison of multiple expression constructs regarding their capacity for maximum recombinant protein production. However, for three model proteins, we found that recombinant protein accumulation (rpa was significantly influenced by leaf age and leaf position effects. The ratio between the highest and lowest amount of protein accumulation (max/min ratio was found to be as high as 11. Therefore, construct-based impacts on the rpa level that are less than 11-fold will be masked by background noise. To address this problem, we developed a leaf disc-based screening assay and infiltration device that allows the rpa level in a whole tobacco plant to be reliably and reproducibly determined. The prototype of the leaf disc infiltration device allows 14 Agrobacterium-mediated infiltration events to be conducted in parallel. As shown for three model proteins, the average max/min rpa ratio was reduced to 1.4 using this method, which allows for a sensitive comparison of different genetic elements affecting recombinant protein expression.

Gene expression of the mismatch repair gene MSH2 in primary colorectal cancer

DEFF Research Database (Denmark)

Jensen, Lars Henrik; Kuramochi, Hidekazu; Crüger, Dorthe Gylling

2011-01-01

promoter was only detected in 14 samples and only at a low level with no correlation to gene expression. MSH2 gene expression was not a prognostic factor for overall survival in univariate or multivariate analysis. The gene expression of MSH2 is a potential quantitative marker ready for further clinical...

Discovery of precursor and mature microRNAs and their putative gene targets using high-throughput sequencing in pineapple (Ananas comosus var. comosus).

Science.gov (United States)

Yusuf, Noor Hydayaty Md; Ong, Wen Dee; Redwan, Raimi Mohamed; Latip, Mariam Abd; Kumar, S Vijay

2015-10-15

MicroRNAs (miRNAs) are a class of small, endogenous non-coding RNAs that negatively regulate gene expression, resulting in the silencing of target mRNA transcripts through mRNA cleavage or translational inhibition. MiRNAs play significant roles in various biological and physiological processes in plants. However, the miRNA-mediated gene regulatory network in pineapple, the model tropical non-climacteric fruit, remains largely unexplored. Here, we report a complete list of pineapple mature miRNAs obtained from high-throughput small RNA sequencing and precursor miRNAs (pre-miRNAs) obtained from ESTs. Two small RNA libraries were constructed from pineapple fruits and leaves, respectively, using Illumina's Solexa technology. Sequence similarity analysis using miRBase revealed 579,179 reads homologous to 153 miRNAs from 41 miRNA families. In addition, a pineapple fruit transcriptome library consisting of approximately 30,000 EST contigs constructed using Solexa sequencing was used for the discovery of pre-miRNAs. In all, four pre-miRNAs were identified (MIR156, MIR399, MIR444 and MIR2673). Furthermore, the same pineapple transcriptome was used to dissect the function of the miRNAs in pineapple by predicting their putative targets in conjunction with their regulatory networks. In total, 23 metabolic pathways were found to be regulated by miRNAs in pineapple. The use of high-throughput sequencing in pineapples to unveil the presence of miRNAs and their regulatory pathways provides insight into the repertoire of miRNA regulation used exclusively in this non-climacteric model plant. Copyright © 2015 Elsevier B.V. All rights reserved.

Heat Stress and Lipopolysaccharide Stimulation of Chicken Macrophage-Like Cell Line Activates Expression of Distinct Sets of Genes.

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Anna Slawinska

Full Text Available Acute heat stress requires immediate adjustment of the stressed individual to sudden changes of ambient temperatures. Chickens are particularly sensitive to heat stress due to development of insufficient physiological mechanisms to mitigate its effects. One of the symptoms of heat stress is endotoxemia that results from release of the lipopolysaccharide (LPS from the guts. Heat-related cytotoxicity is mitigated by the innate immune system, which is comprised mostly of phagocytic cells such as monocytes and macrophages. The objective of this study was to analyze the molecular responses of the chicken macrophage-like HD11 cell line to combined heat stress and lipopolysaccharide treatment in vitro. The cells were heat-stressed and then allowed a temperature-recovery period, during which the gene expression was investigated. LPS was added to the cells to mimic the heat-stress-related endotoxemia. Semi high-throughput gene expression analysis was used to study a gene panel comprised of heat shock proteins, stress-related genes, signaling molecules and immune response genes. HD11 cell line responded to heat stress with increased mRNA abundance of the HSP25, HSPA2 and HSPH1 chaperones as well as DNAJA4 and DNAJB6 co-chaperones. The anti-apoptotic gene BAG3 was also highly up-regulated, providing evidence that the cells expressed pro-survival processes. The immune response of the HD11 cell line to LPS in the heat stress environment (up-regulation of CCL4, CCL5, IL1B, IL8 and iNOS was higher than in thermoneutral conditions. However, the peak in the transcriptional regulation of the immune genes was after two hours of temperature-recovery. Therefore, we propose the potential influence of the extracellular heat shock proteins not only in mitigating effects of abiotic stress but also in triggering the higher level of the immune responses. Finally, use of correlation networks for the data analysis aided in discovering subtle differences in the gene

The relationship among gene expression, the evolution of gene dosage, and the rate of protein evolution.

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Jean-François Gout

2010-05-01

Full Text Available The understanding of selective constraints affecting genes is a major issue in biology. It is well established that gene expression level is a major determinant of the rate of protein evolution, but the reasons for this relationship remain highly debated. Here we demonstrate that gene expression is also a major determinant of the evolution of gene dosage: the rate of gene losses after whole genome duplications in the Paramecium lineage is negatively correlated to the level of gene expression, and this relationship is not a byproduct of other factors known to affect the fate of gene duplicates. This indicates that changes in gene dosage are generally more deleterious for highly expressed genes. This rule also holds for other taxa: in yeast, we find a clear relationship between gene expression level and the fitness impact of reduction in gene dosage. To explain these observations, we propose a model based on the fact that the optimal expression level of a gene corresponds to a trade-off between the benefit and cost of its expression. This COSTEX model predicts that selective pressure against mutations changing gene expression level or affecting the encoded protein should on average be stronger in highly expressed genes and hence that both the frequency of gene loss and the rate of protein evolution should correlate negatively with gene expression. Thus, the COSTEX model provides a simple and common explanation for the general relationship observed between the level of gene expression and the different facets of gene evolution.

Human Mesenchymal Stem Cell Treatment Normalizes Cortical Gene Expression after Traumatic Brain Injury.

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Darkazalli, Ali; Vied, Cynthia; Badger, Crystal-Dawn; Levenson, Cathy W

2017-01-01

Traumatic brain injury (TBI) results in a progressive disease state with many adverse and long-term neurological consequences. Mesenchymal stem cells (MSCs) have emerged as a promising cytotherapy and have been previously shown to reduce secondary apoptosis and cognitive deficits associated with TBI. Consistent with the established literature, we observed that systemically administered human MSCs (hMSCs) accumulate with high specificity at the TBI lesion boundary zone known as the penumbra. Substantial work has been done to illuminate the mechanisms by which MSCs, and the bioactive molecules they secrete, exert their therapeutic effect. However, no such work has been published to examine the effect of MSC treatment on gene expression in the brain post-TBI. In the present study, we use high-throughput RNA sequencing (RNAseq) of cortical tissue from the TBI penumbra to assess the molecular effects of both TBI and subsequent treatment with intravenously delivered hMSCs. RNAseq revealed that expression of almost 7000 cortical genes in the penumbra were differentially regulated by TBI. Pathway analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway database revealed that TBI regulated a large number of genes belonging to pathways involved in metabolism, receptor-mediated cell signaling, neuronal plasticity, immune cell recruitment and infiltration, and neurodegenerative disease. Remarkably, hMSC treatment was found to normalize 49% of all genes disrupted by TBI, with notably robust normalization of specific pathways within the categories mentioned above, including neuroactive receptor-ligand interactions (57%), glycolysis and gluconeogenesis (81%), and Parkinson's disease (100%). These data provide evidence in support of the multi-mechanistic nature of stem cell therapy and suggest that hMSC treatment is capable of simultaneously normalizing a wide variety of important molecular pathways that are disrupted by brain injury.

Noise minimization in eukaryotic gene expression.

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Hunter B Fraser

2004-06-01

Full Text Available All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or "noise." Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

Noise minimization in eukaryotic gene expression

Energy Technology Data Exchange (ETDEWEB)

Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

2004-01-15

All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

Noise minimization in eukaryotic gene expression

International Nuclear Information System (INIS)

Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

2004-01-01

All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection

Evaluation of the hormonal state of columnar apple trees (Malus x domestica) based on high throughput gene expression studies.

Science.gov (United States)

Krost, Clemens; Petersen, Romina; Lokan, Stefanie; Brauksiepe, Bastienne; Braun, Peter; Schmidt, Erwin R

2013-02-01

The columnar phenotype of apple trees (Malus x domestica) is characterized by a compact growth habit with fruit spurs instead of lateral branches. These properties provide significant economic advantages by enabling high density plantings. The columnar growth results from the presence of a dominant allele of the gene Columnar (Co) located on chromosome 10 which can appear in a heterozygous (Co/co) or homozygous (Co/Co) state. Although two deep sequencing approaches could shed some light on the transcriptome of columnar shoot apical meristems (SAMs), the molecular mechanisms of columnar growth are not yet elaborated. Since the influence of phytohormones is believed to have a pivotal role in the establishment of the phenotype, we performed RNA-Seq experiments to study genes associated with hormone homeostasis and clearly affected by the presence of Co. Our results provide a molecular explanation for earlier findings on the hormonal state of columnar apple trees. Additionally, they allow hypotheses on how the columnar phenotype might develop. Furthermore, we show a statistically approved enrichment of differentially regulated genes on chromosome 10 in the course of validating RNA-Seq results using additional gene expression studies.

Positive selection on gene expression in the human brain

DEFF Research Database (Denmark)

Khaitovich, Philipp; Tang, Kun; Franz, Henriette

2006-01-01

Recent work has shown that the expression levels of genes transcribed in the brains of humans and chimpanzees have changed less than those of genes transcribed in other tissues [1] . However, when gene expression changes are mapped onto the evolutionary lineage in which they occurred, the brain...... shows more changes than other tissues in the human lineage compared to the chimpanzee lineage [1] , [2] and [3] . There are two possible explanations for this: either positive selection drove more gene expression changes to fixation in the human brain than in the chimpanzee brain, or genes expressed...... in the brain experienced less purifying selection in humans than in chimpanzees, i.e. gene expression in the human brain is functionally less constrained. The first scenario would be supported if genes that changed their expression in the brain in the human lineage showed more selective sweeps than other genes...

A stochastic approach to multi-gene expression dynamics

International Nuclear Information System (INIS)

Ochiai, T.; Nacher, J.C.; Akutsu, T.

2005-01-01

In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption-Markov property-and the experimental transition probability, which characterizes the gene correlation system. Finally, a gene expression experiment is proposed for future applications of the model

Assays for noninvasive imaging of reporter gene expression

International Nuclear Information System (INIS)

Gambhir, S.S.; Barrio, J.R.; Herschman, H.R.; Phelps, M.E.

1999-01-01

Repeated, noninvasive imaging of reporter gene expression is emerging as a valuable tool for monitoring the expression of genes in animals and humans. Monitoring of organ/cell transplantation in living animals and humans, and the assessment of environmental, behavioral, and pharmacologic modulation of gene expression in transgenic animals should soon be possible. The earliest clinical application is likely to be monitoring human gene therapy in tumors transduced with the herpes simplex virus type 1 thymidine kinase (HSV1-tk) suicide gene. Several candidate assays for imaging reporter gene expression have been studied, utilizing cytosine deaminase (CD), HSV1-tk, and dopamine 2 receptor (D2R) as reporter genes. For the HSV1-tk reporter gene, both uracil nucleoside derivatives (e.g., 5-iodo-2'-fluoro-2'-deoxy-1-β-D-arabinofuranosyl-5-iodouracil [FIAU] labeled with 124 I, 131 I ) and acycloguanosine derivatives {e.g., 8-[ 18 F]fluoro-9-[[2-hydroxy-1-(hydroxymethyl)ethoxy]methyl]guanine (8-[ 18 F]-fluoroganciclovir) ([ 18 F]FGCV), 9-[(3-[ 18 F]fluoro-1-hydroxy-2-propoxy)methyl]guanine ([ 18 F]FHPG)} have been investigated as reporter probes. For the D2R reporter gene, a derivative of spiperone {3-(2'-[ 18 F]-Fluoroethyl)spiperone ([ 18 F]FESP)} has been used with positron emission tomography (PET) imaging. In this review, the principles and specific assays for imaging reporter gene expression are presented and discussed. Specific examples utilizing adenoviral-mediated delivery of a reporter gene as well as tumors expressing reporter genes are discussed

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.

Science.gov (United States)

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.

PRAME gene expression profile in medulloblastoma

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Tânia Maria Vulcani-Freitas

2011-02-01

Full Text Available Medulloblastoma is the most common malignant tumors of central nervous system in the childhood. The treatment is severe, harmful and, thus, has a dismal prognosis. As PRAME is present in various cancers, including meduloblastoma, and has limited expression in normal tissues, this antigen can be an ideal vaccine target for tumor immunotherapy. In order to find a potential molecular target, we investigated PRAME expression in medulloblastoma fragments and we compare the results with the clinical features of each patient. Analysis of gene expression was performed by real-time quantitative PCR from 37 tumor samples. The Mann-Whitney test was used to analysis the relationship between gene expression and clinical characteristics. Kaplan-Meier curves were used to evaluate survival. PRAME was overexpressed in 84% samples. But no statistical association was found between clinical features and PRAME overexpression. Despite that PRAME gene could be a strong candidate for immunotherapy since it is highly expressed in medulloblastomas.

Systematic identification of human housekeeping genes possibly useful as references in gene expression studies.

Science.gov (United States)

Caracausi, Maria; Piovesan, Allison; Antonaros, Francesca; Strippoli, Pierluigi; Vitale, Lorenza; Pelleri, Maria Chiara

2017-09-01

The ideal reference, or control, gene for the study of gene expression in a given organism should be expressed at a medium‑high level for easy detection, should be expressed at a constant/stable level throughout different cell types and within the same cell type undergoing different treatments, and should maintain these features through as many different tissues of the organism. From a biological point of view, these theoretical requirements of an ideal reference gene appear to be best suited to housekeeping (HK) genes. Recent advancements in the quality and completeness of human expression microarray data and in their statistical analysis may provide new clues toward the quantitative standardization of human gene expression studies in biology and medicine, both cross‑ and within‑tissue. The systematic approach used by the present study is based on the Transcriptome Mapper tool and exploits the automated reassignment of probes to corresponding genes, intra‑ and inter‑sample normalization, elaboration and representation of gene expression values in linear form within an indexed and searchable database with a graphical interface recording quantitative levels of expression, expression variability and cross‑tissue width of expression for more than 31,000 transcripts. The present study conducted a meta‑analysis of a pool of 646 expression profile data sets from 54 different human tissues and identified actin γ 1 as the HK gene that best fits the combination of all the traditional criteria to be used as a reference gene for general use; two ribosomal protein genes, RPS18 and RPS27, and one aquaporin gene, POM121 transmembrane nucleporin C, were also identified. The present study provided a list of tissue‑ and organ‑specific genes that may be most suited for the following individual tissues/organs: Adipose tissue, bone marrow, brain, heart, kidney, liver, lung, ovary, skeletal muscle and testis; and also provides in these cases a representative

SIGNATURE: A workbench for gene expression signature analysis

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Chang Jeffrey T

2011-11-01

Full Text Available Abstract Background The biological phenotype of a cell, such as a characteristic visual image or behavior, reflects activities derived from the expression of collections of genes. As such, an ability to measure the expression of these genes provides an opportunity to develop more precise and varied sets of phenotypes. However, to use this approach requires computational methods that are difficult to implement and apply, and thus there is a critical need for intelligent software tools that can reduce the technical burden of the analysis. Tools for gene expression analyses are unusually difficult to implement in a user-friendly way because their application requires a combination of biological data curation, statistical computational methods, and database expertise. Results We have developed SIGNATURE, a web-based resource that simplifies gene expression signature analysis by providing software, data, and protocols to perform the analysis successfully. This resource uses Bayesian methods for processing gene expression data coupled with a curated database of gene expression signatures, all carried out within a GenePattern web interface for easy use and access. Conclusions SIGNATURE is available for public use at http://genepattern.genome.duke.edu/signature/.

Mining gene expression data of multiple sclerosis.

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Pi Guo

Full Text Available Microarray produces a large amount of gene expression data, containing various biological implications. The challenge is to detect a panel of discriminative genes associated with disease. This study proposed a robust classification model for gene selection using gene expression data, and performed an analysis to identify disease-related genes using multiple sclerosis as an example.Gene expression profiles based on the transcriptome of peripheral blood mononuclear cells from a total of 44 samples from 26 multiple sclerosis patients and 18 individuals with other neurological diseases (control were analyzed. Feature selection algorithms including Support Vector Machine based on Recursive Feature Elimination, Receiver Operating Characteristic Curve, and Boruta algorithms were jointly performed to select candidate genes associating with multiple sclerosis. Multiple classification models categorized samples into two different groups based on the identified genes. Models' performance was evaluated using cross-validation methods, and an optimal classifier for gene selection was determined.An overlapping feature set was identified consisting of 8 genes that were differentially expressed between the two phenotype groups. The genes were significantly associated with the pathways of apoptosis and cytokine-cytokine receptor interaction. TNFSF10 was significantly associated with multiple sclerosis. A Support Vector Machine model was established based on the featured genes and gave a practical accuracy of ∼86%. This binary classification model also outperformed the other models in terms of Sensitivity, Specificity and F1 score.The combined analytical framework integrating feature ranking algorithms and Support Vector Machine model could be used for selecting genes for other diseases.

Plasticity-Related Gene Expression During Eszopiclone-Induced Sleep.

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Gerashchenko, Dmitry; Pasumarthi, Ravi K; Kilduff, Thomas S

2017-07-01

Experimental evidence suggests that restorative processes depend on synaptic plasticity changes in the brain during sleep. We used the expression of plasticity-related genes to assess synaptic plasticity changes during drug-induced sleep. We first characterized sleep induced by eszopiclone in mice during baseline conditions and during the recovery from sleep deprivation. We then compared the expression of 18 genes and two miRNAs critically involved in synaptic plasticity in these mice. Gene expression was assessed in the cerebral cortex and hippocampus by the TaqMan reverse transcription polymerase chain reaction and correlated with sleep parameters. Eszopiclone reduced the latency to nonrapid eye movement (NREM) sleep and increased NREM sleep amounts. Eszopiclone had no effect on slow wave activity (SWA) during baseline conditions but reduced the SWA increase during recovery sleep (RS) after sleep deprivation. Gene expression analyses revealed three distinct patterns: (1) four genes had higher expression either in the cortex or hippocampus in the group of mice with increased amounts of wakefulness; (2) a large proportion of plasticity-related genes (7 out of 18 genes) had higher expression during RS in the cortex but not in the hippocampus; and (3) six genes and the two miRNAs showed no significant changes across conditions. Even at a relatively high dose (20 mg/kg), eszopiclone did not reduce the expression of plasticity-related genes during RS period in the cortex. These results indicate that gene expression associated with synaptic plasticity occurs in the cortex in the presence of a hypnotic medication. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Evaluation of suitable reference genes for gene expression studies in bovine muscular tissue

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Dunner Susana

2008-09-01

Full Text Available Abstract Background Real-time reverse transcriptase quantitative polymerase chain reaction (real-time RTqPCR is a technique used to measure mRNA species copy number as a way to determine key genes involved in different biological processes. However, the expression level of these key genes may vary among tissues or cells not only as a consequence of differential expression but also due to different factors, including choice of reference genes to normalize the expression levels of the target genes; thus the selection of reference genes is critical for expression studies. For this purpose, ten candidate reference genes were investigated in bovine muscular tissue. Results The value of stability of ten candidate reference genes included in three groups was estimated: the so called 'classical housekeeping' genes (18S, GAPDH and ACTB, a second set of genes used in expression studies conducted on other tissues (B2M, RPII, UBC and HMBS and a third set of novel genes (SF3A1, EEF1A2 and CASC3. Three different statistical algorithms were used to rank the genes by their stability measures as produced by geNorm, NormFinder and Bestkeeper. The three methods tend to agree on the most stably expressed genes and the least in muscular tissue. EEF1A2 and HMBS followed by SF3A1, ACTB, and CASC3 can be considered as stable reference genes, and B2M, RPII, UBC and GAPDH would not be appropriate. Although the rRNA-18S stability measure seems to be within the range of acceptance, its use is not recommended because its synthesis regulation is not representative of mRNA levels. Conclusion Based on geNorm algorithm, we propose the use of three genes SF3A1, EEF1A2 and HMBS as references for normalization of real-time RTqPCR in muscle expression studies.

Microarray analysis of gene expression profiles of Schistosoma japonicum derived from less-susceptible host water buffalo and susceptible host goat.

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Jianmei Yang

Full Text Available BACKGROUND: Water buffalo and goats are natural hosts for S. japonicum in endemic areas of China. The susceptibility of these two hosts to schistosome infection is different, as water buffalo are less conducive to S. japonicum growth and development. To identify genes that may affect schistosome development and survival, we compared gene expression profiles of schistosomes derived from these two natural hosts using high-throughput microarray technology. RESULTS: The worm recovery rate was lower and the length and width of worms from water buffalo were smaller compared to those from goats following S. japonicum infection for 7 weeks. Besides obvious morphological difference between the schistosomes derived from the two hosts, differences were also observed by scanning and transmission electron microscopy. Microarray analysis showed differentially expressed gene patterns for parasites from the two hosts, which revealed that genes related to lipid and nucleotide metabolism, as well as protein folding, sorting, and degradation were upregulated, while others associated with signal transduction, endocrine function, development, immune function, endocytosis, and amino acid/carbohydrate/glycan metabolism were downregulated in schistosomes from water buffalo. KEGG pathway analysis deduced that the differentially expressed genes mainly involved lipid metabolism, the MAPK and ErbB signaling pathways, progesterone-mediated oocyte maturation, dorso-ventral axis formation, reproduction, and endocytosis, etc. CONCLUSION: The microarray gene analysis in schistosomes derived from water buffalo and goats provide a useful platform to disclose differences determining S. japonicum host compatibility to better understand the interplay between natural hosts and parasites, and identify schistosome target genes associated with susceptibility to screen vaccine candidates.

Expression profiling identifies genes involved in emphysema severity

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Bowman Rayleen V

2009-09-01

Full Text Available Abstract Chronic obstructive pulmonary disease (COPD is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients. Gene expression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressed genes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples. Class comparison identified 98 differentially expressed genes (p p Gene expression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3.

Decoupling Linear and Nonlinear Associations of Gene Expression

KAUST Repository

Itakura, Alan

2013-05-01

The FANTOM consortium has generated a large gene expression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between gene expression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing gene expression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between gene expression patterns than previously anticipated.

Decoupling Linear and Nonlinear Associations of Gene Expression

KAUST Repository

Itakura, Alan

2013-01-01

The FANTOM consortium has generated a large gene expression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between gene expression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing gene expression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between gene expression patterns than previously anticipated.

Genetic architecture of gene expression in the chicken

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Stanley Dragana

2013-01-01

Full Text Available Abstract Background The annotation of many genomes is limited, with a large proportion of identified genes lacking functional assignments. The construction of gene co-expression networks is a powerful approach that presents a way of integrating information from diverse gene expression datasets into a unified analysis which allows inferences to be drawn about the role of previously uncharacterised genes. Using this approach, we generated a condition-free gene co-expression network for the chicken using data from 1,043 publically available Affymetrix GeneChip Chicken Genome Arrays. This data was generated from a diverse range of experiments, including different tissues and experimental conditions. Our aim was to identify gene co-expression modules and generate a tool to facilitate exploration of the functional chicken genome. Results Fifteen modules, containing between 24 and 473 genes, were identified in the condition-free network. Most of the modules showed strong functional enrichment for particular Gene Ontology categories. However, a few showed no enrichment. Transcription factor binding site enrichment was also noted. Conclusions We have demonstrated that this chicken gene co-expression network is a useful tool in gene function prediction and the identification of putative novel transcription factors and binding sites. This work highlights the relevance of this methodology for functional prediction in poorly annotated genomes such as the chicken.

Bayesian assignment of gene ontology terms to gene expression experiments

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Sykacek, P.

2012-01-01

Motivation: Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488

Bayesian assignment of gene ontology terms to gene expression experiments.

Science.gov (United States)

Sykacek, P

2012-09-15

Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.

Gene expression profile data for mouse facial development

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Sonia M. Leach

2017-08-01

Full Text Available This article contains data related to the research articles "Spatial and Temporal Analysis of Gene Expression during Growth and Fusion of the Mouse Facial Prominences" (Feng et al., 2009 [1] and “Systems Biology of facial development: contributions of ectoderm and mesenchyme” (Hooper et al., 2017 In press [2]. Embryonic mammalian craniofacial development is a complex process involving the growth, morphogenesis, and fusion of distinct facial prominences into a functional whole. Aberrant gene regulation during this process can lead to severe craniofacial birth defects, including orofacial clefting. As a means to understand the genes involved in facial development, we had previously dissected the embryonic mouse face into distinct prominences: the mandibular, maxillary or nasal between E10.5 and E12.5. The prominences were then processed intact, or separated into ectoderm and mesenchyme layers, prior analysis of RNA expression using microarrays (Feng et al., 2009, Hooper et al., 2017 in press [1,2]. Here, individual gene expression profiles have been built from these datasets that illustrate the timing of gene expression in whole prominences or in the separated tissue layers. The data profiles are presented as an indexed and clickable list of the genes each linked to a graphical image of that gene׳s expression profile in the ectoderm, mesenchyme, or intact prominence. These data files will enable investigators to obtain a rapid assessment of the relative expression level of any gene on the array with respect to time, tissue, prominence, and expression trajectory.

Integrated olfactory receptor and microarray gene expression databases

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Crasto Chiquito J

2007-06-01

Full Text Available Abstract Background Gene expression patterns of olfactory receptors (ORs are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB, which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. Description ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data. Conclusion ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

Gene expression analysis of flax seed development