Lex-SVM: exploring the potential of exon expression profiling for disease classification.

PubMed

Yuan, Xiongying; Zhao, Yi; Liu, Changning; Bu, Dongbo

2011-04-01

Exon expression profiling technologies, including exon arrays and RNA-Seq, measure the abundance of every exon in a gene. Compared with gene expression profiling technologies like 3' array, exon expression profiling technologies could detect alterations in both transcription and alternative splicing, therefore they are expected to be more sensitive in diagnosis. However, exon expression profiling also brings higher dimension, more redundancy, and significant correlation among features. Ignoring the correlation structure among exons of a gene, a popular classification method like L1-SVM selects exons individually from each gene and thus is vulnerable to noise. To overcome this limitation, we present in this paper a new variant of SVM named Lex-SVM to incorporate correlation structure among exons and known splicing patterns to promote classification performance. Specifically, we construct a new norm, ex-norm, including our prior knowledge on exon correlation structure to regularize the coefficients of a linear SVM. Lex-SVM can be solved efficiently using standard linear programming techniques. The advantage of Lex-SVM is that it can select features group-wisely, force features in a subgroup to take equal weihts and exclude the features that contradict the majority in the subgroup. Experimental results suggest that on exon expression profile, Lex-SVM is more accurate than existing methods. Lex-SVM also generates a more compact model and selects genes more consistently in cross-validation. Unlike L1-SVM selecting only one exon in a gene, Lex-SVM assigns equal weights to as many exons in a gene as possible, lending itself easier for further interpretation.

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

PubMed Central

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

2016-01-01

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

Classification of early-stage non-small cell lung cancer by weighing gene expression profiles with connectivity information.

PubMed

Zhang, Ao; Tian, Suyan

2018-05-01

Pathway-based feature selection algorithms, which utilize biological information contained in pathways to guide which features/genes should be selected, have evolved quickly and become widespread in the field of bioinformatics. Based on how the pathway information is incorporated, we classify pathway-based feature selection algorithms into three major categories-penalty, stepwise forward, and weighting. Compared to the first two categories, the weighting methods have been underutilized even though they are usually the simplest ones. In this article, we constructed three different genes' connectivity information-based weights for each gene and then conducted feature selection upon the resulting weighted gene expression profiles. Using both simulations and a real-world application, we have demonstrated that when the data-driven connectivity information constructed from the data of specific disease under study is considered, the resulting weighted gene expression profiles slightly outperform the original expression profiles. In summary, a big challenge faced by the weighting method is how to estimate pathway knowledge-based weights more accurately and precisely. Only until the issue is conquered successfully will wide utilization of the weighting methods be impossible. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A highly sensitive and accurate gene expression analysis by sequencing ("bead-seq") for a single cell.

PubMed

Matsunaga, Hiroko; Goto, Mari; Arikawa, Koji; Shirai, Masataka; Tsunoda, Hiroyuki; Huang, Huan; Kambara, Hideki

2015-02-15

Analyses of gene expressions in single cells are important for understanding detailed biological phenomena. Here, a highly sensitive and accurate method by sequencing (called "bead-seq") to obtain a whole gene expression profile for a single cell is proposed. A key feature of the method is to use a complementary DNA (cDNA) library on magnetic beads, which enables adding washing steps to remove residual reagents in a sample preparation process. By adding the washing steps, the next steps can be carried out under the optimal conditions without losing cDNAs. Error sources were carefully evaluated to conclude that the first several steps were the key steps. It is demonstrated that bead-seq is superior to the conventional methods for single-cell gene expression analyses in terms of reproducibility, quantitative accuracy, and biases caused during sample preparation and sequencing processes. Copyright © 2014 Elsevier Inc. All rights reserved.

Liver Gene Expression Profiles of Rats Treated with Clofibric Acid

PubMed Central

Michel, Cécile; Desdouets, Chantal; Sacre-Salem, Béatrice; Gautier, Jean-Charles; Roberts, Ruth; Boitier, Eric

2003-01-01

Clofibric acid (CLO) is a peroxisome proliferator (PP) that acts through the peroxisome proliferator activated receptor α, leading to hepatocarcinogenesis in rodents. CLO-induced hepatocarcinogenesis is a multi-step process, first transforming normal liver cells into foci. The combination of laser capture microdissection (LCM) and genomics has the potential to provide expression profiles from such small cell clusters, giving an opportunity to understand the process of cancer development in response to PPs. To our knowledge, this is the first evaluation of the impact of the successive steps of LCM procedure on gene expression profiling by comparing profiles from LCM samples to those obtained with non-microdissected liver samples collected after a 1 month CLO treatment in the rat. We showed that hematoxylin and eosin (H&E) staining and laser microdissection itself do not impact on RNA quality. However, the overall process of the LCM procedure affects the RNA quality, resulting in a bias in the gene profiles. Nonetheless, this bias did not prevent accurate determination of a CLO-specific molecular signature. Thus, gene-profiling analysis of microdissected foci, identified by H&E staining may provide insight into the mechanisms underlying non-genotoxic hepatocarcinogenesis in the rat by allowing identification of specific genes that are regulated by CLO in early pre-neoplastic foci. PMID:14633594

Liver gene expression profiles of rats treated with clofibric acid: comparison of whole liver and laser capture microdissected liver.

PubMed

Michel, Cécile; Desdouets, Chantal; Sacre-Salem, Béatrice; Gautier, Jean-Charles; Roberts, Ruth; Boitier, Eric

2003-12-01

Clofibric acid (CLO) is a peroxisome proliferator (PP) that acts through the peroxisome proliferator activated receptor alpha, leading to hepatocarcinogenesis in rodents. CLO-induced hepatocarcinogenesis is a multi-step process, first transforming normal liver cells into foci. The combination of laser capture microdissection (LCM) and genomics has the potential to provide expression profiles from such small cell clusters, giving an opportunity to understand the process of cancer development in response to PPs. To our knowledge, this is the first evaluation of the impact of the successive steps of LCM procedure on gene expression profiling by comparing profiles from LCM samples to those obtained with non-microdissected liver samples collected after a 1 month CLO treatment in the rat. We showed that hematoxylin and eosin (H&E) staining and laser microdissection itself do not impact on RNA quality. However, the overall process of the LCM procedure affects the RNA quality, resulting in a bias in the gene profiles. Nonetheless, this bias did not prevent accurate determination of a CLO-specific molecular signature. Thus, gene-profiling analysis of microdissected foci, identified by H&E staining may provide insight into the mechanisms underlying non-genotoxic hepatocarcinogenesis in the rat by allowing identification of specific genes that are regulated by CLO in early pre-neoplastic foci.

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

PubMed

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

2017-10-01

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

Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy.

PubMed

Brogden, Kim A; Parashar, Deepak; Hallier, Andrea R; Braun, Terry; Qian, Fang; Rizvi, Naiyer A; Bossler, Aaron D; Milhem, Mohammed M; Chan, Timothy A; Abbasi, Taher; Vali, Shireen

2018-02-27

Programmed Death Ligand 1 (PD-L1) is a co-stimulatory and immune checkpoint protein. PD-L1 expression in non-small cell lung cancers (NSCLC) is a hallmark of adaptive resistance and its expression is often used to predict the outcome of Programmed Death 1 (PD-1) and PD-L1 immunotherapy treatments. However, clinical benefits do not occur in all patients and new approaches are needed to assist in selecting patients for PD-1 or PD-L1 immunotherapies. Here, we hypothesized that patient tumor cell genomics influenced cell signaling and expression of PD-L1, chemokines, and immunosuppressive molecules and these profiles could be used to predict patient clinical responses. We used a recent dataset from NSCLC patients treated with pembrolizumab. Deleterious gene mutational profiles in patient exomes were identified and annotated into a cancer network to create NSCLC patient-specific predictive computational simulation models. Validation checks were performed on the cancer network, simulation model predictions, and PD-1 match rates between patient-specific predicted and clinical responses. Expression profiles of these 24 chemokines and immunosuppressive molecules were used to identify patients who would or would not respond to PD-1 immunotherapy. PD-L1 expression alone was not sufficient to predict which patients would or would not respond to PD-1 immunotherapy. Adding chemokine and immunosuppressive molecule expression profiles allowed patient models to achieve a greater than 85.0% predictive correlation among predicted and reported patient clinical responses. Our results suggested that chemokine and immunosuppressive molecule expression profiles can be used to accurately predict clinical responses thus differentiating among patients who would and would not benefit from PD-1 or PD-L1 immunotherapies.

Selection of reliable reference genes for quantitative real-time PCR gene expression analysis in Jute (Corchorus capsularis) under stress treatments

PubMed Central

Niu, Xiaoping; Qi, Jianmin; Zhang, Gaoyang; Xu, Jiantang; Tao, Aifen; Fang, Pingping; Su, Jianguang

2015-01-01

To accurately measure gene expression using quantitative reverse transcription PCR (qRT-PCR), reliable reference gene(s) are required for data normalization. Corchorus capsularis, an annual herbaceous fiber crop with predominant biodegradability and renewability, has not been investigated for the stability of reference genes with qRT-PCR. In this study, 11 candidate reference genes were selected and their expression levels were assessed using qRT-PCR. To account for the influence of experimental approach and tissue type, 22 different jute samples were selected from abiotic and biotic stress conditions as well as three different tissue types. The stability of the candidate reference genes was evaluated using geNorm, NormFinder, and BestKeeper programs, and the comprehensive rankings of gene stability were generated by aggregate analysis. For the biotic stress and NaCl stress subsets, ACT7 and RAN were suitable as stable reference genes for gene expression normalization. For the PEG stress subset, UBC, and DnaJ were sufficient for accurate normalization. For the tissues subset, four reference genes TUBβ, UBI, EF1α, and RAN were sufficient for accurate normalization. The selected genes were further validated by comparing expression profiles of WRKY15 in various samples, and two stable reference genes were recommended for accurate normalization of qRT-PCR data. Our results provide researchers with appropriate reference genes for qRT-PCR in C. capsularis, and will facilitate gene expression study under these conditions. PMID:26528312

An Efficient Method for the Isolation of Highly Purified RNA from Seeds for Use in Quantitative Transcriptome Analysis.

PubMed

Kanai, Masatake; Mano, Shoji; Nishimura, Mikio

2017-01-11

Plant seeds accumulate large amounts of storage reserves comprising biodegradable organic matter. Humans rely on seed storage reserves for food and as industrial materials. Gene expression profiles are powerful tools for investigating metabolic regulation in plant cells. Therefore, detailed, accurate gene expression profiles during seed development are required for crop breeding. Acquiring highly purified RNA is essential for producing these profiles. Efficient methods are needed to isolate highly purified RNA from seeds. Here, we describe a method for isolating RNA from seeds containing large amounts of oils, proteins, and polyphenols, which have inhibitory effects on high-purity RNA isolation. Our method enables highly purified RNA to be obtained from seeds without the use of phenol, chloroform, or additional processes for RNA purification. This method is applicable to Arabidopsis, rapeseed, and soybean seeds. Our method will be useful for monitoring the expression patterns of low level transcripts in developing and mature seeds.

Asialoglycoprotein receptor 1 is a specific cell-surface marker for isolating hepatocytes derived from human pluripotent stem cells

PubMed Central

Peters, Derek T.; Henderson, Christopher A.; Warren, Curtis R.; Friesen, Max; Xia, Fang; Becker, Caroline E.; Musunuru, Kiran; Cowan, Chad A.

2016-01-01

ABSTRACT Hepatocyte-like cells (HLCs) are derived from human pluripotent stem cells (hPSCs) in vitro, but differentiation protocols commonly give rise to a heterogeneous mixture of cells. This variability confounds the evaluation of in vitro functional assays performed using HLCs. Increased differentiation efficiency and more accurate approximation of the in vivo hepatocyte gene expression profile would improve the utility of hPSCs. Towards this goal, we demonstrate the purification of a subpopulation of functional HLCs using the hepatocyte surface marker asialoglycoprotein receptor 1 (ASGR1). We analyzed the expression profile of ASGR1-positive cells by microarray, and tested their ability to perform mature hepatocyte functions (albumin and urea secretion, cytochrome activity). By these measures, ASGR1-positive HLCs are enriched for the gene expression profile and functional characteristics of primary hepatocytes compared with unsorted HLCs. We have demonstrated that ASGR1-positive sorting isolates a functional subpopulation of HLCs from among the heterogeneous cellular population produced by directed differentiation. PMID:27143754

Impact of sequencing depth and read length on single cell RNA sequencing data of T cells.

PubMed

Rizzetto, Simone; Eltahla, Auda A; Lin, Peijie; Bull, Rowena; Lloyd, Andrew R; Ho, Joshua W K; Venturi, Vanessa; Luciani, Fabio

2017-10-06

Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81% - 100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.

Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies.

PubMed

Pollock, Samuel B; Hu, Amy; Mou, Yun; Martinko, Alexander J; Julien, Olivier; Hornsby, Michael; Ploder, Lynda; Adams, Jarrett J; Geng, Huimin; Müschen, Markus; Sidhu, Sachdev S; Moffat, Jason; Wells, James A

2018-03-13

Human cells express thousands of different surface proteins that can be used for cell classification, or to distinguish healthy and disease conditions. A method capable of profiling a substantial fraction of the surface proteome simultaneously and inexpensively would enable more accurate and complete classification of cell states. We present a highly multiplexed and quantitative surface proteomic method using genetically barcoded antibodies called phage-antibody next-generation sequencing (PhaNGS). Using 144 preselected antibodies displayed on filamentous phage (Fab-phage) against 44 receptor targets, we assess changes in B cell surface proteins after the development of drug resistance in a patient with acute lymphoblastic leukemia (ALL) and in adaptation to oncogene expression in a Myc-inducible Burkitt lymphoma model. We further show PhaNGS can be applied at the single-cell level. Our results reveal that a common set of proteins including FLT3, NCR3LG1, and ROR1 dominate the response to similar oncogenic perturbations in B cells. Linking high-affinity, selective, genetically encoded binders to NGS enables direct and highly multiplexed protein detection, comparable to RNA-sequencing for mRNA. PhaNGS has the potential to profile a substantial fraction of the surface proteome simultaneously and inexpensively to enable more accurate and complete classification of cell states. Copyright © 2018 the Author(s). Published by PNAS.

Multiclass cancer classification using a feature subset-based ensemble from microRNA expression profiles.

PubMed

Piao, Yongjun; Piao, Minghao; Ryu, Keun Ho

2017-01-01

Cancer classification has been a crucial topic of research in cancer treatment. In the last decade, messenger RNA (mRNA) expression profiles have been widely used to classify different types of cancers. With the discovery of a new class of small non-coding RNAs; known as microRNAs (miRNAs), various studies have shown that the expression patterns of miRNA can also accurately classify human cancers. Therefore, there is a great demand for the development of machine learning approaches to accurately classify various types of cancers using miRNA expression data. In this article, we propose a feature subset-based ensemble method in which each model is learned from a different projection of the original feature space to classify multiple cancers. In our method, the feature relevance and redundancy are considered to generate multiple feature subsets, the base classifiers are learned from each independent miRNA subset, and the average posterior probability is used to combine the base classifiers. To test the performance of our method, we used bead-based and sequence-based miRNA expression datasets and conducted 10-fold and leave-one-out cross validations. The experimental results show that the proposed method yields good results and has higher prediction accuracy than popular ensemble methods. The Java program and source code of the proposed method and the datasets in the experiments are freely available at https://sourceforge.net/projects/mirna-ensemble/. Copyright © 2016 Elsevier Ltd. All rights reserved.

A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control consortium

PubMed Central

2014-01-01

We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings. PMID:25150838

Reconstructing Dynamic Promoter Activity Profiles from Reporter Gene Data.

PubMed

Kannan, Soumya; Sams, Thomas; Maury, Jérôme; Workman, Christopher T

2018-03-16

Accurate characterization of promoter activity is important when designing expression systems for systems biology and metabolic engineering applications. Promoters that respond to changes in the environment enable the dynamic control of gene expression without the necessity of inducer compounds, for example. However, the dynamic nature of these processes poses challenges for estimating promoter activity. Most experimental approaches utilize reporter gene expression to estimate promoter activity. Typically the reporter gene encodes a fluorescent protein that is used to infer a constant promoter activity despite the fact that the observed output may be dynamic and is a number of steps away from the transcription process. In fact, some promoters that are often thought of as constitutive can show changes in activity when growth conditions change. For these reasons, we have developed a system of ordinary differential equations for estimating dynamic promoter activity for promoters that change their activity in response to the environment that is robust to noise and changes in growth rate. Our approach, inference of dynamic promoter activity (PromAct), improves on existing methods by more accurately inferring known promoter activity profiles. This method is also capable of estimating the correct scale of promoter activity and can be applied to quantitative data sets to estimate quantitative rates.

Molecular Markers in Patients with Chronic Wounds to Guide Surgical Debridement

PubMed Central

Brem, Harold; Stojadinovic, Olivera; Diegelmann, Robert F; Entero, Hyacinth; Lee, Brian; Pastar, Irena; Golinko, Michael; Rosenberg, Harvey; Tomic-Canic, Marjana

2007-01-01

Chronic wounds, such as venous ulcers, are characterized by physiological impairments manifested by delays in healing, resulting in severe morbidity. Surgical debridement is routinely performed on chronic wounds because it stimulates healing. However, procedures are repeated many times on the same patient because, in contrast to tumor excision, there are no objective biological/molecular markers to guide the extent of debridement. To develop bioassays that can potentially guide surgical debridement, we assessed the pathogenesis of the patients’ wound tissue before and after wound debridement. We obtained biopsies from three patients at two locations, the nonhealing edge (prior to debridement) and the adjacent, nonulcerated skin of the venous ulcers (post debridement), and evaluated their histology, biological response to wounding (migration) and gene expression profile. We found that biopsies from the nonhealing edges exhibit distinct pathogenic morphology (hyperproliferative/hyperkeratotic epidermis; dermal fibrosis; increased procollagen synthesis). Fibroblasts deriving from this location exhibit impaired migration in comparison to the cells from adjacent nonulcerated biopsies, which exhibit normalization of morphology and normal migration capacity. The nonhealing edges have a specific, identifiable, and reproducible gene expression profile. The adjacent nonulcerated biopsies have their own distinctive reproducible gene expression profile, signifying that particular wound areas can be identified by gene expression profiling. We conclude that chronic ulcers contain distinct subpopulations of cells with different capacity to heal and that gene expression profiling can be utilized to identify them. In the future, molecular markers will be developed to identify the nonimpaired tissue, thereby making surgical debridement more accurate and more efficacious. PMID:17515955

Coordinated transcriptional regulation patterns associated with infertility phenotypes in men

PubMed Central

Ellis, Peter J I; Furlong, Robert A; Conner, Sarah J; Kirkman‐Brown, Jackson; Afnan, Masoud; Barratt, Christopher; Griffin, Darren K; Affara, Nabeel A

2007-01-01

Introduction Microarray gene‐expression profiling is a powerful tool for global analysis of the transcriptional consequences of disease phenotypes. Understanding the genetic correlates of particular pathological states is important for more accurate diagnosis and screening of patients, and thus for suggesting appropriate avenues of treatment. As yet, there has been little research describing gene‐expression profiling of infertile and subfertile men, and thus the underlying transcriptional events involved in loss of spermatogenesis remain unclear. Here we present the results of an initial screen of 33 patients with differing spermatogenic phenotypes. Methods Oligonucleotide array expression profiling was performed on testis biopsies for 33 patients presenting for testicular sperm extraction. Significantly regulated genes were selected using a mixed model analysis of variance. Principle components analysis and hierarchical clustering were used to interpret the resulting dataset with reference to the patient history, clinical findings and histological composition of the biopsies. Results Striking patterns of coordinated gene expression were found. The most significant contains multiple germ cell‐specific genes and corresponds to the degree of successful spermatogenesis in each patient, whereas a second pattern corresponds to inflammatory activity within the testis. Smaller‐scale patterns were also observed, relating to unique features of the individual biopsies. PMID:17496197

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

PubMed

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

2016-05-01

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

Temporal expression profiling of plasma proteins reveals oxidative stress in early stages of Type 1 Diabetes progression

DOE PAGES

Liu, Chih-Wei; Bramer, Lisa; Webb-Robertson, Bobbie-Jo; ...

2017-10-07

We report that blood markers other than islet autoantibodies are greatly needed to indicate the pancreatic beta cell destruction process as early as possible, and more accurately reflect the progression of Type 1 Diabetes Mellitus (T1D). To this end, a longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n = 11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with those of the matching healthy controls (n = 10). To our knowledge, the current study represents the largest (> 2000 proteins measured)more » longitudinal expression profiles of human plasma proteome in T1D research. By applying statistical trend analysis on the temporal expression patterns between T1D and controls, and Benjamini-Hochberg procedure for multiple-testing correction, 13 protein groups were regarded as having statistically significant differences during the entire follow-up period. Moreover, 16 protein groups, which play pivotal roles in response to oxidative stress, have consistently abnormal expression trend before seroconversion to islet autoimmunity. Importantly, the expression trends of two key reactive oxygen species-decomposing enzymes, Catalase and Superoxide dismutase were verified independently by ELISA.« less

Temporal expression profiling of plasma proteins reveals oxidative stress in early stages of Type 1 Diabetes progression

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

Liu, Chih-Wei; Bramer, Lisa; Webb-Robertson, Bobbie-Jo

We report that blood markers other than islet autoantibodies are greatly needed to indicate the pancreatic beta cell destruction process as early as possible, and more accurately reflect the progression of Type 1 Diabetes Mellitus (T1D). To this end, a longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n = 11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with those of the matching healthy controls (n = 10). To our knowledge, the current study represents the largest (> 2000 proteins measured)more » longitudinal expression profiles of human plasma proteome in T1D research. By applying statistical trend analysis on the temporal expression patterns between T1D and controls, and Benjamini-Hochberg procedure for multiple-testing correction, 13 protein groups were regarded as having statistically significant differences during the entire follow-up period. Moreover, 16 protein groups, which play pivotal roles in response to oxidative stress, have consistently abnormal expression trend before seroconversion to islet autoimmunity. Importantly, the expression trends of two key reactive oxygen species-decomposing enzymes, Catalase and Superoxide dismutase were verified independently by ELISA.« less

Two-pass imputation algorithm for missing value estimation in gene expression time series.

PubMed

Tsiporkova, Elena; Boeva, Veselka

2007-10-01

Gene expression microarray experiments frequently generate datasets with multiple values missing. However, most of the analysis, mining, and classification methods for gene expression data require a complete matrix of gene array values. Therefore, the accurate estimation of missing values in such datasets has been recognized as an important issue, and several imputation algorithms have already been proposed to the biological community. Most of these approaches, however, are not particularly suitable for time series expression profiles. In view of this, we propose a novel imputation algorithm, which is specially suited for the estimation of missing values in gene expression time series data. The algorithm utilizes Dynamic Time Warping (DTW) distance in order to measure the similarity between time expression profiles, and subsequently selects for each gene expression profile with missing values a dedicated set of candidate profiles for estimation. Three different DTW-based imputation (DTWimpute) algorithms have been considered: position-wise, neighborhood-wise, and two-pass imputation. These have initially been prototyped in Perl, and their accuracy has been evaluated on yeast expression time series data using several different parameter settings. The experiments have shown that the two-pass algorithm consistently outperforms, in particular for datasets with a higher level of missing entries, the neighborhood-wise and the position-wise algorithms. The performance of the two-pass DTWimpute algorithm has further been benchmarked against the weighted K-Nearest Neighbors algorithm, which is widely used in the biological community; the former algorithm has appeared superior to the latter one. Motivated by these findings, indicating clearly the added value of the DTW techniques for missing value estimation in time series data, we have built an optimized C++ implementation of the two-pass DTWimpute algorithm. The software also provides for a choice between three different initial rough imputation methods.

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

PubMed Central

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

2017-01-01

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

Asialoglycoprotein receptor 1 is a specific cell-surface marker for isolating hepatocytes derived from human pluripotent stem cells.

PubMed

Peters, Derek T; Henderson, Christopher A; Warren, Curtis R; Friesen, Max; Xia, Fang; Becker, Caroline E; Musunuru, Kiran; Cowan, Chad A

2016-05-01

Hepatocyte-like cells (HLCs) are derived from human pluripotent stem cells (hPSCs) in vitro, but differentiation protocols commonly give rise to a heterogeneous mixture of cells. This variability confounds the evaluation of in vitro functional assays performed using HLCs. Increased differentiation efficiency and more accurate approximation of the in vivo hepatocyte gene expression profile would improve the utility of hPSCs. Towards this goal, we demonstrate the purification of a subpopulation of functional HLCs using the hepatocyte surface marker asialoglycoprotein receptor 1 (ASGR1). We analyzed the expression profile of ASGR1-positive cells by microarray, and tested their ability to perform mature hepatocyte functions (albumin and urea secretion, cytochrome activity). By these measures, ASGR1-positive HLCs are enriched for the gene expression profile and functional characteristics of primary hepatocytes compared with unsorted HLCs. We have demonstrated that ASGR1-positive sorting isolates a functional subpopulation of HLCs from among the heterogeneous cellular population produced by directed differentiation. © 2016. Published by The Company of Biologists Ltd.

Detailed mechanism of benzene oxidation

NASA Technical Reports Server (NTRS)

Bittker, David A.

1987-01-01

A detailed quantitative mechanism for the oxidation of benzene in both argon and nitrogen diluted systems is presented. Computed ignition delay time for argon diluted mixtures are in satisfactory agreement with experimental results for a wide range of initial conditions. An experimental temperature versus time profile for a nitrogen diluted oxidation was accurately matched and several concentration profiles were matched qualitatively. Application of sensitivity analysis has given approximate rate constant expressions for the two dominant heat release reactions, the oxidation of C6H5 and C5H5 radicals by molecular oxygen.

Prognostic stratification improvement by integrating ID1/ID3/IGJ gene expression signature and immunophenotypic profile in adult patients with B-ALL.

PubMed

Cruz-Rodriguez, Nataly; Combita, Alba L; Enciso, Leonardo J; Raney, Lauren F; Pinzon, Paula L; Lozano, Olga C; Campos, Alba M; Peñaloza, Niyireth; Solano, Julio; Herrera, Maria V; Zabaleta, Jovanny; Quijano, Sandra

2017-02-28

Survival of adults with B-Acute Lymphoblastic Leukemia requires accurate risk stratification of patients in order to provide the appropriate therapy. Contemporary techniques, using clinical and cytogenetic variables are incomplete for prognosis prediction. To improve the classification of adult patients diagnosed with B-ALL into prognosis groups, two strategies were examined and combined: the expression of the ID1/ID3/IGJ gene signature by RT-PCR and the immunophenotypic profile of 19 markers proposed in the EuroFlow protocol by Flow Cytometry in bone marrow samples. Both techniques were correlated to stratify patients into prognostic groups. An inverse relationship between survival and expression of the three-genes signature was observed and an immunophenotypic profile associated with clinical outcome was identified. Markers CD10 and CD20 were correlated with simultaneous overexpression of ID1, ID3 and IGJ. Patients with simultaneous expression of the poor prognosis gene signature and overexpression of CD10 or CD20, had worse Event Free Survival and Overall Survival than patients who had either the poor prognosis gene expression signature or only CD20 or CD10 overexpressed. By utilizing the combined evaluation of these two immunophenotypic markers along with the poor prognosis gene expression signature, the risk stratification can be significantly strengthened. Further studies including a large number of patients are needed to confirm these findings.

Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

PubMed

Huang, Cai; Mezencev, Roman; McDonald, John F; Vannberg, Fredrik

2017-01-01

Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60). The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC) patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.

Diffusion Profiling via a Histogram Approach Distinguishes Low-grade from High-grade Meningiomas, Can Reflect the Respective Proliferative Potential and Progesterone Receptor Status.

PubMed

Gihr, Georg Alexander; Horvath-Rizea, Diana; Garnov, Nikita; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Henkes, Hans; Meyer, Hans Jonas; Hoffmann, Karl-Titus; Surov, Alexey; Schob, Stefan

2018-02-01

Presurgical grading, estimation of growth kinetics, and other prognostic factors are becoming increasingly important for selecting the best therapeutic approach for meningioma patients. Diffusion-weighted imaging (DWI) provides microstructural information and reflects tumor biology. A novel DWI approach, histogram profiling of apparent diffusion coefficient (ADC) volumes, provides more distinct information than conventional DWI. Therefore, our study investigated whether ADC histogram profiling distinguishes low-grade from high-grade lesions and reflects Ki-67 expression and progesterone receptor status. Pretreatment ADC volumes of 37 meningioma patients (28 low-grade, 9 high-grade) were used for histogram profiling. WHO grade, Ki-67 expression, and progesterone receptor status were evaluated. Comparative and correlative statistics investigating the association between histogram profiling and neuropathology were performed. The entire ADC profile (p10, p25, p75, p90, mean, median) was significantly lower in high-grade versus low-grade meningiomas. The lower percentiles, mean, and modus showed significant correlations with Ki-67 expression. Skewness and entropy of the ADC volumes were significantly associated with progesterone receptor status and Ki-67 expression. ROC analysis revealed entropy to be the most accurate parameter distinguishing low-grade from high-grade meningiomas. ADC histogram profiling provides a distinct set of parameters, which help differentiate low-grade versus high-grade meningiomas. Also, histogram metrics correlate significantly with histological surrogates of the respective proliferative potential. More specifically, entropy revealed to be the most promising imaging biomarker for presurgical grading. Both, entropy and skewness were significantly associated with progesterone receptor status and Ki-67 expression and therefore should be investigated further as predictors for prognostically relevant tumor biological features. Since absolute ADC values vary between MRI scanners of different vendors and field strengths, their use is more limited in the presurgical setting.

Blood expression profiles of fragile X premutation carriers identify candidate genes involved in neurodegenerative and infertility phenotypes.

PubMed

Mateu-Huertas, Elisabet; Rodriguez-Revenga, Laia; Alvarez-Mora, Maria Isabel; Madrigal, Irene; Willemsen, Rob; Milà, Montserrat; Martí, Eulàlia; Estivill, Xavier

2014-05-01

Male premutation carriers presenting between 55 and 200 CGG repeats in the Fragile-X-associated (FMR1) gene are at risk of developing Fragile X Tremor/Ataxia Syndrome (FXTAS), and females undergo Premature Ovarian Failure (POF1). Here, we have evaluated gene expression profiles from blood in male FMR1 premutation carriers and detected a strong deregulation of genes enriched in FXTAS relevant biological pathways, including inflammation, neuronal homeostasis and viability. Gene expression profiling distinguished between control individuals, carriers with FXTAS and carriers without FXTAS, with levels of expanded FMR1 mRNA being increased in FXTAS patients. In vitro studies in a neuronal cell model indicate that expression levels of expanded FMR1 5'-UTR are relevant in modulating the transcriptome. Thus, perturbations of the transcriptome may be an interplay between the CGG expansion size and FMR1 expression levels. Several deregulated genes (DFFA, BCL2L11, BCL2L1, APP, SOD1, RNF10, HDAC5, KCNC3, ATXN7, ATXN3 and EAP1) were validated in brain samples of a FXTAS mouse model. Downregulation of EAP1, a gene involved in the female reproductive system physiology, was confirmed in female carriers. Decreased levels were detected in female carriers with POF1 compared to those without POF1, suggesting that EAP1 levels contribute to ovarian insufficiency. In summary, gene expression profiling in blood has uncovered mechanisms that may underlie different pathological aspects of the premutation. A better understanding of the transcriptome dynamics in relation with expanded FMR1 mRNA expression levels and CGG expansion size may provide mechanistic insights into the disease process and a more accurate FXTAS diagnosis to the myriad of phenotypes associated with the premutation. Copyright © 2014. Published by Elsevier Inc.

Gene expression profiling for molecular staging of cutaneous melanoma in patients undergoing sentinel lymph node biopsy.

PubMed

Gerami, Pedram; Cook, Robert W; Russell, Maria C; Wilkinson, Jeff; Amaria, Rodabe N; Gonzalez, Rene; Lyle, Stephen; Jackson, Gilchrist L; Greisinger, Anthony J; Johnson, Clare E; Oelschlager, Kristen M; Stone, John F; Maetzold, Derek J; Ferris, Laura K; Wayne, Jeffrey D; Cooper, Chelsea; Obregon, Roxana; Delman, Keith A; Lawson, David

2015-05-01

A gene expression profile (GEP) test able to accurately identify risk of metastasis for patients with cutaneous melanoma has been clinically validated. We aimed for assessment of the prognostic accuracy of GEP and sentinel lymph node biopsy (SLNB) tests, independently and in combination, in a multicenter cohort of 217 patients. Reverse transcription polymerase chain reaction (RT-PCR) was performed to assess the expression of 31 genes from primary melanoma tumors, and SLNB outcome was determined from clinical data. Prognostic accuracy of each test was determined using Kaplan-Meier and Cox regression analysis of disease-free, distant metastasis-free, and overall survivals. GEP outcome was a more significant and better predictor of each end point in univariate and multivariate regression analysis, compared with SLNB (P < .0001 for all). In combination with SLNB, GEP improved prognostication. For patients with a GEP high-risk outcome and a negative SLNB result, Kaplan-Meier 5-year disease-free, distant metastasis-free, and overall survivals were 35%, 49%, and 54%, respectively. Within the SLNB-negative cohort of patients, overall risk of metastatic events was higher (∼30%) than commonly found in the general population of patients with melanoma. In this study cohort, GEP was an objective tool that accurately predicted metastatic risk in SLNB-eligible patients. Copyright © 2015 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Proteomic analysis of hair shafts from monozygotic twins: Expression profiles and genetically variant peptides.

PubMed

Wu, Pei-Wen; Mason, Katelyn E; Durbin-Johnson, Blythe P; Salemi, Michelle; Phinney, Brett S; Rocke, David M; Parker, Glendon J; Rice, Robert H

2017-07-01

Forensic association of hair shaft evidence with individuals is currently assessed by comparing mitochondrial DNA haplotypes of reference and casework samples, primarily for exclusionary purposes. Present work tests and validates more recent proteomic approaches to extract quantitative transcriptional and genetic information from hair samples of monozygotic twin pairs, which would be predicted to partition away from unrelated individuals if the datasets contain identifying information. Protein expression profiles and polymorphic, genetically variant hair peptides were generated from ten pairs of monozygotic twins. Profiling using the protein tryptic digests revealed that samples from identical twins had typically an order of magnitude fewer protein expression differences than unrelated individuals. The data did not indicate that the degree of difference within twin pairs increased with age. In parallel, data from the digests were used to detect genetically variant peptides that result from common nonsynonymous single nucleotide polymorphisms in genes expressed in the hair follicle. Compilation of the variants permitted sorting of the samples by hierarchical clustering, permitting accurate matching of twin pairs. The results demonstrate that genetic differences are detectable by proteomic methods and provide a framework for developing quantitative statistical estimates of personal identification that increase the value of hair shaft evidence. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A biomarker-based screen of a gene expression compendium ...

EPA Pesticide Factsheets

Computational approaches were developed to identify factors that regulate Nrf2 in a large gene expression compendium of microarray profiles including >2000 comparisons which queried the effects of chemicals, genes, diets, and infectious agents on gene expression in the mouse liver. A gene expression biomarker of 48 genes which accurately predicted Nrf2 activation was used to identify factors which resulted in a gene expression profile with significant correlation to the biomarker. A number of novel insights were made. Chemicals that activated the xenosensor constitutive activated receptor (CAR) consistently activated Nrf2 across hundreds of profiles, possibly downstream of Cyp-induced increases in oxidative stress. Nrf2 activation was also found to be negatively regulated by the growth hormone (GH)- and androgen-regulated transcription factor STAT5b, a transcription factor suppressed by CAR. Nrf2 was activated when STAT5b was suppressed in female mice vs. male mice, after exposure to estrogens, or in genetic mutants in which GH signaling was disrupted. A subset of the mutants that show STAT5b suppression and Nrf2 activation result in increased resistance to environmental stressors and increased longevity. This study describes a novel approach for understanding the network of factors that regulate the Nrf2 pathway and highlights novel interactions between Nrf2, CAR and STAT5b transcription factors. (This abstract does not represent EPA policy.) Computational appr

Evaluation of reference genes for quantitative real-time PCR in oil palm elite planting materials propagated by tissue culture.

PubMed

Chan, Pek-Lan; Rose, Ray J; Abdul Murad, Abdul Munir; Zainal, Zamri; Low, Eng-Ti Leslie; Ooi, Leslie Cheng-Li; Ooi, Siew-Eng; Yahya, Suzaini; Singh, Rajinder

2014-01-01

The somatic embryogenesis tissue culture process has been utilized to propagate high yielding oil palm. Due to the low callogenesis and embryogenesis rates, molecular studies were initiated to identify genes regulating the process, and their expression levels are usually quantified using reverse transcription quantitative real-time PCR (RT-qPCR). With the recent release of oil palm genome sequences, it is crucial to establish a proper strategy for gene analysis using RT-qPCR. Selection of the most suitable reference genes should be performed for accurate quantification of gene expression levels. In this study, eight candidate reference genes selected from cDNA microarray study and literature review were evaluated comprehensively across 26 tissue culture samples using RT-qPCR. These samples were collected from two tissue culture lines and media treatments, which consisted of leaf explants cultures, callus and embryoids from consecutive developmental stages. Three statistical algorithms (geNorm, NormFinder and BestKeeper) confirmed that the expression stability of novel reference genes (pOP-EA01332, PD00380 and PD00569) outperformed classical housekeeping genes (GAPDH, NAD5, TUBULIN, UBIQUITIN and ACTIN). PD00380 and PD00569 were identified as the most stably expressed genes in total samples, MA2 and MA8 tissue culture lines. Their applicability to validate the expression profiles of a putative ethylene-responsive transcription factor 3-like gene demonstrated the importance of using the geometric mean of two genes for normalization. Systematic selection of the most stably expressed reference genes for RT-qPCR was established in oil palm tissue culture samples. PD00380 and PD00569 were selected for accurate and reliable normalization of gene expression data from RT-qPCR. These data will be valuable to the research associated with the tissue culture process. Also, the method described here will facilitate the selection of appropriate reference genes in other oil palm tissues and in the expression profiling of genes relating to yield, biotic and abiotic stresses.

MicroRNA Expression Profiles as Biomarkers of Minor Salivary Gland Inflammation and Dysfunction in Sjögren's Syndrome

PubMed Central

Alevizos, Ilias; Alexander, Stefanie; Turner, R. James; Illei, Gabor G.

2013-01-01

Objective MicroRNA reflect physiologic and pathologic processes and may be used as biomarkers of concurrent pathophysiologic events in complex settings such as autoimmune diseases. We generated microRNA microarray profiles from the minor salivary glands of control subjects without Sjögren's syndrome (SS) and patients with SS who had low-grade or high-grade inflammation and impaired or normal saliva production, to identify microRNA patterns specific to salivary gland inflammation or dysfunction. Methods MicroRNA expression profiles were generated by Agilent microRNA arrays. We developed a novel method for data normalization by identifying housekeeping microRNA. MicroRNA profiles were compared by unsupervised mathematical methods to test how well they distinguish between control subjects and various subsets of patients with SS. Several bioinformatics methods were used to predict the messenger RNA targets of the differentially expressed microRNA. Results MicroRNA expression patterns accurately distinguished salivary glands from control subjects and patients with SS who had low-degree or high-degree inflammation. Using real-time quantitative polymerase chain reaction, we validated 2 microRNA as markers of inflammation in an independent cohort. Comparing microRNA from patients with preserved or low salivary flow identified a set of differentially expressed microRNA, most of which were up-regulated in the group with decreased salivary gland function, suggesting that the targets of microRNA may have a protective effect on epithelial cells. The predicted biologic targets of microRNA associated with inflammation or salivary gland dysfunction identified both overlapping and distinct biologic pathways and processes. Conclusion Distinct microRNA expression patterns are associated with salivary gland inflammation and dysfunction in patients with SS, and microRNA represent a novel group of potential biomarkers. PMID:21280008

Selection and Validation of Reference Genes for qRT-PCR Expression Analysis of Candidate Genes Involved in Olfactory Communication in the Butterfly Bicyclus anynana

PubMed Central

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M.

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes. PMID:25793735

Selection and validation of reference genes for qRT-PCR expression analysis of candidate genes involved in olfactory communication in the butterfly Bicyclus anynana.

PubMed

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes.

DNA copy number, including telomeres and mitochondria, assayed using next-generation sequencing.

PubMed

Castle, John C; Biery, Matthew; Bouzek, Heather; Xie, Tao; Chen, Ronghua; Misura, Kira; Jackson, Stuart; Armour, Christopher D; Johnson, Jason M; Rohl, Carol A; Raymond, Christopher K

2010-04-16

DNA copy number variations occur within populations and aberrations can cause disease. We sought to develop an improved lab-automatable, cost-efficient, accurate platform to profile DNA copy number. We developed a sequencing-based assay of nuclear, mitochondrial, and telomeric DNA copy number that draws on the unbiased nature of next-generation sequencing and incorporates techniques developed for RNA expression profiling. To demonstrate this platform, we assayed UMC-11 cells using 5 million 33 nt reads and found tremendous copy number variation, including regions of single and homogeneous deletions and amplifications to 29 copies; 5 times more mitochondria and 4 times less telomeric sequence than a pool of non-diseased, blood-derived DNA; and that UMC-11 was derived from a male individual. The described assay outputs absolute copy number, outputs an error estimate (p-value), and is more accurate than array-based platforms at high copy number. The platform enables profiling of mitochondrial levels and telomeric length. The assay is lab-automatable and has a genomic resolution and cost that are tunable based on the number of sequence reads.

DNA copy number, including telomeres and mitochondria, assayed using next-generation sequencing

PubMed Central

2010-01-01

Background DNA copy number variations occur within populations and aberrations can cause disease. We sought to develop an improved lab-automatable, cost-efficient, accurate platform to profile DNA copy number. Results We developed a sequencing-based assay of nuclear, mitochondrial, and telomeric DNA copy number that draws on the unbiased nature of next-generation sequencing and incorporates techniques developed for RNA expression profiling. To demonstrate this platform, we assayed UMC-11 cells using 5 million 33 nt reads and found tremendous copy number variation, including regions of single and homogeneous deletions and amplifications to 29 copies; 5 times more mitochondria and 4 times less telomeric sequence than a pool of non-diseased, blood-derived DNA; and that UMC-11 was derived from a male individual. Conclusion The described assay outputs absolute copy number, outputs an error estimate (p-value), and is more accurate than array-based platforms at high copy number. The platform enables profiling of mitochondrial levels and telomeric length. The assay is lab-automatable and has a genomic resolution and cost that are tunable based on the number of sequence reads. PMID:20398377

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

PubMed

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula

PubMed Central

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components. PMID:29692857

Spherical space Bessel-Legendre-Fourier localized modes solver for electromagnetic waves.

PubMed

Alzahrani, Mohammed A; Gauthier, Robert C

2015-10-05

Maxwell's vector wave equations are solved for dielectric configurations that match the symmetry of a spherical computational domain. The electric or magnetic field components and the inverse of the dielectric profile are series expansion defined using basis functions composed of the lowest order spherical Bessel function, polar angle single index dependant Legendre polynomials and azimuthal complex exponential (BLF). The series expressions and non-traditional form of the basis functions result in an eigenvalue matrix formulation of Maxwell's equations that are relatively compact and accurately solvable on a desktop PC. The BLF matrix returns the frequencies and field profiles for steady states modes. The key steps leading to the matrix populating expressions are provided. The validity of the numerical technique is confirmed by comparing the results of computations to those published using complementary techniques.

Primary Characterization of Small RNAs in Symbiotic Nitrogen-Fixing Bacteria.

PubMed

Robledo, Marta; García-Tomsig, Natalia I; Jiménez-Zurdo, José I

2018-01-01

High-throughput transcriptome profiling (RNAseq) has uncovered large and heterogeneous populations of small noncoding RNA species (sRNAs) with potential regulatory roles in bacteria. A large fraction of sRNAs are differentially regulated and rely on protein-assisted antisense interactions to trans-encoded target mRNAs to fine-tune posttranscriptional reprogramming of gene expression in response to external cues. However, annotation and function of sRNAs are still largely overlooked in nonmodel bacteria with complex lifestyles. Here, we describe experimental protocols successfully applied for the accurate annotation, expression profiling and target mRNA identification of trans-acting sRNAs in the nitrogen-fixing α-rhizobium Sinorhizobium meliloti. The protocols presented here can be similarly applied for the characterization of trans-sRNAs in genetically tractable α-proteobacteria of agronomical or clinical relevance interacting with eukaryotic hosts.

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

PubMed

Zeidan, Amer M; Prebet, Thomas; Saad Aldin, Ehab; Gore, Steven David

2014-04-01

Evaluation of: Pellagatti A, Benner A, Mills KI et al. Identification of gene expression-based prognostic markers in the hematopoietic stem cells of patients with myelodysplastic syndromes. J. Clin. Oncol. 31(28), 3557-3564 (2013). Patients with myelodysplastic syndromes (MDS) exhibit wide heterogeneity in clinical outcomes making accurate risk-stratification an integral part of the risk-adaptive management paradigm. Current prognostic schemes for MDS rely on clinicopathological parameters. Despite the increasing knowledge of the genetic landscape of MDS and the prognostic impact of many newly discovered molecular aberrations, none to date has been incorporated formally into the major risk models. Efforts are ongoing to use data generated from genome-wide high-throughput techniques to improve the 'individualized' outcome prediction for patients. We here discuss an important paper in which gene expression profiling (GEP) technology was applied to marrow CD34(+) cells from 125 MDS patients to generate and validate a standardized GEP-based prognostic signature.

Constrained clusters of gene expression profiles with pathological features.

PubMed

Sese, Jun; Kurokawa, Yukinori; Monden, Morito; Kato, Kikuya; Morishita, Shinichi

2004-11-22

Gene expression profiles should be useful in distinguishing variations in disease, since they reflect accurately the status of cells. The primary clustering of gene expression reveals the genotypes that are responsible for the proximity of members within each cluster, while further clustering elucidates the pathological features of the individual members of each cluster. However, since the first clustering process and the second classification step, in which the features are associated with clusters, are performed independently, the initial set of clusters may omit genes that are associated with pathologically meaningful features. Therefore, it is important to devise a way of identifying gene expression clusters that are associated with pathological features. We present the novel technique of 'itemset constrained clustering' (IC-Clustering), which computes the optimal cluster that maximizes the interclass variance of gene expression between groups, which are divided according to the restriction that only divisions that can be expressed using common features are allowed. This constraint automatically labels each cluster with a set of pathological features which characterize that cluster. When applied to liver cancer datasets, IC-Clustering revealed informative gene expression clusters, which could be annotated with various pathological features, such as 'tumor' and 'man', or 'except tumor' and 'normal liver function'. In contrast, the k-means method overlooked these clusters.

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

PubMed

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

2016-09-15

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

A cross-species analysis method to analyze animal models' similarity to human's disease state

PubMed Central

2012-01-01

Background Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism. Results We developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery. We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning. Conclusions We developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for drug research, such as potential drug candidates, possible drug repositioning, side effects and information about pharmacology. PMID:23282076

A cross-species analysis method to analyze animal models' similarity to human's disease state.

PubMed

Yu, Shuhao; Zheng, Lulu; Li, Yun; Li, Chunyan; Ma, Chenchen; Li, Yixue; Li, Xuan; Hao, Pei

2012-01-01

Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism. We developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery. We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning. We developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for drug research, such as potential drug candidates, possible drug repositioning, side effects and information about pharmacology.

A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons

PubMed Central

Tian, Tian; Salis, Howard M.

2015-01-01

Natural and engineered genetic systems require the coordinated expression of proteins. In bacteria, translational coupling provides a genetically encoded mechanism to control expression level ratios within multi-cistronic operons. We have developed a sequence-to-function biophysical model of translational coupling to predict expression level ratios in natural operons and to design synthetic operons with desired expression level ratios. To quantitatively measure ribosome re-initiation rates, we designed and characterized 22 bi-cistronic operon variants with systematically modified intergenic distances and upstream translation rates. We then derived a thermodynamic free energy model to calculate de novo initiation rates as a result of ribosome-assisted unfolding of intergenic RNA structures. The complete biophysical model has only five free parameters, but was able to accurately predict downstream translation rates for 120 synthetic bi-cistronic and tri-cistronic operons with rationally designed intergenic regions and systematically increased upstream translation rates. The biophysical model also accurately predicted the translation rates of the nine protein atp operon, compared to ribosome profiling measurements. Altogether, the biophysical model quantitatively predicts how translational coupling controls protein expression levels in synthetic and natural bacterial operons, providing a deeper understanding of an important post-transcriptional regulatory mechanism and offering the ability to rationally engineer operons with desired behaviors. PMID:26117546

Predicting survival times for neuroblastoma patients using RNA-seq expression profiles.

PubMed

Grimes, Tyler; Walker, Alejandro R; Datta, Susmita; Datta, Somnath

2018-05-30

Neuroblastoma is the most common tumor of early childhood and is notorious for its high variability in clinical presentation. Accurate prognosis has remained a challenge for many patients. In this study, expression profiles from RNA-sequencing are used to predict survival times directly. Several models are investigated using various annotation levels of expression profiles (genes, transcripts, and introns), and an ensemble predictor is proposed as a heuristic for combining these different profiles. The use of RNA-seq data is shown to improve accuracy in comparison to using clinical data alone for predicting overall survival times. Furthermore, clinically high-risk patients can be subclassified based on their predicted overall survival times. In this effort, the best performing model was the elastic net using both transcripts and introns together. This model separated patients into two groups with 2-year overall survival rates of 0.40±0.11 (n=22) versus 0.80±0.05 (n=68). The ensemble approach gave similar results, with groups 0.42±0.10 (n=25) versus 0.82±0.05 (n=65). This suggests that the ensemble is able to effectively combine the individual RNA-seq datasets. Using predicted survival times based on RNA-seq data can provide improved prognosis by subclassifying clinically high-risk neuroblastoma patients. This article was reviewed by Subharup Guha and Isabel Nepomuceno.

A Targeted Quantitative Proteomics Strategy for Global Kinome Profiling of Cancer Cells and Tissues*

PubMed Central

Xiao, Yongsheng; Guo, Lei; Wang, Yinsheng

2014-01-01

Kinases are among the most intensively pursued enzyme superfamilies as targets for anti-cancer drugs. Large data sets on inhibitor potency and selectivity for more than 400 human kinases became available recently, offering the opportunity to design rationally novel kinase-based anti-cancer therapies. However, the expression levels and activities of kinases are highly heterogeneous among different types of cancer and even among different stages of the same cancer. The lack of effective strategy for profiling the global kinome hampers the development of kinase-targeted cancer chemotherapy. Here, we introduced a novel global kinome profiling method, based on our recently developed isotope-coded ATP-affinity probe and a targeted proteomic method using multiple-reaction monitoring (MRM), for assessing simultaneously the expression of more than 300 kinases in human cells and tissues. This MRM-based assay displayed much better sensitivity, reproducibility, and accuracy than the discovery-based shotgun proteomic method. Approximately 250 kinases could be routinely detected in the lysate of a single cell line. Additionally, the incorporation of iRT into MRM kinome library rendered our MRM kinome assay easily transferrable across different instrument platforms and laboratories. We further employed this approach for profiling kinase expression in two melanoma cell lines, which revealed substantial kinome reprogramming during cancer progression and demonstrated an excellent correlation between the anti-proliferative effects of kinase inhibitors and the expression levels of their target kinases. Therefore, this facile and accurate kinome profiling assay, together with the kinome-inhibitor interaction map, could provide invaluable knowledge to predict the effectiveness of kinase inhibitor drugs and offer the opportunity for individualized cancer chemotherapy. PMID:24520089

Microarray-based cancer prediction using soft computing approach.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2009-05-26

One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

Epidermal Growth Factor Receptor (EGFR) mutation analysis, gene expression profiling and EGFR protein expression in primary prostate cancer

PubMed Central

2011-01-01

Background Activating mutations of the epidermal growth factor receptor (EGFR) confer sensitivity to the tyrosine kinase inhibitors (TKi), gefitinib and erlotinib. We analysed EGFR expression, EGFR mutation status and gene expression profiles of prostate cancer (PC) to supply a rationale for EGFR targeted therapies in this disease. Methods Mutational analysis of EGFR TK domain (exons from 18 to 21) and immunohistochemistry for EGFR were performed on tumour tissues derived from radical prostatectomy from 100 PC patients. Gene expression profiling using oligo-microarrays was also carried out in 51 of the PC samples. Results EGFR protein overexpression (EGFRhigh) was found in 36% of the tumour samples, and mutations were found in 13% of samples. Patients with EGFRhigh tumours experienced a significantly increased risk of biochemical relapse (hazard ratio-HR 2.52, p=0.02) compared with patients with tumours expressing low levels of EGFR (EGFRlow). Microarray analysis did not reveal any differences in gene expression between EGFRhigh and EGFRlow tumours. Conversely, in EGFRhigh tumours, we were able to identify a 79 gene signature distinguishing mutated from non-mutated tumours. Additionally, 29 genes were found to be differentially expressed between mutated/EGFRhigh (n=3) and mutated/EGFRlow tumours (n=5). Four of the down-regulated genes, U19/EAF2, ABCC4, KLK3 and ANXA3 and one of the up-regulated genes, FOXC1, are involved in PC progression. Conclusions Based on our findings, we hypothesize that accurate definition of the EGFR status could improve prognostic stratification and we suggest a possible role for EGFR-directed therapies in PC patients. Having been generated in a relatively small sample of patients, our results warrant confirmation in larger series. PMID:21266046

Epidermal Growth Factor Receptor (EGFR) mutation analysis, gene expression profiling and EGFR protein expression in primary prostate cancer.

PubMed

Peraldo-Neia, Caterina; Migliardi, Giorgia; Mello-Grand, Maurizia; Montemurro, Filippo; Segir, Raffaella; Pignochino, Ymera; Cavalloni, Giuliana; Torchio, Bruno; Mosso, Luciano; Chiorino, Giovanna; Aglietta, Massimo

2011-01-25

Activating mutations of the epidermal growth factor receptor (EGFR) confer sensitivity to the tyrosine kinase inhibitors (TKi), gefitinib and erlotinib. We analysed EGFR expression, EGFR mutation status and gene expression profiles of prostate cancer (PC) to supply a rationale for EGFR targeted therapies in this disease. Mutational analysis of EGFR TK domain (exons from 18 to 21) and immunohistochemistry for EGFR were performed on tumour tissues derived from radical prostatectomy from 100 PC patients. Gene expression profiling using oligo-microarrays was also carried out in 51 of the PC samples. EGFR protein overexpression (EGFRhigh) was found in 36% of the tumour samples, and mutations were found in 13% of samples. Patients with EGFRhigh tumours experienced a significantly increased risk of biochemical relapse (hazard ratio-HR 2.52, p=0.02) compared with patients with tumours expressing low levels of EGFR (EGFRlow). Microarray analysis did not reveal any differences in gene expression between EGFRhigh and EGFRlow tumours. Conversely, in EGFRhigh tumours, we were able to identify a 79 gene signature distinguishing mutated from non-mutated tumours. Additionally, 29 genes were found to be differentially expressed between mutated/EGFRhigh (n=3) and mutated/EGFRlow tumours (n=5). Four of the down-regulated genes, U19/EAF2, ABCC4, KLK3 and ANXA3 and one of the up-regulated genes, FOXC1, are involved in PC progression. Based on our findings, we hypothesize that accurate definition of the EGFR status could improve prognostic stratification and we suggest a possible role for EGFR-directed therapies in PC patients. Having been generated in a relatively small sample of patients, our results warrant confirmation in larger series.

Expression profiles of key phenylpropanoid genes during Vanilla planifolia pod development reveal a positive correlation between PAL gene expression and vanillin biosynthesis.

PubMed

Fock-Bastide, Isabelle; Palama, Tony Lionel; Bory, Séverine; Lécolier, Aurélie; Noirot, Michel; Joët, Thierry

2014-01-01

In Vanilla planifolia pods, development of flavor precursors is dependent on the phenylpropanoid pathway. The distinctive vanilla aroma is produced by numerous phenolic compounds of which vanillin is the most important. Because of the economic importance of vanilla, vanillin biosynthetic pathways have been extensively studied but agreement has not yet been reached on the processes leading to its accumulation. In order to explore the transcriptional control exerted on these pathways, five key phenylpropanoid genes expressed during pod development were identified and their mRNA accumulation profiles were evaluated during pod development and maturation using quantitative real-time PCR. As a prerequisite for expression analysis using qRT-PCR, five potential reference genes were tested, and two genes encoding Actin and EF1 were shown to be the most stable reference genes for accurate normalization during pod development. For the first time, genes encoding a phenylalanine ammonia-lyase (VpPAL1) and a cinnamate 4-hydroxylase (VpC4H1) were identified in vanilla pods and studied during maturation. Among phenylpropanoid genes, differential regulation was observed from 3 to 8 months after pollination. VpPAL1 was gradually up-regulated, reaching the maximum expression level at maturity. In contrast, genes encoding 4HBS, C4H, OMT2 and OMT3 did not show significant increase in expression levels after the fourth month post-pollination. Expression profiling of these key phenylpropanoid genes is also discussed in light of accumulation patterns for key phenolic compounds. Interestingly, VpPAL1 gene expression was shown to be positively correlated to maturation and vanillin accumulation. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

High expression of ID family and IGJ genes signature as predictor of low induction treatment response and worst survival in adult Hispanic patients with B-acute lymphoblastic leukemia.

PubMed

Cruz-Rodriguez, Nataly; Combita, Alba L; Enciso, Leonardo J; Quijano, Sandra M; Pinzon, Paula L; Lozano, Olga C; Castillo, Juan S; Li, Li; Bareño, Jose; Cardozo, Claudia; Solano, Julio; Herrera, Maria V; Cudris, Jennifer; Zabaleta, Jovanny

2016-04-05

B-Acute lymphoblastic leukemia (B-ALL) represents a hematologic malignancy with poor clinical outcome and low survival rates in adult patients. Remission rates in Hispanic population are almost 30% lower and Overall Survival (OS) nearly two years inferior than those reported in other ethnic groups. Only 61% of Colombian adult patients with ALL achieve complete remission (CR), median overall survival is 11.3 months and event-free survival (EFS) is 7.34 months. Identification of prognostic factors is crucial for the application of proper treatment strategies and subsequently for successful outcome. Our goal was to identify a gene expression signature that might correlate with response to therapy and evaluate the utility of these as prognostic tool in hispanic patients. We included 43 adult patients newly diagnosed with B-ALL. We used microarray analysis in order to identify genes that distinguish poor from good response to treatment using differential gene expression analysis. The expression profile was validated by real-time PCR (RT-PCT). We identified 442 differentially expressed genes between responders and non-responders to induction treatment. Hierarchical analysis according to the expression of a 7-gene signature revealed 2 subsets of patients that differed in their clinical characteristics and outcome. Our study suggests that response to induction treatment and clinical outcome of Hispanic patients can be predicted from the onset of the disease and that gene expression profiles can be used to stratify patient risk adequately and accurately. The present study represents the first that shows the gene expression profiling of B-ALL Colombian adults and its relevance for stratification in the early course of disease.

Development and application of a comparative fatty acid analysis method to investigate voriconazole-induced hepatotoxicity.

PubMed

Chen, Guan-yuan; Chiu, Huai-hsuan; Lin, Shu-wen; Tseng, Yufeng Jane; Tsai, Sung-jeng; Kuo, Ching-hua

2015-01-01

As fatty acids play an important role in biological regulation, the profiling of fatty acid expression has been used to discover various disease markers and to understand disease mechanisms. This study developed an effective and accurate comparative fatty acid analysis method using differential labeling to speed up the metabolic profiling of fatty acids. Fatty acids were derivatized with unlabeled (D0) or deuterated (D3) methanol, followed by GC-MS analysis. The comparative fatty acid analysis method was validated using a series of samples with different ratios of D0/D3-labeled fatty acid standards and with mouse liver extracts. Using a lipopolysaccharide (LPS)-treated mouse model, we found that the fatty acid profiles after LPS treatment were similar between the conventional single-sample analysis approach and the proposed comparative approach, with a Pearson's correlation coefficient of approximately 0.96. We applied the comparative method to investigate voriconazole-induced hepatotoxicity and revealed the toxicity mechanism as well as the potential of using fatty acids as toxicity markers. In conclusion, the comparative fatty acid profiling technique was determined to be fast and accurate and allowed the discovery of potential fatty acid biomarkers in a more economical and efficient manner. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparison of Niskin vs. in situ approaches for analysis of gene expression in deep Mediterranean Sea water samples

NASA Astrophysics Data System (ADS)

Edgcomb, V. P.; Taylor, C.; Pachiadaki, M. G.; Honjo, S.; Engstrom, I.; Yakimov, M.

2016-07-01

Obtaining an accurate picture of microbial processes occurring in situ is essential for our understanding of marine biogeochemical cycles of global importance. Water samples are typically collected at depth and returned to the sea surface for processing and downstream experiments. Metatranscriptome analysis is one powerful approach for investigating metabolic activities of microorganisms in their habitat and which can be informative for determining responses of microbiota to disturbances such as the Deepwater Horizon oil spill. For studies of microbial processes occurring in the deep sea, however, sample handling, pressure, and other changes during sample recovery can subject microorganisms to physiological changes that alter the expression profile of labile messenger RNA. Here we report a comparison of gene expression profiles for whole microbial communities in a bathypelagic water column sample collected in the Eastern Mediterranean Sea using Niskin bottle sample collection and a new water column sampler for studies of marine microbial ecology, the Microbial Sampler - In Situ Incubation Device (MS-SID). For some taxa, gene expression profiles from samples collected and preserved in situ were significantly different from potentially more stressful Niskin sampling and preservation on deck. Some categories of transcribed genes also appear to be affected by sample handling more than others. This suggests that for future studies of marine microbial ecology, particularly targeting deep sea samples, an in situ sample collection and preservation approach should be considered.

Integrated analysis of copy number alteration and RNA expression profiles of cancer using a high-resolution whole-genome oligonucleotide array.

PubMed

Jung, Seung-Hyun; Shin, Seung-Hun; Yim, Seon-Hee; Choi, Hye-Sun; Lee, Sug-Hyung; Chung, Yeun-Jun

2009-07-31

Recently, microarray-based comparative genomic hybridization (array-CGH) has emerged as a very efficient technology with higher resolution for the genome-wide identification of copy number alterations (CNA). Although CNAs are thought to affect gene expression, there is no platform currently available for the integrated CNA-expression analysis. To achieve high-resolution copy number analysis integrated with expression profiles, we established human 30k oligoarray-based genome-wide copy number analysis system and explored the applicability of this system for integrated genome and transcriptome analysis using MDA-MB-231 cell line. We compared the CNAs detected by the oligoarray with those detected by the 3k BAC array for validation. The oligoarray identified the single copy difference more accurately and sensitively than the BAC array. Seventeen CNAs detected by both platforms in MDA-MB-231 such as gains of 5p15.33-13.1, 8q11.22-8q21.13, 17p11.2, and losses of 1p32.3, 8p23.3-8p11.21, and 9p21 were consistently identified in previous studies on breast cancer. There were 122 other small CNAs (mean size 1.79 mb) that were detected by oligoarray only, not by BAC-array. We performed genomic qPCR targeting 7 CNA regions, detected by oligoarray only, and one non-CNA region to validate the oligoarray CNA detection. All qPCR results were consistent with the oligoarray-CGH results. When we explored the possibility of combined interpretation of both DNA copy number and RNA expression profiles, mean DNA copy number and RNA expression levels showed a significant correlation. In conclusion, this 30k oligoarray-CGH system can be a reasonable choice for analyzing whole genome CNAs and RNA expression profiles at a lower cost.

Stem cell media culture of melanoma results in the induction of a nonrepresentative neural expression profile.

PubMed

Anaka, Matthew; Freyer, Claudia; Gedye, Craig; Caballero, Otavia; Davis, Ian D; Behren, Andreas; Cebon, Jonathan

2012-02-01

The ability of cell lines to accurately represent cancer is a major concern in preclinical research. Culture of glioma cells as neurospheres in stem cell media (SCM) has been shown to better represent the genotype and phenotype of primary glioblastoma in comparison to serum cell lines. Despite the use of neurosphere-like models of many malignancies, there has been no robust analysis of whether other cancers benefit from a more representative phenotype and genotype when cultured in SCM. We analyzed the growth properties, transcriptional profile, and genotype of melanoma cells grown de novo in SCM, as while melanocytes share a common precursor with neural cells, melanoma frequently demonstrates divergent behavior in cancer stem cell assays. SCM culture of melanoma cells induced a neural lineage gene expression profile that was not representative of matched patient tissue samples and which could be induced in serum cell lines by switching them into SCM. There was no enrichment for expression of putative melanoma stem cell markers, but the SCM expression profile did overlap significantly with that of SCM cultures of glioma, suggesting that the observed phenotype is media-specific rather than melanoma-specific. Xenografts derived from either culture condition provided the best representation of melanoma in situ. Finally, SCM culture of melanoma did not prevent ongoing acquisition of DNA copy number abnormalities. In conclusion, SCM culture of melanoma does not provide a better representation of the phenotype or genotype of metastatic melanoma, and the resulting neural bias could potentially confound therapeutic target identification. Copyright © 2011 AlphaMed Press.

Evidence for the importance of personalized molecular profiling in pancreatic cancer.

PubMed

Lili, Loukia N; Matyunina, Lilya V; Walker, L DeEtte; Daneker, George W; McDonald, John F

2014-03-01

There is a growing body of evidence that targeted gene therapy holds great promise for the future treatment of cancer. A crucial step in this therapy is the accurate identification of appropriate candidate genes/pathways for targeted treatment. One approach is to identify variant genes/pathways that are significantly enriched in groups of afflicted individuals relative to control subjects. However, if there are multiple molecular pathways to the same cancer, the molecular determinants of the disease may be heterogeneous among individuals and possibly go undetected by group analyses. In an effort to explore this question in pancreatic cancer, we compared the most significantly differentially expressed genes/pathways between cancer and control patient samples as determined by group versus personalized analyses. We found little to no overlap between genes/pathways identified by gene expression profiling using group analyses relative to those identified by personalized analyses. Our results indicate that personalized and not group molecular profiling is the most appropriate approach for the identification of putative candidates for targeted gene therapy of pancreatic and perhaps other cancers with heterogeneous molecular etiology.

Extension of the Helmholtz-Smoluchowski velocity to the hydrophobic microchannels with velocity slip.

PubMed

Park, H M; Kim, T W

2009-01-21

Electrokinetic flows through hydrophobic microchannels experience velocity slip at the microchannel wall, which affects volumetric flow rate and solute retention time. The usual method of predicting the volumetric flow rate and velocity profile for hydrophobic microchannels is to solve the Navier-Stokes equation and the Poisson-Boltzmann equation for the electric potential with the boundary condition of velocity slip expressed by the Navier slip coefficient, which is computationally demanding and defies analytic solutions. In the present investigation, we have devised a simple method of predicting the velocity profiles and volumetric flow rates of electrokinetic flows by extending the concept of the Helmholtz-Smoluchowski velocity to microchannels with Navier slip. The extended Helmholtz-Smoluchowski velocity is simple to use and yields accurate results as compared to the exact solutions. Employing the extended Helmholtz-Smoluchowski velocity, the analytical expressions for volumetric flow rate and velocity profile for electrokinetic flows through rectangular microchannels with Navier slip have been obtained at high values of zeta potential. The range of validity of the extended Helmholtz-Smoluchowski velocity is also investigated.

Detecting regulatory gene-environment interactions with unmeasured environmental factors.

PubMed

Fusi, Nicoló; Lippert, Christoph; Borgwardt, Karsten; Lawrence, Neil D; Stegle, Oliver

2013-06-01

Genomic studies have revealed a substantial heritable component of the transcriptional state of the cell. To fully understand the genetic regulation of gene expression variability, it is important to study the effect of genotype in the context of external factors such as alternative environmental conditions. In model systems, explicit environmental perturbations have been considered for this purpose, allowing to directly test for environment-specific genetic effects. However, such experiments are limited to species that can be profiled in controlled environments, hampering their use in important systems such as human. Moreover, even in seemingly tightly regulated experimental conditions, subtle environmental perturbations cannot be ruled out, and hence unknown environmental influences are frequent. Here, we propose a model-based approach to simultaneously infer unmeasured environmental factors from gene expression profiles and use them in genetic analyses, identifying environment-specific associations between polymorphic loci and individual gene expression traits. In extensive simulation studies, we show that our method is able to accurately reconstruct environmental factors and their interactions with genotype in a variety of settings. We further illustrate the use of our model in a real-world dataset in which one environmental factor has been explicitly experimentally controlled. Our method is able to accurately reconstruct the true underlying environmental factor even if it is not given as an input, allowing to detect genuine genotype-environment interactions. In addition to the known environmental factor, we find unmeasured factors involved in novel genotype-environment interactions. Our results suggest that interactions with both known and unknown environmental factors significantly contribute to gene expression variability. and implementation: Software available at http://pmbio.github.io/envGPLVM/. Supplementary data are available at Bioinformatics online.

A long non-coding RNA expression profile can predict early recurrence in hepatocellular carcinoma after curative resection.

PubMed

Lv, Yufeng; Wei, Wenhao; Huang, Zhong; Chen, Zhichao; Fang, Yuan; Pan, Lili; Han, Xueqiong; Xu, Zihai

2018-06-20

The aim of this study was to develop a novel long non-coding RNA (lncRNA) expression signature to accurately predict early recurrence for patients with hepatocellular carcinoma (HCC) after curative resection. Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple lncRNAs with differential expression between early recurrence (ER) group and non-early recurrence (non-ER) group of HCC. Least absolute shrinkage and selection operator (LASSO) for logistic regression models were used to develop a lncRNA-based classifier for predicting ER in the training set. An independent test set was used to validated the predictive value of this classifier. Futhermore, a co-expression network based on these lncRNAs and its highly related genes was constructed and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of genes in the network were performed. We identified 10 differentially expressed lncRNAs, including 3 that were upregulated and 7 that were downregulated in ER group. The lncRNA-based classifier was constructed based on 7 lncRNAs (AL035661.1, PART1, AC011632.1, AC109588.1, AL365361.1, LINC00861 and LINC02084), and its accuracy was 0.83 in training set, 0.87 in test set and 0.84 in total set. And ROC curve analysis showed the AUROC was 0.741 in training set, 0.824 in the test set and 0.765 in total set. A functional enrichment analysis suggested that the genes of which is highly related to 4 lncRNAs were involved in immune system. This 7-lncRNA expression profile can effectively predict the early recurrence after surgical resection for HCC. This article is protected by copyright. All rights reserved.

Reference gene selection for quantitative reverse transcription-polymerase chain reaction normalization during in vitro adventitious rooting in Eucalyptus globulus Labill.

PubMed

de Almeida, Márcia R; Ruedell, Carolina M; Ricachenevsky, Felipe K; Sperotto, Raul A; Pasquali, Giancarlo; Fett-Neto, Arthur G

2010-09-20

Eucalyptus globulus and its hybrids are very important for the cellulose and paper industry mainly due to their low lignin content and frost resistance. However, rooting of cuttings of this species is recalcitrant and exogenous auxin application is often necessary for good root development. To date one of the most accurate methods available for gene expression analysis is quantitative reverse transcription-polymerase chain reaction (qPCR); however, reliable use of this technique requires reference genes for normalization. There is no single reference gene that can be regarded as universal for all experiments and biological materials. Thus, the identification of reliable reference genes must be done for every species and experimental approach. The present study aimed at identifying suitable control genes for normalization of gene expression associated with adventitious rooting in E. globulus microcuttings. By the use of two distinct algorithms, geNorm and NormFinder, we have assessed gene expression stability of eleven candidate reference genes in E. globulus: 18S, ACT2, EF2, EUC12, H2B, IDH, SAND, TIP41, TUA, UBI and 33380. The candidate reference genes were evaluated in microccuttings rooted in vitro, in presence or absence of auxin, along six time-points spanning the process of adventitious rooting. Overall, the stability profiles of these genes determined with each one of the algorithms were very similar. Slight differences were observed in the most stable pair of genes indicated by each program: IDH and SAND for geNorm, and H2B and TUA for NormFinder. Both programs identified UBI and 18S as the most variable genes. To validate these results and select the most suitable reference genes, the expression profile of the ARGONAUTE1 gene was evaluated in relation to the most stable candidate genes indicated by each algorithm. Our study showed that expression stability varied between putative reference genes tested in E. globulus. Based on the AGO1 relative expression profile obtained using the genes suggested by the algorithms, H2B and TUA were considered as the most suitable reference genes for expression studies in E. globulus adventitious rooting. UBI and 18S were unsuitable for use as controls in qPCR related to this process. These findings will enable more accurate and reliable normalization of qPCR results for gene expression studies in this economically important woody plant, particularly related to rooting and clonal propagation.

Reference gene selection for quantitative reverse transcription-polymerase chain reaction normalization during in vitro adventitious rooting in Eucalyptus globulus Labill

PubMed Central

2010-01-01

Background Eucalyptus globulus and its hybrids are very important for the cellulose and paper industry mainly due to their low lignin content and frost resistance. However, rooting of cuttings of this species is recalcitrant and exogenous auxin application is often necessary for good root development. To date one of the most accurate methods available for gene expression analysis is quantitative reverse transcription-polymerase chain reaction (qPCR); however, reliable use of this technique requires reference genes for normalization. There is no single reference gene that can be regarded as universal for all experiments and biological materials. Thus, the identification of reliable reference genes must be done for every species and experimental approach. The present study aimed at identifying suitable control genes for normalization of gene expression associated with adventitious rooting in E. globulus microcuttings. Results By the use of two distinct algorithms, geNorm and NormFinder, we have assessed gene expression stability of eleven candidate reference genes in E. globulus: 18S, ACT2, EF2, EUC12, H2B, IDH, SAND, TIP41, TUA, UBI and 33380. The candidate reference genes were evaluated in microccuttings rooted in vitro, in presence or absence of auxin, along six time-points spanning the process of adventitious rooting. Overall, the stability profiles of these genes determined with each one of the algorithms were very similar. Slight differences were observed in the most stable pair of genes indicated by each program: IDH and SAND for geNorm, and H2B and TUA for NormFinder. Both programs indentified UBI and 18S as the most variable genes. To validate these results and select the most suitable reference genes, the expression profile of the ARGONAUTE1 gene was evaluated in relation to the most stable candidate genes indicated by each algorithm. Conclusion Our study showed that expression stability varied between putative reference genes tested in E. globulus. Based on the AGO1 relative expression profile obtained using the genes suggested by the algorithms, H2B and TUA were considered as the most suitable reference genes for expression studies in E. globulus adventitious rooting. UBI and 18S were unsuitable for use as controls in qPCR related to this process. These findings will enable more accurate and reliable normalization of qPCR results for gene expression studies in this economically important woody plant, particularly related to rooting and clonal propagation. PMID:20854682

Correlating cellular and molecular signatures of mucosal immunity that distinguish HIV controllers from noncontrollers.

PubMed

Loke, P'ng; Favre, David; Hunt, Peter W; Leung, Jacqueline M; Kanwar, Bittoo; Martin, Jeffrey N; Deeks, Steven G; McCune, Joseph M

2010-04-15

HIV "controllers" are persons infected with human immunodeficiency virus, type I (HIV) who maintain long-term control of viremia without antiviral therapy and who usually do not develop the acquired immune deficiency syndrome (AIDS). In this study, we have correlated results from polychromatic flow cytometry and oligonucleotide expression arrays to characterize the mucosal immune responses of these subjects in relation to untreated HIV(+) persons with high viral loads and progressive disease ("noncontrollers"). Paired peripheral blood and rectosigmoid biopsies were analyzed from 9 controllers and 11 noncontrollers. Several cellular immune parameters were found to be concordant between the 2 compartments. Compared with noncontrollers, the mucosal tissues of controllers had similar levels of effector T cells and fewer regulatory T cells (Tregs). Using principal component analysis to correlate immunologic parameters with gene expression profiles, transcripts were identified that accurately distinguished between controllers and noncontrollers. Direct 2-way comparison also revealed genes that are significantly different in their expression between controllers and noncontrollers, all of which had reduced expression in controllers. In addition to providing an approach that integrates flow cytometry datasets with transcriptional profiling analysis, these results underscore the importance of the sustained inflammatory response that attends progressive HIV disease.

Evaluation of Reference Genes for Quantitative Real-Time PCR in Oil Palm Elite Planting Materials Propagated by Tissue Culture

PubMed Central

Chan, Pek-Lan; Rose, Ray J.; Abdul Murad, Abdul Munir; Zainal, Zamri; Leslie Low, Eng-Ti; Ooi, Leslie Cheng-Li; Ooi, Siew-Eng; Yahya, Suzaini; Singh, Rajinder

2014-01-01

Background The somatic embryogenesis tissue culture process has been utilized to propagate high yielding oil palm. Due to the low callogenesis and embryogenesis rates, molecular studies were initiated to identify genes regulating the process, and their expression levels are usually quantified using reverse transcription quantitative real-time PCR (RT-qPCR). With the recent release of oil palm genome sequences, it is crucial to establish a proper strategy for gene analysis using RT-qPCR. Selection of the most suitable reference genes should be performed for accurate quantification of gene expression levels. Results In this study, eight candidate reference genes selected from cDNA microarray study and literature review were evaluated comprehensively across 26 tissue culture samples using RT-qPCR. These samples were collected from two tissue culture lines and media treatments, which consisted of leaf explants cultures, callus and embryoids from consecutive developmental stages. Three statistical algorithms (geNorm, NormFinder and BestKeeper) confirmed that the expression stability of novel reference genes (pOP-EA01332, PD00380 and PD00569) outperformed classical housekeeping genes (GAPDH, NAD5, TUBULIN, UBIQUITIN and ACTIN). PD00380 and PD00569 were identified as the most stably expressed genes in total samples, MA2 and MA8 tissue culture lines. Their applicability to validate the expression profiles of a putative ethylene-responsive transcription factor 3-like gene demonstrated the importance of using the geometric mean of two genes for normalization. Conclusions Systematic selection of the most stably expressed reference genes for RT-qPCR was established in oil palm tissue culture samples. PD00380 and PD00569 were selected for accurate and reliable normalization of gene expression data from RT-qPCR. These data will be valuable to the research associated with the tissue culture process. Also, the method described here will facilitate the selection of appropriate reference genes in other oil palm tissues and in the expression profiling of genes relating to yield, biotic and abiotic stresses. PMID:24927412

RWEN: Response-Weighted Elastic Net For Prediction of Chemosensitivity of Cancer Cell Lines. | Office of Cancer Genomics

Cancer.gov

Motivation: In recent years there have been several efforts to generate sensitivity profiles of collections of genomically characterized cell lines to panels of candidate therapeutic compounds. These data provide the basis for the development of in silico models of sensitivity based on cellular, genetic, or expression biomarkers of cancer cells. However, a remaining challenge is an efficient way to identify accurate sets of biomarkers to validate.

Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework.

PubMed

Yang, Lingjian; Ainali, Chrysanthi; Tsoka, Sophia; Papageorgiou, Lazaros G

2014-12-05

Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outcome. Traditional approaches where expression of genes were treated independently suffer from low prediction accuracy and difficulty of biological interpretation. Current research efforts focus on integrating information on protein interactions through biochemical pathway datasets with expression profiles to propose pathway-based classifiers that can enhance disease diagnosis and prognosis. As most of the pathway activity inference methods in literature are either unsupervised or applied on two-class datasets, there is good scope to address such limitations by proposing novel methodologies. A supervised multiclass pathway activity inference method using optimisation techniques is reported. For each pathway expression dataset, patterns of its constituent genes are summarised into one composite feature, termed pathway activity, and a novel mathematical programming model is proposed to infer this feature as a weighted linear summation of expression of its constituent genes. Gene weights are determined by the optimisation model, in a way that the resulting pathway activity has the optimal discriminative power with regards to disease phenotypes. Classification is then performed on the resulting low-dimensional pathway activity profile. The model was evaluated through a variety of published gene expression profiles that cover different types of disease. We show that not only does it improve classification accuracy, but it can also perform well in multiclass disease datasets, a limitation of other approaches from the literature. Desirable features of the model include the ability to control the maximum number of genes that may participate in determining pathway activity, which may be pre-specified by the user. Overall, this work highlights the potential of building pathway-based multi-phenotype classifiers for accurate disease diagnosis and prognosis problems.

Theory of Fiber Optical Bragg Grating: Revisited

NASA Technical Reports Server (NTRS)

Tai, H.

2003-01-01

The reflected signature of an optical fiber Bragg grating is analyzed using the transfer function method. This approach is capable to cast all relevant quantities into proper places and provides a better physical understanding. The relationship between reflected signal, number of periods, index of refraction, and reflected wave phase is elucidated. The condition for which the maximum reflectivity is achieved is fully examined. We also have derived an expression to predict the reflectivity minima accurately when the reflected wave is detuned. Furthermore, using the segmented potential approach, this model can handle arbitrary index of refraction profiles and compare the strength of optical reflectivity of different profiles. The condition of a non-uniform grating is also addressed.

A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification.

PubMed

Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang

2017-08-23

Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.

Using Genome-Wide Expression Profiling to Define Gene Networks Relevant to the Study of Complex Traits: From RNA Integrity to Network Topology

PubMed Central

O'Brien, M.A.; Costin, B.N.; Miles, M.F.

2014-01-01

Postgenomic studies of the function of genes and their role in disease have now become an area of intense study since efforts to define the raw sequence material of the genome have largely been completed. The use of whole-genome approaches such as microarray expression profiling and, more recently, RNA-sequence analysis of transcript abundance has allowed an unprecedented look at the workings of the genome. However, the accurate derivation of such high-throughput data and their analysis in terms of biological function has been critical to truly leveraging the postgenomic revolution. This chapter will describe an approach that focuses on the use of gene networks to both organize and interpret genomic expression data. Such networks, derived from statistical analysis of large genomic datasets and the application of multiple bioinformatics data resources, poten-tially allow the identification of key control elements for networks associated with human disease, and thus may lead to derivation of novel therapeutic approaches. However, as discussed in this chapter, the leveraging of such networks cannot occur without a thorough understanding of the technical and statistical factors influencing the derivation of genomic expression data. Thus, while the catch phrase may be “it's the network … stupid,” the understanding of factors extending from RNA isolation to genomic profiling technique, multivariate statistics, and bioinformatics are all critical to defining fully useful gene networks for study of complex biology. PMID:23195313

Pediatric Crohn disease patients exhibit specific ileal transcriptome and microbiome signature.

PubMed

Haberman, Yael; Tickle, Timothy L; Dexheimer, Phillip J; Kim, Mi-Ok; Tang, Dora; Karns, Rebekah; Baldassano, Robert N; Noe, Joshua D; Rosh, Joel; Markowitz, James; Heyman, Melvin B; Griffiths, Anne M; Crandall, Wallace V; Mack, David R; Baker, Susan S; Huttenhower, Curtis; Keljo, David J; Hyams, Jeffrey S; Kugathasan, Subra; Walters, Thomas D; Aronow, Bruce; Xavier, Ramnik J; Gevers, Dirk; Denson, Lee A

2014-08-01

Interactions between the host and gut microbial community likely contribute to Crohn disease (CD) pathogenesis; however, direct evidence for these interactions at the onset of disease is lacking. Here, we characterized the global pattern of ileal gene expression and the ileal microbial community in 359 treatment-naive pediatric patients with CD, patients with ulcerative colitis (UC), and control individuals. We identified core gene expression profiles and microbial communities in the affected CD ilea that are preserved in the unaffected ilea of patients with colon-only CD but not present in those with UC or control individuals; therefore, this signature is specific to CD and independent of clinical inflammation. An abnormal increase of antimicrobial dual oxidase (DUOX2) expression was detected in association with an expansion of Proteobacteria in both UC and CD, while expression of lipoprotein APOA1 gene was downregulated and associated with CD-specific alterations in Firmicutes. The increased DUOX2 and decreased APOA1 gene expression signature favored oxidative stress and Th1 polarization and was maximally altered in patients with more severe mucosal injury. A regression model that included APOA1 gene expression and microbial abundance more accurately predicted month 6 steroid-free remission than a model using clinical factors alone. These CD-specific host and microbe profiles identify the ileum as the primary inductive site for all forms of CD and may direct prognostic and therapeutic approaches.

Gene expression profiling of whole blood: Comparison of target preparation methods for accurate and reproducible microarray analysis

PubMed Central

Vartanian, Kristina; Slottke, Rachel; Johnstone, Timothy; Casale, Amanda; Planck, Stephen R; Choi, Dongseok; Smith, Justine R; Rosenbaum, James T; Harrington, Christina A

2009-01-01

Background Peripheral blood is an accessible and informative source of transcriptomal information for many human disease and pharmacogenomic studies. While there can be significant advantages to analyzing RNA isolated from whole blood, particularly in clinical studies, the preparation of samples for microarray analysis is complicated by the need to minimize artifacts associated with highly abundant globin RNA transcripts. The impact of globin RNA transcripts on expression profiling data can potentially be reduced by using RNA preparation and labeling methods that remove or block globin RNA during the microarray assay. We compared four different methods for preparing microarray hybridization targets from human whole blood collected in PAXGene tubes. Three of the methods utilized the Affymetrix one-cycle cDNA synthesis/in vitro transcription protocol but varied treatment of input RNA as follows: i. no treatment; ii. treatment with GLOBINclear; or iii. treatment with globin PNA oligos. In the fourth method cDNA targets were prepared with the Ovation amplification and labeling system. Results We find that microarray targets generated with labeling methods that reduce globin mRNA levels or minimize the impact of globin transcripts during hybridization detect more transcripts in the microarray assay compared with the standard Affymetrix method. Comparison of microarray results with quantitative PCR analysis of a panel of genes from the NF-kappa B pathway shows good correlation of transcript measurements produced with all four target preparation methods, although method-specific differences in overall correlation were observed. The impact of freezing blood collected in PAXGene tubes on data reproducibility was also examined. Expression profiles show little or no difference when RNA is extracted from either fresh or frozen blood samples. Conclusion RNA preparation and labeling methods designed to reduce the impact of globin mRNA transcripts can significantly improve the sensitivity of the DNA microarray expression profiling assay for whole blood samples. While blockage of globin transcripts during first strand cDNA synthesis with globin PNAs resulted in the best overall performance in this study, we conclude that selection of a protocol for expression profiling studies in blood should depend on several factors, including implementation requirements of the method and study design. RNA isolated from either freshly collected or frozen blood samples stored in PAXGene tubes can be used without altering gene expression profiles. PMID:19123946

miR-MaGiC improves quantification accuracy for small RNA-seq.

PubMed

Russell, Pamela H; Vestal, Brian; Shi, Wen; Rudra, Pratyaydipta D; Dowell, Robin; Radcliffe, Richard; Saba, Laura; Kechris, Katerina

2018-05-15

Many tools have been developed to profile microRNA (miRNA) expression from small RNA-seq data. These tools must contend with several issues: the small size of miRNAs, the small number of unique miRNAs, the fact that similar miRNAs can be transcribed from multiple loci, and the presence of miRNA isoforms known as isomiRs. Methods failing to address these issues can return misleading information. We propose a novel quantification method designed to address these concerns. We present miR-MaGiC, a novel miRNA quantification method, implemented as a cross-platform tool in Java. miR-MaGiC performs stringent mapping to a core region of each miRNA and defines a meaningful set of target miRNA sequences by collapsing the miRNA space to "functional groups". We hypothesize that these two features, mapping stringency and collapsing, provide more optimal quantification to a more meaningful unit (i.e., miRNA family). We test miR-MaGiC and several published methods on 210 small RNA-seq libraries, evaluating each method's ability to accurately reflect global miRNA expression profiles. We define accuracy as total counts close to the total number of input reads originating from miRNAs. We find that miR-MaGiC, which incorporates both stringency and collapsing, provides the most accurate counts.

A translatable predictor of human radiation exposure.

PubMed

Lucas, Joseph; Dressman, Holly K; Suchindran, Sunil; Nakamura, Mai; Chao, Nelson J; Himburg, Heather; Minor, Kerry; Phillips, Gary; Ross, Joel; Abedi, Majid; Terbrueggen, Robert; Chute, John P

2014-01-01

Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major threat to both public health and national security. In the event of a radiological or nuclear disaster, rapid and accurate biodosimetry of thousands of potentially affected individuals will be essential for effective medical management to occur. Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood (PB) and humans treated with total body irradiation (TBI). Interestingly, a gene expression profile developed via analysis of murine PB radiation response alone was inaccurate in predicting human radiation injury. In contrast, generation of a gene expression profile which incorporated data from ex vivo irradiated human PB and human TBI patients yielded an 18-gene radiation classifier which was highly accurate at predicting human radiation status and discriminating medically relevant radiation dose levels in human samples. Although the patient population was relatively small, the accuracy of this classifier in discriminating radiation dose levels in human TBI patients was not substantially confounded by gender, diagnosis or prior exposure to chemotherapy. We have further incorporated genes from this human radiation signature into a rapid and high-throughput chemical ligation-dependent probe amplification assay (CLPA) which was able to discriminate radiation dose levels in a pilot study of ex vivo irradiated human blood and samples from human TBI patients. Our results illustrate the potential for translation of a human genetic signature for the diagnosis of human radiation exposure and suggest the basis for further testing of CLPA as a candidate biodosimetric assay.

Introducing GAMER: A fast and accurate method for ray-tracing galaxies using procedural noise

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

Groeneboom, N. E.; Dahle, H., E-mail: nicolaag@astro.uio.no

2014-03-10

We developed a novel approach for fast and accurate ray-tracing of galaxies using procedural noise fields. Our method allows for efficient and realistic rendering of synthetic galaxy morphologies, where individual components such as the bulge, disk, stars, and dust can be synthesized in different wavelengths. These components follow empirically motivated overall intensity profiles but contain an additional procedural noise component that gives rise to complex natural patterns that mimic interstellar dust and star-forming regions. These patterns produce more realistic-looking galaxy images than using analytical expressions alone. The method is fully parallelized and creates accurate high- and low- resolution images thatmore » can be used, for example, in codes simulating strong and weak gravitational lensing. In addition to having a user-friendly graphical user interface, the C++ software package GAMER is easy to implement into an existing code.« less

Introducing GAMER: A Fast and Accurate Method for Ray-tracing Galaxies Using Procedural Noise

NASA Astrophysics Data System (ADS)

Groeneboom, N. E.; Dahle, H.

2014-03-01

We developed a novel approach for fast and accurate ray-tracing of galaxies using procedural noise fields. Our method allows for efficient and realistic rendering of synthetic galaxy morphologies, where individual components such as the bulge, disk, stars, and dust can be synthesized in different wavelengths. These components follow empirically motivated overall intensity profiles but contain an additional procedural noise component that gives rise to complex natural patterns that mimic interstellar dust and star-forming regions. These patterns produce more realistic-looking galaxy images than using analytical expressions alone. The method is fully parallelized and creates accurate high- and low- resolution images that can be used, for example, in codes simulating strong and weak gravitational lensing. In addition to having a user-friendly graphical user interface, the C++ software package GAMER is easy to implement into an existing code.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

PubMed Central

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

PubMed

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

Molecular Classifiers for Acute Kidney Transplant Rejection in Peripheral Blood by Whole Genome Gene Expression Profiling

PubMed Central

Kurian, S. M.; Williams, A. N.; Gelbart, T.; Campbell, D.; Mondala, T. S.; Head, S. R.; Horvath, S.; Gaber, L.; Thompson, R.; Whisenant, T.; Lin, W.; Langfelder, P.; Robison, E. H.; Schaffer, R. L.; Fisher, J. S.; Friedewald, J.; Flechner, S. M.; Chan, L. K.; Wiseman, A. C.; Shidban, H.; Mendez, R.; Heilman, R.; Abecassis, M. M.; Marsh, C. L.; Salomon, D. R.

2015-01-01

There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction. PMID:24725967

Quantitative confirmation of diffusion-limited oxidation theories

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

Gillen, K.T.; Clough, R.L.

1990-01-01

Diffusion-limited (heterogeneous) oxidation effects are often important for studies of polymer degradation. Such effects are common in polymers subjected to ionizing radiation at relatively high dose rate. To better understand the underlying oxidation processes and to aid in the planning of accelerated aging studies, it would be desirable to be able to monitor and quantitatively understand these effects. In this paper, we briefly review a theoretical diffusion approach which derives model profiles for oxygen surrounded sheets of material by combining oxygen permeation rates with kinetically based oxygen consumption expressions. The theory leads to a simple governing expression involving the oxygenmore » consumption and permeation rates together with two model parameters {alpha} and {beta}. To test the theory, gamma-initiated oxidation of a sheet of commercially formulated EPDM rubber was performed under conditions which led to diffusion-limited oxidation. Profile shapes from the theoretical treatments are shown to accurately fit experimentally derived oxidation profiles. In addition, direct measurements on the same EPDM material of the oxygen consumption and permeation rates, together with values of {alpha} and {beta} derived from the fitting procedure, allow us to quantitatively confirm for the first time the governing theoretical relationship. 17 refs., 3 figs.« less

The role of molecular diagnostic testing in the management of thyroid nodules.

PubMed

Moore, Maureen D; Panjwani, Suraj; Gray, Katherine D; Finnerty, Brendan M; Zarnegar, Rasa; Fahey, Thomas J

2017-06-01

Fine needle aspiration (FNA) with cytologic examination remains the standard of care for investigation of thyroid nodules. However, as many as 30% of FNA samples are cytologically indeterminate for malignancy, which confounds clinical management. To reduce the burden of repeat diagnostic testing and unnecessary surgery, there has been extensive investigation into molecular markers that can be detected on FNA specimens to more accurately stratify a patient's risk of malignancy. Areas covered: In this review, the authors discuss recent evidence and progress in molecular markers used in the diagnosis of thyroid cancer highlighting somatic gene alterations, molecular technologies and microRNA analysis. Expert commentary: The goal of molecular markers is to improve diagnostic accuracy and aid clinicians in the preoperative management of thyroid lesions. Modalities such as direct mutation analysis, mRNA gene expression profiling, next-generation sequencing, and miRNA expression profiling have been explored to improve the diagnostic accuracy of thyroid nodule FNA. Although no perfect test has been discovered, molecular diagnostic testing has revolutionized the management of thyroid nodules.

ALDH1 is an immunohistochemical diagnostic marker for solitary fibrous tumours and haemangiopericytomas of the meninges emerging from gene profiling study

PubMed Central

2013-01-01

Background Solitary Fibrous Tumours (SFT) and haemangiopericytomas (HPC) are rare meningeal tumours that have to be distinguished from meningiomas and more rarely from synovial sarcomas. We recently found that ALDH1A1 was overexpressed in SFT and HPC as compared to soft tissue sarcomas. Using whole-genome DNA microarrays, we defined the gene expression profiles of 16 SFT/HPC (9 HPC and 7 SFT). Expression profiles were compared to publicly available expression profiles of additional SFT or HPC, meningiomas and synovial sarcomas. We also performed an immunohistochemical (IHC) study with anti-ALDH1 and anti-CD34 antibodies on Tissue Micro-Arrays including 38 SFT (25 meningeal and 13 extrameningeal), 55 meningeal haemangiopericytomas (24 grade II, 31 grade III), 163 meningiomas (86 grade I, 62 grade II, 15 grade III) and 98 genetically confirmed synovial sarcomas. Results ALDH1A1 gene was overexpressed in SFT/HPC, as compared to meningiomas and synovial sarcomas. These findings were confirmed at the protein level. 84% of the SFT and 85.4% of the HPC were positive with anti-ALDH1 antibody, while only 7.1% of synovial sarcomas and 1.2% of meningiomas showed consistent expression. Positivity was usually more diffuse in SFT/HPC compared to other tumours with more than 50% of tumour cells immunostained in 32% of SFT and 50.8% of HPC. ALDH1 was a sensitive and specific marker for the diagnosis of SFT (SE = 84%, SP = 98.8%) and HPC (SE = 84.5%, SP = 98.7%) of the meninges. In association with CD34, ALDH1 expression had a specificity and positive predictive value of 100%. Conclusion We show that ALDH1, a stem cell marker, is an accurate diagnostic marker for SFT and HPC, which improves the diagnostic value of CD34. ALDH1 could also be a new therapeutic target for these tumours which are not sensitive to conventional chemotherapy. PMID:24252471

Spatial reconstruction of single-cell gene expression data.

PubMed

Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

2015-05-01

Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

Two-dimensional dispersion of magnetostatic volume spin waves

NASA Astrophysics Data System (ADS)

Buijnsters, Frank J.; van Tilburg, Lennert J. A.; Fasolino, Annalisa; Katsnelson, Mikhail I.

2018-06-01

Owing to the dipolar (magnetostatic) interaction, long-wavelength spin waves in in-plane magnetized films show an unusual dispersion behavior, which can be mathematically described by the model of and and refinements thereof. However, solving the two-dimensional dispersion requires the evaluation of a set of coupled transcendental equations and one has to rely on numerics. In this work, we present a systematic perturbative analysis of the spin wave model. An expansion in the in-plane wavevector allows us to obtain explicit closed-form expressions for the dispersion relation and mode profiles in various asymptotic regimes. Moreover, we derive a very accurate semi-analytical expression for the dispersion relation of the lowest-frequency mode that is straightforward to evaluate.

BJUT at TREC 2015 Microblog Track: Real-Time Filtering Using Non-negative Matrix Factorization

DTIC Science & Technology

2015-11-20

information to extend the query, al- leviates the problem of concept drift in query expansion. In User profiles Twitter Google Bing accurate ambiguity...index as the query expansion document set; second- ly,put the interest file in twitter search energy to get back the relevant twetts, the interest in...for clustering is demonstrated in Figure 2. We will be the result of the search energy Twitter as the original expression of interest, the initial

Characterization and response of newly developed high-grade glioma cultures to the tyrosine kinase inhibitors, erlotinib, gefitinib and imatinib

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

Kinsella, Paula, E-mail: paula.kinsella@dcu.ie; Howley, Rachel, E-mail: rhowley@rcsi.ie; Doolan, Padraig, E-mail: padraig.doolan@dcu.ie

2012-03-10

High-grade gliomas (HGG), are the most common aggressive brain tumours in adults. Inhibitors targeting growth factor signalling pathways in glioma have shown a low clinical response rate. To accurately evaluate response to targeted therapies further in vitro studies are necessary. Growth factor pathway expression using epidermal growth factor receptor (EGFR), mutant EGFR (EGFRvIII), platelet derived growth factor receptor (PDGFR), C-Kit and C-Abl together with phosphatase and tensin homolog (PTEN) expression and downstream activation of AKT and phosphorylated ribosomal protein S6 (P70S6K) was analysed in 26 primary glioma cultures treated with the tyrosine kinase inhibitors (TKIs) erlotinib, gefitinib and imatinib. Responsemore » to TKIs was assessed using 50% inhibitory concentrations (IC{sub 50}). Response for each culture was compared with the EGFR/PDGFR immunocytochemical pathway profile using hierarchical cluster analysis (HCA) and principal component analysis (PCA). Erlotinib response was not strongly associated with high expression of the growth factor pathway components. PTEN expression did not correlate with response to any of the three TKIs. Increased EGFR expression was associated with gefitinib response; increased PDGFR-{alpha} expression was associated with imatinib response. The results of this in vitro study suggest gefitinib and imatinib may have therapeutic potential in HGG tumours with a corresponding growth factor receptor expression profile. -- Highlights: Black-Right-Pointing-Pointer Non-responders had low EGFR expression, high PDGFR-{beta}, and a low proliferation rate. Black-Right-Pointing-Pointer PTEN is not indicative of response to a TKI. Black-Right-Pointing-Pointer Erlotinib response was not associated with expression of the proteins examined. Black-Right-Pointing-Pointer Imatinib-response correlated with expression of PDGFR-{alpha}. Black-Right-Pointing-Pointer Gefitinib response correlated with increased expression of EGFR.« less

MOPED 2.5—An Integrated Multi-Omics Resource: Multi-Omics Profiling Expression Database Now Includes Transcriptomics Data

PubMed Central

Montague, Elizabeth; Stanberry, Larissa; Higdon, Roger; Janko, Imre; Lee, Elaine; Anderson, Nathaniel; Choiniere, John; Stewart, Elizabeth; Yandl, Gregory; Broomall, William; Kolker, Natali

2014-01-01

Abstract Multi-omics data-driven scientific discovery crucially rests on high-throughput technologies and data sharing. Currently, data are scattered across single omics repositories, stored in varying raw and processed formats, and are often accompanied by limited or no metadata. The Multi-Omics Profiling Expression Database (MOPED, http://moped.proteinspire.org) version 2.5 is a freely accessible multi-omics expression database. Continual improvement and expansion of MOPED is driven by feedback from the Life Sciences Community. In order to meet the emergent need for an integrated multi-omics data resource, MOPED 2.5 now includes gene relative expression data in addition to protein absolute and relative expression data from over 250 large-scale experiments. To facilitate accurate integration of experiments and increase reproducibility, MOPED provides extensive metadata through the Data-Enabled Life Sciences Alliance (DELSA Global, http://delsaglobal.org) metadata checklist. MOPED 2.5 has greatly increased the number of proteomics absolute and relative expression records to over 500,000, in addition to adding more than four million transcriptomics relative expression records. MOPED has an intuitive user interface with tabs for querying different types of omics expression data and new tools for data visualization. Summary information including expression data, pathway mappings, and direct connection between proteins and genes can be viewed on Protein and Gene Details pages. These connections in MOPED provide a context for multi-omics expression data exploration. Researchers are encouraged to submit omics data which will be consistently processed into expression summaries. MOPED as a multi-omics data resource is a pivotal public database, interdisciplinary knowledge resource, and platform for multi-omics understanding. PMID:24910945

SUPERMODEL ANALYSIS OF GALAXY CLUSTERS

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

Fusco-Femiano, R.; Cavaliere, A.; Lapi, A.

2009-11-01

We present the analysis of the X-ray brightness and temperature profiles for six clusters belonging to both the Cool Core (CC) and Non Cool Core (NCC) classes, in terms of the Supermodel (SM) developed by Cavaliere et al. Based on the gravitational wells set by the dark matter (DM) halos, the SM straightforwardly expresses the equilibrium of the intracluster plasma (ICP) modulated by the entropy deposited at the boundary by standing shocks from gravitational accretion, and injected at the center by outgoing blast waves from mergers or from outbursts of active galactic nuclei. The cluster set analyzed here highlights notmore » only how simply the SM represents the main dichotomy CC versus NCC clusters in terms of a few ICP parameters governing the radial entropy run, but also how accurately it fits even complex brightness and temperature profiles. For CC clusters like A2199 and A2597, the SM with a low level of central entropy straightforwardly yields the characteristic peaked profile of the temperature marked by a decline toward the center, without requiring currently strong radiative cooling and high mass deposition rates. NCC clusters like A1656 require instead a central entropy floor of a substantial level, and some like A2256 and even more A644 feature structured temperature profiles that also call for a definite floor extension; in such conditions the SM accurately fits the observations, and suggests that in these clusters the ICP has been just remolded by a merger event, in the way of a remnant cool core. The SM also predicts that DM halos with high concentration should correlate with flatter entropy profiles and steeper brightness in the outskirts; this is indeed the case with A1689, for which from X-rays we find concentration values c approx 10, the hallmark of an early halo formation. Thus, we show the SM to constitute a fast tool not only to provide wide libraries of accurate fits to X-ray temperature and density profiles, but also to retrieve from the ICP archives specific information concerning the physical histories of DM and baryons in the inner and the outer cluster regions.« less

Combining differential expression, chromosomal and pathway analyses for the molecular characterization of renal cell carcinoma

PubMed Central

Furge, Kyle A; Dykema, Karl; Petillo, David; Westphal, Michael; Zhang, Zhongfa; Kort, Eric J; Teh, Bin Tean

2007-01-01

Using high-throughput gene-expression profiling technology, we can now gain a better understanding of the complex biology that is taking place in cancer cells. This complexity is largely dictated by the abnormal genetic makeup of the cancer cells. This abnormal genetic makeup can have profound effects on cellular activities such as cell growth, cell survival and other regulatory processes. Based on the pattern of gene expression, or molecular signatures of the tumours, we can distinguish or subclassify different types of cancers according to their cell of origin, behaviour, and the way they respond to therapeutic agents and radiation. These approaches will lead to better molecular subclassification of tumours, the basis of personalized medicine. We have, to date, done whole-genome microarray gene-expression profiling on several hundreds of kidney tumours. We adopt a combined bioinformatic approach, based on an integrative analysis of the gene-expression data. These data are used to identify both cytogenetic abnormalities and molecular pathways that are deregulated in renal cell carcinoma (RCC). For example, we have identified the deregulation of the VHL-hypoxia pathway in clear-cell RCC, as previously known, and the c-Myc pathway in aggressive papillary RCC. Besides the more common clear-cell, papillary and chromophobe RCCs, we are currently characterizing the molecular signatures of rarer forms of renal neoplasia such as carcinoma of the collecting ducts, mixed epithelial and stromal tumours, chromosome Xp11 translocations associated with papillary RCC, renal medullary carcinoma, mucinous tubular and spindle-cell carcinoma, and a group of unclassified tumours. Continued development and improvement in the field of molecular profiling will better characterize cancer and provide more accurate diagnosis, prognosis and prediction of drug response. PMID:18542781

Defining the molecular profile of planarian pluripotent stem cells using a combinatorial RNAseq, RNA interference and irradiation approach.

PubMed

Solana, Jordi; Kao, Damian; Mihaylova, Yuliana; Jaber-Hijazi, Farah; Malla, Sunir; Wilson, Ray; Aboobaker, Aziz

2012-01-01

Planarian stem cells, or neoblasts, drive the almost unlimited regeneration capacities of freshwater planarians. Neoblasts are traditionally described by their morphological features and by the fact that they are the only proliferative cell type in asexual planarians. Therefore, they can be specifically eliminated by irradiation. Irradiation, however, is likely to induce transcriptome-wide changes in gene expression that are not associated with neoblast ablation. This has affected the accurate description of their specific transcriptomic profile. We introduce the use of Smed-histone-2B RNA interference (RNAi) for genetic ablation of neoblast cells in Schmidtea mediterranea as an alternative to irradiation. We characterize the rapid, neoblast-specific phenotype induced by Smed-histone-2B RNAi, resulting in neoblast ablation. We compare and triangulate RNA-seq data after using both irradiation and Smed-histone-2B RNAi over a time course as means of neoblast ablation. Our analyses show that Smed-histone-2B RNAi eliminates neoblast gene expression with high specificity and discrimination from gene expression in other cellular compartments. We compile a high confidence list of genes downregulated by both irradiation and Smed-histone-2B RNAi and validate their expression in neoblast cells. Lastly, we analyze the overall expression profile of neoblast cells. Our list of neoblast genes parallels their morphological features and is highly enriched for nuclear components, chromatin remodeling factors, RNA splicing factors, RNA granule components and the machinery of cell division. Our data reveal that the regulation of planarian stem cells relies on posttranscriptional regulatory mechanisms and suggest that planarians are an ideal model for this understudied aspect of stem cell biology.

Defining the molecular profile of planarian pluripotent stem cells using a combinatorial RNA-seq, RNA interference and irradiation approach

PubMed Central

2012-01-01

Background Planarian stem cells, or neoblasts, drive the almost unlimited regeneration capacities of freshwater planarians. Neoblasts are traditionally described by their morphological features and by the fact that they are the only proliferative cell type in asexual planarians. Therefore, they can be specifically eliminated by irradiation. Irradiation, however, is likely to induce transcriptome-wide changes in gene expression that are not associated with neoblast ablation. This has affected the accurate description of their specific transcriptomic profile. Results We introduce the use of Smed-histone-2B RNA interference (RNAi) for genetic ablation of neoblast cells in Schmidtea mediterranea as an alternative to irradiation. We characterize the rapid, neoblast-specific phenotype induced by Smed-histone-2B RNAi, resulting in neoblast ablation. We compare and triangulate RNA-seq data after using both irradiation and Smed-histone-2B RNAi over a time course as means of neoblast ablation. Our analyses show that Smed-histone-2B RNAi eliminates neoblast gene expression with high specificity and discrimination from gene expression in other cellular compartments. We compile a high confidence list of genes downregulated by both irradiation and Smed-histone-2B RNAi and validate their expression in neoblast cells. Lastly, we analyze the overall expression profile of neoblast cells. Conclusions Our list of neoblast genes parallels their morphological features and is highly enriched for nuclear components, chromatin remodeling factors, RNA splicing factors, RNA granule components and the machinery of cell division. Our data reveal that the regulation of planarian stem cells relies on posttranscriptional regulatory mechanisms and suggest that planarians are an ideal model for this understudied aspect of stem cell biology. PMID:22439894

The written mathematical communication profile of prospective math teacher in mathematical proving

NASA Astrophysics Data System (ADS)

Pantaleon, K. V.; Juniati, D.; Lukito, A.; Mandur, K.

2018-01-01

Written mathematical communication is the process of expressing mathematical ideas and understanding in writing. It is one of the important aspects that must be mastered by the prospective math teacher as tool of knowledge transfer. This research was a qualitative research that aimed to describe the mathematical communication profile of the prospective mathematics teacher in mathematical proving. This research involved 48 students of Mathematics Education Study Program; one of them with moderate math skills was chosen as the main subject. Data were collected through tests, assignments, and task-based interviews. The results of this study point out that in the proof of geometry, the subject explains what is understood, presents the idea in the form of drawing and symbols, and explains the content/meaning of a representation accurately and clearly, but the subject can not convey the argument systematically and logically. Whereas in the proof of algebra, the subject describes what is understood, explains the method used, and describes the content/meaning of a symbolic representation accurately, systematically, logically, but the argument presented is not clear because it is insufficient detailed and complete.

An accurate analytic description of neutrino oscillations in matter

NASA Astrophysics Data System (ADS)

Akhmedov, E. Kh.; Niro, Viviana

2008-12-01

A simple closed-form analytic expression for the probability of two-flavour neutrino oscillations in a matter with an arbitrary density profile is derived. Our formula is based on a perturbative expansion and allows an easy calculation of higher order corrections. The expansion parameter is small when the density changes relatively slowly along the neutrino path and/or neutrino energy is not very close to the Mikheyev-Smirnov-Wolfenstein (MSW) resonance energy. Our approximation is not equivalent to the adiabatic approximation and actually goes beyond it. We demonstrate the validity of our results using a few model density profiles, including the PREM density profile of the Earth. It is shown that by combining the results obtained from the expansions valid below and above the MSW resonance one can obtain a very good description of neutrino oscillations in matter in the entire energy range, including the resonance region.

Identification of appropriate reference genes for normalizing transcript expression by quantitative real-time PCR in Litsea cubeba.

PubMed

Lin, Liyuan; Han, Xiaojiao; Chen, Yicun; Wu, Qingke; Wang, Yangdong

2013-12-01

Quantitative real-time PCR has emerged as a highly sensitive and widely used method for detection of gene expression profiles, via which accurate detection depends on reliable normalization. Since no single control is appropriate for all experimental treatments, it is generally advocated to select suitable internal controls prior to use for normalization. This study reported the evaluation of the expression stability of twelve potential reference genes in different tissue/organs and six fruit developmental stages of Litsea cubeba in order to screen the superior internal reference genes for data normalization. Two softwares-geNorm, and NormFinder-were used to identify stability of these candidate genes. The cycle threshold difference and coefficient of variance were also calculated to evaluate the expression stability of candidate genes. F-BOX, EF1α, UBC, and TUA were selected as the most stable reference genes across 11 sample pools. F-BOX, EF1α, and EIF4α exhibited the highest expression stability in different tissue/organs and different fruit developmental stages. Besides, a combination of two stable reference genes would be sufficient for gene expression normalization in different fruit developmental stages. In addition, the relative expression profiles of DXS and DXR were evaluated by EF1α, UBC, and SAMDC. The results further validated the reliability of stable reference genes and also highlighted the importance of selecting suitable internal controls for L. cubeba. These reference genes will be of great importance for transcript normalization in future gene expression studies on L. cubeba.

GTA: a game theoretic approach to identifying cancer subnetwork markers.

PubMed

Farahmand, S; Goliaei, S; Ansari-Pour, N; Razaghi-Moghadam, Z

2016-03-01

The identification of genetic markers (e.g. genes, pathways and subnetworks) for cancer has been one of the most challenging research areas in recent years. A subset of these studies attempt to analyze genome-wide expression profiles to identify markers with high reliability and reusability across independent whole-transcriptome microarray datasets. Therefore, the functional relationships of genes are integrated with their expression data. However, for a more accurate representation of the functional relationships among genes, utilization of the protein-protein interaction network (PPIN) seems to be necessary. Herein, a novel game theoretic approach (GTA) is proposed for the identification of cancer subnetwork markers by integrating genome-wide expression profiles and PPIN. The GTA method was applied to three distinct whole-transcriptome breast cancer datasets to identify the subnetwork markers associated with metastasis. To evaluate the performance of our approach, the identified subnetwork markers were compared with gene-based, pathway-based and network-based markers. We show that GTA is not only capable of identifying robust metastatic markers, it also provides a higher classification performance. In addition, based on these GTA-based subnetworks, we identified a new bonafide candidate gene for breast cancer susceptibility.

Multiplexed quantitation of protein expression and phosphorylation based on functionalized soluble nanopolymers

PubMed Central

Pan, Li; Iliuk, Anton; Yu, Shuai; Geahlen, Robert L.; Tao, W. Andy

2012-01-01

We report here for the first time the multiplexed quantitation of phosphorylation and protein expression based on a functionalized soluble nanopolymer. The soluble nanopolymer, pIMAGO, is functionalized with Ti (IV) ions for chelating phosphoproteins in high specificity, and with infrared fluorescent tags for direct, multiplexed assays. The nanopolymer allows for direct competition for epitopes on proteins of interest, thus facilitating simultaneous detection of phosphorylation by pIMAGO and total protein amount by protein antibody in the same well of microplates. The new strategy has a great potential to measure cell signaling events by clearly distinguishing actual phosphorylation signals from protein expression changes, thus providing a powerful tool to accurately profile cellular signal transduction in healthy and disease cells. We anticipate broad applications of this new strategy in monitoring cellular signaling pathways and discovering new signaling events. PMID:23088311

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

PubMed Central

Hulsman, Marc; Lelieveldt, Boudewijn P. F.; de Ridder, Jeroen; Reinders, Marcel

2015-01-01

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale). PMID:25965262

DMirNet: Inferring direct microRNA-mRNA association networks.

PubMed

Lee, Minsu; Lee, HyungJune

2016-12-05

MicroRNAs (miRNAs) play important regulatory roles in the wide range of biological processes by inducing target mRNA degradation or translational repression. Based on the correlation between expression profiles of a miRNA and its target mRNA, various computational methods have previously been proposed to identify miRNA-mRNA association networks by incorporating the matched miRNA and mRNA expression profiles. However, there remain three major issues to be resolved in the conventional computation approaches for inferring miRNA-mRNA association networks from expression profiles. 1) Inferred correlations from the observed expression profiles using conventional correlation-based methods include numerous erroneous links or over-estimated edge weight due to the transitive information flow among direct associations. 2) Due to the high-dimension-low-sample-size problem on the microarray dataset, it is difficult to obtain an accurate and reliable estimate of the empirical correlations between all pairs of expression profiles. 3) Because the previously proposed computational methods usually suffer from varying performance across different datasets, a more reliable model that guarantees optimal or suboptimal performance across different datasets is highly needed. In this paper, we present DMirNet, a new framework for identifying direct miRNA-mRNA association networks. To tackle the aforementioned issues, DMirNet incorporates 1) three direct correlation estimation methods (namely Corpcor, SPACE, Network deconvolution) to infer direct miRNA-mRNA association networks, 2) the bootstrapping method to fully utilize insufficient training expression profiles, and 3) a rank-based Ensemble aggregation to build a reliable and robust model across different datasets. Our empirical experiments on three datasets demonstrate the combinatorial effects of necessary components in DMirNet. Additional performance comparison experiments show that DMirNet outperforms the state-of-the-art Ensemble-based model [1] which has shown the best performance across the same three datasets, with a factor of up to 1.29. Further, we identify 43 putative novel multi-cancer-related miRNA-mRNA association relationships from an inferred Top 1000 direct miRNA-mRNA association network. We believe that DMirNet is a promising method to identify novel direct miRNA-mRNA relations and to elucidate the direct miRNA-mRNA association networks. Since DMirNet infers direct relationships from the observed data, DMirNet can contribute to reconstructing various direct regulatory pathways, including, but not limited to, the direct miRNA-mRNA association networks.

Comparative Study of Regulatory Circuits in Two Sea Urchin Species Reveals Tight Control of Timing and High Conservation of Expression Dynamics

PubMed Central

Gildor, Tsvia; Ben-Tabou de-Leon, Smadar

2015-01-01

Accurate temporal control of gene expression is essential for normal development and must be robust to natural genetic and environmental variation. Studying gene expression variation within and between related species can delineate the level of expression variability that development can tolerate. Here we exploit the comprehensive model of sea urchin gene regulatory networks and generate high-density expression profiles of key regulatory genes of the Mediterranean sea urchin, Paracentrotus lividus (Pl). The high resolution of our studies reveals highly reproducible gene initiation times that have lower variation than those of maximal mRNA levels between different individuals of the same species. This observation supports a threshold behavior of gene activation that is less sensitive to input concentrations. We then compare Mediterranean sea urchin gene expression profiles to those of its Pacific Ocean relative, Strongylocentrotus purpuratus (Sp). These species shared a common ancestor about 40 million years ago and show highly similar embryonic morphologies. Our comparative analyses of five regulatory circuits operating in different embryonic territories reveal a high conservation of the temporal order of gene activation but also some cases of divergence. A linear ratio of 1.3-fold between gene initiation times in Pl and Sp is partially explained by scaling of the developmental rates with temperature. Scaling the developmental rates according to the estimated Sp-Pl ratio and normalizing the expression levels reveals a striking conservation of relative dynamics of gene expression between the species. Overall, our findings demonstrate the ability of biological developmental systems to tightly control the timing of gene activation and relative dynamics and overcome expression noise induced by genetic variation and growth conditions. PMID:26230518

Impact of Ischemia and Procurement Conditions on Gene Expression in Renal Cell Carcinoma

PubMed Central

Liu, Nick W.; Sanford, Thomas; Srinivasan, Ramaprasad; Liu, Jack L.; Khurana, Kiranpreet; Aprelikova, Olga; Valero, Vladimir; Bechert, Charles; Worrell, Robert; Pinto, Peter A.; Yang, Youfeng; Merino, Maria; Linehan, W. Marston; Bratslavsky, Gennady

2013-01-01

Purpose Previous studies have shown that ischemia alters gene expression in normal and malignant tissues. There are no studies that evaluated effects of ischemia in renal tumors. This study examines the impact of ischemia and tissue procurement conditions on RNA integrity and gene expression in renal cell carcinoma. Experimental Design Ten renal tumors were resected without renal hilar clamping from 10 patients with renal clear cell carcinoma. Immediately after tumor resection, a piece of tumor was snap frozen. Remaining tumor samples were stored at 4C, 22C and 37C and frozen at 5, 30, 60, 120, and 240 minutes. Histopathologic evaluation was performed on all tissue samples, and only those with greater than 80% tumor were selected for further analysis. RNA integrity was confirmed by electropherograms and quantitated using RIN index. Altered gene expression was assessed by paired, two-sample t-test between the zero time point and aliquots from various conditions obtained from the same tumor. Results One hundred and forty microarrays were performed. Some RNA degradation was observed 240 mins after resection at 37C. The expression of over 4,000 genes was significantly altered by ischemia times or storage conditions. The greatest gene expression changes were observed with longer ischemia time and warmer tissue procurement conditions. Conclusion RNA from kidney cancer remains intact for up to 4 hours post surgical resection regardless of storage conditions. Despite excellent RNA preservation, time after resection and procurement conditions significantly influence gene expression profiles. Meticulous attention to pre-acquisition variables is of paramount importance for accurate tumor profiling. PMID:23136194

Selecting a set of housekeeping genes for quantitative real-time PCR in normal and tetraploid haemocytes of soft-shell clams, Mya arenaria.

PubMed

Siah, A; Dohoo, C; McKenna, P; Delaporte, M; Berthe, F C J

2008-09-01

The transcripts involved in the molecular mechanisms of haemic neoplasia in relation to the haemocyte ploidy status of the soft-shell clam, Mya arenaria, have yet to be identified. For this purpose, real-time quantitative RT-PCR constitutes a sensitive and efficient technique, which can help determine the gene expression involved in haemocyte tetraploid status in clams affected by haemic neoplasia. One of the critical steps in comparing transcription profiles is the stability of selected housekeeping genes, as well as an accurate normalization. In this study, we selected five reference genes, S18, L37, EF1, EF2 and actin, generally used as single control genes. Their expression was analyzed by real-time quantitative RT-PCR at different levels of haemocyte ploidy status in order to select the most stable genes. Using the geNorm software, our results showed that L37, EF1 and S18 represent the most stable gene expressions related to various ploidy status ranging from 0 to 78% of tetraploid haemocytes in clams sampled in North River (Prince Edward Island, Canada). However, actin gene expression appeared to be highly regulated. Hence, using it as a housekeeping gene in tetraploid haemocytes can result in inaccurate data. To compare gene expression levels related to haemocyte ploidy status in Mya arenaria, using L37, EF1 and S18 as housekeeping genes for accurate normalization is therefore recommended.

Hartree-Fock theory of the inhomogeneous electron gas at a jellium metal surface: Rigorous upper bounds to the surface energy and accurate work functions

NASA Astrophysics Data System (ADS)

Sahni, V.; Ma, C. Q.

1980-12-01

The inhomogeneous electron gas at a jellium metal surface is studied in the Hartree-Fock approximation by Kohn-Sham density functional theory. Rigorous upper bounds to the surface energy are derived by application of the Rayleigh-Ritz variational principle for the energy, the surface kinetic, electrostatic, and nonlocal exchange energy functionals being determined exactly for the accurate linear-potential model electronic wave functions. The densities obtained by the energy minimization constraint are then employed to determine work-function results via the variationally accurate "displaced-profile change-in-self-consistent-field" expression. The theoretical basis of this non-self-consistent procedure and its demonstrated accuracy for the fully correlated system (as treated within the local-density approximation for exchange and correlation) leads us to conclude these results for the surface energies and work functions to be essentially exact. Work-function values are also determined by the Koopmans'-theorem expression, both for these densities as well as for those obtained by satisfaction of the constraint set on the electrostatic potential by the Budd-Vannimenus theorem. The use of the Hartree-Fock results in the accurate estimation of correlation-effect contributions to these surface properties of the nonuniform electron gas is also indicated. In addition, the original work and approximations made by Bardeen in this attempt at a solution of the Hartree-Fock problem are briefly reviewed in order to contrast with the present work.

Calculation of zero-offset vertical seismic profiles generated by a horizontal point force acting on the surface of an elastic half-space

USGS Publications Warehouse

Hsi-Ping, Liu

1990-01-01

Impulse responses including near-field terms have been obtained in closed form for the zero-offset vertical seismic profiles generated by a horizontal point force acting on the surface of an elastic half-space. The method is based on the correspondence principle. Through transformation of variables, the Fourier transform of the elastic impulse response is put in a form such that the Fourier transform of the corresponding anelastic impulse response can be expressed as elementary functions and their definite integrals involving distance angular frequency, phase velocities, and attenuation factors. These results are used for accurate calculation of shear-wave arrival rise times of synthetic seismograms needed for data interpretation of anelastic-attenuation measurements in near-surface sediment. -Author

Distinct iris gene expression profiles of primary angle closure glaucoma and primary open angle glaucoma and their interaction with ocular biometric parameters.

PubMed

Seet, Li-Fong; Narayanaswamy, Arun; Finger, Sharon N; Htoon, Hla M; Nongpiur, Monisha E; Toh, Li Zhen; Ho, Henrietta; Perera, Shamira A; Wong, Tina T

2016-11-01

This study aimed to evaluate differences in iris gene expression profiles between primary angle closure glaucoma (PACG) and primary open angle glaucoma (POAG) and their interaction with biometric characteristics. Prospective study. Thirty-five subjects with PACG and thirty-three subjects with POAG who required trabeculectomy were enrolled at the Singapore National Eye Centre, Singapore. Iris specimens, obtained by iridectomy, were analysed by real-time polymerase chain reaction for expression of type I collagen, vascular endothelial growth factor (VEGF)-A, -B and -C, as well as VEGF receptors (VEGFRs) 1 and 2. Anterior segment optical coherence tomography (ASOCT) imaging for biometric parameters, including anterior chamber depth (ACD), anterior chamber volume (ACV) and lens vault (LV), was also performed pre-operatively. Relative mRNA levels between PACG and POAG irises, biometric measurements, discriminant analyses using genes and biometric parameters. COL1A1, VEGFB, VEGFC and VEGFR2 mRNA expression was higher in PACG compared to POAG irises. LV, ACD and ACV were significantly different between the two subgroups. Discriminant analyses based on gene expression, biometric parameters or a combination of both gene expression and biometrics (LV and ACV), correctly classified 94.1%, 85.3% and 94.1% of the original PACG and POAG cases, respectively. The discriminant function combining genes and biometrics demonstrated the highest accuracy in cross-validated classification of the two glaucoma subtypes. Distinct iris gene expression supports the pathophysiological differences that exist between PACG and POAG. Biometric parameters can combine with iris gene expression to more accurately define PACG from POAG. © 2016 The Authors. Clinical & Experimental Ophthalmology published by John Wiley & Sons Australia, Ltd on behalf of Royal Australian and New Zealand College of Ophthalmologists.

Estimating replicate time shifts using Gaussian process regression

PubMed Central

Liu, Qiang; Andersen, Bogi; Smyth, Padhraic; Ihler, Alexander

2010-01-01

Motivation: Time-course gene expression datasets provide important insights into dynamic aspects of biological processes, such as circadian rhythms, cell cycle and organ development. In a typical microarray time-course experiment, measurements are obtained at each time point from multiple replicate samples. Accurately recovering the gene expression patterns from experimental observations is made challenging by both measurement noise and variation among replicates' rates of development. Prior work on this topic has focused on inference of expression patterns assuming that the replicate times are synchronized. We develop a statistical approach that simultaneously infers both (i) the underlying (hidden) expression profile for each gene, as well as (ii) the biological time for each individual replicate. Our approach is based on Gaussian process regression (GPR) combined with a probabilistic model that accounts for uncertainty about the biological development time of each replicate. Results: We apply GPR with uncertain measurement times to a microarray dataset of mRNA expression for the hair-growth cycle in mouse back skin, predicting both profile shapes and biological times for each replicate. The predicted time shifts show high consistency with independently obtained morphological estimates of relative development. We also show that the method systematically reduces prediction error on out-of-sample data, significantly reducing the mean squared error in a cross-validation study. Availability: Matlab code for GPR with uncertain time shifts is available at http://sli.ics.uci.edu/Code/GPRTimeshift/ Contact: ihler@ics.uci.edu PMID:20147305

The Genomic and Transcriptomic Landscape of a HeLa Cell Line

PubMed Central

Landry, Jonathan J. M.; Pyl, Paul Theodor; Rausch, Tobias; Zichner, Thomas; Tekkedil, Manu M.; Stütz, Adrian M.; Jauch, Anna; Aiyar, Raeka S.; Pau, Gregoire; Delhomme, Nicolas; Gagneur, Julien; Korbel, Jan O.; Huber, Wolfgang; Steinmetz, Lars M.

2013-01-01

HeLa is the most widely used model cell line for studying human cellular and molecular biology. To date, no genomic reference for this cell line has been released, and experiments have relied on the human reference genome. Effective design and interpretation of molecular genetic studies performed using HeLa cells require accurate genomic information. Here we present a detailed genomic and transcriptomic characterization of a HeLa cell line. We performed DNA and RNA sequencing of a HeLa Kyoto cell line and analyzed its mutational portfolio and gene expression profile. Segmentation of the genome according to copy number revealed a remarkably high level of aneuploidy and numerous large structural variants at unprecedented resolution. Some of the extensive genomic rearrangements are indicative of catastrophic chromosome shattering, known as chromothripsis. Our analysis of the HeLa gene expression profile revealed that several pathways, including cell cycle and DNA repair, exhibit significantly different expression patterns from those in normal human tissues. Our results provide the first detailed account of genomic variants in the HeLa genome, yielding insight into their impact on gene expression and cellular function as well as their origins. This study underscores the importance of accounting for the strikingly aberrant characteristics of HeLa cells when designing and interpreting experiments, and has implications for the use of HeLa as a model of human biology. PMID:23550136

The Profile of Heparanase Expression Distinguishes Differentiated Thyroid Carcinoma from Benign Neoplasms

PubMed Central

Matos, Leandro Luongo; Suarez, Eloah Rabello; Theodoro, Thérèse Rachell; Trufelli, Damila Cristina; Melo, Carina Mucciolo; Garcia, Larissa Ferraz; Oliveira, Olivia Capela Grimaldi; Matos, Maria Graciela Luongo; Kanda, Jossi Ledo; Nader, Helena Bonciani; Martins, João Roberto Maciel; Pinhal, Maria Aparecida Silva

2015-01-01

Introduction The search for a specific marker that could help to distinguish between differentiated thyroid carcinoma and benign lesions remains elusive in clinical practice. Heparanase (HPSE) is an endo-beta-glucoronidase implicated in the process of tumor invasion, and the heparanase-2 (HPSE2) modulates HPSE activity. The aim of this study was to evaluate the role of heparanases in the development and differential diagnosis of follicular pattern thyroid lesions. Methods HPSE and HPSE2 expression by qRT-PCR, immunohistochemistry evaluation, western blot analysis and HPSE enzymatic activity were evaluated. Results The expression of heparanases by qRT-PCR showed an increase of HPSE2 in thyroid carcinoma (P = 0.001). HPSE activity was found to be higher in the malignant neoplasms than in the benign tumors (P<0.0001). On Western blot analysis, HPSE2 isoforms were detected only in malignant tumors. The immunohistochemical assay allowed us to establish a distinct pattern for malignant and benign tumors. Carcinomas showed a typical combination of positive labeling for neoplastic cells and negative immunostaining in colloid, when compared to benign tumors (P<0.0001). The proposed diagnostic test presents sensitivity and negative predictive value of around 100%, showing itself to be an accurate test for distinguishing between malignant and benign lesions. Conclusions This study shows, for the first time, a distinct profile of HPSE expression in thyroid carcinoma suggesting its role in carcinogenesis. PMID:26488476

Transcriptomics in cancer diagnostics: developments in technology, clinical research and commercialization.

PubMed

Sager, Monica; Yeat, Nai Chien; Pajaro-Van der Stadt, Stefan; Lin, Charlotte; Ren, Qiuyin; Lin, Jimmy

2015-01-01

Transcriptomic technologies are evolving to diagnose cancer earlier and more accurately to provide greater predictive and prognostic utility to oncologists and patients. Digital techniques such as RNA sequencing are replacing still-imaging techniques to provide more detailed analysis of the transcriptome and aberrant expression that causes oncogenesis, while companion diagnostics are developing to determine the likely effectiveness of targeted treatments. This article examines recent advancements in molecular profiling research and technology as applied to cancer diagnosis, clinical applications and predictions for the future of personalized medicine in oncology.

Analytical solution for wave propagation through a graded index interface between a right-handed and a left-handed material.

PubMed

Dalarsson, Mariana; Tassin, Philippe

2009-04-13

We have investigated the transmission and reflection properties of structures incorporating left-handed materials with graded index of refraction. We present an exact analytical solution to Helmholtz' equation for a graded index profile changing according to a hyperbolic tangent function along the propagation direction. We derive expressions for the field intensity along the graded index structure, and we show excellent agreement between the analytical solution and the corresponding results obtained by accurate numerical simulations. Our model straightforwardly allows for arbitrary spectral dispersion.

Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis.

PubMed

Chapman, Robert W; Reading, Benjamin J; Sullivan, Craig V

2014-01-01

Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing <2% of the queried ovary transcriptome explained >90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic "fingerprint". Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness.

Ovary Transcriptome Profiling via Artificial Intelligence Reveals a Transcriptomic Fingerprint Predicting Egg Quality in Striped Bass, Morone saxatilis

PubMed Central

2014-01-01

Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing <2% of the queried ovary transcriptome explained >90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic “fingerprint”. Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness. PMID:24820964

Machine-learning approach identifies a pattern of gene expression in peripheral blood that can accurately detect ischaemic stroke

PubMed Central

O’Connell, Grant C; Petrone, Ashley B; Treadway, Madison B; Tennant, Connie S; Lucke-Wold, Noelle; Chantler, Paul D; Barr, Taura L

2016-01-01

Early and accurate diagnosis of stroke improves the probability of positive outcome. The objective of this study was to identify a pattern of gene expression in peripheral blood that could potentially be optimised to expedite the diagnosis of acute ischaemic stroke (AIS). A discovery cohort was recruited consisting of 39 AIS patients and 24 neurologically asymptomatic controls. Peripheral blood was sampled at emergency department admission, and genome-wide expression profiling was performed via microarray. A machine-learning technique known as genetic algorithm k-nearest neighbours (GA/kNN) was then used to identify a pattern of gene expression that could optimally discriminate between groups. This pattern of expression was then assessed via qRT-PCR in an independent validation cohort, where it was evaluated for its ability to discriminate between an additional 39 AIS patients and 30 neurologically asymptomatic controls, as well as 20 acute stroke mimics. GA/kNN identified 10 genes (ANTXR2, STK3, PDK4, CD163, MAL, GRAP, ID3, CTSZ, KIF1B and PLXDC2) whose coordinate pattern of expression was able to identify 98.4% of discovery cohort subjects correctly (97.4% sensitive, 100% specific). In the validation cohort, the expression levels of the same 10 genes were able to identify 95.6% of subjects correctly when comparing AIS patients to asymptomatic controls (92.3% sensitive, 100% specific), and 94.9% of subjects correctly when comparing AIS patients with stroke mimics (97.4% sensitive, 90.0% specific). The transcriptional pattern identified in this study shows strong diagnostic potential, and warrants further evaluation to determine its true clinical efficacy. PMID:29263821

Exploring valid reference genes for quantitative real-time PCR analysis in Sesamia inferens (Lepidoptera: Noctuidae).

PubMed

Sun, Meng; Lu, Ming-Xing; Tang, Xiao-Tian; Du, Yu-Zhou

2015-01-01

The pink stem borer, Sesamia inferens, which is endemic in China and other parts of Asia, is a major pest of rice and causes significant yield loss in this host plant. Very few studies have addressed gene expression in S. inferens. Quantitative real-time PCR (qRT-PCR) is currently the most accurate and sensitive method for gene expression analysis. In qRT-PCR, data are normalized using reference genes, which help control for internal differences and reduce error between samples. In this study, seven candidate reference genes, 18S ribosomal RNA (18S rRNA), elongation factor 1 (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein S13 (RPS13), ribosomal protein S20 (RPS20), tubulin (TUB), and β-actin (ACTB) were evaluated for their suitability in normalizing gene expression under different experimental conditions. The results indicated that three genes (RPS13, RPS20, and EF1) were optimal for normalizing gene expression in different insect tissues (head, epidermis, fat body, foregut, midgut, hindgut, Malpighian tubules, haemocytes, and salivary glands). 18S rRNA, EF1, and GAPDH were best for normalizing expression with respect to developmental stages and sex (egg masses; first, second, third, fourth, fifth, and sixth instar larvae; male and female pupae; and one-day-old male and female adults). 18S rRNA, RPS20, and TUB were optimal for fifth instars exposed to different temperatures (-8, -6, -4, -2, 0, and 27°C). To validate this recommendation, the expression profile of a target gene heat shock protein 83 gene (hsp83) was investigated, and results showed the selection was necessary and effective. In conclusion, this study describes reference gene sets that can be used to accurately measure gene expression in S. inferens.

RankProd 2.0: a refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets.

PubMed

Del Carratore, Francesco; Jankevics, Andris; Eisinga, Rob; Heskes, Tom; Hong, Fangxin; Breitling, Rainer

2017-09-01

The Rank Product (RP) is a statistical technique widely used to detect differentially expressed features in molecular profiling experiments such as transcriptomics, metabolomics and proteomics studies. An implementation of the RP and the closely related Rank Sum (RS) statistics has been available in the RankProd Bioconductor package for several years. However, several recent advances in the understanding of the statistical foundations of the method have made a complete refactoring of the existing package desirable. We implemented a completely refactored version of the RankProd package, which provides a more principled implementation of the statistics for unpaired datasets. Moreover, the permutation-based P -value estimation methods have been replaced by exact methods, providing faster and more accurate results. RankProd 2.0 is available at Bioconductor ( https://www.bioconductor.org/packages/devel/bioc/html/RankProd.html ) and as part of the mzMatch pipeline ( http://www.mzmatch.sourceforge.net ). rainer.breitling@manchester.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Spatial reconstruction of single-cell gene expression

PubMed Central

Satija, Rahul; Farrell, Jeffrey A.; Gennert, David; Schier, Alexander F.; Regev, Aviv

2015-01-01

Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. PMID:25867923

Statistical inference for time course RNA-Seq data using a negative binomial mixed-effect model.

PubMed

Sun, Xiaoxiao; Dalpiaz, David; Wu, Di; S Liu, Jun; Zhong, Wenxuan; Ma, Ping

2016-08-26

Accurate identification of differentially expressed (DE) genes in time course RNA-Seq data is crucial for understanding the dynamics of transcriptional regulatory network. However, most of the available methods treat gene expressions at different time points as replicates and test the significance of the mean expression difference between treatments or conditions irrespective of time. They thus fail to identify many DE genes with different profiles across time. In this article, we propose a negative binomial mixed-effect model (NBMM) to identify DE genes in time course RNA-Seq data. In the NBMM, mean gene expression is characterized by a fixed effect, and time dependency is described by random effects. The NBMM is very flexible and can be fitted to both unreplicated and replicated time course RNA-Seq data via a penalized likelihood method. By comparing gene expression profiles over time, we further classify the DE genes into two subtypes to enhance the understanding of expression dynamics. A significance test for detecting DE genes is derived using a Kullback-Leibler distance ratio. Additionally, a significance test for gene sets is developed using a gene set score. Simulation analysis shows that the NBMM outperforms currently available methods for detecting DE genes and gene sets. Moreover, our real data analysis of fruit fly developmental time course RNA-Seq data demonstrates the NBMM identifies biologically relevant genes which are well justified by gene ontology analysis. The proposed method is powerful and efficient to detect biologically relevant DE genes and gene sets in time course RNA-Seq data.

Transcriptome profile of a bovine respiratory disease pathogen: Mannheimia haemolytica PHL213

PubMed Central

2012-01-01

Background Computational methods for structural gene annotation have propelled gene discovery but face certain drawbacks with regards to prokaryotic genome annotation. Identification of transcriptional start sites, demarcating overlapping gene boundaries, and identifying regulatory elements such as small RNA are not accurate using these approaches. In this study, we re-visit the structural annotation of Mannheimia haemolytica PHL213, a bovine respiratory disease pathogen. M. haemolytica is one of the causative agents of bovine respiratory disease that results in about $3 billion annual losses to the cattle industry. We used RNA-Seq and analyzed the data using freely-available computational methods and resources. The aim was to identify previously unannotated regions of the genome using RNA-Seq based expression profile to complement the existing annotation of this pathogen. Results Using the Illumina Genome Analyzer, we generated 9,055,826 reads (average length ~76 bp) and aligned them to the reference genome using Bowtie. The transcribed regions were analyzed using SAMTOOLS and custom Perl scripts in conjunction with BLAST searches and available gene annotation information. The single nucleotide resolution map enabled the identification of 14 novel protein coding regions as well as 44 potential novel sRNA. The basal transcription profile revealed that 2,506 of the 2,837 annotated regions were expressed in vitro, at 95.25% coverage, representing all broad functional gene categories in the genome. The expression profile also helped identify 518 potential operon structures involving 1,086 co-expressed pairs. We also identified 11 proteins with mutated/alternate start codons. Conclusions The application of RNA-Seq based transcriptome profiling to structural gene annotation helped correct existing annotation errors and identify potential novel protein coding regions and sRNA. We used computational tools to predict regulatory elements such as promoters and terminators associated with the novel expressed regions for further characterization of these novel functional elements. Our study complements the existing structural annotation of Mannheimia haemolytica PHL213 based on experimental evidence. Given the role of sRNA in virulence gene regulation and stress response, potential novel sRNA described in this study can form the framework for future studies to determine the role of sRNA, if any, in M. haemolytica pathogenesis. PMID:23046475

Prediction of clinical behaviour and treatment for cancers.

PubMed

Futschik, Matthias E; Sullivan, Mike; Reeve, Anthony; Kasabov, Nikola

2003-01-01

Prediction of clinical behaviour and treatment for cancers is based on the integration of clinical and pathological parameters. Recent reports have demonstrated that gene expression profiling provides a powerful new approach for determining disease outcome. If clinical and microarray data each contain independent information then it should be possible to combine these datasets to gain more accurate prognostic information. Here, we have used existing clinical information and microarray data to generate a combined prognostic model for outcome prediction for diffuse large B-cell lymphoma (DLBCL). A prediction accuracy of 87.5% was achieved. This constitutes a significant improvement compared to the previously most accurate prognostic model with an accuracy of 77.6%. The model introduced here may be generally applicable to the combination of various types of molecular and clinical data for improving medical decision support systems and individualising patient care.

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

PubMed

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

2014-01-01

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

Whole-transcriptome brain expression and exon-usage profiling in major depression and suicide: evidence for altered glial, endothelial and ATPase activity

PubMed Central

Pantazatos, Spiro P.; Huang, Yung-yu; Rosoklija, Gorazd B.; Dwork, Andrew J.; Arango, Victoria; Mann, J. John

2016-01-01

Brain gene expression profiling studies of suicide and depression using oligonucleotide microarrays have often failed to distinguish these two phenotypes. Moreover, next generation sequencing (NGS) approaches are more accurate in quantifying gene expression and can detect alternative splicing. Using RNA-seq, we examined whole-exome gene and exon expression in non-psychiatric controls (CON, N=29), DSM-IV major depressive disorder suicides (MDD-S, N=21) and MDD non-suicides (MDD, N=9) in dorsal lateral prefrontal cortex (Brodmann Area 9) of sudden-death medication-free individuals postmortem. Using small RNA-seq, we also examined miRNA expression (9 samples per group). DeSeq2 identified thirty-five genes differentially expressed between groups and surviving adjustment for false discovery rate (adjusted p<0.1). In depression, altered genes include humanin like-8 (MTRNRL8), interleukin-8 (IL8), and serpin peptidase inhibitor, clade H (SERPINH1) and chemokine ligand 4 (CCL4), while exploratory gene ontology (GO) analyses revealed lower expression of immune-related pathways such as chemokine receptor activity, chemotaxis and cytokine biosynthesis, and angiogenesis and vascular development in (adjusted p<0.1). Hypothesis-driven GO analysis suggests lower expression of genes involved in oligodendrocyte differentiation, regulation of glutamatergic neurotransmission, and oxytocin receptor expression in both suicide and depression, and provisional evidence for altered DNA-dependent ATPase expression in suicide only. DEXSEq analysis identified differential exon usage in ATPase, class II, type 9B (adjusted p<0.1) in depression. Differences in miRNA expression or structural gene variants were not detected. Results lend further support for models in which deficits in microglial, endothelial (blood-brain barrier), ATPase activity and astrocytic cell functions contribute to MDD and suicide, and identify putative pathways and mechanisms for further study in these disorders. PMID:27528462

Whole-transcriptome brain expression and exon-usage profiling in major depression and suicide: evidence for altered glial, endothelial and ATPase activity.

PubMed

Pantazatos, S P; Huang, Y-Y; Rosoklija, G B; Dwork, A J; Arango, V; Mann, J J

2017-05-01

Brain gene expression profiling studies of suicide and depression using oligonucleotide microarrays have often failed to distinguish these two phenotypes. Moreover, next generation sequencing approaches are more accurate in quantifying gene expression and can detect alternative splicing. Using RNA-seq, we examined whole-exome gene and exon expression in non-psychiatric controls (CON, N=29), DSM-IV major depressive disorder suicides (MDD-S, N=21) and MDD non-suicides (MDD, N=9) in the dorsal lateral prefrontal cortex (Brodmann Area 9) of sudden death medication-free individuals post mortem. Using small RNA-seq, we also examined miRNA expression (nine samples per group). DeSeq2 identified 35 genes differentially expressed between groups and surviving adjustment for false discovery rate (adjusted P<0.1). In depression, altered genes include humanin-like-8 (MTRNRL8), interleukin-8 (IL8), and serpin peptidase inhibitor, clade H (SERPINH1) and chemokine ligand 4 (CCL4), while exploratory gene ontology (GO) analyses revealed lower expression of immune-related pathways such as chemokine receptor activity, chemotaxis and cytokine biosynthesis, and angiogenesis and vascular development in (adjusted P<0.1). Hypothesis-driven GO analysis suggests lower expression of genes involved in oligodendrocyte differentiation, regulation of glutamatergic neurotransmission, and oxytocin receptor expression in both suicide and depression, and provisional evidence for altered DNA-dependent ATPase expression in suicide only. DEXSEq analysis identified differential exon usage in ATPase, class II, type 9B (adjusted P<0.1) in depression. Differences in miRNA expression or structural gene variants were not detected. Results lend further support for models in which deficits in microglial, endothelial (blood-brain barrier), ATPase activity and astrocytic cell functions contribute to MDD and suicide, and identify putative pathways and mechanisms for further study in these disorders.

Novel blood-based microRNA biomarker panel for early diagnosis of chronic pancreatitis

PubMed Central

Xin, Lei; Gao, Jun; Wang, Dan; Lin, Jin-Huan; Liao, Zhuan; Ji, Jun-Tao; Du, Ting-Ting; Jiang, Fei; Hu, Liang-Hao; Li, Zhao-Shen

2017-01-01

Chronic pancreatitis (CP) is an inflammatory disease characterized by progressive fibrosis of pancreas. Early diagnosis will improve the prognosis of patients. This study aimed to obtain serum miRNA biomarkers for early diagnosis of CP. In the current study, we analyzed the differentially expressed miRNAs (DEmiRs) of CP patients from Gene Expression Omnibus (GEO), and the DEmiRs in plasma of early CP patients (n = 10) from clinic by miRNA microarrays. Expression levels of DEmiRs were further tested in clinical samples including early CP patients (n = 20), late CP patients (n = 20) and healthy controls (n = 18). The primary endpoints were area under curve (AUC) and expression levels of DEmiRs. Four DEmiRs (hsa-miR-320a-d) were obtained from GEO CP, meanwhile two (hsa-miR-221 and hsa-miR-130a) were identified as distinct biomarkers of early CP by miRNA microarrays. When applied on clinical serum samples, hsa-miR-320a-d were accurate in predicting late CP, while hsa-miR-221 and hsa-miR-130a were accurate in predicting early CP with AUC of 100.0% and 87.5%. Our study indicates that miRNA expression profile is different in early and late CP. Hsa-miR-221 and hsa-miR-130a are biomarkers of early CP, and the panel of the above 6 serum miRNAs has the potential to be applied clinically for early diagnosis of CP. PMID:28074846

Quantitative Analysis of the KSHV Transcriptome Following Primary Infection of Blood and Lymphatic Endothelial Cells

PubMed Central

Bruce, A. Gregory; Barcy, Serge; DiMaio, Terri; Gan, Emilia; Garrigues, H. Jacques; Lagunoff, Michael; Rose, Timothy M.

2017-01-01

The transcriptome of the Kaposi’s sarcoma-associated herpesvirus (KSHV/HHV8) after primary latent infection of human blood (BEC), lymphatic (LEC) and immortalized (TIME) endothelial cells was analyzed using RNAseq, and compared to long-term latency in BCBL-1 lymphoma cells. Naturally expressed transcripts were obtained without artificial induction, and a comprehensive annotation of the KSHV genome was determined. A set of unique coding sequence (UCDS) features and a process to resolve overlapping transcripts were developed to accurately quantitate transcript levels from specific promoters. Similar patterns of KSHV expression were detected in BCBL-1 cells undergoing long-term latent infections and in primary latent infections of both BEC and LEC cultures. High expression levels of poly-adenylated nuclear (PAN) RNA and spliced and unspliced transcripts encoding the K12 Kaposin B/C complex and associated microRNA region were detected, with an elevated expression of a large set of lytic genes in all latently infected cultures. Quantitation of non-overlapping regions of transcripts across the complete KSHV genome enabled for the first time accurate evaluation of the KSHV transcriptome associated with viral latency in different cell types. Hierarchical clustering applied to a gene correlation matrix identified modules of co-regulated genes with similar correlation profiles, which corresponded with biological and functional similarities of the encoded gene products. Gene modules were differentially upregulated during latency in specific cell types indicating a role for cellular factors associated with differentiated and/or proliferative states of the host cell to influence viral gene expression. PMID:28335496

Gene expression profiles of fin regeneration in loach (Paramisgurnus dabryanu).

PubMed

Li, Li; He, Jingya; Wang, Linlin; Chen, Weihua; Chang, Zhongjie

2017-11-01

Teleost fins can regenerate accurate position-matched structure and function after amputation. However, we still lack systematic transcriptional profiling and methodologies to understand the molecular basis of fin regeneration. After histological analysis, we established a suppression subtraction hybridization library containing 418 distinct sequences expressed differentially during the process of blastema formation and differentiation in caudal fin regeneration. Genome ontology and comparative analysis of differential distribution of our data and the reference zebrafish genome showed notable subcategories, including multi-organism processes, response to stimuli, extracellular matrix, antioxidant activity, and cell junction function. KEGG pathway analysis allowed the effective identification of relevant genes in those pathways involved in tissue morphogenesis and regeneration, including tight junction, cell adhesion molecules, mTOR and Jak-STAT signaling pathway. From relevant function subcategories and signaling pathways, 78 clones were examined for further Southern-blot hybridization. Then, 17 genes were chosen and characterized using semi-quantitative PCR. Then 4 candidate genes were identified, including F11r, Mmp9, Agr2 and one without a match to any database. After real-time quantitative PCR, the results showed obvious expression changes in different periods of caudal fin regeneration. We can assume that the 4 candidates, likely valuable genes associated with fin regeneration, deserve additional attention. Thus, our study demonstrated how to investigate the transcript profiles with an emphasis on bioinformatics intervention and how to identify potential genes related to fin regeneration processes. The results also provide a foundation or knowledge for further research into genes and molecular mechanisms of fin regeneration. Copyright © 2017 Elsevier B.V. All rights reserved.

Reference Genes for Accurate Transcript Normalization in Citrus Genotypes under Different Experimental Conditions

PubMed Central

Mafra, Valéria; Kubo, Karen S.; Alves-Ferreira, Marcio; Ribeiro-Alves, Marcelo; Stuart, Rodrigo M.; Boava, Leonardo P.; Rodrigues, Carolina M.; Machado, Marcos A.

2012-01-01

Real-time reverse transcription PCR (RT-qPCR) has emerged as an accurate and widely used technique for expression profiling of selected genes. However, obtaining reliable measurements depends on the selection of appropriate reference genes for gene expression normalization. The aim of this work was to assess the expression stability of 15 candidate genes to determine which set of reference genes is best suited for transcript normalization in citrus in different tissues and organs and leaves challenged with five pathogens (Alternaria alternata, Phytophthora parasitica, Xylella fastidiosa and Candidatus Liberibacter asiaticus). We tested traditional genes used for transcript normalization in citrus and orthologs of Arabidopsis thaliana genes described as superior reference genes based on transcriptome data. geNorm and NormFinder algorithms were used to find the best reference genes to normalize all samples and conditions tested. Additionally, each biotic stress was individually analyzed by geNorm. In general, FBOX (encoding a member of the F-box family) and GAPC2 (GAPDH) was the most stable candidate gene set assessed under the different conditions and subsets tested, while CYP (cyclophilin), TUB (tubulin) and CtP (cathepsin) were the least stably expressed genes found. Validation of the best suitable reference genes for normalizing the expression level of the WRKY70 transcription factor in leaves infected with Candidatus Liberibacter asiaticus showed that arbitrary use of reference genes without previous testing could lead to misinterpretation of data. Our results revealed FBOX, SAND (a SAND family protein), GAPC2 and UPL7 (ubiquitin protein ligase 7) to be superior reference genes, and we recommend their use in studies of gene expression in citrus species and relatives. This work constitutes the first systematic analysis for the selection of superior reference genes for transcript normalization in different citrus organs and under biotic stress. PMID:22347455

Universal analytical scattering form factor for shell-, core-shell, or homogeneous particles with continuously variable density profile shape.

PubMed

Foster, Tobias

2011-09-01

A novel analytical and continuous density distribution function with a widely variable shape is reported and used to derive an analytical scattering form factor that allows us to universally describe the scattering from particles with the radial density profile of homogeneous spheres, shells, or core-shell particles. Composed by the sum of two Fermi-Dirac distribution functions, the shape of the density profile can be altered continuously from step-like via Gaussian-like or parabolic to asymptotically hyperbolic by varying a single "shape parameter", d. Using this density profile, the scattering form factor can be calculated numerically. An analytical form factor can be derived using an approximate expression for the original Fermi-Dirac distribution function. This approximation is accurate for sufficiently small rescaled shape parameters, d/R (R being the particle radius), up to values of d/R ≈ 0.1, and thus captures step-like, Gaussian-like, and parabolic as well as asymptotically hyperbolic profile shapes. It is expected that this form factor is particularly useful in a model-dependent analysis of small-angle scattering data since the applied continuous and analytical function for the particle density profile can be compared directly with the density profile extracted from the data by model-free approaches like the generalized inverse Fourier transform method. © 2011 American Chemical Society

Distinct endothelial phenotypes evoked by arterial waveforms derived from atherosclerosis-susceptible and -resistant regions of human vasculature

NASA Astrophysics Data System (ADS)

Dai, Guohao; Kaazempur-Mofrad, Mohammad R.; Natarajan, Sripriya; Zhang, Yuzhi; Vaughn, Saran; Blackman, Brett R.; Kamm, Roger D.; García-Cardeña, Guillermo; Gimbrone, Michael A., Jr.

2004-10-01

Atherosclerotic lesion localization to regions of disturbed flow within certain arterial geometries, in humans and experimental animals, suggests an important role for local hemodynamic forces in atherogenesis. To explore how endothelial cells (EC) acquire functional/dysfunctional phenotypes in response to vascular region-specific flow patterns, we have used an in vitro dynamic flow system to accurately reproduce arterial shear stress waveforms on cultured human EC and have examined the effects on EC gene expression by using a high-throughput transcriptional profiling approach. The flow patterns in the carotid artery bifurcations of several normal human subjects were characterized by using 3D flow analysis based on actual vascular geometries and blood flow profiles. Two prototypic arterial waveforms, "athero-prone" and "athero-protective," were defined as representative of the wall shear stresses in two distinct regions of the carotid artery (carotid sinus and distal internal carotid artery) that are typically "susceptible" or "resistant," respectively, to atherosclerotic lesion development. These two waveforms were applied to cultured EC, and cDNA microarrays were used to analyze the differential patterns of EC gene expression. In addition, the differential effects of athero-prone vs. athero-protective waveforms were further characterized on several parameters of EC structure and function, including actin cytoskeletal organization, expression and localization of junctional proteins, activation of the NF-B transcriptional pathway, and expression of proinflammatory cytokines and adhesion molecules. These global gene expression patterns and functional data reveal a distinct phenotypic modulation in response to the wall shear stresses present in atherosclerosis-susceptible vs. atherosclerosis-resistant human arterial geometries.

Gene expression patterns in rainbow trout, Oncorhynchus mykiss, exposed to a suite of model toxicants

PubMed Central

Hook, Sharon E.; Skillman, Ann D.; Small, Jack A.; Schultz, Irvin R.

2008-01-01

The increased availability and use of DNA microarrays has allowed the characterization of gene expression patterns associated with exposure to different toxicants. An important question is whether toxicant induced changes in gene expression in fish are sufficiently diverse to allow for identification of specific modes of action and/or specific contaminants. In theory, each class of toxicant may generate a gene expression profile unique to its mode of toxic action. In this study, isogenic (cloned) rainbow trout Oncorhynchus mykiss were exposed to sublethal levels of a series of model toxicants with varying modes of action, including ethynylestradiol (xeno-estrogen), 2,2,4,4′-tetrabromodiphenyl ether (BDE-47, thyroid active), diquat (oxidant stressor), chromium VI, and benzo[a]pyrene (BaP) for a period of 1–3 weeks. An additional experiment measured trenbolone (anabolic steroid; model androgen) induced gene expression changes in sexually mature female trout. Following exposure, fish were euthanized, livers removed and RNA extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Atlantic Salmon/Trout array (GRASP project, University of Victoria) spotted with 16,000 cDNA’s. The slides were scanned to measure abundance of a given transcript in each sample relative to controls. Data were analyzed via Genespring (Silicon Genetics) to identify a list of up- and downregulated genes, as well as to determine gene clustering patterns that can be used as “expression signatures”. The results indicate each toxicant exposure caused between 64 and 222 genes to be significantly altered in expression. Most genes exhibiting altered expression responded to only one of the toxicants and relatively few were co-expressed in multiple treatments. For example, BaP and Diquat, both of which exert toxicity via oxidative stress, upregulated 28 of the same genes, of over 100 genes altered by either treatment. Other genes associated with steroidogenesis, p450 and estrogen responsive genes appear to be useful for selectively identifying toxicant mode of action in fish, suggesting a link between gene expression profile and mode of toxicity. Our array results showed good agreement with quantitative real time polymerase chain reaction (qRT PCR), which demonstrates that the arrays are an accurate measure of gene expression. The specificity of the gene expression profile in response to a model toxicant, the link between genes with altered expression and mode of toxic action, and the consistency between array and qRT PCR results all suggest that cDNA microarrays have the potential to screen environmental contaminants for biomarkers and mode of toxic action. PMID:16488489

Gene expression patterns in rainbow trout, Oncorhynchus mykiss, exposed to a suite of model toxicants.

PubMed

Hook, Sharon E; Skillman, Ann D; Small, Jack A; Schultz, Irvin R

2006-05-25

The increased availability and use of DNA microarrays has allowed the characterization of gene expression patterns associated with exposure to different toxicants. An important question is whether toxicant induced changes in gene expression in fish are sufficiently diverse to allow for identification of specific modes of action and/or specific contaminants. In theory, each class of toxicant may generate a gene expression profile unique to its mode of toxic action. In this study, isogenic (cloned) rainbow trout Oncorhynchus mykiss were exposed to sublethal levels of a series of model toxicants with varying modes of action, including ethynylestradiol (xeno-estrogen), 2,2,4,4'-tetrabromodiphenyl ether (BDE-47, thyroid active), diquat (oxidant stressor), chromium VI, and benzo[a]pyrene (BaP) for a period of 1-3 weeks. An additional experiment measured trenbolone (anabolic steroid; model androgen) induced gene expression changes in sexually mature female trout. Following exposure, fish were euthanized, livers removed and RNA extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Atlantic Salmon/Trout array (GRASP project, University of Victoria) spotted with 16,000 cDNA's. The slides were scanned to measure abundance of a given transcript in each sample relative to controls. Data were analyzed via Genespring (Silicon Genetics) to identify a list of up- and downregulated genes, as well as to determine gene clustering patterns that can be used as "expression signatures". The results indicate each toxicant exposure caused between 64 and 222 genes to be significantly altered in expression. Most genes exhibiting altered expression responded to only one of the toxicants and relatively few were co-expressed in multiple treatments. For example, BaP and Diquat, both of which exert toxicity via oxidative stress, upregulated 28 of the same genes, of over 100 genes altered by either treatment. Other genes associated with steroidogenesis, p450 and estrogen responsive genes appear to be useful for selectively identifying toxicant mode of action in fish, suggesting a link between gene expression profile and mode of toxicity. Our array results showed good agreement with quantitative real time polymerase chain reaction (qRT PCR), which demonstrates that the arrays are an accurate measure of gene expression. The specificity of the gene expression profile in response to a model toxicant, the link between genes with altered expression and mode of toxic action, and the consistency between array and qRT PCR results all suggest that cDNA microarrays have the potential to screen environmental contaminants for biomarkers and mode of toxic action.

Cell-of-Origin in Diffuse Large B-Cell Lymphoma: Are the Assays Ready for the Clinic?

PubMed

Scott, David W

2015-01-01

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma worldwide and consists of a heterogeneous group of cancers classified together on the basis of shared morphology, immunophenotype, and aggressive clinical behavior. It is now recognized that this malignancy comprises at least two distinct molecular subtypes identified by gene expression profiling: the activated B-cell-like (ABC) and the germinal center B-cell-like (GCB) groups-the cell-of-origin (COO) classification. These two groups have different genetic mutation landscapes, pathobiology, and outcomes following treatment. Evidence is accumulating that novel agents have selective activity in one or the other COO group, making COO a predictive biomarker. Thus, there is now a pressing need for accurate and robust methods to assign COO, to support clinical trials, and ultimately guide treatment decisions for patients. The "gold standard" methods for COO are based on gene expression profiling (GEP) of RNA from fresh frozen tissue using microarray technology, which is an impractical solution when formalin-fixed paraffin-embedded tissue (FFPET) biopsies are the standard diagnostic material. This review outlines the history of the COO classification before examining the practical implementation of COO assays applicable to FFPET biopsies. The immunohistochemistry (IHC)-based algorithms and gene expression-based assays suitable for the highly degraded RNA from FFPET are discussed. Finally, the technical and practical challenges that still need to be addressed are outlined before robust gene expression-based assays are used in the routine management of patients with DLBCL.

HIV-1 Infection of Primary CD4+ T Cells Regulates the Expression of Specific Human Endogenous Retrovirus HERV-K (HML-2) Elements.

PubMed

Young, George R; Terry, Sandra N; Manganaro, Lara; Cuesta-Dominguez, Alvaro; Deikus, Gintaras; Bernal-Rubio, Dabeiba; Campisi, Laura; Fernandez-Sesma, Ana; Sebra, Robert; Simon, Viviana; Mulder, Lubbertus C F

2018-01-01

Endogenous retroviruses (ERVs) occupy extensive regions of the human genome. Although many of these retroviral elements have lost their ability to replicate, those whose insertion took place more recently, such as the HML-2 group of HERV-K elements, still retain intact open reading frames and the capacity to produce certain viral RNA and/or proteins. Transcription of these ERVs is, however, tightly regulated by dedicated epigenetic control mechanisms. Nonetheless, it has been reported that some pathological states, such as viral infections and certain cancers, coincide with ERV expression, suggesting that transcriptional reawakening is possible. HML-2 elements are reportedly induced during HIV-1 infection, but the conserved nature of these elements has, until recently, rendered their expression profiling problematic. Here, we provide comprehensive HERV-K HML-2 expression profiles specific for productively HIV-1-infected primary human CD4 + T cells. We combined enrichment of HIV-1 infected cells using a reporter virus expressing a surface reporter for gentle and efficient purification with long-read single-molecule real-time sequencing. We show that three HML-2 proviruses-6q25.1, 8q24.3, and 19q13.42-are upregulated on average between 3- and 5-fold in HIV-1-infected CD4 + T cells. One provirus, HML-2 12q24.33, in contrast, was repressed in the presence of active HIV replication. In conclusion, this report identifies the HERV-K HML-2 loci whose expression profiles differ upon HIV-1 infection in primary human CD4 + T cells. These data will help pave the way for further studies on the influence of endogenous retroviruses on HIV-1 replication. IMPORTANCE Endogenous retroviruses inhabit big portions of our genome. Moreover, although they are mainly inert, some of the evolutionarily younger members maintain the ability to express both RNA and proteins. We have developed an approach using long-read single-molecule real-time (SMRT) sequencing that produces long reads that allow us to obtain detailed and accurate HERV-K HML-2 expression profiles. We applied this approach to study HERV-K expression in the presence or absence of productive HIV-1 infection of primary human CD4 + T cells. In addition to using SMRT sequencing, our strategy also includes the magnetic selection of the infected cells so that levels of background expression due to uninfected cells are kept at a minimum. The results presented here provide a blueprint for in-depth studies of the interactions of the authentic upregulated HERV-K HML-2 elements and HIV-1. Copyright © 2017 American Society for Microbiology.

Transcriptional and Enzymatic Profiling of Pleurotus ostreatus Laccase Genes in Submerged and Solid-State Fermentation Cultures

PubMed Central

Castanera, Raúl; Pérez, Gúmer; Omarini, Alejandra; Alfaro, Manuel; Pisabarro, Antonio G.; Faraco, Vincenza; Amore, Antonella

2012-01-01

The genome of the white rot basidiomycete Pleurotus ostreatus includes 12 phenol oxidase (laccase) genes. In this study, we examined their expression profiles in different fungal strains under different culture conditions (submerged and solid cultures) and in the presence of a wheat straw extract, which was used as an inducer of the laccase gene family. We used a reverse transcription-quantitative PCR (RT-qPCR)-based approach and focused on determining the reaction parameters (in particular, the reference gene set for the normalization and reaction efficiency determinations) used to achieve an accurate estimation of the relative gene expression values. The results suggested that (i) laccase gene transcription is upregulated in the induced submerged fermentation (iSmF) cultures but downregulated in the solid fermentation (SSF) cultures, (ii) the Lacc2 and Lacc10 genes are the main sources of laccase activity in the iSmF cultures upon induction with water-soluble wheat straw extracts, and (iii) an additional, as-yet-uncharacterized activity (Unk1) is specifically induced in SSF cultures that complements the activity of Lacc2 and Lacc10. Moreover, both the enzymatic laccase activities and the Lacc gene family transcription profiles greatly differ between closely related strains. These differences can be targeted for biotechnological breeding programs for enzyme production in submerged fermentation reactors. PMID:22467498

Spin relaxation in quantum dots due to electron exchange with leads.

PubMed

Vorontsov, A B; Vavilov, M G

2008-11-28

We calculate spin relaxation rates in lateral quantum dot systems due to electron exchange between dots and leads. Using rate equations, we develop a theoretical description of the experimentally observed electric current in the spin blockade regime of double quantum dots. A single expression fits the entire current profile and describes the structure of both the conduction peaks and the suppressed ("valley") region. Extrinsic rates calculated here have to be taken into account for accurate extraction of intrinsic relaxation rates due to the spin-orbit and hyperfine spin scattering mechanisms from spin blockade measurements.

Selection and testing of reference genes for accurate RT-qPCR in rice seedlings under iron toxicity.

PubMed

Santos, Fabiane Igansi de Castro Dos; Marini, Naciele; Santos, Railson Schreinert Dos; Hoffman, Bianca Silva Fernandes; Alves-Ferreira, Marcio; de Oliveira, Antonio Costa

2018-01-01

Reverse Transcription quantitative PCR (RT-qPCR) is a technique for gene expression profiling with high sensibility and reproducibility. However, to obtain accurate results, it depends on data normalization by using endogenous reference genes whose expression is constitutive or invariable. Although the technique is widely used in plant stress analyzes, the stability of reference genes for iron toxicity in rice (Oryza sativa L.) has not been thoroughly investigated. Here, we tested a set of candidate reference genes for use in rice under this stressful condition. The test was performed using four distinct methods: NormFinder, BestKeeper, geNorm and the comparative ΔCt. To achieve reproducible and reliable results, Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines were followed. Valid reference genes were found for shoot (P2, OsGAPDH and OsNABP), root (OsEF-1a, P8 and OsGAPDH) and root+shoot (OsNABP, OsGAPDH and P8) enabling us to perform further reliable studies for iron toxicity in both indica and japonica subspecies. The importance of the study of other than the traditional endogenous genes for use as normalizers is also shown here.

Selection and testing of reference genes for accurate RT-qPCR in rice seedlings under iron toxicity

PubMed Central

dos Santos, Fabiane Igansi de Castro; Marini, Naciele; dos Santos, Railson Schreinert; Hoffman, Bianca Silva Fernandes; Alves-Ferreira, Marcio

2018-01-01

Reverse Transcription quantitative PCR (RT-qPCR) is a technique for gene expression profiling with high sensibility and reproducibility. However, to obtain accurate results, it depends on data normalization by using endogenous reference genes whose expression is constitutive or invariable. Although the technique is widely used in plant stress analyzes, the stability of reference genes for iron toxicity in rice (Oryza sativa L.) has not been thoroughly investigated. Here, we tested a set of candidate reference genes for use in rice under this stressful condition. The test was performed using four distinct methods: NormFinder, BestKeeper, geNorm and the comparative ΔCt. To achieve reproducible and reliable results, Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines were followed. Valid reference genes were found for shoot (P2, OsGAPDH and OsNABP), root (OsEF-1a, P8 and OsGAPDH) and root+shoot (OsNABP, OsGAPDH and P8) enabling us to perform further reliable studies for iron toxicity in both indica and japonica subspecies. The importance of the study of other than the traditional endogenous genes for use as normalizers is also shown here. PMID:29494624

miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades.

PubMed

Friedländer, Marc R; Mackowiak, Sebastian D; Li, Na; Chen, Wei; Rajewsky, Nikolaus

2012-01-01

microRNAs (miRNAs) are a large class of small non-coding RNAs which post-transcriptionally regulate the expression of a large fraction of all animal genes and are important in a wide range of biological processes. Recent advances in high-throughput sequencing allow miRNA detection at unprecedented sensitivity, but the computational task of accurately identifying the miRNAs in the background of sequenced RNAs remains challenging. For this purpose, we have designed miRDeep2, a substantially improved algorithm which identifies canonical and non-canonical miRNAs such as those derived from transposable elements and informs on high-confidence candidates that are detected in multiple independent samples. Analyzing data from seven animal species representing the major animal clades, miRDeep2 identified miRNAs with an accuracy of 98.6-99.9% and reported hundreds of novel miRNAs. To test the accuracy of miRDeep2, we knocked down the miRNA biogenesis pathway in a human cell line and sequenced small RNAs before and after. The vast majority of the >100 novel miRNAs expressed in this cell line were indeed specifically downregulated, validating most miRDeep2 predictions. Last, a new miRNA expression profiling routine, low time and memory usage and user-friendly interactive graphic output can make miRDeep2 useful to a wide range of researchers.

Determination of accurate vertical atmospheric profiles of extinction and turbulence

NASA Astrophysics Data System (ADS)

Hammel, Steve; Campbell, James; Hallenborg, Eric

2017-09-01

Our ability to generate an accurate vertical profile characterizing the atmosphere from the surface to a point above the boundary layer top is quite rudimentary. The region from a land or sea surface to an altitude of 3000 meters is dynamic and particularly important to the performance of many active optical systems. Accurate and agile instruments are necessary to provide measurements in various conditions, and models are needed to provide the framework and predictive capability necessary for system design and optimization. We introduce some of the path characterization instruments and describe the first work to calibrate and validate them. Along with a verification of measurement accuracy, the tests must also establish each instruments performance envelope. Measurement of these profiles in the field is a problem, and we will present a discussion of recent field test activity to address this issue. The Comprehensive Atmospheric Boundary Layer Extinction/Turbulence Resolution Analysis eXperiment (CABLE/TRAX) was conducted late June 2017. There were two distinct objectives for the experiment: 1) a comparison test of various scintillometers and transmissometers on a homogeneous horizontal path; 2) a vertical profile experiment. In this paper we discuss only the vertical profiling effort, and we describe the instruments that generated data for vertical profiles of absorption, scattering, and turbulence. These three profiles are the core requirements for an accurate assessment of laser beam propagation.

Evaluation of Suitable Reference Genes for Normalization of qPCR Gene Expression Studies in Brinjal (Solanum melongena L.) During Fruit Developmental Stages.

PubMed

Kanakachari, Mogilicherla; Solanke, Amolkumar U; Prabhakaran, Narayanasamy; Ahmad, Israr; Dhandapani, Gurusamy; Jayabalan, Narayanasamy; Kumar, Polumetla Ananda

2016-02-01

Brinjal/eggplant/aubergine is one of the major solanaceous vegetable crops. Recent availability of genome information greatly facilitates the fundamental research on brinjal. Gene expression patterns during different stages of fruit development can provide clues towards the understanding of its biological functions. Quantitative real-time PCR (qPCR) has become one of the most widely used methods for rapid and accurate quantification of gene expression. However, its success depends on the use of a suitable reference gene for data normalization. For qPCR analysis, a single reference gene is not universally suitable for all experiments. Therefore, reference gene validation is a crucial step. Suitable reference genes for qPCR analysis of brinjal fruit development have not been investigated so far. In this study, we have selected 21 candidate reference genes from the Brinjal (Solanum melongena) Plant Gene Indices database (compbio.dfci.harvard.edu/tgi/plant.html) and studied their expression profiles by qPCR during six different fruit developmental stages (0, 5, 10, 20, 30, and 50 days post anthesis) along with leaf samples of the Pusa Purple Long (PPL) variety. To evaluate the stability of gene expression, geNorm and NormFinder analytical softwares were used. geNorm identified SAND (SAND family protein) and TBP (TATA binding protein) as the best pairs of reference genes in brinjal fruit development. The results showed that for brinjal fruit development, individual or a combination of reference genes should be selected for data normalization. NormFinder identified Expressed gene (expressed sequence) as the best single reference gene in brinjal fruit development. In this study, we have identified and validated for the first time reference genes to provide accurate transcript normalization and quantification at various fruit developmental stages of brinjal which can also be useful for gene expression studies in other Solanaceae plant species.

Dynamic association rules for gene expression data analysis.

PubMed

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 DAR algorithm not only was able to identify a set of differentially expressed genes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to gene expression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.

Expression and methylation of BDNF in the human brain in schizophrenia.

PubMed

Cheah, Sern-Yih; McLeay, Robert; Wockner, Leesa F; Lawford, Bruce R; Young, Ross McD; Morris, Charles P; Voisey, Joanne

2017-08-01

To examine the combined effect of the BDNF Val66Met (rs6265) polymorphism and BDNF DNA methylation on transcriptional regulation of the BDNF gene. DNA methylation profiles were generated for CpG sites proximal to Val66Met, within BDNF promoter I and exon V for prefrontal cortex samples from 25 schizophrenia and 25 control subjects. Val66Met genotypes and BDNF mRNA expression data were generated by transcriptome sequencing. Expression, methylation and genotype data were correlated and examined for association with schizophrenia. There was 43% more of the BDNF V-VIII-IX transcript in schizophrenia samples. BDNF mRNA expression and DNA methylation of seven CpG sites were not associated with schizophrenia after accounting for age and PMI effects. BDNF mRNA expression and DNA methylation were not altered by Val66Met after accounting for age and PMI effects. DNA methylation of one CpG site had a marginally significant positive correlation with mRNA expression in schizophrenia subjects. Schizophrenia risk was not associated with differential BDNF mRNA expression and DNA methylation. A larger age-matched cohort with comprehensive clinical history is required to accurately identify the effects of genotype, mRNA expression and DNA methylation on schizophrenia risk.

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Cardiac allograft gene expression profiling test... Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a) Identification. A cardiac allograft gene expression profiling test system is a device that measures the...

Perspectives of gene expression profiling for diagnosis and therapy in haematological malignancies.

PubMed

Bacher, Ulrike; Kohlmann, Alexander; Haferlach, Torsten

2009-05-01

Considering the heterogeneity of leukaemias and the widening spectrum of therapeutic strategies, novel diagnostic methods are urgently needed for haematological malignancies. For a decade, gene expression profiling (GEP) has been applied in leukaemia research. Thus, various studies demonstrated worldwide that the majority of genetically defined leukaemia subtypes are accurately predictable by GEP, for example, with respect to reciprocal rearrangements in acute myeloid leukaemia (AML). Moreover, novel prognostically relevant gene classifiers were developed as, for example, in normal karyotype AML. Considering the lymphatic malignancies, GEP studies defined novel clinically relevant subtypes in diffuse large B cell lymphoma (DLBCL), and improved the discrimination of Burkitt lymphoma and DLBCL cases, overcoming considerable overlaps of these entities that exist from morphological and genetic perspectives. Treatment-specific sensitivity assays are being developed for targeted drugs such as farnesyl transferase inhibitors in AML or imatinib in BCR-ABL1 positive acute lymphoblastic leukaemia (ALL). Irrespectively of these proceedings, an introduction of the microarray technology in haematological practice requires diagnostic algorithms and strategies for interaction with currently established diagnostic techniques. Large multicentre studies such as the MILE Study (Microarray Innovations in LEukemia) aim at translating this methodology into clinical routine workflows and to catalyze this process.

Defining pancreatic endocrine precursors and their descendants.

PubMed

White, Peter; May, Catherine Lee; Lamounier, Rodrigo N; Brestelli, John E; Kaestner, Klaus H

2008-03-01

The global incidence of diabetes continues to increase. Cell replacement therapy and islet transplantation offer hope, especially for severely affected patients. Efforts to differentiate insulin-producing beta-cells from progenitor or stem cells require knowledge of the transcriptional programs that regulate the development of the endocrine pancreas. Differentiation toward the endocrine lineage is dependent on the transcription factor Neurogenin 3 (Neurog3, Ngn3). We utilize a Neurog3-enhanced green fluorescent protein knock-in mouse model to isolate endocrine progenitor cells from embryonic pancreata (embryonic day [E]13.5 through E17.5). Using advanced genomic approaches, we generate a comprehensive gene expression profile of these progenitors and their immediate descendants. A total of 1,029 genes were identified as being temporally regulated in the endocrine lineage during fetal development, 237 of which are transcriptional regulators. Through pathway analysis, we have modeled regulatory networks involving these proteins that highlight the complex transcriptional hierarchy governing endocrine differentiation. We have been able to accurately capture the gene expression profile of the pancreatic endocrine progenitors and their descendants. The list of temporally regulated genes identified in fetal endocrine precursors and their immediate descendants provides a novel and important resource for developmental biologists and diabetes researchers alike.

The Martian Neutral Atmosphere from the Radio Science Experiment MaRS on Mars Express

NASA Astrophysics Data System (ADS)

Tellmann, Silvia; Paetzold, Martin; Haeusler, Bernd; Tyler, G. L.; Hinson, David P.

The Mars Express Radio Science Experiment (MaRS) has been sounding the Martian atmo-sphere and ionosphere by means of radio occultation since 2004. To date more than 570 sound-ings covering all latitudes during almost all seasons have been obtained in seven occultation seasons, mostly in the northern hemisphere. The highly elliptical orbit of Mars Express provides access to a large range of local times and locations which we use to investigate latitudinal, diurnal, and seasonal behavior of the atmosphere. Observed radial profiles of neutral number density, n[r], are used to obtain accurate measurements of temperature, T[r], and pressure, p[r], from the surface boundary layer to altitudes of 50 km with a vertical resolution of only a few hundred metres. Typical measurement accuracies of the temperature are in the range of ten percent at the upper boundary and fractions of a Kelvin near the surface. Several soundings are located in the polar regions of both hemispheres. These measurements will be used to examine the seasonal variations at high latitudes. The high vertical resolution and accuracy of the temperature profiles allows us to investigate the CO2 supersaturation and condensation near the poles. Atmospheric waves can be identified and will be investigated with regard to their spatial oc-currence over all latitude ranges. The MaRS experiment is funded by DLR under grant 50QM0701.

Absolute quantification of microbial taxon abundances.

PubMed

Props, Ruben; Kerckhof, Frederiek-Maarten; Rubbens, Peter; De Vrieze, Jo; Hernandez Sanabria, Emma; Waegeman, Willem; Monsieurs, Pieter; Hammes, Frederik; Boon, Nico

2017-02-01

High-throughput amplicon sequencing has become a well-established approach for microbial community profiling. Correlating shifts in the relative abundances of bacterial taxa with environmental gradients is the goal of many microbiome surveys. As the abundances generated by this technology are semi-quantitative by definition, the observed dynamics may not accurately reflect those of the actual taxon densities. We combined the sequencing approach (16S rRNA gene) with robust single-cell enumeration technologies (flow cytometry) to quantify the absolute taxon abundances. A detailed longitudinal analysis of the absolute abundances resulted in distinct abundance profiles that were less ambiguous and expressed in units that can be directly compared across studies. We further provide evidence that the enrichment of taxa (increase in relative abundance) does not necessarily relate to the outgrowth of taxa (increase in absolute abundance). Our results highlight that both relative and absolute abundances should be considered for a comprehensive biological interpretation of microbiome surveys.

A charge-based model of Junction Barrier Schottky rectifiers

NASA Astrophysics Data System (ADS)

Latorre-Rey, Alvaro D.; Mudholkar, Mihir; Quddus, Mohammed T.; Salih, Ali

2018-06-01

A new charge-based model of the electric field distribution for Junction Barrier Schottky (JBS) diodes is presented, based on the description of the charge-sharing effect between the vertical Schottky junction and the lateral pn-junctions that constitute the active cell of the device. In our model, the inherently 2-D problem is transformed into a simple but accurate 1-D problem which has a closed analytical solution that captures the reshaping and reduction of the electric field profile responsible for the improved electrical performance of these devices, while preserving physically meaningful expressions that depend on relevant device parameters. The validation of the model is performed by comparing calculated electric field profiles with drift-diffusion simulations of a JBS device showing good agreement. Even though other fully 2-D models already available provide higher accuracy, they lack physical insight making the proposed model an useful tool for device design.

Accurate polynomial expressions for the density and specific volume of seawater using the TEOS-10 standard

NASA Astrophysics Data System (ADS)

Roquet, F.; Madec, G.; McDougall, Trevor J.; Barker, Paul M.

2015-06-01

A new set of approximations to the standard TEOS-10 equation of state are presented. These follow a polynomial form, making it computationally efficient for use in numerical ocean models. Two versions are provided, the first being a fit of density for Boussinesq ocean models, and the second fitting specific volume which is more suitable for compressible models. Both versions are given as the sum of a vertical reference profile (6th-order polynomial) and an anomaly (52-term polynomial, cubic in pressure), with relative errors of ∼0.1% on the thermal expansion coefficients. A 75-term polynomial expression is also presented for computing specific volume, with a better accuracy than the existing TEOS-10 48-term rational approximation, especially regarding the sound speed, and it is suggested that this expression represents a valuable approximation of the TEOS-10 equation of state for hydrographic data analysis. In the last section, practical aspects about the implementation of TEOS-10 in ocean models are discussed.

Molecular and cytogenomic profiling of hepatic adenocarcinoma expressing inhibinA, a mimicker of neuroendocrine tumors: proposal to reclassify as "cholangioblastic variant of intrahepatic cholangiocarcinoma".

PubMed

Braxton, David R; Saxe, Debra; Damjanov, Nevena; Stashek, Kristen; Shroff, Stuti; Morrissette, Jennifer D; Tondon, Rashmi; Furth, Emma E

2017-04-01

Only a single case report exists in the literature of hepatic adenocarcinoma expressing InhibinA in a young woman, in which the authors proposed it to be a rare variant of intrahepatic cholangiocarcinoma (iCCA). We present novel molecular and histologic findings in our series of three cases occurring in young women and show these tumors may mimic well-differentiated neuroendocrine tumors (NET). Immunohistochemical (IHC) profiling was performed along with a next-generation sequencing (NGS) 47-gene solid tumor panel, and cytogenomic profiling via single-nucleotide polypmorphism microarray. IHC for inhibinA, chromogranin A (ChrA), and synaptophysin (Syn) was surveyed in liver tumors and in fetal liver. Two of the three patients recurred with metastatic disease with two confirmed deaths. Histological patterns present in the tumors included solid, trabecular, organoid, microcystic, and blastemal-like. IHC was positive for cytokeratin 7 in 3/3, cytokeratin 19 in 3/3, inhibinA in 3/3, ChrA in 3/3, Syn in 3/3, Sox9 in 2/3 and HepPar1 in 0/3. NGS was negative for pathogenic mutations. Recurrent cytogenomic abnormalities included gain of 17q, and loss of 6q. InhibinA was strong and diffusely expressed in 0/10 (0%) iCCA, 0/15 (0%) hepatocellular carcinomas (HCC), in the biliary component of 1/4 (25%) combined HCC-iCCA, 0/4 hepatoblastomas, 1/8 (13%) metastatic NET, and in 1/8 fetal liver tissues. We propose a classification of "cholangioblastic variant of intrahepatic cholangiocarcinoma" and molecular pathogenesis for this rare malignancy. Accurate identification on core biopsy is crucial for clinical management as it may mimic neuroendocrine neoplasms. Copyright © 2017 Elsevier Inc. All rights reserved.

Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

PubMed Central

Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

2014-01-01

Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

Using microRNA profiling in urine samples to develop a non-invasive test for bladder cancer.

PubMed

Mengual, Lourdes; Lozano, Juan José; Ingelmo-Torres, Mercedes; Gazquez, Cristina; Ribal, María José; Alcaraz, Antonio

2013-12-01

Current standard methods used to detect and monitor bladder urothelial cell carcinoma (UCC) are invasive or have low sensitivity. The incorporation into clinical practice of a non-invasive tool for UCC assessment would enormously improve patients' quality of life and outcome. This study aimed to examine the microRNA (miRNA) expression profiles in urines of UCC patients in order to develop a non-invasive accurate and reliable tool to diagnose and provide information on the aggressiveness of the tumor. We performed a global miRNA expression profiling analysis of the urinary cells from 40 UCC patients and controls using TaqMan Human MicroRNA Array followed by validation of 22 selected potentially diagnostic and prognostic miRNAs in a separate cohort of 277 samples using a miRCURY LNA qPCR system. miRNA-based signatures were developed by multivariate logistic regression analysis and internally cross-validated. In the initial cohort of patients, we identified 40 and 30 aberrantly expressed miRNA in UCC compared with control urines and in high compared with low grade tumors, respectively. Quantification of 22 key miRNAs in an independent cohort resulted in the identification of a six miRNA diagnostic signature with a sensitivity of 84.8% and specificity of 86.5% (AUC = 0.92) and a two miRNA prognostic model with a sensitivity of 84.95% and a specificity of 74.14% (AUC = 0.83). Internal cross-validation analysis confirmed the accuracy rates of both models, reinforcing the strength of our findings. Although the data needs to be externally validated, miRNA analysis in urine appears to be a valuable tool for the non-invasive assessment of UCC. Copyright © 2013 UICC.

Global microRNA expression profiling of microdissected tissues identifies miR-135b as a novel biomarker for pancreatic ductal adenocarcinoma.

PubMed

Munding, Johanna B; Adai, Alex T; Maghnouj, Abdelouahid; Urbanik, Aleksandra; Zöllner, Hannah; Liffers, Sven T; Chromik, Ansgar M; Uhl, Waldemar; Szafranska-Schwarzbach, Anna E; Tannapfel, Andrea; Hahn, Stephan A

2012-07-15

Pancreatic ductal adenocarcinoma (PDAC) is known for its poor prognosis resulting from being diagnosed at an advanced stage. Accurate early diagnosis and new therapeutic modalities are therefore urgently needed. MicroRNAs (miRNAs), considered a new class of biomarkers and therapeutic targets, may be able to fulfill those needs. Combining tissue microdissection with global miRNA array analyses, cell type-specific miRNA expression profiles were generated for normal pancreatic ductal cells, acinar cells, PDAC cells derived from xenografts and also from macrodissected chronic pancreatitis (CP) tissues. We identified 78 miRNAs differentially expressed between ND and PDAC cells providing new insights into the miRNA-driven pathophysiological mechanisms involved in PDAC development. Having filtered miRNAs which are upregulated in the three pairwise comparisons of PDAC vs. ND, PDAC vs. AZ and PDAC vs. CP, we identified 15 miRNA biomarker candidates including miR-135b. Using relative qRT-PCR to measure miR-135b normalized to miR-24 in 75 FFPE specimens (42 PDAC and 33 CP) covering a broad range of tumor content, we discriminated CP from PDAC with a sensitivity and specificity of 92.9% [95% CI=(80.5, 98.5)] and 93.4% [95% CI=(79.8, 99.3)], respectively. Furthermore, the area under the curve (AUC) value reached of 0.97 was accompanied by positive and negative predictive values of 95% and 91%, respectively. In conclusion, we report pancreatic cell-specific global miRNA profiles, which offer new candidate miRNAs to be exploited for functional studies in PDAC. Furthermore, we provide evidence that miRNAs are well-suited analytes for development of sensitive and specific aid-in-diagnosis tests for PDAC. Copyright © 2011 UICC.

Characterization of reference genes for qPCR analysis in various tissues of the Fujian oyster Crassostrea angulata

NASA Astrophysics Data System (ADS)

Pu, Fei; Yang, Bingye; Ke, Caihuan

2015-07-01

Accurate quantification of transcripts using quantitative real-time polymerase chain reaction (qPCR) depends on the identification of reliable reference genes for normalization. This study aimed to identify and validate seven reference genes, including actin-2 ( ACT-2), elongation factor 1 alpha ( EF-1α), elongation factor 1 beta ( EF-1β), glyceraldehyde-3-phosphate dehydrogenase ( GAPDH), ubiquitin ( UBQ), β-tubulin ( β-TUB), and 18S ribosomal RNA, from Crassostrea angulata, a valuable marine bivalve cultured worldwide. Transcript levels of the candidate reference genes were examined using qPCR analysis and showed differential expression patterns in the mantle, gill, adductor muscle, labial palp, visceral mass, hemolymph and gonad tissues. Quantitative data were analyzed using the geNorm software to assess the expression stability of the candidate reference genes, revealing that β-TUB and UBQ were the most stable genes. The commonly used GAPDH and 18S rRNA showed low stability, making them unsuitable candidates in this system. The expression pattern of the G protein β-subunit gene ( Gβ) across tissue types was also examined and normalized to the expression of each or both of UBQ and β-TUB as internal controls. This revealed consistent trends with all three normalization approaches, thus validating the reliability of UBQ and β-TUB as optimal internal controls. The study provides the first validated reference genes for accurate data normalization in transcript profiling in Crassostrea angulata, which will be indispensable for further functional genomics studies in this economically valuable marine bivalve.

Next-generation sequencing facilitates quantitative analysis of wild-type and Nrl−/− retinal transcriptomes

PubMed Central

Brooks, Matthew J.; Rajasimha, Harsha K.; Roger, Jerome E.

2011-01-01

Purpose Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis. Methods Retinal mRNA profiles of 21-day-old wild-type (WT) and neural retina leucine zipper knockout (Nrl−/−) mice were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Results Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. PMID:22162623

Exploring Valid Reference Genes for Quantitative Real-Time PCR Analysis in Sesamia inferens (Lepidoptera: Noctuidae)

PubMed Central

Sun, Meng; Lu, Ming-Xing; Tang, Xiao-Tian; Du, Yu-Zhou

2015-01-01

The pink stem borer, Sesamia inferens, which is endemic in China and other parts of Asia, is a major pest of rice and causes significant yield loss in this host plant. Very few studies have addressed gene expression in S. inferens. Quantitative real-time PCR (qRT-PCR) is currently the most accurate and sensitive method for gene expression analysis. In qRT-PCR, data are normalized using reference genes, which help control for internal differences and reduce error between samples. In this study, seven candidate reference genes, 18S ribosomal RNA (18S rRNA), elongation factor 1 (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein S13 (RPS13), ribosomal protein S20 (RPS20), tubulin (TUB), and β-actin (ACTB) were evaluated for their suitability in normalizing gene expression under different experimental conditions. The results indicated that three genes (RPS13, RPS20, and EF1) were optimal for normalizing gene expression in different insect tissues (head, epidermis, fat body, foregut, midgut, hindgut, Malpighian tubules, haemocytes, and salivary glands). 18S rRNA, EF1, and GAPDH were best for normalizing expression with respect to developmental stages and sex (egg masses; first, second, third, fourth, fifth, and sixth instar larvae; male and female pupae; and one-day-old male and female adults). 18S rRNA, RPS20, and TUB were optimal for fifth instars exposed to different temperatures (−8, −6, −4, −2, 0, and 27°C). To validate this recommendation, the expression profile of a target gene heat shock protein 83 gene (hsp83) was investigated, and results showed the selection was necessary and effective. In conclusion, this study describes reference gene sets that can be used to accurately measure gene expression in S. inferens. PMID:25585250

Thickness and an Altered miRNA Expression in the Epicardial Adipose Tissue Is Associated With Coronary Heart Disease in Sudden Death Victims.

PubMed

Marí-Alexandre, Josep; Barceló-Molina, Moises; Sanz-Sánchez, Jorge; Molina, Pilar; Sancho, Jennifer; Abellán, Yolanda; Santaolaria-Ayora, María Luisa; Giner, Juan; Martínez-Dolz, Luis; Estelles, Amparo; Braza-Boïls, Aitana; Zorio, Esther

2018-02-10

An increased epicardial adipose tissue (EAT) thickness has become a new risk factor for coronary heart disease (CHD). We aimed to study the role of EAT dysfunction as a CHD marker by focusing on its thickness and microRNA (miRNA) expression profile, and the potential factors possibly influencing them. One hundred and fifty-five CHD sudden cardiac death victims and 84 non-CHD-sudden death controls were prospectively enrolled at autopsy. A representative subset underwent EAT thickness measurements and EAT miRNA expression profiling. Epicardial adipose tissue thickness was increased and allowed an accurate diagnosis of patient status (among other measurements, EAT score area under the curve 0.718, P < .001). Epicardial adipose tissue from patients showed 14 up- and 14 down-regulated miRNAs and miR-34a-3p, -34a-5p, -124-3p, -125a-5p, 628-5p, -1303 and -4286 were validated by quantitative real-time polymerase chain reaction. Patients exhibited higher EAT levels of miR-34a-3p and -34a-5p than controls (with a positive trend considering EAT from coronaries without stenosis, with stable stenosis and complicated plaques) and correlated with age only in controls. The mild positive correlation between liver and EAT miR-34a-5p levels in patients (r = 0.295, P = .020) dramatically increased in EAT from complicated plaques (r = 0.799, P = .017). Similar correlations were observed for high-sensitivity-C-reactive protein levels and miR-34a-5p levels both in EAT and liver extracts. Increased age-independent levels of miR-34a-3p and -34a-5p characterize the EAT miRNA expression profile of CHD regardless of EAT thickness, anthropometric parameters, and the presence of underlying atherosclerotic plaques. Copyright © 2018 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Biomarkers of Coordinate Metabolic Reprogramming in Colorectal Tumors in Mice and Humans

PubMed Central

Manna, Soumen K.; Tanaka, Naoki; Krausz, Kristopher W.; Haznadar, Majda; Xue, Xiang; Matsubara, Tsutomu; Bowman, Elise D.; Fearon, Eric R.; Harris, Curtis C.; Shah, Yatrik M.; Gonzalez, Frank J.

2014-01-01

BACKGROUND & AIMS There are no robust noninvasive methods for colorectal cancer screening and diagnosis. Metabolomic and gene expression analyses of urine and tissue samples from mice and humans were used to identify markers of colorectal carcinogenesis. METHODS Mass spectrometry-based metabolomic analyses of urine and tissues from wild-type C57BL/6J and ApcMin/+ mice, as well as from mice with azoxymethane-induced tumors, was employed in tandem with gene expression analysis. Metabolomics profiles were also determined on colon tumor and adjacent non-tumor tissues from 39 patients. The effects of β-catenin activity on metabolic profiles were assessed in mice with colon-specific disruption of Apc. RESULTS Thirteen markers were found in urine associated with development of colorectal tumors in ApcMin/+ mice. Metabolites related to polyamine metabolism, nucleic acid metabolism, and methylation, identified tumor-bearing mice with 100% accuracy, and also accurately identified mice with polyps. Changes in gene expression in tumor samples from mice reflected the observed changes in metabolic products detected in urine; similar changes were observed in mice with azoxymethane-induced tumors and mice with colon-specific activation of β-catenin. The metabolic alterations indicated by markers in urine therefore appear to occur during early stages of tumorigenesis, when cancer cells are proliferating. In tissues from patients, tumors had stage-dependent increases in 12 metabolites associated with the same metabolic pathways identified in mice (including amino acid metabolism and polyamine metabolism). Ten metabolites that were increased in tumor tissues, compared with non-tumor tissues (proline, threonine, glutamic acid, arginine, N1-acetylspermidine, xanthine, uracil, betaine, symmetric dimethylarginine, and asymmetric-dimethylarginine), were also increased in urine from tumor-bearing mice. CONCLUSIONS Gene expression and metabolomic profiles of urine and tissue samples from mice with colorectal tumors and of colorectal tumor samples from patients revealed metabolites associated with specific metabolic changes that are indicative of early-stage tumor development. These urine and tissue markers might be used in early detection of colorectal cancer. PMID:24440673

Development and validation of a harmonized TaqMan-based triplex real-time RT-PCR protocol for the quantitative detection of normalized gene expression profiles of seven porcine cytokines.

PubMed

Petrov, Anja; Beer, Martin; Blome, Sandra

2014-01-01

Dysregulation of cytokine responses plays a major role in the pathogenesis of severe and life-threatening infectious diseases like septicemia or viral hemorrhagic fevers. In pigs, diseases like African and classical swine fever are known to show exaggerated cytokine releases. To study these responses and their impact on disease severity and outcome in detail, reliable, highly specific and sensitive methods are needed. For cytokine research on the molecular level, real-time RT-PCRs have been proven to be suitable. Yet, the currently available and most commonly used SYBR Green I assays or heterogeneous gel-based RT-PCRs for swine show a significant lack of specificity and sensitivity. The latter is however absolutely essential for an accurate quantification of rare cytokine transcripts as well as for detection of small changes in gene expressions. For this reason, a harmonized TaqMan-based triplex real-time RT-PCR protocol for the quantitative detection of normalized gene expression profiles of seven porcine cytokines was designed and validated within the presented study. Cytokines were chosen to represent different immunological pathways and targets known to be involved in the pathogenesis of the above mentioned porcine diseases, namely interleukin (IL)-1β, IL-2, IL-4, IL-6, IL-8, tumor necrosis factor (TNF)-α and interferon (IFN)-α. Beta-Actin and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) served as reference genes for normalization. For absolute quantification a synthetic standard plasmid was constructed comprising all target cytokines and reference genes within a single molecule allowing the generation of positive control RNA. The standard as well as positive RNAs from samples, and additionally more than 400 clinical samples, which were collected from animal trials, were included in the validation process to assess analytical sensitivity and applicability under routine conditions. The resulting assay allows the reliable assessment of gene expression profiles and provides a broad applicability to any kind of immunological research in swine.

Cross-Species Transcriptome Profiling Identifies New Alveolar Epithelial Type I Cell–Specific Genes

PubMed Central

Sunohara, Mitsuhiro; Pouldar, Tiffany M.; Wang, Hongjun; Liu, Yixin; Rieger, Megan E.; Tran, Evelyn; Flodby, Per; Siegmund, Kimberly D.; Crandall, Edward D.; Laird-Offringa, Ite A.

2017-01-01

Diseases involving the distal lung alveolar epithelium include chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, and lung adenocarcinoma. Accurate labeling of specific cell types is critical for determining the contribution of each to the pathogenesis of these diseases. The distal lung alveolar epithelium is composed of two cell types, alveolar epithelial type 1 (AT1) and type 2 (AT2) cells. Although cell type–specific markers, most prominently surfactant protein C, have allowed detailed lineage tracing studies of AT2 cell differentiation and the cells’ roles in disease, studies of AT1 cells have been hampered by a lack of genes with expression unique to AT1 cells. In this study, we performed genome-wide expression profiling of multiple rat organs together with purified rat AT2, AT1, and in vitro differentiated AT1-like cells, resulting in the identification of 54 candidate AT1 cell markers. Cross-referencing with genes up-regulated in human in vitro differentiated AT1-like cells narrowed the potential list to 18 candidate genes. Testing the top four candidate genes at RNA and protein levels revealed GRAM domain 2 (GRAMD2), a protein of unknown function, as highly specific to AT1 cells. RNA sequencing (RNAseq) confirmed that GRAMD2 is transcriptionally silent in human AT2 cells. Immunofluorescence verified that GRAMD2 expression is restricted to the plasma membrane of AT1 cells and is not expressed in bronchial epithelial cells, whereas reverse transcription–polymerase chain reaction confirmed that it is not expressed in endothelial cells. Using GRAMD2 as a new AT1 cell–specific gene will enhance AT1 cell isolation, the investigation of alveolar epithelial cell differentiation potential, and the contribution of AT1 cells to distal lung diseases. PMID:27749084

Self-Expression on Social Media: Do Tweets Present Accurate and Positive Portraits of Impulsivity, Self-Esteem, and Attachment Style?

PubMed

Orehek, Edward; Human, Lauren J

2017-01-01

Self-expression values are at an all-time high, and people are increasingly relying upon social media platforms to express themselves positively and accurately. We examined whether self-expression on the social media platform Twitter elicits positive and accurate social perceptions. Eleven perceivers rated 128 individuals (targets; total dyadic impressions = 1,408) on their impulsivity, self-esteem, and attachment style, based solely on the information provided in targets' 10 most recent tweets. Targets were on average perceived normatively and with distinctive self-other agreement, indicating both positive and accurate social perceptions. There were also individual differences in how positively and accurately targets were perceived, which exploratory analyses indicated may be partially driven by differential word usage, such as the use of positive emotion words and self- versus other-focus. This study demonstrates that self-expression on social media can elicit both positive and accurate perceptions and begins to shed light on how to curate such perceptions.

eXpression2Kinases (X2K) Web: linking expression signatures to upstream cell signaling networks.

PubMed

Clarke, Daniel J B; Kuleshov, Maxim V; Schilder, Brian M; Torre, Denis; Duffy, Mary E; Keenan, Alexandra B; Lachmann, Alexander; Feldmann, Axel S; Gundersen, Gregory W; Silverstein, Moshe C; Wang, Zichen; Ma'ayan, Avi

2018-05-25

While gene expression data at the mRNA level can be globally and accurately measured, profiling the activity of cell signaling pathways is currently much more difficult. eXpression2Kinases (X2K) computationally predicts involvement of upstream cell signaling pathways, given a signature of differentially expressed genes. X2K first computes enrichment for transcription factors likely to regulate the expression of the differentially expressed genes. The next step of X2K connects these enriched transcription factors through known protein-protein interactions (PPIs) to construct a subnetwork. The final step performs kinase enrichment analysis on the members of the subnetwork. X2K Web is a new implementation of the original eXpression2Kinases algorithm with important enhancements. X2K Web includes many new transcription factor and kinase libraries, and PPI networks. For demonstration, thousands of gene expression signatures induced by kinase inhibitors, applied to six breast cancer cell lines, are provided for fetching directly into X2K Web. The results are displayed as interactive downloadable vector graphic network images and bar graphs. Benchmarking various settings via random permutations enabled the identification of an optimal set of parameters to be used as the default settings in X2K Web. X2K Web is freely available from http://X2K.cloud.

Gene Expression Profiling of Benign and Malignant Pheochromocytoma

PubMed Central

BROUWERS, FREDERIEKE M.; ELKAHLOUN, ABDEL G.; MUNSON, PETER J.; EISENHOFER, GRAEME; BARB, JENNIFER; LINEHAN, W. MARSTON; LENDERS, JACQUES W.M.; DE KRIJGER, RONALD; MANNELLI, MASSIMO; UDELSMAN, ROBERT; OCAL, IDRIS T.; SHULKIN, BARRY L.; BORNSTEIN, STEFAN R.; BREZA, JAN; KSINANTOVA, LUCIA; PACAK, KAREL

2016-01-01

There are currently no reliable diagnostic and prognostic markers or effective treatments for malignant pheochromocytoma. This study used oligonucleotide microarrays to examine gene expression profiles in pheochromocytomas from 90 patients, including 20 with malignant tumors, the latter including metastases and primary tumors from which metastases developed. Other subgroups of tumors included those defined by tissue norepinephrine compared to epinephrine contents (i.e., noradrenergic versus adrenergic phenotypes), adrenal versus extra-adrenal locations, and presence of germline mutations of genes pre-disposing to the tumor. Correcting for the confounding influence of nora-drenergic versus adrenergic catecholamine phenotype by the analysis of variance revealed a larger and more accurate number of genes that discriminated benign from malignant pheochromocytomas than when the confounding influence of catecholamine phenotype was not considered. Seventy percent of these genes were underexpressed in malignant compared to benign tumors. Similarly, 89% of genes were underexpressed in malignant primary tumors compared to benign tumors, suggesting that malignant potential is largely characterized by a less-differentiated pattern of gene expression. The present database of differentially expressed genes provides a unique resource for mapping the pathways leading to malignancy and for establishing new targets for treatment and diagnostic and prognostic markers of malignant disease. The database may also be useful for examining mechanisms of tumorigenesis and genotype–phenotype relationships. Further progress on the basis of this database can be made from follow-up confirmatory studies, application of bioinformatics approaches for data mining and pathway analyses, testing in pheochromocytoma cell culture and animal model systems, and retrospective and prospective studies of diagnostic markers. PMID:17102123

Multi-walled carbon nanotube-induced gene signatures in the mouse lung: potential predictive value for human lung cancer risk and prognosis

PubMed Central

Guo, Nancy L; Wan, Ying-Wooi; Denvir, James; Porter, Dale W; Pacurari, Maricica; Wolfarth, Michael G; Castranova, Vincent; Qian, Yong

2012-01-01

Concerns over the potential for multi-walled carbon nanotubes (MWCNT) to induce lung carcinogenesis have emerged. This study sought to (1) identify gene expression signatures in the mouse lungs following pharyngeal aspiration of well-dispersed MWCNT and (2) determine if these genes were associated with human lung cancer risk and progression. Genome-wide mRNA expression profiles were analyzed in mouse lungs (n=160) exposed to 0, 10, 20, 40, or 80 µg of MWCNT by pharyngeal aspiration at 1, 7, 28, and 56 days post-exposure. By using pairwise-Statistical Analysis of Microarray (SAM) and linear modeling, 24 genes were selected, which have significant changes in at least two time points, have a more than 1.5 fold change at all doses, and are significant in the linear model for the dose or the interaction of time and dose. Additionally, a 38-gene set was identified as related to cancer from 330 genes differentially expressed at day 56 post-exposure in functional pathway analysis. Using the expression profiles of the cancer-related gene set in 8 mice at day 56 post-exposure to 10 µg of MWCNT, a nearest centroid classification accurately predicts human lung cancer survival with a significant hazard ratio in training set (n=256) and test set (n=186). Furthermore, both gene signatures were associated with human lung cancer risk (n=164) with significant odds ratios. These results may lead to development of a surveillance approach for early detection of lung cancer and prognosis associated with MWCNT in the workplace. PMID:22891886

How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population.

PubMed

De Keyser, Ellen; Desmet, Laurence; Van Bockstaele, Erik; De Riek, Jan

2013-06-24

Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population. An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H. Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway.

How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population

PubMed Central

2013-01-01

Background Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population. Results An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H. Conclusions Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway. PMID:23800303

Impaired perception of facial emotion in developmental prosopagnosia.

PubMed

Biotti, Federica; Cook, Richard

2016-08-01

Developmental prosopagnosia (DP) is a neurodevelopmental condition characterised by difficulties recognising faces. Despite severe difficulties recognising facial identity, expression recognition is typically thought to be intact in DP; case studies have described individuals who are able to correctly label photographic displays of facial emotion, and no group differences have been reported. This pattern of deficits suggests a locus of impairment relatively late in the face processing stream, after the divergence of expression and identity analysis pathways. To date, however, there has been little attempt to investigate emotion recognition systematically in a large sample of developmental prosopagnosics using sensitive tests. In the present study, we describe three complementary experiments that examine emotion recognition in a sample of 17 developmental prosopagnosics. In Experiment 1, we investigated observers' ability to make binary classifications of whole-face expression stimuli drawn from morph continua. In Experiment 2, observers judged facial emotion using only the eye-region (the rest of the face was occluded). Analyses of both experiments revealed diminished ability to classify facial expressions in our sample of developmental prosopagnosics, relative to typical observers. Imprecise expression categorisation was particularly evident in those individuals exhibiting apperceptive profiles, associated with problems encoding facial shape accurately. Having split the sample of prosopagnosics into apperceptive and non-apperceptive subgroups, only the apperceptive prosopagnosics were impaired relative to typical observers. In our third experiment, we examined the ability of observers' to classify the emotion present within segments of vocal affect. Despite difficulties judging facial emotion, the prosopagnosics exhibited excellent recognition of vocal affect. Contrary to the prevailing view, our results suggest that many prosopagnosics do experience difficulties classifying expressions, particularly those with apperceptive profiles. These individuals may have difficulties forming view-invariant structural descriptions at an early stage in the face processing stream, before identity and expression pathways diverge. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2008-11-01

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

Epigenomic profiling of DNA methylation in paired prostate cancer versus adjacent benign tissue

PubMed Central

Geybels, Milan S.; Zhao, Shanshan; Wong, Chao-Jen; Bibikova, Marina; Klotzle, Brandy; Wu, Michael; Ostrander, Elaine A.; Fan, Jian-Bing; Feng, Ziding; Stanford, Janet L.

2016-01-01

Background Aberrant DNA methylation may promote prostate carcinogenesis. We investigated epigenome-wide DNA methylation profiles in prostate cancer (PCa) compared to adjacent benign tissue to identify differentially methylated CpG sites. Methods The study included paired PCa and adjacent benign tissue samples from 20 radical prostatectomy patients. Epigenetic profiling was done using the Infinium HumanMethylation450 BeadChip. Linear models that accounted for the paired study design and False Discovery Rate Q-values were used to evaluate differential CpG methylation. mRNA expression levels of the genes with the most differentially methylated CpG sites were analyzed. Results In total, 2,040 differentially methylated CpG sites were identified in PCa versus adjacent benign tissue (Q-value <0.001), the majority of which were hypermethylated (n = 1,946; 95%). DNA methylation profiles accurately distinguished between PCa and benign tissue samples. Twenty-seven top-ranked hypermethylated CpGs had a mean methylation difference of at least 40% between tissue types, which included 25 CpGs in 17 genes. Furthermore, for ten genes over 50% of promoter region CpGs were hypermethylated in PCa versus benign tissue. The top-ranked differentially methylated genes included three genes that were associated with both promoter hypermethylation and reduced gene expression: SCGB3A1, HIF3A, and AOX1. Analysis of The Cancer Genome Atlas (TCGA) data provided confirmatory evidence for our findings. Conclusions This study of PCa versus adjacent benign tissue showed many differentially methylated CpGs and regions in and outside gene promoter regions, which may potentially be used for the development of future epigenetic-based diagnostic tests or as therapeutic targets. PMID:26383847

Epigenomic profiling of DNA methylation in paired prostate cancer versus adjacent benign tissue.

PubMed

Geybels, Milan S; Zhao, Shanshan; Wong, Chao-Jen; Bibikova, Marina; Klotzle, Brandy; Wu, Michael; Ostrander, Elaine A; Fan, Jian-Bing; Feng, Ziding; Stanford, Janet L

2015-12-01

Aberrant DNA methylation may promote prostate carcinogenesis. We investigated epigenome-wide DNA methylation profiles in prostate cancer (PCa) compared to adjacent benign tissue to identify differentially methylated CpG sites. The study included paired PCa and adjacent benign tissue samples from 20 radical prostatectomy patients. Epigenetic profiling was done using the Infinium HumanMethylation450 BeadChip. Linear models that accounted for the paired study design and False Discovery Rate Q-values were used to evaluate differential CpG methylation. mRNA expression levels of the genes with the most differentially methylated CpG sites were analyzed. In total, 2,040 differentially methylated CpG sites were identified in PCa versus adjacent benign tissue (Q-value < 0.001), the majority of which were hypermethylated (n = 1,946; 95%). DNA methylation profiles accurately distinguished between PCa and benign tissue samples. Twenty-seven top-ranked hypermethylated CpGs had a mean methylation difference of at least 40% between tissue types, which included 25 CpGs in 17 genes. Furthermore, for 10 genes over 50% of promoter region CpGs were hypermethylated in PCa versus benign tissue. The top-ranked differentially methylated genes included three genes that were associated with both promoter hypermethylation and reduced gene expression: SCGB3A1, HIF3A, and AOX1. Analysis of The Cancer Genome Atlas (TCGA) data provided confirmatory evidence for our findings. This study of PCa versus adjacent benign tissue showed many differentially methylated CpGs and regions in and outside gene promoter regions, which may potentially be used for the development of future epigenetic-based diagnostic tests or as therapeutic targets. © 2015 Wiley Periodicals, Inc.

Protein profile of basal prostate epithelial progenitor cells--stage-specific embryonal antigen 4 expressing cells have enhanced regenerative potential in vivo.

PubMed

Höfner, Thomas; Klein, Corinna; Eisen, Christian; Rigo-Watermeier, Teresa; Haferkamp, Axel; Sprick, Martin R

2016-04-01

The long-term propagation of basal prostate progenitor cells ex vivo has been very difficult in the past. The development of novel methods to expand prostate progenitor cells in vitro allows determining their cell surface phenotype in greater detail. Mouse (Lin(-)Sca-1(+) CD49f(+) Trop2(high)-phenotype) and human (Lin(-) CD49f(+) TROP2(high)) basal prostate progenitor cells were expanded in vitro. Human and mouse cells were screened using 242 anti-human or 176 antimouse monoclonal antibodies recognizing the cell surface protein profile. Quantitative expression was evaluated at the single-cell level using flow cytometry. Differentially expressed cell surface proteins were evaluated in conjunction with the known CD49f(+)/TROP2(high) phenotype of basal prostate progenitor cells and characterized by in vivo sandwich-transplantation experiments using nude mice. The phenotype of basal prostate progenitor cells was determined as CD9(+)/CD24(+)/CD29(+)/CD44(+)/CD47(+)/CD49f(+)/CD104(+)/CD147(+)/CD326(+)/Trop2(high) of mouse as well as human origin. Our analysis revealed several proteins, such as CD13, Syndecan-1 and stage-specific embryonal antigens (SSEAs), as being differentially expressed on murine and human CD49f(+) TROP2(+) basal prostate progenitor cells. Transplantation experiments suggest that CD49f(+) TROP2(high) SSEA-4(high) human prostate basal progenitor cells to be more potent to regenerate prostate tubules in vivo as compared with CD49f(+) TROP2(high) or CD49f(+) TROP2(high) SSEA-4(low) cells. Determination of the cell surface protein profile of functionally defined murine and human basal prostate progenitor cells reveals differentially expressed proteins that may change the potency and regenerative function of epithelial progenitor cells within the prostate. SSEA-4 is a candidate cell surface marker that putatively enables a more accurate identification of the basal PESC lineage. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Band-to-band tunneling distance analysis in the heterogate electron–hole bilayer tunnel field-effect transistor

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

Padilla, J. L., E-mail: jose.padilladelatorre@epfl.ch; Departamento de Electrónica y Tecnología de los Computadores, Universidad de Granada, Avda. Fuentenueva s/n, 18071 Granada; Palomares, A.

In this work, we analyze the behavior of the band-to-band tunneling distance between electron and hole subbands resulting from field-induced quantum confinement in the heterogate electron–hole bilayer tunnel field-effect transistor. We show that, analogously to the explicit formula for the tunneling distance that can be easily obtained in the semiclassical framework where the conduction and valence band edges are allowed states, an equivalent analytical expression can be derived in the presence of field-induced quantum confinement for describing the dependence of the tunneling distance on the body thickness and material properties of the channel. This explicit expression accounting for quantum confinementmore » holds valid provided that the potential wells for electrons and holes at the top and bottom of the channel can be approximated by triangular profiles. Analytical predictions are compared to simulation results showing very accurate agreement.« less

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

PubMed

Kim, Yoonji; Kim, Jaejik

2018-06-15

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

General solution for diffusion-controlled dissolution of spherical particles. 1. Theory.

PubMed

Wang, J; Flanagan, D R

1999-07-01

Three classical particle dissolution rate expressions are commonly used to interpret particle dissolution rate phenomena. Our analysis shows that an assumption used in the derivation of the traditional cube-root law may not be accurate under all conditions for diffusion-controlled particle dissolution. Mathematical analysis shows that the three classical particle dissolution rate expressions are approximate solutions to a general diffusion layer model. The cube-root law is most appropriate when particle size is much larger than the diffusion layer thickness, the two-thirds-root expression applies when the particle size is much smaller than the diffusion layer thickness. The square-root expression is intermediate between these two models. A general solution to the diffusion layer model for monodispersed spherical particles dissolution was derived for sink and nonsink conditions. Constant diffusion layer thickness was assumed in the derivation. Simulated dissolution data showed that the ratio between particle size and diffusion layer thickness (a0/h) is an important factor in controlling the shape of particle dissolution profiles. A new semiempirical general particle dissolution equation is also discussed which encompasses the three classical particle dissolution expressions. The success of the general equation in explaining limitations of traditional particle dissolution expressions demonstrates the usefulness of the general diffusion layer model.

Whole transcriptome profiling of taste bud cells.

PubMed

Sukumaran, Sunil K; Lewandowski, Brian C; Qin, Yumei; Kotha, Ramana; Bachmanov, Alexander A; Margolskee, Robert F

2017-08-08

Analysis of single-cell RNA-Seq data can provide insights into the specific functions of individual cell types that compose complex tissues. Here, we examined gene expression in two distinct subpopulations of mouse taste cells: Tas1r3-expressing type II cells and physiologically identified type III cells. Our RNA-Seq libraries met high quality control standards and accurately captured differential expression of marker genes for type II (e.g. the Tas1r genes, Plcb2, Trpm5) and type III (e.g. Pkd2l1, Ncam, Snap25) taste cells. Bioinformatics analysis showed that genes regulating responses to stimuli were up-regulated in type II cells, while pathways related to neuronal function were up-regulated in type III cells. We also identified highly expressed genes and pathways associated with chemotaxis and axon guidance, providing new insights into the mechanisms underlying integration of new taste cells into the taste bud. We validated our results by immunohistochemically confirming expression of selected genes encoding synaptic (Cplx2 and Pclo) and semaphorin signalling pathway (Crmp2, PlexinB1, Fes and Sema4a) components. The approach described here could provide a comprehensive map of gene expression for all taste cell subpopulations and will be particularly relevant for cell types in taste buds and other tissues that can be identified only by physiological methods.

Trunk density profile estimates from dual X-ray absorptiometry.

PubMed

Wicke, Jason; Dumas, Geneviève A; Costigan, Patrick A

2008-01-01

Accurate body segment parameters are necessary to estimate joint loads when using biomechanical models. Geometric methods can provide individualized data for these models but the accuracy of the geometric methods depends on accurate segment density estimates. The trunk, which is important in many biomechanical models, has the largest variability in density along its length. Therefore, the objectives of this study were to: (1) develop a new method for modeling trunk density profiles based on dual X-ray absorptiometry (DXA) and (2) develop a trunk density function for college-aged females and males that can be used in geometric methods. To this end, the density profiles of 25 females and 24 males were determined by combining the measurements from a photogrammetric method and DXA readings. A discrete Fourier transformation was then used to develop the density functions for each sex. The individual density and average density profiles compare well with the literature. There were distinct differences between the profiles of two of participants (one female and one male), and the average for their sex. It is believed that the variations in these two participants' density profiles were a result of the amount and distribution of fat they possessed. Further studies are needed to support this possibility. The new density functions eliminate the uniform density assumption associated with some geometric models thus providing more accurate trunk segment parameter estimates. In turn, more accurate moments and forces can be estimated for the kinetic analyses of certain human movements.

Indexed variation graphs for efficient and accurate resistome profiling.

PubMed

Rowe, Will P M; Winn, Martyn D

2018-05-14

Antimicrobial resistance remains a major threat to global health. Profiling the collective antimicrobial resistance genes within a metagenome (the "resistome") facilitates greater understanding of antimicrobial resistance gene diversity and dynamics. In turn, this can allow for gene surveillance, individualised treatment of bacterial infections and more sustainable use of antimicrobials. However, resistome profiling can be complicated by high similarity between reference genes, as well as the sheer volume of sequencing data and the complexity of analysis workflows. We have developed an efficient and accurate method for resistome profiling that addresses these complications and improves upon currently available tools. Our method combines a variation graph representation of gene sets with an LSH Forest indexing scheme to allow for fast classification of metagenomic sequence reads using similarity-search queries. Subsequent hierarchical local alignment of classified reads against graph traversals enables accurate reconstruction of full-length gene sequences using a scoring scheme. We provide our implementation, GROOT, and show it to be both faster and more accurate than a current reference-dependent tool for resistome profiling. GROOT runs on a laptop and can process a typical 2 gigabyte metagenome in 2 minutes using a single CPU. Our method is not restricted to resistome profiling and has the potential to improve current metagenomic workflows. GROOT is written in Go and is available at https://github.com/will-rowe/groot (MIT license). will.rowe@stfc.ac.uk. Supplementary data are available at Bioinformatics online.

A Mouse Model for the Metabolic Effects of the Human Fat Mass and Obesity Associated FTO Gene

PubMed Central

Church, Chris; Deacon, Robert; Gerken, Thomas; Lee, Angela; Moir, Lee; Mecinović, Jasmin; Quwailid, Mohamed M.; Schofield, Christopher J.; Ashcroft, Frances M.; Cox, Roger D.

2009-01-01

Human FTO gene variants are associated with body mass index and type 2 diabetes. Because the obesity-associated SNPs are intronic, it is unclear whether changes in FTO expression or splicing are the cause of obesity or if regulatory elements within intron 1 influence upstream or downstream genes. We tested the idea that FTO itself is involved in obesity. We show that a dominant point mutation in the mouse Fto gene results in reduced fat mass, increased energy expenditure, and unchanged physical activity. Exposure to a high-fat diet enhances lean mass and lowers fat mass relative to control mice. Biochemical studies suggest the mutation occurs in a structurally novel domain and modifies FTO function, possibly by altering its dimerisation state. Gene expression profiling revealed increased expression of some fat and carbohydrate metabolism genes and an improved inflammatory profile in white adipose tissue of mutant mice. These data provide direct functional evidence that FTO is a causal gene underlying obesity. Compared to the reported mouse FTO knockout, our model more accurately reflects the effect of human FTO variants; we observe a heterozygous as well as homozygous phenotype, a smaller difference in weight and adiposity, and our mice do not show perinatal lethality or an age-related reduction in size and length. Our model suggests that a search for human coding mutations in FTO may be informative and that inhibition of FTO activity is a possible target for the treatment of morbid obesity. PMID:19680540

ACCURATE: Greenhouse Gas Profiles Retrieval from Combined IR-Laser and Microwave Occultation Measurements

NASA Astrophysics Data System (ADS)

Proschek, Veronika; Kirchengast, Gottfried; Schweitzer, Susanne; Fritzer, Johannes

2010-05-01

The new climate satellite concept ACCURATE (Atmospheric Climate and Chemistry in the UTLS Region And climate Trends Explorer) enables simultaneous measurement of profiles of greenhouse gases, isotopes, wind and thermodynamic variables from Low Earth Orbit (LEO) satellites. The measurement principle applied is a combination of the novel LEO-LEO infrared laser occultation (LIO) technique and the already better studied LEO-LEO microwave occultation (LMO) technique. Resulting occultation events are evenly distributed around the world, have high vertical resolution and accuracy and are stable over long time periods. The LIO uses near-monochromatic signals in the short-wave infrared range (~2-2.5 μm for ACCURATE). These signals are absorbed by various trace species in the Earth's atmosphere. Profiles of the concentration of the absorbing species can be derived from signal transmission measurements. Accurately known temperature, pressure and humidity profiles derived from simultaneously measured LMO signals are essential pre-information for the retrieval of the trace species profiles. These LMO signals lie in the microwave band region from 17-23 GHz and, optionally, 178-195 GHz. The current ACCURATE mission design is arranged for the measurement of six greenhouse gases (GHG) (H2O, CO2, CH4, N2O, O3, CO) and four isotopes (13CO2, C18OO, HDO, H218O), with focus on the upper troposphere/lower stratosphere region (UTLS, 5-35 km). Wind speed in line-of-sight can be derived from a line-symmetric transmission difference which is caused by wind-induced Doppler shift. By-products are information on cloud layering, aerosol extinction, and scintillation strength. We introduce the methodology to retrieve GHG profiles from quasi-realistic forward-simulated intensities of LIO signals and thermodynamic profiles retrieved in a preceding step from LMO signals. Key of the retrieval methodology is the differencing of two LIO transmission signals, one being GHG sensitive on a target absorption line and one being a close-by reference outside of any absorption lines. The reference signal is used to remove atmospheric broadband" effects by this differential absorption" approach. Refractivity and impact parameter of the LIO signals, needed for the retrieval, can be computed from the LMO-derived thermodynamic profiles. An Abel Transform converts the differential LIO log-transmission profile to the absorption coefficient. Based on the absorption coefficient and the absorption cross section of the GHG under investigation, that can as well be computed from the LMO-derived profiles, the number density profile or volume mixing ratio of the desired GHG can be finally derived. When using several LIO signals, best sensitive to the same GHG at different heights, a joint optimal GHG profile can be constructed by combining the individual profiles in an inverse-variance-weighted manner (practically used for H2O, obtained from 3-4 signals, and for CO2, obtained from 2 isotope signals). The thermodynamic parameters (temperature, pressure and humidity) derived from LMO as basis for the LIO retrieval are found to be accurate to better than 0.5 K for temperature, 0.2% for pressure, and 10% for humidity. The accuracy of retrieved trace species profiles is found better than 1% to 4% for single profiles in the UTLS region (outside clouds which block infrared) and the profiles are essentially unbiased (biases

Matrigel Basement Membrane Matrix influences expression of microRNAs in cancer cell lines

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

Price, Karina J.; School of Medicine and Pharmacology, University of Western Australia, Nedlands, WA 6008; Tsykin, Anna

2012-10-19

Highlights: Black-Right-Pointing-Pointer Matrigel alters cancer cell line miRNA expression relative to culture on plastic. Black-Right-Pointing-Pointer Many identified Matrigel-regulated miRNAs are implicated in cancer. Black-Right-Pointing-Pointer miR-1290, -210, -32 and -29b represent a Matrigel-induced miRNA signature. Black-Right-Pointing-Pointer miR-32 down-regulates Integrin alpha 5 (ITGA5) mRNA. -- Abstract: Matrigel is a medium rich in extracellular matrix (ECM) components used for three-dimensional cell culture and is known to alter cellular phenotypes and gene expression. microRNAs (miRNAs) are small, non-coding RNAs that regulate gene expression and have roles in cancer. While miRNA profiles of numerous cell lines cultured on plastic have been reported, the influence ofmore » Matrigel-based culture on cancer cell miRNA expression is largely unknown. This study investigated the influence of Matrigel on the expression of miRNAs that might facilitate ECM-associated cancer cell growth. We performed miRNA profiling by microarray using two colon cancer cell lines (SW480 and SW620), identifying significant differential expression of miRNAs between cells cultured in Matrigel and on plastic. Many of these miRNAs have previously been implicated in cancer-related processes. A common Matrigel-induced miRNA signature comprised of up-regulated miR-1290 and miR-210 and down-regulated miR-29b and miR-32 was identified using RT-qPCR across five epithelial cancer cell lines (SW480, SW620, HT-29, A549 and MDA-MB-231). Experimental modulation of these miRNAs altered expression of their known target mRNAs involved in cell adhesion, proliferation and invasion, in colon cancer cell lines. Furthermore, ITGA5 was identified as a novel putative target of miR-32 that may facilitate cancer cell interactions with the ECM. We propose that culture of cancer cell lines in Matrigel more accurately recapitulates miRNA expression and function in cancer than culture on plastic and thus is a valuable approach to the in vitro study of miRNAs.« less

Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

NASA Astrophysics Data System (ADS)

Teschendorff, Andrew E.; Enver, Tariq

2017-06-01

The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes.

Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

PubMed Central

Teschendorff, Andrew E.; Enver, Tariq

2017-01-01

The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes. PMID:28569836

Discrete ordinates solutions of nongray radiative transfer with diffusely reflecting walls

NASA Technical Reports Server (NTRS)

Menart, J. A.; Lee, Haeok S.; Kim, Tae-Kuk

1993-01-01

Nongray gas radiation in a plane parallel slab bounded by gray, diffusely reflecting walls is studied using the discrete ordinates method. The spectral equation of transfer is averaged over a narrow wavenumber interval preserving the spectral correlation effect. The governing equations are derived by considering the history of multiple reflections between two reflecting wails. A closure approximation is applied so that only a finite number of reflections have to be explicitly included. The closure solutions express the physics of the problem to a very high degree and show relatively little error. Numerical solutions are obtained by applying a statistical narrow-band model for gas properties and a discrete ordinates code. The net radiative wail heat fluxes and the radiative source distributions are obtained for different temperature profiles. A zeroth-degree formulation, where no wall reflection is handled explicitly, is sufficient to predict the radiative transfer accurately for most cases considered, when compared with increasingly accurate solutions based on explicitly tracing a larger number of wail reflections without any closure approximation applied.

Digital sorting of complex tissues for cell type-specific gene expression profiles.

PubMed

Zhong, Yi; Wan, Ying-Wooi; Pang, Kaifang; Chow, Lionel M L; Liu, Zhandong

2013-03-07

Cellular heterogeneity is present in almost all gene expression profiles. However, transcriptome analysis of tissue specimens often ignores the cellular heterogeneity present in these samples. Standard deconvolution algorithms require prior knowledge of the cell type frequencies within a tissue or their in vitro expression profiles. Furthermore, these algorithms tend to report biased estimations. Here, we describe a Digital Sorting Algorithm (DSA) for extracting cell-type specific gene expression profiles from mixed tissue samples that is unbiased and does not require prior knowledge of cell type frequencies. The results suggest that DSA is a specific and sensitivity algorithm in gene expression profile deconvolution and will be useful in studying individual cell types of complex tissues.

Identification of stable reference genes for gene expression analysis of three-dimensional cultivated human bone marrow-derived mesenchymal stromal cells for bone tissue engineering.

PubMed

Rauh, Juliane; Jacobi, Angela; Stiehler, Maik

2015-02-01

The principles of tissue engineering (TE) are widely used for bone regeneration concepts. Three-dimensional (3D) cultivation of autologous human mesenchymal stromal cells (MSCs) on porous scaffolds is the basic prerequisite to generate newly formed bone tissue. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a specific and sensitive analytical tool for the measurement of mRNA-levels in cells or tissues. For an accurate quantification of gene expression levels, stably expressed reference genes (RGs) are essential to obtain reliable results. Since the 3D environment can affect a cell's morphology, proliferation, and gene expression profile compared with two-dimensional (2D) cultivation, there is a need to identify robust RGs for the quantification of gene expression. So far, this issue has not been adequately investigated. The aim of this study was to identify the most stably expressed RGs for gene expression analysis of 3D-cultivated human bone marrow-derived MSCs (BM-MSCs). For this, we analyzed the gene expression levels of n=31 RGs in 3D-cultivated human BM-MSCs from six different donors compared with conventional 2D cultivation using qRT-PCR. MSCs isolated from bone marrow aspirates were cultivated on human cancellous bone cube scaffolds for 14 days. Osteogenic differentiation was assessed by cell-specific alkaline phosphatase (ALP) activity and expression of osteogenic marker genes. Expression levels of potential reference and target genes were quantified using commercially available TaqMan(®) assays. mRNA expression stability of RGs was determined by calculating the coefficient of variation (CV) and using the algorithms of geNorm and NormFinder. Using both algorithms, we identified TATA box binding protein (TBP), transferrin receptor (p90, CD71) (TFRC), and hypoxanthine phosphoribosyltransferase 1 (HPRT1) as the most stably expressed RGs in 3D-cultivated BM-MSCs. Notably, genes that are routinely used as RGs, for example, beta actin (ACTB) and ribosomal protein L37a (RPL37A), were among the least stable genes. We recommend the combined use of TBP, TFRC, and HPRT1 for the accurate and robust normalization of qRT-PCR data of 3D-cultivated human BM-MSCs.

Identification of Stable Reference Genes for Gene Expression Analysis of Three-Dimensional Cultivated Human Bone Marrow-Derived Mesenchymal Stromal Cells for Bone Tissue Engineering

PubMed Central

Rauh, Juliane; Jacobi, Angela

2015-01-01

The principles of tissue engineering (TE) are widely used for bone regeneration concepts. Three-dimensional (3D) cultivation of autologous human mesenchymal stromal cells (MSCs) on porous scaffolds is the basic prerequisite to generate newly formed bone tissue. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a specific and sensitive analytical tool for the measurement of mRNA-levels in cells or tissues. For an accurate quantification of gene expression levels, stably expressed reference genes (RGs) are essential to obtain reliable results. Since the 3D environment can affect a cell's morphology, proliferation, and gene expression profile compared with two-dimensional (2D) cultivation, there is a need to identify robust RGs for the quantification of gene expression. So far, this issue has not been adequately investigated. The aim of this study was to identify the most stably expressed RGs for gene expression analysis of 3D-cultivated human bone marrow-derived MSCs (BM-MSCs). For this, we analyzed the gene expression levels of n=31 RGs in 3D-cultivated human BM-MSCs from six different donors compared with conventional 2D cultivation using qRT-PCR. MSCs isolated from bone marrow aspirates were cultivated on human cancellous bone cube scaffolds for 14 days. Osteogenic differentiation was assessed by cell-specific alkaline phosphatase (ALP) activity and expression of osteogenic marker genes. Expression levels of potential reference and target genes were quantified using commercially available TaqMan® assays. mRNA expression stability of RGs was determined by calculating the coefficient of variation (CV) and using the algorithms of geNorm and NormFinder. Using both algorithms, we identified TATA box binding protein (TBP), transferrin receptor (p90, CD71) (TFRC), and hypoxanthine phosphoribosyltransferase 1 (HPRT1) as the most stably expressed RGs in 3D-cultivated BM-MSCs. Notably, genes that are routinely used as RGs, for example, beta actin (ACTB) and ribosomal protein L37a (RPL37A), were among the least stable genes. We recommend the combined use of TBP, TFRC, and HPRT1 for the accurate and robust normalization of qRT-PCR data of 3D-cultivated human BM-MSCs. PMID:25000821

Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine.

PubMed

Lobo, Nazleen C; Gedye, Craig; Apostoli, Anthony J; Brown, Kevin R; Paterson, Joshua; Stickle, Natalie; Robinette, Michael; Fleshner, Neil; Hamilton, Robert J; Kulkarni, Girish; Zlotta, Alexandre; Evans, Andrew; Finelli, Antonio; Moffat, Jason; Jewett, Michael A S; Ailles, Laurie

2016-07-16

Patients with clear cell renal cell carcinoma (ccRCC) have few therapeutic options, as ccRCC is unresponsive to chemotherapy and is highly resistant to radiation. Recently targeted therapies have extended progression-free survival, but responses are variable and no significant overall survival benefit has been achieved. Commercial ccRCC cell lines are often used as model systems to develop novel therapeutic approaches, but these do not accurately recapitulate primary ccRCC tumors at the genomic and transcriptional levels. Furthermore, ccRCC exhibits significant intertumor genetic heterogeneity, and the limited cell lines available fail to represent this aspect of ccRCC. Our objective was to generate accurate preclinical in vitro models of ccRCC using tumor tissues from ccRCC patients. ccRCC primary single cell suspensions were cultured in fetal bovine serum (FBS)-containing media or defined serum-free media. Established cultures were characterized by genomic verification of mutations present in the primary tumors, expression of renal epithelial markers, and transcriptional profiling. The apparent efficiency of primary cell culture establishment was high in both culture conditions, but genotyping revealed that the majority of cultures contained normal, not cancer cells. ccRCC characteristically shows biallelic loss of the von Hippel Lindau (VHL) gene, leading to accumulation of hypoxia-inducible factor (HIF) and expression of HIF target genes. Purification of cells based on expression of carbonic anhydrase IX (CA9), a cell surface HIF target, followed by culture in FBS enabled establishment of ccRCC cell cultures with an efficiency of >80 %. Culture in serum-free conditions selected for growth of normal renal proximal tubule epithelial cells. Transcriptional profiling of ccRCC and matched normal cell cultures identified up- and down-regulated networks in ccRCC and comparison to The Cancer Genome Atlas confirmed the clinical validity of our cell cultures. The ability to establish primary cultures of ccRCC cells and matched normal kidney epithelial cells from almost every patient provides a resource for future development of novel therapies and personalized medicine for ccRCC patients.

Effect of carbon monoxide on gene expression in cerebrocortical astrocytes: Validation of reference genes for quantitative real-time PCR.

PubMed

Oliveira, Sara R; Vieira, Helena L A; Duarte, Carlos B

2015-09-15

Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is a widely used technique to characterize changes in gene expression in complex cellular and tissue processes, such as cytoprotection or inflammation. The accurate assessment of changes in gene expression depends on the selection of adequate internal reference gene(s). Carbon monoxide (CO) affects several metabolic pathways and de novo protein synthesis is crucial in the cellular responses to this gasotransmitter. Herein a selection of commonly used reference genes was analyzed to identify the most suitable internal control genes to evaluate the effect of CO on gene expression in cultured cerebrocortical astrocytes. The cells were exposed to CO by treatment with CORM-A1 (CO releasing molecule A1) and four different algorithms (geNorm, NormFinder, Delta Ct and BestKeeper) were applied to evaluate the stability of eight putative reference genes. Our results indicate that Gapdh (glyceraldehyde-3-phosphate dehydrogenase) together with Ppia (peptidylpropyl isomerase A) is the most suitable gene pair for normalization of qRT-PCR results under the experimental conditions used. Pgk1 (phosphoglycerate kinase 1), Hprt1 (hypoxanthine guanine phosphoribosyl transferase I), Sdha (Succinate Dehydrogenase Complex, Subunit A), Tbp (TATA box binding protein), Actg1 (actin gamma 1) and Rn18s (18S rRNA) genes presented less stable expression profiles in cultured cortical astrocytes exposed to CORM-A1 for up to 60 min. For validation, we analyzed the effect of CO on the expression of Bdnf and bcl-2. Different results were obtained, depending on the reference genes used. A significant increase in the expression of both genes was found when the results were normalized with Gapdh and Ppia, in contrast with the results obtained when the other genes were used as reference. These findings highlight the need for a proper and accurate selection of the reference genes used in the quantification of qRT-PCR results in studies on the effect of CO in gene expression. Copyright © 2015 Elsevier Inc. All rights reserved.

The prognostic implication of the expression of EGFR, p53, cyclin D1, Bcl-2 and p16 in primary locally advanced oral squamous cell carcinoma cases: a tissue microarray study.

PubMed

Solomon, Monica Charlotte; Vidyasagar, M S; Fernandes, Donald; Guddattu, Vasudev; Mathew, Mary; Shergill, Ankur Kaur; Carnelio, Sunitha; Chandrashekar, Chetana

2016-12-01

Oral squamous cell carcinomas comprise a heterogeneous tumor cell population with varied molecular characteristics, which makes prognostication of these tumors a complex and challenging issue. Thus, molecular profiling of these tumors is advantageous for an accurate prognostication and treatment planning. This is a retrospective study on a cohort of primary locally advanced oral squamous cell carcinomas (n = 178) of an Indian rural population. The expression of EGFR, p53, cyclin D1, Bcl-2 and p16 in a cohort of primary locally advanced oral squamous cell carcinomas was evaluated. A potential biomarker that can predict the tumor response to treatment was identified. Formalin-fixed paraffin-embedded tumor blocks of (n = 178) of histopathologically diagnosed cases of locally advanced oral squamous cell carcinomas were selected. Tissue microarray blocks were constructed with 2 cores of 2 mm diameter from each tumor block. Four-micron-thick sections were cut from these tissue microarray blocks. These tissue microarray sections were immunohistochemically stained for EGFR, p53, Bcl-2, cyclin D1 and p16. In this cohort, EGFR was the most frequently expressed 150/178 (84%) biomarker of the cases. Kaplan-Meier analysis showed a significant association (p = 0.038) between expression of p53 and a poor prognosis. A Poisson regression analysis showed that tumors that expressed p53 had a two times greater chance of recurrence (unadjusted IRR-95% CI 2.08 (1.03, 4.5), adjusted IRR-2.29 (1.08, 4.8) compared with the tumors that did not express this biomarker. Molecular profiling of oral squamous cell carcinomas will enable us to categorize our patients into more realistic risk groups. With biologically guided tumor characterization, personalized treatment protocols can be designed for individual patients, which will improve the quality of life of these patients.

A comparison of honeybee (Apis mellifera) queen, worker and drone larvae by RNA-Seq.

PubMed

He, Xu-Jiang; Jiang, Wu-Jun; Zhou, Mi; Barron, Andrew B; Zeng, Zhi-Jiang

2017-11-06

Honeybees (Apis mellifera) have haplodiploid sex determination: males develop from unfertilized eggs and females develop from fertilized ones. The differences in larval food also determine the development of females. Here we compared the total somatic gene expression profiles of 2-day and 4-day-old drone, queen and worker larvae by RNA-Seq. The results from a co-expression network analysis on all expressed genes showed that 2-day-old drone and worker larvae were closer in gene expression profiles than 2-day-old queen larvae. This indicated that for young larvae (2-day-old) environmental factors such as larval diet have a greater effect on gene expression profiles than ploidy or sex determination. Drones had the most distinct gene expression profiles at the 4-day larval stage, suggesting that haploidy, or sex dramatically affects the gene expression of honeybee larvae. Drone larvae showed fewer differences in gene expression profiles at the 2-day and 4-day time points than the worker and queen larval comparisons (598 against 1190 and 1181), suggesting a different pattern of gene expression regulation during the larval development of haploid males compared to diploid females. This study indicates that early in development the queen caste has the most distinct gene expression profile, perhaps reflecting the very rapid growth and morphological specialization of this caste compared to workers and drones. Later in development the haploid male drones have the most distinct gene expression profile, perhaps reflecting the influence of ploidy or sex determination on gene expression. © 2017 Institute of Zoology, Chinese Academy of Sciences.

Tuning the chemosensory window

PubMed Central

Zhou, Shanshan; Mackay, Trudy FC

2010-01-01

Accurate perception of chemical signals from the environment is critical for the fitness of most animals. Drosophila melanogaster experiences its chemical environment through families of chemoreceptors that include olfactory receptors, gustatory receptors and odorant binding proteins. Its chemical environment, however, changes during its life cycle and the interpretation of chemical signals is dependent on dynamic social and physical surroundings. Phenotypic plasticity of gene expression of the chemoreceptor repertoire allows flies to adjust the chemosensory window through which they “view” their world and to modify the ensemble of expressed chemoreceptor proteins in line with their developmental and physiological state and according to their needs to locate food and oviposition sites under different social and physical environmental conditions. Furthermore, males and females differ in their expression profiles of chemoreceptor genes. Thus, each sex experiences its chemical environment via combinatorial activation of distinct chemoreceptor ensembles. The remarkable phenotypic plasticity of the chemoreceptor repertoire raises several fundamental questions. What are the mechanisms that translate environmental cues into regulation of chemoreceptor gene expression? How are gustatory and olfactory cues integrated perceptually? What is the relationship between ensembles of odorant binding proteins and odorant receptors? And, what is the significance of co-regulated chemoreceptor transcriptional networks? PMID:20305396

Early diffusion of gene expression profiling in breast cancer patients associated with areas of high income inequality.

PubMed

Ponce, Ninez A; Ko, Michelle; Liang, Su-Ying; Armstrong, Joanne; Toscano, Michele; Chanfreau-Coffinier, Catherine; Haas, Jennifer S

2015-04-01

With the Affordable Care Act reducing coverage disparities, social factors could prominently determine where and for whom innovations first diffuse in health care markets. Gene expression profiling is a potentially cost-effective innovation that guides chemotherapy decisions in early-stage breast cancer, but adoption has been uneven across the United States. Using a sample of commercially insured women, we evaluated whether income inequality in metropolitan areas was associated with receipt of gene expression profiling during its initial diffusion in 2006-07. In areas with high income inequality, gene expression profiling receipt was higher than elsewhere, but it was associated with a 10.6-percentage-point gap between high- and low-income women. In areas with low rates of income inequality, gene expression profiling receipt was lower, with no significant differences by income. Even among insured women, income inequality may indirectly shape diffusion of gene expression profiling, with benefits accruing to the highest-income patients in the most unequal places. Policies reducing gene expression profiling disparities should address low-inequality areas and, in unequal places, practice settings serving low-income patients. Project HOPE—The People-to-People Health Foundation, Inc.

Codetype-based interpretation of the MMPI-2 in an outpatient psychotherapy sample.

PubMed

Koffmann, Andrew

2015-01-01

In an evaluation of the codetype-based interpretation of the MMPI-2, 48 doctoral student psychotherapists rated their clients' (N = 120) standardized interpretations as more accurate when based on the profile's codetype, in comparison with ratings for interpretations based on alternate codetypes. Effect sizes ranged from nonsignificant to large, depending on the degree of proximity between the profile's codetype and the alternate codetype. There was weak evidence to suggest that well-defined profiles yielded more accurate interpretations than undefined profiles. It appears that codetype-based interpretation of the MMPI-2 is generally valid, but there might be little difference in the accuracy of interpretations based on nearby codetypes.

Transcriptional risk scores link GWAS to eQTLs and predict complications in Crohn's disease.

PubMed

Marigorta, Urko M; Denson, Lee A; Hyams, Jeffrey S; Mondal, Kajari; Prince, Jarod; Walters, Thomas D; Griffiths, Anne; Noe, Joshua D; Crandall, Wallace V; Rosh, Joel R; Mack, David R; Kellermayer, Richard; Heyman, Melvin B; Baker, Susan S; Stephens, Michael C; Baldassano, Robert N; Markowitz, James F; Kim, Mi-Ok; Dubinsky, Marla C; Cho, Judy; Aronow, Bruce J; Kugathasan, Subra; Gibson, Greg

2017-10-01

Gene expression profiling can be used to uncover the mechanisms by which loci identified through genome-wide association studies (GWAS) contribute to pathology. Given that most GWAS hits are in putative regulatory regions and transcript abundance is physiologically closer to the phenotype of interest, we hypothesized that summation of risk-allele-associated gene expression, namely a transcriptional risk score (TRS), should provide accurate estimates of disease risk. We integrate summary-level GWAS and expression quantitative trait locus (eQTL) data with RNA-seq data from the RISK study, an inception cohort of pediatric Crohn's disease. We show that TRSs based on genes regulated by variants linked to inflammatory bowel disease (IBD) not only outperform genetic risk scores (GRSs) in distinguishing Crohn's disease from healthy samples, but also serve to identify patients who in time will progress to complicated disease. Our dissection of eQTL effects may be used to distinguish genes whose association with disease is through promotion versus protection, thereby linking statistical association to biological mechanism. The TRS approach constitutes a potential strategy for personalized medicine that enhances inference from static genotypic risk assessment.

A powerful and flexible statistical framework for testing hypotheses of allele-specific gene expression from RNA-seq data

PubMed Central

Skelly, Daniel A.; Johansson, Marnie; Madeoy, Jennifer; Wakefield, Jon; Akey, Joshua M.

2011-01-01

Variation in gene expression is thought to make a significant contribution to phenotypic diversity among individuals within populations. Although high-throughput cDNA sequencing offers a unique opportunity to delineate the genome-wide architecture of regulatory variation, new statistical methods need to be developed to capitalize on the wealth of information contained in RNA-seq data sets. To this end, we developed a powerful and flexible hierarchical Bayesian model that combines information across loci to allow both global and locus-specific inferences about allele-specific expression (ASE). We applied our methodology to a large RNA-seq data set obtained in a diploid hybrid of two diverse Saccharomyces cerevisiae strains, as well as to RNA-seq data from an individual human genome. Our statistical framework accurately quantifies levels of ASE with specified false-discovery rates, achieving high reproducibility between independent sequencing platforms. We pinpoint loci that show unusual and biologically interesting patterns of ASE, including allele-specific alternative splicing and transcription termination sites. Our methodology provides a rigorous, quantitative, and high-resolution tool for profiling ASE across whole genomes. PMID:21873452

Evaluating whole transcriptome amplification for gene profiling experiments using RNA-Seq.

PubMed

Faherty, Sheena L; Campbell, C Ryan; Larsen, Peter A; Yoder, Anne D

2015-07-30

RNA-Seq has enabled high-throughput gene expression profiling to provide insight into the functional link between genotype and phenotype. Low quantities of starting RNA can be a severe hindrance for studies that aim to utilize RNA-Seq. To mitigate this bottleneck, whole transcriptome amplification (WTA) technologies have been developed to generate sufficient sequencing targets from minute amounts of RNA. Successful WTA requires accurate replication of transcript abundance without the loss or distortion of specific mRNAs. Here, we test the efficacy of NuGEN's Ovation RNA-Seq V2 system, which uses linear isothermal amplification with a unique chimeric primer for amplification, using white adipose tissue from standard laboratory rats (Rattus norvegicus). Our goal was to investigate potential biological artifacts introduced through WTA approaches by establishing comparisons between matched raw and amplified RNA libraries derived from biological replicates. We found that 93% of expressed genes were identical between all unamplified versus matched amplified comparisons, also finding that gene density is similar across all comparisons. Our sequencing experiment and downstream bioinformatic analyses using the Tuxedo analysis pipeline resulted in the assembly of 25,543 high-quality transcripts. Libraries constructed from raw RNA and WTA samples averaged 15,298 and 15,253 expressed genes, respectively. Although significant differentially expressed genes (P < 0.05) were identified in all matched samples, each of these represents less than 0.15% of all shared genes for each comparison. Transcriptome amplification is efficient at maintaining relative transcript frequencies with no significant bias when using this NuGEN linear isothermal amplification kit under ideal laboratory conditions as presented in this study. This methodology has broad applications, from clinical and diagnostic, to field-based studies when sample acquisition, or sample preservation, methods prove challenging.

RNA Editome in Rhesus Macaque Shaped by Purifying Selection

PubMed Central

Yang, Xin-Zhuang; Tan, Bertrand Chin-Ming; Fang, Huaying; Liu, Chu-Jun; Shi, Mingming; Ye, Zhi-Qiang; Zhang, Yong E.; Deng, Minghua; Zhang, Xiuqin; Li, Chuan-Yun

2014-01-01

Understanding of the RNA editing process has been broadened considerably by the next generation sequencing technology; however, several issues regarding this regulatory step remain unresolved – the strategies to accurately delineate the editome, the mechanism by which its profile is maintained, and its evolutionary and functional relevance. Here we report an accurate and quantitative profile of the RNA editome for rhesus macaque, a close relative of human. By combining genome and transcriptome sequencing of multiple tissues from the same animal, we identified 31,250 editing sites, of which 99.8% are A-to-G transitions. We verified 96.6% of editing sites in coding regions and 97.5% of randomly selected sites in non-coding regions, as well as the corresponding levels of editing by multiple independent means, demonstrating the feasibility of our experimental paradigm. Several lines of evidence supported the notion that the adenosine deamination is associated with the macaque editome – A-to-G editing sites were flanked by sequences with the attributes of ADAR substrates, and both the sequence context and the expression profile of ADARs are relevant factors in determining the quantitative variance of RNA editing across different sites and tissue types. In support of the functional relevance of some of these editing sites, substitution valley of decreased divergence was detected around the editing site, suggesting the evolutionary constraint in maintaining some of these editing substrates with their double-stranded structure. These findings thus complement the “continuous probing” model that postulates tinkering-based origination of a small proportion of functional editing sites. In conclusion, the macaque editome reported here highlights RNA editing as a widespread functional regulation in primate evolution, and provides an informative framework for further understanding RNA editing in human. PMID:24722121

Dual RNA regulatory control of a Staphylococcus aureus virulence factor.

PubMed

Chabelskaya, Svetlana; Bordeau, Valérie; Felden, Brice

2014-04-01

In pathogens, the accurate programming of virulence gene expression is essential for infection. It is achieved by sophisticated arrays of regulatory proteins and ribonucleic acids (sRNAs), but in many cases their contributions and connections are not yet known. Based on genetic, biochemical and structural evidence, we report that the expression pattern of a Staphylococcus aureus host immune evasion protein is enabled by the collaborative actions of RNAIII and small pathogenicity island RNA D (SprD). Their combined expression profiles during bacterial growth permit early and transient synthesis of Sbi to avoid host immune responses. Together, these two sRNAs use antisense mechanisms to monitor Sbi expression at the translational level. Deletion analysis combined with structural analysis of RNAIII in complex with its novel messenger RNA (mRNA) target indicate that three distant RNAIII domains interact with distinct sites of the sbi mRNA and that two locations are deep in the sbi coding region. Through distinct domains, RNAIII lowers production of two proteins required for avoiding innate host immunity, staphylococcal protein A and Sbi. Toeprints and in vivo mutational analysis reveal a novel regulatory module within RNAIII essential for attenuation of Sbi translation. The sophisticated translational control of mRNA by two differentially expressed sRNAs ensures supervision of host immune escape by a major pathogen.

Pre-vaccination inflammation and B-cell signalling predict age-related hyporesponse to hepatitis B vaccination

PubMed Central

Fourati, Slim; Cristescu, Razvan; Loboda, Andrey; Talla, Aarthi; Filali, Ali; Railkar, Radha; Schaeffer, Andrea K.; Favre, David; Gagnon, Dominic; Peretz, Yoav; Wang, I-Ming; Beals, Chan R.; Casimiro, Danilo R.; Carayannopoulos, Leonidas N.; Sékaly, Rafick-Pierre

2016-01-01

Aging is associated with hyporesponse to vaccination, whose mechanisms remain unclear. In this study hepatitis B virus (HBV)-naive older adults received three vaccines, including one against HBV. Here we show, using transcriptional and cytometric profiling of whole blood collected before vaccination, that heightened expression of genes that augment B-cell responses and higher memory B-cell frequencies correlate with stronger responses to HBV vaccine. In contrast, higher levels of inflammatory response transcripts and increased frequencies of pro-inflammatory innate cells correlate with weaker responses to this vaccine. Increased numbers of erythrocytes and the haem-induced response also correlate with poor response to the HBV vaccine. A transcriptomics-based pre-vaccination predictor of response to HBV vaccine is built and validated in distinct sets of older adults. This moderately accurate (area under the curve≈65%) but robust signature is supported by flow cytometry and cytokine profiling. This study is the first that identifies baseline predictors and mechanisms of response to the HBV vaccine. PMID:26742691

Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia

PubMed Central

Wang, Lili; Fan, Jean; Francis, Joshua M.; Georghiou, George; Hergert, Sarah; Li, Shuqiang; Gambe, Rutendo; Zhou, Chensheng W.; Yang, Chunxiao; Xiao, Sheng; Cin, Paola Dal; Bowden, Michaela; Kotliar, Dylan; Shukla, Sachet A.; Brown, Jennifer R.; Neuberg, Donna; Alessi, Dario R.; Zhang, Cheng-Zhong; Kharchenko, Peter V.; Livak, Kenneth J.; Wu, Catherine J.

2017-01-01

Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype–phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy. PMID:28679620

RNA-Stabilized Whole Blood Samples but Not Peripheral Blood Mononuclear Cells Can Be Stored for Prolonged Time Periods Prior to Transcriptome Analysis

PubMed Central

Debey-Pascher, Svenja; Hofmann, Andrea; Kreusch, Fatima; Schuler, Gerold; Schuler-Thurner, Beatrice; Schultze, Joachim L.; Staratschek-Jox, Andrea

2011-01-01

Microarray-based transcriptome analysis of peripheral blood as surrogate tissue has become an important approach in clinical implementations. However, application of gene expression profiling in routine clinical settings requires careful consideration of the influence of sample handling and RNA isolation methods on gene expression profile outcome. We evaluated the effect of different sample preservation strategies (eg, cryopreservation of peripheral blood mononuclear cells or freezing of PAXgene-stabilized whole blood samples) on gene expression profiles. Expression profiles obtained from cryopreserved peripheral blood mononuclear cells differed substantially from those of their nonfrozen counterpart samples. Furthermore, expression profiles in cryopreserved peripheral blood mononuclear cell samples were found to undergo significant alterations with increasing storage period, whereas long-term freezing of PAXgene RNA stabilized whole blood samples did not significantly affect stability of gene expression profiles. This report describes important technical aspects contributing toward the establishment of robust and reliable guidance for gene expression studies using peripheral blood and provides a promising strategy for reliable implementation in routine handling for diagnostic purposes. PMID:21704280

Temperature Profile in Fuel and Tie-Tubes for Nuclear Thermal Propulsion Systems

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

Vishal Patel

A finite element method to calculate temperature profiles in heterogeneous geometries of tie-tube moderated LEU nuclear thermal propulsion systems and HEU designs with tie-tubes is developed and implemented in MATLAB. This new method is compared to previous methods to demonstrate shortcomings in those methods. Typical methods to analyze peak fuel centerline temperature in hexagonal geometries rely on spatial homogenization to derive an analytical expression. These methods are not applicable to cores with tie-tube elements because conduction to tie-tubes cannot be accurately modeled with the homogenized models. The fuel centerline temperature directly impacts safety and performance so it must be predictedmore » carefully. The temperature profile in tie-tubes is also important when high temperatures are expected in the fuel because conduction to the tie-tubes may cause melting in tie-tubes, which may set maximum allowable performance. Estimations of maximum tie-tube temperature can be found from equivalent tube methods, however this method tends to be approximate and overly conservative. A finite element model of heat conduction on a unit cell can model spatial dependence and non-linear conductivity for fuel and tie-tube systems allowing for higher design fidelity of Nuclear Thermal Propulsion.« less

Profiling over 1500 lipids in induced lung sputum and the implications in studying lung diseases.

PubMed

t'Kindt, Ruben; Telenga, Eef D; Jorge, Lucie; Van Oosterhout, Antoon J M; Sandra, Pat; Ten Hacken, Nick H T; Sandra, Koen

2015-01-01

Induced lung sputum is a valuable matrix in the study of respiratory diseases. Although the methodology of sputum collection has evolved to a point where it is repeatable and responsive to inflammation, its use in molecular profiling studies is still limited. Here, an in-depth lipid profiling of induced lung sputum using high-resolution liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (LC-Q-TOF MS) is described. An enormous complexity in lipid composition could be revealed. Over 1500 intact lipids, originating from 6 major lipid classes, have been accurately identified in 120 μL of induced sputum. By number and measured intensity, glycerophospholipids represent the largest lipid class, followed by sphingolipids, glycerolipids, fatty acyls, sterol lipids, and prenol lipids. Several prenol lipids, originating from tobacco, could be detected in the lung sputum of smokers. To illustrate the utility of the methodology in studying respiratory diseases, a comparative lipid screening was performed on lung sputum extracts in order to study the effect of Chronic Obstructive Pulmonary Disease (COPD) on the lung barrier lipidome. Results show that sphingolipid expression in induced sputum significantly differs between smokers with and without COPD.

Profiling Pre-MicroRNA and Mature MicroRNA Expressions Using a Single Microarray and Avoiding Separate Sample Preparation

PubMed Central

Gan, Lin; Denecke, Bernd

2013-01-01

Mature microRNA is a crucial component in the gene expression regulation network. At the same time, microRNA gene expression and procession is regulated in a precise and collaborated way. Pre-microRNAs mediate products during the microRNA transcription process, they can provide hints of microRNA gene expression regulation or can serve as alternative biomarkers. To date, little effort has been devoted to pre-microRNA expression profiling. In this study, three human and three mouse microRNA profile data sets, based on the Affymetrix miRNA 2.0 array, have been re-analyzed for both mature and pre-microRNA signals as a primary test of parallel mature/pre-microRNA expression profiling on a single platform. The results not only demonstrated a glimpse of pre-microRNA expression in human and mouse, but also the relationship of microRNA expressions between pre- and mature forms. The study also showed a possible application of currently available microRNA microarrays in profiling pre-microRNA expression in a time and cost effective manner. PMID:27605179

Fully automated laser ray tracing system to measure changes in the crystalline lens GRIN profile.

PubMed

Qiu, Chen; Maceo Heilman, Bianca; Kaipio, Jari; Donaldson, Paul; Vaghefi, Ehsan

2017-11-01

Measuring the lens gradient refractive index (GRIN) accurately and reliably has proven an extremely challenging technical problem. A fully automated laser ray tracing (LRT) system was built to address this issue. The LRT system captures images of multiple laser projections before and after traversing through an ex vivo lens. These LRT images, combined with accurate measurements of the lens geometry, are used to calculate the lens GRIN profile. Mathematically, this is an ill-conditioned problem; hence, it is essential to apply biologically relevant constraints to produce a feasible solution. The lens GRIN measurements were compared with previously published data. Our GRIN retrieval algorithm produces fast and accurate measurements of the lens GRIN profile. Experiments to study the optics of physiologically perturbed lenses are the future direction of this research.

Fully automated laser ray tracing system to measure changes in the crystalline lens GRIN profile

PubMed Central

Qiu, Chen; Maceo Heilman, Bianca; Kaipio, Jari; Donaldson, Paul; Vaghefi, Ehsan

2017-01-01

Measuring the lens gradient refractive index (GRIN) accurately and reliably has proven an extremely challenging technical problem. A fully automated laser ray tracing (LRT) system was built to address this issue. The LRT system captures images of multiple laser projections before and after traversing through an ex vivo lens. These LRT images, combined with accurate measurements of the lens geometry, are used to calculate the lens GRIN profile. Mathematically, this is an ill-conditioned problem; hence, it is essential to apply biologically relevant constraints to produce a feasible solution. The lens GRIN measurements were compared with previously published data. Our GRIN retrieval algorithm produces fast and accurate measurements of the lens GRIN profile. Experiments to study the optics of physiologically perturbed lenses are the future direction of this research. PMID:29188093

That "poker face" just might lose you the game! The impact of expressive suppression and mimicry on sensitivity to facial expressions of emotion.

PubMed

Schneider, Kristin G; Hempel, Roelie J; Lynch, Thomas R

2013-10-01

Successful interpersonal functioning often requires both the ability to mask inner feelings and the ability to accurately recognize others' expressions--but what if effortful control of emotional expressions impacts the ability to accurately read others? In this study, we examined the influence of self-controlled expressive suppression and mimicry on facial affect sensitivity--the speed with which one can accurately identify gradually intensifying facial expressions of emotion. Muscle activity of the brow (corrugator, related to anger), upper lip (levator, related to disgust), and cheek (zygomaticus, related to happiness) were recorded using facial electromyography while participants randomized to one of three conditions (Suppress, Mimic, and No-Instruction) viewed a series of six distinct emotional expressions (happiness, sadness, fear, anger, surprise, and disgust) as they morphed from neutral to full expression. As hypothesized, individuals instructed to suppress their own facial expressions showed impairment in facial affect sensitivity. Conversely, mimicry of emotion expressions appeared to facilitate facial affect sensitivity. Results suggest that it is difficult for a person to be able to simultaneously mask inner feelings and accurately "read" the facial expressions of others, at least when these expressions are at low intensity. The combined behavioral and physiological data suggest that the strategies an individual selects to control his or her own expression of emotion have important implications for interpersonal functioning.

MicroRNAs show a wide diversity of expression profiles in the developing and mature central nervous system

PubMed Central

Kapsimali, Marika; Kloosterman, Wigard P; de Bruijn, Ewart; Rosa, Frederic; Plasterk, Ronald HA; Wilson, Stephen W

2007-01-01

Background MicroRNA (miRNA) encoding genes are abundant in vertebrate genomes but very few have been studied in any detail. Bioinformatic tools allow prediction of miRNA targets and this information coupled with knowledge of miRNA expression profiles facilitates formulation of hypotheses of miRNA function. Although the central nervous system (CNS) is a prominent site of miRNA expression, virtually nothing is known about the spatial and temporal expression profiles of miRNAs in the brain. To provide an overview of the breadth of miRNA expression in the CNS, we performed a comprehensive analysis of the neuroanatomical expression profiles of 38 abundant conserved miRNAs in developing and adult zebrafish brain. Results Our results show miRNAs have a wide variety of different expression profiles in neural cells, including: expression in neuronal precursors and stem cells (for example, miR-92b); expression associated with transition from proliferation to differentiation (for example, miR-124); constitutive expression in mature neurons (miR-124 again); expression in both proliferative cells and their differentiated progeny (for example, miR-9); regionally restricted expression (for example, miR-222 in telencephalon); and cell-type specific expression (for example, miR-218a in motor neurons). Conclusion The data we present facilitate prediction of likely modes of miRNA function in the CNS and many miRNA expression profiles are consistent with the mutual exclusion mode of function in which there is spatial or temporal exclusion of miRNAs and their targets. However, some miRNAs, such as those with cell-type specific expression, are more likely to be co-expressed with their targets. Our data provide an important resource for future functional studies of miRNAs in the CNS. PMID:17711588

One-dimensional wave bottom boundary layer model comparison: specific eddy viscosity and turbulence closure models

USGS Publications Warehouse

Puleo, J.A.; Mouraenko, O.; Hanes, D.M.

2004-01-01

Six one-dimensional-vertical wave bottom boundary layer models are analyzed based on different methods for estimating the turbulent eddy viscosity: Laminar, linear, parabolic, k—one equation turbulence closure, k−ε—two equation turbulence closure, and k−ω—two equation turbulence closure. Resultant velocity profiles, bed shear stresses, and turbulent kinetic energy are compared to laboratory data of oscillatory flow over smooth and rough beds. Bed shear stress estimates for the smooth bed case were most closely predicted by the k−ω model. Normalized errors between model predictions and measurements of velocity profiles over the entire computational domain collected at 15° intervals for one-half a wave cycle show that overall the linear model was most accurate. The least accurate were the laminar and k−ε models. Normalized errors between model predictions and turbulence kinetic energy profiles showed that the k−ω model was most accurate. Based on these findings, when the smallest overall velocity profile prediction error is required, the processing requirements and error analysis suggest that the linear eddy viscosity model is adequate. However, if accurate estimates of bed shear stress and TKE are required then, of the models tested, the k−ω model should be used.

Validation of Reference Genes for Gene Expression Studies in Virus-Infected Nicotiana benthamiana Using Quantitative Real-Time PCR

PubMed Central

Han, Chenggui; Yu, Jialin; Li, Dawei; Zhang, Yongliang

2012-01-01

Nicotiana benthamiana is the most widely-used experimental host in plant virology. The recent release of the draft genome sequence for N. benthamiana consolidates its role as a model for plant–pathogen interactions. Quantitative real-time PCR (qPCR) is commonly employed for quantitative gene expression analysis. For valid qPCR analysis, accurate normalisation of gene expression against an appropriate internal control is required. Yet there has been little systematic investigation of reference gene stability in N. benthamiana under conditions of viral infections. In this study, the expression profiles of 16 commonly used housekeeping genes (GAPDH, 18S, EF1α, SAMD, L23, UK, PP2A, APR, UBI3, SAND, ACT, TUB, GBP, F-BOX, PPR and TIP41) were determined in N. benthamiana and those with acceptable expression levels were further selected for transcript stability analysis by qPCR of complementary DNA prepared from N. benthamiana leaf tissue infected with one of five RNA plant viruses (Tobacco necrosis virus A, Beet black scorch virus, Beet necrotic yellow vein virus, Barley stripe mosaic virus and Potato virus X). Gene stability was analysed in parallel by three commonly-used dedicated algorithms: geNorm, NormFinder and BestKeeper. Statistical analysis revealed that the PP2A, F-BOX and L23 genes were the most stable overall, and that the combination of these three genes was sufficient for accurate normalisation. In addition, the suitability of PP2A, F-BOX and L23 as reference genes was illustrated by expression-level analysis of AGO2 and RdR6 in virus-infected N. benthamiana leaves. This is the first study to systematically examine and evaluate the stability of different reference genes in N. benthamiana. Our results not only provide researchers studying these viruses a shortlist of potential housekeeping genes to use as normalisers for qPCR experiments, but should also guide the selection of appropriate reference genes for gene expression studies of N. benthamiana under other biotic and abiotic stress conditions. PMID:23029521

Comparative prion disease gene expression profiling using the prion disease mimetic, cuprizone

PubMed Central

Moody, Laura R; Herbst, Allen J; Yoo, Han Sang; Vanderloo, Joshua P

2009-01-01

Identification of genes expressed in response to prion infection may elucidate biomarkers for disease, identify factors involved in agent replication, mechanisms of neuropathology and therapeutic targets. Although several groups have sought to identify gene expression changes specific to prion disease, expression profiles rife with cell population changes have consistently been identified. Cuprizone, a neurotoxicant, qualitatively mimics the cell population changes observed in prion disease, resulting in both spongiform change and astrocytosis. The use of cuprizone-treated animals as an experimental control during comparative expression profiling allows for the identification of transcripts whose expression increases during prion disease and remains unchanged during cuprizone-triggered neuropathology. In this study, expression profiles from the brains of mice preclinically and clinically infected with Rocky Mountain Laboratory (RML) mouse-adapted scrapie agent and age-matched controls were profiled using Affymetrix gene arrays. In total, 164 genes were differentially regulated during prion infection. Eighty-three of these transcripts have been previously undescribed as differentially regulated during prion disease. A 0.4% cuprizone diet was utilized as a control for comparative expression profiling. Cuprizone treatment induced spongiosis and astrocyte proliferation as indicated by glial fibrillary acidic protein (Gfap) transcriptional activation and immunohistochemistry. Gene expression profiles from brain tissue obtained from cuprizone-treated mice identified 307 differentially regulated transcript changes. After comparative analysis, 17 transcripts unaffected by cuprizone treatment but increasing in expression from preclinical to clinical prion infection were identified. Here we describe the novel use of the prion disease mimetic, cuprizone, to control for cell population changes in the brain during prion infection. PMID:19535908

Defective Cell Cycle Checkpoint Functions in Melanoma Are Associated with Altered Patterns of Gene Expression

PubMed Central

Kaufmann, William K.; Nevis, Kathleen R.; Qu, Pingping; Ibrahim, Joseph G.; Zhou, Tong; Zhou, Yingchun; Simpson, Dennis A.; Helms-Deaton, Jennifer; Cordeiro-Stone, Marila; Moore, Dominic T.; Thomas, Nancy E.; Hao, Honglin; Liu, Zhi; Shields, Janiel M.; Scott, Glynis A.; Sharpless, Norman E.

2009-01-01

Defects in DNA damage responses may underlie genetic instability and malignant progression in melanoma. Cultures of normal human melanocytes (NHMs) and melanoma lines were analyzed to determine whether global patterns of gene expression could predict the efficacy of DNA damage cell cycle checkpoints that arrest growth and suppress genetic instability. NHMs displayed effective G1 and G2 checkpoint responses to ionizing radiation-induced DNA damage. A majority of melanoma cell lines (11/16) displayed significant quantitative defects in one or both checkpoints. Melanomas with B-RAF mutations as a class displayed a significant defect in DNA damage G2 checkpoint function. In contrast the epithelial-like subtype of melanomas with wild-type N-RAS and B-RAF alleles displayed an effective G2 checkpoint but a significant defect in G1 checkpoint function. RNA expression profiling revealed that melanoma lines with defects in the DNA damage G1 checkpoint displayed reduced expression of p53 transcriptional targets, such as CDKN1A and DDB2, and enhanced expression of proliferation-associated genes, such as CDC7 and GEMININ. A Bayesian analysis tool was more accurate than significance analysis of microarrays for predicting checkpoint function using a leave-one-out method. The results suggest that defects in DNA damage checkpoints may be recognized in melanomas through analysis of gene expression. PMID:17597816

Potential of gene expression profiling in the management of childhood acute lymphoblastic leukemia.

PubMed

Bhojwani, Deepa; Moskowitz, Naomi; Raetz, Elizabeth A; Carroll, William L

2007-01-01

Childhood acute lymphoblastic leukemia (ALL) is a heterogeneous disease. Current treatment approaches are tailored according to the clinical features of the host, genotypic features of the leukemic blast, and early response to therapy. Although these approaches have been successful in dramatically improving outcomes, approximately 20% of children with ALL still relapse and many of these children do not have an identifiable adverse risk factor at presentation. Further insights into the biologic basis of the disease may contribute to novel, rational treatment strategies. Childhood ALL has served as an example for demonstrating the feasibility and potential of high-throughput technologies such as global gene expression or transcript profiling. In the last decade or so, utilization of these techniques has grown exponentially. As the methodology undergoes refinement and validation, it is plausible that microarrays may be used in the routine management of childhood ALL in the next few years. This article discusses the numerous applications to date of gene expression profiling in childhood ALL. Multiple investigators have made it evident that microarrays can be used as a single platform for the accurate classification of ALL into the various cytogenetic subtypes. Additional promising utilities include prediction of early response to therapy, overall outcome, and adverse effects. Identification of patients who are predicted to have an unfavorable outcome may allow for early intervention such as intensification of therapy or avoidance of drugs that are associated with specific secondary effects such as therapy-related acute myelogenous leukemia. Knowledge has been gained into pathways contributing to leukemogenesis and chemoresistance. Therapeutic targets have been identified, some of which are entering clinical trials following validation in additional preclinical models. These newer methods of genome analyses complemented by studies involving the proteome as well as host polymorphisms will have a profound impact on the diagnosis and management of childhood ALL.

Investigating the Receptive-Expressive Vocabulary Profile in Children with Idiopathic ASD and Comorbid ASD and Fragile X Syndrome.

PubMed

Haebig, Eileen; Sterling, Audra

2017-02-01

Previous work has noted that some children with autism spectrum disorder (ASD) display weaknesses in receptive vocabulary relative to expressive vocabulary abilities. The current study extended previous work by examining the receptive-expressive vocabulary profile in boys with idiopathic ASD and boys with concomitant ASD and fragile X syndrome (ASD + FXS). On average, boys with ASD + FXS did not display the same atypical receptive-expressive profile as boys with idiopathic ASD. Notably, there was variation in vocabulary abilities and profiles in both groups. Although we did not identify predictors of receptive-expressive differences, we demonstrated that nonverbal IQ and expressive vocabulary positively predicted concurrent receptive vocabulary knowledge and receptive vocabulary predicted expressive vocabulary. We discuss areas of overlap and divergence in subgroups of ASD.

Investigating the Receptive-Expressive Vocabulary Profile in Children with Idiopathic ASD and Comorbid ASD and Fragile X Syndrome

PubMed Central

Sterling, Audra

2016-01-01

Previous work has noted that some children with autism spectrum disorder (ASD) display weaknesses in receptive vocabulary relative to expressive vocabulary abilities. The current study extended previous work by examining the receptive-expressive vocabulary profile in boys with idiopathic ASD and boys with concomitant ASD and fragile X syndrome (ASD + FXS). On average, boys with ASD + FXS did not display the same atypical receptive-expressive profile as boys with idiopathic ASD. Notably, there was variation in vocabulary abilities and profiles in both groups. Although we did not identify predictors of receptive-expressive differences, we demonstrated that nonverbal IQ and expressive vocabulary positively predicted concurrent receptive vocabulary knowledge and receptive vocabulary predicted expressive vocabulary. We discuss areas of overlap and divergence in subgroups of ASD. PMID:27796729

A Novel Real-Time PCR Assay of microRNAs Using S-Poly(T), a Specific Oligo(dT) Reverse Transcription Primer with Excellent Sensitivity and Specificity

PubMed Central

Kang, Kang; Zhang, Xiaoying; Liu, Hongtao; Wang, Zhiwei; Zhong, Jiasheng; Huang, Zhenting; Peng, Xiao; Zeng, Yan; Wang, Yuna; Yang, Yi; Luo, Jun; Gou, Deming

2012-01-01

Background MicroRNAs (miRNAs) are small, non-coding RNAs capable of postranscriptionally regulating gene expression. Accurate expression profiling is crucial for understanding the biological roles of miRNAs, and exploring them as biomarkers of diseases. Methodology/Principal Findings A novel, highly sensitive, and reliable miRNA quantification approach,termed S-Poly(T) miRNA assay, is designed. In this assay, miRNAs are subjected to polyadenylation and reverse transcription with a S-Poly(T) primer that contains a universal reverse primer, a universal Taqman probe, an oligo(dT)11 sequence and six miRNA-specific bases. Individual miRNAs are then amplified by a specific forward primer and a universal reverse primer, and the PCR products are detected by a universal Taqman probe. The S-Poly(T) assay showed a minimum of 4-fold increase in sensitivity as compared with the stem-loop or poly(A)-based methods. A remarkable specificity in discriminating among miRNAs with high sequence similarity was also obtained with this approach. Using this method, we profiled miRNAs in human pulmonary arterial smooth muscle cells (HPASMC) and identified 9 differentially expressed miRNAs associated with hypoxia treatment. Due to its outstanding sensitivity, the number of circulating miRNAs from normal human serum was significantly expanded from 368 to 518. Conclusions/Significance With excellent sensitivity, specificity, and high-throughput, the S-Poly(T) method provides a powerful tool for miRNAs quantification and identification of tissue- or disease-specific miRNA biomarkers. PMID:23152780

Identification of Emotional Facial Expressions: Effects of Expression, Intensity, and Sex on Eye Gaze.

PubMed

Wells, Laura Jean; Gillespie, Steven Mark; Rotshtein, Pia

2016-01-01

The identification of emotional expressions is vital for social interaction, and can be affected by various factors, including the expressed emotion, the intensity of the expression, the sex of the face, and the gender of the observer. This study investigates how these factors affect the speed and accuracy of expression recognition, as well as dwell time on the two most significant areas of the face: the eyes and the mouth. Participants were asked to identify expressions from female and male faces displaying six expressions (anger, disgust, fear, happiness, sadness, and surprise), each with three levels of intensity (low, moderate, and normal). Overall, responses were fastest and most accurate for happy expressions, but slowest and least accurate for fearful expressions. More intense expressions were also classified most accurately. Reaction time showed a different pattern, with slowest response times recorded for expressions of moderate intensity. Overall, responses were slowest, but also most accurate, for female faces. Relative to male observers, women showed greater accuracy and speed when recognizing female expressions. Dwell time analyses revealed that attention to the eyes was about three times greater than on the mouth, with fearful eyes in particular attracting longer dwell times. The mouth region was attended to the most for fearful, angry, and disgusted expressions and least for surprise. These results extend upon previous findings to show important effects of expression, emotion intensity, and sex on expression recognition and gaze behaviour, and may have implications for understanding the ways in which emotion recognition abilities break down.

Identification of Emotional Facial Expressions: Effects of Expression, Intensity, and Sex on Eye Gaze

PubMed Central

Rotshtein, Pia

2016-01-01

The identification of emotional expressions is vital for social interaction, and can be affected by various factors, including the expressed emotion, the intensity of the expression, the sex of the face, and the gender of the observer. This study investigates how these factors affect the speed and accuracy of expression recognition, as well as dwell time on the two most significant areas of the face: the eyes and the mouth. Participants were asked to identify expressions from female and male faces displaying six expressions (anger, disgust, fear, happiness, sadness, and surprise), each with three levels of intensity (low, moderate, and normal). Overall, responses were fastest and most accurate for happy expressions, but slowest and least accurate for fearful expressions. More intense expressions were also classified most accurately. Reaction time showed a different pattern, with slowest response times recorded for expressions of moderate intensity. Overall, responses were slowest, but also most accurate, for female faces. Relative to male observers, women showed greater accuracy and speed when recognizing female expressions. Dwell time analyses revealed that attention to the eyes was about three times greater than on the mouth, with fearful eyes in particular attracting longer dwell times. The mouth region was attended to the most for fearful, angry, and disgusted expressions and least for surprise. These results extend upon previous findings to show important effects of expression, emotion intensity, and sex on expression recognition and gaze behaviour, and may have implications for understanding the ways in which emotion recognition abilities break down. PMID:27942030

Design and evaluation of Actichip, a thematic microarray for the study of the actin cytoskeleton

PubMed Central

Muller, Jean; Mehlen, André; Vetter, Guillaume; Yatskou, Mikalai; Muller, Arnaud; Chalmel, Frédéric; Poch, Olivier; Friederich, Evelyne; Vallar, Laurent

2007-01-01

Background The actin cytoskeleton plays a crucial role in supporting and regulating numerous cellular processes. Mutations or alterations in the expression levels affecting the actin cytoskeleton system or related regulatory mechanisms are often associated with complex diseases such as cancer. Understanding how qualitative or quantitative changes in expression of the set of actin cytoskeleton genes are integrated to control actin dynamics and organisation is currently a challenge and should provide insights in identifying potential targets for drug discovery. Here we report the development of a dedicated microarray, the Actichip, containing 60-mer oligonucleotide probes for 327 genes selected for transcriptome analysis of the human actin cytoskeleton. Results Genomic data and sequence analysis features were retrieved from GenBank and stored in an integrative database called Actinome. From these data, probes were designed using a home-made program (CADO4MI) allowing sequence refinement and improved probe specificity by combining the complementary information recovered from the UniGene and RefSeq databases. Actichip performance was analysed by hybridisation with RNAs extracted from epithelial MCF-7 cells and human skeletal muscle. Using thoroughly standardised procedures, we obtained microarray images with excellent quality resulting in high data reproducibility. Actichip displayed a large dynamic range extending over three logs with a limit of sensitivity between one and ten copies of transcript per cell. The array allowed accurate detection of small changes in gene expression and reliable classification of samples based on the expression profiles of tissue-specific genes. When compared to two other oligonucleotide microarray platforms, Actichip showed similar sensitivity and concordant expression ratios. Moreover, Actichip was able to discriminate the highly similar actin isoforms whereas the two other platforms did not. Conclusion Our data demonstrate that Actichip is a powerful alternative to commercial high density microarrays for cytoskeleton gene profiling in normal or pathological samples. Actichip is available upon request. PMID:17727702

DNA methylation profiling identifies global methylation differences and markers of adrenocortical tumors.

PubMed

Rechache, Nesrin S; Wang, Yonghong; Stevenson, Holly S; Killian, J Keith; Edelman, Daniel C; Merino, Maria; Zhang, Lisa; Nilubol, Naris; Stratakis, Constantine A; Meltzer, Paul S; Kebebew, Electron

2012-06-01

It is not known whether there are any DNA methylation alterations in adrenocortical tumors. The objective of the study was to determine the methylation profile of normal adrenal cortex and benign and malignant adrenocortical tumors. Genome-wide methylation status of CpG regions were determined in normal (n = 19), benign (n = 48), primary malignant (n = 8), and metastatic malignant (n = 12) adrenocortical tissue samples. An integrated analysis of genome-wide methylation and mRNA expression in benign vs. malignant adrenocortical tissue samples was also performed. Methylation profiling revealed the following: 1) that methylation patterns were distinctly different and could distinguish normal, benign, primary malignant, and metastatic tissue samples; 2) that malignant samples have global hypomethylation; and 3) that the methylation of CpG regions are different in benign adrenocortical tumors by functional status. Normal compared with benign samples had the least amount of methylation differences, whereas normal compared with primary and metastatic adrenocortical carcinoma samples had the greatest variability in methylation (adjusted P ≤ 0.01). Of 215 down-regulated genes (≥2-fold, adjusted P ≤ 0.05) in malignant primary adrenocortical tumor samples, 52 of these genes were also hypermethylated. Malignant adrenocortical tumors are globally hypomethylated as compared with normal and benign tumors. Methylation profile differences may accurately distinguish between primary benign and malignant adrenocortical tumors. Several differentially methylated sites are associated with genes known to be dysregulated in malignant adrenocortical tumors.

3D gut-liver chip with a PK model for prediction of first-pass metabolism.

PubMed

Lee, Dong Wook; Ha, Sang Keun; Choi, Inwook; Sung, Jong Hwan

2017-11-07

Accurate prediction of first-pass metabolism is essential for improving the time and cost efficiency of drug development process. Here, we have developed a microfluidic gut-liver co-culture chip that aims to reproduce the first-pass metabolism of oral drugs. This chip consists of two separate layers for gut (Caco-2) and liver (HepG2) cell lines, where cells can be co-cultured in both 2D and 3D forms. Both cell lines were maintained well in the chip, verified by confocal microscopy and measurement of hepatic enzyme activity. We investigated the PK profile of paracetamol in the chip, and corresponding PK model was constructed, which was used to predict PK profiles for different chip design parameters. Simulation results implied that a larger absorption surface area and a higher metabolic capacity are required to reproduce the in vivo PK profile of paracetamol more accurately. Our study suggests the possibility of reproducing the human PK profile on a chip, contributing to accurate prediction of pharmacological effect of drugs.

Artificial neural network classifier predicts neuroblastoma patients' outcome.

PubMed

Cangelosi, Davide; Pelassa, Simone; Morini, Martina; Conte, Massimo; Bosco, Maria Carla; Eva, Alessandra; Sementa, Angela Rita; Varesio, Luigi

2016-11-08

More than fifty percent of neuroblastoma (NB) patients with adverse prognosis do not benefit from treatment making the identification of new potential targets mandatory. Hypoxia is a condition of low oxygen tension, occurring in poorly vascularized tissues, which activates specific genes and contributes to the acquisition of the tumor aggressive phenotype. We defined a gene expression signature (NB-hypo), which measures the hypoxic status of the neuroblastoma tumor. We aimed at developing a classifier predicting neuroblastoma patients' outcome based on the assessment of the adverse effects of tumor hypoxia on the progression of the disease. Multi-layer perceptron (MLP) was trained on the expression values of the 62 probe sets constituting NB-hypo signature to develop a predictive model for neuroblastoma patients' outcome. We utilized the expression data of 100 tumors in a leave-one-out analysis to select and construct the classifier and the expression data of the remaining 82 tumors to test the classifier performance in an external dataset. We utilized the Gene set enrichment analysis (GSEA) to evaluate the enrichment of hypoxia related gene sets in patients predicted with "Poor" or "Good" outcome. We utilized the expression of the 62 probe sets of the NB-Hypo signature in 182 neuroblastoma tumors to develop a MLP classifier predicting patients' outcome (NB-hypo classifier). We trained and validated the classifier in a leave-one-out cross-validation analysis on 100 tumor gene expression profiles. We externally tested the resulting NB-hypo classifier on an independent 82 tumors' set. The NB-hypo classifier predicted the patients' outcome with the remarkable accuracy of 87 %. NB-hypo classifier prediction resulted in 2 % classification error when applied to clinically defined low-intermediate risk neuroblastoma patients. The prediction was 100 % accurate in assessing the death of five low/intermediated risk patients. GSEA of tumor gene expression profile demonstrated the hypoxic status of the tumor in patients with poor prognosis. We developed a robust classifier predicting neuroblastoma patients' outcome with a very low error rate and we provided independent evidence that the poor outcome patients had hypoxic tumors, supporting the potential of using hypoxia as target for neuroblastoma treatment.

Single cell gene expression profiling of cortical osteoblast lineage cells.

PubMed

Flynn, James M; Spusta, Steven C; Rosen, Clifford J; Melov, Simon

2013-03-01

In tissues with complex architectures such as bone, it is often difficult to purify and characterize specific cell types via molecular profiling. Single cell gene expression profiling is an emerging technology useful for characterizing transcriptional profiles of individual cells isolated from heterogeneous populations. In this study we describe a novel procedure for the isolation and characterization of gene expression profiles of single osteoblast lineage cells derived from cortical bone. Mixed populations of different cell types were isolated from adult long bones of C57BL/6J mice by enzymatic digestion, and subsequently subjected to FACS to purify and characterize osteoblast lineage cells via a selection strategy using antibodies against CD31, CD45, and alkaline phosphatase (AP), specific for mature osteoblasts. The purified individual osteoblast lineage cells were then profiled at the single cell level via nanofluidic PCR. This method permits robust gene expression profiling on single osteoblast lineage cells derived from mature bone, potentially from anatomically distinct sites. In conjunction with this technique, we have also shown that it is possible to carry out single cell profiling on cells purified from fixed and frozen bone samples without compromising the gene expression signal. The latter finding means the technique can be extended to biopsies of bone from diseased individuals. Our approach for single cell expression profiling provides a new dimension to the transcriptional profile of the primary osteoblast lineage population in vivo, and has the capacity to greatly expand our understanding of how these cells may function in vivo under normal and diseased states. Copyright © 2012 Elsevier Inc. All rights reserved.

Genomic and Expression Profiling of Benign and Malignant Nerve Sheath Profiling of Benign and Malignant Nerve Sheath

DTIC Science & Technology

2007-05-01

Benign and Malignant Nerve Sheath Tumors in Neurofibromatosis Patients PRINCIPAL INVESTIGATOR: Matt van de Rijn, M.D., Ph.D. Torsten...Annual 3. DATES COVERED 1 May 2006 –30 Apr 2007 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Genomic and Expression Profiling of Benign and Malignant Nerve...Award Number: DAMD17-03-1-0297 Title: Genomic and Expression Profiling of Benign and Malignant Nerve Sheath Tumors in Neurofibromatosis

Ground state of a confined Yukawa plasma including correlation effects

NASA Astrophysics Data System (ADS)

Henning, C.; Ludwig, P.; Filinov, A.; Piel, A.; Bonitz, M.

2007-09-01

The ground state of an externally confined one-component Yukawa plasma is derived analytically using the local density approximation (LDA). In particular, the radial density profile is computed. The results are compared with the recently obtained mean-field (MF) density profile [Henning , Phys. Rev. E 74, 056403 (2006)]. While the MF results are more accurate for weak screening, the LDA with correlations included yields the proper description for large screening. By comparison with first-principles simulations for three-dimensional spherical Yukawa crystals, we demonstrate that the two approximations complement each other. Together they accurately describe the density profile in the full range of screening parameters.

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

PubMed

Wu, Zhenhua Jeremy; Meyer, Clifford A; Choudhury, Sibgat; Shipitsin, Michail; Maruyama, Reo; Bessarabova, Marina; Nikolskaya, Tatiana; Sukumar, Saraswati; Schwartzman, Armin; Liu, Jun S; Polyak, Kornelia; Liu, X Shirley

2010-12-01

We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.

Time-course analysis of the Shewanella amazonensis SB2B proteome in response to sodium chloride shock.

PubMed

Parnell, J Jacob; Callister, Stephen J; Rompato, Giovanni; Nicora, Carrie D; Paša-Tolić, Ljiljana; Williamson, Ashley; Pfrender, Michael E

2011-01-01

Shewanellae are microbial models for environmental stress response; however, the sequential expression of mechanisms in response to stress is poorly understood. Here we experimentally determine the response mechanisms of Shewanella amazonensis SB2B during sodium chloride stress using a novel liquid chromatography and accurate mass-time tag mass spectrometry time-course proteomics approach. The response of SB2B involves an orchestrated sequence of events comprising increased signal transduction associated with motility and restricted growth. Following a metabolic shift to branched chain amino acid degradation, motility and cellular replication proteins return to pre-perturbed levels. Although sodium chloride stress is associated with a change in the membrane fatty acid composition in other organisms, this is not the case for SB2B as fatty acid degradation pathways are not expressed and no change in the fatty acid profile is observed. These findings suggest that shifts in membrane composition may be an indirect physiological response to high NaCl stress.

Optimal control of build height utilizing optical profilometry in cold spray deposits

NASA Astrophysics Data System (ADS)

Chakraborty, Abhijit; Shishkin, Sergey; Birnkrant, Michael J.

2017-04-01

Part-to-part variability and poor part quality due to failure to maintain geometric specifications pose a challenge for adopting Additive Manufacturing (AM) as a viable manufacturing process. In recent years, In-process Monitoring and Control (InPMC) has received a lot of attention as an approach to overcome these obstacles. The ability to sense geometry of the deposited layers accurately enables effective process monitoring and control of AM application. This paper demonstrates an application of geometry sensing technique for the coating deposition Cold Spray process, where solid powders are accelerated through a nozzle, collides with the substrate and adheres to it. Often the deposited surface has shape irregularities. This paper proposes an approach to suppress the iregularities by controlling the deposition height. An analytical control-oriented model is developed that expresses the resulting height of deposit as an integral function of nozzle velocity and angle. In order to obtain height information at each layer, a Micro-Epsilon laser line scanner was used for surface profiling after each deposition. This surface profile information, specifically the layer height, was then fed back to an optimal control algorithm which manipulated the nozzle speed to control the layer height to a pre specified height. While the problem is heavily nonlinear, we were able to transform it into equivalent Optimal Control problem linear w.r.t. input. That enabled development of two solution methods: one is fast and approximate, while another is more accurate but still efficient.

Electrolyte for EC-V profiling of InP and GaAs based structures

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

Faur, M.; Faur, M.; Goradia, M.

Electrochemical C-V (EC-V) profiling is the most often used and convenient method for accurate majority carrier concentration depth profiling of semiconductors. Although, according to the authors, FAP is the best electrolyte for accurate profiling of InP structures, it does not work well with other III-V compounds. To overcome this, recently, the authors have developed a new electrolyte, which they call UNIEL (UNIversal ELectrolyte), which works well with all the materials. However, as with the FAP electrolyte, the presence of HF makes the UNIEL incompatible with the electrochemical cell of Polaron EC-V profilers manufactured by BIO-RAD. By slightly modifying the electrochemicalmore » cell configuration the authors are able to use both the FAP and UNIEL electrolytes, without destroying the calomel electrode. Recently, they have, nevertheless, experimented with variations of the UNIEL with no HF content for EC-V profiling of structures based on InP and GaAs. Presently available results are presented here.« less

ColoLipidGene: signature of lipid metabolism-related genes to predict prognosis in stage-II colon cancer patients

PubMed Central

Vargas, Teodoro; Moreno-Rubio, Juan; Herranz, Jesús; Cejas, Paloma; Molina, Susana; González-Vallinas, Margarita; Mendiola, Marta; Burgos, Emilio; Aguayo, Cristina; Custodio, Ana B.; Machado, Isidro; Ramos, David; Gironella, Meritxell; Espinosa-Salinas, Isabel; Ramos, Ricardo; Martín-Hernández, Roberto; Risueño, Alberto; De Las Rivas, Javier; Reglero, Guillermo; Yaya, Ricardo; Fernández-Martos, Carlos; Aparicio, Jorge; Maurel, Joan; Feliu, Jaime; de Molina, Ana Ramírez

2015-01-01

Lipid metabolism plays an essential role in carcinogenesis due to the requirements of tumoral cells to sustain increased structural, energetic and biosynthetic precursor demands for cell proliferation. We investigated the association between expression of lipid metabolism-related genes and clinical outcome in intermediate-stage colon cancer patients with the aim of identifying a metabolic profile associated with greater malignancy and increased risk of relapse. Expression profile of 70 lipid metabolism-related genes was determined in 77 patients with stage II colon cancer. Cox regression analyses using c-index methodology was applied to identify a metabolic-related signature associated to prognosis. The metabolic signature was further confirmed in two independent validation sets of 120 patients and additionally, in a group of 264 patients from a public database. The combined analysis of these 4 genes, ABCA1, ACSL1, AGPAT1 and SCD, constitutes a metabolic-signature (ColoLipidGene) able to accurately stratify stage II colon cancer patients with 5-fold higher risk of relapse with strong statistical power in the four independent groups of patients. The identification of a group of 4 genes that predict survival in intermediate-stage colon cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy, and avoids the toxic and unnecessary chemotherapy in patients classified as low-risk group. PMID:25749516

Structural imprints in vivo decode RNA regulatory mechanisms.

PubMed

Spitale, Robert C; Flynn, Ryan A; Zhang, Qiangfeng Cliff; Crisalli, Pete; Lee, Byron; Jung, Jong-Wha; Kuchelmeister, Hannes Y; Batista, Pedro J; Torre, Eduardo A; Kool, Eric T; Chang, Howard Y

2015-03-26

Visualizing the physical basis for molecular behaviour inside living cells is a great challenge for biology. RNAs are central to biological regulation, and the ability of RNA to adopt specific structures intimately controls every step of the gene expression program. However, our understanding of physiological RNA structures is limited; current in vivo RNA structure profiles include only two of the four nucleotides that make up RNA. Here we present a novel biochemical approach, in vivo click selective 2'-hydroxyl acylation and profiling experiment (icSHAPE), which enables the first global view, to our knowledge, of RNA secondary structures in living cells for all four bases. icSHAPE of the mouse embryonic stem cell transcriptome versus purified RNA folded in vitro shows that the structural dynamics of RNA in the cellular environment distinguish different classes of RNAs and regulatory elements. Structural signatures at translational start sites and ribosome pause sites are conserved from in vitro conditions, suggesting that these RNA elements are programmed by sequence. In contrast, focal structural rearrangements in vivo reveal precise interfaces of RNA with RNA-binding proteins or RNA-modification sites that are consistent with atomic-resolution structural data. Such dynamic structural footprints enable accurate prediction of RNA-protein interactions and N(6)-methyladenosine (m(6)A) modification genome wide. These results open the door for structural genomics of RNA in living cells and reveal key physiological structures controlling gene expression.

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

PubMed

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

2011-01-01

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

Two-dimensional analytical model of double-gate tunnel FETs with interface trapped charges including effects of channel mobile charge carriers

NASA Astrophysics Data System (ADS)

Xu, Huifang; Dai, Yuehua

2017-02-01

A two-dimensional analytical model of double-gate (DG) tunneling field-effect transistors (TFETs) with interface trapped charges is proposed in this paper. The influence of the channel mobile charges on the potential profile is also taken into account in order to improve the accuracy of the models. On the basis of potential profile, the electric field is derived and the expression for the drain current is obtained by integrating the BTBT generation rate. The model can be used to study the impact of interface trapped charges on the surface potential, the shortest tunneling length, the drain current and the threshold voltage for varying interface trapped charge densities, length of damaged region as well as the structural parameters of the DG TFET and can also be utilized to design the charge trapped memory devices based on TFET. The biggest advantage of this model is that it is more accurate, and in its expression there are no fitting parameters with small calculating amount. Very good agreements for both the potential, drain current and threshold voltage are observed between the model calculations and the simulated results. Project supported by the National Natural Science Foundation of China (No. 61376106), the University Natural Science Research Key Project of Anhui Province (No. KJ2016A169), and the Introduced Talents Project of Anhui Science and Technology University.

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

PubMed Central

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

2011-01-01

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

Gene expression inference with deep learning.

PubMed

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.

Gene expression inference with deep learning

PubMed Central

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

2016-01-01

Motivation: 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. Results: 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. Availability and implementation: D-GEX is available at https://github.com/uci-cbcl/D-GEX. Contact: xhx@ics.uci.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26873929

PROFILES OF GENE EXPRESSION ASSOCIATED WITH TETRACYCLINE OVER EXPRESSION OF HSP70 IN MCF-7 BREAST CANCER CELLS

EPA Science Inventory

Profiles of gene expression associated with tetracycline over expression of HSP70 in MCF-7 breast cancer cells.

Heat shock proteins (HSPs) protect cells from damage through their function as molecular chaperones. Some cancers reveal high levels of HSP70 expression in asso...

VISCOPLASTIC FLUID MODEL FOR DEBRIS FLOW ROUTING.

USGS Publications Warehouse

Chen, Cheng-lung

1986-01-01

This paper describes how a generalized viscoplastic fluid model, which was developed based on non-Newtonian fluid mechanics, can be successfully applied to routing a debris flow down a channel. The one-dimensional dynamic equations developed for unsteady clear-water flow can be used for debris flow routing if the flow parameters, such as the momentum (or energy) correction factor and the resistance coefficient, can be accurately evaluated. The writer's generalized viscoplastic fluid model can be used to express such flow parameters in terms of the rheological parameters for debris flow in wide channels. A preliminary analysis of the theoretical solutions reveals the importance of the flow behavior index and the so-called modified Froude number for uniformly progressive flow in snout profile modeling.

Oncocytic Type Intraductal Papillary Mucinous Neoplasm of the Pancreas with Unusually Low Mucin Production Mimicking Intraductal Tubulopapillary Neoplasm: A Report of a Case Diagnosed by a Preoperative Endoscopic Biopsy

PubMed Central

Yoshida, Yukinari; Endo, Takao; Tanaka, Eiichi; Kikuchi, Takefumi; Akino, Kimishige; Mita, Hiroaki; Adachi, Yasuyo; Nakamura, Masahiro; Adachi, Yasushi; Ishii, Yoshifumi; Matsumoto, Joe; Hirano, Satoshi; Nitta, Takeo; Mitsuhashi, Tomoko; Kato, Yasuo

2017-01-01

We herein report the case of a 78-year-old woman with an intraductal tumor with scant mucin production in a moderately dilated main pancreatic duct that resembled an intraductal tubulopapillary neoplasm (ITPN) on imaging. An endoscopic transpapillary forceps biopsy enabled an accurate preoperative diagnosis of the tumor as an oncocytic type intraductal papillary mucinous neoplasm (IPMN) of the pancreas microscopically showing papillary growth consisting of oncocytic cells with a typical mucin expression profile, although with few intraepithelial lumina containing mucin. This is the first case of an oncocytic type IPMN mimicking an ITPN that was able to be diagnosed preoperatively. PMID:29021473

An efficient numerical procedure for thermohydrodynamic analysis of cavitating bearings

NASA Technical Reports Server (NTRS)

Vijayaraghavan, D.

1995-01-01

An efficient and accurate numerical procedure to determine the thermo-hydrodynamic performance of cavitating bearings is described. This procedure is based on the earlier development of Elrod for lubricating films, in which the properties across the film thickness are determined at Lobatto points and their distributions are expressed by collocated polynomials. The cavitated regions and their boundaries are rigorously treated. Thermal boundary conditions at the surfaces, including heat dissipation through the metal to the ambient, are incorporated. Numerical examples are presented comparing the predictions using this procedure with earlier theoretical predictions and experimental data. With a few points across the film thickness and across the journal and the bearing in the radial direction, the temperature profile is very well predicted.

Emerging immunotherapy and strategies directly targeting B cells for the treatment of diffuse large B-cell lymphoma.

PubMed

Witkowska, Magdalena; Smolewski, Piotr

2015-01-01

During the last decade, significant prolonged survival in diffusive large B-cell lymphoma (DLBCL) has been observed. The efficacy of initial treatment improved mostly due to addition of a chimeric anti-CD20 monoclonal antibody (rituximab) to standard chemotherapeutic regimens. Moreover, accurate understanding of DLBCL pathogenesis and remarkable progress in gene expression profiling have led to the development of a variety of tumor-specific regimens. Novel agents target directly the pathways involved in signal transduction, lead to apoptosis and cancer cells differentiation. In this article, we mainly focus on new treatment options, such as monoclonal antibodies, tyrosine kinase inhibitors and immunomodulatory drugs, currently investigated in aggressive B-cell lymphoma with particular attention to DLBCL type.

Similar protein expression profiles of ovarian and endometrial high-grade serous carcinomas.

PubMed

Hiramatsu, Kosuke; Yoshino, Kiyoshi; Serada, Satoshi; Yoshihara, Kosuke; Hori, Yumiko; Fujimoto, Minoru; Matsuzaki, Shinya; Egawa-Takata, Tomomi; Kobayashi, Eiji; Ueda, Yutaka; Morii, Eiichi; Enomoto, Takayuki; Naka, Tetsuji; Kimura, Tadashi

2016-03-01

Ovarian and endometrial high-grade serous carcinomas (HGSCs) have similar clinical and pathological characteristics; however, exhaustive protein expression profiling of these cancers has yet to be reported. We performed protein expression profiling on 14 cases of HGSCs (7 ovarian and 7 endometrial) and 18 endometrioid carcinomas (9 ovarian and 9 endometrial) using iTRAQ-based exhaustive and quantitative protein analysis. We identified 828 tumour-expressed proteins and evaluated the statistical similarity of protein expression profiles between ovarian and endometrial HGSCs using unsupervised hierarchical cluster analysis (P<0.01). Using 45 statistically highly expressed proteins in HGSCs, protein ontology analysis detected two enriched terms and proteins composing each term: IMP2 and MCM2. Immunohistochemical analyses confirmed the higher expression of IMP2 and MCM2 in ovarian and endometrial HGSCs as well as in tubal and peritoneal HGSCs than in endometrioid carcinomas (P<0.01). The knockdown of either IMP2 or MCM2 by siRNA interference significantly decreased the proliferation rate of ovarian HGSC cell line (P<0.01). We demonstrated the statistical similarity of the protein expression profiles of ovarian and endometrial HGSC beyond the organs. We suggest that increased IMP2 and MCM2 expression may underlie some of the rapid HGSC growth observed clinically.

A fast algorithm for determining bounds and accurate approximate p-values of the rank product statistic for replicate experiments.

PubMed

Heskes, Tom; Eisinga, Rob; Breitling, Rainer

2014-11-21

The rank product method is a powerful statistical technique for identifying differentially expressed molecules in replicated experiments. A critical issue in molecule selection is accurate calculation of the p-value of the rank product statistic to adequately address multiple testing. Both exact calculation and permutation and gamma approximations have been proposed to determine molecule-level significance. These current approaches have serious drawbacks as they are either computationally burdensome or provide inaccurate estimates in the tail of the p-value distribution. We derive strict lower and upper bounds to the exact p-value along with an accurate approximation that can be used to assess the significance of the rank product statistic in a computationally fast manner. The bounds and the proposed approximation are shown to provide far better accuracy over existing approximate methods in determining tail probabilities, with the slightly conservative upper bound protecting against false positives. We illustrate the proposed method in the context of a recently published analysis on transcriptomic profiling performed in blood. We provide a method to determine upper bounds and accurate approximate p-values of the rank product statistic. The proposed algorithm provides an order of magnitude increase in throughput as compared with current approaches and offers the opportunity to explore new application domains with even larger multiple testing issue. The R code is published in one of the Additional files and is available at http://www.ru.nl/publish/pages/726696/rankprodbounds.zip .

Structure-related clustering of gene expression fingerprints of thp-1 cells exposed to smaller polycyclic aromatic hydrocarbons.

PubMed

Wan, B; Yarbrough, J W; Schultz, T W

2008-01-01

This study was undertaken to test the hypothesis that structurally similar PAHs induce similar gene expression profiles. THP-1 cells were exposed to a series of 12 selected PAHs at 50 microM for 24 hours and gene expressions profiles were analyzed using both unsupervised and supervised methods. Clustering analysis of gene expression profiles revealed that the 12 tested chemicals were grouped into five clusters. Within each cluster, the gene expression profiles are more similar to each other than to the ones outside the cluster. One-methylanthracene and 1-methylfluorene were found to have the most similar profiles; dibenzothiophene and dibenzofuran were found to share common profiles with fluorine. As expression pattern comparisons were expanded, similarity in genomic fingerprint dropped off dramatically. Prediction analysis of microarrays (PAM) based on the clustering pattern generated 49 predictor genes that can be used for sample discrimination. Moreover, a significant analysis of Microarrays (SAM) identified 598 genes being modulated by tested chemicals with a variety of biological processes, such as cell cycle, metabolism, and protein binding and KEGG pathways being significantly (p < 0.05) affected. It is feasible to distinguish structurally different PAHs based on their genomic fingerprints, which are mechanism based.

Use of Attribute Driven Incremental Discretization and Logic Learning Machine to build a prognostic classifier for neuroblastoma patients.

PubMed

Cangelosi, Davide; Muselli, Marco; Parodi, Stefano; Blengio, Fabiola; Becherini, Pamela; Versteeg, Rogier; Conte, Massimo; Varesio, Luigi

2014-01-01

Cancer patient's outcome is written, in part, in the gene expression profile of the tumor. We previously identified a 62-probe sets signature (NB-hypo) to identify tissue hypoxia in neuroblastoma tumors and showed that NB-hypo stratified neuroblastoma patients in good and poor outcome 1. It was important to develop a prognostic classifier to cluster patients into risk groups benefiting of defined therapeutic approaches. Novel classification and data discretization approaches can be instrumental for the generation of accurate predictors and robust tools for clinical decision support. We explored the application to gene expression data of Rulex, a novel software suite including the Attribute Driven Incremental Discretization technique for transforming continuous variables into simplified discrete ones and the Logic Learning Machine model for intelligible rule generation. We applied Rulex components to the problem of predicting the outcome of neuroblastoma patients on the bases of 62 probe sets NB-hypo gene expression signature. The resulting classifier consisted in 9 rules utilizing mainly two conditions of the relative expression of 11 probe sets. These rules were very effective predictors, as shown in an independent validation set, demonstrating the validity of the LLM algorithm applied to microarray data and patients' classification. The LLM performed as efficiently as Prediction Analysis of Microarray and Support Vector Machine, and outperformed other learning algorithms such as C4.5. Rulex carried out a feature selection by selecting a new signature (NB-hypo-II) of 11 probe sets that turned out to be the most relevant in predicting outcome among the 62 of the NB-hypo signature. Rules are easily interpretable as they involve only few conditions. Our findings provided evidence that the application of Rulex to the expression values of NB-hypo signature created a set of accurate, high quality, consistent and interpretable rules for the prediction of neuroblastoma patients' outcome. We identified the Rulex weighted classification as a flexible tool that can support clinical decisions. For these reasons, we consider Rulex to be a useful tool for cancer classification from microarray gene expression data.

Field tests of a down-hole TDR profiling water content measurement system

USDA-ARS?s Scientific Manuscript database

Accurate soil profile water content monitoring at multiple depths has previously been possible only using the neutron probe (NP), but with great effort and at unsatisfactory intervals. Despite the existence of several capacitance systems for profile water content measurements, accuracy and spatial r...

Joint profiling of greenhouse gases, isotopes, thermodynamic variables, and wind from space by combined microwave and IR laser occultation: the ACCURATE concept

NASA Astrophysics Data System (ADS)

Kirchengast, G.; Schweitzer, S.

2008-12-01

The ACCURATE (Atmospheric Climate and Chemistry in the UTLS Region And climate Trends Explorer) mission was conceived at the Wegener Center in late 2004 and subsequently proposed in 2005 by an international team of more than 20 scientific partners from more than 12 countries to an ESA selection process for next Earth Explorer Missions. While the mission was not selected for formal pre-phase A study, it received very positive evaluation and was recommended for further development and demonstration. ACCURATE employs the occultation measurement principle, known for its unique combination of high vertical resolution, accuracy and long-term stability, in a novel way. It systematically combines use of highly stable signals in the MW 17-23/178-196 GHz bands (LEO-LEO MW crosslink occultation) with laser signals in the SWIR 2-2.5 μm band (LEO-LEO IR laser crosslink occultation) for exploring and monitoring climate and chemistry in the atmosphere with focus on the UTLS region (upper troposphere/lower stratosphere, 5-35 km). The MW occultation is an advanced and at the same time compact version of the LEO-LEO MW occultation concept, studied in 2002-2004 for the ACE+ mission project of ESA for frequencies including the 17-23 GHz band, complemented by U.S. study heritage for frequencies including the 178-196 GHz bands (R. Kursinski et al., Univ. of Arizona, Tucson). The core of ACCURATE is tight synergy of the IR laser crosslinks with the MW crosslinks. The observed parameters, obtained simultaneously and in a self-calibrated manner based on Doppler shift and differential log-transmission profiles, comprise the fundamental thermodynamic variables of the atmosphere (temperature, pressure/geopotential height, humidity) retrieved from the MW bands, complemented by line-of-sight wind, six greenhouse gases (GHGs) and key species of UTLS chemistry (H2O, CO2, CH4, N2O, O3, CO) and four CO2 and H2O isotopes (HDO, H218O, 13CO2, C18OO) from the SWIR band. Furthermore, profiles of aerosol extinction, cloud layering, and turbulence are obtained. All profiles come with accurate height knowledge (< 10 m uncertainty), since measuring height as a function of time is intrinsic to the MW occultation part of ACCURATE. The presentation will introduce ACCURATE along the lines above, with emphasis on the climate science value and the new IR laser occultation capability. The focus will then be on retrieval performance analysis results obtained so far, in particular regarding the profiles of GHGs, isotopes, and wind. The results provide evidence that the GHG and isotope profiles can generally be retrieved within 5-35 km outside clouds with < 1% to 5% rms accuracy at 1-2 km vertical resolution, and wind with < 2 m/s accuracy. Monthly mean climatological profiles, assuming ~40 profiles per climatologic grid box per month, are found unbiased (free of time-varying biases) and at < 0.2% to 0.5% rms accuracy. These encouraging results are discussed in light of the potential of the ACCURATE technique to provide benchmark data for future monitoring of climate, GHGs, and chemistry variability and change. European science and demonstration activities are outlined, including international participation opportunities.

Reference gene selection for normalization of RT-qPCR gene expression data from Actinidia deliciosa leaves infected with Pseudomonas syringae pv. actinidiae

PubMed Central

Petriccione, Milena; Mastrobuoni, Francesco; Zampella, Luigi; Scortichini, Marco

2015-01-01

Normalization of data, by choosing the appropriate reference genes (RGs), is fundamental for obtaining reliable results in reverse transcription-quantitative PCR (RT-qPCR). In this study, we assessed Actinidia deliciosa leaves inoculated with two doses of Pseudomonas syringae pv. actinidiae during a period of 13 days for the expression profile of nine candidate RGs. Their expression stability was calculated using four algorithms: geNorm, NormFinder, BestKeeper and the deltaCt method. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and protein phosphatase 2A (PP2A) were the most stable genes, while β-tubulin and 7s-globulin were the less stable. Expression analysis of three target genes, chosen for RGs validation, encoding the reactive oxygen species scavenging enzymes ascorbate peroxidase (APX), superoxide dismutase (SOD) and catalase (CAT) indicated that a combination of stable RGs, such as GAPDH and PP2A, can lead to an accurate quantification of the expression levels of such target genes. The APX level varied during the experiment time course and according to the inoculum doses, whereas both SOD and CAT resulted down-regulated during the first four days, and up-regulated afterwards, irrespective of inoculum dose. These results can be useful for better elucidating the molecular interaction in the A. deliciosa/P. s. pv. actinidiae pathosystem and for RGs selection in bacteria-plant pathosystems. PMID:26581656

Use of the thin sheath approximation for obtaining ion temperatures from the ISEE 1 limited aperture RPA. [for magnetosphere

NASA Technical Reports Server (NTRS)

Comfort, R. H.; Baugher, C. R.; Chappell, C. R.

1982-01-01

A procedure for analyzing low-energy (less than approximately 100 eV) ion data from the plasma composition experiment on ISEE 1 is set forth. The method is based on a derived analytic expression for particle flux to a limited aperture retarding potential analyzer (RPA) in the thin sheath approximation, which makes allowance for some effects of a charged spacecraft on plasma particle trajectories. Calculations using simulated data are employed in testing the efficacy and accuracy of the technique. On the basis of an analysis of these calculation results and the mathematical model, the method is seen as being able to provide accurate ion temperatures from all good plasmaspheric RPA data. It is noted that corresponding densities and spacecraft potentials should be accurate when spacecraft potentials are negative but that they are subject to error for positive spacecraft potentials, particularly when ion Mach numbers are much less than 1. An analysis of data from a representative ISEE 1 pass produces a plasmasphere temperature profile that is consistent in overall structure with previous observations.

Thermal structure of the Martian atmosphere retrieved from the IR- spectrometry in the 15 mkm CO2 band

NASA Astrophysics Data System (ADS)

Zasova, L.; Formisano, V.; Grassi, D.; Igantiev, N.; Moroz, V.

Thermal IR spectrometry is one of the methods of the Martian atmosphere investigation below 55 km. The temperature profiles retrieved from the 15 μm CO2 band may be used for MIRA database. This approach gives the vertical resolution of several kilometers and accuracy of several Kelvins. An aerosol abundance, which influences the temperature profiles, is obtained from the continuum of the same spectrum. It is taken into account in the temperature retrieval procedure in a self- consistent way. Although this method has limited vertical resolution it possesses some advantages. For example, the radio occultation method gives the temperature profiles with higher spectral resolution, but the radio observations are sparse in space and local time. Direct measurements, which give the most accurate results, enable to obtain the temperature profiles only for some chosen points (landing places). Actually, the thermal IR-spectrometry is the only method, which allows to monitor the temperature profiles with good coverage both in space and local time. The first measurements of this kind were fulfilled by IRIS, installed on board of Mariner 9. This spectrometer was characterized by rather high spectral resolution (2.4 cm-1). The temperature profiles vs. local time dependencies for different latitudes and seasons were retrieved, including dust storm conditions, North polar night, Tharsis volcanoes. The obtained temperature profiles have been compared with the temperature profiles for the same conditions, taken from Climate Data Base (European GCM). The Planetary Fourier Spectrometer onboard Mars Express (which is planned to be launched in 2003) has the spectral range 1.2-45 μm and spectral resolution of 1.5 cm- 1. Temperature retrieval is one of the main scientific goals of the experiment. It opens a possibility to get a series of temperature profiles taken for different conditions, which can later be used in MIRA producing.

A method to identify differential expression profiles of time-course gene data with Fourier transformation.

PubMed

Kim, Jaehee; Ogden, Robert Todd; Kim, Haseong

2013-10-18

Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization.The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics.

Ultrahigh-resolution spectroscopy with atomic or molecular dark resonances: Exact steady-state line shapes and asymptotic profiles in the adiabatic pulsed regime

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

Zanon-Willette, Thomas; Clercq, Emeric de; Arimondo, Ennio

2011-12-15

Exact and asymptotic line shape expressions are derived from the semiclassical density matrix representation describing a set of closed three-level {Lambda} atomic or molecular states including decoherences, relaxation rates, and light shifts. An accurate analysis of the exact steady-state dark-resonance profile describing the Autler-Townes doublet, the electromagnetically induced transparency or coherent population trapping resonance, and the Fano-Feshbach line shape leads to the linewidth expression of the two-photon Raman transition and frequency shifts associated to the clock transition. From an adiabatic analysis of the dynamical optical Bloch equations in the weak field limit, a pumping time required to efficiently trap amore » large number of atoms into a coherent superposition of long-lived states is established. For a highly asymmetrical configuration with different decay channels, a strong two-photon resonance based on a lower states population inversion is established when the driving continuous-wave laser fields are greatly unbalanced. When time separated resonant two-photon pulses are applied in the adiabatic pulsed regime for atomic or molecular clock engineering, where the first pulse is long enough to reach a coherent steady-state preparation and the second pulse is very short to avoid repumping into a new dark state, dark-resonance fringes mixing continuous-wave line shape properties and coherent Ramsey oscillations are created. Those fringes allow interrogation schemes bypassing the power broadening effect. Frequency shifts affecting the central clock fringe computed from asymptotic profiles and related to the Raman decoherence process exhibit nonlinear shapes with the three-level observable used for quantum measurement. We point out that different observables experience different shifts on the lower-state clock transition.« less

Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

PubMed Central

2014-01-01

Background Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. Results S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. Conclusions This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved. PMID:24444313

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

PubMed

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

2017-01-01

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

GENE EXPRESSION PROFILES IN ARSENIC-TREATED MCF-7 BREAST CANCER CELLS EXPRESSING DIFFERENT LEVELS OF HSP70

EPA Science Inventory

Gene expression profiles in arsenic-treated MCF-7 breast cancer cells expressing different levels of HSP70

Gail Nelson, Susan Hester, Ernest Winkfield, Jill Barnes, James Allen
Environmental Carcinogenesis Division, NHEERL, ORD, US Environmental Protection Agency, Rese...

qpure: A Tool to Estimate Tumor Cellularity from Genome-Wide Single-Nucleotide Polymorphism Profiles

PubMed Central

Song, Sarah; Nones, Katia; Miller, David; Harliwong, Ivon; Kassahn, Karin S.; Pinese, Mark; Pajic, Marina; Gill, Anthony J.; Johns, Amber L.; Anderson, Matthew; Holmes, Oliver; Leonard, Conrad; Taylor, Darrin; Wood, Scott; Xu, Qinying; Newell, Felicity; Cowley, Mark J.; Wu, Jianmin; Wilson, Peter; Fink, Lynn; Biankin, Andrew V.; Waddell, Nic; Grimmond, Sean M.; Pearson, John V.

2012-01-01

Tumour cellularity, the relative proportion of tumour and normal cells in a sample, affects the sensitivity of mutation detection, copy number analysis, cancer gene expression and methylation profiling. Tumour cellularity is traditionally estimated by pathological review of sectioned specimens; however this method is both subjective and prone to error due to heterogeneity within lesions and cellularity differences between the sample viewed during pathological review and tissue used for research purposes. In this paper we describe a statistical model to estimate tumour cellularity from SNP array profiles of paired tumour and normal samples using shifts in SNP allele frequency at regions of loss of heterozygosity (LOH) in the tumour. We also provide qpure, a software implementation of the method. Our experiments showed that there is a medium correlation 0.42 (-value = 0.0001) between tumor cellularity estimated by qpure and pathology review. Interestingly there is a high correlation 0.87 (-value 2.2e-16) between cellularity estimates by qpure and deep Ion Torrent sequencing of known somatic KRAS mutations; and a weaker correlation 0.32 (-value = 0.004) between IonTorrent sequencing and pathology review. This suggests that qpure may be a more accurate predictor of tumour cellularity than pathology review. qpure can be downloaded from https://sourceforge.net/projects/qpure/. PMID:23049875

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

PubMed Central

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

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

PubMed

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.

SPECIATE Version 4.5 Database Development Documentation

EPA Science Inventory

This product updated SPECIATE 4.4 with new emission profiles to address high priority Agency data gaps and to included new, more accurate emission profiles generated by research underway within and outside the Agency.

A manufacturing error measurement methodology for a rotary vector reducer cycloidal gear based on a gear measuring center

NASA Astrophysics Data System (ADS)

Li, Tianxing; Zhou, Junxiang; Deng, Xiaozhong; Li, Jubo; Xing, Chunrong; Su, Jianxin; Wang, Huiliang

2018-07-01

A manufacturing error of a cycloidal gear is the key factor affecting the transmission accuracy of a robot rotary vector (RV) reducer. A methodology is proposed to realize the digitized measurement and data processing of the cycloidal gear manufacturing error based on the gear measuring center, which can quickly and accurately measure and evaluate the manufacturing error of the cycloidal gear by using both the whole tooth profile measurement and a single tooth profile measurement. By analyzing the particularity of the cycloidal profile and its effect on the actual meshing characteristics of the RV transmission, the cycloid profile measurement strategy is planned, and the theoretical profile model and error measurement model of cycloid-pin gear transmission are established. Through the digital processing technology, the theoretical trajectory of the probe and the normal vector of the measured point are calculated. By means of precision measurement principle and error compensation theory, a mathematical model for the accurate calculation and data processing of manufacturing error is constructed, and the actual manufacturing error of the cycloidal gear is obtained by the optimization iterative solution. Finally, the measurement experiment of the cycloidal gear tooth profile is carried out on the gear measuring center and the HEXAGON coordinate measuring machine, respectively. The measurement results verify the correctness and validity of the measurement theory and method. This methodology will provide the basis for the accurate evaluation and the effective control of manufacturing precision of the cycloidal gear in a robot RV reducer.

Comprehensive evaluation of candidate reference genes for gene expression studies in Lysiphlebia japonica (Hymenoptera: Aphidiidae) using RT-qPCR.

PubMed

Gao, Xue-Ke; Zhang, Shuai; Luo, Jun-Yu; Wang, Chun-Yi; Lü, Li-Min; Zhang, Li-Juan; Zhu, Xiang-Zhen; Wang, Li; Lu, Hui; Cui, Jin-Jie

2017-12-30

Lysiphlebia japonica (Ashmead) is a predominant parasitoid of cotton-melon aphids in the fields of northern China with a proven ability to effectively control cotton aphid populations in early summer. For accurate normalization of gene expression in L. japonica using quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR), reference genes with stable gene expression patterns are essential. However, no appropriate reference genes is L. japonica have been investigated to date. In the present study, 12 selected housekeeping genes from L. japonica were cloned. We evaluated the stability of these genes under various experimental treatments by RT-qPCR using four independent (geNorm, NormFinder, BestKeeper and Delta Ct) and one comparative (RefFinder) algorithm. We identified genes showing the most stable levels of expression: DIMT, 18S rRNA, and RPL13 during different stages; AK, RPL13, and TBP among sexes; EF1A, PPI, and RPL27 in different tissues, and EF1A, RPL13, and PPI in adults fed on different diets. Moreover, the expression profile of a target gene (odorant receptor 1, OR1) studied during the developmental stages confirms the reliability of the chosen selected reference genes. This study provides for the first time a comprehensive list of suitable reference genes for gene expression studies in L. japonica and will benefit subsequent genomics and functional genomics research on this natural enemy. Copyright © 2017. Published by Elsevier B.V.

Dysregulation of miRNAs in bladder cancer: altered expression with aberrant biogenesis procedure

PubMed Central

Dong, Fan; Xu, Tianyuan; Shen, Yifan; Zhong, Shan; Chen, Shanwen; Ding, Qiang; Shen, Zhoujun

2017-01-01

Aberrant expression profiles of miRNAs are widely observed in the clinical tissue specimens and urine samples as well as the blood samples of bladder cancer patients. These profiles are closely related to the pathological features of bladder cancer, such as the tumour stage/grade, metastasis, recurrence and chemo-sensitivity. MiRNA biogenesis forms the basis of miRNA expression and function, and its dysregulation has been shown to be essential for variations in miRNA expression profiles as well as tumourigenesis and cancer progression. In this review, we summarize the up-to-date and widely reported miRNAs in bladder cancer that display significantly altered expression. We then compare the miRNA expression profiles among three different sample types (tissue, urine and blood) from patients with bladder cancer. Moreover, for the first time, we outline the dysregulated miRNA biogenesis network in bladder cancer from different levels and analyse its possible relationship with aberrant miRNA expression and the pathological characteristics of the disease. PMID:28187437

Molecular profiles of pre- and postoperative breast cancer tumours reveal differentially expressed genes.

PubMed

Riis, Margit L H; Lüders, Torben; Markert, Elke K; Haakensen, Vilde D; Nesbakken, Anne-Jorun; Kristensen, Vessela N; Bukholm, Ida R K

2012-01-01

Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology.

Molecular Profiles of Pre- and Postoperative Breast Cancer Tumours Reveal Differentially Expressed Genes

PubMed Central

Riis, Margit L. H.; Lüders, Torben; Markert, Elke K.; Haakensen, Vilde D.; Nesbakken, Anne-Jorun; Kristensen, Vessela N.; Bukholm, Ida R. K.

2012-01-01

Gene expression studies on breast cancer have generally been performed on tissue obtained at the time of surgery. In this study, we have compared the gene expression profiles in preoperative tissue (core needle biopsies) while tumor is still in its normal milieu to postoperative tissue from the same tumor obtained during surgery. Thirteen patients were included of which eleven had undergone sentinel node diagnosis procedure before operation. Microarray gene expression analysis was performed using total RNA from all the samples. Paired significance analysis of microarrays revealed 228 differently expressed genes, including several early response stress-related genes such as members of the fos and jun families as well as genes of which the expression has previously been associated with cancer. The expression profiles found in the analyses of breast cancer tissue must be evaluated with caution. Different profiles may simply be the result of differences in the surgical trauma and timing of when samples are taken and not necessarily associated with tumor biology. PMID:23227362

Expression profiles of antimicrobial peptides (AMPs) and their regulation by Relish

NASA Astrophysics Data System (ADS)

Wang, Dongdong; Li, Fuhua; Li, Shihao; Wen, Rong; Xiang, Jianhai

2012-07-01

Antimicrobial peptides (AMPs), as key immune effectors, play important roles in the innate immune system of invertebrates. Different types of AMPs, including Penaeidin, Crustin, ALF (antilipopolysaccharide factor) have been identified in different penaeid shrimp; however, systematic analyses on the function of different AMPs in shrimp responsive to different types of bacteria are very limited. In this study, we analyzed the expression profiles of AMPs in the Chinese shrimps, Fenneropenaeus chinensis, simultaneously by real-time RT-PCR (reverse transcription-polymerase chain reaction) when shrimp were challenged with Micrococcus lysodeikticus (Gram-positive, G+) or Vibrio anguillarium (Gram-negative, G-). Different AMPs showed different expression profiles when shrimp were injected with one type of bacterium, and one AMP also showed different expression profiles when shrimp were challenged with different bacteria. Furthermore, the expression of these AMPs showed temporal expression profiles, suggesting that different AMPs function coordinately in bacteria-infected shrimp. An RNA interference approach was used to study the function of the Relish transcription factor in regulating the transcription of different AMPs. The current study showed that Relish could regulate the transcription of different AMPs in shrimp. Differential expression profiles of AMPs in shrimp injected with different types of bacteria indicated that a complicated antimicrobial response network existed in shrimp. These data contribute to our understanding of immunity in shrimp and may provide a strategy for the control of disease in shrimp.

Baculovirus induced transcripts in hemocytes from Heliothis virescens

USDA-ARS?s Scientific Manuscript database

Using RNA-sequencing digital difference expression profiling methods we have assessed the gene expression profiles of hemocytes harvested from Heliothis virescens that were challenged with Helicoverpa zea single nucleopolyhedrovirus (HzSNPV). A reference transcriptome of hemocyte-expressed transcri...

Influence of in vivo growth on human glioma cell line gene expression: Convergent profiles under orthotopic conditions

PubMed Central

Camphausen, Kevin; Purow, Benjamin; Sproull, Mary; Scott, Tamalee; Ozawa, Tomoko; Deen, Dennis F.; Tofilon, Philip J.

2005-01-01

Defining the molecules that regulate tumor cell survival is an essential prerequisite for the development of targeted approaches to cancer treatment. Whereas many studies aimed at identifying such targets use human tumor cells grown in vitro or as s.c. xenografts, it is unclear whether such experimental models replicate the phenotype of the in situ tumor cell. To begin addressing this issue, we have used microarray analysis to define the gene expression profile of two human glioma cell lines (U251 and U87) when grown in vitro and in vivo as s.c. or as intracerebral (i.c.) xenografts. For each cell line, the gene expression profile generated from tissue culture was significantly different from that generated from the s.c. tumor, which was significantly different from those grown i.c. The disparity between the i.c gene expression profiles and those generated from s.c. xenografts suggests that whereas an in vivo growth environment modulates gene expression, orthotopic growth conditions induce a different set of modifications. In this study the U251 and U87 gene expression profiles generated under the three growth conditions were also compared. As expected, the profiles of the two glioma cell lines were significantly different when grown as monolayer cultures. However, the glioma cell lines had similar gene expression profiles when grown i.c. These results suggest that tumor cell gene expression, and thus phenotype, as defined in vitro is affected not only by in vivo growth but also by orthotopic growth, which may have implications regarding the identification of relevant targets for cancer therapy. PMID:15928080

Preanalytical variables and phosphoepitope expression in FFPE tissue: quantitative epitope assessment after variable cold ischemic time.

PubMed

Vassilakopoulou, Maria; Parisi, Fabio; Siddiqui, Summar; England, Allison M; Zarella, Elizabeth R; Anagnostou, Valsamo; Kluger, Yuval; Hicks, David G; Rimm, David L; Neumeister, Veronique M

2015-03-01

Individualized targeted therapies for cancer patients require accurate and reproducible assessment of biomarkers to be able to plan treatment accordingly. Recent studies have shown highly variable effects of preanalytical variables on gene expression profiling and protein levels of different tissue types. Several publications have described protein degradation of tissue samples as a direct result of delay of formalin fixation of the tissue. Phosphorylated proteins are more labile and epitope degradation can happen within 30 min of cold ischemic time. To address this issue, we evaluated the change in antigenicity of a series of phosphoproteins in paraffin-embedded samples from breast tumors as a function of time to formalin fixation. A tissue microarray consisting of 93 breast cancer specimens with documented time-to-fixation was used to evaluate changes in antigenicity of 12 phosphoepitopes frequently used in research settings as a function of cold ischemic time. Analysis was performed in a quantitative manner using the AQUA technology for quantitative immunofluorescence. For each marker, least squares univariate linear regression was performed and confidence intervals were computed using bootstrapping. The majority of the epitopes tested revealed changes in expression levels with increasing time to formalin fixation. Some phosphorylated proteins, such as phospho-HSP27 and phospho-S6 RP, involved in post-translational modification and stress response pathways increased in expression or phosphorylation levels. Others (like phospho-AKT, phosphor-ERK1/2, phospho-Tyrosine, phospho-MET, and others) are quite labile and loss of antigenicity can be reported within 1-2 h of cold ischemic time. Therefore specimen collection should be closely monitored and subjected to quality control measures to ensure accurate measurement of these epitopes. However, a few phosphoepitopes (like phospho-JAK2 and phospho-ER) are sufficiently robust for routine usage in companion diagnostic testing.

Model-based redesign of global transcription regulation

PubMed Central

Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso

2009-01-01

Synthetic biology aims to the design or redesign of biological systems. In particular, one possible goal could be the rewiring of the transcription regulation network by exchanging the endogenous promoters. To achieve this objective, we have adapted current methods to the inference of a model based on ordinary differential equations that is able to predict the network response after a major change in its topology. Our procedure utilizes microarray data for training. We have experimentally validated our inferred global regulatory model in Escherichia coli by predicting transcriptomic profiles under new perturbations. We have also tested our methodology in silico by providing accurate predictions of the underlying networks from expression data generated with artificial genomes. In addition, we have shown the predictive power of our methodology by obtaining the gene profile in experimental redesigns of the E. coli genome, where rewiring the transcriptional network by means of knockouts of master regulators or by upregulating transcription factors controlled by different promoters. Our approach is compatible with most network inference methods, allowing to explore computationally future genome-wide redesign experiments in synthetic biology. PMID:19188257

Schizophrenia proteomics: biomarkers on the path to laboratory medicine?

PubMed Central

Lakhan, Shaheen Emmanuel

2006-01-01

Over two million Americans are afflicted with schizophrenia, a debilitating mental health disorder with a unique symptomatic and epidemiological profile. Genomics studies have hinted towards candidate schizophrenia susceptibility chromosomal loci and genes. Modern proteomic tools, particularly mass spectrometry and expression scanning, aim to identify both pathogenic-revealing and diagnostically significant biomarkers. Only a few studies on basic proteomics have been conducted for psychiatric disorders relative to the plethora of cancer specific experiments. One such proteomic utility enables the discovery of proteins and biological marker fingerprinting profiling techniques (SELDI-TOF-MS), and then subjects them to tandem mass spectrometric fragmentation and de novo protein sequencing (MALDI-TOF/TOF-MS) for the accurate identification and characterization of the proteins. Such utilities can explain the pathogenesis of neuro-psychiatric disease, provide more objective testing methods, and further demonstrate a biological basis to mental illness. Although clinical proteomics in schizophrenia have yet to reveal a biomarker with diagnostic specificity, methods that better characterize the disorder using endophenotypes can advance findings. Schizophrenia biomarkers could potentially revolutionize its psychopharmacology, changing it into a more hypothesis and genomic/proteomic-driven science. PMID:16846510

Pilot study of facial soft tissue thickness differences among three skeletal classes in Japanese females.

PubMed

Utsuno, Hajime; Kageyama, Toru; Uchida, Keiichi; Yoshino, Mineo; Oohigashi, Shina; Miyazawa, Hiroo; Inoue, Katsuhiro

2010-02-25

Facial reconstruction is a technique used in forensic anthropology to estimate the appearance of the antemortem face from unknown human skeletal remains. This requires accurate skull assessment (for variables such as age, sex, and race) and soft tissue thickness data. However, the skull can provide only limited information, and further data are needed to reconstruct the face. The authors herein obtained further information from the skull in order to reconstruct the face more accurately. Skulls can be classified into three facial types on the basis of orthodontic skeletal classes (namely, straight facial profile, type I, convex facial profile, type II, and concave facial profile, type III). This concept was applied to facial tissue measurement and soft tissue depth was compared in each skeletal class in a Japanese female population. Differences of soft tissue depth between skeletal classes were observed, and this information may enable more accurate reconstruction than sex-specific depth alone. 2009 Elsevier Ireland Ltd. All rights reserved.

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

PubMed Central

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

2015-01-01

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

s -wave scattering length of a Gaussian potential

NASA Astrophysics Data System (ADS)

Jeszenszki, Peter; Cherny, Alexander Yu.; Brand, Joachim

2018-04-01

We provide accurate expressions for the s -wave scattering length for a Gaussian potential well in one, two, and three spatial dimensions. The Gaussian potential is widely used as a pseudopotential in the theoretical description of ultracold-atomic gases, where the s -wave scattering length is a physically relevant parameter. We first describe a numerical procedure to compute the value of the s -wave scattering length from the parameters of the Gaussian, but find that its accuracy is limited in the vicinity of singularities that result from the formation of new bound states. We then derive simple analytical expressions that capture the correct asymptotic behavior of the s -wave scattering length near the bound states. Expressions that are increasingly accurate in wide parameter regimes are found by a hierarchy of approximations that capture an increasing number of bound states. The small number of numerical coefficients that enter these expressions is determined from accurate numerical calculations. The approximate formulas combine the advantages of the numerical and approximate expressions, yielding an accurate and simple description from the weakly to the strongly interacting limit.

Comparative Analysis of the miRNome of Bovine Milk Fat, Whey and Cells.

PubMed

Li, Ran; Dudemaine, Pier-Luc; Zhao, Xin; Lei, Chuzhao; Ibeagha-Awemu, Eveline Mengwi

2016-01-01

Abundant miRNAs have been identified in milk and mammary gland tissues of different species. Typically, RNA in milk can be extracted from different fractions including fat, whey and cells and the mRNA transcriptome of milk could serve as an indicator of the transcriptome of mammary gland tissue. However, it has not been adequately validated if the miRNA transcriptome of any milk fraction could be representative of that of mammary gland tissue. The objectives of this study were to (1) characterize the miRNA expression spectra from three milk fractions- fat, whey and cells; (2) compare miRNome profiles of milk fractions (fat, whey and cells) with mammary gland tissue miRNome, and (3) determine which milk fraction miRNome profile could be a better representative of the miRNome profile of mammary gland tissue. Milk from four healthy Canadian Holstein cows in mid lactation was collected and fractionated. Total RNA extracted from each fraction was used for library preparation followed by small RNA sequencing. In addition, miRNA transcripts of mammary gland tissues from twelve Holstein cows in our previous study were used to compare our data. We identified 210, 200 and 249 known miRNAs from milk fat, whey and cells, respectively, with 188 universally expressed in the three fractions. In addition, 33, 31 and 36 novel miRNAs from milk fat, whey and cells were identified, with 28 common in the three fractions. Among 20 most highly expressed miRNAs in each fraction, 14 were expressed in common and 11 were further shared with mammary gland tissue. The three milk fractions demonstrated a clear separation from each other using a hierarchical cluster analysis with milk fat and whey being most closely related. The miRNome correlation between milk fat and mammary gland tissue (rmean = 0.866) was significantly higher than the other two pairs (p < 0.01), whey/mammary gland tissue (rmean = 0.755) and milk cell/mammary gland tissue (rmean = 0.75), suggesting that milk fat could be an alternative non-invasive source of RNA in assessing miRNA activities in bovine mammary gland. Predicted target genes (1802) of 14 highly expressed miRNAs in milk fractions were enriched in fundamental cellular functions, infection, organ and tissue development. Furthermore, some miRNAs were highly enriched (FDR <0.05) in milk whey (3), cells (11) and mammary gland tissue (14) suggesting specific regulatory functions in the various fractions. In conclusion, we have obtained a comprehensive miRNA profile of the different milk fractions using high throughput sequencing. Our comparative analysis showed that miRNAs from milk fat accurately portrayed the miRNome of mammary gland tissue. Functional annotation of the top expressed miRNAs in milk confirmed their critical regulatory roles in mammary gland functions and potentially to milk recipients.

Comparative Analysis of the miRNome of Bovine Milk Fat, Whey and Cells

PubMed Central

Li, Ran; Dudemaine, Pier-Luc; Zhao, Xin; Lei, Chuzhao; Ibeagha-Awemu, Eveline Mengwi

2016-01-01

Abundant miRNAs have been identified in milk and mammary gland tissues of different species. Typically, RNA in milk can be extracted from different fractions including fat, whey and cells and the mRNA transcriptome of milk could serve as an indicator of the transcriptome of mammary gland tissue. However, it has not been adequately validated if the miRNA transcriptome of any milk fraction could be representative of that of mammary gland tissue. The objectives of this study were to (1) characterize the miRNA expression spectra from three milk fractions- fat, whey and cells; (2) compare miRNome profiles of milk fractions (fat, whey and cells) with mammary gland tissue miRNome, and (3) determine which milk fraction miRNome profile could be a better representative of the miRNome profile of mammary gland tissue. Milk from four healthy Canadian Holstein cows in mid lactation was collected and fractionated. Total RNA extracted from each fraction was used for library preparation followed by small RNA sequencing. In addition, miRNA transcripts of mammary gland tissues from twelve Holstein cows in our previous study were used to compare our data. We identified 210, 200 and 249 known miRNAs from milk fat, whey and cells, respectively, with 188 universally expressed in the three fractions. In addition, 33, 31 and 36 novel miRNAs from milk fat, whey and cells were identified, with 28 common in the three fractions. Among 20 most highly expressed miRNAs in each fraction, 14 were expressed in common and 11 were further shared with mammary gland tissue. The three milk fractions demonstrated a clear separation from each other using a hierarchical cluster analysis with milk fat and whey being most closely related. The miRNome correlation between milk fat and mammary gland tissue (rmean = 0.866) was significantly higher than the other two pairs (p < 0.01), whey/mammary gland tissue (rmean = 0.755) and milk cell/mammary gland tissue (rmean = 0.75), suggesting that milk fat could be an alternative non-invasive source of RNA in assessing miRNA activities in bovine mammary gland. Predicted target genes (1802) of 14 highly expressed miRNAs in milk fractions were enriched in fundamental cellular functions, infection, organ and tissue development. Furthermore, some miRNAs were highly enriched (FDR <0.05) in milk whey (3), cells (11) and mammary gland tissue (14) suggesting specific regulatory functions in the various fractions. In conclusion, we have obtained a comprehensive miRNA profile of the different milk fractions using high throughput sequencing. Our comparative analysis showed that miRNAs from milk fat accurately portrayed the miRNome of mammary gland tissue. Functional annotation of the top expressed miRNAs in milk confirmed their critical regulatory roles in mammary gland functions and potentially to milk recipients. PMID:27100870

Integrated analysis of long noncoding RNA and mRNA expression profile in children with obesity by microarray analysis.

PubMed

Liu, Yuesheng; Ji, Yuqiang; Li, Min; Wang, Min; Yi, Xiaoqing; Yin, Chunyan; Wang, Sisi; Zhang, Meizhen; Zhao, Zhao; Xiao, Yanfeng

2018-06-08

Long noncoding RNAs (lncRNAs) have an important role in adipose tissue function and energy metabolism homeostasis, and abnormalities may lead to obesity. To investigate whether lncRNAs are involved in childhood obesity, we investigated the differential expression profile of lncRNAs in obese children compared with non-obese children. A total number of 1268 differentially expressed lncRNAs and 1085 differentially expressed mRNAs were identified. Gene Ontology (GO) and pathway analysis revealed that these lncRNAs were involved in varied biological processes, including the inflammatory response, lipid metabolic process, osteoclast differentiation and fatty acid metabolism. In addition, the lncRNA-mRNA co-expression network and the protein-protein interaction (PPI) network were constructed to identify hub regulatory lncRNAs and genes based on the microarray expression profiles. This study for the first time identifies an expression profile of differentially expressed lncRNAs in obese children and indicated hub lncRNA RP11-20G13.3 attenuated adipogenesis of preadipocytes, which is conducive to the search for new diagnostic and therapeutic strategies of childhood obesity.

Gene Expression Profiling Predicts the Development of Oral Cancer

PubMed Central

Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

2011-01-01

Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635

Accurate assessment and identification of naturally occurring cellular cobalamins.

PubMed

Hannibal, Luciana; Axhemi, Armend; Glushchenko, Alla V; Moreira, Edward S; Brasch, Nicola E; Jacobsen, Donald W

2008-01-01

Accurate assessment of cobalamin profiles in human serum, cells, and tissues may have clinical diagnostic value. However, non-alkyl forms of cobalamin undergo beta-axial ligand exchange reactions during extraction, which leads to inaccurate profiles having little or no diagnostic value. Experiments were designed to: 1) assess beta-axial ligand exchange chemistry during the extraction and isolation of cobalamins from cultured bovine aortic endothelial cells, human foreskin fibroblasts, and human hepatoma HepG2 cells, and 2) to establish extraction conditions that would provide a more accurate assessment of endogenous forms containing both exchangeable and non-exchangeable beta-axial ligands. The cobalamin profile of cells grown in the presence of [ 57Co]-cyanocobalamin as a source of vitamin B12 shows that the following derivatives are present: [ 57Co]-aquacobalamin, [ 57Co]-glutathionylcobalamin, [ 57Co]-sulfitocobalamin, [ 57Co]-cyanocobalamin, [ 57Co]-adenosylcobalamin, [ 57Co]-methylcobalamin, as well as other yet unidentified corrinoids. When the extraction is performed in the presence of excess cold aquacobalaminacting as a scavenger cobalamin (i.e. "cold trapping"), the recovery of both [ 57Co]-glutathionylcobalamin and [ 57Co]-sulfitocobalamin decreases to low but consistent levels. In contrasts, the [ 57Co]-nitrocobalamin observed in the extracts prepared without excess aquacobalamin is undetected in extracts prepared with cold trapping. This demonstrates that beta-ligand exchange occur with non-covalently bound beta-ligands. The exception to this observation is cyanocobalamin with a non-exchangeable CN- group. It is now possible to obtain accurate profiles of cellular cobalamin.

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

Yang, K; Li, X; Liu, B

Purpose: To accurately measure CT bow-tie profiles from various manufacturers and to provide non-proprietary information for CT system modeling. Methods: A GOS-based linear detector (0.8 mm per pixel and 51.2 cm in length) with a fast data sampling speed (0.24 ms/sample) was used to measure the relative profiles of bow-tie filters from a collection of eight CT scanners by three different vendors, GE (LS Xtra, LS VCT, Discovery HD750), Siemens (Sensation 64, Edge, Flash, Force), and Philips (iBrilliance 256). The linear detector was first calibrated for its energy response within typical CT beam quality ranges and compared with an ionmore » chamber and analytical modeling (SPECTRA and TASMIP). A geometrical calibration process was developed to determine key parameters including the distance from the focal spot to the linear detector, the angular increment of the gantry at each data sampling, the location of the central x-ray on the linear detector, and the angular response of the detector pixel. Measurements were performed under axial-scan modes for most representative bow-tie filters and kV selections from each scanner. Bow-tie profiles were determined by re-binning the measured rotational data with an angular accuracy of 0.1 degree using the calibrated geometrical parameters. Results: The linear detector demonstrated an energy response as a solid state detector, which is close to the CT imaging detector. The geometrical calibration was proven to be sufficiently accurate (< 1mm in error for distances >550 mm) and the bow-tie profiles measured from rotational mode matched closely to those from the gantry-stationary mode. Accurate profiles were determined for a total of 21 bow-tie filters and 83 filter/kV combinations from the abovementioned scanner models. Conclusion: A new improved approach of CT bow-tie measurement was proposed and accurate bow-tie profiles were provided for a broad list of CT scanner models.« less

Integrated lipidomics and transcriptomic analysis of peripheral blood reveals significantly enriched pathways in type 2 diabetes mellitus.

PubMed

Zhao, Chen; Mao, Jinghe; Ai, Junmei; Shenwu, Ming; Shi, Tieliu; Zhang, Daqing; Wang, Xiaonan; Wang, Yunliang; Deng, Youping

2013-01-01

Insulin resistance is a key element in the pathogenesis of type 2 diabetes mellitus. Plasma free fatty acids were assumed to mediate the insulin resistance, while the relationship between lipid and glucose disposal remains to be demonstrated across liver, skeletal muscle and blood. We profiled both lipidomics and gene expression of 144 total peripheral blood samples, 84 from patients with T2D and 60 from healthy controls. Then, factor and partial least squares models were used to perform a combined analysis of lipidomics and gene expression profiles to uncover the bioprocesses that are associated with lipidomic profiles in type 2 diabetes. According to factor analysis of the lipidomic profile, several species of lipids were found to be correlated with different phenotypes, including diabetes-related C23:2CE, C23:3CE, C23:4CE, ePE36:4, ePE36:5, ePE36:6; race-related (African-American) PI36:1; and sex-related PE34:1 and LPC18:2. The major variance of gene expression profile was not caused by known factors and no significant difference can be directly derived from differential gene expression profile. However, the combination of lipidomic and gene expression analyses allows us to reveal the correlation between the altered lipid profile with significantly enriched pathways, such as one carbon pool by folate, arachidonic acid metabolism, insulin signaling pathway, amino sugar and nucleotide sugar metabolism, propanoate metabolism, and starch and sucrose metabolism. The genes in these pathways showed a good capability to classify diabetes samples. Combined analysis of gene expression and lipidomic profiling reveals type 2 diabetes-associated lipid species and enriched biological pathways in peripheral blood, while gene expression profile does not show direct correlation. Our findings provide a new clue to better understand the mechanism of disordered lipid metabolism in association with type 2 diabetes.

Molecular subtypes of osteosarcoma identified by reducing tumor heterogeneity through an interspecies comparative approach

PubMed Central

Scott, Milcah C.; Sarver, Aaron L.; Gavin, Katherine J.; Thayanithy, Venugopal; Getzy, David M.; Newman, Robert A.; Cutter, Gary R.; Lindblad-Toh, Kerstin; Kisseberth, William C.; Hunter, Lawrence E.; Subramanian, Subbaya; Breen, Matthew; Modiano, Jaime F.

2011-01-01

The heterogeneous and chaotic nature of osteosarcoma has confounded accurate molecular classification, prognosis, and prediction for this tumor. The occurrence of spontaneous osteosarcoma is largely confined to humans and dogs. While the clinical features are remarkably similar in both species, the organization of dogs into defined breeds provides a more homogeneous genetic background that may increase the likelihood to uncover molecular subtypes for this complex disease. We thus hypothesized that molecular profiles derived from canine osteosarcoma would aid in molecular subclassification of this disease when applied to humans. To test the hypothesis, we performed genome wide gene expression profiling in a cohort of dogs with osteosarcoma, primarily from high-risk breeds. To further reduce inter-sample heterogeneity, we assessed tumor-intrinsic properties through use of an extensive panel of osteosarcoma-derived cell lines. We observed strong differential gene expression that segregated samples into two groups with differential survival probabilities. Groupings were characterized by the inversely correlated expression of genes associated with G2/M transition and DNA damage checkpoint and microenvironment-interaction categories. This signature was preserved in data from whole tumor samples of three independent dog osteosarcoma cohorts, with stratification into the two expected groups. Significantly, this restricted signature partially overlapped a previously defined, predictive signature for soft tissue sarcomas, and it unmasked orthologous molecular subtypes and their corresponding natural histories in five independent data sets from human patients with osteosarcoma. Our results indicate that the narrower genetic diversity of dogs can be utilized to group complex human osteosarcoma into biologically and clinically relevant molecular subtypes. This in turn may enhance prognosis and prediction, and identify relevant therapeutic targets. PMID:21621658

Divergence between motoneurons: gene expression profiling provides a molecular characterization of functionally discrete somatic and autonomic motoneurons

PubMed Central

Cui, Dapeng; Dougherty, Kimberly J.; Machacek, David W.; Sawchuk, Michael; Hochman, Shawn; Baro, Deborah J.

2009-01-01

Studies in the developing spinal cord suggest that different motoneuron (MN) cell types express very different genetic programs, but the degree to which adult programs differ is unknown. To compare genetic programs between adult MN columnar cell types, we used laser capture micro-dissection (LCM) and Affymetrix microarrays to create expression profiles for three columnar cell types: lateral and medial MNs from lumbar segments and sympathetic preganglionic motoneurons located in the thoracic intermediolateral nucleus. A comparison of the three expression profiles indicated that ~7% (813/11,552) of the genes showed significant differences in their expression levels. The largest differences were observed between sympathetic preganglionic MNs and the lateral motor column, with 6% (706/11,552) of the genes being differentially expressed. Significant differences in expression were observed for 1.8% (207/11,552) of the genes when comparing sympathetic preganglionic MNs with the medial motor column. Lateral and medial MNs showed the least divergence, with 1.3% (150/11,552) of the genes being differentially expressed. These data indicate that the amount of divergence in expression profiles between identified columnar MNs does not strictly correlate with divergence of function as defined by innervation patterns (somatic/muscle vs. autonomic/viscera). Classification of the differentially expressed genes with regard to function showed that they underpin all fundamental cell systems and processes, although most differentially expressed genes encode proteins involved in signal transduction. Mining the expression profiles to examine transcription factors essential for MN development suggested that many of the same transcription factors participatein combinatorial codes in embryonic and adult neurons, but patterns of expression change significantly. PMID:16317082

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

Genomic Expression Patterns in Menstrually-Related Migraine in Adolescents

PubMed Central

Hershey, Andrew; Horn, Paul; Kabbouche, Marielle; O'Brien, Hope; Powers, Scott

2011-01-01

Background Exacerbation of migraine with menses is common in adolescent girls and women with migraine, occurring in up to 60% of females with migraine. These migraines are oftentimes longer and more disabling and may be related to estrogen levels and hormonal fluctuations. Objective This study identifies the unique genomic expression pattern of menstrually-related migraine (MRM) in comparison to migraine occurring outside the menstrual period and headache free controls. Methods Whole blood samples were obtained from female subjects having an acute migraine during their menstrual period (MRM) or outside of their menstrual period (nonMRM) and controls (C) – females having a menstrual period without any history of headache. The mRNA was isolated from these samples and genomic profile was assessed. Affymetrix Human Exon ST 1.0 arrays were used to examine the genomic expression pattern differences between these three groups. Results Blood genomic expression patterns were obtained on 56 subjects (MRM = 18, nonMRM = 18 and C = 20). Unique genomic expression patterns were observed for both MRM and nonMRM. For MRM, 77 genes were identified that were unique to MRM, while 61 genes were commonly expressed for MRM and nonMRM and 127 genes appeared to have a unique expression pattern for nonMRM. In addition, there were 279 genes that differentially expressed for MRM compared to nonMRM that were not differentially expressed for nonMRM. Gene ontology of these samples indicated many of these groups of genes were functionally related and included categories of immunomodulation/inflammation, mitochondrial function and DNA homeostasis. Conclusions Blood genomic patterns can accurately differentiate MRM from nonMRM. These results indicate that MRM involves a unique molecular biology pathway that can be identified with a specific biomarker and suggest that individuals with MRM have a different underlying genetic etiology. PMID:22220971

Automated Detection of Knickpoints and Knickzones Across Transient Landscapes

NASA Astrophysics Data System (ADS)

Gailleton, B.; Mudd, S. M.; Clubb, F. J.

2017-12-01

Mountainous regions are ubiquitously dissected by river channels, which transmit climate and tectonic signals to the rest of the landscape by adjusting their long profiles. Fluvial response to allogenic forcing is often expressed through the upstream propagation of steepened reaches, referred to as knickpoints or knickzones. The identification and analysis of these steepened reaches has numerous applications in geomorphology, such as modelling long-term landscape evolution, understanding controls on fluvial incision, and constraining tectonic uplift histories. Traditionally, the identification of knickpoints or knickzones from fluvial profiles requires manual selection or calibration. This process is both time-consuming and subjective, as different workers may select different steepened reaches within the profile. We propose an objective, statistically-based method to systematically pick knickpoints/knickzones on a landscape scale using an outlier-detection algorithm. Our method integrates river profiles normalised by drainage area (Chi, using the approach of Perron and Royden, 2013), then separates the chi-elevation plots into a series of transient segments using the method of Mudd et al. (2014). This method allows the systematic detection of knickpoints across a DEM, regardless of size, using a high-performance algorithm implemented in the open-source Edinburgh Land Surface Dynamics Topographic Tools (LSDTopoTools) software package. After initial knickpoint identification, outliers are selected using several sorting and binning methods based on the Median Absolute Deviation, to avoid the influence sample size. We test our method on a series of DEMs and grid resolutions, and show that our method consistently identifies accurate knickpoint locations across each landscape tested.

Face in profile view reduces perceived facial expression intensity: an eye-tracking study.

PubMed

Guo, Kun; Shaw, Heather

2015-02-01

Recent studies measuring the facial expressions of emotion have focused primarily on the perception of frontal face images. As we frequently encounter expressive faces from different viewing angles, having a mechanism which allows invariant expression perception would be advantageous to our social interactions. Although a couple of studies have indicated comparable expression categorization accuracy across viewpoints, it is unknown how perceived expression intensity and associated gaze behaviour change across viewing angles. Differences could arise because diagnostic cues from local facial features for decoding expressions could vary with viewpoints. Here we manipulated orientation of faces (frontal, mid-profile, and profile view) displaying six common facial expressions of emotion, and measured participants' expression categorization accuracy, perceived expression intensity and associated gaze patterns. In comparison with frontal faces, profile faces slightly reduced identification rates for disgust and sad expressions, but significantly decreased perceived intensity for all tested expressions. Although quantitatively viewpoint had expression-specific influence on the proportion of fixations directed at local facial features, the qualitative gaze distribution within facial features (e.g., the eyes tended to attract the highest proportion of fixations, followed by the nose and then the mouth region) was independent of viewpoint and expression type. Our results suggest that the viewpoint-invariant facial expression processing is categorical perception, which could be linked to a viewpoint-invariant holistic gaze strategy for extracting expressive facial cues. Copyright © 2014 Elsevier B.V. All rights reserved.

Radar - ESRL Wind Profiler with RASS, Wasco Airport - Derived Data

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

McCaffrey, Katherine

Profiles of turbulence dissipation rate for 15-minute intervals, time-stamped at the beginning of the 15-minute period, during the final 30 minutes of each hour. During that time, the 915-MHz wind profiling radar was in an optimized configuration with a vertically pointing beam only for measuring accurate spectral widths of vertical velocity. A bias-corrected dissipation rate also was profiled (described in McCaffrey et al. 2017). Hourly files contain two 15-minute profiles.

New signal processing technique for density profile reconstruction using reflectometry.

PubMed

Clairet, F; Ricaud, B; Briolle, F; Heuraux, S; Bottereau, C

2011-08-01

Reflectometry profile measurement requires an accurate determination of the plasma reflected signal. Along with a good resolution and a high signal to noise ratio of the phase measurement, adequate data analysis is required. A new data processing based on time-frequency tomographic representation is used. It provides a clearer separation between multiple components and improves isolation of the relevant signals. In this paper, this data processing technique is applied to two sets of signals coming from two different reflectometer devices used on the Tore Supra tokamak. For the standard density profile reflectometry, it improves the initialization process and its reliability, providing a more accurate profile determination in the far scrape-off layer with density measurements as low as 10(16) m(-1). For a second reflectometer, which provides measurements in front of a lower hybrid launcher, this method improves the separation of the relevant plasma signal from multi-reflection processes due to the proximity of the plasma.

A method to identify differential expression profiles of time-course gene data with Fourier transformation

PubMed Central

2013-01-01

Background Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. Results This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization. The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Conclusions Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics. PMID:24134721

Loss of ATRX, associated with DNA methylation pattern of chromosome end, impacted biological behaviors of astrocytic tumors

PubMed Central

Zhang, Wei; Yang, Pei; Zhang, Chuanbao; Li, Mingyang; Yao, Kun; Wang, Hongjun; Li, Qingbin; Jiang, Chuanlu; Jiang, Tao

2015-01-01

Loss of ATRX leads to epigenetic alterations, including abnormal levels of DNA methylation at repetitive elements such as telomeres in murine cells. We conducted an extensive DNA methylation and mRNA expression profile study on a cohort of 82 patients with astrocytic tumors to study whether ATRX expression was associated with DNA methylation level in astrocytic tumors and in which cellular functions it participated. We observed that astrocytic tumors with lower ATRX expression harbored higher DNA methylation level at chromatin end and astrocytic tumors with ATRX-low had distinct gene expression profile and DNA methylation profile compared with ATRX-high tumors. Then, we uncovered that several ATRX associated biological functions in the DNA methylation and mRNA expression profile (GEP), including apoptotic process, DNA-dependent positive regulation of transcription, chromatin modification, and observed that ATRX expression was companied by MGMT methylation and expression. We also found that loss of ATRX caused by siRNA induced apoptotic cells increasing, reduced tumor cell proliferation and repressed the cell migration in glioma cells. Our results showed ATRX-related regulatory functions of the combined profiles from DNA methylation and mRNA expression in astrocytic tumors, and delineated that loss of ATRX impacted biological behaviors of astrocytic tumor cells, providing important resources for future dissection of ATRX role in glioma. PMID:25971279

Loss of ATRX, associated with DNA methylation pattern of chromosome end, impacted biological behaviors of astrocytic tumors.

PubMed

Cai, Jinquan; Chen, Jing; Zhang, Wei; Yang, Pei; Zhang, Chuanbao; Li, Mingyang; Yao, Kun; Wang, Hongjun; Li, Qingbin; Jiang, Chuanlu; Jiang, Tao

2015-07-20

Loss of ATRX leads to epigenetic alterations, including abnormal levels of DNA methylation at repetitive elements such as telomeres in murine cells. We conducted an extensive DNA methylation and mRNA expression profile study on a cohort of 82 patients with astrocytic tumors to study whether ATRX expression was associated with DNA methylation level in astrocytic tumors and in which cellular functions it participated. We observed that astrocytic tumors with lower ATRX expression harbored higher DNA methylation level at chromatin end and astrocytic tumors with ATRX-low had distinct gene expression profile and DNA methylation profile compared with ATRX-high tumors. Then, we uncovered that several ATRX associated biological functions in the DNA methylation and mRNA expression profile (GEP), including apoptotic process, DNA-dependent positive regulation of transcription, chromatin modification, and observed that ATRX expression was companied by MGMT methylation and expression. We also found that loss of ATRX caused by siRNA induced apoptotic cells increasing, reduced tumor cell proliferation and repressed the cell migration in glioma cells. Our results showed ATRX-related regulatory functions of the combined profiles from DNA methylation and mRNA expression in astrocytic tumors, and delineated that loss of ATRX impacted biological behaviors of astrocytic tumor cells, providing important resources for future dissection of ATRX role in glioma.

A microcosm of musical expression: II. Quantitative analysis of pianists' dynamics in the initial measures of Chopin's Etude in E major.

PubMed

Repp, B H

1999-03-01

Patterns of expressive dynamics were measured in bars 1-5 of 115 commercially recorded performances of Chopin's Etude in E major, op. 10, No. 3. The grand average pattern (or dynamic profile) was representative of many performances and highly similar to the average dynamic profile of a group of advanced student performances, which suggests a widely shared central norm of expressive dynamics. The individual dynamic profiles were subjected to principal components analysis, which yielded Varimax-rotated components, each representing a different, nonstandard dynamic profile associated with a small subset of performances. Most performances had dynamic patterns resembling a mixture of several components, and no clustering of of performances into distinct groups was apparent. Some weak relationships of dynamic profiles with sociocultural variables were found, most notably a tendency of female pianists to exhibit a greater dynamic range in the melody. Within the melody, there were no significant relationships between expressive timing [Repp, J. Acoust. Soc. Am. 104, 1085-1100 (1998)] and expressive dynamics. These two important dimensions seemed to be controlled independently at this local level and thus offer the artist many degrees of freedom in giving a melody expressive shape.

Medroxyprogesterone acetate-treated human, primary endometrial epithelial cells reveal unique gene expression signature linked to innate immunity and HIV-1 susceptibility.

PubMed

Woods, Matthew W; Zahoor, Muhammad Atif; Dizzell, Sara; Verschoor, Chris P; Kaushic, Charu

2018-01-01

Medroxyprogesterone acetate (MPA), a progestin-based hormonal contraceptive designed to mimic progesterone, has been linked to increased human immunodeficiency virus (HIV-1) susceptibility. Genital epithelial cells (GECs) form the mucosal lining of the female genital tract (FGT) and provide the first line of protection against HIV-1. The impact of endogenous sex hormones or MPA on the gene expression profile of GECs has not been comprehensively documented. Using microarray analysis, we characterized the transcriptional profile of primary endometrial epithelial cells grown in physiological levels of E2, P4, and MPA. Each hormone treatment altered the gene expression profile of GECs in a unique manner. Interestingly, although MPA is a progestogen, the gene expression profile induced by it was distinct from P4. MPA increased gene expression of genes related to inflammation and cholesterol synthesis linked to innate immunity and HIV-1 susceptibility. The analysis of gene expression profiles provides insights into the effects of sex hormones and MPA on GECs and allows us to posit possible mechanisms of the MPA-mediated increase in HIV-1 acquisition. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

DEVELOPMENT OF PROTEIN PROFILE TECHNOLOGY TO EVALUATE ECOLOGICAL EFFECTS OF ENVIRONMENTAL CHEMICALS USING A SMALL FISH MODEL

EPA Science Inventory

The rationale for this research is: i) Protein expression changes with life stage, disease, tissue type and environmental stressors; ii) Technology allows rapid analysis of large numbers of proteins to provide protein expression profiles; iii) Protein profiles are used as specifi...

Network Modeling Reveals Prevalent Negative Regulatory Relationships between Signaling Sectors in Arabidopsis Immune Signaling

PubMed Central

Sato, Masanao; Tsuda, Kenichi; Wang, Lin; Coller, John; Watanabe, Yuichiro; Glazebrook, Jane; Katagiri, Fumiaki

2010-01-01

Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2). This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i) the components of the network are highly interconnected; and (ii) negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a “sector-switching” network, which effectively balances two apparently conflicting demands, robustness against pathogenic perturbations and moderation of negative impacts of immune responses on plant fitness. PMID:20661428

A functional glycoprotein competitive recognition and signal amplification strategy for carbohydrate-protein interaction profiling and cell surface carbohydrate expression evaluation

NASA Astrophysics Data System (ADS)

Wang, Yangzhong; Chen, Zhuhai; Liu, Yang; Li, Jinghong

2013-07-01

A simple and sensitive carbohydrate biosensor has been suggested as a potential tool for accurate analysis of cell surface carbohydrate expression as well as carbohydrate-based therapeutics for a variety of diseases and infections. In this work, a sensitive biosensor for carbohydrate-lectin profiling and in situ cell surface carbohydrate expression was designed by taking advantage of a functional glycoprotein of glucose oxidase acting as both a multivalent recognition unit and a signal amplification probe. Combining the gold nanoparticle catalyzed luminol electrogenerated chemiluminescence and nanocarrier for active biomolecules, the number of cell surface carbohydrate groups could be conveniently read out. The apparent dissociation constant between GOx@Au probes and Con A was detected to be 1.64 nM and was approximately 5 orders of magnitude smaller than that of mannose and Con A, which would arise from the multivalent effect between the probe and Con A. Both glycoproteins and gold nanoparticles contribute to the high affinity between carbohydrates and lectin. The as-proposed biosensor exhibits excellent analytical performance towards the cytosensing of K562 cells with a detection limit of 18 cells, and the mannose moieties on a single K562 cell were determined to be 1.8 × 1010. The biosensor can also act as a useful tool for antibacterial drug screening and mechanism investigation. This strategy integrates the excellent biocompatibility and multivalent recognition of glycoproteins as well as the significant enzymatic catalysis and gold nanoparticle signal amplification, and avoids the cell pretreatment and labelling process. This would contribute to the glycomic analysis and the understanding of complex native glycan-related biological processes.A simple and sensitive carbohydrate biosensor has been suggested as a potential tool for accurate analysis of cell surface carbohydrate expression as well as carbohydrate-based therapeutics for a variety of diseases and infections. In this work, a sensitive biosensor for carbohydrate-lectin profiling and in situ cell surface carbohydrate expression was designed by taking advantage of a functional glycoprotein of glucose oxidase acting as both a multivalent recognition unit and a signal amplification probe. Combining the gold nanoparticle catalyzed luminol electrogenerated chemiluminescence and nanocarrier for active biomolecules, the number of cell surface carbohydrate groups could be conveniently read out. The apparent dissociation constant between GOx@Au probes and Con A was detected to be 1.64 nM and was approximately 5 orders of magnitude smaller than that of mannose and Con A, which would arise from the multivalent effect between the probe and Con A. Both glycoproteins and gold nanoparticles contribute to the high affinity between carbohydrates and lectin. The as-proposed biosensor exhibits excellent analytical performance towards the cytosensing of K562 cells with a detection limit of 18 cells, and the mannose moieties on a single K562 cell were determined to be 1.8 × 1010. The biosensor can also act as a useful tool for antibacterial drug screening and mechanism investigation. This strategy integrates the excellent biocompatibility and multivalent recognition of glycoproteins as well as the significant enzymatic catalysis and gold nanoparticle signal amplification, and avoids the cell pretreatment and labelling process. This would contribute to the glycomic analysis and the understanding of complex native glycan-related biological processes. Electronic supplementary information (ESI) available: Experimental details; characterization of probes; the influence of electrolyte pH; probe concentration and glucose concentration on the electrode ECL effect. See DOI: 10.1039/c3nr01598j

Constraining Basin Depth and Fault Displacement in the Malombe Basin Using Potential Field Methods

NASA Astrophysics Data System (ADS)

Beresh, S. C. M.; Elifritz, E. A.; Méndez, K.; Johnson, S.; Mynatt, W. G.; Mayle, M.; Atekwana, E. A.; Laó-Dávila, D. A.; Chindandali, P. R. N.; Chisenga, C.; Gondwe, S.; Mkumbwa, M.; Kalaguluka, D.; Kalindekafe, L.; Salima, J.

2017-12-01

The Malombe Basin is part of the Malawi Rift which forms the southern part of the Western Branch of the East African Rift System. At its southern end, the Malawi Rift bifurcates into the Bilila-Mtakataka and Chirobwe-Ntcheu fault systems and the Lake Malombe Rift Basin around the Shire Horst, a competent block under the Nankumba Peninsula. The Malombe Basin is approximately 70km from north to south and 35km at its widest point from east to west, bounded by reversing-polarity border faults. We aim to constrain the depth of the basin to better understand displacement of each border fault. Our work utilizes two east-west gravity profiles across the basin coupled with Source Parameter Imaging (SPI) derived from a high-resolution aeromagnetic survey. The first gravity profile was done across the northern portion of the basin and the second across the southern portion. Gravity and magnetic data will be used to constrain basement depths and the thickness of the sedimentary cover. Additionally, Shuttle Radar Topography Mission (SRTM) data is used to understand the topographic expression of the fault scarps. Estimates for minimum displacement of the border faults on either side of the basin were made by adding the elevation of the scarps to the deepest SPI basement estimates at the basin borders. Our preliminary results using SPI and SRTM data show a minimum displacement of approximately 1.3km for the western border fault; the minimum displacement for the eastern border fault is 740m. However, SPI merely shows the depth to the first significantly magnetic layer in the subsurface, which may or may not be the actual basement layer. Gravimetric readings are based on subsurface density and thus circumvent issues arising from magnetic layers located above the basement; therefore expected results for our work will be to constrain more accurate basin depth by integrating the gravity profiles. Through more accurate basement depth estimates we also gain more accurate displacement estimates for the Basin's faults. Not only do the improved depth estimates serve as a proxy to the viability of hydrocarbon exploration efforts in the region, but the improved displacement estimates also provide a better understanding of extension accommodation within the Malawi Rift.

Fermentanomics: Relating quality attributes of a monoclonal antibody to cell culture process variables and raw materials using multivariate data analysis.

PubMed

Rathore, Anurag S; Kumar Singh, Sumit; Pathak, Mili; Read, Erik K; Brorson, Kurt A; Agarabi, Cyrus D; Khan, Mansoor

2015-01-01

Fermentanomics is an emerging field of research and involves understanding the underlying controlled process variables and their effect on process yield and product quality. Although major advancements have occurred in process analytics over the past two decades, accurate real-time measurement of significant quality attributes for a biotech product during production culture is still not feasible. Researchers have used an amalgam of process models and analytical measurements for monitoring and process control during production. This article focuses on using multivariate data analysis as a tool for monitoring the internal bioreactor dynamics, the metabolic state of the cell, and interactions among them during culture. Quality attributes of the monoclonal antibody product that were monitored include glycosylation profile of the final product along with process attributes, such as viable cell density and level of antibody expression. These were related to process variables, raw materials components of the chemically defined hybridoma media, concentration of metabolites formed during the course of the culture, aeration-related parameters, and supplemented raw materials such as glucose, methionine, threonine, tryptophan, and tyrosine. This article demonstrates the utility of multivariate data analysis for correlating the product quality attributes (especially glycosylation) to process variables and raw materials (especially amino acid supplements in cell culture media). The proposed approach can be applied for process optimization to increase product expression, improve consistency of product quality, and target the desired quality attribute profile. © 2015 American Institute of Chemical Engineers.

Using patient-derived xenograft models of colorectal liver metastases to predict chemosensitivity.

PubMed

Brown, Kai M; Xue, Aiqun; Julovi, Sohel M; Gill, Anthony J; Pavlakis, Nick; Samra, Jaswinder S; Smith, Ross C; Hugh, Thomas J

2018-07-01

Few in vivo models for colorectal cancer have been demonstrated to show external validity by accurately predicting clinical patient outcomes. Patient-derived xenograft (PDX) models of cancer have characteristics that might provide a form of translational research leading to personalized cancer care. The aim of this pilot study was to assess the feasibility of using PDXs as a platform for predicting patient colorectal liver metastases responses, in this case by correlating PDX and patient tumor responses to either folinic acid, fluorouracil plus oxaliplatin or folinic acid, fluorouracil plus irinotecan-based regimens. Sixteen patients underwent potentially curative resection of colorectal liver metastases, and tumors were grafted into NOD.CB17-Prkdc scid /Arc mice. Mice were divided into groups to determine relative tumor growth in response to treatment. Tumors were analyzed by immunohistochemistry for Ki67 and Excision repair cross-complementation group 1. An engraftment rate of 81% was achieved. Overall, there was a 67% positive match rate between eligible patient and PDX chemosensitivity profiles. There was a significant difference in relative decrease in Ki67 expression between sensitive/stable versus resistant PDXs for both treatment regimens. There was no statistically significant correlation between baseline ERCC1 expression and response to Oxaliplatin + 5-Fluorouracil in the PDXs. This pilot study supports the feasibility of using PDX models of advanced colorectal cancer in larger studies to potentially predict patient chemosensitivity profiles. Copyright © 2018 Elsevier Inc. All rights reserved.

Novel method for the rapid isolation of RPE cells specifically for RNA extraction and analysis

PubMed Central

Wang, Cynthia Xin-Zhao; Zhang, Kaiyan; Aredo, Bogale; Lu, Hua; Ufret-Vincenty, Rafael L.

2012-01-01

RPE cells are involved in the pathogenesis of many retinal diseases. Accurate analysis of RPE gene expression profiles in different scenarios will increase our understanding of disease mechanisms. Our objective in this study was to develop an improved method for the isolation of RPE cells, specifically for RNA analysis. Mouse RPE cells were isolated using different techniques, including mechanical dissociation techniques and a new technique we refer to here as “Simultaneous RPE cell Isolation and RNA Stabilization” (SRIRS method). RNA was extracted from the RPE cells. An RNA bioanalyzer was used to determine the quantity and quality of RNA. qPCR was used to determine contamination with non-RPE-derived RNA. Several parameters with a potential impact on the isolation protocol were studied and optimized. A marked improvement in the quantity and quality of RPE-derived RNA was obtained with the SRIRS technique. We could get the RPE in direct contact with the RNA protecting agent within 1 minute of enucleation, and the RPE isolated within 11 minutes of enucleation. There was no significant contamination with vascular, choroidal or scleral-derived RNA. We have developed a fast, easy and reliable method for the isolation of RPE cells that leads to a high yield of RPE-derived RNA while preserving its quality. We believe this technique will be useful for future studies looking at gene expression profiles of RPE cells and their role in the pathophysiology of retinal diseases. PMID:22721721

At a Glance: Forty Schools That Serve Low-Income Students

ERIC Educational Resources Information Center

Independent School, 2016

2016-01-01

This article provides a list of low and no tuition independent schools. Profile information is accurate as of May 2016. Profiles contain student body information, how the school works, the school mission, and contact information. [Online Feature

Accurate optimization of amino acid form factors for computing small-angle X-ray scattering intensity of atomistic protein structures

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

Tong, Dudu; Yang, Sichun; Lu, Lanyuan

2016-06-20

Structure modellingviasmall-angle X-ray scattering (SAXS) data generally requires intensive computations of scattering intensity from any given biomolecular structure, where the accurate evaluation of SAXS profiles using coarse-grained (CG) methods is vital to improve computational efficiency. To date, most CG SAXS computing methods have been based on a single-bead-per-residue approximation but have neglected structural correlations between amino acids. To improve the accuracy of scattering calculations, accurate CG form factors of amino acids are now derived using a rigorous optimization strategy, termed electron-density matching (EDM), to best fit electron-density distributions of protein structures. This EDM method is compared with and tested againstmore » other CG SAXS computing methods, and the resulting CG SAXS profiles from EDM agree better with all-atom theoretical SAXS data. By including the protein hydration shell represented by explicit CG water molecules and the correction of protein excluded volume, the developed CG form factors also reproduce the selected experimental SAXS profiles with very small deviations. Taken together, these EDM-derived CG form factors present an accurate and efficient computational approach for SAXS computing, especially when higher molecular details (represented by theqrange of the SAXS data) become necessary for effective structure modelling.« less

Variation-preserving normalization unveils blind spots in gene expression profiling

PubMed Central

Roca, Carlos P.; Gomes, Susana I. L.; Amorim, Mónica J. B.; Scott-Fordsmand, Janeck J.

2017-01-01

RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the normalization of gene expression levels, which is currently performed following the implicit assumption that most genes are not differentially expressed. Here, we present a mathematical approach to normalization that makes no assumption of this sort. We have found that variation in gene expression is much larger than currently believed, and that it can be measured with available assays. Our results also explain, at least partially, the reproducibility problems encountered in transcriptomics studies. We expect that this improvement in detection will help efforts to realize the full potential of gene expression profiling, especially in analyses of cellular processes involving complex modulations of gene expression. PMID:28276435

Gene expression profiling of intestinal regeneration in the sea cucumber

PubMed Central

Ortiz-Pineda, Pablo A; Ramírez-Gómez, Francisco; Pérez-Ortiz, Judit; González-Díaz, Sebastián; Santiago-De Jesús, Francisco; Hernández-Pasos, Josue; Del Valle-Avila, Cristina; Rojas-Cartagena, Carmencita; Suárez-Castillo, Edna C; Tossas, Karen; Méndez-Merced, Ana T; Roig-López, José L; Ortiz-Zuazaga, Humberto; García-Arrarás, José E

2009-01-01

Background Among deuterostomes, the regenerative potential is maximally expressed in echinoderms, animals that can quickly replace most injured organs. In particular, sea cucumbers are excellent models for studying organ regeneration since they regenerate their digestive tract after evisceration. However, echinoderms have been sidelined in modern regeneration studies partially because of the lack of genome-wide profiling approaches afforded by modern genomic tools. For the last decade, our laboratory has been using the sea cucumber Holothuria glaberrima to dissect the cellular and molecular events that allow for such amazing regenerative processes. We have already established an EST database obtained from cDNA libraries of normal and regenerating intestine at two different regeneration stages. This database now has over 7000 sequences. Results In the present work we used a custom-made microchip from Agilent with 60-mer probes for these ESTs, to determine the gene expression profile during intestinal regeneration. Here we compared the expression profile of animals at three different intestinal regeneration stages (3-, 7- and 14-days post evisceration) against the profile from normal (uneviscerated) intestines. The number of differentially expressed probes ranged from 70% at p < 0.05 to 39% at p < 0.001. Clustering analyses show specific profiles of expression for early (first week) and late (second week) regeneration stages. We used semiquantitative reverse transcriptase polymerase chain reaction (RT-PCR) to validate the expression profile of fifteen microarray detected differentially expressed genes which resulted in over 86% concordance between both techniques. Most of the differentially expressed ESTs showed no clear similarity to sequences in the databases and might represent novel genes associated with regeneration. However, other ESTs were similar to genes known to be involved in regeneration-related processes, wound healing, cell proliferation, differentiation, morphological plasticity, cell survival, stress response, immune challenge, and neoplastic transformation. Among those that have been validated, cytoskeletal genes, such as actins, and developmental genes, such as Wnt and Hox genes, show interesting expression profiles during regeneration. Conclusion Our findings set the base for future studies into the molecular basis of intestinal regeneration. Moreover, it advances the use of echinoderms in regenerative biology, animals that because of their amazing properties and their key evolutionary position, might provide important clues to the genetic basis of regenerative processes. PMID:19505337

Two different protein expression profiles of oral squamous cell carcinoma analyzed by immunoprecipitation high-performance liquid chromatography.

PubMed

Kim, Soung Min; Jeong, Dasul; Kim, Min Keun; Lee, Sang Shin; Lee, Suk Keun

2017-08-08

Oral squamous cell carcinoma (OSCC) is one of the most dangerous cancers in the body, producing serious complications with individual behaviors. Many different pathogenetic factors are involved in the carcinogenesis of OSCC. Cancer cells derived from oral keratinocytes can produce different carcinogenic signaling pathways through differences in protein expression, but their protein expression profiles cannot be easily explored with ordinary detection methods. The present study compared the protein expression profiles between two different types of OSCCs, which were analyzed through immunoprecipitation high-performance liquid chromatography (IP-HPLC). Two types of squamous cell carcinoma (SCC) occurred in a mandibular (SCC-1) and maxillary gingiva (SCC-2), but their clinical features and progression were quite different from each other. SCC-1 showed a large gingival ulceration with severe halitosis and extensive bony destruction, while SCC-2 showed a relatively small papillary gingival swelling but rapidly grew to form a large submucosal mass, followed by early cervical lymph node metastasis. In the histological observation, SCC-1 was relatively well differentiated with a severe inflammatory reaction, while SCC-2 showed severely infiltrative growth of each cancer islets accompanied with a mild inflammatory reaction. IP-HPLC analysis revealed contrary protein expression profiles analyzed by 72 different oncogenic proteins. SCC-1 showed more cellular apoptosis and invasive growth than SCC-2 through increased expression of caspases, MMPs, p53 signaling, FAS signaling, TGF-β1 signaling, and angiogenesis factors, while SCC-2 showed more cellular growth and survival than SCC-1 through the increased expression of proliferating factors, RAS signaling, eIF5A signaling, WNT signaling, and survivin. The increased trends of cellular apoptosis and invasiveness in the protein expression profiles of SCC-1 were implicative of its extensive gingival ulceration and bony destruction, while the increased trends of cellular proliferation and survival in the protein profile of SCC-2 were implicative of its rapid growing tumor mass and early lymph node metastasis. These analyses of the essential oncogenic protein expression profiles in OSCC provide important information for genetic counseling or customized gene therapy in cancer treatment. Therefore, protein expression profile analysis through IP-HPLC is helpful not only for the molecular genetic diagnosis of cancer but also in identifying target molecules for customized gene therapy in near future.

Local Context Finder (LCF) reveals multidimensional relationships among mRNA expression profiles of Arabidopsis responding to pathogen infection

PubMed Central

Katagiri, Fumiaki; Glazebrook, Jane

2003-01-01

A major task in computational analysis of mRNA expression profiles is definition of relationships among profiles on the basis of similarities among them. This is generally achieved by pattern recognition in the distribution of data points representing each profile in a high-dimensional space. Some drawbacks of commonly used pattern recognition algorithms stem from their use of a globally linear space and/or limited degrees of freedom. A pattern recognition method called Local Context Finder (LCF) is described here. LCF uses nonlinear dimensionality reduction for pattern recognition. Then it builds a network of profiles based on the nonlinear dimensionality reduction results. LCF was used to analyze mRNA expression profiles of the plant host Arabidopsis interacting with the bacterial pathogen Pseudomonas syringae. In one case, LCF revealed two dimensions essential to explain the effects of the NahG transgene and the ndr1 mutation on resistant and susceptible responses. In another case, plant mutants deficient in responses to pathogen infection were classified on the basis of LCF analysis of their profiles. The classification by LCF was consistent with the results of biological characterization of the mutants. Thus, LCF is a powerful method for extracting information from expression profile data. PMID:12960373

Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing

PubMed Central

2012-01-01

Background RNA sequencing (RNA-Seq) has emerged as a powerful approach for the detection of differential gene expression with both high-throughput and high resolution capabilities possible depending upon the experimental design chosen. Multiplex experimental designs are now readily available, these can be utilised to increase the numbers of samples or replicates profiled at the cost of decreased sequencing depth generated per sample. These strategies impact on the power of the approach to accurately identify differential expression. This study presents a detailed analysis of the power to detect differential expression in a range of scenarios including simulated null and differential expression distributions with varying numbers of biological or technical replicates, sequencing depths and analysis methods. Results Differential and non-differential expression datasets were simulated using a combination of negative binomial and exponential distributions derived from real RNA-Seq data. These datasets were used to evaluate the performance of three commonly used differential expression analysis algorithms and to quantify the changes in power with respect to true and false positive rates when simulating variations in sequencing depth, biological replication and multiplex experimental design choices. Conclusions This work quantitatively explores comparisons between contemporary analysis tools and experimental design choices for the detection of differential expression using RNA-Seq. We found that the DESeq algorithm performs more conservatively than edgeR and NBPSeq. With regard to testing of various experimental designs, this work strongly suggests that greater power is gained through the use of biological replicates relative to library (technical) replicates and sequencing depth. Strikingly, sequencing depth could be reduced as low as 15% without substantial impacts on false positive or true positive rates. PMID:22985019

Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing.

PubMed

Robles, José A; Qureshi, Sumaira E; Stephen, Stuart J; Wilson, Susan R; Burden, Conrad J; Taylor, Jennifer M

2012-09-17

RNA sequencing (RNA-Seq) has emerged as a powerful approach for the detection of differential gene expression with both high-throughput and high resolution capabilities possible depending upon the experimental design chosen. Multiplex experimental designs are now readily available, these can be utilised to increase the numbers of samples or replicates profiled at the cost of decreased sequencing depth generated per sample. These strategies impact on the power of the approach to accurately identify differential expression. This study presents a detailed analysis of the power to detect differential expression in a range of scenarios including simulated null and differential expression distributions with varying numbers of biological or technical replicates, sequencing depths and analysis methods. Differential and non-differential expression datasets were simulated using a combination of negative binomial and exponential distributions derived from real RNA-Seq data. These datasets were used to evaluate the performance of three commonly used differential expression analysis algorithms and to quantify the changes in power with respect to true and false positive rates when simulating variations in sequencing depth, biological replication and multiplex experimental design choices. This work quantitatively explores comparisons between contemporary analysis tools and experimental design choices for the detection of differential expression using RNA-Seq. We found that the DESeq algorithm performs more conservatively than edgeR and NBPSeq. With regard to testing of various experimental designs, this work strongly suggests that greater power is gained through the use of biological replicates relative to library (technical) replicates and sequencing depth. Strikingly, sequencing depth could be reduced as low as 15% without substantial impacts on false positive or true positive rates.

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

Latest Developments on Obtaining Accurate Measurements with Pitot Tubes in ZPG Turbulent Boundary Layers

NASA Astrophysics Data System (ADS)

Nagib, Hassan; Vinuesa, Ricardo

2013-11-01

Ability of available Pitot tube corrections to provide accurate mean velocity profiles in ZPG boundary layers is re-examined following the recent work by Bailey et al. Measurements by Bailey et al., carried out with probes of diameters ranging from 0.2 to 1.89 mm, together with new data taken with larger diameters up to 12.82 mm, show deviations with respect to available high-quality datasets and hot-wire measurements in the same Reynolds number range. These deviations are significant in the buffer region around y+ = 30 - 40 , and lead to disagreement in the von Kármán coefficient κ extracted from profiles. New forms for shear, near-wall and turbulence corrections are proposed, highlighting the importance of the latest one. Improved agreement in mean velocity profiles is obtained with new forms, where shear and near-wall corrections contribute with around 85%, and remaining 15% of the total correction comes from turbulence correction. Finally, available algorithms to correct wall position in profile measurements of wall-bounded flows are tested, using as benchmark the corrected Pitot measurements with artificially simulated probe shifts and blockage effects. We develop a new scheme, κB - Musker, which is able to accurately locate wall position.

Validation of endogenous reference genes for qRT-PCR analysis of human visceral adipose samples

PubMed Central

2010-01-01

Background Given the epidemic proportions of obesity worldwide and the concurrent prevalence of metabolic syndrome, there is an urgent need for better understanding the underlying mechanisms of metabolic syndrome, in particular, the gene expression differences which may participate in obesity, insulin resistance and the associated series of chronic liver conditions. Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in different tissues and experimental conditions. However, variations in amount of starting material, enzymatic efficiency and presence of inhibitors can lead to quantification errors. Hence the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Recent studies have shown that both obesity and presence of insulin resistance influence an expression of commonly used reference genes in omental fat. In this study we validated candidate reference genes suitable for qRT-PCR profiling experiments using visceral adipose samples from obese and lean individuals. Results Cross-validation of expression stability of eight selected reference genes using three popular algorithms, GeNorm, NormFinder and BestKeeper found ACTB and RPII as most stable reference genes. Conclusions We recommend ACTB and RPII as stable reference genes most suitable for gene expression studies of human visceral adipose tissue. The use of these genes as a reference pair may further enhance the robustness of qRT-PCR in this model system. PMID:20492695

Validation of endogenous reference genes for qRT-PCR analysis of human visceral adipose samples.

PubMed

Mehta, Rohini; Birerdinc, Aybike; Hossain, Noreen; Afendy, Arian; Chandhoke, Vikas; Younossi, Zobair; Baranova, Ancha

2010-05-21

Given the epidemic proportions of obesity worldwide and the concurrent prevalence of metabolic syndrome, there is an urgent need for better understanding the underlying mechanisms of metabolic syndrome, in particular, the gene expression differences which may participate in obesity, insulin resistance and the associated series of chronic liver conditions. Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in different tissues and experimental conditions. However, variations in amount of starting material, enzymatic efficiency and presence of inhibitors can lead to quantification errors. Hence the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Recent studies have shown that both obesity and presence of insulin resistance influence an expression of commonly used reference genes in omental fat. In this study we validated candidate reference genes suitable for qRT-PCR profiling experiments using visceral adipose samples from obese and lean individuals. Cross-validation of expression stability of eight selected reference genes using three popular algorithms, GeNorm, NormFinder and BestKeeper found ACTB and RPII as most stable reference genes. We recommend ACTB and RPII as stable reference genes most suitable for gene expression studies of human visceral adipose tissue. The use of these genes as a reference pair may further enhance the robustness of qRT-PCR in this model system.

Selection of reference genes for gene expression studies in virus-infected monocots using quantitative real-time PCR.

PubMed

Zhang, Kun; Niu, Shaofang; Di, Dianping; Shi, Lindan; Liu, Deshui; Cao, Xiuling; Miao, Hongqin; Wang, Xianbing; Han, Chenggui; Yu, Jialin; Li, Dawei; Zhang, Yongliang

2013-10-10

Both genome-wide transcriptomic surveys of the mRNA expression profiles and virus-induced gene silencing-based molecular studies of target gene during virus-plant interaction involve the precise estimation of the transcript abundance. Quantitative real-time PCR (qPCR) is the most widely adopted technique for mRNA quantification. In order to obtain reliable quantification of transcripts, identification of the best reference genes forms the basis of the preliminary work. Nevertheless, the stability of internal controls in virus-infected monocots needs to be fully explored. In this work, the suitability of ten housekeeping genes (ACT, EF1α, FBOX, GAPDH, GTPB, PP2A, SAND, TUBβ, UBC18 and UK) for potential use as reference genes in qPCR were investigated in five different monocot plants (Brachypodium, barley, sorghum, wheat and maize) under infection with different viruses including Barley stripe mosaic virus (BSMV), Brome mosaic virus (BMV), Rice black-streaked dwarf virus (RBSDV) and Sugarcane mosaic virus (SCMV). By using three different algorithms, the most appropriate reference genes or their combinations were identified for different experimental sets and their effectiveness for the normalisation of expression studies were further validated by quantitative analysis of a well-studied PR-1 gene. These results facilitate the selection of desirable reference genes for more accurate gene expression studies in virus-infected monocots. Copyright © 2013 Elsevier B.V. All rights reserved.

A gene expression biomarker accurately predicts estrogen ...

EPA Pesticide Factsheets

The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1 screening tests. The ToxCast program currently includes 18 HTS in vitro assays that evaluate the ability of chemicals to modulate estrogen receptor α (ERα), an important endocrine target. We propose microarray-based gene expression profiling as a complementary approach to predict ERα modulation and have developed computational methods to identify ERα modulators in an existing database of whole-genome microarray data. The ERα biomarker consisted of 46 ERα-regulated genes with consistent expression patterns across 7 known ER agonists and 3 known ER antagonists. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments in MCF-7 cells. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% or 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) OECD ER reference chemicals including “very weak” agonists and replicated predictions based on 18 in vitro ER-associated HTS assays. For 114 chemicals present in both the HTS data and the MCF-7 c

Comparative proteomic analysis of differentially expressed proteins between peripheral sensory and motor nerves.

PubMed

He, Qianru; Man, Lili; Ji, Yuhua; Zhang, Shuqiang; Jiang, Maorong; Ding, Fei; Gu, Xiaosong

2012-06-01

Peripheral sensory and motor nerves have different functions and different approaches to regeneration, especially their distinct ability to accurately reinervate terminal nerve pathways. To understand the molecular aspects underlying these differences, the proteomics technique by coupling isobaric tags for relative and absolute quantitation (iTRAQ) with online two-dimensional liquid chromatography tandem mass spectrometry (2D LC-MS/MS) was used to investigate the protein profile of sensory and motor nerve samples from rats. A total of 1472 proteins were identified in either sensory or motor nerve. Of them, 100 proteins showed differential expressions between both nerves, and some of them were validated by quantitative real time RT-PCR, Western blot analysis, and immunohistochemistry. In the light of functional categorization, the differentially expressed proteins in sensory and motor nerves, belonging to a broad range of classes, were related to a diverse array of biological functions, which included cell adhesion, cytoskeleton, neuronal plasticity, neurotrophic activity, calcium-binding, signal transduction, transport, enzyme catalysis, lipid metabolism, DNA-binding, synaptosome function, actin-binding, ATP-binding, extracellular matrix, and commitment to other lineages. The relatively higher expressed proteins in either sensory or motor nerve were tentatively discussed in combination with their specific molecular characteristics. It is anticipated that the database generated in this study will provide a solid foundation for further comprehensive investigation of functional differences between sensory and motor nerves, including the specificity of their regeneration.

Gene set differential analysis of time course expression profiles via sparse estimation in functional logistic model with application to time-dependent biomarker detection.

PubMed

Kayano, Mitsunori; Matsui, Hidetoshi; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2016-04-01

High-throughput time course expression profiles have been available in the last decade due to developments in measurement techniques and devices. Functional data analysis, which treats smoothed curves instead of originally observed discrete data, is effective for the time course expression profiles in terms of dimension reduction, robustness, and applicability to data measured at small and irregularly spaced time points. However, the statistical method of differential analysis for time course expression profiles has not been well established. We propose a functional logistic model based on elastic net regularization (F-Logistic) in order to identify the genes with dynamic alterations in case/control study. We employ a mixed model as a smoothing method to obtain functional data; then F-Logistic is applied to time course profiles measured at small and irregularly spaced time points. We evaluate the performance of F-Logistic in comparison with another functional data approach, i.e. functional ANOVA test (F-ANOVA), by applying the methods to real and synthetic time course data sets. The real data sets consist of the time course gene expression profiles for long-term effects of recombinant interferon β on disease progression in multiple sclerosis. F-Logistic distinguishes dynamic alterations, which cannot be found by competitive approaches such as F-ANOVA, in case/control study based on time course expression profiles. F-Logistic is effective for time-dependent biomarker detection, diagnosis, and therapy. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...

21 CFR 862.1163 - Cardiac allograft gene expression profiling test system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL TOXICOLOGY DEVICES Clinical Chemistry Test Systems § 862.1163 Cardiac allograft gene expression profiling test system. (a...

Expression and secretory profile of buffalo fetal fibroblasts and Wharton's jelly feeder layers.

PubMed

Parmar, Mehtab S; Mishra, Smruti Ranjan; Somal, Anjali; Pandey, Sriti; Kumar, G Sai; Sarkar, Mihir; Chandra, Vikash; Sharma, G Taru

2017-05-01

The present study examined the comparative expression and secretory profile of vital signaling molecules in buffalo fetal fibroblasts (BFF) and Wharton's jelly (BWJ) feeder layers at different passages. Both feeder layers were expanded up to 8th passage. Signaling molecules viz. bone morphogenetic protein 4 (BMP4), fibroblast growth factor 2 (FGF2), leukemia inhibitory factor (LIF) and transforming growth factor beta 1 (TGFB1) and pluripotency-associated transcriptional factors (POU5F1, SOX2, NANOG, KLF4, MYC and FOXD3) were immunolocalized in the both feeder types. A clear variation in the expression pattern of key signaling molecules with passaging was registered in both feeders compared to primary culture (0 passage). The conditioned media (CM) was collected from different passages (2, 4, 6, 8) of both the feeder layers and was quantified using enzyme-linked immunosorbent assay (ELISA). Concomitant to expression profile, protein quantification also revealed differences in the concentration of signaling molecules at different time points. Conjointly, expression and secretory profile revealed that 2nd passage of BFF and 6th passage of BWJ exhibit optimal levels of key signaling molecules thus may be selected as best passages for embryonic stem cells (ESCs) propagation. Further, the effect of mitomycin-C (MMC) treatment on the expression profile of signaling molecules in the selected passages of BFF and BWJ revealed that MMC modulates the expression profile of these molecules. In conclusion, the results indicate that feeder layers vary in expression and secretory pattern of vital signaling molecules with passaging. Based on these findings, the appropriate feeder passages may be selected for the quality propagation of buffalo ESCs. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2009-01-01

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

Gene Expression Profiles of Chlamydophila pneumoniae during the Developmental Cycle and Iron Depletion–Mediated Persistence

PubMed Central

Mäurer, André P; Mehlitz, Adrian; Mollenkopf, Hans J; Meyer, Thomas F

2007-01-01

The obligate intracellular, gram-negative bacterium Chlamydophila pneumoniae (Cpn) has impact as a human pathogen. Little is known about changes in the Cpn transcriptome during its biphasic developmental cycle (the acute infection) and persistence. The latter stage has been linked to chronic diseases. To analyze Cpn CWL029 gene expression, we designed a pathogen-specific oligo microarray and optimized the extraction method for pathogen RNA. Throughout the acute infection, ratio expression profiles for each gene were generated using 48 h post infection as a reference. Based on these profiles, significantly expressed genes were separated into 12 expression clusters using self-organizing map clustering and manual sorting into the “early”, “mid”, “late”, and “tardy” cluster classes. The latter two were differentiated because the “tardy” class showed steadily increasing expression at the end of the cycle. The transcriptome of the Cpn elementary body (EB) and published EB proteomics data were compared to the cluster profile of the acute infection. We found an intriguing association between “late” genes and genes coding for EB proteins, whereas “tardy” genes were mainly associated with genes coding for EB mRNA. It has been published that iron depletion leads to Cpn persistence. We compared the gene expression profiles during iron depletion–mediated persistence with the expression clusters of the acute infection. This led to the finding that establishment of iron depletion–mediated persistence is more likely a mid-cycle arrest in development rather than a completely distinct gene expression pattern. Here, we describe the Cpn transcriptome during the acute infection, differentiating “late” genes, which correlate to EB proteins, and “tardy” genes, which lead to EB mRNA. Expression profiles during iron mediated–persistence led us to propose the hypothesis that the transcriptomic “clock” is arrested during acute mid-cycle. PMID:17590080

Accurate assessment and identification of naturally occurring cellular cobalamins

PubMed Central

Hannibal, Luciana; Axhemi, Armend; Glushchenko, Alla V.; Moreira, Edward S.; Brasch, Nicola E.; Jacobsen, Donald W.

2009-01-01

Background Accurate assessment of cobalamin profiles in human serum, cells, and tissues may have clinical diagnostic value. However, non-alkyl forms of cobalamin undergo β-axial ligand exchange reactions during extraction, which leads to inaccurate profiles having little or no diagnostic value. Methods Experiments were designed to: 1) assess β-axial ligand exchange chemistry during the extraction and isolation of cobalamins from cultured bovine aortic endothelial cells, human foreskin fibroblasts, and human hepatoma HepG2 cells, and 2) to establish extraction conditions that would provide a more accurate assessment of endogenous forms containing both exchangeable and non-exchangeable β-axial ligands. Results The cobalamin profile of cells grown in the presence of [57Co]-cyanocobalamin as a source of vitamin B12 shows that the following derivatives are present: [57Co]-aquacobalamin, [57Co]-glutathionylcobalamin, [57Co]-sulfitocobalamin, [57Co]-cyanocobalamin, [57Co]-adenosylcobalamin, [57Co]-methylcobalamin, as well as other yet unidentified corrinoids. When the extraction is performed in the presence of excess cold aquacobalamin acting as a scavenger cobalamin (i.e., “cold trapping”), the recovery of both [57Co]-glutathionylcobalamin and [57Co]-sulfitocobalamin decreases to low but consistent levels. In contrast, the [57Co]-nitrocobalamin observed in extracts prepared without excess aquacobalamin is undetectable in extracts prepared with cold trapping. Conclusions This demonstrates that β-ligand exchange occurs with non-covalently bound β-ligands. The exception to this observation is cyanocobalamin with a non-covalent but non-exchangeable− CNT group. It is now possible to obtain accurate profiles of cellular cobalamins. PMID:18973458

A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors

DTIC Science & Technology

2015-10-01

1 Award Number: W81XWH-10-1-0585 TITLE: A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors...TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors 5a. CONTRACT NUMBER W81XWH...BRCAlike, i.e. not HR deficient and are resistant to PARPis but are sensitive to platinum . These tumors exhibit alterations in another DNA repair

Near-Inertial and Tidal Currents Detected with a Vessel Mounted Acoustic Doppler Current Profiler in the Western Mediterranean Sea

NASA Technical Reports Server (NTRS)

Garcia-Gorriz, E.; Candela, J.; Font, J.

1998-01-01

The Acoustic Doppler Current Profiler (ADCP) combined with accurate navigation provides absolute current velocities which include information from all the frequencies which have a dynamical presence in the ocean.

A novel approach for data integration and disease subtyping

PubMed Central

Tagett, Rebecca; Diaz, Diana

2017-01-01

Advances in high-throughput technologies allow for measurements of many types of omics data, yet the meaningful integration of several different data types remains a significant challenge. Another important and difficult problem is the discovery of molecular disease subtypes characterized by relevant clinical differences, such as survival. Here we present a novel approach, called perturbation clustering for data integration and disease subtyping (PINS), which is able to address both challenges. The framework has been validated on thousands of cancer samples, using gene expression, DNA methylation, noncoding microRNA, and copy number variation data available from the Gene Expression Omnibus, the Broad Institute, The Cancer Genome Atlas (TCGA), and the European Genome-Phenome Archive. This simultaneous subtyping approach accurately identifies known cancer subtypes and novel subgroups of patients with significantly different survival profiles. The results were obtained from genome-scale molecular data without any other type of prior knowledge. The approach is sufficiently general to replace existing unsupervised clustering approaches outside the scope of bio-medical research, with the additional ability to integrate multiple types of data. PMID:29066617

Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experiments

PubMed Central

Brodsky, Leonid; Leontovich, Andrei; Shtutman, Michael; Feinstein, Elena

2004-01-01

Mathematical methods of analysis of microarray hybridizations deal with gene expression profiles as elementary units. However, some of these profiles do not reflect a biologically relevant transcriptional response, but rather stem from technical artifacts. Here, we describe two technically independent but rationally interconnected methods for identification of such artifactual profiles. Our diagnostics are based on detection of deviations from uniformity, which is assumed as the main underlying principle of microarray design. Method 1 is based on detection of non-uniformity of microarray distribution of printed genes that are clustered based on the similarity of their expression profiles. Method 2 is based on evaluation of the presence of gene-specific microarray spots within the slides’ areas characterized by an abnormal concentration of low/high differential expression values, which we define as ‘patterns of differentials’. Applying two novel algorithms, for nested clustering (method 1) and for pattern detection (method 2), we can make a dual estimation of the profile’s quality for almost every printed gene. Genes with artifactual profiles detected by method 1 may then be removed from further analysis. Suspicious differential expression values detected by method 2 may be either removed or weighted according to the probabilities of patterns that cover them, thus diminishing their input in any further data analysis. PMID:14999086

FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues.

PubMed

El-Manzalawy, Yasser; Abbas, Mostafa; Malluhi, Qutaibah; Honavar, Vasant

2016-01-01

A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles). Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein-protein and protein-DNA interfaces.

Global gene expression profile of peripheral blood mononuclear cells challenged with Theileria annulata in crossbred and indigenous cattle.

PubMed

Kumar, Amod; Gaur, Gyanendra Kumar; Gandham, Ravi Kumar; Panigrahi, Manjit; Ghosh, Shrikant; Saravanan, B C; Bhushan, Bharat; Tiwari, Ashok Kumar; Sulabh, Sourabh; Priya, Bhuvana; V N, Muhasin Asaf; Gupta, Jay Prakash; Wani, Sajad Ahmad; Sahu, Amit Ranjan; Sahoo, Aditya Prasad

2017-01-01

Bovine tropical theileriosis is an important haemoprotozoan disease associated with high rates of morbidity and mortality particularly in exotic and crossbred cattle. It is one of the major constraints of the livestock development programmes in India and Southeast Asia. Indigenous cattle (Bos indicus) are reported to be comparatively less affected than exotic and crossbred cattle. However, genetic basis of resistance to tropical theileriosis in indigenous cattle is not well documented. Recent studies incited an idea that differentially expressed genes in exotic and indigenous cattle play significant role in breed specific resistance to tropical theileriosis. The present study was designed to determine the global gene expression profile in peripheral blood mononuclear cells derived from indigenous (Tharparkar) and cross-bred cattle following in vitro infection of T. annulata (Parbhani strain). Two separate microarray experiments were carried out each for cross-bred and Tharparkar cattle. The cross-bred cattle showed 1082 differentially expressed genes (DEGs). Out of total DEGs, 597 genes were down-regulated and 485 were up-regulated. Their fold change varied from 2283.93 to -4816.02. Tharparkar cattle showed 875 differentially expressed genes including 451 down-regulated and 424 up-regulated. The fold change varied from 94.93 to -19.20. A subset of genes was validated by qRT-PCR and results were correlated well with microarray data indicating that microarray results provided an accurate report of transcript level. Functional annotation study of DEGs confirmed their involvement in various pathways including response to oxidative stress, immune system regulation, cell proliferation, cytoskeletal changes, kinases activity and apoptosis. Gene network analysis of these DEGs plays an important role to understand the interaction among genes. It is therefore, hypothesized that the different susceptibility to tropical theileriosis exhibited by indigenous and crossbred cattle is due to breed-specific differences in the dealing of infected cells with other immune cells, which ultimately influence the immune response responded against T. annulata infection. Copyright © 2016 Elsevier B.V. All rights reserved.

Dynamic transcriptomic analysis in hircine longissimus dorsi muscle from fetal to neonatal development stages.

PubMed

Zhan, Siyuan; Zhao, Wei; Song, Tianzeng; Dong, Yao; Guo, Jiazhong; Cao, Jiaxue; Zhong, Tao; Wang, Linjie; Li, Li; Zhang, Hongping

2018-01-01

Muscle growth and development from fetal to neonatal stages consist of a series of delicately regulated and orchestrated changes in expression of genes. In this study, we performed whole transcriptome profiling based on RNA-Seq of caprine longissimus dorsi muscle tissue obtained from prenatal stages (days 45, 60, and 105 of gestation) and neonatal stage (the 3-day-old newborn) to identify genes that are differentially expressed and investigate their temporal expression profiles. A total of 3276 differentially expressed genes (DEGs) were identified (Q value < 0.01). Time-series expression profile clustering analysis indicated that DEGs were significantly clustered into eight clusters which can be divided into two classes (Q value < 0.05), class I profiles with downregulated patterns and class II profiles with upregulated patterns. Based on cluster analysis, GO enrichment analysis found that 75, 25, and 8 terms to be significantly enriched in biological process (BP), cellular component (CC), and molecular function (MF) categories in class I profiles, while 35, 21, and 8 terms to be significantly enriched in BP, CC, and MF in class II profiles. KEGG pathway analysis revealed that DEGs from class I profiles were significantly enriched in 22 pathways and the most enriched pathway was Rap1 signaling pathway. DEGs from class II profiles were significantly enriched in 17 pathways and the mainly enriched pathway was AMPK signaling pathway. Finally, six selected DEGs from our sequencing results were confirmed by qPCR. Our study provides a comprehensive understanding of the molecular mechanisms during goat skeletal muscle development from fetal to neonatal stages and valuable information for future studies of muscle development in goats.

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

PubMed

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

2015-01-01

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

Metabolic Profiling and Identification of Shikonins in Root Periderm of Two Invasive Echium spp. Weeds in Australia.

PubMed

Skoneczny, Dominik; Weston, Paul A; Zhu, Xiaocheng; Gurr, Geoff M; Callaway, Ragan M; Barrow, Russel A; Weston, Leslie A

2017-02-21

Metabolic profiling can be successfully implemented to analyse a living system's response to environmental conditions by providing critical information on an organism's physiological state at a particular point in time and allowing for both quantitative and qualitative assessment of a specific subset(s) of key metabolites. Shikonins are highly reactive chemicals that affect various cell signalling pathways and possess antifungal, antibacterial and allelopathic activity. Based on previous bioassay results, bioactive shikonins, are likely to play important roles in the regulation of rhizosphere interactions with neighbouring plants, microbes and herbivores. An effective platform allowing for rapid identification and accurate profiling of numerous structurally similar, difficult-to-separate bioactive isohexenylnaphthazarins (shikonins) was developed using UHPLC Q-TOF MS. Root periderm tissues of the invasive Australian weeds Echium plantagineum and its congener E. vulgare were extracted overnight in ethanol for shikonin profiling. Shikonin production was evaluated at seedling, rosette and flowering stages. Five populations of each species were compared for qualitative and quantitative differences in shikonin formation. Each species showed little populational variation in qualitative shikonin production; however, shikonin was considerably low in one population of E. plantagineum from Western New South Wales . Seedlings of all populations produced the bioactive metabolite acetylshikonin and production was upregulated over time. Mature plants of both species produced significantly higher total levels of shikonins and isovalerylshikonin > dimethylacrylshikonin > shikonin > acetylshikonin in mature E. plantagineum . Although qualitative metabolic profiles in both Echium spp. were nearly identical, shikonin abundance in mature plant periderm was approximately 2.5 times higher in perennial E. vulgare extracts in comparison to those of the annual E. plantagineum. These findings contribute to our understanding of the biosynthesis of shikonins in roots of two related invasive plants and their expression in relation to plant phenological stage.

Bioorthogonal Metabolic Labeling of Nascent RNA in Neurons Improves the Sensitivity of Transcriptome-Wide Profiling.

PubMed

Zajaczkowski, Esmi L; Zhao, Qiong-Yi; Zhang, Zong Hong; Li, Xiang; Wei, Wei; Marshall, Paul R; Leighton, Laura J; Nainar, Sarah; Feng, Chao; Spitale, Robert C; Bredy, Timothy W

2018-06-15

Transcriptome-wide expression profiling of neurons has provided important insights into the underlying molecular mechanisms and gene expression patterns that transpire during learning and memory formation. However, there is a paucity of tools for profiling stimulus-induced RNA within specific neuronal cell populations. A bioorthogonal method to chemically label nascent (i.e., newly transcribed) RNA in a cell-type-specific and temporally controlled manner, which is also amenable to bioconjugation via click chemistry, was recently developed and optimized within conventional immortalized cell lines. However, its value within a more fragile and complicated cellular system such as neurons, as well as for transcriptome-wide expression profiling, has yet to be demonstrated. Here, we report the visualization and sequencing of activity-dependent nascent RNA derived from neurons using this labeling method. This work has important implications for improving transcriptome-wide expression profiling and visualization of nascent RNA in neurons, which has the potential to provide valuable insights into the mechanisms underlying neural plasticity, learning, and memory.

MicroRNA expression in melanocytic nevi: the usefulness of formalin-fixed, paraffin-embedded material for miRNA microarray profiling.

PubMed

Glud, Martin; Klausen, Mikkel; Gniadecki, Robert; Rossing, Maria; Hastrup, Nina; Nielsen, Finn C; Drzewiecki, Krzysztof T

2009-05-01

MicroRNAs (miRNAs) are small, noncoding RNA molecules that regulate cellular differentiation, proliferation, and apoptosis. MiRNAs are expressed in a developmentally regulated and tissue-specific manner. Aberrant expression may contribute to pathological processes such as cancer, and miRNA may therefore serve as biomarkers that may be useful in a clinical environment for diagnosis of various diseases. Most miRNA profiling studies have used fresh tissue samples. However, in some types of cancer, including malignant melanoma, fresh material is difficult to obtain from primary tumors, and most surgical specimens are formalin fixed and paraffin embedded (FFPE). To explore whether FFPE material would be suitable for miRNA profiling in melanocytic lesions, we compared miRNA expression patterns in FFPE versus fresh frozen samples, obtained from 15 human melanocytic nevi. Out of microarray data, we identified 84 miRNAs that were expressed in both types of samples and represented an miRNA profile of melanocytic nevi. Our results showed a high correlation in miRNA expression (Spearman r-value of 0.80) between paired FFPE and fresh frozen material. The data were further validated by quantitative RT-PCR. In conclusion, FFPE specimens of melanocytic lesions are suitable as a source for miRNA microarray profiling.

MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype.

PubMed

Blenkiron, Cherie; Goldstein, Leonard D; Thorne, Natalie P; Spiteri, Inmaculada; Chin, Suet-Feung; Dunning, Mark J; Barbosa-Morais, Nuno L; Teschendorff, Andrew E; Green, Andrew R; Ellis, Ian O; Tavaré, Simon; Caldas, Carlos; Miska, Eric A

2007-01-01

MicroRNAs (miRNAs), a class of short non-coding RNAs found in many plants and animals, often act post-transcriptionally to inhibit gene expression. Here we report the analysis of miRNA expression in 93 primary human breast tumors, using a bead-based flow cytometric miRNA expression profiling method. Of 309 human miRNAs assayed, we identify 133 miRNAs expressed in human breast and breast tumors. We used mRNA expression profiling to classify the breast tumors as luminal A, luminal B, basal-like, HER2+ and normal-like. A number of miRNAs are differentially expressed between these molecular tumor subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumor subtypes in an independent data set. In some cases, changes in miRNA expression correlate with genomic loss or gain; in others, changes in miRNA expression are likely due to changes in primary transcription and or miRNA biogenesis. Finally, the expression of DICER1 and AGO2 is correlated with tumor subtype and may explain some of the changes in miRNA expression observed. This study represents the first integrated analysis of miRNA expression, mRNA expression and genomic changes in human breast cancer and may serve as a basis for functional studies of the role of miRNAs in the etiology of breast cancer. Furthermore, we demonstrate that bead-based flow cytometric miRNA expression profiling might be a suitable platform to classify breast cancer into prognostic molecular subtypes.

Gene Expression Profiling of Peripheral Blood From Kidney Transplant Recipients for the Early Detection of Digestive System Cancer.

PubMed

Kusaka, M; Okamoto, M; Takenaka, M; Sasaki, H; Fukami, N; Kataoka, K; Ito, T; Kenmochi, T; Hoshinaga, K; Shiroki, R

2017-06-01

Kidney transplant recipients are at increased risk of developing cancer in comparison with the general population. To effectively manage post-transplantation malignancies, it is essential to proactively monitor patients. A long-term intensive screening program was associated with a reduced incidence of cancer after transplantation. This study evaluated the usefulness of the gene expression profiling of peripheral blood samples obtained from kidney transplant patients and adopted a screening test for detecting cancer of the digestive system (gastric, colon, pancreas, and biliary tract). Nineteen patients were included in this study and a total of 53 gene expression screening tests were performed. The gene expression profiles of blood-delivered total RNA and whole genome human gene expression profiles were obtained. We investigated the expression levels of 2665 genes associated with digestive cancers and counted the number of genes in which expression was altered. A hierarchical clustering analysis was also performed. The final prediction of the cancer possibility was determined according to an algorithm. The number of genes in which expression was altered was significantly increased in the kidney transplant recipients in comparison with the general population (1091 ± 63 vs 823 ± 94; P = .0024). The number of genes with altered expression decreased after the induction of mechanistic target of rapamycin (mTOR) inhibitor (1484 ± 227 vs 883 ± 154; P = .0439). No cases of possible digestive cancer were detected in this study period. The gene expression profiling of peripheral blood samples may be a useful and noninvasive diagnostic tool that allows for the early detection of cancer of the digestive system. Copyright © 2017 Elsevier Inc. All rights reserved.

The Disruption of Celf6, a Gene Identified by Translational Profiling of Serotonergic Neurons, Results in Autism-Related Behaviors

PubMed Central

Dougherty, Joseph D.; Maloney, Susan E.; Wozniak, David F.; Rieger, Michael A.; Sonnenblick, Lisa; Coppola, Giovanni; Mahieu, Nathaniel G.; Zhang, Juliet; Cai, Jinlu; Patti, Gary J.; Abrahams, Brett S.; Geschwind, Daniel H.; Heintz, Nathaniel

2013-01-01

The immense molecular diversity of neurons challenges our ability to understand the genetic and cellular etiology of neuropsychiatric disorders. Leveraging knowledge from neurobiology may help parse the genetic complexity: identifying genes important for a circuit that mediates a particular symptom of a disease may help identify polymorphisms that contribute to risk for the disease as a whole. The serotonergic system has long been suspected in disorders that have symptoms of repetitive behaviors and resistance to change, including autism. We generated a bacTRAP mouse line to permit translational profiling of serotonergic neurons. From this, we identified several thousand serotonergic-cell expressed transcripts, of which 174 were highly enriched, including all known markers of these cells. Analysis of common variants near the corresponding genes in the AGRE collection implicated the RNA binding protein CELF6 in autism risk. Screening for rare variants in CELF6 identified an inherited premature stop codon in one of the probands. Subsequent disruption of Celf6 in mice resulted in animals exhibiting resistance to change and decreased ultrasonic vocalization as well as abnormal levels of serotonin in the brain. This work provides a reproducible and accurate method to profile serotonergic neurons under a variety of conditions and suggests a novel paradigm for gaining information on the etiology of psychiatric disorders. PMID:23407934

The Qiagen Investigator® Quantiplex HYres as an alternative kit for DNA quantification.

PubMed

Frégeau, Chantal J; Laurin, Nancy

2015-05-01

The Investigator® Quantiplex HYres kit was evaluated as a potential replacement for dual DNA quantification of casework samples. This kit was determined to be highly sensitive with a limit of quantification and limit of detection of 0.0049ng/μL and 0.0003ng/μL, respectively, for both human and male DNA, using full or half reaction volumes. It was also accurate in assessing the amount of male DNA present in 96 mock and actual casework male:female mixtures (various ratios) processed in this exercise. The close correlation between the male/human DNA ratios expressed in percentages derived from the Investigator® Quantiplex HYres quantification results and the male DNA proportion calculated in mixed AmpFlSTR® Profiler® Plus or AmpFlSTR® Identifiler® Plus profiles, using the Amelogenin Y peak and STR loci, allowed guidelines to be developed to facilitate decisions regarding when to submit samples to Y-STR rather than autosomal STR profiling. The internal control (IC) target was shown to be more sensitive to inhibitors compared to the human and male DNA targets included in the Investigator® Quantiplex HYres kit serving as a good quality assessor of DNA extracts. The new kit met our criteria of enhanced sensitivity, accuracy, consistency, reliability and robustness for casework DNA quantification. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

Characterization of stem cells and cancer cells on the basis of gene expression profile stability, plasticity, and robustness: dynamical systems theory of gene expressions under cell-cell interaction explains mutational robustness of differentiated cells and suggests how cancer cells emerge.

PubMed

Kaneko, Kunihiko

2011-06-01

Here I present and discuss a model that, among other things, appears able to describe the dynamics of cancer cell origin from the perspective of stable and unstable gene expression profiles. In identifying such aberrant gene expression profiles as lying outside the normal stable states attracted through development and normal cell differentiation, the hypothesis explains why cancer cells accumulate mutations, to which they are not robust, and why these mutations create a new stable state far from the normal gene expression profile space. Such cells are in strong contrast with normal cell types that appeared as an attractor state in the gene expression dynamical system under cell-cell interaction and achieved robustness to noise through evolution, which in turn also conferred robustness to mutation. In complex gene regulation networks, other aberrant cellular states lacking such high robustness are expected to remain, which would correspond to cancer cells. Copyright © 2011 WILEY Periodicals, Inc.

Gene expression profiling of single cells on large-scale oligonucleotide arrays

PubMed Central

Hartmann, Claudia H.; Klein, Christoph A.

2006-01-01

Over the last decade, important insights into the regulation of cellular responses to various stimuli were gained by global gene expression analyses of cell populations. More recently, specific cell functions and underlying regulatory networks of rare cells isolated from their natural environment moved to the center of attention. However, low cell numbers still hinder gene expression profiling of rare ex vivo material in biomedical research. Therefore, we developed a robust method for gene expression profiling of single cells on high-density oligonucleotide arrays with excellent coverage of low abundance transcripts. The protocol was extensively tested with freshly isolated single cells of very low mRNA content including single epithelial, mature and immature dendritic cells and hematopoietic stem cells. Quantitative PCR confirmed that the PCR-based global amplification method did not change the relative ratios of transcript abundance and unsupervised hierarchical cluster analysis revealed that the histogenetic origin of an individual cell is correctly reflected by the gene expression profile. Moreover, the gene expression data from dendritic cells demonstrate that cellular differentiation and pathway activation can be monitored in individual cells. PMID:17071717

Toward more accurate loss tangent measurements in reentrant cavities

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

Moyer, R. D.

1980-05-01

Karpova has described an absolute method for measurement of dielectric properties of a solid in a coaxial reentrant cavity. His cavity resonance equation yields very accurate results for dielectric constants. However, he presented only approximate expressions for the loss tangent. This report presents more exact expressions for that quantity and summarizes some experimental results.

Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization.

PubMed

Liang, Yong; Chai, Hua; Liu, Xiao-Ying; Xu, Zong-Ben; Zhang, Hai; Leung, Kwong-Sak

2016-03-01

One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles. Both Cox proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients' clinical treatment. Nevertheless, two main dilemmas limit the accuracy of these prediction methods. One is that the small sample size and censored data remain a bottleneck for training robust and accurate Cox classification model. In addition to that, similar phenotype tumours and prognoses are actually completely different diseases at the genotype and molecular level. Thus, the utility of the AFT model for the survival time prediction is limited when such biological differences of the diseases have not been previously identified. To try to overcome these two main dilemmas, we proposed a novel semi-supervised learning method based on the Cox and AFT models to accurately predict the treatment risk and the survival time of the patients. Moreover, we adopted the efficient L1/2 regularization approach in the semi-supervised learning method to select the relevant genes, which are significantly associated with the disease. The results of the simulation experiments show that the semi-supervised learning model can significant improve the predictive performance of Cox and AFT models in survival analysis. The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets. The advantages of our proposed semi-supervised learning method include: 1) significantly increase the available training samples from censored data; 2) high capability for identifying the survival risk classes of patient in Cox model; 3) high predictive accuracy for patients' survival time in AFT model; 4) strong capability of the relevant biomarker selection. Consequently, our proposed semi-supervised learning model is one more appropriate tool for survival analysis in clinical cancer research.

ICG: a wiki-driven knowledgebase of internal control genes for RT-qPCR normalization.

PubMed

Sang, Jian; Wang, Zhennan; Li, Man; Cao, Jiabao; Niu, Guangyi; Xia, Lin; Zou, Dong; Wang, Fan; Xu, Xingjian; Han, Xiaojiao; Fan, Jinqi; Yang, Ye; Zuo, Wanzhu; Zhang, Yang; Zhao, Wenming; Bao, Yiming; Xiao, Jingfa; Hu, Songnian; Hao, Lili; Zhang, Zhang

2018-01-04

Real-time quantitative PCR (RT-qPCR) has become a widely used method for accurate expression profiling of targeted mRNA and ncRNA. Selection of appropriate internal control genes for RT-qPCR normalization is an elementary prerequisite for reliable expression measurement. Here, we present ICG (http://icg.big.ac.cn), a wiki-driven knowledgebase for community curation of experimentally validated internal control genes as well as their associated experimental conditions. Unlike extant related databases that focus on qPCR primers in model organisms (mainly human and mouse), ICG features harnessing collective intelligence in community integration of internal control genes for a variety of species. Specifically, it integrates a comprehensive collection of more than 750 internal control genes for 73 animals, 115 plants, 12 fungi and 9 bacteria, and incorporates detailed information on recommended application scenarios corresponding to specific experimental conditions, which, collectively, are of great help for researchers to adopt appropriate internal control genes for their own experiments. Taken together, ICG serves as a publicly editable and open-content encyclopaedia of internal control genes and accordingly bears broad utility for reliable RT-qPCR normalization and gene expression characterization in both model and non-model organisms. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

EgoNet: identification of human disease ego-network modules

PubMed Central

2014-01-01

Background Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks. Results We present EgoNet, a novel method based on egocentric network-analysis techniques, to exhaustively search and prioritize disease subnetworks and gene markers from a large-scale biological network. When applied to a triple-negative breast cancer (TNBC) microarray dataset, the top selected modules contain both known gene markers in TNBC and novel candidates, such as RAD51 and DOK1, which play a central role in their respective ego-networks by connecting many differentially expressed genes. Conclusions Our results suggest that EgoNet, which is based on the ego network concept, allows the identification of novel biomarkers and provides a deeper understanding of their roles in complex diseases. PMID:24773628

Identification of innate lymphoid cells in single-cell RNA-Seq data.

PubMed

Suffiotti, Madeleine; Carmona, Santiago J; Jandus, Camilla; Gfeller, David

2017-07-01

Innate lymphoid cells (ILCs) consist of natural killer (NK) cells and non-cytotoxic ILCs that are broadly classified into ILC1, ILC2, and ILC3 subtypes. These cells recently emerged as important early effectors of innate immunity for their roles in tissue homeostasis and inflammation. Over the last few years, ILCs have been extensively studied in mouse and human at the functional and molecular level, including gene expression profiling. However, sorting ILCs with flow cytometry for gene expression analysis is a delicate and time-consuming process. Here we propose and validate a novel framework for studying ILCs at the transcriptomic level using single-cell RNA-Seq data. Our approach combines unsupervised clustering and a new cell type classifier trained on mouse ILC gene expression data. We show that this approach can accurately identify different ILCs, especially ILC2 cells, in human lymphocyte single-cell RNA-Seq data. Our new model relies only on genes conserved across vertebrates, thereby making it in principle applicable in any vertebrate species. Considering the rapid increase in throughput of single-cell RNA-Seq technology, our work provides a computational framework for studying ILC2 cells in single-cell transcriptomic data and may help exploring their conservation in distant vertebrate species.

A gene expression signature associated with survival in metastatic melanoma

PubMed Central

Mandruzzato, Susanna; Callegaro, Andrea; Turcatel, Gianluca; Francescato, Samuela; Montesco, Maria C; Chiarion-Sileni, Vanna; Mocellin, Simone; Rossi, Carlo R; Bicciato, Silvio; Wang, Ena; Marincola, Francesco M; Zanovello, Paola

2006-01-01

Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells. PMID:17129373

Genomics of Mature and Immature Olfactory Sensory Neurons

PubMed Central

Nickell, Melissa D.; Breheny, Patrick; Stromberg, Arnold J.; McClintock, Timothy S.

2014-01-01

The continuous replacement of neurons in the olfactory epithelium provides an advantageous model for investigating neuronal differentiation and maturation. By calculating the relative enrichment of every mRNA detected in samples of mature mouse olfactory sensory neurons (OSNs), immature OSNs, and the residual population of neighboring cell types, and then comparing these ratios against the known expression patterns of >300 genes, enrichment criteria that accurately predicted the OSN expression patterns of nearly all genes were determined. We identified 847 immature OSN-specific and 691 mature OSN-specific genes. The control of gene expression by chromatin modification and transcription factors, and neurite growth, protein transport, RNA processing, cholesterol biosynthesis, and apoptosis via death domain receptors, were overrepresented biological processes in immature OSNs. Ion transport (ion channels), presynaptic functions, and cilia-specific processes were overrepresented in mature OSNs. Processes overrepresented among the genes expressed by all OSNs were protein and ion transport, ER overload response, protein catabolism, and the electron transport chain. To more accurately represent gradations in mRNA abundance and identify all genes expressed in each cell type, classification methods were used to produce probabilities of expression in each cell type for every gene. These probabilities, which identified 9,300 genes expressed in OSNs, were 96% accurate at identifying genes expressed in OSNs and 86% accurate at discriminating genes specific to mature and immature OSNs. This OSN gene database not only predicts the genes responsible for the major biological processes active in OSNs, but also identifies thousands of never before studied genes that support OSN phenotypes. PMID:22252456

Expression profiling of the mouse early embryo: Reflections and Perspectives

PubMed Central

Ko, Minoru S. H.

2008-01-01

Laboratory mouse plays important role in our understanding of early mammalian development and provides invaluable model for human early embryos, which are difficult to study for ethical and technical reasons. Comprehensive collection of cDNA clones, their sequences, and complete genome sequence information, which have been accumulated over last two decades, have provided even more advantages to mouse models. Here the progress in global gene expression profiling in early mouse embryos and, to some extent, stem cells are reviewed and the future directions and challenges are discussed. The discussions include the restatement of global gene expression profiles as snapshot of cellular status, and subsequent distinction between the differentiation state and physiological state of the cells. The discussions then extend to the biological problems that can be addressed only through global expression profiling, which include: bird’s-eye view of global gene expression changes, molecular index for developmental potency, cell lineage trajectory, microarray-guided cell manipulation, and the possibility of delineating gene regulatory cascades and networks. PMID:16739220

Expression signature as a biomarker for prenatal diagnosis of trisomy 21.

PubMed

Volk, Marija; Maver, Aleš; Lovrečić, Luca; Juvan, Peter; Peterlin, Borut

2013-01-01

A universal biomarker panel with the potential to predict high-risk pregnancies or adverse pregnancy outcome does not exist. Transcriptome analysis is a powerful tool to capture differentially expressed genes (DEG), which can be used as biomarker-diagnostic-predictive tool for various conditions in prenatal setting. In search of biomarker set for predicting high-risk pregnancies, we performed global expression profiling to find DEG in Ts21. Subsequently, we performed targeted validation and diagnostic performance evaluation on a larger group of case and control samples. Initially, transcriptomic profiles of 10 cultivated amniocyte samples with Ts21 and 9 with normal euploid constitution were determined using expression microarrays. Datasets from Ts21 transcriptomic studies from GEO repository were incorporated. DEG were discovered using linear regression modelling and validated using RT-PCR quantification on an independent sample of 16 cases with Ts21 and 32 controls. The classification performance of Ts21 status based on expression profiling was performed using supervised machine learning algorithm and evaluated using a leave-one-out cross validation approach. Global gene expression profiling has revealed significant expression changes between normal and Ts21 samples, which in combination with data from previously performed Ts21 transcriptomic studies, were used to generate a multi-gene biomarker for Ts21, comprising of 9 gene expression profiles. In addition to biomarker's high performance in discriminating samples from global expression profiling, we were also able to show its discriminatory performance on a larger sample set 2, validated using RT-PCR experiment (AUC=0.97), while its performance on data from previously published studies reached discriminatory AUC values of 1.00. Our results show that transcriptomic changes might potentially be used to discriminate trisomy of chromosome 21 in the prenatal setting. As expressional alterations reflect both, causal and reactive cellular mechanisms, transcriptomic changes may thus have future potential in the diagnosis of a wide array of heterogeneous diseases that result from genetic disturbances.

mRNA expression profiling of laser microbeam microdissected cells from slender embryonic structures.

PubMed

Scheidl, Stefan J; Nilsson, Sven; Kalén, Mattias; Hellström, Mats; Takemoto, Minoru; Håkansson, Joakim; Lindahl, Per

2002-03-01

Microarray hybridization has rapidly evolved as an important tool for genomic studies and studies of gene regulation at the transcriptome level. Expression profiles from homogenous samples such as yeast and mammalian cell cultures are currently extending our understanding of biology, whereas analyses of multicellular organisms are more difficult because of tissue complexity. The combination of laser microdissection, RNA amplification, and microarray hybridization has the potential to provide expression profiles from selected populations of cells in vivo. In this article, we present and evaluate an experimental procedure for global gene expression analysis of slender embryonic structures using laser microbeam microdissection and laser pressure catapulting. As a proof of principle, expression profiles from 1000 cells in the mouse embryonic (E9.5) dorsal aorta were generated and compared with profiles for captured mesenchymal cells located one cell diameter further away from the aortic lumen. A number of genes were overexpressed in the aorta, including 11 previously known markers for blood vessels. Among the blood vessel markers were endoglin, tie-2, PDGFB, and integrin-beta1, that are important regulators of blood vessel formation. This demonstrates that microarray analysis of laser microbeam micro-dissected cells is sufficiently sensitive for identifying genes with regulative functions.

ABC gene expression profiles have clinical importance and possibly form a new hallmark of cancer.

PubMed

Dvorak, Pavel; Pesta, Martin; Soucek, Pavel

2017-05-01

Adenosine triphosphate-binding cassette proteins constitute a large family of active transporters through extracellular and intracellular membranes. Increased drug efflux based on adenosine triphosphate-binding cassette protein activity is related to the development of cancer cell chemoresistance. Several articles have focused on adenosine triphosphate-binding cassette gene expression profiles (signatures), based on the expression of all 49 human adenosine triphosphate-binding cassette genes, in individual tumor types and reported connections to established clinicopathological features. The aim of this study was to test our theory about the existence of adenosine triphosphate-binding cassette gene expression profiles common to multiple types of tumors, which may modify tumor progression and provide clinically relevant information. Such general adenosine triphosphate-binding cassette profiles could constitute a new attribute of carcinogenesis. Our combined cohort consisted of tissues from 151 cancer patients-breast, colorectal, and pancreatic carcinomas. Standard protocols for RNA isolation and quantitative real-time polymerase chain reaction were followed. Gene expression data from individual tumor types as well as a merged tumor dataset were analyzed by bioinformatics tools. Several general adenosine triphosphate-binding cassette profiles, with differences in gene functions, were established and shown to have significant relations to clinicopathological features such as tumor size, histological grade, or clinical stage. Genes ABCC7, A3, A8, A12, and C8 prevailed among the most upregulated or downregulated ones. In conclusion, the results supported our theory about general adenosine triphosphate-binding cassette gene expression profiles and their importance for cancer on clinical as well as research levels. The presence of ABCC7 (official symbol CFTR) among the genes with key roles in the profiles supports the emerging evidence about its crucial role in various cancers. Graphical abstract.

Combination of gene expression patterns in whole blood discriminate between tuberculosis infection states

PubMed Central

2014-01-01

Background Genetic factors are involved in susceptibility or protection to tuberculosis (TB). Apart from gene polymorphisms and mutations, changes in levels of gene expression, induced by non-genetic factors, may also determine whether individuals progress to active TB. Methods We analysed the expression level of 45 genes in a total of 47 individuals (23 healthy household contacts and 24 new smear-positive pulmonary TB patients) in Addis Ababa using a dual colour multiplex ligation-dependent probe amplification (dcRT-MLPA) technique to assess gene expression profiles that may be used to distinguish TB cases and their contacts and also latently infected (LTBI) and uninfected household contacts. Results The gene expression level of BLR1, Bcl2, IL4d2, IL7R, FCGR1A, MARCO, MMP9, CCL19, and LTF had significant discriminatory power between sputum smear-positive TB cases and household contacts, with AUCs of 0.84, 0.81, 0.79, 0.79, 0.78, 0.76, 0.75, 0.75 and 0.68 respectively. The combination of Bcl2, BLR1, FCGR1A, IL4d2 and MARCO identified 91.66% of active TB cases and 95.65% of household contacts without active TB. The expression of CCL19, TGFB1, and Foxp3 showed significant difference between LTBI and uninfected contacts, with AUCs of 0.85, 0.82, and 0.75, respectively, whereas the combination of BPI, CCL19, FoxP3, FPR1 and TGFB1 identified 90.9% of QFT- and 91.6% of QFT+ household contacts. Conclusions Expression of single and especially combinations of host genes can accurately differentiate between active TB cases and healthy individuals as well as between LTBI and uninfected contacts. PMID:24885723

Evaluation and Validation of Reference Genes for qRT-PCR Normalization in Frankliniella occidentalis (Thysanoptera:Thripidae)

PubMed Central

Zheng, Yu-Tao; Li, Hong-Bo; Lu, Ming-Xing; Du, Yu-Zhou

2014-01-01

Quantitative real time PCR (qRT-PCR) has emerged as a reliable and reproducible technique for studying gene expression analysis. For accurate results, the normalization of data with reference genes is particularly essential. Once the transcriptome sequencing of Frankliniella occidentalis was completed, numerous unigenes were identified and annotated. Unfortunately, there are no studies on the stability of reference genes used in F. occidentalis. In this work, seven candidate reference genes, including actin, 18S rRNA, H3, tubulin, GAPDH, EF-1 and RPL32, were evaluated for their suitability as normalization genes under different experimental conditions using the statistical software programs BestKeeper, geNorm, Normfinder and the comparative ΔCt method. Because the rankings of the reference genes provided by each of the four programs were different, we chose a user-friendly web-based comprehensive tool RefFinder to get the final ranking. The result demonstrated that EF-1 and RPL32 displayed the most stable expression in different developmental stages; RPL32 and GAPDH showed the most stable expression at high temperatures, while 18S and EF-1 exhibited the most stable expression at low temperatures. In this study, we validated the suitable reference genes in F. occidentalis for gene expression profiling under different experimental conditions. The choice of internal standard is very important in the normalization of the target gene expression levels, thus validating and selecting the best genes will help improve the quality of gene expression data of F. occidentalis. What is more, these validated reference genes could serve as the basis for the selection of candidate reference genes in other insects. PMID:25356721

Evaluation and validation of reference genes for qRT-PCR normalization in Frankliniella occidentalis (Thysanoptera: Thripidae).

PubMed

Zheng, Yu-Tao; Li, Hong-Bo; Lu, Ming-Xing; Du, Yu-Zhou

2014-01-01

Quantitative real time PCR (qRT-PCR) has emerged as a reliable and reproducible technique for studying gene expression analysis. For accurate results, the normalization of data with reference genes is particularly essential. Once the transcriptome sequencing of Frankliniella occidentalis was completed, numerous unigenes were identified and annotated. Unfortunately, there are no studies on the stability of reference genes used in F. occidentalis. In this work, seven candidate reference genes, including actin, 18S rRNA, H3, tubulin, GAPDH, EF-1 and RPL32, were evaluated for their suitability as normalization genes under different experimental conditions using the statistical software programs BestKeeper, geNorm, Normfinder and the comparative ΔCt method. Because the rankings of the reference genes provided by each of the four programs were different, we chose a user-friendly web-based comprehensive tool RefFinder to get the final ranking. The result demonstrated that EF-1 and RPL32 displayed the most stable expression in different developmental stages; RPL32 and GAPDH showed the most stable expression at high temperatures, while 18S and EF-1 exhibited the most stable expression at low temperatures. In this study, we validated the suitable reference genes in F. occidentalis for gene expression profiling under different experimental conditions. The choice of internal standard is very important in the normalization of the target gene expression levels, thus validating and selecting the best genes will help improve the quality of gene expression data of F. occidentalis. What is more, these validated reference genes could serve as the basis for the selection of candidate reference genes in other insects.

Efficient calculation of general Voigt profiles

NASA Astrophysics Data System (ADS)

Cope, D.; Khoury, R.; Lovett, R. J.

1988-02-01

An accurate and efficient program is presented for the computation of OIL profiles, generalizations of the Voigt profile resulting from the one-interacting-level model of Ward et al. (1974). These profiles have speed dependent shift and width functions and have asymmetric shapes. The program contains an adjustable error control parameter and includes the Voigt profile as a special case, although the general nature of this program renders it slower than a specialized Voigt profile method. Results on accuracy and computation time are presented for a broad set of test parameters, and a comparison is made with previous work on the asymptotic behavior of general Voigt profiles.

EAST kinetic equilibrium reconstruction combining with Polarimeter-Interferometer internal measurement constraints

NASA Astrophysics Data System (ADS)

Lian, H.; Liu, H. Q.; Li, K.; Zou, Z. Y.; Qian, J. P.; Wu, M. Q.; Li, G. Q.; Zeng, L.; Zang, Q.; Lv, B.; Jie, Y. X.; EAST Team

2017-12-01

Plasma equilibrium reconstruction plays an important role in the tokamak plasma research. With a high temporal and spatial resolution, the POlarimeter-INTerferometer (POINT) system on EAST has provided effective measurements for 102s H-mode operation. Based on internal Faraday rotation measurements provided by the POINT system, the equilibrium reconstruction with a more accurate core current profile constraint has been demonstrated successfully on EAST. Combining other experimental diagnostics and external magnetic fields measurement, the kinetic equilibrium has also been reconstructed on EAST. Take the pressure and edge current information from kinetic EFIT into the equilibrium reconstruction with Faraday rotation constraint, the new equilibrium reconstruction not only provides a more accurate internal current profile but also contains edge current and pressure information. One time slice result using new kinetic equilibrium reconstruction with POINT data constraints is demonstrated in this paper and the result shows there is a reversed shear of q profile and the pressure profile is also contained. The new improved equilibrium reconstruction is greatly helpful to the future theoretical analysis.

Specific identification of Bacillus anthracis strains

NASA Astrophysics Data System (ADS)

Krishnamurthy, Thaiya; Deshpande, Samir; Hewel, Johannes; Liu, Hongbin; Wick, Charles H.; Yates, John R., III

2007-01-01

Accurate identification of human pathogens is the initial vital step in treating the civilian terrorism victims and military personnel afflicted in biological threat situations. We have applied a powerful multi-dimensional protein identification technology (MudPIT) along with newly generated software termed Profiler to identify the sequences of specific proteins observed for few strains of Bacillus anthracis, a human pathogen. Software termed Profiler was created to initially screen the MudPIT data of B. anthracis strains and establish the observed proteins specific for its strains. A database was also generated using Profiler containing marker proteins of B. anthracis and its strains, which in turn could be used for detecting the organism and its corresponding strains in samples. Analysis of the unknowns by our methodology, combining MudPIT and Profiler, led to the accurate identification of the anthracis strains present in samples. Thus, a new approach for the identification of B. anthracis strains in unknown samples, based on the molecular mass and sequences of marker proteins, has been ascertained.

microRNA-342, microRNA-191 and microRNA-510 are differentially expressed in T regulatory cells of type 1 diabetic patients.

PubMed

Hezova, Renata; Slaby, Ondrej; Faltejskova, Petra; Mikulkova, Zuzana; Buresova, Ivana; Raja, K R Muthu; Hodek, Jan; Ovesna, Jaroslava; Michalek, Jaroslav

2010-01-01

Regulatory T cells (Tregs) are critical regulators of autoimmune diseases, including type 1 diabetes mellitus. It is hypothesised that Tregs' function can be influenced by changes in the expression of specific microRNAs (miRNAs). Thus, we performed miRNAs profiling in a population of Tregs separated from peripheral blood of five type 1 diabetic patients and six healthy donors. For more detailed molecular characterisation of Tregs, we additionally compared miRNAs expression profiles of Tregs and conventional T cells. Tregs were isolated according to CD3+, CD4+, CD25(hi)+ and CD127- by flow cytometry, and miRNA expression profiling was performed using TaqMan Array Human MicroRNA Panel-1 (384-well low density array). In Tregs of diabetic patients we found significantly increased expression of miRNA-510 (p=0.05) and decreased expression of both miRNA-342 (p<0.0001) and miRNA-191 (p=0.0079). When comparing Tregs and T cells, we revealed that Tregs had significant higher expression of miRNA-146a and lower expression of eight specific miRNAs (20b, 31, 99a, 100, 125b, 151, 335, and 365). To our knowledge, this is the first study demonstrating changes in miRNA expression profiles occurring in Tregs of T1D patients and a miRNAs signature of adult Tregs.

Stress amplifies sex differences in primate prefrontal profiles of gene expression.

PubMed

Lee, Alex G; Hagenauer, Megan; Absher, Devin; Morrison, Kathleen E; Bale, Tracy L; Myers, Richard M; Watson, Stanley J; Akil, Huda; Schatzberg, Alan F; Lyons, David M

2017-11-02

Stress is a recognized risk factor for mood and anxiety disorders that occur more often in women than men. Prefrontal brain regions mediate stress coping, cognitive control, and emotion. Here, we investigate sex differences and stress effects on prefrontal cortical profiles of gene expression in squirrel monkey adults. Dorsolateral, ventrolateral, and ventromedial prefrontal cortical regions from 18 females and 12 males were collected after stress or no-stress treatment conditions. Gene expression profiles were acquired using HumanHT-12v4.0 Expression BeadChip arrays adapted for squirrel monkeys. Extensive variation between prefrontal cortical regions was discerned in the expression of numerous autosomal and sex chromosome genes. Robust sex differences were also identified across prefrontal cortical regions in the expression of mostly autosomal genes. Genes with increased expression in females compared to males were overrepresented in mitogen-activated protein kinase and neurotrophin signaling pathways. Many fewer genes with increased expression in males compared to females were discerned, and no molecular pathways were identified. Effect sizes for sex differences were greater in stress compared to no-stress conditions for ventromedial and ventrolateral prefrontal cortical regions but not dorsolateral prefrontal cortex. Stress amplifies sex differences in gene expression profiles for prefrontal cortical regions involved in stress coping and emotion regulation. Results suggest molecular targets for new treatments of stress disorders in human mental health.

Comparison of the Predictive Accuracy of DNA Array-Based Multigene Classifiers across cDNA Arrays and Affymetrix GeneChips

PubMed Central

Stec, James; Wang, Jing; Coombes, Kevin; Ayers, Mark; Hoersch, Sebastian; Gold, David L.; Ross, Jeffrey S; Hess, Kenneth R.; Tirrell, Stephen; Linette, Gerald; Hortobagyi, Gabriel N.; Symmans, W. Fraser; Pusztai, Lajos

2005-01-01

We examined how well differentially expressed genes and multigene outcome classifiers retain their class-discriminating values when tested on data generated by different transcriptional profiling platforms. RNA from 33 stage I-III breast cancers was hybridized to both Affymetrix GeneChip and Millennium Pharmaceuticals cDNA arrays. Only 30% of all corresponding gene expression measurements on the two platforms had Pearson correlation coefficient r ≥ 0.7 when UniGene was used to match probes. There was substantial variation in correlation between different Affymetrix probe sets matched to the same cDNA probe. When cDNA and Affymetrix probes were matched by basic local alignment tool (BLAST) sequence identity, the correlation increased substantially. We identified 182 genes in the Affymetrix and 45 in the cDNA data (including 17 common genes) that accurately separated 91% of cases in supervised hierarchical clustering in each data set. Cross-platform testing of these informative genes resulted in lower clustering accuracy of 45 and 79%, respectively. Several sets of accurate five-gene classifiers were developed on each platform using linear discriminant analysis. The best 100 classifiers showed average misclassification error rate of 2% on the original data that rose to 19.5% when tested on data from the other platform. Random five-gene classifiers showed misclassification error rate of 33%. We conclude that multigene predictors optimized for one platform lose accuracy when applied to data from another platform due to missing genes and sequence differences in probes that result in differing measurements for the same gene. PMID:16049308

Modeling keratinocyte wound healing dynamics: Cell-cell adhesion promotes sustained collective migration.

PubMed

Nardini, John T; Chapnick, Douglas A; Liu, Xuedong; Bortz, David M

2016-07-07

The in vitro migration of keratinocyte cell sheets displays behavioral and biochemical similarities to the in vivo wound healing response of keratinocytes in animal model systems. In both cases, ligand-dependent Epidermal Growth Factor Receptor (EGFR) activation is sufficient to elicit collective cell migration into the wound. Previous mathematical modeling studies of in vitro wound healing assays assume that physical connections between cells have a hindering effect on cell migration, but biological literature suggests a more complicated story. By combining mathematical modeling and experimental observations of collectively migrating sheets of keratinocytes, we investigate the role of cell-cell adhesion during in vitro keratinocyte wound healing assays. We develop and compare two nonlinear diffusion models of the wound healing process in which cell-cell adhesion either hinders or promotes migration. Both models can accurately fit the leading edge propagation of cell sheets during wound healing when using a time-dependent rate of cell-cell adhesion strength. The model that assumes a positive role of cell-cell adhesion on migration, however, is robust to changes in the leading edge definition and yields a qualitatively accurate density profile. Using RNAi for the critical adherens junction protein, α-catenin, we demonstrate that cell sheets with wild type cell-cell adhesion expression maintain migration into the wound longer than cell sheets with decreased cell-cell adhesion expression, which fails to exhibit collective migration. Our modeling and experimental data thus suggest that cell-cell adhesion promotes sustained migration as cells pull neighboring cells into the wound during wound healing. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparative analysis of inflamed and non-inflamed colon biopsies reveals strong proteomic inflammation profile in patients with ulcerative colitis

PubMed Central

2012-01-01

Background Accurate diagnostic and monitoring tools for ulcerative colitis (UC) are missing. Our aim was to describe the proteomic profile of UC and search for markers associated with disease exacerbation. Therefore, we aimed to characterize specific proteins associated with inflamed colon mucosa from patients with acute UC using mass spectrometry-based proteomic analysis. Methods Biopsies were sampled from rectum, sigmoid colon and left colonic flexure from twenty patients with active proctosigmoiditis and from four healthy controls for proteomics and histology. Proteomic profiles of whole colonic biopsies were characterized using 2D-gel electrophoresis, and peptide mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was applied for identification of differently expressed protein spots. Results A total of 597 spots were annotated by image analysis and 222 of these had a statistically different protein level between inflamed and non-inflamed tissue in the patient group. Principal component analysis clearly grouped non-inflamed samples separately from the inflamed samples indicating that the proteomic signature of colon mucosa with acute UC is strong. Totally, 43 individual protein spots were identified, including proteins involved in energy metabolism (triosephosphate isomerase, glycerol-3-phosphate-dehydrogenase, alpha enolase and L-lactate dehydrogenase B-chain) and in oxidative stress (superoxide dismutase, thioredoxins and selenium binding protein). Conclusions A distinct proteomic profile of inflamed tissue in UC patients was found. Specific proteins involved in energy metabolism and oxidative stress were identified as potential candidate markers for UC. PMID:22726388

RNA Expression Profiles from Blood for the Diagnosis of Stroke and its Causes

PubMed Central

Sharp, Frank R; Jickling, Glen C; Stamova, Boryana; Tian, Yingfang; Zhan, Xinhua; Ander, Bradley P; Cox, Christopher; Kuczynski, Beth; Liu, DaZhi

2013-01-01

A blood test to detect stroke and its causes would be particularly useful in babies, young children, and patients in intensive care units, and for emergencies when imaging is difficult to obtain or unavailable. Using whole genome microarrays, we first showed specific gene expression profiles in rats 24 hours after ischemic and hemorrhagic stroke, hypoxia, and hypoglycemia. These proof-of-principle studies revealed that groups of genes (called gene profiles) can distinguish ischemic stroke patients from controls 3 hours to 24 hours after the strokes. In addition, gene expression profiles have been developed that distinguish stroke due to large-vessel atherosclerosis from cardioembolic stroke. These profiles will be useful for predicting the causes of cryptogenic stroke. Our results in adults suggest similar diagnostic tools could be developed for children. PMID:21636778

Identifying profiles of actual and perceived motor competence among adolescents: associations with motivation, physical activity, and sports participation.

PubMed

De Meester, An; Maes, Jolien; Stodden, David; Cardon, Greet; Goodway, Jacqueline; Lenoir, Matthieu; Haerens, Leen

2016-11-01

The present study identified adolescents' motor competence (MC)-based profiles (e.g., high actual and low perceived MC), and accordingly investigated differences in motivation for physical education (PE), physical activity (PA) levels, and sports participation between profiles by using regression analyses. Actual MC was measured with the Körperkoordinationstest für Kinder. Adolescents (n = 215; 66.0% boys; mean age = 13.64 ± .58 years) completed validated questionnaires to assess perceived MC, motivation for PE, PA-levels, and sports participation. Actual and perceived MC were only moderately correlated and cluster analyses identified four groups. Two groups of overestimators (low - overestimation, average - overestimation) were identified (51%), who particularly displayed better motivation for PE when compared to their peers who accurately estimated themselves (low - accurate, average - accurate). Moreover, adolescents with low actual MC, but high perceived MC were significantly more active than adolescents with low actual MC who accurately estimated themselves. Results pointed in the same direction for organised sports participation. Underestimators were not found in the current sample, which is positive as underestimation might negatively influence adolescents' motivation to achieve and persist in PA and sports. In conclusion, results emphasise that developing perceived MC, especially among adolescents with low levels of actual MC, seems crucial to stimulate motivation for PE, and engagement in PA and sports.

Gene-expression profiling for rejection surveillance after cardiac transplantation.

PubMed

Pham, Michael X; Teuteberg, Jeffrey J; Kfoury, Abdallah G; Starling, Randall C; Deng, Mario C; Cappola, Thomas P; Kao, Andrew; Anderson, Allen S; Cotts, William G; Ewald, Gregory A; Baran, David A; Bogaev, Roberta C; Elashoff, Barbara; Baron, Helen; Yee, James; Valantine, Hannah A

2010-05-20

Endomyocardial biopsy is the standard method of monitoring for rejection in recipients of a cardiac transplant. However, this procedure is uncomfortable, and there are risks associated with it. Gene-expression profiling of peripheral-blood specimens has been shown to correlate with the results of an endomyocardial biopsy. We randomly assigned 602 patients who had undergone cardiac transplantation 6 months to 5 years previously to be monitored for rejection with the use of gene-expression profiling or with the use of routine endomyocardial biopsies, in addition to clinical and echocardiographic assessment of graft function. We performed a noninferiority comparison of the two approaches with respect to the composite primary outcome of rejection with hemodynamic compromise, graft dysfunction due to other causes, death, or retransplantation. During a median follow-up period of 19 months, patients who were monitored with gene-expression profiling and those who underwent routine biopsies had similar 2-year cumulative rates of the composite primary outcome (14.5% and 15.3%, respectively; hazard ratio with gene-expression profiling, 1.04; 95% confidence interval, 0.67 to 1.68). The 2-year rates of death from any cause were also similar in the two groups (6.3% and 5.5%, respectively; P=0.82). Patients who were monitored with the use of gene-expression profiling underwent fewer biopsies per person-year of follow-up than did patients who were monitored with the use of endomyocardial biopsies (0.5 vs. 3.0, P<0.001). Among selected patients who had received a cardiac transplant more than 6 months previously and who were at a low risk for rejection, a strategy of monitoring for rejection that involved gene-expression profiling, as compared with routine biopsies, was not associated with an increased risk of serious adverse outcomes and resulted in the performance of significantly fewer biopsies. (ClinicalTrials.gov number, NCT00351559.) 2010 Massachusetts Medical Society

Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project.

PubMed

Gerstein, Mark B; Lu, Zhi John; Van Nostrand, Eric L; Cheng, Chao; Arshinoff, Bradley I; Liu, Tao; Yip, Kevin Y; Robilotto, Rebecca; Rechtsteiner, Andreas; Ikegami, Kohta; Alves, Pedro; Chateigner, Aurelien; Perry, Marc; Morris, Mitzi; Auerbach, Raymond K; Feng, Xin; Leng, Jing; Vielle, Anne; Niu, Wei; Rhrissorrakrai, Kahn; Agarwal, Ashish; Alexander, Roger P; Barber, Galt; Brdlik, Cathleen M; Brennan, Jennifer; Brouillet, Jeremy Jean; Carr, Adrian; Cheung, Ming-Sin; Clawson, Hiram; Contrino, Sergio; Dannenberg, Luke O; Dernburg, Abby F; Desai, Arshad; Dick, Lindsay; Dosé, Andréa C; Du, Jiang; Egelhofer, Thea; Ercan, Sevinc; Euskirchen, Ghia; Ewing, Brent; Feingold, Elise A; Gassmann, Reto; Good, Peter J; Green, Phil; Gullier, Francois; Gutwein, Michelle; Guyer, Mark S; Habegger, Lukas; Han, Ting; Henikoff, Jorja G; Henz, Stefan R; Hinrichs, Angie; Holster, Heather; Hyman, Tony; Iniguez, A Leo; Janette, Judith; Jensen, Morten; Kato, Masaomi; Kent, W James; Kephart, Ellen; Khivansara, Vishal; Khurana, Ekta; Kim, John K; Kolasinska-Zwierz, Paulina; Lai, Eric C; Latorre, Isabel; Leahey, Amber; Lewis, Suzanna; Lloyd, Paul; Lochovsky, Lucas; Lowdon, Rebecca F; Lubling, Yaniv; Lyne, Rachel; MacCoss, Michael; Mackowiak, Sebastian D; Mangone, Marco; McKay, Sheldon; Mecenas, Desirea; Merrihew, Gennifer; Miller, David M; Muroyama, Andrew; Murray, John I; Ooi, Siew-Loon; Pham, Hoang; Phippen, Taryn; Preston, Elicia A; Rajewsky, Nikolaus; Rätsch, Gunnar; Rosenbaum, Heidi; Rozowsky, Joel; Rutherford, Kim; Ruzanov, Peter; Sarov, Mihail; Sasidharan, Rajkumar; Sboner, Andrea; Scheid, Paul; Segal, Eran; Shin, Hyunjin; Shou, Chong; Slack, Frank J; Slightam, Cindie; Smith, Richard; Spencer, William C; Stinson, E O; Taing, Scott; Takasaki, Teruaki; Vafeados, Dionne; Voronina, Ksenia; Wang, Guilin; Washington, Nicole L; Whittle, Christina M; Wu, Beijing; Yan, Koon-Kiu; Zeller, Georg; Zha, Zheng; Zhong, Mei; Zhou, Xingliang; Ahringer, Julie; Strome, Susan; Gunsalus, Kristin C; Micklem, Gos; Liu, X Shirley; Reinke, Valerie; Kim, Stuart K; Hillier, LaDeana W; Henikoff, Steven; Piano, Fabio; Snyder, Michael; Stein, Lincoln; Lieb, Jason D; Waterston, Robert H

2010-12-24

We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor-binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor-binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.

Measurement of the configuration of a concave surface by the interference of reflected light

NASA Technical Reports Server (NTRS)

Kumazawa, T.; Sakamoto, T.; Shida, S.

1985-01-01

A method whereby a concave surface is irradiated with coherent light and the resulting interference fringes yield information on the concave surface is described. This method can be applied to a surface which satisfies the following conditions: (1) the concave face has a mirror surface; (2) the profile of the face is expressed by a mathematical function with a point of inflection. In this interferometry, multilight waves reflected from the concave surface interfere and make fringes wherever the reflected light propagates. Interference fringe orders. Photographs of the fringe patterns for a uniformly loaded thin silicon plate clamped at the edge are shown experimentally. The experimental and the theoretical values of the maximum optical path difference show good agreement. This simple method can be applied to obtain accurate information on concave surfaces.

Refractive index dispersion sensing using an array of photonic crystal resonant reflectors

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

Hermannsson, Pétur G.; Vannahme, Christoph; Smith, Cameron L. C.

2015-08-10

Refractive index sensing plays a key role in various environmental and biological sensing applications. Here, a method is presented for measuring the absolute refractive index dispersion of liquids using an array of photonic crystal resonant reflectors of varying periods. It is shown that by covering the array with a sample liquid and measuring the resonance wavelength associated with transverse electric polarized quasi guided modes as a function of period, the refractive index dispersion of the liquid can be accurately obtained using an analytical expression. This method is compact, can perform measurements at arbitrary number of wavelengths, and requires only amore » minute sample volume. The ability to sense a material's dispersion profile offers an added dimension of information that may be of benefit to optofluidic lab-on-a-chip applications.« less

Investigating the Receptive-Expressive Vocabulary Profile in Children with Idiopathic ASD and Comorbid ASD and Fragile X Syndrome

ERIC Educational Resources Information Center

Haebig, Eileen; Sterling, Audra

2017-01-01

Previous work has noted that some children with autism spectrum disorder (ASD) display weaknesses in receptive vocabulary relative to expressive vocabulary abilities. The current study extended previous work by examining the receptive-expressive vocabulary profile in boys with idiopathic ASD and boys with concomitant ASD and fragile X syndrome…

Accurate Identification of Fear Facial Expressions Predicts Prosocial Behavior

PubMed Central

Marsh, Abigail A.; Kozak, Megan N.; Ambady, Nalini

2009-01-01

The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants’ ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale. PMID:17516803

Accurate identification of fear facial expressions predicts prosocial behavior.

PubMed

Marsh, Abigail A; Kozak, Megan N; Ambady, Nalini

2007-05-01

The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants' ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale.

Characterization of the transcriptome profiles related to globin gene switching during in vitro erythroid maturation

PubMed Central

2012-01-01

Background The fetal and adult globin genes in the human β-globin cluster on chromosome 11 are sequentially expressed to achieve normal hemoglobin switching during human development. The pharmacological induction of fetal γ-globin (HBG) to replace abnormal adult sickle βS-globin is a successful strategy to treat sickle cell disease; however the molecular mechanism of γ-gene silencing after birth is not fully understood. Therefore, we performed global gene expression profiling using primary erythroid progenitors grown from human peripheral blood mononuclear cells to characterize gene expression patterns during the γ-globin to β-globin (γ/β) switch observed throughout in vitro erythroid differentiation. Results We confirmed erythroid maturation in our culture system using cell morphologic features defined by Giemsa staining and the γ/β-globin switch by reverse transcription-quantitative PCR (RT-qPCR) analysis. We observed maximal γ-globin expression at day 7 with a switch to a predominance of β-globin expression by day 28 and the γ/β-globin switch occurred around day 21. Expression patterns for transcription factors including GATA1, GATA2, KLF1 and NFE2 confirmed our system produced the expected pattern of expression based on the known function of these factors in globin gene regulation. Subsequent gene expression profiling was performed with RNA isolated from progenitors harvested at day 7, 14, 21, and 28 in culture. Three major gene profiles were generated by Principal Component Analysis (PCA). For profile-1 genes, where expression decreased from day 7 to day 28, we identified 2,102 genes down-regulated > 1.5-fold. Ingenuity pathway analysis (IPA) for profile-1 genes demonstrated involvement of the Cdc42, phospholipase C, NF-Kβ, Interleukin-4, and p38 mitogen activated protein kinase (MAPK) signaling pathways. Transcription factors known to be involved in γ-and β-globin regulation were identified. The same approach was used to generate profile-2 genes where expression was up-regulated over 28 days in culture. IPA for the 2,437 genes with > 1.5-fold induction identified the mitotic roles of polo-like kinase, aryl hydrocarbon receptor, cell cycle control, and ATM (Ataxia Telangiectasia Mutated Protein) signaling pathways; transcription factors identified included KLF1, GATA1 and NFE2 among others. Finally, profile-3 was generated from 1,579 genes with maximal expression at day 21, around the time of the γ/β-globin switch. IPA identified associations with cell cycle control, ATM, and aryl hydrocarbon receptor signaling pathways. Conclusions The transcriptome analysis completed with erythroid progenitors grown in vitro identified groups of genes with distinct expression profiles, which function in metabolic pathways associated with cell survival, hematopoiesis, blood cells activation, and inflammatory responses. This study represents the first report of a transcriptome analysis in human primary erythroid progenitors to identify transcription factors involved in hemoglobin switching. Our results also demonstrate that the in vitro liquid culture system is an excellent model to define mechanisms of global gene expression and the DNA-binding protein and signaling pathways involved in globin gene regulation. PMID:22537182

MicroRNA expression profiling during the life cycle of the silkworm (Bombyx mori)

PubMed Central

Liu, Shiping; Zhang, Liang; Li, Qibin; Zhao, Ping; Duan, Jun; Cheng, Daojun; Xiang, Zhonghuai; Xia, Qingyou

2009-01-01

Background MicroRNAs (miRNAs) are expressed by a wide range of eukaryotic organisms, and function in diverse biological processes. Numerous miRNAs have been identified in Bombyx mori, but the temporal expression profiles of miRNAs corresponding to each stage transition over the entire life cycle of the silkworm remain to be established. To obtain a comprehensive overview of the correlation between miRNA expression and stage transitions, we performed a whole-life test and subsequent stage-by-stage examinations on nearly one hundred miRNAs in the silkworm. Results Our results show that miRNAs display a wide variety of expression profiles over the whole life of the silkworm, including continuous expression from embryo to adult (miR-184), up-regulation over the entire life cycle (let-7 and miR-100), down-regulation over the entire life cycle (miR-124), expression associated with embryogenesis (miR-29 and miR-92), up-regulation from early 3rd instar to pupa (miR-275), and complementary pulses in expression between miR-34b and miR-275. Stage-by-stage examinations revealed further expression patterns, such as emergence at specific time-points during embryogenesis and up-regulation of miRNA groups in late embryos (miR-1 and bantam), expression associated with stage transition between instar and molt larval stages (miR-34b), expression associated with silk gland growth and spinning activity (miR-274), continuous high expression from the spinning larval to pupal and adult stages (miR-252 and miR-31a), a coordinate expression trough in day 3 pupae of both sexes (miR-10b and miR-281), up-regulation in pupal metamorphosis of both sexes (miR-29b), and down-regulation in pupal metamorphosis of both sexes (miR-275). Conclusion We present the full-scale expression profiles of miRNAs throughout the life cycle of Bombyx mori. The whole-life expression profile was further investigated via stage-by-stage analysis. Our data provide an important resource for more detailed functional analysis of miRNAs in this animal. PMID:19785751

MicroRNA expression profiling during the life cycle of the silkworm (Bombyx mori).

PubMed

Liu, Shiping; Zhang, Liang; Li, Qibin; Zhao, Ping; Duan, Jun; Cheng, Daojun; Xiang, Zhonghuai; Xia, Qingyou

2009-09-28

MicroRNAs (miRNAs) are expressed by a wide range of eukaryotic organisms, and function in diverse biological processes. Numerous miRNAs have been identified in Bombyx mori, but the temporal expression profiles of miRNAs corresponding to each stage transition over the entire life cycle of the silkworm remain to be established. To obtain a comprehensive overview of the correlation between miRNA expression and stage transitions, we performed a whole-life test and subsequent stage-by-stage examinations on nearly one hundred miRNAs in the silkworm. Our results show that miRNAs display a wide variety of expression profiles over the whole life of the silkworm, including continuous expression from embryo to adult (miR-184), up-regulation over the entire life cycle (let-7 and miR-100), down-regulation over the entire life cycle (miR-124), expression associated with embryogenesis (miR-29 and miR-92), up-regulation from early 3rd instar to pupa (miR-275), and complementary pulses in expression between miR-34b and miR-275. Stage-by-stage examinations revealed further expression patterns, such as emergence at specific time-points during embryogenesis and up-regulation of miRNA groups in late embryos (miR-1 and bantam), expression associated with stage transition between instar and molt larval stages (miR-34b), expression associated with silk gland growth and spinning activity (miR-274), continuous high expression from the spinning larval to pupal and adult stages (miR-252 and miR-31a), a coordinate expression trough in day 3 pupae of both sexes (miR-10b and miR-281), up-regulation in pupal metamorphosis of both sexes (miR-29b), and down-regulation in pupal metamorphosis of both sexes (miR-275). We present the full-scale expression profiles of miRNAs throughout the life cycle of Bombyx mori. The whole-life expression profile was further investigated via stage-by-stage analysis. Our data provide an important resource for more detailed functional analysis of miRNAs in this animal.

Distinct profiles of expressed sequence tags during intestinal regeneration in the sea cucumber Holothuria glaberrima

PubMed Central

Rojas-Cartagena, Carmencita; Ortíz-Pineda, Pablo; Ramírez-Gómez, Francisco; Suárez-Castillo, Edna C.; Matos-Cruz, Vanessa; Rodríguez, Carlos; Ortíz-Zuazaga, Humberto; García-Arrarás, José E.

2010-01-01

Repair and regeneration are key processes for tissue maintenance, and their disruption may lead to disease states. Little is known about the molecular mechanisms that underline the repair and regeneration of the digestive tract. The sea cucumber Holothuria glaberrima represents an excellent model to dissect and characterize the molecular events during intestinal regeneration. To study the gene expression profile, cDNA libraries were constructed from normal, 3-day, and 7-day regenerating intestines of H. glaberrima. Clones were randomly sequenced and queried against the nonredundant protein database at the National Center for Biotechnology Information. RT-PCR analyses were made of several genes to determine their expression profile during intestinal regeneration. A total of 5,173 sequences from three cDNA libraries were obtained. About 46.2, 35.6, and 26.2% of the sequences for the normal, 3-days, and 7-days cDNA libraries, respectively, shared significant similarity with known sequences in the protein database of GenBank but only present 10% of similarity among them. Analysis of the libraries in terms of functional processes, protein domains, and most common sequences suggests that a differential expression profile is taking place during the regeneration process. Further examination of the expressed sequence tag dataset revealed that 12 putative genes are differentially expressed at significant level (R > 6). Experimental validation by RT-PCR analysis reveals that at least three genes (unknown C-4677-1, melanotransferrin, and centaurin) present a differential expression during regeneration. These findings strongly suggest that the gene expression profile varies among regeneration stages and provide evidence for the existence of differential gene expression. PMID:17579180

Behaviorally activated mRNA expression profiles produce signatures of learning and enhanced inhibition in aged rats with preserved memory.

PubMed

Haberman, Rebecca P; Colantuoni, Carlo; Koh, Ming Teng; Gallagher, Michela

2013-01-01

Aging is often associated with cognitive decline, but many elderly individuals maintain a high level of function throughout life. Here we studied outbred rats, which also exhibit individual differences across a spectrum of outcomes that includes both preserved and impaired spatial memory. Previous work in this model identified the CA3 subfield of the hippocampus as a region critically affected by age and integral to differing cognitive outcomes. Earlier microarray profiling revealed distinct gene expression profiles in the CA3 region, under basal conditions, for aged rats with intact memory and those with impairment. Because prominent age-related deficits within the CA3 occur during neural encoding of new information, here we used microarray analysis to gain a broad perspective of the aged CA3 transcriptome under activated conditions. Behaviorally-induced CA3 expression profiles differentiated aged rats with intact memory from those with impaired memory. In the activated profile, we observed substantial numbers of genes (greater than 1000) exhibiting increased expression in aged unimpaired rats relative to aged impaired, including many involved in synaptic plasticity and memory mechanisms. This unimpaired aged profile also overlapped significantly with a learning induced gene profile previously acquired in young adults. Alongside the increased transcripts common to both young learning and aged rats with preserved memory, many transcripts behaviorally-activated in the current study had previously been identified as repressed in the aged unimpaired phenotype in basal expression. A further distinct feature of the activated profile of aged rats with intact memory is the increased expression of an ensemble of genes involved in inhibitory synapse function, which could control the phenotype of neural hyperexcitability found in the CA3 region of aged impaired rats. These data support the conclusion that aged subjects with preserved memory recruit adaptive mechanisms to retain tight control over excitability under both basal and activated conditions.

High-coverage methylation data of a gene model before and after DNA damage and homologous repair.

PubMed

Pezone, Antonio; Russo, Giusi; Tramontano, Alfonso; Florio, Ermanno; Scala, Giovanni; Landi, Rosaria; Zuchegna, Candida; Romano, Antonella; Chiariotti, Lorenzo; Muller, Mark T; Gottesman, Max E; Porcellini, Antonio; Avvedimento, Enrico V

2017-04-11

Genome-wide methylation analysis is limited by its low coverage and the inability to detect single variants below 10%. Quantitative analysis provides accurate information on the extent of methylation of single CpG dinucleotide, but it does not measure the actual polymorphism of the methylation profiles of single molecules. To understand the polymorphism of DNA methylation and to decode the methylation signatures before and after DNA damage and repair, we have deep sequenced in bisulfite-treated DNA a reporter gene undergoing site-specific DNA damage and homologous repair. In this paper, we provide information on the data generation, the rationale for the experiments and the type of assays used, such as cytofluorimetry and immunoblot data derived during a previous work published in Scientific Reports, describing the methylation and expression changes of a model gene (GFP) before and after formation of a double-strand break and repair by homologous-recombination or non-homologous-end-joining. These data provide: 1) a reference for the analysis of methylation polymorphism at selected loci in complex cell populations; 2) a platform and the tools to compare transcription and methylation profiles.

High-coverage methylation data of a gene model before and after DNA damage and homologous repair

PubMed Central

Pezone, Antonio; Russo, Giusi; Tramontano, Alfonso; Florio, Ermanno; Scala, Giovanni; Landi, Rosaria; Zuchegna, Candida; Romano, Antonella; Chiariotti, Lorenzo; Muller, Mark T.; Gottesman, Max E.; Porcellini, Antonio; Avvedimento, Enrico V.

2017-01-01

Genome-wide methylation analysis is limited by its low coverage and the inability to detect single variants below 10%. Quantitative analysis provides accurate information on the extent of methylation of single CpG dinucleotide, but it does not measure the actual polymorphism of the methylation profiles of single molecules. To understand the polymorphism of DNA methylation and to decode the methylation signatures before and after DNA damage and repair, we have deep sequenced in bisulfite-treated DNA a reporter gene undergoing site-specific DNA damage and homologous repair. In this paper, we provide information on the data generation, the rationale for the experiments and the type of assays used, such as cytofluorimetry and immunoblot data derived during a previous work published in Scientific Reports, describing the methylation and expression changes of a model gene (GFP) before and after formation of a double-strand break and repair by homologous-recombination or non-homologous-end-joining. These data provide: 1) a reference for the analysis of methylation polymorphism at selected loci in complex cell populations; 2) a platform and the tools to compare transcription and methylation profiles. PMID:28398335

Dipole saturated absorption modeling in gas phase: Dealing with a Gaussian beam

NASA Astrophysics Data System (ADS)

Dupré, Patrick

2018-01-01

With the advent of new accurate and sensitive spectrometers, cf. combining optical cavities (for absorption enhancement), the requirement for reliable molecular transition modeling is becoming more pressing. Unfortunately, there is no trivial approach which can provide a definitive formalism allowing us to solve the coupled systems of equations associated with nonlinear absorption. Here, we propose a general approach to deal with any spectral shape of the electromagnetic field interacting with a molecular species under saturation conditions. The development is specifically applied to Gaussian-shaped beams. To make the analytical expressions tractable, approximations are proposed. Finally, two or three numerical integrations are required for describing the Lamb-dip profile. The implemented model allows us to describe the saturated absorption under low pressure conditions where the broadening by the transit-time may dominate the collision rates. The model is applied to two specific overtone transitions of the molecular acetylene. The simulated line shapes are discussed versus the collision and the transit-time rates. The specific collisional and collision-free regimes are illustrated, while the Rabi frequency controls the intermediate regime. We illustrate how to recover the input parameters by fitting the simulated profiles.

Comparative bioinformatics analyses and profiling of lysosome-related organelle proteomes

NASA Astrophysics Data System (ADS)

Hu, Zhang-Zhi; Valencia, Julio C.; Huang, Hongzhan; Chi, An; Shabanowitz, Jeffrey; Hearing, Vincent J.; Appella, Ettore; Wu, Cathy

2007-01-01

Complete and accurate profiling of cellular organelle proteomes, while challenging, is important for the understanding of detailed cellular processes at the organelle level. Mass spectrometry technologies coupled with bioinformatics analysis provide an effective approach for protein identification and functional interpretation of organelle proteomes. In this study, we have compiled human organelle reference datasets from large-scale proteomic studies and protein databases for seven lysosome-related organelles (LROs), as well as the endoplasmic reticulum and mitochondria, for comparative organelle proteome analysis. Heterogeneous sources of human organelle proteins and rodent homologs are mapped to human UniProtKB protein entries based on ID and/or peptide mappings, followed by functional annotation and categorization using the iProXpress proteomic expression analysis system. Cataloging organelle proteomes allows close examination of both shared and unique proteins among various LROs and reveals their functional relevance. The proteomic comparisons show that LROs are a closely related family of organelles. The shared proteins indicate the dynamic and hybrid nature of LROs, while the unique transmembrane proteins may represent additional candidate marker proteins for LROs. This comparative analysis, therefore, provides a basis for hypothesis formulation and experimental validation of organelle proteins and their functional roles.

Gene Expression Profiling of Monkeypox Virus-Infected Cells Reveals Novel Interfaces for Host-Virus Interactions

DTIC Science & Technology

2010-07-28

expression is plotted on Y -axis after normalization to mock-treated samples. Results plotted to compare calculated fold change in expression of each gene ...RESEARCH Open Access Gene expression profiling of monkeypox virus-infected cells reveals novel interfaces for host-virus interactions Abdulnaser...suppress antiviral cell defenses, exploit host cell machinery, and delay infection-induced cell death. However, a comprehensive study of all host genes

Network-Induced Classification Kernels for Gene Expression Profile Analysis

PubMed Central

Dror, Gideon; Shamir, Ron

2012-01-01

Abstract Computational classification of gene expression profiles into distinct disease phenotypes has been highly successful to date. Still, robustness, accuracy, and biological interpretation of the results have been limited, and it was suggested that use of protein interaction information jointly with the expression profiles can improve the results. Here, we study three aspects of this problem. First, we show that interactions are indeed relevant by showing that co-expressed genes tend to be closer in the network of interactions. Second, we show that the improved performance of one extant method utilizing expression and interactions is not really due to the biological information in the network, while in another method this is not the case. Finally, we develop a new kernel method—called NICK—that integrates network and expression data for SVM classification, and demonstrate that overall it achieves better results than extant methods while running two orders of magnitude faster. PMID:22697242

Decomposition Odour Profiling in the Air and Soil Surrounding Vertebrate Carrion

PubMed Central

2014-01-01

Chemical profiling of decomposition odour is conducted in the environmental sciences to detect malodourous target sources in air, water or soil. More recently decomposition odour profiling has been employed in the forensic sciences to generate a profile of the volatile organic compounds (VOCs) produced by decomposed remains. The chemical profile of decomposition odour is still being debated with variations in the VOC profile attributed to the sample collection technique, method of chemical analysis, and environment in which decomposition occurred. To date, little consideration has been given to the partitioning of odour between different matrices and the impact this has on developing an accurate VOC profile. The purpose of this research was to investigate the decomposition odour profile surrounding vertebrate carrion to determine how VOCs partition between soil and air. Four pig carcasses (Sus scrofa domesticus L.) were placed on a soil surface to decompose naturally and their odour profile monitored over a period of two months. Corresponding control sites were also monitored to determine the VOC profile of the surrounding environment. Samples were collected from the soil below and the air (headspace) above the decomposed remains using sorbent tubes and analysed using gas chromatography-mass spectrometry. A total of 249 compounds were identified but only 58 compounds were common to both air and soil samples. This study has demonstrated that soil and air samples produce distinct subsets of VOCs that contribute to the overall decomposition odour. Sample collection from only one matrix will reduce the likelihood of detecting the complete spectrum of VOCs, which further confounds the issue of determining a complete and accurate decomposition odour profile. Confirmation of this profile will enhance the performance of cadaver-detection dogs that are tasked with detecting decomposition odour in both soil and air to locate victim remains. PMID:24740412

Decomposition odour profiling in the air and soil surrounding vertebrate carrion.

PubMed

Forbes, Shari L; Perrault, Katelynn A

2014-01-01

Chemical profiling of decomposition odour is conducted in the environmental sciences to detect malodourous target sources in air, water or soil. More recently decomposition odour profiling has been employed in the forensic sciences to generate a profile of the volatile organic compounds (VOCs) produced by decomposed remains. The chemical profile of decomposition odour is still being debated with variations in the VOC profile attributed to the sample collection technique, method of chemical analysis, and environment in which decomposition occurred. To date, little consideration has been given to the partitioning of odour between different matrices and the impact this has on developing an accurate VOC profile. The purpose of this research was to investigate the decomposition odour profile surrounding vertebrate carrion to determine how VOCs partition between soil and air. Four pig carcasses (Sus scrofa domesticus L.) were placed on a soil surface to decompose naturally and their odour profile monitored over a period of two months. Corresponding control sites were also monitored to determine the VOC profile of the surrounding environment. Samples were collected from the soil below and the air (headspace) above the decomposed remains using sorbent tubes and analysed using gas chromatography-mass spectrometry. A total of 249 compounds were identified but only 58 compounds were common to both air and soil samples. This study has demonstrated that soil and air samples produce distinct subsets of VOCs that contribute to the overall decomposition odour. Sample collection from only one matrix will reduce the likelihood of detecting the complete spectrum of VOCs, which further confounds the issue of determining a complete and accurate decomposition odour profile. Confirmation of this profile will enhance the performance of cadaver-detection dogs that are tasked with detecting decomposition odour in both soil and air to locate victim remains.

Alkaloid profiling of the traditional Chinese medicine Rhizoma corydalis using high performance liquid chromatography-tandem quadrupole time-of-flight mass spectrometry

PubMed Central

Sun, Mingqian; Liu, Jianxun; Lin, Chengren; Miao, Lan; Lin, Li

2014-01-01

Since alkaloids are the major active constituents of Rhizoma corydalis (RC), a convenient and accurate analytical method is needed for their identification and characterization. Here we report a method to profile the alkaloids in RC based on liquid chromatography-tandem quadrupole time-of-flight mass spectrometry (LC–Q-TOF-MS/MS). A total of 16 alkaloids belonging to four different classes were identified by comparison with authentic standards. The fragmentation pathway of each class of alkaloid was clarified and their differences were elucidated. Furthermore, based on an analysis of fragmentation pathways and alkaloid profiling, a rapid and accurate method for the identification of unknown alkaloids in RC is proposed. The method could also be useful for the quality control of RC. PMID:26579385

Cellular and molecular maturation in fetal and adult ovine calcaneal tendons

PubMed Central

Russo, Valentina; Mauro, Annunziata; Martelli, Alessandra; Di Giacinto, Oriana; Di Marcantonio, Lisa; Nardinocchi, Delia; Berardinelli, Paolo; Barboni, Barbara

2015-01-01

Processes of development during fetal life profoundly transform tendons from a plastic tissue into a highly differentiated structure, characterised by a very low ability to regenerate after injury in adulthood. Sheep tendon is frequently used as a translational model to investigate cell-based regenerative approaches. However, in contrast to other species, analytical and comparative baseline studies on the normal developmental maturation of sheep tendons from fetal through to adult life are not currently available. Thus, a detailed morphological and biochemical study was designed to characterise tissue maturation during mid- (2 months of pregnancy: 14 cm of length) and late fetal (4 months: 40 cm of length) life, through to adulthood. The results confirm that ovine tendon morphology undergoes profound transformations during this period. Endotenon was more developed in fetal tendons than in adult tissues, and its cell phenotype changed through tendon maturation. Indeed, groups of large rounded cells laying on smaller and more compacted ones expressing osteocalcin, vascular endothelial growth factor (VEGF) and nerve growth factor (NGF) were identified exclusively in fetal mid-stage tissues, and not in late fetal or adult tendons. VEGF, NGF as well as blood vessels and nerve fibers showed decreased expression during tendon development. Moreover, the endotenon of mid- and late fetuses contained identifiable cells that expressed several pluripotent stem cell markers [Telomerase Reverse Transcriptase (TERT), SRY Determining Region Y Box-2 (SOX2), Nanog Homeobox (NANOG) and Octamer Binding Transcription Factor-4A (OCT-4A)]. These cells were not identifiable in adult specimens. Ovine tendon development was also accompanied by morphological modifications to cell nuclei, and a progressive decrease in cellularity, proliferation index and expression of connexins 43 and 32. Tendon maturation was similarly characterised by modulation of several other gene expression profiles, including Collagen type I, Collagen type III, Scleraxis B, Tenomodulin, Trombospondin 4 and Osteocalcin. These gene profiles underwent a dramatic reduction in adult tissues. Transforming growth factor-1 expression (involved in collagen synthesis) underwent a similar decrease. In conclusion, these morphological studies carried out on sheep tendons at different stages of development and aging offer normal structural and molecular baseline data to allow accurate evaluation of data from subsequent interventional studies investigating tendon healing and regeneration in ovine experimental models. PMID:25546075

Integrated analysis of numerous heterogeneous gene expression profiles for detecting robust disease-specific biomarkers and proposing drug targets.

PubMed

Amar, David; Hait, Tom; Izraeli, Shai; Shamir, Ron

2015-09-18

Genome-wide expression profiling has revolutionized biomedical research; vast amounts of expression data from numerous studies of many diseases are now available. Making the best use of this resource in order to better understand disease processes and treatment remains an open challenge. In particular, disease biomarkers detected in case-control studies suffer from low reliability and are only weakly reproducible. Here, we present a systematic integrative analysis methodology to overcome these shortcomings. We assembled and manually curated more than 14,000 expression profiles spanning 48 diseases and 18 expression platforms. We show that when studying a particular disease, judicious utilization of profiles from other diseases and information on disease hierarchy improves classification quality, avoids overoptimistic evaluation of that quality, and enhances disease-specific biomarker discovery. This approach yielded specific biomarkers for 24 of the analyzed diseases. We demonstrate how to combine these biomarkers with large-scale interaction, mutation and drug target data, forming a highly valuable disease summary that suggests novel directions in disease understanding and drug repurposing. Our analysis also estimates the number of samples required to reach a desired level of biomarker stability. This methodology can greatly improve the exploitation of the mountain of expression profiles for better disease analysis. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Modelling gene expression profiles related to prostate tumor progression using binary states

PubMed Central

2013-01-01

Background Cancer is a complex disease commonly characterized by the disrupted activity of several cancer-related genes such as oncogenes and tumor-suppressor genes. Previous studies suggest that the process of tumor progression to malignancy is dynamic and can be traced by changes in gene expression. Despite the enormous efforts made for differential expression detection and biomarker discovery, few methods have been designed to model the gene expression level to tumor stage during malignancy progression. Such models could help us understand the dynamics and simplify or reveal the complexity of tumor progression. Methods We have modeled an on-off state of gene activation per sample then per stage to select gene expression profiles associated to tumor progression. The selection is guided by statistical significance of profiles based on random permutated datasets. Results We show that our method identifies expected profiles corresponding to oncogenes and tumor suppressor genes in a prostate tumor progression dataset. Comparisons with other methods support our findings and indicate that a considerable proportion of significant profiles is not found by other statistical tests commonly used to detect differential expression between tumor stages nor found by other tailored methods. Ontology and pathway analysis concurred with these findings. Conclusions Results suggest that our methodology may be a valuable tool to study tumor malignancy progression, which might reveal novel cancer therapies. PMID:23721350

Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

NASA Astrophysics Data System (ADS)

Schwarz, Jakob; Kirchengast, Gottfried; Schwaerz, Marc

2018-05-01

Global Navigation Satellite System (GNSS) radio occultation (RO) observations are highly accurate, long-term stable data sets and are globally available as a continuous record from 2001. Essential climate variables for the thermodynamic state of the free atmosphere - such as pressure, temperature, and tropospheric water vapor profiles (involving background information) - can be derived from these records, which therefore have the potential to serve as climate benchmark data. However, to exploit this potential, atmospheric profile retrievals need to be very accurate and the remaining uncertainties quantified and traced throughout the retrieval chain from raw observations to essential climate variables. The new Reference Occultation Processing System (rOPS) at the Wegener Center aims to deliver such an accurate RO retrieval chain with integrated uncertainty propagation. Here we introduce and demonstrate the algorithms implemented in the rOPS for uncertainty propagation from excess phase to atmospheric bending angle profiles, for estimated systematic and random uncertainties, including vertical error correlations and resolution estimates. We estimated systematic uncertainty profiles with the same operators as used for the basic state profiles retrieval. The random uncertainty is traced through covariance propagation and validated using Monte Carlo ensemble methods. The algorithm performance is demonstrated using test day ensembles of simulated data as well as real RO event data from the satellite missions CHAllenging Minisatellite Payload (CHAMP); Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC); and Meteorological Operational Satellite A (MetOp). The results of the Monte Carlo validation show that our covariance propagation delivers correct uncertainty quantification from excess phase to bending angle profiles. The results from the real RO event ensembles demonstrate that the new uncertainty estimation chain performs robustly. Together with the other parts of the rOPS processing chain this part is thus ready to provide integrated uncertainty propagation through the whole RO retrieval chain for the benefit of climate monitoring and other applications.

Design and field tests of an access-tube soil water sensor

USDA-ARS?s Scientific Manuscript database

Accurate soil profile water content monitoring at multiple depths until now, has been possible only using the neutron probe (NP), but with great effort and at infrequent time intervals. Despite the existence of several electromagnetic sensor systems for profile water content measurements, accuracy ...

Regulation and Gene Expression Profiling of NKG2D Positive Human Cytomegalovirus-Primed CD4+ T-Cells

PubMed Central

Jensen, Helle; Folkersen, Lasse; Skov, Søren

2012-01-01

NKG2D is a stimulatory receptor expressed by natural killer (NK) cells, CD8+ T-cells, and γδ T-cells. NKG2D expression is normally absent from CD4+ T-cells, however recently a subset of NKG2D+ CD4+ T-cells has been found, which is specific for human cytomegalovirus (HCMV). This particular subset of HCMV-specific NKG2D+ CD4+ T-cells possesses effector-like functions, thus resembling the subsets of NKG2D+ CD4+ T-cells found in other chronic inflammations. However, the precise mechanism leading to NKG2D expression on HCMV-specific CD4+ T-cells is currently not known. In this study we used genome-wide analysis of individual genes and gene set enrichment analysis (GSEA) to investigate the gene expression profile of NKG2D+ CD4+ T-cells, generated from HCMV-primed CD4+ T-cells. We show that the HCMV-primed NKG2D+ CD4+ T-cells possess a higher differentiated phenotype than the NKG2D– CD4+ T-cells, both at the gene expression profile and cytokine profile. The ability to express NKG2D at the cell surface was primarily determined by the activation or differentiation status of the CD4+ T-cells and not by the antigen presenting cells. We observed a correlation between CD94 and NKG2D expression in the CD4+ T-cells following HCMV stimulation. However, knock-down of CD94 did not affect NKG2D cell surface expression or signaling. In addition, we show that NKG2D is recycled at the cell surface of activated CD4+ T-cells, whereas it is produced de novo in resting CD4+ T-cells. These findings provide novel information about the gene expression profile of HCMV-primed NKG2D+ CD4+ T-cells, as well as the mechanisms regulating NKG2D cell surface expression. PMID:22870231

Regulation and gene expression profiling of NKG2D positive human cytomegalovirus-primed CD4+ T-cells.

PubMed

Jensen, Helle; Folkersen, Lasse; Skov, Søren

2012-01-01

NKG2D is a stimulatory receptor expressed by natural killer (NK) cells, CD8(+) T-cells, and γδ T-cells. NKG2D expression is normally absent from CD4(+) T-cells, however recently a subset of NKG2D(+) CD4(+) T-cells has been found, which is specific for human cytomegalovirus (HCMV). This particular subset of HCMV-specific NKG2D(+) CD4(+) T-cells possesses effector-like functions, thus resembling the subsets of NKG2D(+) CD4(+) T-cells found in other chronic inflammations. However, the precise mechanism leading to NKG2D expression on HCMV-specific CD4(+) T-cells is currently not known. In this study we used genome-wide analysis of individual genes and gene set enrichment analysis (GSEA) to investigate the gene expression profile of NKG2D(+) CD4(+) T-cells, generated from HCMV-primed CD4(+) T-cells. We show that the HCMV-primed NKG2D(+) CD4(+) T-cells possess a higher differentiated phenotype than the NKG2D(-) CD4(+) T-cells, both at the gene expression profile and cytokine profile. The ability to express NKG2D at the cell surface was primarily determined by the activation or differentiation status of the CD4(+) T-cells and not by the antigen presenting cells. We observed a correlation between CD94 and NKG2D expression in the CD4(+) T-cells following HCMV stimulation. However, knock-down of CD94 did not affect NKG2D cell surface expression or signaling. In addition, we show that NKG2D is recycled at the cell surface of activated CD4(+) T-cells, whereas it is produced de novo in resting CD4(+) T-cells. These findings provide novel information about the gene expression profile of HCMV-primed NKG2D(+) CD4(+) T-cells, as well as the mechanisms regulating NKG2D cell surface expression.

CHANGES IN GENE EXPRESSION PROFILE FOLLOWING SHORT-TERM EXPOSURE TO AN ENVIRONMENTALLY RELEVANT MIXTURE OF PHAHS

EPA Science Inventory

Changes in gene expression profile following short-term exposure to an environmentally relevant mixture of PHAHs
Polyhalogenated aromatic hydrocarbons (PHAH) including, polychlorinated biphenyls (PCBs), polychlorinated dibenzodioxins (PCDDS) and polychlorinated dibenzofurans...

Uncovering Suitable Reference Proteins for Expression Studies in Human Adipose Tissue with Relevance to Obesity

PubMed Central

Pérez-Pérez, Rafael; López, Juan A.; García-Santos, Eva; Camafeita, Emilio; Gómez-Serrano, María; Ortega-Delgado, Francisco J.; Ricart, Wifredo; Fernández-Real, José M.; Peral, Belén

2012-01-01

Background Protein expression studies based on the two major intra-abdominal human fat depots, the subcutaneous and the omental fat, can shed light into the mechanisms involved in obesity and its co-morbidities. Here we address, for the first time, the identification and validation of reference proteins for data standardization, which are essential for accurate comparison of protein levels in expression studies based on fat from obese and non-obese individuals. Methodology and Findings To uncover adipose tissue proteins equally expressed either in omental and subcutaneous fat depots (study 1) or in omental fat from non-obese and obese individuals (study 2), we have reanalyzed our previously published data based on two-dimensional fluorescence difference gel electrophoresis. Twenty-four proteins (12 in study 1 and 12 in study 2) with similar expression levels in all conditions tested were selected and identified by mass spectrometry. Immunoblotting analysis was used to confirm in adipose tissue the expression pattern of the potential reference proteins and three proteins were validated: PARK7, ENOA and FAA. Western Blot analysis was also used to test customary loading control proteins. ENOA, PARK7 and the customary loading control protein Beta-actin showed steady expression profiles in fat from non-obese and obese individuals, whilst FAA maintained steady expression levels across paired omental and subcutaneous fat samples. Conclusions ENOA, PARK7 and Beta-actin are proper reference standards in obesity studies based on omental fat, whilst FAA is the best loading control for the comparative analysis of omental and subcutaneous adipose tissues either in obese and non-obese subjects. Neither customary loading control proteins GAPDH and TBB5 nor CALX are adequate standards in differential expression studies on adipose tissue. The use of the proposed reference proteins will facilitate the adequate analysis of proteins differentially expressed in the context of obesity, an aim difficult to achieve before this study. PMID:22272336

lpxC and yafS are the most suitable internal controls to normalize real time RT-qPCR expression in the phytopathogenic bacteria Dickeya dadantii.

PubMed

Hommais, Florence; Zghidi-Abouzid, Ouafa; Oger-Desfeux, Christine; Pineau-Chapelle, Emilie; Van Gijsegem, Frederique; Nasser, William; Reverchon, Sylvie

2011-01-01

Quantitative RT-PCR is the method of choice for studying, with both sensitivity and accuracy, the expression of genes. A reliable normalization of the data, using several reference genes, is critical for an accurate quantification of gene expression. Here, we propose a set of reference genes, of the phytopathogenic bacteria Dickeya dadantii and Pectobacterium atrosepticum, which are stable in a wide range of growth conditions. We extracted, from a D. dadantii micro-array transcript profile dataset comprising thirty-two different growth conditions, an initial set of 49 expressed genes with very low variation in gene expression. Out of these, we retained 10 genes representing different functional categories, different levels of expression (low, medium, and high) and with no systematic variation in expression correlating with growth conditions. We measured the expression of these reference gene candidates using quantitative RT-PCR in 50 different experimental conditions, mimicking the environment encountered by the bacteria in their host and directly during the infection process in planta. The two most stable genes (ABF-0017965 (lpxC) and ABF-0020529 (yafS) were successfully used for normalization of RT-qPCR data. Finally, we demonstrated that the ortholog of lpxC and yafS in Pectobacterium atrosepticum also showed stable expression in diverse growth conditions. We have identified at least two genes, lpxC (ABF-0017965) and yafS (ABF-0020509), whose expressions are stable in a wide range of growth conditions and during infection. Thus, these genes are considered suitable for use as reference genes for the normalization of real-time RT-qPCR data of the two main pectinolytic phytopathogenic bacteria D. dadantii and P. atrosepticum and, probably, of other Enterobacteriaceae. Moreover, we defined general criteria to select good reference genes in bacteria.

A novel individual-cell-based mathematical model based on multicellular tumour spheroids for evaluating doxorubicin-related delivery in avascular regions.

PubMed

Liu, Jiali; Yan, Fangrong; Chen, Hongzhu; Wang, Wenjie; Liu, Wenyue; Hao, Kun; Wang, Guangji; Zhou, Fang; Zhang, Jingwei

2017-09-01

Effective drug delivery in the avascular regions of tumours, which is crucial for the promising antitumour activity of doxorubicin-related therapy, is governed by two inseparable processes: intercellular diffusion and intracellular retention. To accurately evaluate doxorubicin-related delivery in the avascular regions, these two processes should be assessed together. Here we describe a new approach to such an assessment. An individual-cell-based mathematical model based on multicellular tumour spheroids was developed that describes the different intercellular diffusion and intracellular retention kinetics of doxorubicin in each cell layer. The different effects of a P-glycoprotein inhibitor (LY335979) and a hypoxia inhibitor (YC-1) were quantitatively evaluated and compared, in vitro (tumour spheroids) and in vivo (HepG2 tumours in mice). This approach was further tested by evaluating in these models, an experimental doxorubicin derivative, INNO 206, which is in Phase II clinical trials. Inhomogeneous, hypoxia-induced, P-glycoprotein expression compromised active transport of doxorubicin in the central area, that is, far from the vasculature. LY335979 inhibited efflux due to P-glycoprotein but limited levels of doxorubicin outside the inner cells, whereas YC-1 co-administration specifically increased doxorubicin accumulation in the inner cells without affecting the extracellular levels. INNO 206 exhibited a more effective distribution profile than doxorubicin. The individual-cell-based mathematical model accurately evaluated and predicted doxorubicin-related delivery and regulation in the avascular regions of tumours. The described framework provides a mechanistic basis for the proper development of doxorubicin-related drug co-administration profiles and nanoparticle development and could avoid unnecessary clinical trials. © 2017 The British Pharmacological Society.

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

PubMed

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

2016-10-01

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

Diversity in the carotenoid profiles and the expression of genes related to carotenoid accumulation among citrus genotypes

PubMed Central

Ikoma, Yoshinori; Matsumoto, Hikaru; Kato, Masaya

2016-01-01

Carotenoids are not only important to the plants themselves but also are beneficial to human health. Since citrus fruit is a good source of carotenoids for the human diet, it is important to study carotenoid profiles and the accumulation mechanism in citrus fruit. Thus, in the present paper, we describe the diversity in the carotenoid profiles of fruit among citrus genotypes. In regard to carotenoids, such as β-cryptoxanthin, violaxanthin, lycopene, and β-citraurin, the relationship between the carotenoid profile and the expression of carotenoid-biosynthetic genes is discussed. Finally, recent results of quantitative trait locus (QTL) analyses of carotenoid contents and expression levels of carotenoid-biosynthetic genes in citrus fruit are shown. PMID:27069398

Performance Assessment of Kernel Density Clustering for Gene Expression Profile Data

PubMed Central

Zeng, Beiyan; Chen, Yiping P.; Smith, Oscar H.

2003-01-01

Kernel density smoothing techniques have been used in classification or supervised learning of gene expression profile (GEP) data, but their applications to clustering or unsupervised learning of those data have not been explored and assessed. Here we report a kernel density clustering method for analysing GEP data and compare its performance with the three most widely-used clustering methods: hierarchical clustering, K-means clustering, and multivariate mixture model-based clustering. Using several methods to measure agreement, between-cluster isolation, and withincluster coherence, such as the Adjusted Rand Index, the Pseudo F test, the r2 test, and the profile plot, we have assessed the effectiveness of kernel density clustering for recovering clusters, and its robustness against noise on clustering both simulated and real GEP data. Our results show that the kernel density clustering method has excellent performance in recovering clusters from simulated data and in grouping large real expression profile data sets into compact and well-isolated clusters, and that it is the most robust clustering method for analysing noisy expression profile data compared to the other three methods assessed. PMID:18629292

Integrative Analysis of Longitudinal Metabolomics Data from a Personal Multi-Omics Profile

PubMed Central

Stanberry, Larissa; Mias, George I.; Haynes, Winston; Higdon, Roger; Snyder, Michael; Kolker, Eugene

2013-01-01

The integrative personal omics profile (iPOP) is a pioneering study that combines genomics, transcriptomics, proteomics, metabolomics and autoantibody profiles from a single individual over a 14-month period. The observation period includes two episodes of viral infection: a human rhinovirus and a respiratory syncytial virus. The profile studies give an informative snapshot into the biological functioning of an organism. We hypothesize that pathway expression levels are associated with disease status. To test this hypothesis, we use biological pathways to integrate metabolomics and proteomics iPOP data. The approach computes the pathways’ differential expression levels at each time point, while taking into account the pathway structure and the longitudinal design. The resulting pathway levels show strong association with the disease status. Further, we identify temporal patterns in metabolite expression levels. The changes in metabolite expression levels also appear to be consistent with the disease status. The results of the integrative analysis suggest that changes in biological pathways may be used to predict and monitor the disease. The iPOP experimental design, data acquisition and analysis issues are discussed within the broader context of personal profiling. PMID:24958148

Decoherence in yeast cell populations and its implications for genome-wide expression noise.

PubMed

Briones, M R S; Bosco, F

2009-01-20

Gene expression "noise" is commonly defined as the stochastic variation of gene expression levels in different cells of the same population under identical growth conditions. Here, we tested whether this "noise" is amplified with time, as a consequence of decoherence in global gene expression profiles (genome-wide microarrays) of synchronized cells. The stochastic component of transcription causes fluctuations that tend to be amplified as time progresses, leading to a decay of correlations of expression profiles, in perfect analogy with elementary relaxation processes. Measuring decoherence, defined here as a decay in the auto-correlation function of yeast genome-wide expression profiles, we found a slowdown in the decay of correlations, opposite to what would be expected if, as in mixing systems, correlations decay exponentially as the equilibrium state is reached. Our results indicate that the populational variation in gene expression (noise) is a consequence of temporal decoherence, in which the slow decay of correlations is a signature of strong interdependence of the transcription dynamics of different genes.

Microarray evaluation of gene expression profiles in inflamed and healthy human dental pulp: the role of IL1beta and CD40 in pulp inflammation.

PubMed

Gatta, V; Zizzari, V L; Dd ' Amico, V; Salini, L; D' Aurora, M; Franchi, S; Antonucci, I; Sberna, M T; Gherlone, E; Stuppia, L; Tetè, S

2012-01-01

Dental pulp undergoes a number of changes passing from healthy status to inflammation due to deep decay. These changes are regulated by several genes resulting differently expressed in inflamed and healthy dental pulp, and the knowledge of the processes underlying this differential expression is of great relevance in the identification of the pathogenesis of the disease. In this study, the gene expression profile of inflamed and healthy dental pulps were compared by microarray analysis, and data obtained were analyzed by Ingenuity Pathway Analysis (IPA) software. This analysis allows to focus on a variety of genes, typically expressed in inflamed tissues. The comparison analysis showed an increased expression of several genes in inflamed pulp, among which IL1β and CD40 resulted of particular interest. These results indicate that gene expression profile of human dental pulp in different physiological and pathological conditions may become an useful tool for improving our knowledge about processes regulating pulp inflammation.

Neighboring Genes Show Correlated Evolution in Gene Expression

PubMed Central

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 (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As 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

Alteration of the gene expression profile of T-cell receptor αβ-modified T-cells with diffuse large B-cell lymphoma specificity.

PubMed

Zha, Xianfeng; Yin, Qingsong; Tan, Huo; Wang, Chunyan; Chen, Shaohua; Yang, Lijian; Li, Bo; Wu, Xiuli; Li, Yangqiu

2013-05-01

Antigen-specific, T-cell receptor (TCR)-modified cytotoxic T lymphocytes (CTLs) that target tumors are an attractive strategy for specific adoptive immunotherapy. Little is known about whether there are any alterations in the gene expression profile after TCR gene transduction in T cells. We constructed TCR gene-redirected CTLs with specificity for diffuse large B-cell lymphoma (DLBCL)-associated antigens to elucidate the gene expression profiles of TCR gene-redirected T-cells, and we further analyzed the gene expression profile pattern of these redirected T-cells by Affymetrix microarrays. The resulting data were analyzed using Bioconductor software, a two-fold cut-off expression change was applied together with anti-correlation of the profile ratios to render the microarray analysis set. The fold change of all genes was calculated by comparing the three TCR gene-modified T-cells and a negative control counterpart. The gene pathways were analyzed using Bioconductor and Kyoto Encyclopedia of Genes and Genomes. Identical genes whose fold change was greater than or equal to 2.0 in all three TCR gene-redirected T-cell groups in comparison with the negative control were identified as the differentially expressed genes. The differentially expressed genes were comprised of 33 up-regulated genes and 1 down-regulated gene including JUNB, FOS, TNF, INF-γ, DUSP2, IL-1B, CXCL1, CXCL2, CXCL9, CCL2, CCL4, and CCL8. These genes are mainly involved in the TCR signaling, mitogen-activated protein kinase signaling, and cytokine-cytokine receptor interaction pathways. In conclusion, we characterized the gene expression profile of DLBCL-specific TCR gene-redirected T-cells. The changes corresponded to an up-regulation in the differentiation and proliferation of the T-cells. These data may help to explain some of the characteristics of the redirected T-cells.

Global Gene Expression Profiling of the Asymptomatic Bacteriuria Escherichia coli Strain 83972 in the Human Urinary Tract†

PubMed Central

Roos, Viktoria; Klemm, Per

2006-01-01

Urinary tract infections (UTIs) are an important health problem worldwide, with many million cases each year. Escherichia coli is the most common organism causing UTIs in humans. The asymptomatic bacteriuria E. coli strain 83972 is an excellent colonizer of the human urinary tract, where it causes long-term bladder colonization. The strain has been used for prophylactic purposes in patients prone to more severe and recurrent UTIs. For this study, we used DNA microarrays to monitor the expression profile of strain 83972 in the human urinary tract. Significant differences in expression levels were seen between the in vivo expression profiles of strain 83972 in three patients and the corresponding in vitro expression profiles in lab medium and human urine. The data revealed an in vivo lifestyle of microaerobic growth with respiration of nitrate coupled to degradation of sugar acids and amino acids, with no signs of attachment to host tissues. Interestingly, genes involved in NO protection and metabolism showed significant up-regulation in the patients. This is one of the first studies to address bacterial whole-genome expression in humans and the first study to investigate global gene expression of an E. coli strain in the human urinary tract. PMID:16714589

Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients.

PubMed

Rapin, Nicolas; Bagger, Frederik Otzen; Jendholm, Johan; Mora-Jensen, Helena; Krogh, Anders; Kohlmann, Alexander; Thiede, Christian; Borregaard, Niels; Bullinger, Lars; Winther, Ole; Theilgaard-Mönch, Kim; Porse, Bo T

2014-02-06

Gene expression profiling has been used extensively to characterize cancer, identify novel subtypes, and improve patient stratification. However, it has largely failed to identify transcriptional programs that differ between cancer and corresponding normal cells and has not been efficient in identifying expression changes fundamental to disease etiology. Here we present a method that facilitates the comparison of any cancer sample to its nearest normal cellular counterpart, using acute myeloid leukemia (AML) as a model. We first generated a gene expression-based landscape of the normal hematopoietic hierarchy, using expression profiles from normal stem/progenitor cells, and next mapped the AML patient samples to this landscape. This allowed us to identify the closest normal counterpart of individual AML samples and determine gene expression changes between cancer and normal. We find the cancer vs normal method (CvN method) to be superior to conventional methods in stratifying AML patients with aberrant karyotype and in identifying common aberrant transcriptional programs with potential importance for AML etiology. Moreover, the CvN method uncovered a novel poor-outcome subtype of normal-karyotype AML, which allowed for the generation of a highly prognostic survival signature. Collectively, our CvN method holds great potential as a tool for the analysis of gene expression profiles of cancer patients.

A Prognostic Gene Expression Profile That Predicts Circulating Tumor Cell Presence in Breast Cancer Patients

PubMed Central

Molloy, Timothy J.; Roepman, Paul; Naume, Bjørn; van't Veer, Laura J.

2012-01-01

The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into “good prognosis” or “poor prognosis” are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the “CTC profile” also provided prognostic information independent of the well-established and powerful ‘70-gene’ prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays. PMID:22384245

Absorption profiles of the potassium 4s-4p and 4p-5s lines perturbed by helium

NASA Astrophysics Data System (ADS)

Allard, N. F.

2011-12-01

An accurate determination of the complete profile including the extreme far wing is required to model the contribution of strong alkali resonance lines to brown dwarf spectra. A unified theory of collisional line profiles has been applied for the evaluation of the absorption coefficients of potassium perturbed by helium. Results are reported here from the optical range to the near-infrared.

Intratracheally instilled titanium dioxide nanoparticles translocate to heart and liver and activate complement cascade in the heart of C57BL/6 mice

PubMed Central

Husain, Mainul; Wu, Dongmei; Saber, Anne T.; Decan, Nathalie; Jacobsen, Nicklas R.; Williams, Andrew; Yauk, Carole L.; Wallin, Hakan; Vogel, Ulla; Halappanavar, Sabina

2015-01-01

Abstract An estimated 1% or less of nanoparticles (NPs) deposited in the lungs translocate to systemic circulation and enter other organs; however, this estimation may not be accurate given the low sensitivity of existing in vivo NP detection methods. Moreover, the biological effects of such low levels of translocation are unclear. We employed a nano-scale hyperspectral microscope to spatially observe and spectrally profile NPs in tissues and blood following pulmonary deposition in mice. In addition, we characterized effects occurring in blood, liver and heart at the mRNA and protein level following translocation from the lungs. Adult female C57BL/6 mice were exposed via intratracheal instillation to 18 or 162 µg of industrially relevant titanium dioxide nanoparticles (nano-TiO2) alongside vehicle controls. Using the nano-scale hyperspectral microscope, translocation to heart and liver was confirmed at both doses, and to blood at the highest dose, in mice analyzed 24 h post-exposure. Global gene expression profiling and ELISA analysis revealed activation of complement cascade and inflammatory processes in heart and specific activation of complement factor 3 in blood, suggesting activation of an early innate immune response essential for particle opsonisation and clearance. The liver showed a subtle response with changes in the expression of genes associated with acute phase response. This study characterizes the subtle systemic effects that occur in liver and heart tissues following pulmonary exposure and low levels of translocation of nano-TiO2 from lungs. PMID:25993494

Snowball: resampling combined with distance-based regression to discover transcriptional consequences of a driver mutation

PubMed Central

Xu, Yaomin; Guo, Xingyi; Sun, Jiayang; Zhao, Zhongming

2015-01-01

Motivation: Large-scale cancer genomic studies, such as The Cancer Genome Atlas (TCGA), have profiled multidimensional genomic data, including mutation and expression profiles on a variety of cancer cell types, to uncover the molecular mechanism of cancerogenesis. More than a hundred driver mutations have been characterized that confer the advantage of cell growth. However, how driver mutations regulate the transcriptome to affect cellular functions remains largely unexplored. Differential analysis of gene expression relative to a driver mutation on patient samples could provide us with new insights in understanding driver mutation dysregulation in tumor genome and developing personalized treatment strategies. Results: Here, we introduce the Snowball approach as a highly sensitive statistical analysis method to identify transcriptional signatures that are affected by a recurrent driver mutation. Snowball utilizes a resampling-based approach and combines a distance-based regression framework to assign a robust ranking index of genes based on their aggregated association with the presence of the mutation, and further selects the top significant genes for downstream data analyses or experiments. In our application of the Snowball approach to both synthesized and TCGA data, we demonstrated that it outperforms the standard methods and provides more accurate inferences to the functional effects and transcriptional dysregulation of driver mutations. Availability and implementation: R package and source code are available from CRAN at http://cran.r-project.org/web/packages/DESnowball, and also available at http://bioinfo.mc.vanderbilt.edu/DESnowball/. Contact: zhongming.zhao@vanderbilt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25192743

Identification of high-risk cutaneous melanoma tumors is improved when combining the online American Joint Committee on Cancer Individualized Melanoma Patient Outcome Prediction Tool with a 31-gene expression profile-based classification.

PubMed

Ferris, Laura K; Farberg, Aaron S; Middlebrook, Brooke; Johnson, Clare E; Lassen, Natalie; Oelschlager, Kristen M; Maetzold, Derek J; Cook, Robert W; Rigel, Darrell S; Gerami, Pedram

2017-05-01

A significant proportion of patients with American Joint Committee on Cancer (AJCC)-defined early-stage cutaneous melanoma have disease recurrence and die. A 31-gene expression profile (GEP) that accurately assesses metastatic risk associated with primary cutaneous melanomas has been described. We sought to compare accuracy of the GEP in combination with risk determined using the web-based AJCC Individualized Melanoma Patient Outcome Prediction Tool. GEP results from 205 stage I/II cutaneous melanomas with sufficient clinical data for prognostication using the AJCC tool were classified as low (class 1) or high (class 2) risk. Two 5-year overall survival cutoffs (AJCC 79% and 68%), reflecting survival for patients with stage IIA or IIB disease, respectively, were assigned for binary AJCC risk. Cox univariate analysis revealed significant risk classification of distant metastasis-free and overall survival (hazard ratio range 3.2-9.4, P < .001) for both tools. In all, 43 (21%) cases had discordant GEP and AJCC classification (using 79% cutoff). Eleven of 13 (85%) deaths in that group were predicted as high risk by GEP but low risk by AJCC. Specimens reflect tertiary care center referrals; more effective therapies have been approved for clinical use after accrual. The GEP provides valuable prognostic information and improves identification of high-risk melanomas when used together with the AJCC online prediction tool. Copyright © 2016 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Development and Application of a Cohesive Sediment Transport Model in Coastal Louisiana

NASA Astrophysics Data System (ADS)

Sorourian, S.; Nistor, I.

2017-12-01

The Louisiana coast has suffered from rapid land loss due to the combined effects of increasing the rate of eustatic sea level rise, insufficient riverine sediment input and subsidence. The sediment in this region is dominated by cohesive sediments (up to 80% of clay). This study presents a new model for calculating suspended sediment concentration (SSC) of cohesive sediments. Several new concepts are incorporated into the proposed model, which is capable of estimating the spatial and temporal variation in the concentration of cohesive sediment. First, the model incorporates the effect of electrochemical forces between cohesive sediment particles. Second, the wave friction factor is expressed in terms of the median particle size diameter in order to enhance the accuracy of the estimation of bed shear stress. Third, the erosion rate of cohesive sediments is also expressed in time-dependent form. Simulated SSC profiles are compared with field data collected from Vermilion Bay, Louisiana. The results of the proposed model agree well with the experimental data, as soon as steady state condition is achieved. The results of the new numerical models provide a better estimation of the suspended sediment concentration profile compared to the initial model developed by Mehta and Li, 2003. Among the proposed developments, the formulation of a time-dependent erosion rate shows the most accurate results. Coupling of present model with the Finite-Volume, primitive equation Community Ocean Model (FVCOM) would shed light on the fate of fine-grained sediments in order to increase overall retention and restoration of the Louisiana coastal plain.

Microarray profiling of gene expression in human adipocytes in response to anthocyanins.

PubMed

Tsuda, Takanori; Ueno, Yuki; Yoshikawa, Toshikazu; Kojo, Hitoshi; Osawa, Toshihiko

2006-04-14

Adipocyte dysfunction is strongly associated with the development of obesity and insulin resistance. It is accepted that the regulation of adipocytokine secretion or the adipocyte specific gene expression is one of the most important targets for the prevention of obesity and amelioration of insulin sensitivity. Recently, we demonstrated that anthocyanins, which are pigments widespread in the plant kingdom, have the potency of anti-obesity in mice and the enhancement adipocytokine secretion and its gene expression in adipocytes. In this study, we have shown the gene expression profile in human adipocytes treated with anthocyanins (cyanidin 3-glucoside; C3G or cyanidin; Cy). The human adipocytes were treated with 100 microM C3G, Cy or vehicle for 24 h. The total RNA from the adipocytes was isolated and carried out GeneChip microarray analysis. Based on the gene expression profile, we demonstrated the significant changes of adipocytokine expression (up-regulation of adiponectin and down-regulation of plasminogen activator inhibitor-1 and interleukin-6). Some of lipid metabolism related genes (uncoupling protein2, acylCoA oxidase1 and perilipin) also significantly induced in both common the C3G or Cy treatment groups. These studies have provided an overview of the gene expression profiles in human adipocytes treated with anthocyanins and demonstrated that anthocyanins can regulate adipocytokine gene expression to ameliorate adipocyte function related with obesity and diabetes that merit further investigation.

Real-time ultrawide-band group delay profile monitoring through low-noise incoherent temporal interferometry.

PubMed

Park, Yongwoo; Malacarne, Antonio; Azaña, José

2011-02-28

A simple, highly accurate measurement technique for real-time monitoring of the group delay (GD) profiles of photonic dispersive devices over ultra-broad spectral bandwidths (e.g. an entire communication wavelength band) is demonstrated. The technique is based on time-domain self-interference of an incoherent light pulse after linear propagation through the device under test, providing a measurement wavelength range as wide as the source spectral bandwidth. Significant enhancement in the signal-to-noise ratio of the self-interference signal has been observed by use of a relatively low-noise incoherent light source as compared with the theoretical estimate for a white-noise light source. This fact combined with the use of balanced photo-detection has allowed us to significantly reduce the number of profiles that need to be averaged to reach a targeted GD measurement accuracy, thus achieving reconstruction of the device GD profile in real time. We report highly-accurate monitoring of (i) the group-delay ripple (GDR) profile of a 10-m long chirped fiber Bragg grating over the full C band (~42 nm), and (ii) the group velocity dispersion (GVD) and dispersion slope (DS) profiles of a ~2-km long dispersion compensating fiber module over an ~72-nm wavelength range, both captured at a 15 frames/s video rate update, with demonstrated standard deviations in the captured GD profiles as low as ~1.6 ps.

Developmental transcriptional profiling reveals key insights into Triticeae reproductive development.

PubMed

Tran, Frances; Penniket, Carolyn; Patel, Rohan V; Provart, Nicholas J; Laroche, André; Rowland, Owen; Robert, Laurian S

2013-06-01

Despite their importance, there remains a paucity of large-scale gene expression-based studies of reproductive development in species belonging to the Triticeae. As a first step to address this deficiency, a gene expression atlas of triticale reproductive development was generated using the 55K Affymetrix GeneChip(®) wheat genome array. The global transcriptional profiles of the anther/pollen, ovary and stigma were analyzed at concurrent developmental stages, and co-expressed as well as preferentially expressed genes were identified. Data analysis revealed both novel and conserved regulatory factors underlying Triticeae floral development and function. This comprehensive resource rests upon detailed gene annotations, and the expression profiles are readily accessible via a web browser. © 2013 Her Majesty the Queen in Right of Canada as represented by the Minister of Agriculture and Agri-Food Canada.

Integration of neutron time-of-flight single-crystal Bragg peaks in reciprocal space

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

Schultz, Arthur J; Joergensen, Mads; Wang, Xiaoping

2014-01-01

The intensity of single crystal Bragg peaks obtained by mapping neutron time-of-flight event data into reciprocal space and integrating in various ways are compared. These include spherical integration with a fixed radius, ellipsoid fitting and integrating of the peak intensity and one-dimensional peak profile fitting. In comparison to intensities obtained by integrating in real detector histogram space, the data integrated in reciprocal space results in better agreement factors and more accurate atomic parameters. Furthermore, structure refinement using integrated intensities from one-dimensional profile fitting is demonstrated to be more accurate than simple peak-minus-background integration.

A methodology to generate high-resolution digital elevation model (DEM) and surface water profile for a physical model using close range photogrammetric (CRP) technique

NASA Astrophysics Data System (ADS)

Mali, V. K.; Kuiry, S. N.

2015-12-01

Comprehensive understanding of the river flow dynamics with varying topography in a real field is very intricate and difficult. Conventional experimental methods based on manual data collection are time consuming and prone to many errors. Recently, remotely sensed satellite imageries are at the best to provide necessary information for large area provided the high resolution but which are very expensive and untimely, consequently, attaining accurate river bathymetry from relatively course resolution and untimely imageries are inaccurate and impractical. Despite of that, these data are often being used to calibrate the river flow models, though these models require highly accurate morpho-dynamic data in order to predict the flow field precisely. Under this circumstance, these data could be supplemented through experimental observations in a physical model with modern techniques. This paper proposes a methodology to generate highly accurate river bathymetry and water surface (WS) profile for a physical model of river network system using CRP technique. For the task accomplishment, a number of DSLR Nikon D5300 cameras (mounted at 3.5 m above the river bed) were used to capture the images of the physical model and the flooding scenarios during the experiments. During experiment, non-specular materials were introduced at the inlet and images were taken simultaneously from different orientations and altitudes with significant overlap of 80%. Ground control points were surveyed using two ultrasonic sensors with ±0.5 mm vertical accuracy. The captured images are, then processed in PhotoScan software to generate the DEM and WS profile. The generated data were then passed through statistical analysis to identify errors. Accuracy of WS profile was limited by extent and density of non-specular powder and stereo-matching discrepancies. Furthermore, several factors of camera including orientation, illumination and altitude of camera. The CRP technique for a large scale physical model can significantly reduce the time and manual labour and avoids human errors in taking data using point gauge. Obtained highly accurate DEM and WS profile can be used in mathematical models for accurate prediction of river dynamics. This study would be very helpful for sediment transport study and can also be extended for real case studies.

A methodology to generate high-resolution digital elevation model (DEM) and surface water profile for a physical model using close range photogrammetric (CRP) technique

NASA Astrophysics Data System (ADS)

Méndez Incera, F. J.; Erikson, L. H.; Ruggiero, P.; Barnard, P.; Camus, P.; Rueda Zamora, A. C.

2014-12-01

Comprehensive understanding of the river flow dynamics with varying topography in a real field is very intricate and difficult. Conventional experimental methods based on manual data collection are time consuming and prone to many errors. Recently, remotely sensed satellite imageries are at the best to provide necessary information for large area provided the high resolution but which are very expensive and untimely, consequently, attaining accurate river bathymetry from relatively course resolution and untimely imageries are inaccurate and impractical. Despite of that, these data are often being used to calibrate the river flow models, though these models require highly accurate morpho-dynamic data in order to predict the flow field precisely. Under this circumstance, these data could be supplemented through experimental observations in a physical model with modern techniques. This paper proposes a methodology to generate highly accurate river bathymetry and water surface (WS) profile for a physical model of river network system using CRP technique. For the task accomplishment, a number of DSLR Nikon D5300 cameras (mounted at 3.5 m above the river bed) were used to capture the images of the physical model and the flooding scenarios during the experiments. During experiment, non-specular materials were introduced at the inlet and images were taken simultaneously from different orientations and altitudes with significant overlap of 80%. Ground control points were surveyed using two ultrasonic sensors with ±0.5 mm vertical accuracy. The captured images are, then processed in PhotoScan software to generate the DEM and WS profile. The generated data were then passed through statistical analysis to identify errors. Accuracy of WS profile was limited by extent and density of non-specular powder and stereo-matching discrepancies. Furthermore, several factors of camera including orientation, illumination and altitude of camera. The CRP technique for a large scale physical model can significantly reduce the time and manual labour and avoids human errors in taking data using point gauge. Obtained highly accurate DEM and WS profile can be used in mathematical models for accurate prediction of river dynamics. This study would be very helpful for sediment transport study and can also be extended for real case studies.

Impact of Profiling Technologies in the Understanding of Recombinant Protein Production

NASA Astrophysics Data System (ADS)

Vijayendran, Chandran; Flaschel, Erwin

Since expression profiling methods have been available in a high throughput fashion, the implication of these technologies in the field of biotechnology has increased dramatically. Microarray technology is one such unique and efficient methodology for simultaneous exploration of expression levels of numerous genes. Likewise, two-dimensional gel electrophoresis or multidimensional liquid chromatography coupled with mass spectrometry are extensively utilised for studying expression levels of numerous proteins. In the field of biotechnology these highly parallel analytical methods have paved the way to study and understand various biological phenomena depending on expression patterns. The next phenomenological level is represented by the metabolome and the (metabolic) fluxome. However, this chapter reviews gene and protein profiling and their impact on understanding recombinant protein production. We focus on the computational methods utilised for the analyses of data obtained from these profiling technologies as well as prominent results focusing on recombinant protein expression with Escherichia coli. Owing to the knowledge accumulated with respect to cellular signals triggered during recombinant protein production, this field is on the way to design strategies for developing improved processes. Both gene and protein profiling have exhibited a handful of functional categories to concentrate on in order to identify target genes and proteins, respectively, involved in the signalling network with major impact on recombinant protein production.

mRNA Expression Profiling of Laser Microbeam Microdissected Cells from Slender Embryonic Structures

PubMed Central

Scheidl, Stefan J.; Nilsson, Sven; Kalén, Mattias; Hellström, Mats; Takemoto, Minoru; Håkansson, Joakim; Lindahl, Per

2002-01-01

Microarray hybridization has rapidly evolved as an important tool for genomic studies and studies of gene regulation at the transcriptome level. Expression profiles from homogenous samples such as yeast and mammalian cell cultures are currently extending our understanding of biology, whereas analyses of multicellular organisms are more difficult because of tissue complexity. The combination of laser microdissection, RNA amplification, and microarray hybridization has the potential to provide expression profiles from selected populations of cells in vivo. In this article, we present and evaluate an experimental procedure for global gene expression analysis of slender embryonic structures using laser microbeam microdissection and laser pressure catapulting. As a proof of principle, expression profiles from 1000 cells in the mouse embryonic (E9.5) dorsal aorta were generated and compared with profiles for captured mesenchymal cells located one cell diameter further away from the aortic lumen. A number of genes were overexpressed in the aorta, including 11 previously known markers for blood vessels. Among the blood vessel markers were endoglin, tie-2, PDGFB, and integrin-β1, that are important regulators of blood vessel formation. This demonstrates that microarray analysis of laser microbeam micro-dissected cells is sufficiently sensitive for identifying genes with regulative functions. PMID:11891179

Three-dimensional tissue assemblies: novel models for the study of Salmonella enterica serovar Typhimurium pathogenesis

NASA Technical Reports Server (NTRS)

Nickerson, C. A.; Goodwin, T. J.; Terlonge, J.; Ott, C. M.; Buchanan, K. L.; Uicker, W. C.; Emami, K.; LeBlanc, C. L.; Ramamurthy, R.; Clarke, M. S.;

Prognostic role of a multigene reverse transcriptase-PCR assay in patients with node-negative breast cancer not receiving adjuvant systemic therapy.

PubMed

Esteva, Francisco J; Sahin, Aysegul A; Cristofanilli, Massimo; Coombes, Kevin; Lee, Sang-Joon; Baker, Joffre; Cronin, Maureen; Walker, Michael; Watson, Drew; Shak, Steven; Hortobagyi, Gabriel N

2005-05-01

To test the ability of a reverse transcriptase-PCR (RT-PCR) assay, based on gene expression profiles, to accurately determine the risk of recurrence in patients with node-negative breast cancer who did not receive systemic therapy using formalin-fixed, paraffin-embedded tissue. A secondary objective was to determine whether the quantitative RT-PCR data correlated with immunohistochemistry assay data regarding estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 status. We obtained archival paraffin-embedded tissue from patients with invasive breast cancer but no axillary lymph node involvement who had received no adjuvant systemic therapy and been followed for at least 5 years. RNA was extracted from three 10-microm-thick sections. The expression of 16 cancer-related genes and 5 reference genes was quantified using RT-PCR. A gene expression algorithm was used to calculate a recurrence score for each patient. We then assessed the ability of the test to accurately predict distant recurrence-free survival in this population. We identified 149 eligible patients. Median age at diagnosis was 59 years; mean tumor diameter was 2 cm; and 69% of tumors were estrogen receptor positive. Median follow-up was 18 years. The 5-year disease-free survival rate for the group was 80%. The 21 gene-based recurrence score was not predictive of distant disease recurrence. However, a high concordance between RT-PCR and immunohistochemical assays for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 status was noted. RT-PCR can be done on paraffin-embedded tissue to validate the large numbers of genes associated with breast cancer recurrence. However, further work needs to be done to develop an assay to identify the likelihood of recurrent disease in patients with node-negative breast cancer who do not receive adjuvant tamoxifen or chemotherapy.

Three-Dimensional Tissue Assemblies: Novel Models for the Study of Salmonella enterica Serovar Typhimurium Pathogenesis

PubMed Central

Nickerson, Cheryl A.; Goodwin, Thomas J.; Terlonge, Jacqueline; Ott, C. Mark; Buchanan, Kent L.; Uicker, William C.; Emami, Kamal; LeBlanc, Carly L.; Ramamurthy, Rajee; Clarke, Mark S.; Vanderburg, Charles R.; Hammond, Timothy; Pierson, Duane L.

2001-01-01

The lack of readily available experimental systems has limited knowledge pertaining to the development of Salmonella-induced gastroenteritis and diarrheal disease in humans. We used a novel low-shear stress cell culture system developed at the National Aeronautics and Space Administration in conjunction with cultivation of three-dimensional (3-D) aggregates of human intestinal tissue to study the infectivity of Salmonella enterica serovar Typhimurium for human intestinal epithelium. Immunohistochemical characterization and microscopic analysis of 3-D aggregates of the human intestinal epithelial cell line Int-407 revealed that the 3-D cells more accurately modeled human in vivo differentiated tissues than did conventional monolayer cultures of the same cells. Results from infectivity studies showed that Salmonella established infection of the 3-D cells in a much different manner than that observed for monolayers. Following the same time course of infection with Salmonella, 3-D Int-407 cells displayed minimal loss of structural integrity compared to that of Int-407 monolayers. Furthermore, Salmonella exhibited significantly lower abilities to adhere to, invade, and induce apoptosis of 3-D Int-407 cells than it did for infected Int-407 monolayers. Analysis of cytokine expression profiles of 3-D Int-407 cells and monolayers following infection with Salmonella revealed significant differences in expression of interleukin 1α (IL-1α), IL-1β, IL-6, IL-1Ra, and tumor necrosis factor alpha mRNAs between the two cultures. In addition, uninfected 3-D Int-407 cells constitutively expressed higher levels of transforming growth factor β1 mRNA and prostaglandin E2 than did uninfected Int-407 monolayers. By more accurately modeling many aspects of human in vivo tissues, the 3-D intestinal cell model generated in this study offers a novel approach for studying microbial infectivity from the perspective of the host-pathogen interaction. PMID:11598087

Genomic expression patterns in medication overuse headaches

PubMed Central

Hershey, Andrew D; Burdine, Danny; Kabbouche, Marielle A; Powers, Scott W

2016-01-01

Background Chronic daily headache (CDH) and chronic migraine (CM) are one of the most frequent problems encountered in neurology, are often difficult to treat, and frequently complicated by medication-overuse headache (MOH). Proper recognition of MOH may alter treatment outcome and prevent long term disability. Objective This study identifies the unique genomic expression pattern MOH that respond to cessation of the overused medication. Methods Baseline occurrence of MOH and typical pattern of response to medication cessation were measured from a large database. Whole blood samples from patients with CM with or without MOH were obtained and their genomic profile was assessed. Affymetrix human U133 plus2 arrays were used to examine the genomic expression patterns prior to treatment and 6–12 weeks later. Headache characterisation and response to treatment based on headache frequency and disability were compared. Results Of 1311 patients reporting daily or continuous headaches, 513 (39.1%) reported overusing analgesic medication. At follow-up, 44.5% had a 50% or greater reduction in headache frequency, while 41.6% had no change. Blood genomic expression patterns were obtained on 33 patients with 19 (57.6%) overusing analgesic medication with a unique genomic expression pattern in MOH that responded to cessation of analgesics. Gene ontology of these samples indicated a significant number were involved with brain and immunological tissues, including multiple signalling pathways and apoptosis. Conclusions Blood genomic patterns can accurately identify MOH patients that respond to medication cessation. These results suggest that MOH involves a unique molecular biology pathway that can be identified with a specific biomarker. PMID:20974594

Comparative expression profile of NOD1/2 and certain acute inflammatory cytokines in thermal-stressed cell culture model of native and crossbred cattle

NASA Astrophysics Data System (ADS)

Bhanuprakash, V.; Singh, Umesh; Sengar, Gyanendra Singh; Raja, T. V.; Sajjanar, Basavraj; Alex, Rani; Kumar, Sushil; Alyethodi, R. R.; Kumar, Ashish; Sharma, Ankur; Kumar, Suresh; Bhusan, Bharat; Deb, Rajib

2017-05-01

Thermotolerance depends mainly on the health and immune status of the animals. The variation in the immune status of the animals may alter the level of tolerance of animals exposed to heat or cold stress. The present study was conducted to investigate the expression profile of two important nucleotide binding and oligomerization domain receptors (NLRs) (NOD1 and NOD2) and their central signalling molecule RIP2 gene during in vitro thermal-stressed bovine peripheral blood mononuclear cells (PBMCs) of native (Sahiwal) and crossbred (Sahiwal X HF) cattle. We also examined the differential expression profile of certain acute inflammatory cytokines in in vitro thermal-stressed PBMC culture among native and its crossbred counterparts. Results revealed that the expression profile of NOD1/2 positively correlates with the thermal stress, signalling molecule and cytokines. Present findings also highlighted that the expression patterns during thermal stress were comparatively superior among indigenous compared to crossbred cattle which may add references regarding the better immune adaptability of Zebu cattle.

Differential chemokine, chemokine receptor and cytokine expression in Epstein-Barr virus-associated lymphoproliferative diseases.

PubMed

Ohshima, Koichi; Karube, Kennosuke; Hamasaki, Makoto; Tutiya, Takeshi; Yamaguchi, Takahiro; Suefuji, Hiroaki; Suzuki, Keiko; Suzumiya, Junji; Ohga, Shouichi; Kikuchi, Masahiro

2003-08-01

T cell immunity plays an important role in the clinicopathology of Epstein-Barr virus (EBV)-associated diseases. Acute EBV-induced infectious mononucleosis (IM) is a common self-limiting disease, however, other EBV-associated diseases, including chronic active EBV infection (CAEBV), NK cell lymphoma (NKL), and Hodgkin's lymphoma (HL), exhibit distinct clinical features. Chemokines are members of a family of small-secreted proteins. The relationships between chemokines and the chemokine receptor (R) are thought to be important for selectivity of local immunity. Some chemokines, chemokine R and cytokines closely associate with the T cell subtypes, Th1 and Th2 T cells and cytotoxic cells. To clarify the role of T cell immunity in EBV-associated diseases, we conducted gene expression profiling, using chemokine, chemokine R and cytokine DNA chips. Compared to EBV negative non-specific lymphadenitis, CAEBV and NKL exhibited diffuse down- and up-regulation, respectively, of these gene profiles. IM had a predominantly Th1-type profile, whereas HL had a mixed Th1/Th2-type profile. Reduction of the Th1-type cytokine interferon gamma (IFN-gamma) in CAEBV was confirmed by Reverse transcriptase-polymerase chain reaction, whereas IFN-gamma expression was markedly enhanced in NKL, and moderately enhanced in IM. Compared to IM, CAEBV showed slight elevation of "regulated upon activation, normal T expressed and secreted" (RANTES), but almost all other genes assayed were down-regulated. NKL exhibited elevated expression of numerous genes, particularly IFN-gamma-inducible-10 (IP-10) and monokine induced by IFN-gamma (MIG). HL showed variable elevated and reduced expression of various genes, with increased expression of IL-13 receptor and MIG. Our study demonstrated the enormous potential of gene expression profiling for clarifying the pathogenesis of EBV-associated diseases.

Gene expression profiling in liver and testis of rats to characterize the toxicity of triazole fungicides.

PubMed

Tully, Douglas B; Bao, Wenjun; Goetz, Amber K; Blystone, Chad R; Ren, Hongzu; Schmid, Judith E; Strader, Lillian F; Wood, Carmen R; Best, Deborah S; Narotsky, Michael G; Wolf, Douglas C; Rockett, John C; Dix, David J

2006-09-15

Four triazole fungicides were studied using toxicogenomic techniques to identify potential mechanisms of action. Adult male Sprague-Dawley rats were dosed for 14 days by gavage with fluconazole, myclobutanil, propiconazole, or triadimefon. Following exposure, serum was collected for hormone measurements, and liver and testes were collected for histology, enzyme biochemistry, or gene expression profiling. Body and testis weights were unaffected, but liver weights were significantly increased by all four triazoles, and hepatocytes exhibited centrilobular hypertrophy. Myclobutanil exposure increased serum testosterone and decreased sperm motility, but no treatment-related testis histopathology was observed. We hypothesized that gene expression profiles would identify potential mechanisms of toxicity and used DNA microarrays and quantitative real-time PCR (qPCR) to generate profiles. Triazole fungicides are designed to inhibit fungal cytochrome P450 (CYP) 51 enzyme but can also modulate the expression and function of mammalian CYP genes and enzymes. Triazoles affected the expression of numerous CYP genes in rat liver and testis, including multiple Cyp2c and Cyp3a isoforms as well as other xenobiotic metabolizing enzyme (XME) and transporter genes. For some genes, such as Ces2 and Udpgtr2, all four triazoles had similar effects on expression, suggesting possible common mechanisms of action. Many of these CYP, XME and transporter genes are regulated by xeno-sensing nuclear receptors, and hierarchical clustering of CAR/PXR-regulated genes demonstrated the similarities of toxicogenomic responses in liver between all four triazoles and in testis between myclobutanil and triadimefon. Triazoles also affected expression of multiple genes involved in steroid hormone metabolism in the two tissues. Thus, gene expression profiles helped identify possible toxicological mechanisms of the triazole fungicides.

Alteration in gene expression profile and oncogenicity of esophageal squamous cell carcinoma by RIZ1 upregulation.

PubMed

Dong, Shang-Wen; Li, Dong; Xu, Cong; Sun, Pei; Wang, Yuan-Guo; Zhang, Peng

2013-10-07

To investigate the effect of retinoblastoma protein-interacting zinc finger gene 1 (RIZ1) upregulation in gene expression profile and oncogenicity of human esophageal squamous cell carcinoma (ESCC) cell line TE13. TE13 cells were transfected with pcDNA3.1(+)/RIZ1 and pcDNA3.1(+). Changes in gene expression profile were screened and the microarray results were confirmed by reverse transcription-polymerase chain reaction (RT-PCR). Nude mice were inoculated with TE13 cells to establish ESCC xenografts. After two weeks, the inoculated mice were randomly divided into three groups. Tumors were injected with normal saline, transfection reagent pcDNA3.1(+) and transfection reagent pcDNA3.1(+)/RIZ1, respectively. Tumor development was quantified, and changes in gene expression of RIZ1 transfected tumors were detected by RT-PCR and Western blotting. DNA microarray data showed that RIZ1 transfection induced widespread changes in gene expression profile of cell line TE13, with 960 genes upregulated and 1163 downregulated. Treatment of tumor xenografts with RIZ1 recombinant plasmid significantly inhibited tumor growth, decreased tumor size, and increased expression of RIZ1 mRNA compared to control groups. The changes in gene expression profile were also observed in vivo after RIZ1 transfection. Most of the differentially expressed genes were associated with cell development, supervision of viral replication, lymphocyte costimulatory and immune system development in esophageal cells. RIZ1 gene may be involved in multiple cancer pathways, such as cytokine receptor interaction and transforming growth factor beta signaling. The development and progression of esophageal cancer are related to the inactivation of RIZ1. Virus infection may also be an important factor.

[Preliminary analysis of retinal gene expression profile of diabetic rat].

PubMed

Mei, Yan; Zhou, Hong-ying; Xiang, Tao; Lu, You-guang; Li, Ai-dong; Tang, En-jie; Yang, Hui-jun

2005-10-01

Establishing the retinal gene expression profiles of non-diabetic rat and diabetic rat and comparing the profiles in order to analyze the possible genes related with diabetic retinopathy. The whole retinal transcriptional fragments of non-diabetic rat and 8-week diabetic rat were obtained by restriction fragments differential display-PCR (RFDD-PCR). Bioinformatic analysis of retinal gene expression was performed using soft wares, including Fragment Analysis. After comparison of the expression profiles, the related gene fragments of diabetic retinopathy were initially selected as the target gene of further approach. A total of 3639 significant fragments were obtained. By means of more than 3-fold contrast of fluorescent intensity as the differential expression standard, the authors got 840 differential fragments, accounting for 23.08% of the expressed numbers and including 5 visual related genes, 13 excitatory neruotransmitter genes and 3 inhibitory neurotransmitter genes. At the 8th week, the expression of Rhodopsin kinase, beta-arrestin, Phosducinìrod photoreceptor cGMP-gated channel and Rpe65 as well as iGlu R1-4 were down-regulated. mGluRs and GABA-Rs were all up-regulated, whereas the expression of GlyR was unchanged. These results prompt again that the changes in retinal nervous layer of rat have occurred at an early stage of diabetes. The genes expression pattern of visual related genes and excitatory and inhibitory neurotransmitters in rat diabetic retina have been involved in neuro-dysfunctions of diabetic retina.

Changes in gene expression associated with response to neoadjuvant chemotherapy in breast cancer.

PubMed

Hannemann, Juliane; Oosterkamp, Hendrika M; Bosch, Cathy A J; Velds, Arno; Wessels, Lodewyk F A; Loo, Claudette; Rutgers, Emiel J; Rodenhuis, Sjoerd; van de Vijver, Marc J

2005-05-20

At present, clinically useful markers predicting response of primary breast carcinomas to either doxorubicin-cyclophosphamide (AC) or doxorubicin-docetaxel (AD) are lacking. We investigated whether gene expression profiles of the primary tumor could be used to predict treatment response to either of those chemotherapy regimens. Within a single-institution, randomized, phase II trial, patients with locally advanced breast cancer received six courses of either AC (n = 24) or AD (n = 24) neoadjuvant chemotherapy. Gene expression profiles were generated from core-needle biopsies obtained before treatment and correlated with the response of the primary tumor to the chemotherapy administered. Additionally, pretreatment gene expression profiles were compared with those in tumors remaining after chemotherapy. Ten (20%) of 48 patients showed a (near) pathologic complete remission of the primary tumor after treatment. No gene expression pattern correlating with response could be identified for all patients or for the AC or AD groups separately. The comparison of the pretreatment biopsy and the tumor excised after chemotherapy revealed differences in gene expression in tumors that showed a partial remission but not in tumors that did not respond to chemotherapy. No gene expression profile predicting the response of primary breast carcinomas to AC- or AD-based neoadjuvant chemotherapy could be detected in this interim analysis. More subtle differences in gene expression are likely to be present but can only be reliably identified by studying a larger group of patients. Response of a breast tumor to neoadjuvant chemotherapy results in alterations in gene expression.

Functional Analyses of NSF1 in Wine Yeast Using Interconnected Correlation Clustering and Molecular Analyses

PubMed Central

Bessonov, Kyrylo; Walkey, Christopher J.; Shelp, Barry J.; van Vuuren, Hennie J. J.; Chiu, David; van der Merwe, George

2013-01-01

Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of correlation values related to gene expression profiles extracted from given microarray datasets. ICC can be applied to any microarray dataset and any target gene. We applied this method to microarray data generated from wine fermentations and selected NSF1, which encodes a C2H2 zinc finger-type transcription factor, as the target gene. The validity of the method was verified by accurate identifications of the previously known functional roles of NSF1. In addition, we identified and verified potential new functions for this gene; specifically, NSF1 is a negative regulator for the expression of sulfur metabolism genes, the nuclear localization of Nsf1 protein (Nsf1p) is controlled in a sulfur-dependent manner, and the transcription of NSF1 is regulated by Met4p, an important transcriptional activator of sulfur metabolism genes. The inter-disciplinary approach adopted here highlighted the accuracy and relevancy of the ICC method in mining for novel gene functions using complex microarray datasets with a limited number of samples. PMID:24130853

Comparison of reverse transcription-quantitative polymerase chain reaction methods and platforms for single cell gene expression analysis.

PubMed

Fox, Bridget C; Devonshire, Alison S; Baradez, Marc-Olivier; Marshall, Damian; Foy, Carole A

2012-08-15

Single cell gene expression analysis can provide insights into development and disease progression by profiling individual cellular responses as opposed to reporting the global average of a population. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is the "gold standard" for the quantification of gene expression levels; however, the technical performance of kits and platforms aimed at single cell analysis has not been fully defined in terms of sensitivity and assay comparability. We compared three kits using purification columns (PicoPure) or direct lysis (CellsDirect and Cells-to-CT) combined with a one- or two-step RT-qPCR approach using dilutions of cells and RNA standards to the single cell level. Single cell-level messenger RNA (mRNA) analysis was possible using all three methods, although the precision, linearity, and effect of lysis buffer and cell background differed depending on the approach used. The impact of using a microfluidic qPCR platform versus a standard instrument was investigated for potential variability introduced by preamplification of template or scaling down of the qPCR to nanoliter volumes using laser-dissected single cell samples. The two approaches were found to be comparable. These studies show that accurate gene expression analysis is achievable at the single cell level and highlight the importance of well-validated experimental procedures for low-level mRNA analysis. Copyright © 2012 Elsevier Inc. All rights reserved.

Metastatic canine mammary carcinomas can be identified by a gene expression profile that partly overlaps with human breast cancer profiles

PubMed Central

2010-01-01

Background Similar to human breast cancer mammary tumors of the female dog are commonly associated with a fatal outcome due to the development of distant metastases. However, the molecular defects leading to metastasis are largely unknown and the value of canine mammary carcinoma as a model for human breast cancer is unclear. In this study, we analyzed the gene expression signatures associated with mammary tumor metastasis and asked for parallels with the human equivalent. Methods Messenger RNA expression profiles of twenty-seven lymph node metastasis positive or negative canine mammary carcinomas were established by microarray analysis. Differentially expressed genes were functionally characterized and associated with molecular pathways. The findings were also correlated with published data on human breast cancer. Results Metastatic canine mammary carcinomas had 1,011 significantly differentially expressed genes when compared to non-metastatic carcinomas. Metastatic carcinomas had a significant up-regulation of genes associated with cell cycle regulation, matrix modulation, protein folding and proteasomal degradation whereas cell differentiation genes, growth factor pathway genes and regulators of actin organization were significantly down-regulated. Interestingly, 265 of the 1,011 differentially expressed canine genes are also related to human breast cancer and, vice versa, parts of a human prognostic gene signature were identified in the expression profiles of the metastatic canine tumors. Conclusions Metastatic canine mammary carcinomas can be discriminated from non-metastatic carcinomas by their gene expression profiles. More than one third of the differentially expressed genes are also described of relevance for human breast cancer. Many of the differentially expressed genes are linked to functions and pathways which appear to be relevant for the induction and maintenance of metastatic progression and may represent new therapeutic targets. Furthermore, dogs are in some aspects suitable as a translational model for human breast tumors in order to identify prognostic molecular signatures and potential therapeutic targets. PMID:21062462

Sister grouping of chimpanzees and humans as revealed by genome-wide phylogenetic analysis of brain gene expression profiles

PubMed Central

Uddin, Monica; Wildman, Derek E.; Liu, Guozhen; Xu, Wenbo; Johnson, Robert M.; Hof, Patrick R.; Kapatos, Gregory; Grossman, Lawrence I.; Goodman, Morris

2004-01-01

Gene expression profiles from the anterior cingulate cortex (ACC) of human, chimpanzee, gorilla, and macaque samples provide clues about genetic regulatory changes in human and other catarrhine primate brains. The ACC, a cerebral neocortical region, has human-specific histological features. Physiologically, an individual's ACC displays increased activity during that individual's performance of cognitive tasks. Of ≈45,000 probe sets on microarray chips representing transcripts of all or most human genes, ≈16,000 were commonly detected in human ACC samples and comparable numbers, 14,000–15,000, in gorilla and chimpanzee ACC samples. Phylogenetic results obtained from gene expression profiles contradict the traditional expectation that the non-human African apes (i.e., chimpanzee and gorilla) should be more like each other than either should be like humans. Instead, the chimpanzee ACC profiles are more like the human than like the gorilla; these profiles demonstrate that chimpanzees are the sister group of humans. Moreover, for those unambiguous expression changes mapping to important biological processes and molecular functions that statistically are significantly represented in the data, the chimpanzee clade shows at least as much apparent regulatory evolution as does the human clade. Among important changes in the ancestry of both humans and chimpanzees, but to a greater extent in humans, are the up-regulated expression profiles of aerobic energy metabolism genes and neuronal function-related genes, suggesting that increased neuronal activity required increased supplies of energy. PMID:14976249

Accurately estimating PSF with straight lines detected by Hough transform

NASA Astrophysics Data System (ADS)

Wang, Ruichen; Xu, Liangpeng; Fan, Chunxiao; Li, Yong

2018-04-01

This paper presents an approach to estimating point spread function (PSF) from low resolution (LR) images. Existing techniques usually rely on accurate detection of ending points of the profile normal to edges. In practice however, it is often a great challenge to accurately localize profiles of edges from a LR image, which hence leads to a poor PSF estimation of the lens taking the LR image. For precisely estimating the PSF, this paper proposes firstly estimating a 1-D PSF kernel with straight lines, and then robustly obtaining the 2-D PSF from the 1-D kernel by least squares techniques and random sample consensus. Canny operator is applied to the LR image for obtaining edges and then Hough transform is utilized to extract straight lines of all orientations. Estimating 1-D PSF kernel with straight lines effectively alleviates the influence of the inaccurate edge detection on PSF estimation. The proposed method is investigated on both natural and synthetic images for estimating PSF. Experimental results show that the proposed method outperforms the state-ofthe- art and does not rely on accurate edge detection.

Four-miRNA signature as a prognostic tool for lung adenocarcinoma.

PubMed

Lin, Yan; Lv, Yufeng; Liang, Rong; Yuan, Chunling; Zhang, Jinyan; He, Dan; Zheng, Xiaowen; Zhang, Jianfeng

2018-01-01

The aim of this study was to generate a novel miRNA expression signature to accurately predict prognosis for patients with lung adenocarcinoma (LUAD). Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple miRNAs with differential expression between LUAD and paired healthy tissues. We then evaluated the prognostic values of the differentially expressed miRNAs using univariate/multivariate Cox regression analysis. This analysis was ultimately used to construct a four-miRNA signature that effectively predicted patient survival. Finally, we analyzed potential functional roles of the target genes for these four miRNAs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Based on our cutoff criteria ( P <0.05 and |log2FC| >1.0), we identified a total of 187 differentially expressed miRNAs, including 148 that were upregulated in LUAD tissues and 39 that were downregulated. Four miRNAs (miR-148a-5p, miR-31-5p, miR-548v, and miR-550a-5p) were independently associated with survival based on Kaplan-Meier analysis. We generated a signature index based on the expression of these four miRNAs and stratified patients into low- and high-risk groups. Patients in the high-risk group had significantly shorter survival times than those in the low-risk group ( P =0.002). A functional enrichment analysis suggested that the target genes of these four miRNAs were involved in protein phosphorylation and the Hippo and sphingolipid signaling pathways. Taken together, our results suggest that our four-miRNA signature can be used as a prognostic tool for patients with LUAD.

Identification and validation of reference genes for quantitative real-time PCR normalization and its applications in lycium.

PubMed

Zeng, Shaohua; Liu, Yongliang; Wu, Min; Liu, Xiaomin; Shen, Xiaofei; Liu, Chunzhao; Wang, Ying

2014-01-01

Lycium barbarum and L. ruthenicum are extensively used as traditional Chinese medicinal plants. Next generation sequencing technology provides a powerful tool for analyzing transcriptomic profiles of gene expression in non-model species. Such gene expression can then be confirmed with quantitative real-time polymerase chain reaction (qRT-PCR). Therefore, use of systematically identified suitable reference genes is a prerequisite for obtaining reliable gene expression data. Here, we calculated the expression stability of 18 candidate reference genes across samples from different tissues and grown under salt stress using geNorm and NormFinder procedures. The geNorm-determined rank of reference genes was similar to those defined by NormFinder with some differences. Both procedures confirmed that the single most stable reference gene was ACNTIN1 for L. barbarum fruits, H2B1 for L. barbarum roots, and EF1α for L. ruthenicum fruits. PGK3, H2B2, and PGK3 were identified as the best stable reference genes for salt-treated L. ruthenicum leaves, roots, and stems, respectively. H2B1 and GAPDH1+PGK1 for L. ruthenicum and SAMDC2+H2B1 for L. barbarum were the best single and/or combined reference genes across all samples. Finally, expression of salt-responsive gene NAC, fruit ripening candidate gene LrPG, and anthocyanin genes were investigated to confirm the validity of the selected reference genes. Suitable reference genes identified in this study provide a foundation for accurately assessing gene expression and further better understanding of novel gene function to elucidate molecular mechanisms behind particular biological/physiological processes in Lycium.

Conditional clustering of temporal expression profiles

PubMed Central

Wang, Ling; Montano, Monty; Rarick, Matt; Sebastiani, Paola

2008-01-01

Background Many microarray experiments produce temporal profiles in different biological conditions but common cluster techniques are not able to analyze the data conditional on the biological conditions. Results This article presents a novel technique to cluster data from time course microarray experiments performed across several experimental conditions. Our algorithm uses polynomial models to describe the gene expression patterns over time, a full Bayesian approach with proper conjugate priors to make the algorithm invariant to linear transformations, and an iterative procedure to identify genes that have a common temporal expression profile across two or more experimental conditions, and genes that have a unique temporal profile in a specific condition. Conclusion We use simulated data to evaluate the effectiveness of this new algorithm in finding the correct number of clusters and in identifying genes with common and unique profiles. We also use the algorithm to characterize the response of human T cells to stimulations of antigen-receptor signaling gene expression temporal profiles measured in six different biological conditions and we identify common and unique genes. These studies suggest that the methodology proposed here is useful in identifying and distinguishing uniquely stimulated genes from commonly stimulated genes in response to variable stimuli. Software for using this clustering method is available from the project home page. PMID:18334028

Extended Lindhard-Scharf-Schiott Theory for Ion Implantation Profiles Expressed with Pearson Function

NASA Astrophysics Data System (ADS)

Suzuki, Kunihiro

2009-04-01

Ion implantation profiles are expressed by the Pearson function with first, second, third, and fourth moment parameters of Rp, ΔRp, γ, and β. We derived an analytical model for these profile moments by solving a Lindhard-Scharf-Schiott (LSS) integration equation using perturbation approximation. This analytical model reproduces Monte Carlo data that were well calibrated to reproduce a vast experimental database. The extended LSS theory is vital for instantaneously predicting ion implantation profiles with any combination of incident ions and substrate atoms including their energy dependence.

SPERM RNA AMPLIFICATION FOR GENE EXPRESSION PROFILING BY DNA MICROARRAY TECHNOLOGY

EPA Science Inventory

Sperm RNA Amplification for Gene Expression Profiling by DNA Microarray Technology
Hongzu Ren, Kary E. Thompson, Judith E. Schmid and David J. Dix, Reproductive Toxicology Division, NHEERL, Office of Research and Development, US Environmental Protection Agency, Research Triang...

EXPRESSION PROFILING OF FIVE RAT STRAINS REVEAL TRANSCRIPTIONAL MODES IN THE ANTIGEN PROCESSING PATHWAY

EPA Science Inventory

Comparative gene expression profiling of rat strains with genetic predisposition to diverse cardiovascular diseases can help decode the transcriptional program that governs cellular behavior. We hypothesized that co-transcribed, intra-pathway, functionally coherent genes can be r...

GENE EXPRESSION PROFILING TO IDENTIFY MECHANISMS OF MALE REPRODUCTIVE TOXICITY

EPA Science Inventory

Gene Expression Profiling to Identify Mechanisms of Male Reproductive Toxicity
David J. Dix
National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA.
Ab...

Multiclass cancer diagnosis using tumor gene expression signatures

DOE PAGES

Ramaswamy, S.; Tamayo, P.; Rifkin, R.; ...

2001-12-11

The optimal treatment of patients with cancer depends on establishing accurate diagnoses by using a complex combination of clinical and histopathological data. In some instances, this task is difficult or impossible because of atypical clinical presentation or histopathology. To determine whether the diagnosis of multiple common adult malignancies could be achieved purely by molecular classification, we subjected 218 tumor samples, spanning 14 common tumor types, and 90 normal tissue samples to oligonucleotide microarray gene expression analysis. The expression levels of 16,063 genes and expressed sequence tags were used to evaluate the accuracy of a multiclass classifier based on a supportmore » vector machine algorithm. Overall classification accuracy was 78%, far exceeding the accuracy of random classification (9%). Poorly differentiated cancers resulted in low-confidence predictions and could not be accurately classified according to their tissue of origin, indicating that they are molecularly distinct entities with dramatically different gene expression patterns compared with their well differentiated counterparts. Taken together, these results demonstrate the feasibility of accurate, multiclass molecular cancer classification and suggest a strategy for future clinical implementation of molecular cancer diagnostics.« less

Gene Expression Analyses of Subchondral Bone in Early Experimental Osteoarthritis by Microarray

PubMed Central

Chen, YuXian; Shen, Jun; Lu, HuaDing; Zeng, Chun; Ren, JianHua; Zeng, Hua; Li, ZhiFu; Chen, ShaoMing; Cai, DaoZhang; Zhao, Qing

2012-01-01

Osteoarthritis (OA) is a degenerative joint disease that affects both cartilage and bone. A better understanding of the early molecular changes in subchondral bone may help elucidate the pathogenesis of OA. We used microarray technology to investigate the time course of molecular changes in the subchondral bone in the early stages of experimental osteoarthritis in a rat model. We identified 2,234 differentially expressed (DE) genes at 1 week, 1,944 at 2 weeks and 1,517 at 4 weeks post-surgery. Further analyses of the dysregulated genes indicated that the events underlying subchondral bone remodeling occurred sequentially and in a time-dependent manner at the gene expression level. Some of the identified dysregulated genes that were identified have suspected roles in bone development or remodeling; these genes include Alp, Igf1, Tgf β1, Postn, Mmp3, Tnfsf11, Acp5, Bmp5, Aspn and Ihh. The differences in the expression of these genes were confirmed by real-time PCR, and the results indicated that our microarray data accurately reflected gene expression patterns characteristic of early OA. To validate the results of our microarray analysis at the protein level, immunohistochemistry staining was used to investigate the expression of Mmp3 and Aspn protein in tissue sections. These analyses indicate that Mmp3 protein expression completely matched the results of both the microarray and real-time PCR analyses; however, Aspn protein expression was not observed to differ at any time. In summary, our study demonstrated a simple method of separation of subchondral bone sample from the knee joint of rat, which can effectively avoid bone RNA degradation. These findings also revealed the gene expression profiles of subchondral bone in the rat OA model at multiple time points post-surgery and identified important DE genes with known or suspected roles in bone development or remodeling. These genes may be novel diagnostic markers or therapeutic targets for OA. PMID:22384228

Gene expression analysis predicts insect venom anaphylaxis in indolent systemic mastocytosis.

PubMed

Niedoszytko, M; Bruinenberg, M; van Doormaal, J J; de Monchy, J G R; Nedoszytko, B; Koppelman, G H; Nawijn, M C; Wijmenga, C; Jassem, E; Elberink, J N G Oude

2011-05-01

Anaphylaxis to insect venom (Hymenoptera) is most severe in patients with mastocytosis and may even lead to death. However, not all patients with mastocytosis suffer from anaphylaxis. The aim of the study was to analyze differences in gene expression between patients with indolent systemic mastocytosis (ISM) and a history of insect venom anaphylaxis (IVA) compared to those patients without a history of anaphylaxis, and to determine the predictive use of gene expression profiling. Whole-genome gene expression analysis was performed in peripheral blood cells. Twenty-two adults with ISM were included: 12 with a history of IVA and 10 without a history of anaphylaxis of any kind. Significant differences in single gene expression corrected for multiple testing were found for 104 transcripts (P < 0.05). Gene ontology analysis revealed that the differentially expressed genes were involved in pathways responsible for the development of cancer and focal and cell adhesion suggesting that the expression of genes related to the differentiation state of cells is higher in patients with a history of anaphylaxis. Based on the gene expression profiles, a naïve Bayes prediction model was built identifying patients with IVA. In ISM, gene expression profiles are different between patients with a history of IVA and those without. These findings might reflect a more pronounced mast cells dysfunction in patients without a history of anaphylaxis. Gene expression profiling might be a useful tool to predict the risk of anaphylaxis on insect venom in patients with ISM. Prospective studies are needed to substantiate any conclusions. © 2010 John Wiley & Sons A/S.

Excited atoms in the free-burning Ar arc: treatment of the resonance radiation

NASA Astrophysics Data System (ADS)

Golubovskii, Yu; Kalanov, D.; Gortschakow, S.; Baeva, M.; Uhrlandt, D.

2016-11-01

The collisional-radiative model with an emphasis on the accurate treatment of the resonance radiation transport is developed and applied to the free-burning Ar arc plasma. This model allows for analysis of the influence of resonance radiation on the spatial density profiles of the atoms in different excited states. The comparison of the radial density profiles obtained using an effective transition probability approximation with the results of the accurate solution demonstrates the distinct impact of transport on the profiles and absolute densities of the excited atoms, especially in the arc fringes. The departures from the Saha-Boltzmann equilibrium distributions, caused by different radiative transitions, are analyzed. For the case of the DC arc, the local thermodynamic equilibrium (LTE) state holds close to the arc axis, while strong deviations from the equilibrium state on the periphery occur. In the intermediate radial positions the conditions of partial LTE are fulfilled.

Scanning moiré and spatial-offset phase-stepping for surface inspection of structures

NASA Astrophysics Data System (ADS)

Yoneyama, S.; Morimoto, Y.; Fujigaki, M.; Ikeda, Y.

2005-06-01

In order to develop a high-speed and accurate surface inspection system of structures such as tunnels, a new surface profile measurement method using linear array sensors is studied. The sinusoidal grating is projected on a structure surface. Then, the deformed grating is scanned by linear array sensors that move together with the grating projector. The phase of the grating is analyzed by a spatial offset phase-stepping method to perform accurate measurement. The surface profile measurements of the wall with bricks and the concrete surface of a structure are demonstrated using the proposed method. The change of geometry or fabric of structures and the defects on structure surfaces can be detected by the proposed method. It is expected that the surface profile inspection system of tunnels measuring from a running train can be constructed based on the proposed method.

Metatranscriptomic profiles of Eastern subterranean termites, Reticulitermes flavipes (Kollar) fed on second generation feedstocks.

PubMed

Rajarapu, Swapna Priya; Shreve, Jacob T; Bhide, Ketaki P; Thimmapuram, Jyothi; Scharf, Michael E

2015-04-22

Second generation lignocellulosic feedstocks are being considered as an alternative to first generation biofuels that are derived from grain starches and sugars. However, the current pre-treatment methods for second generation biofuel production are inefficient and expensive due to the recalcitrant nature of lignocellulose. In this study, we used the lower termite Reticulitermes flavipes (Kollar), as a model to identify potential pretreatment genes/enzymes specifically adapted for use against agricultural feedstocks. Metatranscriptomic profiling was performed on worker termite guts after feeding on corn stover (CS), soybean residue (SR), or 98% pure cellulose (paper) to identify (i) microbial community, (ii) pathway level and (iii) gene-level responses. Microbial community profiles after CS and SR feeding were different from the paper feeding profile, and protist symbiont abundance decreased significantly in termites feeding on SR and CS relative to paper. Functional profiles after CS feeding were similar to paper and SR; whereas paper and SR showed different profiles. Amino acid and carbohydrate metabolism pathways were downregulated in termites feeding on SR relative to paper and CS. Gene expression analyses showed more significant down regulation of genes after SR feeding relative to paper and CS. Stereotypical lignocellulase genes/enzymes were not differentially expressed, but rather were among the most abundant/constitutively-expressed genes. These results suggest that the effect of CS and SR feeding on termite gut lignocellulase composition is minimal and thus, the most abundantly expressed enzymes appear to encode the best candidate catalysts for use in saccharification of these and related second-generation feedstocks. Further, based on these findings we hypothesize that the most abundantly expressed lignocellulases, rather than those that are differentially expressed have the best potential as pretreatment enzymes for CS and SR feedstocks.

Tensor decomposition-based and principal-component-analysis-based unsupervised feature extraction applied to the gene expression and methylation profiles in the brains of social insects with multiple castes.

PubMed

Taguchi, Y-H

2018-05-08

Even though coexistence of multiple phenotypes sharing the same genomic background is interesting, it remains incompletely understood. Epigenomic profiles may represent key factors, with unknown contributions to the development of multiple phenotypes, and social-insect castes are a good model for elucidation of the underlying mechanisms. Nonetheless, previous studies have failed to identify genes associated with aberrant gene expression and methylation profiles because of the lack of suitable methodology that can address this problem properly. A recently proposed principal component analysis (PCA)-based and tensor decomposition (TD)-based unsupervised feature extraction (FE) can solve this problem because these two approaches can deal with gene expression and methylation profiles even when a small number of samples is available. PCA-based and TD-based unsupervised FE methods were applied to the analysis of gene expression and methylation profiles in the brains of two social insects, Polistes canadensis and Dinoponera quadriceps. Genes associated with differential expression and methylation between castes were identified, and analysis of enrichment of Gene Ontology terms confirmed reliability of the obtained sets of genes from the biological standpoint. Biologically relevant genes, shown to be associated with significant differential gene expression and methylation between castes, were identified here for the first time. The identification of these genes may help understand the mechanisms underlying epigenetic control of development of multiple phenotypes under the same genomic conditions.

Special relativity effects for space-based coherent lidar experiments

NASA Technical Reports Server (NTRS)

Raogudimetla, V. S.

1994-01-01

There is a great need to develop a system that can measure accurately atmospheric wind profiles because an accurate data of wind profiles in the atmosphere constitutes single most input for reliable simulations of global climate numerical methods. Also such data helps us understand atmospheric circulation and climate dynamics better. Because of this need for accurate wind measurements, a space-based Laser Atmospheric Winds Sounder (LAWS) is being designed at MSFC to measure wind profiles in the lower atmosphere of the earth with an accuracy of 1 m/s at lower altitudes to 5m/s at higher altitudes. This system uses an orbiting spacecraft with a pulsed laser source and measures the Doppler shift between the transmitted and received frequencies to estimate the atmospheric wind velocities. If a significant return from the ground (sea) is possible, the spacecraft speed and height are estimated from it and these results and the Doppler shift are then used to estimate the wind velocities in the atmosphere. It is expected that at the proposed wavelengths, there will be enough backscatter from the aerosols but there may no be significant return from the ground. So a coherent (heterodyne) detection system is being proposed for signal processing because it can provide high signal to noise ratio and sensitivity and thus make the best use of low ground return. However, for a heterodyne detection scheme to provide the best results, it is important that the receiving aperture be aligned properly for the proposed wind sounder, this amounts to only a few microradians tolerance in alignment. It is suspected that the satellite motion relative to the ground may introduce errors in the order of a few microradians because of special relativity. Hence, the problem of laser scattering off a moving fixed target when the source and receiver are moving, which was not treated in the past in the literature, was analyzed in the following, using relativistic electrodynamics and applied to the case of the space-based coherent lidar, assuming flat ground. Here an interest in developing analytical expression for the location of the receiving point for the return with respect to the satellite, receiving angle and Doppler shift in frequency and amount of tip, all as measured in the satellite moving coordinate system and the diffuse scattering angle at the ground which does not require any compensation. All the three cases of retro-reflection, specular reflection and diffuse scattering by the ground should be treated though retro-reflection and diffuse scattering are more important.

Neighboring Genes Show Correlated Evolution in Gene Expression.

PubMed

Ghanbarian, Avazeh T; Hurst, Laurence D

2015-07-01

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 (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As 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. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Validation of Biomarkers Predictive of Recurrence Following Prostatectomy

DTIC Science & Technology

2011-04-14

Bergerheim U, Ekman P, DeMarzo AM, Tibshirani R, Botstein D, Brown PO, Brooks JD, Pollack JR: Gene expression profiling identifies clinically...P, DeMarzo AM, Tibshirani R, Botstein D, Brown PO, Brooks JD, Pollack JR: Gene expression profiling identifies clinically relevant subtypes of

Customizing chemotherapy for colon cancer: the potential of gene expression profiling.

PubMed

Mariadason, John M; Arango, Diego; Augenlicht, Leonard H

2004-06-01

The value of gene expression profiling, or microarray analysis, for the classification and prognosis of multiple forms of cancer is now clearly established. For colon cancer, expression profiling can readily discriminate between normal and tumor tissue, and to some extent between tumors of different histopathological stage and prognosis. While a definitive in vivo study demonstrating the potential of this methodology for predicting response to chemotherapy is presently lacking, the ability of microarrays to distinguish other subtleties of colon cancer phenotype, as well as recent in vitro proof-of-principle experiments utilizing colon cancer cell lines, illustrate the potential of this methodology for predicting the probability of response to specific chemotherapeutic agents. This review discusses some of the recent advances in the use of microarray analysis for understanding and distinguishing colon cancer subtypes, and attempts to identify challenges that need to be overcome in order to achieve the goal of using gene expression profiling for customizing chemotherapy in colon cancer.

Introducing Cytology-Based Theranostics in Oral Squamous Cell Carcinoma: A Pilot Program.

PubMed

Patrikidou, Anna; Valeri, Rosalia Maria; Kitikidou, Kyriaki; Destouni, Charikleia; Vahtsevanos, Konstantinos

2016-04-01

We aimed to evaluate the feasibility and reliability of brush cytology in the biomarker expression profiling of oral squamous cell carcinomas within the concept of theranostics, and to correlate this biomarker profile with patient measurable outcomes. Markers representative of prognostic gene expression changes in oral squamous cell carcinoma was selected. These markers were also selected to involve pathways for which commercially available or investigational agents exist for clinical application. A set of 7 markers were analysed by immunocytochemistry on the archival primary tumour material of 99 oral squamous cell carcinoma patients. We confirmed the feasibility of the technique for the expression profiling of oral squamous cell carcinomas. Furthermore, our results affirm the prognostic significance of the epidermal growth factor receptor (EGFR) family and the angiogenic pathway in oral squamous cell carcinoma, confirming their interest for targeted therapy. Brush cytology appears feasible and applicable for the expression profiling of oral squamous cell carcinoma within the concept of theranostics, according to sample availability.

Stem cell and neurogenic gene-expression profiles link prostate basal cells to aggressive prostate cancer

PubMed Central

Zhang, Dingxiao; Park, Daechan; Zhong, Yi; Lu, Yue; Rycaj, Kiera; Gong, Shuai; Chen, Xin; Liu, Xin; Chao, Hsueh-Ping; Whitney, Pamela; Calhoun-Davis, Tammy; Takata, Yoko; Shen, Jianjun; Iyer, Vishwanath R.; Tang, Dean G.

2016-01-01

The prostate gland mainly contains basal and luminal cells constructed as a pseudostratified epithelium. Annotation of prostate epithelial transcriptomes provides a foundation for discoveries that can impact disease understanding and treatment. Here we describe a genome-wide transcriptome analysis of human benign prostatic basal and luminal epithelial populations using deep RNA sequencing. Through molecular and biological characterizations, we show that the differential gene-expression profiles account for their distinct functional properties. Strikingly, basal cells preferentially express gene categories associated with stem cells, neurogenesis and ribosomal RNA (rRNA) biogenesis. Consistent with this profile, basal cells functionally exhibit intrinsic stem-like and neurogenic properties with enhanced rRNA transcription activity. Of clinical relevance, the basal cell gene-expression profile is enriched in advanced, anaplastic, castration-resistant and metastatic prostate cancers. Therefore, we link the cell-type-specific gene signatures to aggressive subtypes of prostate cancer and identify gene signatures associated with adverse clinical features. PMID:26924072

Stem cell and neurogenic gene-expression profiles link prostate basal cells to aggressive prostate cancer.

PubMed

Zhang, Dingxiao; Park, Daechan; Zhong, Yi; Lu, Yue; Rycaj, Kiera; Gong, Shuai; Chen, Xin; Liu, Xin; Chao, Hsueh-Ping; Whitney, Pamela; Calhoun-Davis, Tammy; Takata, Yoko; Shen, Jianjun; Iyer, Vishwanath R; Tang, Dean G

2016-02-29

The prostate gland mainly contains basal and luminal cells constructed as a pseudostratified epithelium. Annotation of prostate epithelial transcriptomes provides a foundation for discoveries that can impact disease understanding and treatment. Here we describe a genome-wide transcriptome analysis of human benign prostatic basal and luminal epithelial populations using deep RNA sequencing. Through molecular and biological characterizations, we show that the differential gene-expression profiles account for their distinct functional properties. Strikingly, basal cells preferentially express gene categories associated with stem cells, neurogenesis and ribosomal RNA (rRNA) biogenesis. Consistent with this profile, basal cells functionally exhibit intrinsic stem-like and neurogenic properties with enhanced rRNA transcription activity. Of clinical relevance, the basal cell gene-expression profile is enriched in advanced, anaplastic, castration-resistant and metastatic prostate cancers. Therefore, we link the cell-type-specific gene signatures to aggressive subtypes of prostate cancer and identify gene signatures associated with adverse clinical features.

Glycosyltransferase Gene Expression Profiles Classify Cancer Types and Propose Prognostic Subtypes

NASA Astrophysics Data System (ADS)

Ashkani, Jahanshah; Naidoo, Kevin J.

2016-05-01

Aberrant glycosylation in tumours stem from altered glycosyltransferase (GT) gene expression but can the expression profiles of these signature genes be used to classify cancer types and lead to cancer subtype discovery? The differential structural changes to cellular glycan structures are predominantly regulated by the expression patterns of GT genes and are a hallmark of neoplastic cell metamorphoses. We found that the expression of 210 GT genes taken from 1893 cancer patient samples in The Cancer Genome Atlas (TCGA) microarray data are able to classify six cancers; breast, ovarian, glioblastoma, kidney, colon and lung. The GT gene expression profiles are used to develop cancer classifiers and propose subtypes. The subclassification of breast cancer solid tumour samples illustrates the discovery of subgroups from GT genes that match well against basal-like and HER2-enriched subtypes and correlates to clinical, mutation and survival data. This cancer type glycosyltransferase gene signature finding provides foundational evidence for the centrality of glycosylation in cancer.

Differential expression of microRNA-675, microRNA-139-3p and microRNA-335 in benign and malignant adrenocortical tumours

PubMed Central

Helwig, J; Bertram, S; Sheu, S Y; Suttorp, A C; Seggewiß, J; Willscher, E; Walz, M K; Worm, K; Schmid, K W

2011-01-01

Background For the clinical management of adrenocortical neoplasms it is crucial to correctly distinguish between benign and malignant tumours. Even histomorphologically based scoring systems do not allow precise separation in single lesions, thus novel parameters are desired which offer a more accurate differentiation. The tremendous potential of microRNAs (miRNAs) as diagnostic biomarkers in surgical pathology has recently been shown in a broad variety of tumours. Methods In order to elucidate the diagnostic impact of miRNA expression in adrenocortical neoplasms, a cohort of 20 adrenocortical specimens including normal adrenal tissue (n=4), adrenocortical adenomas (ACAs) (n=9), adrenocortical carcinomas (ACCs) (n=4) and metastases (n=3) was analysed using TaqMan low density arrays to identify specific miRNA profiles in order to distinguish between benign and malignant adrenocortical lesions. Results were validated in a validation cohort (n=16). Results Concerning the differential diagnosis of ACAs and ACCs, 159 out of 667 miRNAs were up- and 89 were down-regulated in ACAs. Using real-time PCR analysis of three of the most significantly expressed single key miRNAs allowed separation of ACAs from ACCs. ACCs exhibited significantly lower levels of miR-139-3p (up to 8.49-fold, p<0.001), miR-675 (up to 23.25-fold, p<0.001) and miR-335 (up to 5.25-fold, p<0.001). A validation cohort of 16 specimen with known Weiss score showed up-regulation of miR-335 and miR-675 in the majority of cases with probable malignant course, although overlapping values exist. Conclusion miRNA profiling of miR-675 and miR-335 helps in discriminating ACCs from ACAs. miRNA analysis may indicate malignant behaviour in cases with indeterminate malignant potential. PMID:21471143

Structural features based genome-wide characterization and prediction of nucleosome organization

PubMed Central

2012-01-01

Background Nucleosome distribution along chromatin dictates genomic DNA accessibility and thus profoundly influences gene expression. However, the underlying mechanism of nucleosome formation remains elusive. Here, taking a structural perspective, we systematically explored nucleosome formation potential of genomic sequences and the effect on chromatin organization and gene expression in S. cerevisiae. Results We analyzed twelve structural features related to flexibility, curvature and energy of DNA sequences. The results showed that some structural features such as DNA denaturation, DNA-bending stiffness, Stacking energy, Z-DNA, Propeller twist and free energy, were highly correlated with in vitro and in vivo nucleosome occupancy. Specifically, they can be classified into two classes, one positively and the other negatively correlated with nucleosome occupancy. These two kinds of structural features facilitated nucleosome binding in centromere regions and repressed nucleosome formation in the promoter regions of protein-coding genes to mediate transcriptional regulation. Based on these analyses, we integrated all twelve structural features in a model to predict more accurately nucleosome occupancy in vivo than the existing methods that mainly depend on sequence compositional features. Furthermore, we developed a novel approach, named DLaNe, that located nucleosomes by detecting peaks of structural profiles, and built a meta predictor to integrate information from different structural features. As a comparison, we also constructed a hidden Markov model (HMM) to locate nucleosomes based on the profiles of these structural features. The result showed that the meta DLaNe and HMM-based method performed better than the existing methods, demonstrating the power of these structural features in predicting nucleosome positions. Conclusions Our analysis revealed that DNA structures significantly contribute to nucleosome organization and influence chromatin structure and gene expression regulation. The results indicated that our proposed methods are effective in predicting nucleosome occupancy and positions and that these structural features are highly predictive of nucleosome organization. The implementation of our DLaNe method based on structural features is available online. PMID:22449207

Gene expression profiles characterize early graft response in living donor small bowel transplantation: a case report.

PubMed

Bradley, S P; Pahari, M; Uknis, M E; Rastellini, C; Cicalese, L

2006-01-01

The cellular and histological events that occur during the regeneration process in invertebrates have been studied in the field of visceral regeneration. We would like to explore the molecular aspects of the regeneration process in the small intestine. The aim of this study was to characterize the gene expression profiles of the intestinal graft to identify which genes may have a role in regeneration of graft tissue posttransplant. In a patient undergoing living related small bowel transplantation (LRSBTx) in our institution, mucosal biopsies were obtained from the recipient intestine and donor graft at the time of transplant and at weeks 1, 2, 3, and 6 posttransplant. Total RNA was isolated from sample biopsies followed by gene expression profiles determined from the replicate samples (n = 3) for each biopsy using the Affymetrix U133 Plus 2.0 Human GeneChip set. Two profiles were obtained from the data. One profile showed rapid increase of 45 genes immediately after transplant by week 1 with significant changes (P < .05) greater than threefold including the chemokine CXC9 and glutathione-related stress factors, GPX2 and GSTA4. The second profile identified 133 genes that were significantly decreased by threefold or greater immediately after transplant week 1, including UCC1, the human homolog of the Ependymin gene. We have identified two gene expression profiles representing early graft responses to small bowel transplantation. These profiles will serve to identify and study those genes whose products may play a role in accelerating tissue regeneration following segmental LRSBTx.

Integrated Analysis of Dysregulated ncRNA and mRNA Expression Profiles in Humans Exposed to Carbon Nanotubes

PubMed Central

Shvedova, Anna A.; Yanamala, Naveena; Kisin, Elena R.; Khailullin, Timur O.; Birch, M. Eileen; Fatkhutdinova, Liliya M.

2016-01-01

Background As the application of carbon nanotubes (CNT) in consumer products continues to rise, studies have expanded to determine the associated risks of exposure on human and environmental health. In particular, several lines of evidence indicate that exposure to multi-walled carbon nanotubes (MWCNT) could pose a carcinogenic risk similar to asbestos fibers. However, to date the potential markers of MWCNT exposure are not yet explored in humans. Methods In the present study, global mRNA and ncRNA expression profiles in the blood of exposed workers, having direct contact with MWCNT aerosol for at least 6 months (n = 8), were compared with expression profiles of non-exposed (n = 7) workers (e.g., professional and/or technical staff) from the same manufacturing facility. Results Significant changes in the ncRNA and mRNA expression profiles were observed between exposed and non-exposed worker groups. An integrative analysis of ncRNA-mRNA correlations was performed to identify target genes, functional relationships, and regulatory networks in MWCNT-exposed workers. The coordinated changes in ncRNA and mRNA expression profiles revealed a set of miRNAs and their target genes with roles in cell cycle regulation/progression/control, apoptosis and proliferation. Further, the identified pathways and signaling networks also revealed MWCNT potential to trigger pulmonary and cardiovascular effects as well as carcinogenic outcomes in humans, similar to those previously described in rodents exposed to MWCNTs. Conclusion This study is the first to investigate aberrant changes in mRNA and ncRNA expression profiles in the blood of humans exposed to MWCNT. The significant changes in several miRNAs and mRNAs expression as well as their regulatory networks are important for getting molecular insights into the MWCNT-induced toxicity and pathogenesis in humans. Further large-scale prospective studies are necessary to validate the potential applicability of such changes in mRNAs and miRNAs as prognostic markers of MWCNT exposures in humans. PMID:26930275

Route profile analysis system and method

DOEpatents

Mullenhoff, Donald J.; Wilson, Stephen W.

1986-01-01

A system for recording terrain profile information is disclosed. The system accurately senses incremental distances traveled by a vehicle along with vehicle inclination, recording both with elapsed time. The incremental distances can subsequently be differentiated with respect to time to obtain acceleration. The acceleration can then be used by the computer to correct the sensed inclination.

Route profile analysis system and method

DOEpatents

Mullenhoff, D.J.; Wilson, S.W.

1982-07-29

A system for recording terrain profile information is disclosed. The system accurately senses incremental distances traveled by a vehicle along with vehicle inclination, recording both with elapsed time. The incremental distances can subsequently be differentiated with respect to time to obtain acceleration. The computer acceleration can then be used to correct the sensed inclination.

Social-Emotional Functioning of Elementary-Age Deaf Children: A Profile Analysis

ERIC Educational Resources Information Center

Vogel-Walcutt, Jennifer J.; Schatschneider, Christopher; Bowers, Clint

2011-01-01

Discussion and study of the social-emotional development of deaf and hard of hearing children, though extensive, has yet to provide an accurate understanding of the differences between deaf and hearing children. Consequently, the goal of the researchers was to conduct a profile analysis to determine similarities and differences between the two…

Establishment of a New Quality Control and Vaccine Safety Test for Influenza Vaccines and Adjuvants Using Gene Expression Profiling

PubMed Central

Momose, Haruka; Mizukami, Takuo; Kuramitsu, Madoka; Takizawa, Kazuya; Masumi, Atsuko; Araki, Kumiko; Furuhata, Keiko; Yamaguchi, Kazunari; Hamaguchi, Isao

2015-01-01

We have previously identified 17 biomarker genes which were upregulated by whole virion influenza vaccines, and reported that gene expression profiles of these biomarker genes had a good correlation with conventional animal safety tests checking body weight and leukocyte counts. In this study, we have shown that conventional animal tests showed varied and no dose-dependent results in serially diluted bulk materials of influenza HA vaccines. In contrast, dose dependency was clearly shown in the expression profiles of biomarker genes, demonstrating higher sensitivity of gene expression analysis than the current animal safety tests of influenza vaccines. The introduction of branched DNA based-concurrent expression analysis could simplify the complexity of multiple gene expression approach, and could shorten the test period from 7 days to 3 days. Furthermore, upregulation of 10 genes, Zbp1, Mx2, Irf7, Lgals9, Ifi47, Tapbp, Timp1, Trafd1, Psmb9, and Tap2, was seen upon virosomal-adjuvanted vaccine treatment, indicating that these biomarkers could be useful for the safety control of virosomal-adjuvanted vaccines. In summary, profiling biomarker gene expression could be a useful, rapid, and highly sensitive method of animal safety testing compared with conventional methods, and could be used to evaluate the safety of various types of influenza vaccines, including adjuvanted vaccine. PMID:25909814

Global Quantitative Modeling of Chromatin Factor Interactions

PubMed Central

Zhou, Jian; Troyanskaya, Olga G.

2014-01-01

Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896

Rapid identification and typing of Yersinia pestis and other Yersinia species by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry

PubMed Central

2010-01-01

Background Accurate identification is necessary to discriminate harmless environmental Yersinia species from the food-borne pathogens Yersinia enterocolitica and Yersinia pseudotuberculosis and from the group A bioterrorism plague agent Yersinia pestis. In order to circumvent the limitations of current phenotypic and PCR-based identification methods, we aimed to assess the usefulness of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) protein profiling for accurate and rapid identification of Yersinia species. As a first step, we built a database of 39 different Yersinia strains representing 12 different Yersinia species, including 13 Y. pestis isolates representative of the Antiqua, Medievalis and Orientalis biotypes. The organisms were deposited on the MALDI-TOF plate after appropriate ethanol-based inactivation, and a protein profile was obtained within 6 minutes for each of the Yersinia species. Results When compared with a 3,025-profile database, every Yersinia species yielded a unique protein profile and was unambiguously identified. In the second step of analysis, environmental and clinical isolates of Y. pestis (n = 2) and Y. enterocolitica (n = 11) were compared to the database and correctly identified. In particular, Y. pestis was unambiguously identified at the species level, and MALDI-TOF was able to successfully differentiate the three biotypes. Conclusion These data indicate that MALDI-TOF can be used as a rapid and accurate first-line method for the identification of Yersinia isolates. PMID:21073689

Rapid identification and typing of Yersinia pestis and other Yersinia species by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry.

PubMed

Ayyadurai, Saravanan; Flaudrops, Christophe; Raoult, Didier; Drancourt, Michel

2010-11-12

Accurate identification is necessary to discriminate harmless environmental Yersinia species from the food-borne pathogens Yersinia enterocolitica and Yersinia pseudotuberculosis and from the group A bioterrorism plague agent Yersinia pestis. In order to circumvent the limitations of current phenotypic and PCR-based identification methods, we aimed to assess the usefulness of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) protein profiling for accurate and rapid identification of Yersinia species. As a first step, we built a database of 39 different Yersinia strains representing 12 different Yersinia species, including 13 Y. pestis isolates representative of the Antiqua, Medievalis and Orientalis biotypes. The organisms were deposited on the MALDI-TOF plate after appropriate ethanol-based inactivation, and a protein profile was obtained within 6 minutes for each of the Yersinia species. When compared with a 3,025-profile database, every Yersinia species yielded a unique protein profile and was unambiguously identified. In the second step of analysis, environmental and clinical isolates of Y. pestis (n = 2) and Y. enterocolitica (n = 11) were compared to the database and correctly identified. In particular, Y. pestis was unambiguously identified at the species level, and MALDI-TOF was able to successfully differentiate the three biotypes. These data indicate that MALDI-TOF can be used as a rapid and accurate first-line method for the identification of Yersinia isolates.

Changes in global gene expression profiles induced by HPV 16 E6 oncoprotein variants in cervical carcinoma C33-A cells

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

Zacapala-Gómez, Ana Elvira, E-mail: zak_ana@yahoo.com.mx; Del Moral-Hernández, Oscar, E-mail: odelmoralh@gmail.com; Villegas-Sepúlveda, Nicolás, E-mail: nvillega@cinvestav.mx

We analyzed the effects of the expression of HPV 16 E6 oncoprotein variants (AA-a, AA-c, E-A176/G350, E-C188/G350, E-G350), and the E-Prototype in global gene expression profiles in an in vitro model. E6 gene was cloned into an expression vector fused to GFP and was transfected in C33-A cells. Affymetrix GeneChip Human Transcriptome Array 2.0 platform was used to analyze the expression of over 245,000 coding transcripts. We found that HPV16 E6 variants altered the expression of 387 different genes in comparison with E-Prototype. The altered genes are involved in cellular processes related to the development of cervical carcinoma, such asmore » adhesion, angiogenesis, apoptosis, differentiation, cell cycle, proliferation, transcription and protein translation. Our results show that polymorphic changes in HPV16 E6 natural variants are sufficient to alter the overall gene expression profile in C33-A cells, explaining in part the observed differences in oncogenic potential of HPV16 variants. - Highlights: • Amino acid changes in HPV16 E6 variants modulate the transciption of specific genes. • This is the first comparison of global gene expression profile of HPV 16 E6 variants. • Each HPV 16 E6 variant appears to have its own molecular signature.« less

Identification of airway mucosal type 2 inflammation by using clinical biomarkers in asthmatic patients.

PubMed

Silkoff, Philip E; Laviolette, Michel; Singh, Dave; FitzGerald, J Mark; Kelsen, Steven; Backer, Vibeke; Porsbjerg, Celeste M; Girodet, Pierre-Olivier; Berger, Patrick; Kline, Joel N; Chupp, Geoffrey; Susulic, Vedrana S; Barnathan, Elliot S; Baribaud, Frédéric; Loza, Matthew J

2017-09-01

The Airways Disease Endotyping for Personalized Therapeutics (ADEPT) study profiled patients with mild, moderate, and severe asthma and nonatopic healthy control subjects. We explored this data set to define type 2 inflammation based on airway mucosal IL-13-driven gene expression and how this related to clinically accessible biomarkers. IL-13-driven gene expression was evaluated in several human cell lines. We then defined type 2 status in 25 healthy subjects, 28 patients with mild asthma, 29 patients with moderate asthma, and 26 patients with severe asthma based on airway mucosal expression of (1) CCL26 (the most differentially expressed gene), (2) periostin, or (3) a multigene IL-13 in vitro signature (IVS). Clinically accessible biomarkers included fraction of exhaled nitric oxide (Feno) values, blood eosinophil (bEOS) counts, serum CCL26 expression, and serum CCL17 expression. Expression of airway mucosal CCL26, periostin, and IL-13-IVS all facilitated segregation of subjects into type 2-high and type 2-low asthmatic groups, but in the ADEPT study population CCL26 expression was optimal. All subjects with high airway mucosal CCL26 expression and moderate-to-severe asthma had Feno values (≥35 ppb) and/or high bEOS counts (≥300 cells/mm 3 ) compared with a minority (36%) of subjects with low airway mucosal CCL26 expression. A combination of Feno values, bEOS counts, and serum CCL17 and CCL26 expression had 100% positive predictive value and 87% negative predictive value for airway mucosal CCL26-high status. Clinical variables did not differ between subjects with type 2-high and type 2-low status. Eosinophilic inflammation was associated with but not limited to airway mucosal type 2 gene expression. A panel of clinical biomarkers accurately classified type 2 status based on airway mucosal CCL26, periostin, or IL-13-IVS gene expression. Use of Feno values, bEOS counts, and serum marker levels (eg, CCL26 and CCL17) in combination might allow patient selection for novel type 2 therapeutics. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. All rights reserved.

Recognition of Emotion from Facial Expressions with Direct or Averted Eye Gaze and Varying Expression Intensities in Children with Autism Disorder and Typically Developing Children

PubMed Central

Tell, Dina; Davidson, Denise; Camras, Linda A.

2014-01-01

Eye gaze direction and expression intensity effects on emotion recognition in children with autism disorder and typically developing children were investigated. Children with autism disorder and typically developing children identified happy and angry expressions equally well. Children with autism disorder, however, were less accurate in identifying fear expressions across intensities and eye gaze directions. Children with autism disorder rated expressions with direct eyes, and 50% expressions, as more intense than typically developing children. A trend was also found for sad expressions, as children with autism disorder were less accurate in recognizing sadness at 100% intensity with direct eyes than typically developing children. Although the present research showed that children with autism disorder are sensitive to eye gaze direction, impairments in the recognition of fear, and possibly sadness, exist. Furthermore, children with autism disorder and typically developing children perceive the intensity of emotional expressions differently. PMID:24804098

Diverse correlation patterns between microRNAs and their targets during tomato fruit development indicates different modes of microRNA actions.

PubMed

Lopez-Gomollon, Sara; Mohorianu, Irina; Szittya, Gyorgy; Moulton, Vincent; Dalmay, Tamas

2012-12-01

MicroRNAs negatively regulate the accumulation of mRNAs therefore when they are expressed in the same cells their expression profiles show an inverse correlation. We previously described one positively correlated miRNA/target pair, but it is not known how widespread this phenomenon is. Here, we investigated the correlation between the expression profiles of differentially expressed miRNAs and their targets during tomato fruit development using deep sequencing, Northern blot and RT-qPCR. We found an equal number of positively and negatively correlated miRNA/target pairs indicating that positive correlation is more frequent than previously thought. We also found that the correlation between microRNA and target expression profiles can vary between mRNAs belonging to the same gene family and even for the same target mRNA at different developmental stages. Since microRNAs always negatively regulate their targets, the high number of positively correlated microRNA/target pairs suggests that mutual exclusion could be as widespread as temporal regulation. The change of correlation during development suggests that the type of regulatory circuit directed by a microRNA can change over time and can be different for individual gene family members. Our results also highlight potential problems for expression profiling-based microRNA target identification/validation.

Comparative study of hematopoietic stem and progenitor cells between sexes in mice under physiological conditions along time.

PubMed

Gasco, Samanta; Rando, Amaya; Zaragoza, Pilar; García-Redondo, Alberto; Calvo, Ana Cristina; Osta, Rosario

2017-12-01

Hematopoietic stem and progenitor cells (HSPCs) are attractive targets in regenerative medicine, although the differences in their homeostatic maintenance between sexes along time are still under debate. We accurately monitored hematopoietic stem cells (HSCs), common lymphoid progenitors (CLPs), and common myeloid progenitors (CMPs) frequencies by flow cytometry, by performing serial peripheral blood extractions from male and female B6SJL wild-type mice and found no significant differences. Only modest differences were found in the gene expression profile of Slamf1 and Gata2. Our findings suggest that both sexes could be used indistinctly to perform descriptive studies in the murine hematopoietic system, especially for flow cytometry studies in peripheral blood. This would allow diminishing the number of animals needed for the experimental procedures. In addition, the use of serial extractions in the same animals drastically decreases the number of animals needed. © 2017 International Federation for Cell Biology.

Single-band upconversion nanoprobes for multiplexed simultaneous in situ molecular mapping of cancer biomarkers.

PubMed

Zhou, Lei; Wang, Rui; Yao, Chi; Li, Xiaomin; Wang, Chengli; Zhang, Xiaoyan; Xu, Congjian; Zeng, Aijun; Zhao, Dongyuan; Zhang, Fan

2015-04-24

The identification of potential diagnostic markers and target molecules among the plethora of tumour oncoproteins for cancer diagnosis requires facile technology that is capable of quantitatively analysing multiple biomarkers in tumour cells and tissues. Diagnostic and prognostic classifications of human tumours are currently based on the western blotting and single-colour immunohistochemical methods that are not suitable for multiplexed detection. Herein, we report a general and novel method to prepare single-band upconversion nanoparticles with different colours. The expression levels of three biomarkers in breast cancer cells were determined using single-band upconversion nanoparticles, western blotting and immunohistochemical technologies with excellent correlation. Significantly, the application of antibody-conjugated single-band upconversion nanoparticle molecular profiling technology can achieve the multiplexed simultaneous in situ biodetection of biomarkers in breast cancer cells and tissue specimens and produce more accurate results for the simultaneous quantification of proteins present at low levels compared with classical immunohistochemical technology.

[Alternative splicing regulation: implications in cancer diagnosis and treatment].

PubMed

Martínez-Montiel, Nancy; Rosas-Murrieta, Nora; Martínez-Contreras, Rebeca

2015-04-08

The accurate expression of the genetic information is regulated by processes like mRNA splicing, proposed after the discoveries of Phil Sharp and Richard Roberts, who demonstrated the existence of intronic sequences, present in almost every structural eukaryotic gene, which should be precisely removed. This intron removal is called "splicing", which generates different proteins from a single mRNA, with different or even antagonistic functions. We currently know that alternative splicing is the most important source of protein diversity, given that 70% of the human genes undergo splicing and that mutations causing defects in this process could originate up to 50% of genetic diseases, including cancer. When these defects occur in genes involved in cell adhesion, proliferation and cell cycle regulation, there is an impact on cancer progression, rising the opportunity to diagnose and treat some types of cancer according to a particular splicing profile. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

Enduring epigenetic landmarks define the cancer microenvironment

PubMed Central

Pidsley, Ruth; Lawrence, Mitchell G.; Zotenko, Elena; Niranjan, Birunthi; Statham, Aaron; Song, Jenny; Chabanon, Roman M.; Qu, Wenjia; Wang, Hong; Richards, Michelle; Nair, Shalima S.; Armstrong, Nicola J.; Nim, Hieu T.; Papargiris, Melissa; Balanathan, Preetika; French, Hugh; Peters, Timothy; Norden, Sam; Ryan, Andrew; Pedersen, John; Kench, James; Daly, Roger J.; Horvath, Lisa G.; Stricker, Phillip; Frydenberg, Mark; Taylor, Renea A.; Stirzaker, Clare; Risbridger, Gail P.; Clark, Susan J.

2018-01-01

The growth and progression of solid tumors involves dynamic cross-talk between cancer epithelium and the surrounding microenvironment. To date, molecular profiling has largely been restricted to the epithelial component of tumors; therefore, features underpinning the persistent protumorigenic phenotype of the tumor microenvironment are unknown. Using whole-genome bisulfite sequencing, we show for the first time that cancer-associated fibroblasts (CAFs) from localized prostate cancer display remarkably distinct and enduring genome-wide changes in DNA methylation, significantly at enhancers and promoters, compared to nonmalignant prostate fibroblasts (NPFs). Differentially methylated regions associated with changes in gene expression have cancer-related functions and accurately distinguish CAFs from NPFs. Remarkably, a subset of changes is shared with prostate cancer epithelial cells, revealing the new concept of tumor-specific epigenome modifications in the tumor and its microenvironment. The distinct methylome of CAFs provides a novel epigenetic hallmark of the cancer microenvironment and promises new biomarkers to improve interpretation of diagnostic samples. PMID:29650553

Infrasound ray tracing models for real events

NASA Astrophysics Data System (ADS)

Averbuch, Gil; Applbaum, David; Price, Colin; Ben Horin, Yochai

2015-04-01

Infrasound ray tracing models for real events C. Price1, G. Averbuch1, D. Applbaum1, Y. Ben Horin2 (1) Department of Geosciences, Tel Aviv University, Israel (2) Soreq Nuclear Research Center, Yavne, Israel Ray tracing models for infrasound propagation require two atmospheric parameters: the speed of sound profile and the wind profile. The usage of global atmospheric models for the speed of sound and wind profiles raises a fundamental question: can these models provide accurate results for modeling real events that have been detected by the infrasound arrays? Moreover, can these models provide accurate results for events that occurred during extreme weather conditions? We use 2D and 3D ray tracing models based on a modified Hamiltonian for a moving medium. Radiosonde measurements enable us to update the first 20 km of both speed of sound and wind profiles. The 2009 and 2011 Sayarim calibration experiments in Israel served us as a test for the models. In order to answer the question regarding the accuracy of the model during extreme weather conditions, we simulate infrasound sprite signals that were detected by the infrasound array in Mt. Meron, Israel. The results from modeling the Sayarim experiment provided us sufficient insight to conclude that ray tracing modeling can provide accurate results for real events that occurred during fair weather conditions. We conclude that the time delay in the model of the 2009 experiment is due to lack of accuracy in the wind and speed of sound profiles. Perturbed profiles provide accurate results. Earlier arrivals in 2011 are a result of the assumption that the earth is flat (no topography) and the use of local radiosonde measurements for the entire model. Using local radiosonde measurements only for part of the model and neglecting them on other parts prevents the early arrivals. We were able to determine which sprite is the one that got detected in the infrasound array as well as providing a height range for the sprite's height or the sprite's most energetic part. Even though atmospheric wind has a strong influence on infrasound wave propagation, our estimation is that for high altitude sources, extreme weather in the troposphere below has low impact on the trajectories of the waves.

Gene expression profiling of two distinct neuronal populations in the rodent spinal cord.

PubMed

Ryge, Jesper; Westerdahl, Ann-Charlotte; Alstrøm, Preben; Kiehn, Ole

2008-01-01

In the field of neuroscience microarray gene expression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global gene expression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level. We examine the microarray gene expression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The gene expression profiles of the respective cell populations were obtained from amplified mRNA originating from 50-250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential gene expression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population. We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional differences between these two cell populations in generating and transmitting the motor output in the rodent spinal cord.

Gene Expression Profiling of Two Distinct Neuronal Populations in the Rodent Spinal Cord

PubMed Central

Alstrøm, Preben; Kiehn, Ole

2008-01-01

Background In the field of neuroscience microarray gene expression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global gene expression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level. Methodology/Principal Findings We examine the microarray gene expression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The gene expression profiles of the respective cell populations were obtained from amplified mRNA originating from 50–250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential gene expression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population. Conclusions/Significance We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional differences between these two cell populations in generating and transmitting the motor output in the rodent spinal cord. PMID:18923679