Identification and validation of quantitative real-time reverse transcription PCR reference genes for gene expression analysis in teak (Tectona grandis L.f.).

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Galeano, Esteban; Vasconcelos, Tarcísio Sales; Ramiro, Daniel Alves; De Martin, Valentina de Fátima; Carrer, Helaine

2014-07-22

Teak (Tectona grandis L.f.) is currently the preferred choice of the timber trade for fabrication of woody products due to its extraordinary qualities and is widely grown around the world. Gene expression studies are essential to explore wood formation of vascular plants, and quantitative real-time reverse transcription PCR (qRT-PCR) is a sensitive technique employed for quantifying gene expression levels. One or more appropriate reference genes are crucial to accurately compare mRNA transcripts through different tissues/organs and experimental conditions. Despite being the focus of some genetic studies, a lack of molecular information has hindered genetic exploration of teak. To date, qRT-PCR reference genes have not been identified and validated for teak. Identification and cloning of nine commonly used qRT-PCR reference genes from teak, including ribosomal protein 60s (rp60s), clathrin adaptor complexes medium subunit family (Cac), actin (Act), histone 3 (His3), sand family (Sand), β-Tubulin (Β-Tub), ubiquitin (Ubq), elongation factor 1-α (Ef-1α), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Expression profiles of these genes were evaluated by qRT-PCR in six tissue and organ samples (leaf, flower, seedling, root, stem and branch secondary xylem) of teak. Appropriate gene cloning and sequencing, primer specificity and amplification efficiency was verified for each gene. Their stability as reference genes was validated by NormFinder, BestKeeper, geNorm and Delta Ct programs. Results obtained from all programs showed that TgUbq and TgEf-1α are the most stable genes to use as qRT-PCR reference genes and TgAct is the most unstable gene in teak. The relative expression of the teak cinnamyl alcohol dehydrogenase (TgCAD) gene in lignified tissues at different ages was assessed by qRT-PCR, using TgUbq and TgEf-1α as internal controls. These analyses exposed a consistent expression pattern with both reference genes. This study proposes a first broad

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray.

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Fenart, Stéphane; Ndong, Yves-Placide Assoumou; Duarte, Jorge; Rivière, Nathalie; Wilmer, Jeroen; van Wuytswinkel, Olivier; Lucau, Anca; Cariou, Emmanuelle; Neutelings, Godfrey; Gutierrez, Laurent; Chabbert, Brigitte; Guillot, Xavier; Tavernier, Reynald; Hawkins, Simon; Thomasset, Brigitte

2010-10-21

Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties

Development and validation of a flax (Linum usitatissimum L. gene expression oligo microarray

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Gutierrez Laurent

2010-10-01

Full Text Available Abstract Background Flax (Linum usitatissimum L. has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars and its cellulose-rich fibres (fibre-flax cultivars used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples. A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well

Validation of reference genes for RT-qPCR analysis of CYP4T expression in crucian carp

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Fei Mo

2014-09-01

Full Text Available Reference genes are commonly used for normalization of target gene expression during RT-qPCR analysis. However, no housekeeping genes or reference genes have been identified to be stable across different tissue types or under different experimental conditions. To identify the most suitable reference genes for RT-qPCR analysis of target gene expression in the hepatopancreas of crucian carp (Carassius auratus under various conditions (sex, age, water temperature, and drug treatments, seven reference genes, including beta actin (ACTB, beta-2 microglobulin (B2M, embryonic elongation factor-1 alpha (EEF1A, glyceraldehyde phosphate dehydrogenase (GAPDH, alpha tubulin (TUBA, ribosomal protein l8 (RPL8 and glucose-6-phosphate dehydrogenase (G6PDH, were evaluated in this study. The stability and ranking of gene expression were analyzed using three different statistical programs: GeNorm, Normfinder and Bestkeeper. The expression errors associated with selection of the genes were assessed by the relative quantity of CYP4T. The results indicated that all the seven genes exhibited variability under the experimental conditions of this research, and the combination of ACTB/TUBA/EEF1A or of ACTB/EEF1A was the best candidate that raised the accuracy of quantitative analysis of gene expression. The findings highlighted the importance of validation of housekeeping genes for research on gene expression under different conditions of experiment and species.

Validation of suitable reference genes for quantitative gene expression analysis in Panax ginseng

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Meizhen eWang

2016-01-01

Full Text Available Reverse transcription-qPCR (RT-qPCR has become a popular method for gene expression studies. Its results require data normalization by housekeeping genes. No single gene is proved to be stably expressed under all experimental conditions. Therefore, systematic evaluation of reference genes is necessary. With the aim to identify optimum reference genes for RT-qPCR analysis of gene expression in different tissues of Panax ginseng and the seedlings grown under heat stress, we investigated the expression stability of eight candidate reference genes, including elongation factor 1-beta (EF1-β, elongation factor 1-gamma (EF1-γ, eukaryotic translation initiation factor 3G (IF3G, eukaryotic translation initiation factor 3B (IF3B, actin (ACT, actin11 (ACT11, glyceraldehyde-3-phosphate dehydrogenase (GAPDH and cyclophilin ABH-like protein (CYC, using four widely used computational programs: geNorm, Normfinder, BestKeeper, and the comparative ΔCt method. The results were then integrated using the web-based tool RefFinder. As a result, EF1-γ, IF3G and EF1-β were the three most stable genes in different tissues of P. ginseng, while IF3G, ACT11 and GAPDH were the top three-ranked genes in seedlings treated with heat. Using three better reference genes alone or in combination as internal control, we examined the expression profiles of MAR, a multiple function-associated mRNA-like non-coding RNA (mlncRNA in P. ginseng. Taken together, we recommended EF1-γ/IF3G and IF3G/ACT11 as the suitable pair of reference genes for RT-qPCR analysis of gene expression in different tissues of P. ginseng and the seedlings grown under heat stress, respectively. The results serve as a foundation for future studies on P. ginseng functional genomics.

Validation of reference genes for quantitative expression analysis by real-time rt-PCR in four lepidopteran insects.

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Teng, Xiaolu; Zhang, Zan; He, Guiling; Yang, Liwen; Li, Fei

2012-01-01

Quantitative real-time polymerase chain reaction (qPCR) is an efficient and widely used technique to monitor gene expression. Housekeeping genes (HKGs) are often empirically selected as the reference genes for data normalization. However, the suitability of HKGs used as the reference genes has been seldom validated. Here, six HKGs were chosen (actin A3, actin A1, GAPDH, G3PDH, E2F, rp49) in four lepidopteran insects Bombyx mori L. (Lepidoptera: Bombycidae), Plutella xylostella L. (Plutellidae), Chilo suppressalis Walker (Crambidae), and Spodoptera exigua Hübner (Noctuidae) to study their expression stability. The algorithms of geNorm, NormFinder, stability index, and ΔCt analysis were used to evaluate these HKGs. Across different developmental stages, actin A1 was the most stable in P. xylostella and C. suppressalis, but it was the least stable in B. mori and S. exigua. Rp49 and GAPDH were the most stable in B. mori and S. exigua, respectively. In different tissues, GAPDH, E2F, and Rp49 were the most stable in B. mori, S. exigua, and C. suppressalis, respectively. The relative abundances of Siwi genes estimated by 2(-ΔΔCt) method were tested with different HKGs as the reference gene, proving the importance of internal controls in qPCR data analysis. The results not only presented a list of suitable reference genes in four lepidopteran insects, but also proved that the expression stabilities of HKGs were different among evolutionarily close species. There was no single universal reference gene that could be used in all situations. It is indispensable to validate the expression of HKGs before using them as the internal control in qPCR.

Validation of endogenous normalizing genes for expression analyses in adult human testis and germ cell neoplasms.

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Svingen, T; Jørgensen, A; Rajpert-De Meyts, E

2014-08-01

The measurement of gene expression levels in cells and tissues typically depends on a suitable point of reference for inferring biological relevance. For quantitative (or real-time) RT-PCR assays, the method of choice is often to normalize gene expression data to an endogenous gene that is stably expressed across the samples analysed: a so-called normalizing or housekeeping gene. Although this is a valid strategy, the identification of stable normalizing genes has proved challenging and a gene showing stable expression across all cells or tissues is unlikely to exist. Therefore, it is necessary to define suitable normalizing genes for specific cells and tissues. Here, we report on the performance of a panel of nine commonly employed normalizing genes in adult human testis and testicular pathologies. Our analyses revealed significant variability in transcript abundance for commonly used normalizers, highlighting the importance of selecting appropriate normalizing genes as comparative measurements can yield variable results when different normalizing genes are employed. Based on our results, we recommend using RPS20, RPS29 or SRSF4 when analysing relative gene expression levels in human testis and associated testicular pathologies. OCT4 and SALL4 can be used with caution as second-tier normalizers when determining changes in gene expression in germ cells and germ cell tumour components, but the relative transcript abundance appears variable between different germ cell tumour types. We further recommend that such studies should be accompanied by additional assessment of histology and cellularity of each sample. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Validation of reference genes for gene expression analysis in olive (Olea europaea) mesocarp tissue by quantitative real-time RT-PCR

Science.gov (United States)

2014-01-01

Background Gene expression analysis using quantitative reverse transcription PCR (qRT-PCR) is a robust method wherein the expression levels of target genes are normalised using internal control genes, known as reference genes, to derive changes in gene expression levels. Although reference genes have recently been suggested for olive tissues, combined/independent analysis on different cultivars has not yet been tested. Therefore, an assessment of reference genes was required to validate the recent findings and select stably expressed genes across different olive cultivars. Results A total of eight candidate reference genes [glyceraldehyde 3-phosphate dehydrogenase (GAPDH), serine/threonine-protein phosphatase catalytic subunit (PP2A), elongation factor 1 alpha (EF1-alpha), polyubiquitin (OUB2), aquaporin tonoplast intrinsic protein (TIP2), tubulin alpha (TUBA), 60S ribosomal protein L18-3 (60S RBP L18-3) and polypyrimidine tract-binding protein homolog 3 (PTB)] were chosen based on their stability in olive tissues as well as in other plants. Expression stability was examined by qRT-PCR across 12 biological samples, representing mesocarp tissues at various developmental stages in three different olive cultivars, Barnea, Frantoio and Picual, independently and together during the 2009 season with two software programs, GeNorm and BestKeeper. Both software packages identified GAPDH, EF1-alpha and PP2A as the three most stable reference genes across the three cultivars and in the cultivar, Barnea. GAPDH, EF1-alpha and 60S RBP L18-3 were found to be most stable reference genes in the cultivar Frantoio while 60S RBP L18-3, OUB2 and PP2A were found to be most stable reference genes in the cultivar Picual. Conclusions The analyses of expression stability of reference genes using qRT-PCR revealed that GAPDH, EF1-alpha, PP2A, 60S RBP L18-3 and OUB2 are suitable reference genes for expression analysis in developing Olea europaea mesocarp tissues, displaying the highest level

Identification of valid endogenous control genes for determining gene expression in C6 glioma cell line treated with conditioned medium from adipose-derived stem cell.

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Iser, I C; de Campos, R P; Bertoni, A P S; Wink, M R

2015-10-01

There is growing evidence that mesenchymal stem cells (MSCs) can be important players in the tumor microenvironment. They can affect the glioma progression through the modulation of different genes. This modulation can be evaluated through a very useful model, treating the tumor cells with MSC-conditioned medium. However, for an accurate and reliable gene expression analysis, normalization of gene expression data against reference genes is a prerequisite. We performed a systematic review in an attempt to find a reference gene to use when analyzing gene expression in C6 glioma cells lines. Considering that we were not able to find a reference gene originated by an appropriate validation, in this study we evaluated candidate genes to be used as reference gene in C6 cells under different treatments with adipose-derived stem cells conditioned medium (CM-ADSCs). β-actin (ACTB); glyceraldehyde-3-phosphate dehydrogenase (GAPDH); hypoxanthine-guanine phosphoribosyltransferase I (HPRT-1); TATA box binding protein (TBP) and beta-2-microglobulin (B2M) were evaluated by real-time reverse transcription PCR (RT-qPCR). The mean Cq, the maximum fold change (MFC) and NormFinder software were used for reference gene evaluation and selection. The GAPDH and ACTB genes have been the most widely used reference genes to normalize among the different investigated genes in our review, however, controversially these genes underwent a substantial variability among the genes evaluated in the present work. Individually, TBP gene was more stable when compared with other genes analyzed and the combination of TBP and HPRT-1 was even more stable. These results evidence the importance of appropriate validation of reference genes before performing qPCR experiments. Besides, our data will contribute with researchers that work analyzing the role of ADSCs in glioma microenvironment through gene expression. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Selection and validation of reference genes for miRNA expression studies during porcine pregnancy.

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Jocelyn M Wessels

Full Text Available MicroRNAs comprise a family of small non-coding RNAs that modulate several developmental and physiological processes including pregnancy. Their ubiquitous presence is confirmed in mammals, worms, flies and plants. Although rapid advances have been made in microRNA research, information on stable reference genes for validation of microRNA expression is still lacking. Real time PCR is a widely used tool to quantify gene transcripts. An appropriate reference gene must be chosen to minimize experimental error in this system. A small difference in miRNA levels between experimental samples can be biologically meaningful as these entities can affect multiple targets in a pathway. This study examined the suitability of six commercially available reference genes (RNU1A, RNU5A, RNU6B, SNORD25, SCARNA17, and SNORA73A in maternal-fetal tissues from healthy and spontaneously arresting/dying conceptuses from sows were separately analyzed at gestation day 20. Comparisons were also made with non-pregnant endometrial tissues from sows. Spontaneous fetal loss is a prime concern to the commercial pork industry. Our laboratory has previously identified deficits in vasculature development at maternal-fetal interface as one of the major participating causes of fetal loss. Using this well-established model, we have extended our studies to identify suitable microRNA reference genes. A methodical approach to assessing suitability was adopted using standard curve and melting curve analysis, PCR product sequencing, real time PCR expression in a panel of gestational tissues, and geNorm and NormFinder analysis. Our quantitative real time PCR analysis confirmed expression of all 6 reference genes in maternal and fetal tissues. All genes were uniformly expressed in tissues from healthy and spontaneously arresting conceptus attachment sites. Comparisons between tissue types (maternal/fetal/non-pregnant revealed significant differences for RNU5A, RNU6B, SCARNA17, and SNORA73A

Validation of Reference Genes for Quantitative Expression Analysis by Real-Time RT-PCR in Four Lepidopteran Insects

OpenAIRE

Teng, Xiaolu; Zhang, Zan; He, Guiling; Yang, Liwen; Li, Fei

2012-01-01

Quantitative real-time polymerase chain reaction (qPCR) is an efficient and widely used technique to monitor gene expression. Housekeeping genes (HKGs) are often empirically selected as the reference genes for data normalization. However, the suitability of HKGs used as the reference genes has been seldom validated. Here, six HKGs were chosen (actin A3, actin A1, GAPDH, G3PDH, E2F, rp49) in four lepidopteran insects Bombyx mori L. (Lepidoptera: Bombycidae), Plutella xylostella L. (Plutellidae...

Expression profiling identifies genes involved in emphysema severity

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Bowman Rayleen V

2009-09-01

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

Validation of Tuba1a as Appropriate Internal Control for Normalization of Gene Expression Analysis during Mouse Lung Development

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Aditi Mehta

2015-02-01

Full Text Available The expression ratio between the analysed gene and an internal control gene is the most widely used normalization method for quantitative RT-PCR (qRT-PCR expression analysis. The ideal reference gene for a specific experiment is the one whose expression is not affected by the different experimental conditions tested. In this study, we validate the applicability of five commonly used reference genes during different stages of mouse lung development. The stability of expression of five different reference genes (Tuba1a, Actb Gapdh, Rn18S and Hist4h4 was calculated within five experimental groups using the statistical algorithm of geNorm software. Overall, Tuba1a showed the least variability in expression among the different stages of lung development, while Hist4h4 and Rn18S showed the maximum variability in their expression. Expression analysis of two lung specific markers, surfactant protein C (SftpC and Clara cell-specific 10 kDA protein (Scgb1a1, normalized to each of the five reference genes tested here, confirmed our results and showed that incorrect reference gene choice can lead to artefacts. Moreover, a combination of two internal controls for normalization of expression analysis during lung development will increase the accuracy and reliability of results.

Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L. gene expression oligonucleotide microarray.

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Paula Fernandez

Full Text Available Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de. The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons. The resulting Sunflower Unigen Resource (SUR version 1.0 was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01 allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

A Marfan syndrome gene expression phenotype in cultured skin fibroblasts

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Emond Mary

2007-09-01

Full Text Available Abstract Background Marfan syndrome (MFS is a heritable connective tissue disorder caused by mutations in the fibrillin-1 gene. This syndrome constitutes a significant identifiable subtype of aortic aneurysmal disease, accounting for over 5% of ascending and thoracic aortic aneurysms. Results We used spotted membrane DNA macroarrays to identify genes whose altered expression levels may contribute to the phenotype of the disease. Our analysis of 4132 genes identified a subset with significant expression differences between skin fibroblast cultures from unaffected controls versus cultures from affected individuals with known fibrillin-1 mutations. Subsequently, 10 genes were chosen for validation by quantitative RT-PCR. Conclusion Differential expression of many of the validated genes was associated with MFS samples when an additional group of unaffected and MFS affected subjects were analyzed (p-value -6 under the null hypothesis that expression levels in cultured fibroblasts are unaffected by MFS status. An unexpected observation was the range of individual gene expression. In unaffected control subjects, expression ranges exceeding 10 fold were seen in many of the genes selected for qRT-PCR validation. The variation in expression in the MFS affected subjects was even greater.

Understanding gene expression in coronary artery disease through ...

Indian Academy of Sciences (India)

Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes. Prathima ... Table 2. Differentially expressed genes in CAD compared to age and gender matched controls. .... Regulation of nuclear pre-mRNA domain containing 1A.

Gene expression studies of reference genes for quantitative real-time PCR: an overview in insects.

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Shakeel, Muhammad; Rodriguez, Alicia; Tahir, Urfa Bin; Jin, Fengliang

2018-02-01

Whenever gene expression is being examined, it is essential that a normalization process is carried out to eliminate non-biological variations. The use of reference genes, such as glyceraldehyde-3-phosphate dehydrogenase, actin, and ribosomal protein genes, is the usual method of choice for normalizing gene expression. Although reference genes are used to normalize target gene expression, a major problem is that the stability of these genes differs among tissues, developmental stages, species, and responses to abiotic factors. Therefore, the use and validation of multiple reference genes are required. This review discusses the reasons that why RT-qPCR has become the preferred method for validating results of gene expression profiles, the use of specific and non-specific dyes and the importance of use of primers and probes for qPCR as well as to discuss several statistical algorithms developed to help the validation of potential reference genes. The conflicts arising in the use of classical reference genes in gene normalization and their replacement with novel references are also discussed by citing the high stability and low stability of classical and novel reference genes under various biotic and abiotic experimental conditions by employing various methods applied for the reference genes amplification.

Identification and validation of superior reference gene for gene expression normalization via RT-qPCR in staminate and pistillate flowers of Jatropha curcas - A biodiesel plant.

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Karuppaiya, Palaniyandi; Yan, Xiao-Xue; Liao, Wang; Wu, Jun; Chen, Fang; Tang, Lin

2017-01-01

Physic nut (Jatropha curcas L) seed oil is a natural resource for the alternative production of fossil fuel. Seed oil production is mainly depended on seed yield, which was restricted by the low ratio of staminate flowers to pistillate flowers. Further, the mechanism of physic nut flower sex differentiation has not been fully understood yet. Quantitative Real Time-Polymerase Chain Reaction is a reliable and widely used technique to quantify the gene expression pattern in biological samples. However, for accuracy of qRT-PCR, appropriate reference gene is highly desirable to quantify the target gene level. Hence, the present study was aimed to identify the stable reference genes in staminate and pistillate flowers of J. curcas. In this study, 10 candidate reference genes were selected and evaluated for their expression stability in staminate and pistillate flowers, and their stability was validated by five different algorithms (ΔCt, BestKeeper, NormFinder, GeNorm and RefFinder). Resulting, TUB and EF found to be the two most stably expressed reference for staminate flower; while GAPDH1 and EF found to be the most stably expressed reference gene for pistillate flowers. Finally, RT-qPCR assays of target gene AGAMOUS using the identified most stable reference genes confirmed the reliability of selected reference genes in different stages of flower development. AGAMOUS gene expression levels at different stages were further proved by gene copy number analysis. Therefore, the present study provides guidance for selecting appropriate reference genes for analyzing the expression pattern of floral developmental genes in staminate and pistillate flowers of J. curcas.

The effects of antenatal depression and antidepressant treatment on placental gene expression

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Jocelien DA Olivier

2015-01-01

Full Text Available The effects of antenatal depression and antidepressant treatment during pregnancy on both mother and child are vigorously studied, but the underlying biology for these effects is largely unknown. The placenta plays a crucial role in the growth and development of the fetus. We performed a gene expression study on the fetal side of the placenta to investigate gene expression patterns in mothers with antenatal depression and in mothers using antidepressant treatment during pregnancy.Placental samples from mothers with normal pregnancies, from mothers with antenatal depression, and from mothers using antidepressants were collected. We performed a pilot microarray study to investigate alterations in the gene expression and selected several genes from the microarray for biological validation with qPCR in a larger sample.In mothers with antenatal depression 108 genes were differentially expressed, whereas 109 genes were differentially expressed in those using antidepressants. Validation of the microarray revealed more robust gene expression differences in the seven genes picked for confirmation in antidepressant-treated women than in depressed women. Among the genes that were validated ROCK2 and C12orf39 were differentially expressed in both depressed and antidepressant-treated women, whereas ROCK1, GCC2, KTN1, and DNM1L were only differentially expressed in the antidepressant-treated women. In conclusion, antenatal depression and antidepressant exposure during pregnancy are associated with altered gene expression in the placenta. Findings on those genes picked for validation were more robust among antidepressant-treated women than in depressed women, possibly due to the fact that depression is a multifactorial condition with varying degrees of endocrine disruption. It remains to be established whether the alterations found in the gene expression of the placenta are found in the fetus as well.

Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

KAUST Repository

Othoum, Ghofran K

2013-05-01

Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

KAUST Repository

Othoum, Ghofran K

2013-01-01

Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

Decentral gene expression analysis: analytical validation of the Endopredict genomic multianalyte breast cancer prognosis test

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Kronenwett Ralf

2012-10-01

Full Text Available Abstract Background EndoPredict (EP is a clinically validated multianalyte gene expression test to predict distant metastasis in ER-positive, HER2-negative breast cancer treated with endocrine therapy alone. The test is based on the combined analysis of 12 genes in formalin-fixed, paraffin-embedded (FFPE tissue by reverse transcription-quantitative real-time PCR (RT-qPCR. Recently, it was shown that EP is feasible for reliable decentralized assessment of gene expression. The aim of this study was the analytical validation of the performance characteristics of the assay and its verification in a molecular-pathological routine laboratory. Methods Gene expression values to calculate the EP score were assayed by one-step RT-qPCR using RNA from FFPE tumor tissue. Limit of blank, limit of detection, linear range, and PCR efficiency were assessed for each of the 12 PCR assays using serial samples dilutions. Different breast cancer samples were used to evaluate RNA input range, precision and inter-laboratory variability. Results PCR assays were linear up to Cq values between 35.1 and 37.2. Amplification efficiencies ranged from 75% to 101%. The RNA input range without considerable change of the EP score was between 0.16 and 18.5 ng/μl. Analysis of precision (variation of day, day time, instrument, operator, reagent lots resulted in a total noise (standard deviation of 0.16 EP score units on a scale from 0 to 15. The major part of the total noise (SD 0.14 was caused by the replicate-to-replicate noise of the PCR assays (repeatability and was not associated with different operating conditions (reproducibility. Performance characteristics established in the manufacturer’s laboratory were verified in a routine molecular pathology laboratory. Comparison of 10 tumor samples analyzed in two different laboratories showed a Pearson coefficient of 0.995 and a mean deviation of 0.15 score units. Conclusions The EP test showed reproducible performance

Decentral gene expression analysis: analytical validation of the Endopredict genomic multianalyte breast cancer prognosis test

International Nuclear Information System (INIS)

Kronenwett, Ralf; Brase, Jan C; Weber, Karsten E; Fisch, Karin; Müller, Berit M; Schmidt, Marcus; Filipits, Martin; Dubsky, Peter; Petry, Christoph; Dietel, Manfred; Denkert, Carsten; Bohmann, Kerstin; Prinzler, Judith; Sinn, Bruno V; Haufe, Franziska; Roth, Claudia; Averdick, Manuela; Ropers, Tanja; Windbergs, Claudia

2012-01-01

EndoPredict (EP) is a clinically validated multianalyte gene expression test to predict distant metastasis in ER-positive, HER2-negative breast cancer treated with endocrine therapy alone. The test is based on the combined analysis of 12 genes in formalin-fixed, paraffin-embedded (FFPE) tissue by reverse transcription-quantitative real-time PCR (RT-qPCR). Recently, it was shown that EP is feasible for reliable decentralized assessment of gene expression. The aim of this study was the analytical validation of the performance characteristics of the assay and its verification in a molecular-pathological routine laboratory. Gene expression values to calculate the EP score were assayed by one-step RT-qPCR using RNA from FFPE tumor tissue. Limit of blank, limit of detection, linear range, and PCR efficiency were assessed for each of the 12 PCR assays using serial samples dilutions. Different breast cancer samples were used to evaluate RNA input range, precision and inter-laboratory variability. PCR assays were linear up to C q values between 35.1 and 37.2. Amplification efficiencies ranged from 75% to 101%. The RNA input range without considerable change of the EP score was between 0.16 and 18.5 ng/μl. Analysis of precision (variation of day, day time, instrument, operator, reagent lots) resulted in a total noise (standard deviation) of 0.16 EP score units on a scale from 0 to 15. The major part of the total noise (SD 0.14) was caused by the replicate-to-replicate noise of the PCR assays (repeatability) and was not associated with different operating conditions (reproducibility). Performance characteristics established in the manufacturer’s laboratory were verified in a routine molecular pathology laboratory. Comparison of 10 tumor samples analyzed in two different laboratories showed a Pearson coefficient of 0.995 and a mean deviation of 0.15 score units. The EP test showed reproducible performance characteristics with good precision and negligible laboratory

Selection and validation of reference genes for quantitative gene expression analyses in various tissues and seeds at different developmental stages in Bixa orellana L.

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Moreira, Viviane S; Soares, Virgínia L F; Silva, Raner J S; Sousa, Aurizangela O; Otoni, Wagner C; Costa, Marcio G C

2018-05-01

Bixa orellana L., popularly known as annatto, produces several secondary metabolites of pharmaceutical and industrial interest, including bixin, whose molecular basis of biosynthesis remain to be determined. Gene expression analysis by quantitative real-time PCR (qPCR) is an important tool to advance such knowledge. However, correct interpretation of qPCR data requires the use of suitable reference genes in order to reduce experimental variations. In the present study, we have selected four different candidates for reference genes in B. orellana , coding for 40S ribosomal protein S9 (RPS9), histone H4 (H4), 60S ribosomal protein L38 (RPL38) and 18S ribosomal RNA (18SrRNA). Their expression stabilities in different tissues (e.g. flower buds, flowers, leaves and seeds at different developmental stages) were analyzed using five statistical tools (NormFinder, geNorm, BestKeeper, ΔCt method and RefFinder). The results indicated that RPL38 is the most stable gene in different tissues and stages of seed development and 18SrRNA is the most unstable among the analyzed genes. In order to validate the candidate reference genes, we have analyzed the relative expression of a target gene coding for carotenoid cleavage dioxygenase 1 (CCD1) using the stable RPL38 and the least stable gene, 18SrRNA , for normalization of the qPCR data. The results demonstrated significant differences in the interpretation of the CCD1 gene expression data, depending on the reference gene used, reinforcing the importance of the correct selection of reference genes for normalization.

With Reference to Reference Genes: A Systematic Review of Endogenous Controls in Gene Expression Studies.

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Chapman, Joanne R; Waldenström, Jonas

2015-01-01

The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR gene expression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate gene expression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies.

Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis

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dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

2015-01-01

Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis. PMID:26393928

Development and validation of a gene expression-based signature to predict distant metastasis in locoregionally advanced nasopharyngeal carcinoma: a retrospective, multicentre, cohort study.

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Tang, Xin-Ran; Li, Ying-Qin; Liang, Shao-Bo; Jiang, Wei; Liu, Fang; Ge, Wen-Xiu; Tang, Ling-Long; Mao, Yan-Ping; He, Qing-Mei; Yang, Xiao-Jing; Zhang, Yuan; Wen, Xin; Zhang, Jian; Wang, Ya-Qin; Zhang, Pan-Pan; Sun, Ying; Yun, Jing-Ping; Zeng, Jing; Li, Li; Liu, Li-Zhi; Liu, Na; Ma, Jun

2018-03-01

Gene expression patterns can be used as prognostic biomarkers in various types of cancers. We aimed to identify a gene expression pattern for individual distant metastatic risk assessment in patients with locoregionally advanced nasopharyngeal carcinoma. In this multicentre, retrospective, cohort analysis, we included 937 patients with locoregionally advanced nasopharyngeal carcinoma from three Chinese hospitals: the Sun Yat-sen University Cancer Center (Guangzhou, China), the Affiliated Hospital of Guilin Medical University (Guilin, China), and the First People's Hospital of Foshan (Foshan, China). Using microarray analysis, we profiled mRNA gene expression between 24 paired locoregionally advanced nasopharyngeal carcinoma tumours from patients at Sun Yat-sen University Cancer Center with or without distant metastasis after radical treatment. Differentially expressed genes were examined using digital expression profiling in a training cohort (Guangzhou training cohort; n=410) to build a gene classifier using a penalised regression model. We validated the prognostic accuracy of this gene classifier in an internal validation cohort (Guangzhou internal validation cohort, n=204) and two external independent cohorts (Guilin cohort, n=165; Foshan cohort, n=158). The primary endpoint was distant metastasis-free survival. Secondary endpoints were disease-free survival and overall survival. We identified 137 differentially expressed genes between metastatic and non-metastatic locoregionally advanced nasopharyngeal carcinoma tissues. A distant metastasis gene signature for locoregionally advanced nasopharyngeal carcinoma (DMGN) that consisted of 13 genes was generated to classify patients into high-risk and low-risk groups in the training cohort. Patients with high-risk scores in the training cohort had shorter distant metastasis-free survival (hazard ratio [HR] 4·93, 95% CI 2·99-8·16; padvanced nasopharyngeal carcinoma and might be able to predict which patients benefit

Validation of putative reference genes for gene expression studies in human hepatocellular carcinoma using real-time quantitative RT-PCR

International Nuclear Information System (INIS)

Cicinnati, Vito R; Shen, Qingli; Sotiropoulos, Georgios C; Radtke, Arnold; Gerken, Guido; Beckebaum, Susanne

2008-01-01

Reference genes, which are often referred to as housekeeping genes are frequently used to normalize mRNA levels between different samples in quantitative reverse transcription polymerase chain reaction (qRT-PCR). The selection of reference genes is critical for gene expression studies because the expression of these genes may vary among tissues or cells and may change under certain circumstances. Here, a systematic evaluation of six putative reference genes for gene expression studies in human hepatocellular carcinoma (HCC) is presented. Six genes, beta-2-microglobulin (B2M), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), hydroxymethyl-bilane synthase (HMBS), hypoxanthine phosphoribosyl-transferase 1 (HPRT1), succinate dehydrogenase complex, subunit A (SDHA) and ubiquitin C (UBC), with distinct functional characteristics and expression patterns were evaluated by qRT-PCR. Inhibitory substances in RNA samples were quantitatively assessed and controlled using an external RNA control. The stability of selected reference genes was analyzed using both geNorm and NormFinder software. HMBS and GAPDH were identified as the optimal reference genes for normalizing gene expression data between paired tumoral and adjacent non-tumoral tissues derived from patients with HCC. HMBS, GAPDH and UBC were identified to be suitable for the normalization of gene expression data among tumor tissues; whereas the combination of HMBS, B2M, SDHA and GAPDH was suitable for normalizing gene expression data among five liver cancer cell lines, namely Hep3B, HepG2, HuH7, SK-HEP-1 and SNU-182. The determined gene stability was increased after exclusion of RNA samples containing relatively higher inhibitory substances. Of six genes studied, HMBS was found to be the single best reference gene for gene expression studies in HCC. The appropriate choice of combination of more than one reference gene to improve qRT-PCR accuracy depends on the kind of liver tissues or cells under investigation

Validation of putative reference genes for gene expression studies in human hepatocellular carcinoma using real-time quantitative RT-PCR

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Radtke Arnold

2008-11-01

Full Text Available Abstract Background Reference genes, which are often referred to as housekeeping genes are frequently used to normalize mRNA levels between different samples in quantitative reverse transcription polymerase chain reaction (qRT-PCR. The selection of reference genes is critical for gene expression studies because the expression of these genes may vary among tissues or cells and may change under certain circumstances. Here, a systematic evaluation of six putative reference genes for gene expression studies in human hepatocellular carcinoma (HCC is presented. Methods Six genes, beta-2-microglobulin (B2M, glyceraldehyde-3-phosphate dehydrogenase (GAPDH, hydroxymethyl-bilane synthase (HMBS, hypoxanthine phosphoribosyl-transferase 1 (HPRT1, succinate dehydrogenase complex, subunit A (SDHA and ubiquitin C (UBC, with distinct functional characteristics and expression patterns were evaluated by qRT-PCR. Inhibitory substances in RNA samples were quantitatively assessed and controlled using an external RNA control. The stability of selected reference genes was analyzed using both geNorm and NormFinder software. Results HMBS and GAPDH were identified as the optimal reference genes for normalizing gene expression data between paired tumoral and adjacent non-tumoral tissues derived from patients with HCC. HMBS, GAPDH and UBC were identified to be suitable for the normalization of gene expression data among tumor tissues; whereas the combination of HMBS, B2M, SDHA and GAPDH was suitable for normalizing gene expression data among five liver cancer cell lines, namely Hep3B, HepG2, HuH7, SK-HEP-1 and SNU-182. The determined gene stability was increased after exclusion of RNA samples containing relatively higher inhibitory substances. Conclusion Of six genes studied, HMBS was found to be the single best reference gene for gene expression studies in HCC. The appropriate choice of combination of more than one reference gene to improve qRT-PCR accuracy depends on the

Validation of putative reference genes for gene expression studies in human hepatocellular carcinoma using real-time quantitative RT-PCR

Science.gov (United States)

Cicinnati, Vito R; Shen, Qingli; Sotiropoulos, Georgios C; Radtke, Arnold; Gerken, Guido; Beckebaum, Susanne

2008-01-01

Background Reference genes, which are often referred to as housekeeping genes are frequently used to normalize mRNA levels between different samples in quantitative reverse transcription polymerase chain reaction (qRT-PCR). The selection of reference genes is critical for gene expression studies because the expression of these genes may vary among tissues or cells and may change under certain circumstances. Here, a systematic evaluation of six putative reference genes for gene expression studies in human hepatocellular carcinoma (HCC) is presented. Methods Six genes, beta-2-microglobulin (B2M), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), hydroxymethyl-bilane synthase (HMBS), hypoxanthine phosphoribosyl-transferase 1 (HPRT1), succinate dehydrogenase complex, subunit A (SDHA) and ubiquitin C (UBC), with distinct functional characteristics and expression patterns were evaluated by qRT-PCR. Inhibitory substances in RNA samples were quantitatively assessed and controlled using an external RNA control. The stability of selected reference genes was analyzed using both geNorm and NormFinder software. Results HMBS and GAPDH were identified as the optimal reference genes for normalizing gene expression data between paired tumoral and adjacent non-tumoral tissues derived from patients with HCC. HMBS, GAPDH and UBC were identified to be suitable for the normalization of gene expression data among tumor tissues; whereas the combination of HMBS, B2M, SDHA and GAPDH was suitable for normalizing gene expression data among five liver cancer cell lines, namely Hep3B, HepG2, HuH7, SK-HEP-1 and SNU-182. The determined gene stability was increased after exclusion of RNA samples containing relatively higher inhibitory substances. Conclusion Of six genes studied, HMBS was found to be the single best reference gene for gene expression studies in HCC. The appropriate choice of combination of more than one reference gene to improve qRT-PCR accuracy depends on the kind of liver tissues

Development and validation of a gene profile predicting benefit of postmastectomy radiotherapy in patients with high-risk breast cancer: a study of gene expression in the DBCG82bc cohort.

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Tramm, Trine; Mohammed, Hayat; Myhre, Simen; Kyndi, Marianne; Alsner, Jan; Børresen-Dale, Anne-Lise; Sørlie, Therese; Frigessi, Arnoldo; Overgaard, Jens

2014-10-15

To identify genes predicting benefit of radiotherapy in patients with high-risk breast cancer treated with systemic therapy and randomized to receive or not receive postmastectomy radiotherapy (PMRT). The study was based on the Danish Breast Cancer Cooperative Group (DBCG82bc) cohort. Gene-expression analysis was performed in a training set of frozen tumor tissue from 191 patients. Genes were identified through the Lasso method with the endpoint being locoregional recurrence (LRR). A weighted gene-expression index (DBCG-RT profile) was calculated and transferred to quantitative real-time PCR (qRT-PCR) in corresponding formalin-fixed, paraffin-embedded (FFPE) samples, before validation in FFPE from 112 additional patients. Seven genes were identified, and the derived DBCG-RT profile divided the 191 patients into "high LRR risk" and "low LRR risk" groups. PMRT significantly reduced risk of LRR in "high LRR risk" patients, whereas "low LRR risk" patients showed no additional reduction in LRR rate. Technical transfer of the DBCG-RT profile to FFPE/qRT-PCR was successful, and the predictive impact was successfully validated in another 112 patients. A DBCG-RT gene profile was identified and validated, identifying patients with very low risk of LRR and no benefit from PMRT. The profile may provide a method to individualize treatment with PMRT. ©2014 American Association for Cancer Research.

Validating Internal Control Genes for the Accurate Normalization of qPCR Expression Analysis of the Novel Model Plant Setaria viridis.

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Julia Lambret-Frotté

Full Text Available Employing reference genes to normalize the data generated with quantitative PCR (qPCR can increase the accuracy and reliability of this method. Previous results have shown that no single housekeeping gene can be universally applied to all experiments. Thus, the identification of a suitable reference gene represents a critical step of any qPCR analysis. Setaria viridis has recently been proposed as a model system for the study of Panicoid grasses, a crop family of major agronomic importance. Therefore, this paper aims to identify suitable S. viridis reference genes that can enhance the analysis of gene expression in this novel model plant. The first aim of this study was the identification of a suitable RNA extraction method that could retrieve a high quality and yield of RNA. After this, two distinct algorithms were used to assess the gene expression of fifteen different candidate genes in eighteen different samples, which were divided into two major datasets, the developmental and the leaf gradient. The best-ranked pair of reference genes from the developmental dataset included genes that encoded a phosphoglucomutase and a folylpolyglutamate synthase; genes that encoded a cullin and the same phosphoglucomutase as above were the most stable genes in the leaf gradient dataset. Additionally, the expression pattern of two target genes, a SvAP3/PI MADS-box transcription factor and the carbon-fixation enzyme PEPC, were assessed to illustrate the reliability of the chosen reference genes. This study has shown that novel reference genes may perform better than traditional housekeeping genes, a phenomenon which has been previously reported. These results illustrate the importance of carefully validating reference gene candidates for each experimental set before employing them as universal standards. Additionally, the robustness of the expression of the target genes may increase the utility of S. viridis as a model for Panicoid grasses.

Reference gene validation for gene expression normalization in canine osteosarcoma : a geNorm algorithm approach

NARCIS (Netherlands)

Selvarajah, G.T.; Bonestroo, F.A.S.; Timmermans Sprang, E.P.M.; Kirpensteijn, J.|info:eu-repo/dai/nl/189846992; Mol, J.A.|info:eu-repo/dai/nl/070918775

2017-01-01

Background Quantitative PCR (qPCR) is a common method for quantifying mRNA expression. Given the heterogeneity present in tumor tissues, it is crucial to normalize target mRNA expression data using appropriate reference genes that are stably expressed under a variety of pathological and experimental

Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.

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Neutelings Godfrey

2010-04-01

Full Text Available Abstract Background Quantitative real-time PCR (qRT-PCR is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs. Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L. Results Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups. qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59. LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both ge

Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.).

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Huis, Rudy; Hawkins, Simon; Neutelings, Godfrey

2010-04-19

Quantitative real-time PCR (qRT-PCR) is currently the most accurate method for detecting differential gene expression. Such an approach depends on the identification of uniformly expressed 'housekeeping genes' (HKGs). Extensive transcriptomic data mining and experimental validation in different model plants have shown that the reliability of these endogenous controls can be influenced by the plant species, growth conditions and organs/tissues examined. It is therefore important to identify the best reference genes to use in each biological system before using qRT-PCR to investigate differential gene expression. In this paper we evaluate different candidate HKGs for developmental transcriptomic studies in the economically-important flax fiber- and oil-crop (Linum usitatissimum L). Specific primers were designed in order to quantify the expression levels of 20 different potential housekeeping genes in flax roots, internal- and external-stem tissues, leaves and flowers at different developmental stages. After calculations of PCR efficiencies, 13 HKGs were retained and their expression stabilities evaluated by the computer algorithms geNorm and NormFinder. According to geNorm, 2 Transcriptional Elongation Factors (TEFs) and 1 Ubiquitin gene are necessary for normalizing gene expression when all studied samples are considered. However, only 2 TEFs are required for normalizing expression in stem tissues. In contrast, NormFinder identified glyceraldehyde-3-phosphate dehydrogenase (GADPH) as the most stably expressed gene when all samples were grouped together, as well as when samples were classed into different sub-groups.qRT-PCR was then used to investigate the relative expression levels of two splice variants of the flax LuMYB1 gene (homologue of AtMYB59). LuMYB1-1 and LuMYB1-2 were highly expressed in the internal stem tissues as compared to outer stem tissues and other samples. This result was confirmed with both geNorm-designated- and Norm

Stably Expressed Genes Involved in Basic Cellular Functions.

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Kejian Wang

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

Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies

Science.gov (United States)

2014-01-01

Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods. PMID:24708878

Transcriptome-wide selection of a reliable set of reference genes for gene expression studies in potato cyst nematodes (Globodera spp.).

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Sabeh, Michael; Duceppe, Marc-Olivier; St-Arnaud, Marc; Mimee, Benjamin

2018-01-01

Relative gene expression analyses by qRT-PCR (quantitative reverse transcription PCR) require an internal control to normalize the expression data of genes of interest and eliminate the unwanted variation introduced by sample preparation. A perfect reference gene should have a constant expression level under all the experimental conditions. However, the same few housekeeping genes selected from the literature or successfully used in previous unrelated experiments are often routinely used in new conditions without proper validation of their stability across treatments. The advent of RNA-Seq and the availability of public datasets for numerous organisms are opening the way to finding better reference genes for expression studies. Globodera rostochiensis is a plant-parasitic nematode that is particularly yield-limiting for potato. The aim of our study was to identify a reliable set of reference genes to study G. rostochiensis gene expression. Gene expression levels from an RNA-Seq database were used to identify putative reference genes and were validated with qRT-PCR analysis. Three genes, GR, PMP-3, and aaRS, were found to be very stable within the experimental conditions of this study and are proposed as reference genes for future work.

Validation of reference genes for RT-qPCR analysis in Herbaspirillum seropedicae.

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Pessoa, Daniella Duarte Villarinho; Vidal, Marcia Soares; Baldani, José Ivo; Simoes-Araujo, Jean Luiz

2016-08-01

The RT-qPCR technique needs a validated set of reference genes for ensuring the consistency of the results from the gene expression. Expression stabilities for 9 genes from Herbaspirillum seropedicae, strain HRC54, grown with different carbon sources were calculated using geNorm and NormFinder, and the gene rpoA showed the best stability values. Copyright © 2016 Elsevier B.V. All rights reserved.

Genetic Variants Contribute to Gene Expression Variability in Humans

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Hulse, Amanda M.; Cai, James J.

2013-01-01

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

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

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Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

2018-04-23

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis

Gene dosage, expression, and ontology analysis identifies driver genes in the carcinogenesis and chemoradioresistance of cervical cancer.

Directory of Open Access Journals (Sweden)

Malin Lando

2009-11-01

Full Text Available Integrative analysis of gene dosage, expression, and ontology (GO data was performed to discover driver genes in the carcinogenesis and chemoradioresistance of cervical cancers. Gene dosage and expression profiles of 102 locally advanced cervical cancers were generated by microarray techniques. Fifty-two of these patients were also analyzed with the Illumina expression method to confirm the gene expression results. An independent cohort of 41 patients was used for validation of gene expressions associated with clinical outcome. Statistical analysis identified 29 recurrent gains and losses and 3 losses (on 3p, 13q, 21q associated with poor outcome after chemoradiotherapy. The intratumor heterogeneity, assessed from the gene dosage profiles, was low for these alterations, showing that they had emerged prior to many other alterations and probably were early events in carcinogenesis. Integration of the alterations with gene expression and GO data identified genes that were regulated by the alterations and revealed five biological processes that were significantly overrepresented among the affected genes: apoptosis, metabolism, macromolecule localization, translation, and transcription. Four genes on 3p (RYBP, GBE1 and 13q (FAM48A, MED4 correlated with outcome at both the gene dosage and expression level and were satisfactorily validated in the independent cohort. These integrated analyses yielded 57 candidate drivers of 24 genetic events, including novel loci responsible for chemoradioresistance. Further mapping of the connections among genetic events, drivers, and biological processes suggested that each individual event stimulates specific processes in carcinogenesis through the coordinated control of multiple genes. The present results may provide novel therapeutic opportunities of both early and advanced stage cervical cancers.

Differential gene expression between African American and European American colorectal cancer patients.

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Biljana Jovov

Full Text Available The incidence and mortality of colorectal cancer (CRC is higher in African Americans (AAs than other ethnic groups in the U. S., but reasons for the disparities are unknown. We performed gene expression profiling of sporadic CRCs from AAs vs. European Americans (EAs to assess the contribution to CRC disparities. We evaluated the gene expression of 43 AA and 43 EA CRC tumors matched by stage and 40 matching normal colorectal tissues using the Agilent human whole genome 4x44K cDNA arrays. Gene and pathway analyses were performed using Significance Analysis of Microarrays (SAM, Ten-fold cross validation, and Ingenuity Pathway Analysis (IPA. SAM revealed that 95 genes were differentially expressed between AA and EA patients at a false discovery rate of ≤5%. Using IPA we determined that most prominent disease and pathway associations of differentially expressed genes were related to inflammation and immune response. Ten-fold cross validation demonstrated that following 10 genes can predict ethnicity with an accuracy of 94%: CRYBB2, PSPH, ADAL, VSIG10L, C17orf81, ANKRD36B, ZNF835, ARHGAP6, TRNT1 and WDR8. Expression of these 10 genes was validated by qRT-PCR in an independent test set of 28 patients (10 AA, 18 EA. Our results are the first to implicate differential gene expression in CRC racial disparities and indicate prominent difference in CRC inflammation between AA and EA patients. Differences in susceptibility to inflammation support the existence of distinct tumor microenvironments in these two patient populations.

Screening Reliable Reference Genes for RT-qPCR Analysis of Gene Expression in Moringa oleifera.

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Deng, Li-Ting; Wu, Yu-Ling; Li, Jun-Cheng; OuYang, Kun-Xi; Ding, Mei-Mei; Zhang, Jun-Jie; Li, Shu-Qi; Lin, Meng-Fei; Chen, Han-Bin; Hu, Xin-Sheng; Chen, Xiao-Yang

2016-01-01

Moringa oleifera is a promising plant species for oil and forage, but its genetic improvement is limited. Our current breeding program in this species focuses on exploiting the functional genes associated with important agronomical traits. Here, we screened reliable reference genes for accurately quantifying the expression of target genes using the technique of real-time quantitative polymerase chain reaction (RT-qPCR) in M. oleifera. Eighteen candidate reference genes were selected from a transcriptome database, and their expression stabilities were examined in 90 samples collected from the pods in different developmental stages, various tissues, and the roots and leaves under different conditions (low or high temperature, sodium chloride (NaCl)- or polyethyleneglycol (PEG)- simulated water stress). Analyses with geNorm, NormFinder and BestKeeper algorithms revealed that the reliable reference genes differed across sample designs and that ribosomal protein L1 (RPL1) and acyl carrier protein 2 (ACP2) were the most suitable reference genes in all tested samples. The experiment results demonstrated the significance of using the properly validated reference genes and suggested the use of more than one reference gene to achieve reliable expression profiles. In addition, we applied three isotypes of the superoxide dismutase (SOD) gene that are associated with plant adaptation to abiotic stress to confirm the efficacy of the validated reference genes under NaCl and PEG water stresses. Our results provide a valuable reference for future studies on identifying important functional genes from their transcriptional expressions via RT-qPCR technique in M. oleifera.

Selection and validation of a set of reliable reference genes for quantitative sod gene expression analysis in C. elegans

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Vandesompele Jo

2008-01-01

Full Text Available Abstract Background In the nematode Caenorhabditis elegans the conserved Ins/IGF-1 signaling pathway regulates many biological processes including life span, stress response, dauer diapause and metabolism. Detection of differentially expressed genes may contribute to a better understanding of the mechanism by which the Ins/IGF-1 signaling pathway regulates these processes. Appropriate normalization is an essential prerequisite for obtaining accurate and reproducible quantification of gene expression levels. The aim of this study was to establish a reliable set of reference genes for gene expression analysis in C. elegans. Results Real-time quantitative PCR was used to evaluate the expression stability of 12 candidate reference genes (act-1, ama-1, cdc-42, csq-1, eif-3.C, mdh-1, gpd-2, pmp-3, tba-1, Y45F10D.4, rgs-6 and unc-16 in wild-type, three Ins/IGF-1 pathway mutants, dauers and L3 stage larvae. After geNorm analysis, cdc-42, pmp-3 and Y45F10D.4 showed the most stable expression pattern and were used to normalize 5 sod expression levels. Significant differences in mRNA levels were observed for sod-1 and sod-3 in daf-2 relative to wild-type animals, whereas in dauers sod-1, sod-3, sod-4 and sod-5 are differentially expressed relative to third stage larvae. Conclusion Our findings emphasize the importance of accurate normalization using stably expressed reference genes. The methodology used in this study is generally applicable to reliably quantify gene expression levels in the nematode C. elegans using quantitative PCR.

The use of molecular imaging of gene expression by radiotracers in gene therapy

International Nuclear Information System (INIS)

Richard-Fiardo, P.; Franken, P.R.; Harrington, K.J.; Vassaux, G.; Cambien, B.

2011-01-01

Introduction: Progress with gene-based therapies has been hampered by difficulties in monitoring the biodistribution and kinetics of vector-mediated gene expression. Recent developments in non-invasive imaging have allowed researchers and clinicians to assess the location, magnitude and persistence of gene expression in animals and humans. Such advances should eventually lead to improvement in the efficacy and safety of current clinical protocols for future treatments. Areas Covered: The molecular imaging techniques for monitoring gene therapy in the living subject, with a specific highlight on the key reporter gene approaches that have been developed and validated in preclinical models using the latest imaging modalities. The applications of molecular imaging to biotherapy, with a particular emphasis on monitoring of gene and vector biodistribution and on image-guided radiotherapy. Expert Opinion: Among the reporter gene/probe combinations that have been described so far, one stands out, in our view, as the most versatile and easy to implement: the Na/I symporter. This strategy, exploiting more than 50 years of experience in the treatment of differentiated thyroid carcinomas, has been validated in different types of experimental cancers and with different types of oncolytic viruses and is likely to become a key tool in the implementation of human gene therapy. (authors)

Validation of candidate genes putatively associated with resistance to SCMV and MDMV in maize (Zea mays L.) by expression profiling

DEFF Research Database (Denmark)

Uzarowska, Anna; Dionisio, Giuseppe; Sarholz, Barbara

2009-01-01

Background The potyviruses sugarcane mosaic virus (SCMV) and maize dwarf mosaic virus (MDMV) are major pathogens of maize worldwide. Two loci, Scmv1 and Scmv2, have ealier been shown to confer complete resistance to SCMV. Custom-made microarrays containing previously identified SCMV resistance...... the effectiveness and reliability of the combination of different expression profiling approaches for the identification and validation of candidate genes. Genes identified in this study represent possible future targets for manipulation of SCMV resistance in maize....

Cross-species global and subset gene expression profiling identifies genes involved in prostate cancer response to selenium

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Dhir Rajiv

2004-08-01

Full Text Available Abstract Background Gene expression technologies have the ability to generate vast amounts of data, yet there often resides only limited resources for subsequent validation studies. This necessitates the ability to perform sorting and prioritization of the output data. Previously described methodologies have used functional pathways or transcriptional regulatory grouping to sort genes for further study. In this paper we demonstrate a comparative genomics based method to leverage data from animal models to prioritize genes for validation. This approach allows one to develop a disease-based focus for the prioritization of gene data, a process that is essential for systems that lack significant functional pathway data yet have defined animal models. This method is made possible through the use of highly controlled spotted cDNA slide production and the use of comparative bioinformatics databases without the use of cross-species slide hybridizations. Results Using gene expression profiling we have demonstrated a similar whole transcriptome gene expression patterns in prostate cancer cells from human and rat prostate cancer cell lines both at baseline expression levels and after treatment with physiologic concentrations of the proposed chemopreventive agent Selenium. Using both the human PC3 and rat PAII prostate cancer cell lines have gone on to identify a subset of one hundred and fifty-four genes that demonstrate a similar level of differential expression to Selenium treatment in both species. Further analysis and data mining for two genes, the Insulin like Growth Factor Binding protein 3, and Retinoic X Receptor alpha, demonstrates an association with prostate cancer, functional pathway links, and protein-protein interactions that make these genes prime candidates for explaining the mechanism of Selenium's chemopreventive effect in prostate cancer. These genes are subsequently validated by western blots showing Selenium based induction and using

Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

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Bing Jiang

2017-01-01

Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

Gene expression and gene therapy imaging

International Nuclear Information System (INIS)

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

2007-01-01

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

Dynamic gene expression response to altered gravity in human T cells.

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Thiel, Cora S; Hauschild, Swantje; Huge, Andreas; Tauber, Svantje; Lauber, Beatrice A; Polzer, Jennifer; Paulsen, Katrin; Lier, Hartwin; Engelmann, Frank; Schmitz, Burkhard; Schütte, Andreas; Layer, Liliana E; Ullrich, Oliver

2017-07-12

We investigated the dynamics of immediate and initial gene expression response to different gravitational environments in human Jurkat T lymphocytic cells and compared expression profiles to identify potential gravity-regulated genes and adaptation processes. We used the Affymetrix GeneChip® Human Transcriptome Array 2.0 containing 44,699 protein coding genes and 22,829 non-protein coding genes and performed the experiments during a parabolic flight and a suborbital ballistic rocket mission to cross-validate gravity-regulated gene expression through independent research platforms and different sets of control experiments to exclude other factors than alteration of gravity. We found that gene expression in human T cells rapidly responded to altered gravity in the time frame of 20 s and 5 min. The initial response to microgravity involved mostly regulatory RNAs. We identified three gravity-regulated genes which could be cross-validated in both completely independent experiment missions: ATP6V1A/D, a vacuolar H + -ATPase (V-ATPase) responsible for acidification during bone resorption, IGHD3-3/IGHD3-10, diversity genes of the immunoglobulin heavy-chain locus participating in V(D)J recombination, and LINC00837, a long intergenic non-protein coding RNA. Due to the extensive and rapid alteration of gene expression associated with regulatory RNAs, we conclude that human cells are equipped with a robust and efficient adaptation potential when challenged with altered gravitational environments.

An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking

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Sujay Saha

2016-01-01

Full Text Available Most of the gene expression data analysis algorithms require the entire gene expression matrix without any missing values. Hence, it is necessary to devise methods which would impute missing data values accurately. There exist a number of imputation algorithms to estimate those missing values. This work starts with a microarray dataset containing multiple missing values. We first apply the modified version of the fuzzy theory based existing method LRFDVImpute to impute multiple missing values of time series gene expression data and then validate the result of imputation by genetic algorithm (GA based gene ranking methodology along with some regular statistical validation techniques, like RMSE method. Gene ranking, as far as our knowledge, has not been used yet to validate the result of missing value estimation. Firstly, the proposed method has been tested on the very popular Spellman dataset and results show that error margins have been drastically reduced compared to some previous works, which indirectly validates the statistical significance of the proposed method. Then it has been applied on four other 2-class benchmark datasets, like Colorectal Cancer tumours dataset (GDS4382, Breast Cancer dataset (GSE349-350, Prostate Cancer dataset, and DLBCL-FL (Leukaemia for both missing value estimation and ranking the genes, and the results show that the proposed method can reach 100% classification accuracy with very few dominant genes, which indirectly validates the biological significance of the proposed method.

Modeling and validation of autoinducer-mediated bacterial gene expression in microfluidic environments

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Austin, Caitlin M.; Stoy, William; Su, Peter; Harber, Marie C.; Bardill, J. Patrick; Hammer, Brian K.; Forest, Craig R.

2014-01-01

Biosensors exploiting communication within genetically engineered bacteria are becoming increasingly important for monitoring environmental changes. Currently, there are a variety of mathematical models for understanding and predicting how genetically engineered bacteria respond to molecular stimuli in these environments, but as sensors have miniaturized towards microfluidics and are subjected to complex time-varying inputs, the shortcomings of these models have become apparent. The effects of microfluidic environments such as low oxygen concentration, increased biofilm encapsulation, diffusion limited molecular distribution, and higher population densities strongly affect rate constants for gene expression not accounted for in previous models. We report a mathematical model that accurately predicts the biological response of the autoinducer N-acyl homoserine lactone-mediated green fluorescent protein expression in reporter bacteria in microfluidic environments by accommodating these rate constants. This generalized mass action model considers a chain of biomolecular events from input autoinducer chemical to fluorescent protein expression through a series of six chemical species. We have validated this model against experimental data from our own apparatus as well as prior published experimental results. Results indicate accurate prediction of dynamics (e.g., 14% peak time error from a pulse input) and with reduced mean-squared error with pulse or step inputs for a range of concentrations (10 μM–30 μM). This model can help advance the design of genetically engineered bacteria sensors and molecular communication devices. PMID:25379076

GSNFS: Gene subnetwork biomarker identification of lung cancer expression data.

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Doungpan, Narumol; Engchuan, Worrawat; Chan, Jonathan H; Meechai, Asawin

2016-12-05

Gene expression has been used to identify disease gene biomarkers, but there are ongoing challenges. Single gene or gene-set biomarkers are inadequate to provide sufficient understanding of complex disease mechanisms and the relationship among those genes. Network-based methods have thus been considered for inferring the interaction within a group of genes to further study the disease mechanism. Recently, the Gene-Network-based Feature Set (GNFS), which is capable of handling case-control and multiclass expression for gene biomarker identification, has been proposed, partly taking into account of network topology. However, its performance relies on a greedy search for building subnetworks and thus requires further improvement. In this work, we establish a new approach named Gene Sub-Network-based Feature Selection (GSNFS) by implementing the GNFS framework with two proposed searching and scoring algorithms, namely gene-set-based (GS) search and parent-node-based (PN) search, to identify subnetworks. An additional dataset is used to validate the results. The two proposed searching algorithms of the GSNFS method for subnetwork expansion are concerned with the degree of connectivity and the scoring scheme for building subnetworks and their topology. For each iteration of expansion, the neighbour genes of a current subnetwork, whose expression data improved the overall subnetwork score, is recruited. While the GS search calculated the subnetwork score using an activity score of a current subnetwork and the gene expression values of its neighbours, the PN search uses the expression value of the corresponding parent of each neighbour gene. Four lung cancer expression datasets were used for subnetwork identification. In addition, using pathway data and protein-protein interaction as network data in order to consider the interaction among significant genes were discussed. Classification was performed to compare the performance of the identified gene subnetworks with three

Mining gene expression data of multiple sclerosis.

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Pi Guo

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

Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value.

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Laetitia Marisa

Full Text Available Colon cancer (CC pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses.Fresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype-like, normal-like, serrated CC phenotype-like, and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II-III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse-free survival, even after

Inferring causal genomic alterations in breast cancer using gene expression data

Science.gov (United States)

2011-01-01

Background One of the primary objectives in cancer research is to identify causal genomic alterations, such as somatic copy number variation (CNV) and somatic mutations, during tumor development. Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies. Results We developed a framework for identifying recurrent regions of CNV and distinguishing the cancer driver genes from the passenger genes in the regions. By inferring CNV regions across many datasets we were able to identify 109 recurrent amplified/deleted CNV regions. Many of these regions are enriched for genes involved in many important processes associated with tumorigenesis and cancer progression. Genes in these recurrent CNV regions were then examined in the context of gene regulatory networks to prioritize putative cancer driver genes. The cancer driver genes uncovered by the framework include not only well-known oncogenes but also a number of novel cancer susceptibility genes validated via siRNA experiments. Conclusions To our knowledge, this is the first effort to systematically identify and validate drivers for expression based CNV regions in breast cancer. The framework where the wavelet analysis of copy number alteration based on expression coupled with the gene regulatory network analysis, provides a blueprint for leveraging genomic data to identify key regulatory components and gene targets. This integrative approach can be applied to many other large-scale gene expression studies and other novel types of cancer data such as next-generation sequencing based expression (RNA-Seq) as well as CNV data. PMID:21806811

GOBO: gene expression-based outcome for breast cancer online.

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Markus Ringnér

Full Text Available Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo, allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1 rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2 identification of co-expressed genes for creation of potential metagenes, 3 association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

Multiplex cDNA quantification method that facilitates the standardization of gene expression data

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Gotoh, Osamu; Murakami, Yasufumi; Suyama, Akira

2011-01-01

Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations. These requirements impose limitations on the extensive comparison of gene expression data. Here, we report an effective approach to removing the unfavorable limitations by measuring the absolute amounts of gene expression levels on common DNA microarrays. We have developed a multiplex cDNA quantification method called GEP-DEAN (Gene expression profiling by DCN-encoding-based analysis). The method was validated by using chemically synthesized DNA strands of known quantities and cDNA samples prepared from mouse liver, demonstrating that the absolute amounts of cDNA strands were successfully measured with a sensitivity of 18 zmol in a highly multiplexed manner in 7 h. PMID:21415008

Evaluation of Appropriate Reference Genes for Gene Expression Normalization during Watermelon Fruit Development.

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Qiusheng Kong

Full Text Available Gene expression analysis in watermelon (Citrullus lanatus fruit has drawn considerable attention with the availability of genome sequences to understand the regulatory mechanism of fruit development and to improve its quality. Real-time quantitative reverse-transcription PCR (qRT-PCR is a routine technique for gene expression analysis. However, appropriate reference genes for transcript normalization in watermelon fruits have not been well characterized. The aim of this study was to evaluate the appropriateness of 12 genes for their potential use as reference genes in watermelon fruits. Expression variations of these genes were measured in 48 samples obtained from 12 successive developmental stages of parthenocarpic and fertilized fruits of two watermelon genotypes by using qRT-PCR analysis. Considering the effects of genotype, fruit setting method, and developmental stage, geNorm determined clathrin adaptor complex subunit (ClCAC, β-actin (ClACT, and alpha tubulin 5 (ClTUA5 as the multiple reference genes in watermelon fruit. Furthermore, ClCAC alone or together with SAND family protein (ClSAND was ranked as the single or two best reference genes by NormFinder. By using the top-ranked reference genes to normalize the transcript abundance of phytoene synthase (ClPSY1, a good correlation between lycopene accumulation and ClPSY1 expression pattern was observed in ripening watermelon fruit. These validated reference genes will facilitate the accurate measurement of gene expression in the studies on watermelon fruit biology.

Evaluation of Appropriate Reference Genes for Gene Expression Normalization during Watermelon Fruit Development.

Science.gov (United States)

Kong, Qiusheng; Yuan, Jingxian; Gao, Lingyun; Zhao, Liqiang; Cheng, Fei; Huang, Yuan; Bie, Zhilong

2015-01-01

Gene expression analysis in watermelon (Citrullus lanatus) fruit has drawn considerable attention with the availability of genome sequences to understand the regulatory mechanism of fruit development and to improve its quality. Real-time quantitative reverse-transcription PCR (qRT-PCR) is a routine technique for gene expression analysis. However, appropriate reference genes for transcript normalization in watermelon fruits have not been well characterized. The aim of this study was to evaluate the appropriateness of 12 genes for their potential use as reference genes in watermelon fruits. Expression variations of these genes were measured in 48 samples obtained from 12 successive developmental stages of parthenocarpic and fertilized fruits of two watermelon genotypes by using qRT-PCR analysis. Considering the effects of genotype, fruit setting method, and developmental stage, geNorm determined clathrin adaptor complex subunit (ClCAC), β-actin (ClACT), and alpha tubulin 5 (ClTUA5) as the multiple reference genes in watermelon fruit. Furthermore, ClCAC alone or together with SAND family protein (ClSAND) was ranked as the single or two best reference genes by NormFinder. By using the top-ranked reference genes to normalize the transcript abundance of phytoene synthase (ClPSY1), a good correlation between lycopene accumulation and ClPSY1 expression pattern was observed in ripening watermelon fruit. These validated reference genes will facilitate the accurate measurement of gene expression in the studies on watermelon fruit biology.

Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

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Richard Danger

2018-01-01

Full Text Available Bronchiolitis obliterans syndrome (BOS, the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group, and 26 samples at or after BOS diagnosis (diagnosis group. An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group. We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1, T-cell leukemia/lymphoma protein 1A (TCL1A, and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01 and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS.

Validation of cell-free culture using scanning electron microscopy (SEM) and gene expression studies.

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Yang, R; Elankumaran, Y; Hijjawi, N; Ryan, U

2015-06-01

A cell-free culture system for Cryptosporidium parvum was analysed using scanning electron microscopy (SEM) to characterise life cycle stages and compare gene expression in cell-free culture and cell culture using HCT-8 cells. Cryptosporidium parvum samples were harvested at 2 h, 8 h, 14 h, 26 h, 50 h, 74 h, 98 h, 122 h and 170 h, chemically fixed and specimens were observed using a Zeiss 1555 scanning electron microscope. The presence of sporozoites, trophozoites and type I merozoites were identified by SEM. Gene expression in cell culture and cell-free culture was studied using reverse transcriptase quantitative PCR (RT-qPCR) of the sporozoite surface antigen protein (cp15), the glycoprotein 900 (gp900), the Cryptosporidium oocyst wall protein (COWP) and 18S ribosomal RNA (rRNA) genes in both cell free and conventional cell culture. In cell culture, cp15 expression peaked at 74 h, gp900 expression peaked at 74 h and 98 h and COWP expression peaked at 50 h. In cell-free culture, CP15 expression peaked at 98 h, gp900 expression peaked at 74 h and COWP expression peaked at 122 h. The present study is the first to compare gene expression of C. parvum in cell culture and cell-free culture and to characterise life cycle stages of C. parvum in cell-free culture using SEM. Findings from this study showed that gene expression patterns in cell culture and cell-free culture were similar but in cell-free culture, gene expression was delayed for CP15 and COWP in cell free culture compared with the cell culture system and was lower. Although three life cycle stageswere conclusively identified, improvements in SEM methodology should lead to the detection of more life cycle stages. Copyright © 2015 Elsevier Inc. All rights reserved.

Gene expression

International Nuclear Information System (INIS)

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

1983-01-01

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

A Gene Expression Classifier of Node-Positive Colorectal Cancer

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Paul F. Meeh

2009-10-01

Full Text Available We used digital long serial analysis of gene expression to discover gene expression differences between node-negative and node-positive colorectal tumors and developed a multigene classifier able to discriminate between these two tumor types. We prepared and sequenced long serial analysis of gene expression libraries from one node-negative and one node-positive colorectal tumor, sequenced to a depth of 26,060 unique tags, and identified 262 tags significantly differentially expressed between these two tumors (P < 2 x 10-6. We confirmed the tag-to-gene assignments and differential expression of 31 genes by quantitative real-time polymerase chain reaction, 12 of which were elevated in the node-positive tumor. We analyzed the expression levels of these 12 upregulated genes in a validation panel of 23 additional tumors and developed an optimized seven-gene logistic regression classifier. The classifier discriminated between node-negative and node-positive tumors with 86% sensitivity and 80% specificity. Receiver operating characteristic analysis of the classifier revealed an area under the curve of 0.86. Experimental manipulation of the function of one classification gene, Fibronectin, caused profound effects on invasion and migration of colorectal cancer cells in vitro. These results suggest that the development of node-positive colorectal cancer occurs in part through elevated epithelial FN1 expression and suggest novel strategies for the diagnosis and treatment of advanced disease.

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

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Olivier Fedrigo

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

Gene expression profiles in prostate cancer: identification of candidate non-invasive diagnostic markers.

Science.gov (United States)

Mengual, L; Ars, E; Lozano, J J; Burset, M; Izquierdo, L; Ingelmo-Torres, M; Gaya, J M; Algaba, F; Villavicencio, H; Ribal, M J; Alcaraz, A

2014-04-01

To analyze gene expression profiles of prostate cancer (PCa) with the aim of determining the relevant differentially expressed genes and subsequently ascertain whether this differential expression is maintained in post-prostatic massage (PPM) urine samples. Forty-six tissue specimens (36 from PCa patients and 10 controls) and 158 urine PPM-urines (113 from PCa patients and 45 controls) were collected between December 2003 and May 2007. DNA microarrays were used to identify genes differentially expressed between tumour and control samples. Ten genes were technically validated in the same tissue samples by quantitative RT-PCR (RT-qPCR). Forty two selected differentially expressed genes were validated in an independent set of PPM-urines by qRT-PCR. Multidimensional scaling plot according to the expression of all the microarray genes showed a clear distinction between control and tumour samples. A total of 1047 differentially expressed genes (FDR≤.1) were indentified between both groups of samples. We found a high correlation in the comparison of microarray and RT-qPCR gene expression levels (r=.928, P<.001). Thirteen genes maintained the same fold change direction when analyzed in PPM-urine samples and in four of them (HOXC6, PCA3, PDK4 and TMPRSS2-ERG), these differences were statistically significant (P<.05). The analysis of PCa by DNA microarrays provides new putative mRNA markers for PCa diagnosis that, with caution, can be extrapolated to PPM-urines. Copyright © 2013 AEU. Published by Elsevier Espana. All rights reserved.

Prospective Validation of a 21-Gene Expression Assay in Breast Cancer.

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Sparano, Joseph A; Gray, Robert J; Makower, Della F; Pritchard, Kathleen I; Albain, Kathy S; Hayes, Daniel F; Geyer, Charles E; Dees, Elizabeth C; Perez, Edith A; Olson, John A; Zujewski, JoAnne; Lively, Tracy; Badve, Sunil S; Saphner, Thomas J; Wagner, Lynne I; Whelan, Timothy J; Ellis, Matthew J; Paik, Soonmyung; Wood, William C; Ravdin, Peter; Keane, Maccon M; Gomez Moreno, Henry L; Reddy, Pavan S; Goggins, Timothy F; Mayer, Ingrid A; Brufsky, Adam M; Toppmeyer, Deborah L; Kaklamani, Virginia G; Atkins, James N; Berenberg, Jeffrey L; Sledge, George W

2015-11-19

Prior studies with the use of a prospective-retrospective design including archival tumor samples have shown that gene-expression assays provide clinically useful prognostic information. However, a prospectively conducted study in a uniformly treated population provides the highest level of evidence supporting the clinical validity and usefulness of a biomarker. We performed a prospective trial involving women with hormone-receptor-positive, human epidermal growth factor receptor type 2 (HER2)-negative, axillary node-negative breast cancer with tumors of 1.1 to 5.0 cm in the greatest dimension (or 0.6 to 1.0 cm in the greatest dimension and intermediate or high tumor grade) who met established guidelines for the consideration of adjuvant chemotherapy on the basis of clinicopathologic features. A reverse-transcriptase-polymerase-chain-reaction assay of 21 genes was performed on the paraffin-embedded tumor tissue, and the results were used to calculate a score indicating the risk of breast-cancer recurrence; patients were assigned to receive endocrine therapy without chemotherapy if they had a recurrence score of 0 to 10, indicating a very low risk of recurrence (on a scale of 0 to 100, with higher scores indicating a greater risk of recurrence). Of the 10,253 eligible women enrolled, 1626 women (15.9%) who had a recurrence score of 0 to 10 were assigned to receive endocrine therapy alone without chemotherapy. At 5 years, in this patient population, the rate of invasive disease-free survival was 93.8% (95% confidence interval [CI], 92.4 to 94.9), the rate of freedom from recurrence of breast cancer at a distant site was 99.3% (95% CI, 98.7 to 99.6), the rate of freedom from recurrence of breast cancer at a distant or local-regional site was 98.7% (95% CI, 97.9 to 99.2), and the rate of overall survival was 98.0% (95% CI, 97.1 to 98.6). Among patients with hormone-receptor-positive, HER2-negative, axillary node-negative breast cancer who met established guidelines for

Neighboring Genes Show Correlated Evolution in Gene Expression

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Ghanbarian, Avazeh T.; Hurst, Laurence D.

2015-01-01

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

Genome-wide prediction and functional validation of promoter motifs regulating gene expression in spore and infection stages of Phytophthora infestans.

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Sourav Roy

2013-03-01

Full Text Available Most eukaryotic pathogens have complex life cycles in which gene expression networks orchestrate the formation of cells specialized for dissemination or host colonization. In the oomycete Phytophthora infestans, the potato late blight pathogen, major shifts in mRNA profiles during developmental transitions were identified using microarrays. We used those data with search algorithms to discover about 100 motifs that are over-represented in promoters of genes up-regulated in hyphae, sporangia, sporangia undergoing zoosporogenesis, swimming zoospores, or germinated cysts forming appressoria (infection structures. Most of the putative stage-specific transcription factor binding sites (TFBSs thus identified had features typical of TFBSs such as position or orientation bias, palindromy, and conservation in related species. Each of six motifs tested in P. infestans transformants using the GUS reporter gene conferred the expected stage-specific expression pattern, and several were shown to bind nuclear proteins in gel-shift assays. Motifs linked to the appressoria-forming stage, including a functionally validated TFBS, were over-represented in promoters of genes encoding effectors and other pathogenesis-related proteins. To understand how promoter and genome architecture influence expression, we also mapped transcription patterns to the P. infestans genome assembly. Adjacent genes were not typically induced in the same stage, including genes transcribed in opposite directions from small intergenic regions, but co-regulated gene pairs occurred more than expected by random chance. These data help illuminate the processes regulating development and pathogenesis, and will enable future attempts to purify the cognate transcription factors.

Gene prediction validation and functional analysis of redundant pathways

DEFF Research Database (Denmark)

Sønderkær, Mads

2011-01-01

have employed a large mRNA-seq data set to improve and validate ab initio predicted gene models. This direct experimental evidence also provides reliable determinations of UTR regions and polyadenylation sites, which are not easily predicted in plants. Furthermore, once an annotated genome sequence...... is available, gene expression by mRNA-Seq enables acquisition of a more complete overview of gene isoform usage in complex enzymatic pathways enabling the identification of key genes. Metabolism in potatoes This information is useful e.g. for crop improvement based on manipulation of agronomically important...

Using RNA-Seq Data to Evaluate Reference Genes Suitable for Gene Expression Studies in Soybean.

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Aldrin Kay-Yuen Yim

Full Text Available Differential gene expression profiles often provide important clues for gene functions. While reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR is an important tool, the validity of the results depends heavily on the choice of proper reference genes. In this study, we employed new and published RNA-sequencing (RNA-Seq datasets (26 sequencing libraries in total to evaluate reference genes reported in previous soybean studies. In silico PCR showed that 13 out of 37 previously reported primer sets have multiple targets, and 4 of them have amplicons with different sizes. Using a probabilistic approach, we identified new and improved candidate reference genes. We further performed 2 validation tests (with 26 RNA samples on 8 commonly used reference genes and 7 newly identified candidates, using RT-qPCR. In general, the new candidate reference genes exhibited more stable expression levels under the tested experimental conditions. The three newly identified candidate reference genes Bic-C2, F-box protein2, and VPS-like gave the best overall performance, together with the commonly used ELF1b. It is expected that the proposed probabilistic model could serve as an important tool to identify stable reference genes when more soybean RNA-Seq data from different growth stages and treatments are used.

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

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Jun Seita

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

Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes

KAUST Repository

Abusamra, Heba

2016-07-20

The native nature of high dimension low sample size of gene expression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia gene expression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressed genes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.

Genome-wide gene copy number and expression analysis of primary gastric tumors and gastric cancer cell lines

International Nuclear Information System (INIS)

Junnila, Siina; Kokkola, Arto; Karjalainen-Lindsberg, Marja-Liisa; Puolakkainen, Pauli; Monni, Outi

2010-01-01

Gastric cancer is one of the most common malignancies worldwide and the second most common cause of cancer related death. Gene copy number alterations play an important role in the development of gastric cancer and a change in gene copy number is one of the main mechanisms for a cancer cell to control the expression of potential oncogenes and tumor suppressor genes. To highlight genes of potential biological and clinical relevance in gastric cancer, we carried out a systematic array-based survey of gene expression and copy number levels in primary gastric tumors and gastric cancer cell lines and validated the results using an affinity capture based transcript analysis (TRAC assay) and real-time qRT-PCR. Integrated microarray analysis revealed altogether 256 genes that were located in recurrent regions of gains or losses and had at least a 2-fold copy number- associated change in their gene expression. The expression levels of 13 of these genes, ALPK2, ASAP1, CEACAM5, CYP3A4, ENAH, ERBB2, HHIPL2, LTB4R, MMP9, PERLD1, PNMT, PTPRA, and OSMR, were validated in a total of 118 gastric samples using either the qRT-PCR or TRAC assay. All of these 13 genes were differentially expressed between cancerous samples and nonmalignant tissues (p < 0.05) and the association between copy number and gene expression changes was validated for nine (69.2%) of these genes (p < 0.05). In conclusion, integrated gene expression and copy number microarray analysis highlighted genes that may be critically important for gastric carcinogenesis. TRAC and qRT-PCR analyses validated the microarray results and therefore the role of these genes as potential biomarkers for gastric cancer

Gene expression profiling demonstrates WNT/β-catenin pathway genes alteration in Mexican patients with colorectal cancer and diabetes mellitus.

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Ivonne Wence-Chavez, Laura; Palomares-Chacon, Ulises; Pablo Flores-Gutierrez, Juan; Felipe Jave-Suarez, Luis; Del Carmen Aguilar-Lemarroy, Adriana; Barros-Nunez, Patricio; Esperanza Flores-Martinez, Silvia; Sanchez-Corona, Jose; Alejandra Rosales-Reynoso, Monica

2017-01-01

Several studies have shown a strong association between diabetes mellitus (DM) and increased risk of colorectal cancer (CRC). The fundamental mechanisms that support this association are not entirely understood; however, it is believed that hyperinsulinemia and hyperglycemia may be involved. Some proposed mechanisms include upregulation of mitogenic signaling pathways like MAPK, PI3K, mTOR, and WNT, which are involved in cell proliferation, growth, and cancer cell survival. The purpose of this study was to evaluate the gene expression profile and identify differently expressed genes involved in mitogenic pathways in CRC patients with and without DM. In this study, microarray analysis of gene expression followed by quantitative PCR (qPCR) was performed in cancer tissue from CRC patients with and without DM to identify the gene expression profiles and validate the differently expressed genes. Among the study groups, some differently expressed genes were identified. However, when bioinformatics clustering tools were used, a significant modulation of genes involved in the WNT pathway was evident. Therefore, we focused on genes participating in this pathway, such as WNT3A, LRP6, TCF7L2, and FRA-1. Validation of the expression levels of those genes by qPCR showed that CRC patients without type 2 diabetes mellitus (T2DM) expressed significantly more WNT3Ay LRP6, but less TCF7L2 and FRA-1 compared to controls, while in CRC patients with DM the expression levels of WNT3A, LRP6, TCF7L2, and FRA-1 were significantly higher compared to controls. Our results suggest that WNT/β-catenin pathway is upregulated in patients with CRC and DM, demonstrating its importance and involvement in both pathologies.

Gene expression analysis uncovers novel Hedgehog interacting protein (HHIP) effects in human bronchial epithelial cells

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Zhou, Xiaobo; Qiu, Weiliang; Sathirapongsasuti, J. Fah.; Cho, Michael H.; Mancini, John D.; Lao, Taotao; Thibault, Derek M.; Litonjua, Gus; Bakke, Per S.; Gulsvik, Amund; Lomas, David A.; Beaty, Terri H.; Hersh, Craig P.; Anderson, Christopher; Geigenmuller, Ute; Raby, Benjamin A.; Rennard, Stephen I.; Perrella, Mark A.; Choi, Augustine M.K.; Quackenbush, John; Silverman, Edwin K.

2013-01-01

Hedgehog Interacting Protein (HHIP) was implicated in chronic obstructive pulmonary disease (COPD) by genome-wide association studies (GWAS). However, it remains unclear how HHIP contributes to COPD pathogenesis. To identify genes regulated by HHIP, we performed gene expression microarray analysis in a human bronchial epithelial cell line (Beas-2B) stably infected with HHIP shRNAs. HHIP silencing led to differential expression of 296 genes; enrichment for variants nominally associated with COPD was found. Eighteen of the differentially expressed genes were validated by real-time PCR in Beas-2B cells. Seven of 11 validated genes tested in human COPD and control lung tissues demonstrated significant gene expression differences. Functional annotation indicated enrichment for extracellular matrix and cell growth genes. Network modeling demonstrated that the extracellular matrix and cell proliferation genes influenced by HHIP tended to be interconnected. Thus, we identified potential HHIP targets in human bronchial epithelial cells that may contribute to COPD pathogenesis. PMID:23459001

Screening for interaction effects in gene expression data.

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Peter J Castaldi

Full Text Available Expression quantitative trait (eQTL studies are a powerful tool for identifying genetic variants that affect levels of messenger RNA. Since gene expression is controlled by a complex network of gene-regulating factors, one way to identify these factors is to search for interaction effects between genetic variants and mRNA levels of transcription factors (TFs and their respective target genes. However, identification of interaction effects in gene expression data pose a variety of methodological challenges, and it has become clear that such analyses should be conducted and interpreted with caution. Investigating the validity and interpretability of several interaction tests when screening for eQTL SNPs whose effect on the target gene expression is modified by the expression level of a transcription factor, we characterized two important methodological issues. First, we stress the scale-dependency of interaction effects and highlight that commonly applied transformation of gene expression data can induce or remove interactions, making interpretation of results more challenging. We then demonstrate that, in the setting of moderate to strong interaction effects on the order of what may be reasonably expected for eQTL studies, standard interaction screening can be biased due to heteroscedasticity induced by true interactions. Using simulation and real data analysis, we outline a set of reasonable minimum conditions and sample size requirements for reliable detection of variant-by-environment and variant-by-TF interactions using the heteroscedasticity consistent covariance-based approach.

Imaging gene expression in gene therapy

International Nuclear Information System (INIS)

Wiebe, Leonard I.

1997-01-01

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

Identification of suitable reference genes for gene expression normalization in qRT-PCR analysis in watermelon.

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Qiusheng Kong

Full Text Available Watermelon is one of the major Cucurbitaceae crops and the recent availability of genome sequence greatly facilitates the fundamental researches on it. Quantitative real-time reverse transcriptase PCR (qRT-PCR is the preferred method for gene expression analyses, and using validated reference genes for normalization is crucial to ensure the accuracy of this method. However, a systematic validation of reference genes has not been conducted on watermelon. In this study, transcripts of 15 candidate reference genes were quantified in watermelon using qRT-PCR, and the stability of these genes was compared using geNorm and NormFinder. geNorm identified ClTUA and ClACT, ClEF1α and ClACT, and ClCAC and ClTUA as the best pairs of reference genes in watermelon organs and tissues under normal growth conditions, abiotic stress, and biotic stress, respectively. NormFinder identified ClYLS8, ClUBCP, and ClCAC as the best single reference genes under the above experimental conditions, respectively. ClYLS8 and ClPP2A were identified as the best reference genes across all samples. Two to nine reference genes were required for more reliable normalization depending on the experimental conditions. The widely used watermelon reference gene 18SrRNA was less stable than the other reference genes under the experimental conditions. Catalase family genes were identified in watermelon genome, and used to validate the reliability of the identified reference genes. ClCAT1and ClCAT2 were induced and upregulated in the first 24 h, whereas ClCAT3 was downregulated in the leaves under low temperature stress. However, the expression levels of these genes were significantly overestimated and misinterpreted when 18SrRNA was used as a reference gene. These results provide a good starting point for reference gene selection in qRT-PCR analyses involving watermelon.

Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

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Liying Yang

2016-01-01

Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.

Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

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Xi Wang

2015-05-01

Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

GenClust: A genetic algorithm for clustering gene expression data

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Raimondi Alessandra

2005-12-01

Full Text Available Abstract Background Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. Results GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a a novel coding of the search space that is simple, compact and easy to update; (b it can be used naturally in conjunction with data driven internal validation methods. We have experimented with the FOM methodology, specifically conceived for validating clusters of gene expression data. The validity of GenClust has been assessed experimentally on real data sets, both with the use of validation measures and in comparison with other algorithms, i.e., Average Link, Cast, Click and K-means. Conclusion Experiments show that none of the algorithms we have used is markedly superior to the others across data sets and validation measures; i.e., in many cases the observed differences between the worst and best performing algorithm may be statistically insignificant and they could be considered equivalent. However, there are cases in which an algorithm may be better than others and therefore worthwhile. In particular, experiments for GenClust show that, although simple in its data representation, it converges very rapidly to a local optimum and that its ability to identify meaningful clusters is comparable, and sometimes superior, to that of more sophisticated algorithms. In addition, it is well suited for use in conjunction with data driven internal validation measures and, in particular, the FOM methodology.

Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data

OpenAIRE

Ezer, Daphne; Moignard, Victoria; G?ttgens, Berthold; Adryan, Boris

2016-01-01

Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete ...

Clinicopathologic and gene expression parameters predict liver cancer prognosis

International Nuclear Information System (INIS)

Hao, Ke; Zhong, Hua; Greenawalt, Danielle; Ferguson, Mark D; Ng, Irene O; Sham, Pak C; Poon, Ronnie T; Molony, Cliona; Schadt, Eric E; Dai, Hongyue; Luk, John M; Lamb, John; Zhang, Chunsheng; Xie, Tao; Wang, Kai; Zhang, Bin; Chudin, Eugene; Lee, Nikki P; Mao, Mao

2011-01-01

The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome

Imaging gene expression in gene therapy

Energy Technology Data Exchange (ETDEWEB)

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

1997-12-31

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

Gene Expression Differences in Peripheral Blood of Parkinson's Disease Patients with Distinct Progression Profiles.

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Raquel Pinho

Full Text Available The prognosis of neurodegenerative disorders is clinically challenging due to the inexistence of established biomarkers for predicting disease progression. Here, we performed an exploratory cross-sectional, case-control study aimed at determining whether gene expression differences in peripheral blood may be used as a signature of Parkinson's disease (PD progression, thereby shedding light into potential molecular mechanisms underlying disease development. We compared transcriptional profiles in the blood from 34 PD patients who developed postural instability within ten years with those of 33 patients who did not develop postural instability within this time frame. Our study identified >200 differentially expressed genes between the two groups. The expression of several of the genes identified was previously found deregulated in animal models of PD and in PD patients. Relevant genes were selected for validation by real-time PCR in a subset of patients. The genes validated were linked to nucleic acid metabolism, mitochondria, immune response and intracellular-transport. Interestingly, we also found deregulation of these genes in a dopaminergic cell model of PD, a simple paradigm that can now be used to further dissect the role of these molecular players on dopaminergic cell loss. Altogether, our study provides preliminary evidence that expression changes in specific groups of genes and pathways, detected in peripheral blood samples, may be correlated with differential PD progression. Our exploratory study suggests that peripheral gene expression profiling may prove valuable for assisting in prediction of PD prognosis, and identifies novel culprits possibly involved in dopaminergic cell death. Given the exploratory nature of our study, further investigations using independent, well-characterized cohorts will be essential in order to validate our candidates as predictors of PD prognosis and to definitively confirm the value of gene expression

Identification of valid reference genes for the normalization of RT-qPCR expression studies in human breast cancer cell lines treated with and without transient transfection.

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Lin-Lin Liu

Full Text Available Reverse transcription-quantitative polymerase chain reaction (RT-qPCR is a powerful technique for examining gene expression changes during tumorigenesis. Target gene expression is generally normalized by a stably expressed endogenous reference gene; however, reference gene expression may differ among tissues under various circumstances. Because no valid reference genes have been documented for human breast cancer cell lines containing different cancer subtypes treated with transient transfection, we identified appropriate and reliable reference genes from thirteen candidates in a panel of 10 normal and cancerous human breast cell lines under experimental conditions with/without transfection treatments with two transfection reagents. Reference gene expression stability was calculated using four algorithms (geNorm, NormFinder, BestKeeper and comparative delta Ct, and the recommended comprehensive ranking was provided using geometric means of the ranking values using the RefFinder tool. GeNorm analysis revealed that two reference genes should be sufficient for all cases in this study. A stability analysis suggests that 18S rRNA-ACTB is the best reference gene combination across all cell lines; ACTB-GAPDH is best for basal breast cancer cell lines; and HSPCB-ACTB is best for ER+ breast cancer cells. After transfection, the stability ranking of the reference gene fluctuated, especially with Lipofectamine 2000 transfection reagent in two subtypes of basal and ER+ breast cell lines. Comparisons of relative target gene (HER2 expression revealed different expressional patterns depending on the reference genes used for normalization. We suggest that identifying the most stable and suitable reference genes is critical for studying specific cell lines under certain circumstances.

Mercury-induced hepatotoxicity in zebrafish: in vivo mechanistic insights from transcriptome analysis, phenotype anchoring and targeted gene expression validation

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Mathavan Sinnakaruppan

2010-03-01

Full Text Available Abstract Background Mercury is a prominent environmental contaminant that causes detrimental effects to human health. Although the liver has been known to be a main target organ, there is limited information on in vivo molecular mechanism of mercury-induced toxicity in the liver. By using transcriptome analysis, phenotypic anchoring and validation of targeted gene expression in zebrafish, mercury-induced hepatotoxicity was investigated and a number of perturbed cellular processes were identified and compared with those captured in the in vitro human cell line studies. Results Hepato-transcriptome analysis of mercury-exposed zebrafish revealed that the earliest deregulated genes were associated with electron transport chain, mitochondrial fatty acid beta-oxidation, nuclear receptor signaling and apoptotic pathway, followed by complement system and proteasome pathway, and thereafter DNA damage, hypoxia, Wnt signaling, fatty acid synthesis, gluconeogenesis, cell cycle and motility. Comparative meta-analysis of microarray data between zebrafish liver and human HepG2 cells exposed to mercury identified some common toxicological effects of mercury-induced hepatotoxicity in both models. Histological analyses of liver from mercury-exposed fish revealed morphological changes of liver parenchyma, decreased nucleated cell count, increased lipid vesicles, glycogen and apoptotic bodies, thus providing phenotypic evidence for anchoring of the transcriptome analysis. Validation of targeted gene expression confirmed deregulated gene-pathways from enrichment analysis. Some of these genes responding to low concentrations of mercury may serve as toxicogenomic-based markers for detection and health risk assessment of environmental mercury contaminations. Conclusion Mercury-induced hepatotoxicity was triggered by oxidative stresses, intrinsic apoptotic pathway, deregulation of nuclear receptor and kinase activities including Gsk3 that deregulates Wnt signaling

Finding gene regulatory network candidates using the gene expression knowledge base.

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Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

Disease gene characterization through large-scale co-expression analysis.

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Allen Day

2009-12-01

Full Text Available In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET.Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2 and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis.

Validation of endogenous reference genes for qRT-PCR analysis of human visceral adipose samples.

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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.

Validation of endogenous reference genes for qRT-PCR analysis of human visceral adipose samples

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Afendy Arian

2010-05-01

Full Text Available Abstract 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.

Automatic Control of Gene Expression in Mammalian Cells.

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Fracassi, Chiara; Postiglione, Lorena; Fiore, Gianfranco; di Bernardo, Diego

2016-04-15

Automatic control of gene expression in living cells is paramount importance to characterize both endogenous gene regulatory networks and synthetic circuits. In addition, such a technology can be used to maintain the expression of synthetic circuit components in an optimal range in order to ensure reliable performance. Here we present a microfluidics-based method to automatically control gene expression from the tetracycline-inducible promoter in mammalian cells in real time. Our approach is based on the negative-feedback control engineering paradigm. We validated our method in a monoclonal population of cells constitutively expressing a fluorescent reporter protein (d2EYFP) downstream of a minimal CMV promoter with seven tet-responsive operator motifs (CMV-TET). These cells also constitutively express the tetracycline transactivator protein (tTA). In cells grown in standard growth medium, tTA is able to bind the CMV-TET promoter, causing d2EYFP to be maximally expressed. Upon addition of tetracycline to the culture medium, tTA detaches from the CMV-TET promoter, thus preventing d2EYFP expression. We tested two different model-independent control algorithms (relay and proportional-integral (PI)) to force a monoclonal population of cells to express an intermediate level of d2EYFP equal to 50% of its maximum expression level for up to 3500 min. The control input is either tetracycline-rich or standard growth medium. We demonstrated that both the relay and PI controllers can regulate gene expression at the desired level, despite oscillations (dampened in the case of the PI controller) around the chosen set point.

Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L.) gene expression oligonucleotide microarray.

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Fernandez, Paula; Soria, Marcelo; Blesa, David; DiRienzo, Julio; Moschen, Sebastian; Rivarola, Maximo; Clavijo, Bernardo Jose; Gonzalez, Sergio; Peluffo, Lucila; Príncipi, Dario; Dosio, Guillermo; Aguirrezabal, Luis; García-García, Francisco; Conesa, Ana; Hopp, Esteban; Dopazo, Joaquín; Heinz, Ruth Amelia; Paniego, Norma

2012-01-01

Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (psunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

Screening key genes for abdominal aortic aneurysm based on gene expression omnibus dataset.

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Wan, Li; Huang, Jingyong; Ni, Haizhen; Yu, Guanfeng

2018-02-13

Abdominal aortic aneurysm (AAA) is a common cardiovascular system disease with high mortality. The aim of this study was to identify potential genes for diagnosis and therapy in AAA. We searched and downloaded mRNA expression data from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) from AAA and normal individuals. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, transcriptional factors (TFs) network and protein-protein interaction (PPI) network were used to explore the function of genes. Additionally, immunohistochemical (IHC) staining was used to validate the expression of identified genes. Finally, the diagnostic value of identified genes was accessed by receiver operating characteristic (ROC) analysis in GEO database. A total of 1199 DEGs (188 up-regulated and 1011 down-regulated) were identified between AAA and normal individual. KEGG pathway analysis displayed that vascular smooth muscle contraction and pathways in cancer were significantly enriched signal pathway. The top 10 up-regulated and top 10 down-regulated DEGs were used to construct TFs and PPI networks. Some genes with high degrees such as NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16 and FOXO1 were identified to be related to AAA. The consequences of IHC staining showed that CCR7 and PDGFA were up-regulated in tissue samples of AAA. ROC analysis showed that NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA had the potential diagnostic value for AAA. The identified genes including NELL2, CCR7, MGAM, HBB, CSNK2A2, ZBTB16, FOXO1 and PDGFA might be involved in the pathology of AAA.

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

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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.

Identification of Candidate B-Lymphoma Genes by Cross-Species Gene Expression Profiling

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Tompkins, Van S.; Han, Seong-Su; Olivier, Alicia; Syrbu, Sergei; Bair, Thomas; Button, Anna; Jacobus, Laura; Wang, Zebin; Lifton, Samuel; Raychaudhuri, Pradip; Morse, Herbert C.; Weiner, George; Link, Brian; Smith, Brian J.; Janz, Siegfried

2013-01-01

Comparative genome-wide expression profiling of malignant tumor counterparts across the human-mouse species barrier has a successful track record as a gene discovery tool in liver, breast, lung, prostate and other cancers, but has been largely neglected in studies on neoplasms of mature B-lymphocytes such as diffuse large B cell lymphoma (DLBCL) and Burkitt lymphoma (BL). We used global gene expression profiles of DLBCL-like tumors that arose spontaneously in Myc-transgenic C57BL/6 mice as a phylogenetically conserved filter for analyzing the human DLBCL transcriptome. The human and mouse lymphomas were found to have 60 concordantly deregulated genes in common, including 8 genes that Cox hazard regression analysis associated with overall survival in a published landmark dataset of DLBCL. Genetic network analysis of the 60 genes followed by biological validation studies indicate FOXM1 as a candidate DLBCL and BL gene, supporting a number of studies contending that FOXM1 is a therapeutic target in mature B cell tumors. Our findings demonstrate the value of the “mouse filter” for genomic studies of human B-lineage neoplasms for which a vast knowledge base already exists. PMID:24130802

Utility and Limitations of Using Gene Expression Data to Identify Functional Associations.

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Sahra Uygun

2016-12-01

Full Text Available Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets.

Network statistics of genetically-driven gene co-expression modules in mouse crosses

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Marie-Pier eScott-Boyer

2013-12-01

Full Text Available In biology, networks are used in different contexts as ways to represent relationships between entities, such as for instance interactions between genes, proteins or metabolites. Despite progress in the analysis of such networks and their potential to better understand the collective impact of genes on complex traits, one remaining challenge is to establish the biologic validity of gene co-expression networks and to determine what governs their organization. We used WGCNA to construct and analyze seven gene expression datasets from several tissues of mouse recombinant inbred strains (RIS. For six out of the 7 networks, we found that linkage to module QTLs (mQTLs could be established for 29.3% of gene co-expression modules detected in the several mouse RIS. For about 74.6% of such genetically-linked modules, the mQTL was on the same chromosome as the one contributing most genes to the module, with genes originating from that chromosome showing higher connectivity than other genes in the modules. Such modules (that we considered as genetically-driven had network statistic properties (density, centralization and heterogeneity that set them apart from other modules in the network. Altogether, a sizeable portion of gene co-expression modules detected in mouse RIS panels had genetic determinants as their main organizing principle. In addition to providing a biologic interpretation validation for these modules, these genetic determinants imparted on them particular properties that set them apart from other modules in the network, to the point that they can be predicted to a large extent on the basis of their network statistics.

Statistical Considerations for Immunohistochemistry Panel Development after Gene Expression Profiling of Human Cancers

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Betensky, Rebecca A.; Nutt, Catherine L.; Batchelor, Tracy T.; Louis, David N.

2005-01-01

In recent years there have been a number of microarray expression studies in which different types of tumors were classified by identifying a panel of differentially expressed genes. Immunohistochemistry is a practical and robust method for extending gene expression data to common pathological specimens with the advantage of being applicable to paraffin-embedded tissues. However, the number of assays required for successful immunohistochemical classification remains unclear. We propose a simulation-based method for assessing sample size for an immunohistochemistry investigation after a promising gene expression study of human tumors. The goals of such an immunohistochemistry study would be to develop and validate a marker panel that yields improved prognostic classification of cancer patients. We demonstrate how the preliminary gene expression data, coupled with certain realistic assumptions, can be used to estimate the number of immunohistochemical assays required for development. These assumptions are more tenable than alternative assumptions that would be required for crude analytic sample size calculations and that may yield underpowered and inefficient studies. We applied our methods to the design of an immunohistochemistry study for glioma classification and estimated the number of assays required to ensure satisfactory technical and prognostic validation. Simulation approaches for computing power and sample size that are based on existing gene expression data provide a powerful tool for efficient design of follow-up genomic studies. PMID:15858152

Housekeeping gene expression during fetal brain development in the rat-validation by semi-quantitative RT-PCR.

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Al-Bader, Maie Dawoud; Al-Sarraf, Hameed Ali

2005-04-21

Mammalian gene expression is usually carried out at the level of mRNA where the amount of mRNA of interest is measured under different conditions such as growth and development. It is therefore important to use a "housekeeping gene", that does not change in relative abundance during the experimental conditions, as a standard or internal control. However, recent data suggest that expression of some housekeeping genes may vary with the extent of cell proliferation, differentiation and under various experimental conditions. In this study, the expression of various housekeeping genes (18S rRNA [18S], glyceraldehydes-3-phosphate dehydrogenase [G3PDH], beta-glucuronidase [BGLU], histone H4 [HH4], ribosomal protein L19 [RPL19] and cyclophilin [CY]) was investigated during fetal rat brain development using semi-quantitative RT-PCR at 16, 19 and 21 days gestation. It was found that all genes studied, with exception to G3PDH, did not show any change in their expression levels during development. G3PDH, on the other hand, showed increased expression with development. These results suggest that the choice of a housekeeping gene is critical to the interpretation of experimental results and should be modified according to the nature of the study.

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

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Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

2017-11-13

correlated with BMI (r = 0.56, P = 0.04), and hub genes of KCNN1 and AQP10 were differentially expressed. We identified significant genes and specific modules potentially related to BMI based on the gene expression profile data of monozygotic twins. The findings may help further elucidate the underlying mechanisms of obesity development and provide novel insights to research potential gene biomarkers and signaling pathways for obesity treatment. Further analysis and validation of the findings reported here are important and necessary when more sample size is acquired.

Exploring valid reference genes for quantitative real - time rt - pce studies of hydrogenperoxide signaling in arabidopsis

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Zhou, H.; Han, B.; Xie, Y.; Zhang, J.; Shen, W.

2015-01-01

Hydrogen peroxide (H/sub 2/O/sub 2/ ) acts as a signaling molecule modulating the expression of various genes in plants. However, the reference gene(s) used for gene expression analysis of H/sub 2/O/sub 2/ signaling is still arbitrary. A reliable result obtained by quantitative real-time RT-PCR (RT-qPCR) highly depends on accurate transcript normalization using stably expressed reference genes, whereas the inaccurate normalization could easily lead to the false conclusions. In this report, by using geNorm and NormFinder algorithms, 12 candidate reference genes were evaluated and compared in root and shoot tissues of Arabidopsis upon different doses of H/sub 2/O/sub 2/. The results revealed that, in our experimental conditions, three novel reference genes (TIP41-like, UKN, and UBC21) were identified and validated as suitable reference genes for RT-qPCR normalization in both root and shoot tissues under oxidative stress. This conclusion was further confirmed by publicly available microarray data of methyl viologen and drought stress. In comparison with a single reference gene (EF-1a), the expression pattern of ZAT12 modulated by H/sub 2/O/sub 2/, when using TIP41-like, UKN, and UBC21 as multiple reference gene(s), was similar with the previous reports by using northern blotting. Thus, we proposed that these three reference genes might be good candidates for other researchers to include in their reference gene validation in gene expression studies under H/sub 2/O/sub 2/ related oxidative stress. (author)

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

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Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Selection of reference genes for expression studies with fish myogenic cell cultures

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Johnston Ian A

2009-08-01

Full Text Available Abstract Background Relatively few studies have used cell culture systems to investigate gene expression and the regulation of myogenesis in fish. To produce robust data from quantitative real-time PCR mRNA levels need to be normalised using internal reference genes which have stable expression across all experimental samples. We have investigated the expression of eight candidate genes to identify suitable reference genes for use in primary myogenic cell cultures from Atlantic salmon (Salmo salar L.. The software analysis packages geNorm, Normfinder and Best keeper were used to rank genes according to their stability across 42 samples during the course of myogenic differentiation. Results Initial results showed several of the candidate genes exhibited stable expression throughout myogenic culture while Sdha was identified as the least stable gene. Further analysis with geNorm, Normfinder and Bestkeeper identified Ef1α, Hprt1, Ppia and RNApolII as stably expressed. Comparison of data normalised with the geometric average obtained from combinations of any three of these genes showed no significant differences, indicating that any combination of these genes is valid. Conclusion The geometric average of any three of Hprt1, Ef1α, Ppia and RNApolII is suitable for normalisation of gene expression data in primary myogenic cultures from Atlantic salmon.

Selection of reference genes for expression studies with fish myogenic cell cultures.

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Bower, Neil I; Johnston, Ian A

2009-08-10

Relatively few studies have used cell culture systems to investigate gene expression and the regulation of myogenesis in fish. To produce robust data from quantitative real-time PCR mRNA levels need to be normalised using internal reference genes which have stable expression across all experimental samples. We have investigated the expression of eight candidate genes to identify suitable reference genes for use in primary myogenic cell cultures from Atlantic salmon (Salmo salar L.). The software analysis packages geNorm, Normfinder and Best keeper were used to rank genes according to their stability across 42 samples during the course of myogenic differentiation. Initial results showed several of the candidate genes exhibited stable expression throughout myogenic culture while Sdha was identified as the least stable gene. Further analysis with geNorm, Normfinder and Bestkeeper identified Ef1alpha, Hprt1, Ppia and RNApolII as stably expressed. Comparison of data normalised with the geometric average obtained from combinations of any three of these genes showed no significant differences, indicating that any combination of these genes is valid. The geometric average of any three of Hprt1, Ef1alpha, Ppia and RNApolII is suitable for normalisation of gene expression data in primary myogenic cultures from Atlantic salmon.

rpb2 is a reliable reference gene for quantitative gene expression analysis in the dermatophyte Trichophyton rubrum.

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Jacob, Tiago R; Peres, Nalu T A; Persinoti, Gabriela F; Silva, Larissa G; Mazucato, Mendelson; Rossi, Antonio; Martinez-Rossi, Nilce M

2012-05-01

The selection of reference genes used for data normalization to quantify gene expression by real-time PCR amplifications (qRT-PCR) is crucial for the accuracy of this technique. In spite of this, little information regarding such genes for qRT-PCR is available for gene expression analyses in pathogenic fungi. Thus, we investigated the suitability of eight candidate reference genes in isolates of the human dermatophyte Trichophyton rubrum subjected to several environmental challenges, such as drug exposure, interaction with human nail and skin, and heat stress. The stability of these genes was determined by geNorm, NormFinder and Best-Keeper programs. The gene with the most stable expression in the majority of the conditions tested was rpb2 (DNA-dependent RNA polymerase II), which was validated in three T. rubrum strains. Moreover, the combination of rpb2 and chs1 (chitin synthase) genes provided for the most reliable qRT-PCR data normalization in T. rubrum under a broad range of biological conditions. To the best of our knowledge this is the first report on the selection of reference genes for qRT-PCR data normalization in dermatophytes and the results of these studies should permit further analysis of gene expression under several experimental conditions, with improved accuracy and reliability.

Actin gene identification from selected medicinal plants for their use as internal controls for gene expression studies

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Mufti, F.U.D.; Banaras, S.

2015-01-01

Internal control genes are the constitutive genes which maintain the basic cellular functions and regularly express in both normal and stressed conditions in living organisms. They are used in normalization of gene expression studies in comparative analysis of target genes, as their expression remains comparatively unchanged in all varied conditions. Among internal control genes, actin is considered as a candidate gene for expression studies due to its vital role in shaping cytoskeleton and plant physiology. Unfortunately most of such knowledge is limited to only model plants or crops, not much is known about important medicinal plants. Therefore, we selected seven important medicinal wild plants for molecular identification of actin gene. We used gene specific primers designed from the conserved regions of several known orthologues or homologues of actin genes from other plants. The amplified products of 370-380 bp were sequenced and submitted to GeneBank after their confirmation using different bioinformatics tools. All the novel partial sequences of putative actin genes were submitted to GeneBank (Parthenium hysterophorus (KJ774023), Fagonia indica (KJ774024), Rhazya stricta (KJ774025), Whithania coagulans (KJ774026), Capparis decidua (KJ774027), Verbena officinalis (KJ774028) and Aerva javanica (KJ774029)). The comparisons of these partial sequences by Basic Local Alignment Search Tool (BLAST) and phylogenetic trees demonstrated high similarity with known actin genes of other plants. Our findings illustrated highly conserved nature of actin gene among these selected plants. These novel partial fragments of actin genes from these wild medicinal plants can be used as internal controls for future gene expression studies of these important plants after precise validations of their stable expression in such plants. (author)

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

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Usadel Björn

2007-05-01

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

Digital gene expression profiling of flax (Linum usitatissimum L.) stem peel identifies genes enriched in fiber-bearing phloem tissue.

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Guo, Yuan; Qiu, Caisheng; Long, Songhua; Chen, Ping; Hao, Dongmei; Preisner, Marta; Wang, Hui; Wang, Yufu

2017-08-30

To better understand the molecular mechanisms and gene expression characteristics associated with development of bast fiber cell within flax stem phloem, the gene expression profiling of flax stem peels and leaves were screened, using Illumina's Digital Gene Expression (DGE) analysis. Four DGE libraries (2 for stem peel and 2 for leaf), ranging from 6.7 to 9.2 million clean reads were obtained, which produced 7.0 million and 6.8 million mapped reads for flax stem peel and leave, respectively. By differential gene expression analysis, a total of 975 genes, of which 708 (73%) genes have protein-coding annotation, were identified as phloem enriched genes putatively involved in the processes of polysaccharide and cell wall metabolism. Differential expression genes (DEGs) was validated using quantitative RT-PCR, the expression pattern of all nine genes determined by qRT-PCR fitted in well with that obtained by sequencing analysis. Cluster and Gene Ontology (GO) analysis revealed that a large number of genes related to metabolic process, catalytic activity and binding category were expressed predominantly in the stem peels. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the phloem enriched genes suggested approximately 111 biological pathways. The large number of genes and pathways produced from DGE sequencing will expand our understanding of the complex molecular and cellular events in flax bast fiber development and provide a foundation for future studies on fiber development in other bast fiber crops. Copyright © 2017 Elsevier B.V. All rights reserved.

Transcriptional expression of type I interferon response genes and stability of housekeeping genes in the human endometrium and endometriosis

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Vestergaard, Anna L; Knudsen, Ulla B; Munk, Torben

2011-01-01

Endometriosis is a painful chronic female disease defined by the presence of endometrial tissue implants in ectopic locations. The pathogenesis is much debated, and type I interferons could be involved. The expression of genes of the type I interferon response were profiled by a specific PCR Array...... of RNA obtained from ectopic and eutopic endometrium collected from 9 endometriosis patients and 9 healthy control women. Transcriptional expression levels of selected interferon-regulated and housekeeping genes were investigated by real-time quantitative reverse transcriptase PCR (qRT-PCR). Stably...... expressed housekeeping genes for valid normalization of transcriptional studies of endometrium and endometriosis have not yet been published. Here, seven housekeeping genes were evaluated for stability using the GeNorm and NormFinder software. A normalization factor based on HMBS, TBP, and YWHAZ expression...

Identification and validation of reference genes for qRT-PCR studies of the obligate aphid pathogenic fungus Pandora neoaphidis during different developmental stages.

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Zhang, Shutao; Chen, Chun; Xie, Tingna; Ye, Sudan

2017-01-01

The selection of stable reference genes is a critical step for the accurate quantification of gene expression. To identify and validate the reference genes in Pandora neoaphidis-an obligate aphid pathogenic fungus-the expression of 13classical candidate reference genes were evaluated by quantitative real-time reverse transcriptase polymerase chain reaction(qPCR) at four developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae). Four statistical algorithms, including geNorm, NormFinder, BestKeeper and Delta Ct method were used to rank putative reference genes according to their expression stability and indicate the best reference gene or combination of reference genes for accurate normalization. The analysis of comprehensive ranking revealed that ACT1and 18Swas the most stably expressed genes throughout the developmental stages. To further validate the suitability of the reference genes identified in this study, the expression of cell division control protein 25 (CDC25) and Chitinase 1(CHI1) genes were used to further confirm the validated candidate reference genes. Our study presented the first systematic study of reference gene(s) selection for P. neoaphidis study and provided guidelines to obtain more accurate qPCR results for future developmental efforts.

Identification and validation of genes involved in cervical tumourigenesis

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Rajkumar, Thangarajan; Sabitha, Kesavan; Vijayalakshmi, Neelakantan; Shirley, Sundersingh; Bose, Mayil Vahanan; Gopal, Gopisetty; Selvaluxmy, Ganesharaja

2011-01-01

Cervical cancer is the most common cancer among Indian women. This cancer has well defined pre-cancerous stages and evolves over 10-15 years or more. This study was undertaken to identify differentially expressed genes between normal, dysplastic and invasive cervical cancer. A total of 28 invasive cervical cancers, 4 CIN3/CIS, 4 CIN1/CIN2 and 5 Normal cervix samples were studied. We have used microarray technique followed by validation of the significant genes by relative quantitation using Taqman Low Density Array Real Time PCR. Immunohistochemistry was used to study the protein expression of MMP3, UBE2C and p16 in normal, dysplasia and cancers of the cervix. The effect of a dominant negative UBE2C on the growth of the SiHa cells was assessed using a MTT assay. Our study, for the first time, has identified 20 genes to be up-regulated and 14 down-regulated in cervical cancers and 5 up-regulated in CIN3. In addition, 26 genes identified by other studies, as to playing a role in cervical cancer, were also confirmed in our study. UBE2C, CCNB1, CCNB2, PLOD2, NUP210, MELK, CDC20 genes were overexpressed in tumours and in CIN3/CIS relative to both Normal and CIN1/CIN2, suggesting that they could have a role to play in the early phase of tumorigenesis. IL8, INDO, ISG15, ISG20, AGRN, DTXL, MMP1, MMP3, CCL18, TOP2A AND STAT1 were found to be upregulated in tumours. Using Immunohistochemistry, we showed over-expression of MMP3, UBE2C and p16 in cancers compared to normal cervical epithelium and varying grades of dysplasia. A dominant negative UBE2C was found to produce growth inhibition in SiHa cells, which over-expresses UBE2C 4 fold more than HEK293 cells. Several novel genes were found to be differentially expressed in cervical cancer. MMP3, UBE2C and p16 protein overexpression in cervical cancers was confirmed by immunohistochemistry. These will need to be validated further in a larger series of samples. UBE2C could be evaluated further to assess its potential as a

Comparative analysis of clustering methods for gene expression time course data

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Ivan G. Costa

2004-01-01

Full Text Available This work performs a data driven comparative study of clustering methods used in the analysis of gene expression time courses (or time series. Five clustering methods found in the literature of gene expression analysis are compared: agglomerative hierarchical clustering, CLICK, dynamical clustering, k-means and self-organizing maps. In order to evaluate the methods, a k-fold cross-validation procedure adapted to unsupervised methods is applied. The accuracy of the results is assessed by the comparison of the partitions obtained in these experiments with gene annotation, such as protein function and series classification.

Bone to pick: the importance of evaluating reference genes for RT-qPCR quantification of gene expression in craniosynostosis and bone-related tissues and cells

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Yang Xianxian

2012-05-01

Full Text Available Abstract Background RT-qPCR is a common tool for quantification of gene expression, but its accuracy is dependent on the choice and stability (steady state expression levels of the reference gene/s used for normalization. To date, in the bone field, there have been few studies to determine the most stable reference genes and, usually, RT-qPCR data is normalised to non-validated reference genes, most commonly GAPDH, ACTB and 18 S rRNA. Here we draw attention to the potential deleterious impact of using classical reference genes to normalise expression data for bone studies without prior validation of their stability. Results Using the geNorm and Normfinder programs, panels of mouse and human genes were assessed for their stability under three different experimental conditions: 1 disease progression of Crouzon syndrome (craniosynostosis in a mouse model, 2 proliferative culture of cranial suture cells isolated from craniosynostosis patients and 3 osteogenesis of a mouse bone marrow stromal cell line. We demonstrate that classical reference genes are not always the most ‘stable’ genes and that gene ‘stability’ is highly dependent on experimental conditions. Selected stable genes, individually or in combination, were then used to normalise osteocalcin and alkaline phosphatase gene expression data during cranial suture fusion in the craniosynostosis mouse model and strategies compared. Strikingly, the expression trends of alkaline phosphatase and osteocalcin varied significantly when normalised to the least stable, the most stable or the three most stable genes. Conclusion To minimise errors in evaluating gene expression levels, analysis of a reference panel and subsequent normalization to several stable genes is strongly recommended over normalization to a single gene. In particular, we conclude that use of single, non-validated “housekeeping” genes such as GAPDH, ACTB and 18 S rRNA, currently a widespread practice by researchers in

Genome-wide expression in veterans with schizophrenia further validates the immune hypothesis for schizophrenia.

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Fries, Gabriel R; Dimitrov, Dimitre H; Lee, Shuko; Braida, Nicole; Yantis, Jesse; Honaker, Craig; Cuellar, Joe; Walss-Bass, Consuelo

2018-02-01

This study aimed to test whether a dysregulation of gene expression may be the underlying cause of previously reported elevated levels of inflammatory cytokines in veterans with schizophrenia. We performed a genome-wide expression analysis in peripheral blood mononuclear cells from veterans with schizophrenia and controls, and our results show that 167 genes and putative loci were differently expressed between groups. These genes were enriched primarily for pathways related to inflammatory mechanisms and formed networks related to cell death and survival, immune cell trafficking, among others, which is in line with previous reports and further validates the inflammatory hypothesis of schizophrenia. Copyright © 2017 Elsevier B.V. All rights reserved.

Amplification biases: possible differences among deviating gene expressions

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Piumi Francois

2008-01-01

Full Text Available Abstract Background Gene expression profiling has become a tool of choice to study pathological or developmental questions but in most cases the material is scarce and requires sample amplification. Two main procedures have been used: in vitro transcription (IVT and polymerase chain reaction (PCR, the former known as linear and the latter as exponential. Previous reports identified enzymatic pitfalls in PCR and IVT protocols; however the possible differences between the sequences affected by these amplification defaults were only rarely explored. Results Screening a bovine cDNA array dedicated to embryonic stages with embryonic (n = 3 and somatic tissues (n = 2, we proceeded to moderate amplifications starting from 1 μg of total RNA (global PCR or IVT one round. Whatever the tissue, 16% of the probes were involved in deviating gene expressions due to amplification defaults. These distortions were likely due to the molecular features of the affected sequences (position within a gene, GC content, hairpin number but also to the relative abundance of these transcripts within the tissues. These deviating genes mainly encoded housekeeping genes from physiological or cellular processes (70% and constituted 2 subsets which did not overlap (molecular features, signal intensities, gene ID. However, the differential expressions identified between embryonic stages were both reliable (minor intersect with biased expressions and relevant (biologically validated. In addition, the relative expression levels of those genes were biologically similar between amplified and unamplified samples. Conclusion Conversely to the most recent reports which challenged the use of intense amplification procedures on minute amounts of RNA, we chose moderate PCR and IVT amplifications for our gene profiling study. Conclusively, it appeared that systematic biases arose even with moderate amplification procedures, independently of (i the sample used: brain, ovary or embryos, (ii

Identification and validation of reference genes for quantitative RT-PCR normalization in wheat

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Porceddu Enrico

2009-02-01

Full Text Available Abstract Background Usually the reference genes used in gene expression analysis have been chosen for their known or suspected housekeeping roles, however the variation observed in most of them hinders their effective use. The assessed lack of validated reference genes emphasizes the importance of a systematic study for their identification. For selecting candidate reference genes we have developed a simple in silico method based on the data publicly available in the wheat databases Unigene and TIGR. Results The expression stability of 32 genes was assessed by qRT-PCR using a set of cDNAs from 24 different plant samples, which included different tissues, developmental stages and temperature stresses. The selected sequences included 12 well-known HKGs representing different functional classes and 20 genes novel with reference to the normalization issue. The expression stability of the 32 candidate genes was tested by the computer programs geNorm and NormFinder using five different data-sets. Some discrepancies were detected in the ranking of the candidate reference genes, but there was substantial agreement between the groups of genes with the most and least stable expression. Three new identified reference genes appear more effective than the well-known and frequently used HKGs to normalize gene expression in wheat. Finally, the expression study of a gene encoding a PDI-like protein showed that its correct evaluation relies on the adoption of suitable normalization genes and can be negatively affected by the use of traditional HKGs with unstable expression, such as actin and α-tubulin. Conclusion The present research represents the first wide screening aimed to the identification of reference genes and of the corresponding primer pairs specifically designed for gene expression studies in wheat, in particular for qRT-PCR analyses. Several of the new identified reference genes outperformed the traditional HKGs in terms of expression stability

Bidirectional manipulation of gene expression in adipocytes using CRISPRa and siRNA

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Lundh, Morten; Pluciñska, Kaja; Isidor, Marie S

2017-01-01

OBJECTIVE: Functional investigation of novel gene/protein targets associated with adipocyte differentiation or function heavily relies on efficient and accessible tools to manipulate gene expression in adipocytes in vitro. Recent advances in gene-editing technologies such as CRISPR-Cas9 have...... not only eased gene editing but also greatly facilitated modulation of gene expression without altering the genome. Here, we aimed to develop and validate a competent in vitro adipocyte model of controllable functionality as well as multiplexed gene manipulation in adipocytes, using the CRISPRa "SAM......" system and siRNAs to simultaneously overexpress and silence selected genes in the same cell populations. METHODS: We introduced a stable expression of dCas9-VP64 and MS2-P65, the core components of the CRIPSRa SAM system, in mesenchymal C3H/10T1/2 cells through viral delivery and used guide RNAs...

Biofilm-Associated Gene Expression in Staphylococcus pseudintermedius on a Variety of Implant Materials.

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Crawford, Evan C; Singh, Ameet; Gibson, Thomas W G; Scott Weese, J

2016-05-01

To evaluate the expression of biofilm-associated genes in Staphylococcus pseudintermedius on multiple clinically relevant surfaces. In vitro experimental study. Two strains of methicillin-resistant S. pseudintermedius isolated from clinical infections representing the most common international isolates. A quantitative polymerase chain reaction (qPCR) assay for expression of genes related to biofilm initial adhesion, formation/maturation, antimicrobial resistance, and intracellular communication was developed and validated. S. pseudintermedius biofilms were grown on 8 clinically relevant surfaces (polymethylmethacrylate, stainless steel, titanium, latex, silicone, polydioxanone, polystyrene, and glass) and samples of logarithmic and stationary growth phases were collected. Gene expression in samples was measured by qPCR. Significant differences in gene expression were identified between surfaces and between bacterial strains for most gene/strain/surface combinations studied. Expression of genes responsible for production of extracellular matrix were increased in biofilms. Expression of genes responsible for initial adhesion and intracellular communication was markedly variable. Antimicrobial resistance gene expression was increased on multiple surfaces, including stainless steel and titanium. A method for evaluation of expression of multiple biofilm-associated genes in S. pseudintermedius was successfully developed and applied to the study of biofilms on multiple surfaces. Variations in expression of these genes have a bearing on understanding the development and treatment of implant-associated biofilm infections and will inform future clinical research. © Copyright 2016 by The American College of Veterinary Surgeons.

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

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Alok Arun

Full Text Available 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

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

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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

Validation of housekeeping genes for quantitative real-time PCR in in-vivo and in-vitro models of cerebral ischaemia

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Serena Joaquín

2009-06-01

Full Text Available Abstract Background Studies of gene expression in experimental cerebral ischaemia models can contribute to understanding the pathophysiology of brain ischaemia and to identifying prognostic markers and potential therapeutic targets. The normalization of relative qRT-PCR data using a suitable reference gene is a crucial prerequisite for obtaining reliable conclusions. No validated housekeeping genes have been reported for the relative quantification of the mRNA expression profile activated in in-vitro ischaemic conditions, whereas for the in-vivo model different reference genes have been used. The present study aims to determine the expression stability of ten housekeeping genes (Gapdh, β2m, Hprt, Ppia, Rpl13a, Oaz1, 18S rRNA, Gusb, Ywhaz and Sdha to establish their suitability as control genes for in-vitro and in-vivo cerebral ischaemia models. Results The expression stability of the candidate reference genes was evaluated using the 2-ΔC'T method and ANOVA followed by Dunnett's test. For the in-vitro model using primary cultures of rat astrocytes, all genes analysed except for Rpl13a and Sdha were found to have significantly different levels of mRNA expression. These different levels were also found in the case of the in-vivo model of pMCAO in rats except for Hprt, Sdha and Ywhaz mRNA, where the expression did not vary. Sdha and Ywhaz were identified by geNorm and NormFinder as the two most stable genes. Conclusion We have validated endogenous control genes for qRT-PCR analysis of gene expression in in-vitro and in-vivo cerebral ischaemia models. For normalization purposes, Rpl13a and Sdha are found to be the most suitable genes for the in-vitro model and Sdha and Ywhaz for the in-vivo model. Genes previously used as housekeeping genes for the in-vivo model in the literature were not validated as good control genes in the present study, showing the need for careful evaluation for each new experimental setup.

Validation of reference genes in Solenopsis invicta in different developmental stages, castes and tissues.

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Daifeng Cheng

Full Text Available To accurately assess gene expression levels, it is essential to normalize real-time quantitative PCR (RT-qPCR data with suitable internal reference genes. For the red imported fire ant, Solenopsis invicta, reliable reference genes to assess the transcript expression levels of the target genes have not been previously investigated. In this study, we examined the expression levels of five candidate reference genes (rpl18, ef1-beta, act, GAPDH, and tbp in different developmental stages, castes and tissues of S. invicta. To evaluate the suitability of these genes as endogenous controls, three software-based approaches (geNorm, BestKeeper and NormFinder and one web-based comprehensive tool (RefFinder were used to analyze and rank the tested genes. Furthermore, the optimal number of reference gene(s was determined by the pairwise variation value. Our data showed that two of the five candidate genes, rpl18 and ef1-beta, were the most suitable reference genes because they have the most stable expression among different developmental stages, castes and tissues in S. invicta. Although widely used as reference gene in other species, in S. invicta the act gene has high variation in expression and was consequently excluded as a reliable reference gene. The two validated reference genes, rpl18 and ef1-beta, can be widely used for quantification of target gene expression with RT-qPCR technology in S. invicta.

Transcriptome profiling in conifers and the PiceaGenExpress database show patterns of diversification within gene families and interspecific conservation in vascular gene expression

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Raherison Elie

2012-08-01

Full Text Available Abstract Background Conifers have very large genomes (13 to 30 Gigabases that are mostly uncharacterized although extensive cDNA resources have recently become available. This report presents a global overview of transcriptome variation in a conifer tree and documents conservation and diversity of gene expression patterns among major vegetative tissues. Results An oligonucleotide microarray was developed from Picea glauca and P. sitchensis cDNA datasets. It represents 23,853 unique genes and was shown to be suitable for transcriptome profiling in several species. A comparison of secondary xylem and phelloderm tissues showed that preferential expression in these vascular tissues was highly conserved among Picea spp. RNA-Sequencing strongly confirmed tissue preferential expression and provided a robust validation of the microarray design. A small database of transcription profiles called PiceaGenExpress was developed from over 150 hybridizations spanning eight major tissue types. In total, transcripts were detected for 92% of the genes on the microarray, in at least one tissue. Non-annotated genes were predominantly expressed at low levels in fewer tissues than genes of known or predicted function. Diversity of expression within gene families may be rapidly assessed from PiceaGenExpress. In conifer trees, dehydrins and late embryogenesis abundant (LEA osmotic regulation proteins occur in large gene families compared to angiosperms. Strong contrasts and low diversity was observed in the dehydrin family, while diverse patterns suggested a greater degree of diversification among LEAs. Conclusion Together, the oligonucleotide microarray and the PiceaGenExpress database represent the first resource of this kind for gymnosperm plants. The spruce transcriptome analysis reported here is expected to accelerate genetic studies in the large and important group comprised of conifer trees.

Analytical validation of a melanoma diagnostic gene signature using formalin-fixed paraffin-embedded melanocytic lesions.

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Warf, M Bryan; Flake, Darl D; Adams, Doug; Gutin, Alexander; Kolquist, Kathryn A; Wenstrup, Richard J; Roa, Benjamin B

2015-01-01

These studies were to validate the analytical performance of a gene expression signature that differentiates melanoma and nevi, using RNA expression from 14 signature genes and nine normalization genes that generates a melanoma diagnostic score (MDS). Formalin-fixed paraffin-embedded melanocytic lesions were evaluated in these studies. The overall SD of the assay was determined to be 0.69 MDS units. Individual amplicons within the signature had an average amplification efficiency of 92% and a SD less than 0.5 CT. The MDS was reproducible across a 2000-fold dilution range of input RNA. Melanin, an inhibitor of PCR, does not interfere with the signature. These studies indicate this signature is robust and reproducible and is analytically validated on formalin-fixed paraffin-embedded melanocytic lesions.

Evaluation and validation of candidate endogenous control genes for real-time quantitative PCR studies of breast cancer

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Miller Nicola

2007-11-01

Full Text Available Abstract Background Real-time quantitative PCR (RQ-PCR forms the basis of many breast cancer biomarker studies and novel prognostic assays, paving the way towards personalised cancer treatments. Normalisation of relative RQ-PCR data is required to control for non-biological variation introduced during sample preparation. Endogenous control (EC genes, used in this context, should ideally be expressed constitutively and uniformly across treatments in all test samples. Despite widespread recognition that the accuracy of the normalised data is largely dependent on the reliability of the EC, there are no reports of the systematic validation of genes commonly used for this purpose in the analysis of gene expression by RQ-PCR in primary breast cancer tissues. The aim of this study was to identify the most suitable endogenous control genes for RQ-PCR analysis of primary breast tissue from a panel of eleven candidates in current use. Oestrogen receptor alpha (ESR1 was used a target gene to compare the effect of choice of EC on the estimate of gene quantity. Results The expression and validity of candidate ECs (GAPDH, TFRC, ABL, PPIA, HPRT1, RPLP0, B2M, GUSB, MRPL19, PUM1 and PSMC4 was determined in 6 benign and 21 malignant primary breast cancer tissues. Gene expression data was analysed using two different statistical models. MRPL19 and PPIA were identified as the most stable and reliable EC genes, while GUSB, RPLP0 and ABL were least stable. There was a highly significant difference in variance between ECs. ESR1 expression was appreciably higher in malignant compared to benign tissues and there was a significant effect of EC on the magnitude of the error associated with the relative quantity of ESR1. Conclusion We have validated two endogenous control genes, MRPL19 and PPIA, for RQ-PCR analysis of gene expression in primary breast tissue. Of the genes in current use in this field, the above combination offers increased accuracy and resolution in the

Effects of chronic morphine and morphine withdrawal on gene expression in rat peripheral blood mononuclear cells.

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Desjardins, Stephane; Belkai, Emilie; Crete, Dominique; Cordonnier, Laurie; Scherrmann, Jean-Michel; Noble, Florence; Marie-Claire, Cynthia

2008-12-01

Chronic morphine treatment alters gene expression in brain structures. There are increasing evidences showing a correlation, in gene expression modulation, between blood cells and brain in psychological troubles. To test whether gene expression regulation in blood cells could be found in drug addiction, we investigated gene expression profiles in peripheral blood mononuclear (PBMC) cells of saline and morphine-treated rats. In rats chronically treated with morphine, the behavioral signs of spontaneous withdrawal were observed and a withdrawal score was determined. This score enabled to select the time points at which the animals displayed the mildest and strongest withdrawal signs (12 h and 36 h after the last injection). Oligonucleotide arrays were used to assess differential gene expression in the PBMCs and quantitative real-time RT-PCR to validate the modulation of several candidate genes 12 h and 36 h after the last injection. Among the 812 differentially expressed candidates, several genes (Adcy5, Htr2a) and pathways (Map kinases, G-proteins, integrins) have already been described as modulated in the brain of morphine-treated rats. Sixteen out of the twenty-four tested candidates were validated at 12 h, some of them showed a sustained modulation at 36 h while for most of them the modulation evolved as the withdrawal score increased. This study suggests similarities between the gene expression profile in PBMCs and brain of morphine-treated rats. Thus, the searching of correlations between the severity of the withdrawal and the PBMCs gene expression pattern by transcriptional analysis of blood cells could be promising for the study of the mechanisms of addiction.

Identification and validation of reference genes for qRT-PCR studies of the obligate aphid pathogenic fungus Pandora neoaphidis during different developmental stages.

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Shutao Zhang

Full Text Available The selection of stable reference genes is a critical step for the accurate quantification of gene expression. To identify and validate the reference genes in Pandora neoaphidis-an obligate aphid pathogenic fungus-the expression of 13classical candidate reference genes were evaluated by quantitative real-time reverse transcriptase polymerase chain reaction(qPCR at four developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae. Four statistical algorithms, including geNorm, NormFinder, BestKeeper and Delta Ct method were used to rank putative reference genes according to their expression stability and indicate the best reference gene or combination of reference genes for accurate normalization. The analysis of comprehensive ranking revealed that ACT1and 18Swas the most stably expressed genes throughout the developmental stages. To further validate the suitability of the reference genes identified in this study, the expression of cell division control protein 25 (CDC25 and Chitinase 1(CHI1 genes were used to further confirm the validated candidate reference genes. Our study presented the first systematic study of reference gene(s selection for P. neoaphidis study and provided guidelines to obtain more accurate qPCR results for future developmental efforts.

Design parameters to control synthetic gene expression in Escherichia coli.

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Mark Welch

Full Text Available BACKGROUND: Production of proteins as therapeutic agents, research reagents and molecular tools frequently depends on expression in heterologous hosts. Synthetic genes are increasingly used for protein production because sequence information is easier to obtain than the corresponding physical DNA. Protein-coding sequences are commonly re-designed to enhance expression, but there are no experimentally supported design principles. PRINCIPAL FINDINGS: To identify sequence features that affect protein expression we synthesized and expressed in E. coli two sets of 40 genes encoding two commercially valuable proteins, a DNA polymerase and a single chain antibody. Genes differing only in synonymous codon usage expressed protein at levels ranging from undetectable to 30% of cellular protein. Using partial least squares regression we tested the correlation of protein production levels with parameters that have been reported to affect expression. We found that the amount of protein produced in E. coli was strongly dependent on the codons used to encode a subset of amino acids. Favorable codons were predominantly those read by tRNAs that are most highly charged during amino acid starvation, not codons that are most abundant in highly expressed E. coli proteins. Finally we confirmed the validity of our models by designing, synthesizing and testing new genes using codon biases predicted to perform well. CONCLUSION: The systematic analysis of gene design parameters shown in this study has allowed us to identify codon usage within a gene as a critical determinant of achievable protein expression levels in E. coli. We propose a biochemical basis for this, as well as design algorithms to ensure high protein production from synthetic genes. Replication of this methodology should allow similar design algorithms to be empirically derived for any expression system.

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

DEFF Research Database (Denmark)

Manijak, Mieszko P.; Nielsen, Henrik Bjørn

2011-01-01

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

A Toolbox for Quantitative Gene Expression in Varroa destructor: RNA Degradation in Field Samples and Systematic Analysis of Reference Gene Stability.

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Ewan M Campbell

Full Text Available Varroa destructor is the major pest of Apis mellifera and contributes to the global honey bee health crisis threatening food security. Developing new control strategies to combat Varroa will require the application of molecular biology, including gene expression studies by quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR. Both high quality RNA samples and suitable stable internal reference genes are required for accurate gene expression studies. In this study, ten candidate genes (succinate dehydrogenase (SDHA, NADH dehydrogenase (NADH, large ribsosmal subunit, TATA-binding protein, glyceraldehyde-3-phosphate dehydrogenase, 18S rRNA (18S, heat-shock protein 90 (HSP90, cyclophilin, α-tubulin, actin, were evaluated for their suitability as normalization genes using the geNorm, Normfinder, BestKeeper, and comparative ΔCq algorithims. Our study proposes the use of no more than two of the four most stable reference genes (NADH, 18S, SDHA and HSP90 in Varroa gene expression studies. These four genes remain stable in phoretic and reproductive stage Varroa and are unaffected by Deformed wing virus load. When used for determining changes in vitellogenin gene expression, the signal-to-noise ratio (SNR for the relatively unstable genes actin and α-tubulin was much lower than for the stable gene combinations (NADH + HSP90 +18S; NADH + HSP90; or NADH. Using both electropherograms and RT-qPCR for short and long amplicons as quality controls, we demonstrate that high quality RNA can be recovered from Varroa up to 10 days later stored at ambient temperature if collected into RNAlater and provided the body is pierced. This protocol allows the exchange of Varroa samples between international collaborators and field sample collectors without requiring frozen collection or shipping. Our results make important contributions to gene expression studies in Varroa by proposing a validated sampling protocol to obtain high quality Varroa

Integrating chromosomal aberrations and gene expression profiles to dissect rectal tumorigenesis

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Eilers Paul HC

2008-10-01

Full Text Available Abstract Background Accurate staging of rectal tumors is essential for making the correct treatment choice. In a previous study, we found that loss of 17p, 18q and gain of 8q, 13q and 20q could distinguish adenoma from carcinoma tissue and that gain of 1q was related to lymph node metastasis. In order to find markers for tumor staging, we searched for candidate genes on these specific chromosomes. Methods We performed gene expression microarray analysis on 79 rectal tumors and integrated these data with genomic data from the same sample series. We performed supervised analysis to find candidate genes on affected chromosomes and validated the results with qRT-PCR and immunohistochemistry. Results Integration of gene expression and chromosomal instability data revealed similarity between these two data types. Supervised analysis identified up-regulation of EFNA1 in cases with 1q gain, and EFNA1 expression was correlated with the expression of a target gene (VEGF. The BOP1 gene, involved in ribosome biogenesis and related to chromosomal instability, was over-expressed in cases with 8q gain. SMAD2 was the most down-regulated gene on 18q, and on 20q, STMN3 and TGIF2 were highly up-regulated. Immunohistochemistry for SMAD4 correlated with SMAD2 gene expression and 18q loss. Conclusion On basis of integrative analysis this study identified one well known CRC gene (SMAD2 and several other genes (EFNA1, BOP1, TGIF2 and STMN3 that possibly could be used for rectal cancer characterization.

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

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

2015-01-27

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

Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

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Karacali Bilge

2007-10-01

Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

Selection of reference genes for qRT-PCR analysis of gene expression in sea cucumber Apostichopus japonicus during aestivation

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Zhao, Ye; Chen, Muyan; Wang, Tianming; Sun, Lina; Xu, Dongxue; Yang, Hongsheng

2014-11-01

Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is a technique that is widely used for gene expression analysis, and its accuracy depends on the expression stability of the internal reference genes used as normalization factors. However, many applications of qRT-PCR used housekeeping genes as internal controls without validation. In this study, the expression stability of eight candidate reference genes in three tissues (intestine, respiratory tree, and muscle) of the sea cucumber Apostichopus japonicus was assessed during normal growth and aestivation using the geNorm, NormFinder, delta CT, and RefFinder algorithms. The results indicate that the reference genes exhibited significantly different expression patterns among the three tissues during aestivation. In general, the β-tubulin (TUBB) gene was relatively stable in the intestine and respiratory tree tissues. The optimal reference gene combination for intestine was 40S ribosomal protein S18 (RPS18), TUBB, and NADH dehydrogenase (NADH); for respiratory tree, it was β-actin (ACTB), TUBB, and succinate dehydrogenase cytochrome B small subunit (SDHC); and for muscle it was α-tubulin (TUBA) and NADH dehydrogenase [ubiquinone] 1 α subcomplex subunit 13 (NDUFA13). These combinations of internal control genes should be considered for use in further studies of gene expression in A. japonicus during aestivation.

Blood cell gene expression profiling in subjects with aggressive periodontitis and chronic arthritis

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Sørensen, Lars K; Poulsen, Anne Havemose; Sønder, Søren U

2008-01-01

with untreated localized aggressive periodontitis (LAgP) or generalized aggressive periodontitis (GAgP). Differentially expressed genes were validated in groups of subjects with LAgP, GAgP, juvenile idiopathic arthritis (JIA), or rheumatoid arthritis (RA) and controls. METHODS: Candidate genes were identified...

Connecting protein and mRNA burst distributions for stochastic models of gene expression

International Nuclear Information System (INIS)

Elgart, Vlad; Jia, Tao; Fenley, Andrew T; Kulkarni, Rahul

2011-01-01

The intrinsic stochasticity of gene expression can lead to large variability in protein levels for genetically identical cells. Such variability in protein levels can arise from infrequent synthesis of mRNAs which in turn give rise to bursts of protein expression. Protein expression occurring in bursts has indeed been observed experimentally and recent studies have also found evidence for transcriptional bursting, i.e. production of mRNAs in bursts. Given that there are distinct experimental techniques for quantifying the noise at different stages of gene expression, it is of interest to derive analytical results connecting experimental observations at different levels. In this work, we consider stochastic models of gene expression for which mRNA and protein production occurs in independent bursts. For such models, we derive analytical expressions connecting protein and mRNA burst distributions which show how the functional form of the mRNA burst distribution can be inferred from the protein burst distribution. Additionally, if gene expression is repressed such that observed protein bursts arise only from single mRNAs, we show how observations of protein burst distributions (repressed and unrepressed) can be used to completely determine the mRNA burst distribution. Assuming independent contributions from individual bursts, we derive analytical expressions connecting means and variances for burst and steady-state protein distributions. Finally, we validate our general analytical results by considering a specific reaction scheme involving regulation of protein bursts by small RNAs. For a range of parameters, we derive analytical expressions for regulated protein distributions that are validated using stochastic simulations. The analytical results obtained in this work can thus serve as useful inputs for a broad range of studies focusing on stochasticity in gene expression

Gene expression profiles in stages II and III colon cancers

DEFF Research Database (Denmark)

Thorsteinsson, Morten; Kirkeby, Lene T; Hansen, Raino

2012-01-01

PURPOSE: A 128-gene signature has been proposed to predict outcome in patients with stages II and III colorectal cancers. In the present study, we aimed to reproduce and validate the 128-gene signature in external and independent material. METHODS: Gene expression data from the original material...... were retrieved from the Gene Expression Omnibus (GEO) (n¿=¿111) in addition to a Danish data set (n¿=¿37). All patients had stages II and III colon cancers. A Prediction Analysis of Microarray classifier, based on the 128-gene signature and the original training set of stage I (n¿=¿65) and stage IV (n...... correctly predicted as stage IV-like, and the remaining patients were predicted as stage I-like and unclassifiable, respectively. Stage II patients could not be stratified. CONCLUSIONS: The 128-gene signature showed reproducibility in stage III colon cancer, but could not predict recurrence in stage II...

Argudas: lessons for argumentation in biology based on a gene expression use case

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McLeod, Kenneth; Ferguson, Gus; Burger, Albert

2012-01-01

Background In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information online are often both incomplete and inconsistent. Non-monotonic reasoning can help resolve such difficulties - one such form of reasoning is computational argumentation. Essentially this involves asking a computer to debate (i.e. reason about) the validity of a particular statement. Arguments are produced for both...

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

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

2014-05-01

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

Transcriptome database resource and gene expression atlas for the rose

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2012-01-01

Background For centuries roses have been selected based on a number of traits. Little information exists on the genetic and molecular basis that contributes to these traits, mainly because information on expressed genes for this economically important ornamental plant is scarce. Results Here, we used a combination of Illumina and 454 sequencing technologies to generate information on Rosa sp. transcripts using RNA from various tissues and in response to biotic and abiotic stresses. A total of 80714 transcript clusters were identified and 76611 peptides have been predicted among which 20997 have been clustered into 13900 protein families. BLASTp hits in closely related Rosaceae species revealed that about half of the predicted peptides in the strawberry and peach genomes have orthologs in Rosa dataset. Digital expression was obtained using RNA samples from organs at different development stages and under different stress conditions. qPCR validated the digital expression data for a selection of 23 genes with high or low expression levels. Comparative gene expression analyses between the different tissues and organs allowed the identification of clusters that are highly enriched in given tissues or under particular conditions, demonstrating the usefulness of the digital gene expression analysis. A web interface ROSAseq was created that allows data interrogation by BLAST, subsequent analysis of DNA clusters and access to thorough transcript annotation including best BLAST matches on Fragaria vesca, Prunus persica and Arabidopsis. The rose peptides dataset was used to create the ROSAcyc resource pathway database that allows access to the putative genes and enzymatic pathways. Conclusions The study provides useful information on Rosa expressed genes, with thorough annotation and an overview of expression patterns for transcripts with good accuracy. PMID:23164410

Gene expression profiling leads to discovery of correlation of matrix metalloproteinase 11 and heparanase 2 in breast cancer progression

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Fu, Junjie; Khaybullin, Ravil; Zhang, Yanping; Xia, Amy; Qi, Xin

2015-01-01

In order to identify biomarkers involved in breast cancer, gene expression profiling was conducted using human breast cancer tissues. Total RNAs were extracted from 150 clinical patient tissues covering three breast cancer subtypes (Luminal A, Luminal B, and Triple negative) as well as normal tissues. The expression profiles of a total of 50,739 genes were established from a training set of 32 samples using the Agilent Sure Print G3 Human Gene Expression Microarray technology. Data were analyzed using Agilent Gene Spring GX 12.6 software. The expression of several genes was validated using real-time RT-qPCR. Data analysis with Agilent GeneSpring GX 12.6 software showed distinct expression patterns between cancer and normal tissue samples. A group of 28 promising genes were identified with ≥ 10-fold changes of expression level and p-values < 0.05. In particular, MMP11 and HPSE2 were closely examined due to the important roles they play in cancer cell growth and migration. Real-time RT-qPCR analyses of both training and testing sets validated the gene expression profiles of MMP11 and HPSE2. Our findings identified these 2 genes as a novel breast cancer biomarker gene set, which may facilitate the diagnosis and treatment in breast cancer clinical therapies

The utility of optical detection system (qPCR) and bioinformatics methods in reference gene expression analysis

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Skarzyńska, Agnieszka; Pawełkowicz, Magdalena; PlÄ der, Wojciech; Przybecki, Zbigniew

2016-09-01

Real-time quantitative polymerase chain reaction is consider as the most reliable method for gene expression studies. However, the expression of target gene could be misinterpreted due to improper normalization. Therefore, the crucial step for analysing of qPCR data is selection of suitable reference genes, which should be validated experimentally. In order to choice the gene with stable expression in the designed experiment, we performed reference gene expression analysis. In this study genes described in the literature and novel genes predicted as control genes, based on the in silico analysis of transcriptome data were used. Analysis with geNorm and NormFinder algorithms allow to create the ranking of candidate genes and indicate the best reference for flower morphogenesis study. According to the results, genes CACS and CYCL were characterised the most stable expression, but the least suitable genes were TUA and EF.

Validation of endogenous normalizing genes for expression analyses in adult human testis and germ cell neoplasms

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Svingen, T; Jørgensen, Anne; Rajpert-De Meyts, E

2014-01-01

to define suitable normalizing genes for specific cells and tissues. Here, we report on the performance of a panel of nine commonly employed normalizing genes in adult human testis and testicular pathologies. Our analyses revealed significant variability in transcript abundance for commonly used normalizers......, highlighting the importance of selecting appropriate normalizing genes as comparative measurements can yield variable results when different normalizing genes are employed. Based on our results, we recommend using RPS20, RPS29 or SRSF4 when analysing relative gene expression levels in human testis...... and associated testicular pathologies. OCT4 and SALL4 can be used with caution as second-tier normalizers when determining changes in gene expression in germ cells and germ cell tumour components, but the relative transcript abundance appears variable between different germ cell tumour types. We further...

Single muscle fiber gene expression in human skeletal muscle: validation of internal control with exercise

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Jemiolo, Bozena; Trappe, Scott

2004-01-01

Reverse transcription and real-time PCR have become the method of choice for the detection of low-abundance mRNA transcripts obtained from small human muscle biopsy samples. GAPDH, β-actin, β-2M, and 18S rRNA are widely employed as endogenous control genes, with the assumption that their expression is unregulated and constant for given experimental conditions. The aim of this study was to determine if mRNA transcripts could be performed on isolated human single muscle fibers and to determine reliable housekeeping genes (HKGs) using quantitative gene expression protocols at rest and in response to an acute exercise bout. Muscle biopsies were obtained from the gastrocnemius of three adult males before, immediately after, and 4 h following 30 min of treadmill running at 70% of VO 2 max. A total of 40 single fibers (MHC I and IIa) were examined for GAPDH, β-actin, β-2M, and 18S rRNA using quantitative RT-PCR and SYBR Green detection. All analyzed single fiber segments showed ribosomal RNA (28S/18S). No degradation or additional bands below ribosomal were detected (rRNA ratio 1.5-1.8). Also, no high or low-molecular weight genomic DNA contamination was observed. For each housekeeping gene the duplicate average SD was ±0.13 with a CV of 0.58%. Stable expression of GAPDH was observed at all time points for each fiber type (MHC I and IIa). Inconsistent expression of β-actin, β-2M, and 18S rRNA was observed during the post-exercise time points for each fiber type. These data indicate that successful extraction of high quality RNA from human single muscle fibers along with quantification of mRNA of selected genes can be performed. Furthermore, exercise does influence the expression of certain HKGs with GAPDH being the most stable

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

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Benjamin Mayne

2016-10-01

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

Alteration of gene expression and DNA methylation in drug-resistant gastric cancer.

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Maeda, Osamu; Ando, Takafumi; Ohmiya, Naoki; Ishiguro, Kazuhiro; Watanabe, Osamu; Miyahara, Ryoji; Hibi, Yoko; Nagai, Taku; Yamada, Kiyofumi; Goto, Hidemi

2014-04-01

The mechanisms of drug resistance in cancer are not fully elucidated. To study the drug resistance of gastric cancer, we analyzed gene expression and DNA methylation profiles of 5-fluorouracil (5-FU)- and cisplatin (CDDP)-resistant gastric cancer cells and biopsy specimens. Drug-resistant gastric cancer cells were established with culture for >10 months in a medium containing 5-FU or CDDP. Endoscopic biopsy specimens were obtained from gastric cancer patients who underwent chemotherapy with oral fluoropyrimidine S-1 and CDDP. Gene expression and DNA methylation analyses were performed using microarray, and validated using real-time PCR and pyrosequencing, respectively. Out of 17,933 genes, 541 genes commonly increased and 569 genes decreased in both 5-FU- and CDDP-resistant AGS cells. Genes with expression changed by drugs were related to GO term 'extracellular region' and 'p53 signaling pathway' in both 5-FU- and CDDP-treated cells. Expression of 15 genes including KLK13 increased and 12 genes including ETV7 decreased, in both drug-resistant cells and biopsy specimens of two patients after chemotherapy. Out of 10,365 genes evaluated with both expression microarray and methylation microarray, 74 genes were hypermethylated and downregulated, or hypomethylated and upregulated in either 5-FU-resistant or CDDP-resistant cells. Of these genes, expression of 21 genes including FSCN1, CPT1C and NOTCH3, increased from treatment with a demethylating agent. There are alterations of gene expression and DNA methylation in drug-resistant gastric cancer; they may be related to mechanisms of drug resistance and may be useful as biomarkers of gastric cancer drug sensitivity.

Validation of a mouse xenograft model system for gene expression analysis of human acute lymphoblastic leukaemia

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Francis Richard W

2010-04-01

Full Text Available Abstract Background Pre-clinical models that effectively recapitulate human disease are critical for expanding our knowledge of cancer biology and drug resistance mechanisms. For haematological malignancies, the non-obese diabetic/severe combined immunodeficient (NOD/SCID mouse is one of the most successful models to study paediatric acute lymphoblastic leukaemia (ALL. However, for this model to be effective for studying engraftment and therapy responses at the whole genome level, careful molecular characterisation is essential. Results Here, we sought to validate species-specific gene expression profiling in the high engraftment continuous ALL NOD/SCID xenograft. Using the human Affymetrix whole transcript platform we analysed transcriptional profiles from engrafted tissues without prior cell separation of mouse cells and found it to return highly reproducible profiles in xenografts from individual mice. The model was further tested with experimental mixtures of human and mouse cells, demonstrating that the presence of mouse cells does not significantly skew expression profiles when xenografts contain 90% or more human cells. In addition, we present a novel in silico and experimental masking approach to identify probes and transcript clusters susceptible to cross-species hybridisation. Conclusions We demonstrate species-specific transcriptional profiles can be obtained from xenografts when high levels of engraftment are achieved or with the application of transcript cluster masks. Importantly, this masking approach can be applied and adapted to other xenograft models where human tissue infiltration is lower. This model provides a powerful platform for identifying genes and pathways associated with ALL disease progression and response to therapy in vivo.

In search of suitable reference genes for gene expression studies of human renal cell carcinoma by real-time PCR

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Kristiansen Glen

2007-06-01

Full Text Available Abstract Background Housekeeping genes are commonly used as endogenous reference genes for the relative quantification of target genes in gene expression studies. No conclusive systematic study comparing the suitability of different candidate reference genes in clear cell renal cell carcinoma has been published to date. To remedy this situation, 10 housekeeping genes for normalizing purposes of RT-PCR measurements already recommended in various studies were examined with regard to their usefulness as reference genes. Results The expression of the potential reference genes was examined in matched malignant and non-malignant tissue specimens from 25 patients with clear cell renal cell carcinoma. Quality assessment of isolated RNA performed with a 2100 Agilent Bioanalyzer showed a mean RNA integrity number of 8.7 for all samples. The between-run variations related to the crossing points of PCR reactions of a control material ranged from 0.17% to 0.38%. The expression of all genes did not depend on age, sex, and tumour stage. Except the genes TATA box binding protein (TBP and peptidylprolyl isomerase A (PPIA, all genes showed significant differences in expression between malignant and non-malignant pairs. The expression stability of the candidate reference genes was additionally controlled using the software programs geNorm and NormFinder. TBP and PPIA were validated as suitable reference genes by normalizing the target gene ADAM9 using these two most stably expressed genes in comparison with up- and down-regulated housekeeping genes of the panel. Conclusion Our study demonstrated the suitability of the two housekeeping genes PPIA and TBP as endogenous reference genes when comparing malignant tissue samples with adjacent normal tissue samples from clear cell renal cell carcinoma. Both genes are recommended as reference genes for relative gene quantification in gene profiling studies either as single gene or preferably in combination.

Whole-Transcriptome Selection and Evaluation of Internal Reference Genes for Expression Analysis in Protocorm Development of Dendrobium officinale Kimura et Migo.

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Hongqiang An

Full Text Available Dendrobium officinale Kimu et Migo has increased many researchers' interest for its high medical and horticultural values and the molecular mechanism of its protocorm development remains unclear. In this study, 19 genes from 26 most stably expressed genes in whole transcriptome of protocorms and 5 housekeeping genes were used as candidate reference genes and screened with 4 application softwares (geNorm, NormFinder, BestKeeper and RefFinder. The results showed that a few reference genes could effectively normalize expression level of specific genes in protocorm development and the optimal top 2 reference genes were ASS and APH1L. Meanwhile, validation of GNOM, AP2 and temperature induced gene (TIL for normalization demonstrates the usefulness of the validated candidate reference genes. The expression profiles of these genes varied under protocorms and temperature stress according to the stablest and unstablest reference genes, which proved the importance of the choice of appropriate reference genes. The first systematic evaluation of stably expressed genes will be very useful in the future analysis of specific genes expression in D. officinale.

Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

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Yamada Yoichi

2012-12-01

Full Text Available Abstract Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO. MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO correctly identified (p Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively.

Effects of in ovo electroporation on endogenous gene expression: genome-wide analysis

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Chambers David

2011-04-01

Full Text Available Abstract Background In ovo electroporation is a widely used technique to study gene function in developmental biology. Despite the widespread acceptance of this technique, no genome-wide analysis of the effects of in ovo electroporation, principally the current applied across the tissue and exogenous vector DNA introduced, on endogenous gene expression has been undertaken. Here, the effects of electric current and expression of a GFP-containing construct, via electroporation into the midbrain of Hamburger-Hamilton stage 10 chicken embryos, are analysed by microarray. Results Both current alone and in combination with exogenous DNA expression have a small but reproducible effect on endogenous gene expression, changing the expression of the genes represented on the array by less than 0.1% (current and less than 0.5% (current + DNA, respectively. The subset of genes regulated by electric current and exogenous DNA span a disparate set of cellular functions. However, no genes involved in the regional identity were affected. In sharp contrast to this, electroporation of a known transcription factor, Dmrt5, caused a much greater change in gene expression. Conclusions These findings represent the first systematic genome-wide analysis of the effects of in ovo electroporation on gene expression during embryonic development. The analysis reveals that this process has minimal impact on the genetic basis of cell fate specification. Thus, the study demonstrates the validity of the in ovo electroporation technique to study gene function and expression during development. Furthermore, the data presented here can be used as a resource to refine the set of transcriptional responders in future in ovo electroporation studies of specific gene function.

Differential Gene Expression and Aging

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Laurent Seroude

2002-01-01

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

Strategy of gene silencing in cassava for validation of resistance genes

International Nuclear Information System (INIS)

Cortes, Simon; Lopez, Camilo

2010-01-01

Cassava (Manihot esculenta) is a major source of food for more than 1000 million people in the world and constitutes an important staple crop. Cassava bacterial blight, caused by the gram negative bacterium Xanthomonas axonopodis pv. manihotis, is one of the most important constraints for this crop. A candidate resistance gene against cassava bacterial blight, named RXam1, has been identified previously. In this work, we employed the gene silencing approach using the African cassava mosaic virus (ACMV) to validate the function of the RXam1 gene. We used as positive control the su gen, which produce photo blanching in leaves when is silenced. Plants from the SG10735 variety were bombardment with the ACMV-A-SU+ACMV-B y ACMV-A-RXam1+ACMV-B constructions. The silencing efficiency employing the su gene was low, only one of seven plants showed photo blanching. In the putative silenced plants for the RXam1 gene, no presence of siRNAs corresponding to RXam1 was observed; although a low diminution of the RXam1 gene expression was obtained. The growth curves for the Xam strain CIO136 in cassava plants inoculated showing a little but no significance difference in the susceptibility in the silenced plants compared to not silenced

Selection of Reference Genes for Expression Studies in Diaphorina citri (Hemiptera: Liviidae).

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Bassan, Meire Menezes; Angelotti-Mendonc A, Je Ssika; Alves, Gustavo Rodrigues; Yamamoto, Pedro Takao; Moura O Filho, Francisco de Assis Alves

2017-12-05

The Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera: Liviidae), is considered the main vector of the bacteria associated with huanglongbing, a very serious disease that has threatened the world citrus industry. The absence of efficient control management protocols, including a lack of resistant cultivars, has led to the development of different approaches to study this pathosystem. The production of resistant genotypes relies on D. citri gene expression analyses by RT-qPCR to assess control of the vector population. High-quality, reliable RT-qPCR analyses depend upon proper reference gene selection and validation. However, adequate D. citri reference genes have not yet been identified. In the present study, we evaluated the genes EF 1-α, ACT, GAPDH, RPL7, RPL17, and TUB as candidate reference genes for this insect. Gene expression stability was evaluated using the mathematical algorithms deltaCt, NormFinder, BestKeeper, and geNorm, at five insect developmental stages, grown on two different plant hosts [Citrus sinensis (L.) Osbeck (Sapindales: Rutaceae) and Murraya paniculata (L.) Jack (Sapindales: Rutaceae)]. The final gene ranking was calculated using RefFinder software, and the V-ATPase-A gene was selected for validation. According to our results, two reference genes are recommended when different plant hosts and developmental stages are considered. Considering gene expression studies in D. citri grown on M. paniculata, regardless of the insect developmental stage, GAPDH and RPL7 have the best fit as reference genes in RT-qPCR analyses, whereas GAPDH and EF 1-α are recommended as reference genes in insect studies using C. sinensis. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Altered expression pattern of clock genes in a rat model of depression

DEFF Research Database (Denmark)

Christiansen, Sofie; Bouzinova, Elena; Fahrenkrug, Jan

2016-01-01

BACKGROUND: Abnormalities in circadian rhythms may be causal factors in development of major depressive disorder. The biology underlying a causal relationship between circadian rhythm disturbances and depression is slowly being unraveled. Although there is no direct evidence of dysregulation...... of clock gene expression in depressive patients many studies have reported single-nucleotide polymorphisms in clock genes in these patients. METHODS: In the present study we investigated whether a depression-like state in rats associates with alternations of the diurnal expression of clock genes....... The validated chronic mild stress (CMS) animal model of depression was used to investigate rhythmic expression of three clock genes; Per1, Per2 and Bmal1. Brain and liver tissue was collected from 96 animals after 3.5 weeks of CMS (48 control and 48 depression-like rats) at 4 h sampling interval within 24 h. We...

Polycistronic gene expression in Aspergillus niger.

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Schuetze, Tabea; Meyer, Vera

2017-09-25

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

Genome wide gene expression regulation by HIP1 Protein Interactor, HIPPI: Prediction and validation

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Lahiri Ansuman

2011-09-01

Full Text Available Abstract Background HIP1 Protein Interactor (HIPPI is a pro-apoptotic protein that induces Caspase8 mediated apoptosis in cell. We have shown earlier that HIPPI could interact with a specific 9 bp sequence motif, defined as the HIPPI binding site (HBS, present in the upstream promoter of Caspase1 gene and regulate its expression. We also have shown that HIPPI, without any known nuclear localization signal, could be transported to the nucleus by HIP1, a NLS containing nucleo-cytoplasmic shuttling protein. Thus our present work aims at the investigation of the role of HIPPI as a global transcription regulator. Results We carried out genome wide search for the presence of HBS in the upstream sequences of genes. Our result suggests that HBS was predominantly located within 2 Kb upstream from transcription start site. Transcription factors like CREBP1, TBP, OCT1, EVI1 and P53 half site were significantly enriched in the 100 bp vicinity of HBS indicating that they might co-operate with HIPPI for transcription regulation. To illustrate the role of HIPPI on transcriptome, we performed gene expression profiling by microarray. Exogenous expression of HIPPI in HeLa cells resulted in up-regulation of 580 genes (p HIP1 was knocked down. HIPPI-P53 interaction was necessary for HIPPI mediated up-regulation of Caspase1 gene. Finally, we analyzed published microarray data obtained with post mortem brains of Huntington's disease (HD patients to investigate the possible involvement of HIPPI in HD pathogenesis. We observed that along with the transcription factors like CREB, P300, SREBP1, Sp1 etc. which are already known to be involved in HD, HIPPI binding site was also significantly over-represented in the upstream sequences of genes altered in HD. Conclusions Taken together, the results suggest that HIPPI could act as an important transcription regulator in cell regulating a vast array of genes, particularly transcription factors and at least, in part, play a

Alternate bearing in citrus: changes in the expression of flowering control genes and in global gene expression in ON- versus OFF-crop trees.

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Shalom, Liron; Samuels, Sivan; Zur, Naftali; Shlizerman, Lyudmila; Zemach, Hanita; Weissberg, Mira; Ophir, Ron; Blumwald, Eduardo; Sadka, Avi

2012-01-01

Alternate bearing (AB) is the process in fruit trees by which cycles of heavy yield (ON crop) one year are followed by a light yield (OFF crop) the next. Heavy yield usually reduces flowering intensity the following year. Despite its agricultural importance, how the developing crop influences the following year's return bloom and yield is not fully understood. It might be assumed that an 'AB signal' is generated in the fruit, or in another organ that senses fruit presence, and moves into the bud to determine its fate-flowering or vegetative growth. The bud then responds to fruit presence by altering regulatory and metabolic pathways. Determining these pathways, and when they are altered, might indicate the nature of this putative AB signal. We studied bud morphology, the expression of flowering control genes, and global gene expression in ON- and OFF-crop buds. In May, shortly after flowering and fruit set, OFF-crop buds were already significantly longer than ON-crop buds. The number of differentially expressed genes was higher in May than at the other tested time points. Processes differentially expressed between ON- and OFF-crop trees included key metabolic and regulatory pathways, such as photosynthesis and secondary metabolism. The expression of genes of trehalose metabolism and flavonoid metabolism was validated by nCounter technology, and the latter was confirmed by metabolomic analysis. Among genes induced in OFF-crop trees was one homologous to SQUAMOSA PROMOTER BINDING-LIKE (SPL), which controls juvenile-to-adult and annual phase transitions, regulated by miR156. The expression pattern of SPL-like, miR156 and other flowering control genes suggested that fruit load affects bud fate, and therefore development and metabolism, a relatively long time before the flowering induction period. Results shed light on some of the metabolic and regulatory processes that are altered in ON and OFF buds.

Computational prediction and experimental validation of Ciona intestinalis microRNA genes

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Pasquinelli Amy E

2007-11-01

Full Text Available Abstract Background This study reports the first collection of validated microRNA genes in the sea squirt, Ciona intestinalis. MicroRNAs are processed from hairpin precursors to ~22 nucleotide RNAs that base pair to target mRNAs and inhibit expression. As a member of the subphylum Urochordata (Tunicata whose larval form has a notochord, the sea squirt is situated at the emergence of vertebrates, and therefore may provide information about the evolution of molecular regulators of early development. Results In this study, computational methods were used to predict 14 microRNA gene families in Ciona intestinalis. The microRNA prediction algorithm utilizes configurable microRNA sequence conservation and stem-loop specificity parameters, grouping by miRNA family, and phylogenetic conservation to the related species, Ciona savignyi. The expression for 8, out of 9 attempted, of the putative microRNAs in the adult tissue of Ciona intestinalis was validated by Northern blot analyses. Additionally, a target prediction algorithm was implemented, which identified a high confidence list of 240 potential target genes. Over half of the predicted targets can be grouped into the gene ontology categories of metabolism, transport, regulation of transcription, and cell signaling. Conclusion The computational techniques implemented in this study can be applied to other organisms and serve to increase the understanding of the origins of non-coding RNAs, embryological and cellular developmental pathways, and the mechanisms for microRNA-controlled gene regulatory networks.

Combined protein construct and synthetic gene engineering for heterologous protein expression and crystallization using Gene Composer

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Walchli John

2009-04-01

Full Text Available Abstract Background With the goal of improving yield and success rates of heterologous protein production for structural studies we have developed the database and algorithm software package Gene Composer. This freely available electronic tool facilitates the information-rich design of protein constructs and their engineered synthetic gene sequences, as detailed in the accompanying manuscript. Results In this report, we compare heterologous protein expression levels from native sequences to that of codon engineered synthetic gene constructs designed by Gene Composer. A test set of proteins including a human kinase (P38α, viral polymerase (HCV NS5B, and bacterial structural protein (FtsZ were expressed in both E. coli and a cell-free wheat germ translation system. We also compare the protein expression levels in E. coli for a set of 11 different proteins with greatly varied G:C content and codon bias. Conclusion The results consistently demonstrate that protein yields from codon engineered Gene Composer designs are as good as or better than those achieved from the synonymous native genes. Moreover, structure guided N- and C-terminal deletion constructs designed with the aid of Gene Composer can lead to greater success in gene to structure work as exemplified by the X-ray crystallographic structure determination of FtsZ from Bacillus subtilis. These results validate the Gene Composer algorithms, and suggest that using a combination of synthetic gene and protein construct engineering tools can improve the economics of gene to structure research.

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

OpenAIRE

Arun, Alok; Bauml?, V?ronique; Amelot, Ga?l; 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 ident...

Identification of a Common Different Gene Expression Signature in Ischemic Cardiomyopathy

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Yana Li

2018-01-01

Full Text Available The molecular mechanisms underlying the development of ischemic cardiomyopathy (ICM remain poorly understood. Gene expression profiling is helpful to discover the molecular changes taking place in ICM. The aim of this study was to identify the genes that are significantly changed during the development of heart failure caused by ICM. The differentially expressed genes (DEGs were identified from 162 control samples and 227 ICM patients. PANTHER was used to perform gene ontology (GO, and Reactome for pathway enrichment analysis. A protein–protein interaction network was established using STRING and Cytoscape. A further validation was performed by real-time polymerase chain reaction (RT-PCR. A total of 255 common DEGs was found. Gene ontology, pathway enrichment, and protein–protein interaction analysis showed that nucleic acid-binding proteins, enzymes, and transcription factors accounted for a great part of the DEGs, while immune system signaling and cytokine signaling displayed the most significant changes. Furthermore, seven hub genes and nine transcription factors were identified. Interestingly, the top five upregulated DEGs were located on chromosome Y, and four of the top five downregulated DEGs were involved in immune and inflammation signaling. Further, the top DEGs were validated by RT-PCR in human samples. Our study explored the possible molecular mechanisms of heart failure caused by ischemic heart disease.

Evaluation of Reference Genes to Analyze Gene Expression in Silverside Odontesthes humensis Under Different Environmental Conditions

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Tony L. R. Silveira

2018-03-01

Full Text Available Some mammalian reference genes, which are widely used to normalize the qRT-PCR, could not be used for this purpose due to its high expression variation. The normalization with false reference genes leads to misinterpretation of results. The silversides (Odontesthes spp. has been used as models for evolutionary, osmoregulatory and environmental pollution studies but, up to now, there are no studies about reference genes in any Odontesthes species. Furthermore, many studies on silversides have used reference genes without previous validations. Thus, present study aimed to was to clone and sequence potential reference genes, thereby identifying the best ones in Odontesthes humensis considering different tissues, ages and conditions. For this purpose, animals belonging to three ages (adults, juveniles, and immature were exposed to control, Roundup®, and seawater treatments for 24 h. Blood samples were subjected to flow-cytometry and other collected tissues to RNA extraction; cDNA synthesis; molecular cloning; DNA sequencing; and qRT-PCR. The candidate genes tested included 18s, actb, ef1a, eif3g, gapdh, h3a, atp1a, and tuba. Gene expression results were analyzed using five algorithms that ranked the candidate genes. The flow-cytometry data showed that the environmental challenges could trigger a systemic response in the treated fish. Even during this systemic physiological disorder, the consensus analysis of gene expression revealed h3a to be the most stable gene expression when only the treatments were considered. On the other hand, tuba was the least stable gene in the control and gapdh was the least stable in both Roundup® and seawater groups. In conclusion, the consensus analyses of different tissues, ages, and treatments groups revealed that h3a is the most stable gene whereas gapdh and tuba are the least stable genes, even being considered two constitutive genes.

Distinct lithium-induced gene expression effects in lymphoblastoid cell lines from patients with bipolar disorder.

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Fries, Gabriel R; Colpo, Gabriela D; Monroy-Jaramillo, Nancy; Zhao, Junfei; Zhao, Zhongming; Arnold, Jodi G; Bowden, Charles L; Walss-Bass, Consuelo

2017-11-01

Lithium is the most commonly prescribed medication for the treatment of bipolar disorder (BD), yet the mechanisms underlying its beneficial effects are still unclear. We aimed to compare the effects of lithium treatment in lymphoblastoid cell lines (LCLs) from BD patients and controls. LCLs were generated from sixty-two BD patients (based on DSM-IV) and seventeen healthy controls matched for age, sex, and ethnicity. Patients were recruited from outpatient clinics from February 2012 to October 2014. LCLs were treated with 1mM lithium for 7 days followed by microarray gene expression assay and validation by real-time quantitative PCR. Baseline differences between groups, as well as differences between vehicle- and lithium-treated cells within each group were analyzed. The biological significance of differentially expressed genes was examined by pathway enrichment analysis. No significant differences in baseline gene expression (adjusted p-value < 0.05) were detected between groups. Lithium treatment of LCLs from controls did not lead to any significant differences. However, lithium altered the expression of 236 genes in LCLs from patients; those genes were enriched for signaling pathways related to apoptosis. Among those genes, the alterations in the expression of PIK3CG, SERP1 and UPP1 were validated by real-time PCR. A significant correlation was also found between circadian functioning and CEBPG and FGF2 expression levels. In summary, our results suggest that lithium treatment induces expression changes in genes associated with the apoptosis pathway in BD LCLs. The more pronounced effects of lithium in patients compared to controls suggest a disease-specific effect of this drug. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Personality and gene expression: Do individual differences exist in the leukocyte transcriptome?

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Vedhara, Kavita; Gill, Sana; Eldesouky, Lameese; Campbell, Bruce K; Arevalo, Jesusa M G; Ma, Jeffrey; Cole, Steven W

2015-02-01

The temporal and situational stability of personality has led generations of researchers to hypothesize that personality may have enduring effects on health, but the biological mechanisms of such relationships remain poorly understood. In the present study, we utilized a functional genomics approach to examine the relationship between the 5 major dimensions of personality and patterns of gene expression as predicted by 'behavioural immune response' theory. We specifically focussed on two sets of genes previously linked to stress, threat, and adverse socio-environmental conditions: pro-inflammatory genes and genes involved in Type I interferon and antibody responses. An opportunity sample of 121 healthy individuals was recruited (86 females; mean age 24 years). Individuals completed a validated measure of personality; questions relating to current health behaviours; and provided a 5ml sample of peripheral blood for gene expression analysis. Extraversion was associated with increased expression of pro-inflammatory genes and Conscientiousness was associated with reduced expression of pro-inflammatory genes. Both associations were independent of health behaviours, negative affect, and leukocyte subset distributions. Antiviral and antibody-related gene expression was not associated with any personality dimension. The present data shed new light on the long-observed epidemiological associations between personality, physical health, and human longevity. Further research is required to elucidate the biological mechanisms underlying these associations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Gene expression prediction by soft integration and the elastic net-best performance of the DREAM3 gene expression challenge.

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Mika Gustafsson

Full Text Available BACKGROUND: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression values, and here we present the algorithm with best performance. METHODOLOGY/PRINCIPAL FINDINGS: We develop an algorithm by exploring various regression schemes with different model selection procedures. It turns out that the most effective scheme is based on least squares, with a penalty term of a recently developed form called the "elastic net". Key components in the algorithm are the integration of expression data from other experimental conditions than those presented for the challenge and the utilization of transcription factor binding data for guiding the inference process towards known interactions. Of importance is also a cross-validation procedure where each form of external data is used only to the extent it increases the expected performance. CONCLUSIONS/SIGNIFICANCE: Our algorithm proves both the possibility to extract information from large-scale expression data concerning prediction of gene levels, as well as the benefits of integrating different data sources for improving the inference. We believe the former is an important message to those still hesitating on the possibilities for computational approaches, while the latter is part of an important way forward for the future development of the field of computational systems biology.

Detection of growth hormone doping by gene expression profiling of peripheral blood.

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Mitchell, Christopher J; Nelson, Anne E; Cowley, Mark J; Kaplan, Warren; Stone, Glenn; Sutton, Selina K; Lau, Amie; Lee, Carol M Y; Ho, Ken K Y

2009-12-01

GH abuse is a significant problem in many sports, and there is currently no robust test that allows detection of doping beyond a short window after administration. Our objective was to evaluate gene expression profiling in peripheral blood leukocytes in-vivo as a test for GH doping in humans. Seven men and thirteen women were administered GH, 2 mg/d sc for 8 wk. Blood was collected at baseline and at 8 wk. RNA was extracted from the white cell fraction. Microarray analysis was undertaken using Agilent 44K G4112F arrays using a two-color design. Quantitative RT-PCR using TaqMan gene expression assays was performed for validation of selected differentially expressed genes. GH induced an approximately 2-fold increase in circulating IGF-I that was maintained throughout the 8 wk of the study. GH induced significant changes in gene expression with 353 in women and 41 in men detected with a false discovery rate of less than 5%. None of the differentially expressed genes were common between men and women. The maximal changes were a doubling for up-regulated or halving for down-regulated genes, similar in magnitude to the variation between individuals. Quantitative RT-PCR for seven target genes showed good concordance between microarray and quantitative PCR data in women but not in men. Gene expression analysis of peripheral blood leukocytes is unlikely to be a viable approach for the detection of GH doping.

Amygdala nuclei critical for emotional learning exhibit unique gene expression patterns.

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Partin, Alexander C; Hosek, Matthew P; Luong, Jonathan A; Lella, Srihari K; Sharma, Sachein A R; Ploski, Jonathan E

2013-09-01

The amygdala is a heterogeneous, medial temporal lobe structure that has been implicated in the formation, expression and extinction of emotional memories. This structure is composed of numerous nuclei that vary in cytoarchitectonics and neural connections. In particular the lateral nucleus of the amygdala (LA), central nucleus of the amygdala (CeA), and the basal (B) nucleus contribute an essential role to emotional learning. However, to date it is still unclear to what extent these nuclei differ at the molecular level. Therefore we have performed whole genome gene expression analysis on these nuclei to gain a better understanding of the molecular differences and similarities among these nuclei. Specifically the LA, CeA and B nuclei were laser microdissected from the rat brain, and total RNA was isolated from these nuclei and subjected to RNA amplification. Amplified RNA was analyzed by whole genome microarray analysis which revealed that 129 genes are differentially expressed among these nuclei. Notably gene expression patterns differed between the CeA nucleus and the LA and B nuclei. However gene expression differences were not considerably different between the LA and B nuclei. Secondary confirmation of numerous genes was performed by in situ hybridization to validate the microarray findings, which also revealed that for many genes, expression differences among these nuclei were consistent with the embryological origins of these nuclei. Knowing the stable gene expression differences among these nuclei will provide novel avenues of investigation into how these nuclei contribute to emotional arousal and emotional learning, and potentially offer new genetic targets to manipulate emotional learning and memory. Copyright © 2013 Elsevier Inc. All rights reserved.

Age-Specific Gene Expression Profiles of Rhesus Monkey Ovaries Detected by Microarray Analysis

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Hengxi Wei

2015-01-01

Full Text Available The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated and 84 (downregulated genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates.

Gene expression inference with deep learning.

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

2016-06-15

Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Differential gene expression related to Nora virus infection of Drosophila melanogaster.

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Cordes, Ethan J; Licking-Murray, Kellie D; Carlson, Kimberly A

2013-08-01

Nora virus is a recently discovered RNA picorna-like virus that produces a persistent infection in Drosophila melanogaster, but the antiviral pathway or change in gene expression is unknown. We performed cDNA microarray analysis comparing the gene expression profiles of Nora virus infected and uninfected wild-type D. melanogaster. This analysis yielded 58 genes exhibiting a 1.5-fold change or greater and p-value less than 0.01. Of these genes, 46 were up-regulated and 12 down-regulated in response to infection. To validate the microarray results, qRT-PCR was performed with probes for Chorion protein 16 and Troponin C isoform 4, which show good correspondence with cDNA microarray results. Differential regulation of genes associated with Toll and immune-deficient pathways, cytoskeletal development, Janus Kinase-Signal Transducer and Activator of Transcription interactions, and a potential gut-specific innate immune response were found. This genome-wide expression profile of Nora virus infection of D. melanogaster can pinpoint genes of interest for further investigation of antiviral pathways employed, genetic mechanisms, sites of replication, viral persistence, and developmental effects. Copyright © 2013. Published by Elsevier B.V.

Hierarchical clustering of gene expression patterns in the Eomes + lineage of excitatory neurons during early neocortical development

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Cameron David A

2012-08-01

Full Text Available Abstract Background Cortical neurons display dynamic patterns of gene expression during the coincident processes of differentiation and migration through the developing cerebrum. To identify genes selectively expressed by the Eomes + (Tbr2 lineage of excitatory cortical neurons, GFP-expressing cells from Tg(Eomes::eGFP Gsat embryos were isolated to > 99% purity and profiled. Results We report the identification, validation and spatial grouping of genes selectively expressed within the Eomes + cortical excitatory neuron lineage during early cortical development. In these neurons 475 genes were expressed ≥ 3-fold, and 534 genes ≤ 3-fold, compared to the reference population of neuronal precursors. Of the up-regulated genes, 328 were represented at the Genepaint in situ hybridization database and 317 (97% were validated as having spatial expression patterns consistent with the lineage of differentiating excitatory neurons. A novel approach for quantifying in situ hybridization patterns (QISP across the cerebral wall was developed that allowed the hierarchical clustering of genes into putative co-regulated groups. Forty four candidate genes were identified that show spatial expression with Intermediate Precursor Cells, 49 candidate genes show spatial expression with Multipolar Neurons, while the remaining 224 genes achieved peak expression in the developing cortical plate. Conclusions This analysis of differentiating excitatory neurons revealed the expression patterns of 37 transcription factors, many chemotropic signaling molecules (including the Semaphorin, Netrin and Slit signaling pathways, and unexpected evidence for non-canonical neurotransmitter signaling and changes in mechanisms of glucose metabolism. Over half of the 317 identified genes are associated with neuronal disease making these findings a valuable resource for studies of neurological development and disease.

A robust approach based on Weibull distribution for clustering gene expression data

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Gong Binsheng

2011-05-01

Full Text Available Abstract Background Clustering is a widely used technique for analysis of gene expression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the gene expression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering gene expression data, in which the gene expressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete gene expression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters

Elevated expression of prostate cancer-associated genes is linked to down-regulation of microRNAs

International Nuclear Information System (INIS)

Erdmann, Kati; Kaulke, Knut; Thomae, Cathleen; Huebner, Doreen; Sergon, Mildred; Froehner, Michael; Wirth, Manfred P; Fuessel, Susanne

2014-01-01

Recent evidence suggests that the prostate cancer (PCa)-specific up-regulation of certain genes such as AMACR, EZH2, PSGR, PSMA and TRPM8 could be associated with an aberrant expression of non-coding microRNAs (miRNA). In silico analyses were used to search for miRNAs being putative regulators of PCa-associated genes. The expression of nine selected miRNAs (hsa-miR-101, -138, -186, -224, -26a, -26b, -374a, -410, -660) as well as of the aforementioned PCa-associated genes was analyzed by quantitative PCR using 50 malignant (Tu) and matched non-malignant (Tf) tissue samples from prostatectomy specimens as well as 30 samples from patients with benign prostatic hyperplasia (BPH). Then, correlations between paired miRNA and target gene expression levels were analyzed. Furthermore, the effect of exogenously administered miR-26a on selected target genes was determined by quantitative PCR and Western Blot in various PCa cell lines. A luciferase reporter assay was used for target validation. The expression of all selected miRNAs was decreased in PCa tissue samples compared to either control group (Tu vs Tf: -1.35 to -5.61-fold; Tu vs BPH: -1.17 to -5.49-fold). The down-regulation of most miRNAs inversely correlated with an up-regulation of their putative target genes with Spearman correlation coefficients ranging from -0.107 to -0.551. MiR-186 showed a significantly diminished expression in patients with non-organ confined PCa and initial metastases. Furthermore, over-expression of miR-26a reduced the mRNA and protein expression of its potential target gene AMACR in vitro. Using the luciferase reporter assay AMACR was validated as new target for miR-26a. The findings of this study indicate that the expression of specific miRNAs is decreased in PCa and inversely correlates with the up-regulation of their putative target genes. Consequently, miRNAs could contribute to oncogenesis and progression of PCa via an altered miRNA-target gene-interaction

Tumour gene expression predicts response to cetuximab in patients with KRAS wild-type metastatic colorectal cancer.

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Baker, J B; Dutta, D; Watson, D; Maddala, T; Munneke, B M; Shak, S; Rowinsky, E K; Xu, L-A; Harbison, C T; Clark, E A; Mauro, D J; Khambata-Ford, S

2011-02-01

Although it is accepted that metastatic colorectal cancers (mCRCs) that carry activating mutations in KRAS are unresponsive to anti-epidermal growth factor receptor (EGFR) monoclonal antibodies, a significant fraction of KRAS wild-type (wt) mCRCs are also unresponsive to anti-EGFR therapy. Genes encoding EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are promising gene expression-based markers but have not been incorporated into a test to dichotomise KRAS wt mCRC patients with respect to sensitivity to anti-EGFR treatment. We used RT-PCR to test 110 candidate gene expression markers in primary tumours from 144 KRAS wt mCRC patients who received monotherapy with the anti-EGFR antibody cetuximab. Results were correlated with multiple clinical endpoints: disease control, objective response, and progression-free survival (PFS). Expression of many of the tested candidate genes, including EREG and AREG, strongly associate with all clinical endpoints. Using multivariate analysis with two-layer five-fold cross-validation, we constructed a four-gene predictive classifier. Strikingly, patients below the classifier cutpoint had PFS and disease control rates similar to those of patients with KRAS mutant mCRC. Gene expression appears to identify KRAS wt mCRC patients who receive little benefit from cetuximab. It will be important to test this model in an independent validation study.

Selection of Reliable Reference Genes for Gene Expression Studies on Rhododendron molle G. Don.

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Xiao, Zheng; Sun, Xiaobo; Liu, Xiaoqing; Li, Chang; He, Lisi; Chen, Shangping; Su, Jiale

2016-01-01

The quantitative real-time polymerase chain reaction (qRT-PCR) approach has become a widely used method to analyze expression patterns of target genes. The selection of an optimal reference gene is a prerequisite for the accurate normalization of gene expression in qRT-PCR. The present study constitutes the first systematic evaluation of potential reference genes in Rhododendron molle G. Don. Eleven candidate reference genes in different tissues and flowers at different developmental stages of R. molle were assessed using the following three software packages: GeNorm, NormFinder, and BestKeeper. The results showed that EF1- α (elongation factor 1-alpha), 18S (18s ribosomal RNA), and RPL3 (ribosomal protein L3) were the most stable reference genes in developing rhododendron flowers and, thus, in all of the tested samples, while tublin ( TUB ) was the least stable. ACT5 (actin), RPL3 , 18S , and EF1- α were found to be the top four choices for different tissues, whereas TUB was not found to favor qRT-PCR normalization in these tissues. Three stable reference genes are recommended for the normalization of qRT-PCR data in R. molle . Furthermore, the expression profiles of RmPSY (phytoene synthase) and RmPDS (phytoene dehydrogenase) were assessed using EF1- α, 18S , ACT5 , RPL3 , and their combination as internals. Similar trends were found, but these trends varied when the least stable reference gene TUB was used. The results further prove that it is necessary to validate the stability of reference genes prior to their use for normalization under different experimental conditions. This study provides useful information for reliable qRT-PCR data normalization in gene studies of R. molle .

Selection of Reliable Reference Genes for Gene Expression Studies on Rhododendron molle G. Don

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Zheng Xiao

2016-10-01

Full Text Available The quantitative real-time polymerase chain reaction (qRT-PCR approach has become a widely used method to analyze expression patterns of target genes. The selection of an optimal reference gene is a prerequisite for the accurate normalization of gene expression in qRT-PCR. The present study constitutes the first systematic evaluation of potential reference genes in Rhododendron molle G. Don. Eleven candidate reference genes in different tissues and flowers at different developmental stages of R. molle were assessed using the following three software packages: GeNorm, NormFinder and BestKeeper. The results showed that EF1-α (elongation factor 1-alpha, 18S (18s ribosomal RNA and RPL3 (ribosomal protein L3 were the most stable reference genes in developing rhododendron flowers and, thus, in all of the tested samples, while tublin (TUB was the least stable. ACT5 (actin, RPL3, 18S and EF1-α were found to be the top four choices for different tissues, whereas TUB was not found to favor qRT-PCR normalization in these tissues. Three stable reference genes are recommended for the normalization of qRT-PCR data in R. molle. Furthermore, the expression profiles of RmPSY (phytoene synthase and RmPDS (phytoene dehydrogenase were assessed using EF1-α, 18S, ACT5, and RPL3 and their combination as internals. Similar trends were found, but these trends varied when the least stable reference gene TUB was used. The results further prove that it is necessary to validate the stability of reference genes prior to their use for normalization under different experimental conditions. This study provides useful information for reliable qRT-PCR data normalization in gene studies of R. molle.

Integrating mean and variance heterogeneities to identify differentially expressed genes.

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Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

2016-12-06

In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

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

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

2008-01-01

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

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans.

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Gottlieb, Assaf; Daneshjou, Roxana; DeGorter, Marianne; Bourgeois, Stephane; Svensson, Peter J; Wadelius, Mia; Deloukas, Panos; Montgomery, Stephen B; Altman, Russ B

2017-11-24

Genome-wide association studies are useful for discovering genotype-phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into "gene level" effects. Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression-on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort.

cis sequence effects on gene expression

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Jacobs Kevin

2007-08-01

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

Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

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Guo Zheng

2006-01-01

Full Text Available Abstract Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network to address the underlying regulations of genes that can span any unit(s of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex

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

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Paules Richard S

2007-11-01

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

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

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

2014-01-01

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

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

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

2014-01-01

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

Sex-specific associations between particulate matter exposure and gene expression in independent discovery and validation cohorts of middle-aged men and women

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Vrijens, Karen; Winckelmans, Ellen; Tsamou, Maria

2017-01-01

Background: Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases. Objectives: Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population. Methods: Microarray analyses were performed in 98...... healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM10 in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women...

Predator-induced defences in Daphnia pulex: Selection and evaluation of internal reference genes for gene expression studies with real-time PCR

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Gilbert Don

2010-06-01

Full Text Available Abstract Background The planktonic microcrustacean Daphnia pulex is among the best-studied animals in ecological, toxicological and evolutionary research. One aspect that has sustained interest in the study system is the ability of D. pulex to develop inducible defence structures when exposed to predators, such as the phantom midge larvae Chaoborus. The available draft genome sequence for D. pulex is accelerating research to identify genes that confer plastic phenotypes that are regularly cued by environmental stimuli. Yet for quantifying gene expression levels, no experimentally validated set of internal control genes exists for the accurate normalization of qRT-PCR data. Results In this study, we tested six candidate reference genes for normalizing transcription levels of D. pulex genes; alpha tubulin (aTub, glyceraldehyde-3-phosphate dehydrogenase (GAPDH, TATA box binding protein (Tbp syntaxin 16 (Stx16, X-box binding protein 1 (Xbp1 and CAPON, a protein associated with the neuronal nitric oxide synthase, were selected on the basis of an earlier study and from microarray studies. One additional gene, a matrix metalloproteinase (MMP, was tested to validate its transcriptional response to Chaoborus, which was earlier observed in a microarray study. The transcription profiles of these seven genes were assessed by qRT-PCR from RNA of juvenile D. pulex that showed induced defences in comparison to untreated control animals. We tested the individual suitability of genes for expression normalization using the programs geNorm, NormFinder and BestKeeper. Intriguingly, Xbp1, Tbp, CAPON and Stx16 were selected as ideal reference genes. Analyses on the relative expression level using the software REST showed that both classical housekeeping candidate genes (aTub and GAPDH were significantly downregulated, whereas the MMP gene was shown to be significantly upregulated, as predicted. aTub is a particularly ill suited reference gene because five copies are

Evaluation of candidate reference genes for gene expression normalization in Brassica juncea using real time quantitative RT-PCR.

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Ruby Chandna

Full Text Available The real time quantitative reverse transcription PCR (qRT-PCR is becoming increasingly important to gain insight into function of genes. Given the increased sensitivity, ease and reproducibility of qRT-PCR, the requirement of suitable reference genes for normalization has become important and stringent. It is now known that the expression of internal control genes in living organism vary considerably during developmental stages and under different experimental conditions. For economically important Brassica crops, only a couple of reference genes are reported till date. In this study, expression stability of 12 candidate reference genes including ACT2, ELFA, GAPDH, TUA, UBQ9 (traditional housekeeping genes, ACP, CAC, SNF, TIPS-41, TMD, TSB and ZNF (new candidate reference genes, in a diverse set of 49 tissue samples representing different developmental stages, stress and hormone treated conditions and cultivars of Brassica juncea has been validated. For the normalization of vegetative stages the ELFA, ACT2, CAC and TIPS-41 combination would be appropriate whereas TIPS-41 along with CAC would be suitable for normalization of reproductive stages. A combination of GAPDH, TUA, TIPS-41 and CAC were identified as the most suitable reference genes for total developmental stages. In various stress and hormone treated samples, UBQ9 and TIPS-41 had the most stable expression. Across five cultivars of B. juncea, the expression of CAC and TIPS-41 did not vary significantly and were identified as the most stably expressed reference genes. This study provides comprehensive information that the new reference genes selected herein performed better than the traditional housekeeping genes. The selection of most suitable reference genes depends on the experimental conditions, and is tissue and cultivar-specific. Further, to attain accuracy in the results more than one reference genes are necessary for normalization.

Modulation of gene expression made easy

DEFF Research Database (Denmark)

Solem, Christian; Jensen, Peter Ruhdal

2002-01-01

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

Gene expression patterns in peripheral blood correlate with the extent of coronary artery disease.

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Peter R Sinnaeve

Full Text Available Systemic and local inflammation plays a prominent role in the pathogenesis of atherosclerotic coronary artery disease, but the relationship of whole blood gene expression changes with coronary disease remains unclear. We have investigated whether gene expression patterns in peripheral blood correlate with the severity of coronary disease and whether these patterns correlate with the extent of atherosclerosis in the vascular wall. Patients were selected according to their coronary artery disease index (CADi, a validated angiographical measure of the extent of coronary atherosclerosis that correlates with outcome. RNA was extracted from blood of 120 patients with at least a stenosis greater than 50% (CADi > or = 23 and from 121 controls without evidence of coronary stenosis (CADi = 0. 160 individual genes were found to correlate with CADi (rho > 0.2, P<0.003. Prominent differential expression was observed especially in genes involved in cell growth, apoptosis and inflammation. Using these 160 genes, a partial least squares multivariate regression model resulted in a highly predictive model (r(2 = 0.776, P<0.0001. The expression pattern of these 160 genes in aortic tissue also predicted the severity of atherosclerosis in human aortas, showing that peripheral blood gene expression associated with coronary atherosclerosis mirrors gene expression changes in atherosclerotic arteries. In conclusion, the simultaneous expression pattern of 160 genes in whole blood correlates with the severity of coronary artery disease and mirrors expression changes in the atherosclerotic vascular wall.

Microarray meta-analysis to explore abiotic stress-specific gene expression patterns in Arabidopsis.

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Shen, Po-Chih; Hour, Ai-Ling; Liu, Li-Yu Daisy

2017-12-01

Abiotic stresses are the major limiting factors that affect plant growth, development, yield and final quality. Deciphering the underlying mechanisms of plants' adaptations to stresses using few datasets might overlook the different aspects of stress tolerance in plants, which might be simultaneously and consequently operated in the system. Fortunately, the accumulated microarray expression data offer an opportunity to infer abiotic stress-specific gene expression patterns through meta-analysis. In this study, we propose to combine microarray gene expression data under control, cold, drought, heat, and salt conditions and determined modules (gene sets) of genes highly associated with each other according to the observed expression data. By analyzing the expression variations of the Eigen genes from different conditions, we had identified two, three, and five gene modules as cold-, heat-, and salt-specific modules, respectively. Most of the cold- or heat-specific modules were differentially expressed to a particular degree in shoot samples, while most of the salt-specific modules were differentially expressed to a particular degree in root samples. A gene ontology (GO) analysis on the stress-specific modules suggested that the gene modules exclusively enriched stress-related GO terms and that different genes under the same GO terms may be alternatively disturbed in different conditions. The gene regulatory events for two genes, DREB1A and DEAR1, in the cold-specific gene module had also been validated, as evidenced through the literature search. Our protocols study the specificity of the gene modules that were specifically activated under a particular type of abiotic stress. The biplot can also assist to visualize the stress-specific gene modules. In conclusion, our approach has the potential to further elucidate mechanisms in plants and beneficial for future experiments design under different abiotic stresses.

Digital Gene Expression Analysis Based on De Novo Transcriptome Assembly Reveals New Genes Associated with Floral Organ Differentiation of the Orchid Plant Cymbidium ensifolium.

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Fengxi Yang

Full Text Available Cymbidium ensifolium belongs to the genus Cymbidium of the orchid family. Owing to its spectacular flower morphology, C. ensifolium has considerable ecological and cultural value. However, limited genetic data is available for this non-model plant, and the molecular mechanism underlying floral organ identity is still poorly understood. In this study, we characterize the floral transcriptome of C. ensifolium and present, for the first time, extensive sequence and transcript abundance data of individual floral organs. After sequencing, over 10 Gb clean sequence data were generated and assembled into 111,892 unigenes with an average length of 932.03 base pairs, including 1,227 clusters and 110,665 singletons. Assembled sequences were annotated with gene descriptions, gene ontology, clusters of orthologous group terms, the Kyoto Encyclopedia of Genes and Genomes, and the plant transcription factor database. From these annotations, 131 flowering-associated unigenes, 61 CONSTANS-LIKE (COL unigenes and 90 floral homeotic genes were identified. In addition, four digital gene expression libraries were constructed for the sepal, petal, labellum and gynostemium, and 1,058 genes corresponding to individual floral organ development were identified. Among them, eight MADS-box genes were further investigated by full-length cDNA sequence analysis and expression validation, which revealed two APETALA1/AGL9-like MADS-box genes preferentially expressed in the sepal and petal, two AGAMOUS-like genes particularly restricted to the gynostemium, and four DEF-like genes distinctively expressed in different floral organs. The spatial expression of these genes varied distinctly in different floral mutant corresponding to different floral morphogenesis, which validated the specialized roles of them in floral patterning and further supported the effectiveness of our in silico analysis. This dataset generated in our study provides new insights into the molecular mechanisms

Gene expression profiling of liver cancer stem cells by RNA-sequencing.

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David W Y Ho

Full Text Available BACKGROUND: Accumulating evidence supports that tumor growth and cancer relapse are driven by cancer stem cells. Our previous work has demonstrated the existence of CD90(+ liver cancer stem cells (CSCs in hepatocellular carcinoma (HCC. Nevertheless, the characteristics of these cells are still poorly understood. In this study, we employed a more sensitive RNA-sequencing (RNA-Seq to compare the gene expression profiling of CD90(+ cells sorted from tumor (CD90(+CSCs with parallel non-tumorous liver tissues (CD90(+NTSCs and elucidate the roles of putative target genes in hepatocarcinogenesis. METHODOLOGY/PRINCIPAL FINDINGS: CD90(+ cells were sorted respectively from tumor and adjacent non-tumorous human liver tissues using fluorescence-activated cell sorting. The amplified RNAs of CD90(+ cells from 3 HCC patients were subjected to RNA-Seq analysis. A differential gene expression profile was established between CD90(+CSCs and CD90(+NTSCs, and validated by quantitative real-time PCR (qRT-PCR on the same set of amplified RNAs, and further confirmed in an independent cohort of 12 HCC patients. Five hundred genes were differentially expressed (119 up-regulated and 381 down-regulated genes between CD90(+CSCs and CD90(+NTSCs. Gene ontology analysis indicated that the over-expressed genes in CD90(+CSCs were associated with inflammation, drug resistance and lipid metabolism. Among the differentially expressed genes, glypican-3 (GPC3, a member of glypican family, was markedly elevated in CD90(+CSCs compared to CD90(+NTSCs. Immunohistochemistry demonstrated that GPC3 was highly expressed in forty-two human liver tumor tissues but absent in adjacent non-tumorous liver tissues. Flow cytometry indicated that GPC3 was highly expressed in liver CD90(+CSCs and mature cancer cells in liver cancer cell lines and human liver tumor tissues. Furthermore, GPC3 expression was positively correlated with the number of CD90(+CSCs in liver tumor tissues. CONCLUSIONS

Gene Expression Profiling of Liver Cancer Stem Cells by RNA-Sequencing

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Lam, Chi Tat; Ng, Michael N. P.; Yu, Wan Ching; Lau, Joyce; Wan, Timothy; Wang, Xiaoqi; Yan, Zhixiang; Liu, Hang; Fan, Sheung Tat

2012-01-01

Background Accumulating evidence supports that tumor growth and cancer relapse are driven by cancer stem cells. Our previous work has demonstrated the existence of CD90+ liver cancer stem cells (CSCs) in hepatocellular carcinoma (HCC). Nevertheless, the characteristics of these cells are still poorly understood. In this study, we employed a more sensitive RNA-sequencing (RNA-Seq) to compare the gene expression profiling of CD90+ cells sorted from tumor (CD90+CSCs) with parallel non-tumorous liver tissues (CD90+NTSCs) and elucidate the roles of putative target genes in hepatocarcinogenesis. Methodology/Principal Findings CD90+ cells were sorted respectively from tumor and adjacent non-tumorous human liver tissues using fluorescence-activated cell sorting. The amplified RNAs of CD90+ cells from 3 HCC patients were subjected to RNA-Seq analysis. A differential gene expression profile was established between CD90+CSCs and CD90+NTSCs, and validated by quantitative real-time PCR (qRT-PCR) on the same set of amplified RNAs, and further confirmed in an independent cohort of 12 HCC patients. Five hundred genes were differentially expressed (119 up-regulated and 381 down-regulated genes) between CD90+CSCs and CD90+NTSCs. Gene ontology analysis indicated that the over-expressed genes in CD90+CSCs were associated with inflammation, drug resistance and lipid metabolism. Among the differentially expressed genes, glypican-3 (GPC3), a member of glypican family, was markedly elevated in CD90+CSCs compared to CD90+NTSCs. Immunohistochemistry demonstrated that GPC3 was highly expressed in forty-two human liver tumor tissues but absent in adjacent non-tumorous liver tissues. Flow cytometry indicated that GPC3 was highly expressed in liver CD90+CSCs and mature cancer cells in liver cancer cell lines and human liver tumor tissues. Furthermore, GPC3 expression was positively correlated with the number of CD90+CSCs in liver tumor tissues. Conclusions/Significance The identified genes

Using gene expression noise to understand gene regulation

NARCIS (Netherlands)

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

2012-01-01

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

Questioned validity of Gene Expression Dysregulated Domains in Down's Syndrome [v1; ref status: indexed, http://f1000r.es/5ky

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Long H. Do

2015-07-01

Full Text Available Recently, in studies examining fibroblasts obtained from the tissues of one set of monozygotic twins (i.e. fetuses derived from the same egg discordant for trisomy 21 (Down syndrome; DS, Letourneau et al., reported the presence of a defined pattern of dysregulation within specific genomic domains they referred to as Gene Expression Dysregulated Domains (GEDDs. GEDDs were described as alternating segments of increased or decreased gene expression affecting all chromosomes. Strikingly, GEDDs in fibroblasts were largely conserved in induced pluripotent cells (iPSCs generated from the twin’s fibroblasts as well as in fibroblasts from the Ts65Dn mouse model of DS. Our recent analysis failed to find GEDDs. We reexamined the human iPSCs RNAseq data from Letourneau et al., and data from this same research group published earlier examining iPSCs from the same monozygotic twins. An independent analysis of RNAseq data from Ts65Dn fibroblasts also failed to confirm presence of GEDDs. Our analysis questions the validity of GEDDs in DS.

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

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

2017-11-01

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

Cigarette smoke modulates expression of human rhinovirus-induced airway epithelial host defense genes.

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David Proud

Full Text Available Human rhinovirus (HRV infections trigger acute exacerbations of chronic obstructive pulmonary disease (COPD and asthma. The human airway epithelial cell is the primary site of HRV infection and responds to infection with altered expression of multiple genes, the products of which could regulate the outcome to infection. Cigarette smoking aggravates asthma symptoms, and is also the predominant risk factor for the development and progression of COPD. We, therefore, examined whether cigarette smoke extract (CSE modulates viral responses by altering HRV-induced epithelial gene expression. Primary cultures of human bronchial epithelial cells were exposed to medium alone, CSE alone, purified HRV-16 alone or to HRV-16+ CSE. After 24 h, supernatants were collected and total cellular RNA was isolated. Gene array analysis was performed to examine mRNA expression. Additional experiments, using real-time RT-PCR, ELISA and/or western blotting, validated altered expression of selected gene products. CSE and HRV-16 each induced groups of genes that were largely independent of each other. When compared to gene expression in response to CSE alone, cells treated with HRV+CSE showed no obvious differences in CSE-induced gene expression. By contrast, compared to gene induction in response to HRV-16 alone, cells exposed to HRV+CSE showed marked suppression of expression of a number of HRV-induced genes associated with various functions, including antiviral defenses, inflammation, viral signaling and airway remodeling. These changes were not associated with altered expression of type I or type III interferons. Thus, CSE alters epithelial responses to HRV infection in a manner that may negatively impact antiviral and host defense outcomes.

Supervised classification of combined copy number and gene expression data

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Riccadonna S.

2007-12-01

Full Text Available In this paper we apply a predictive profiling method to genome copy number aberrations (CNA in combination with gene expression and clinical data to identify molecular patterns of cancer pathophysiology. Predictive models and optimal feature lists for the platforms are developed by a complete validation SVM-based machine learning system. Ranked list of genome CNA sites (assessed by comparative genomic hybridization arrays – aCGH and of differentially expressed genes (assessed by microarray profiling with Affy HG-U133A chips are computed and combined on a breast cancer dataset for the discrimination of Luminal/ ER+ (Lum/ER+ and Basal-like/ER- classes. Different encodings are developed and applied to the CNA data, and predictive variable selection is discussed. We analyze the combination of profiling information between the platforms, also considering the pathophysiological data. A specific subset of patients is identified that has a different response to classification by chromosomal gains and losses and by differentially expressed genes, corroborating the idea that genomic CNA can represent an independent source for tumor classification.

Transcriptome analysis reveals key differentially expressed genes involved in wheat grain development

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Yonglong Yu

2016-04-01

Full Text Available Wheat seed development is an important physiological process of seed maturation and directly affects wheat yield and quality. In this study, we performed dynamic transcriptome microarray analysis of an elite Chinese bread wheat cultivar (Jimai 20 during grain development using the GeneChip Wheat Genome Array. Grain morphology and scanning electron microscope observations showed that the period of 11–15 days post-anthesis (DPA was a key stage for the synthesis and accumulation of seed starch. Genome-wide transcriptional profiling and significance analysis of microarrays revealed that the period from 11 to 15 DPA was more important than the 15–20 DPA stage for the synthesis and accumulation of nutritive reserves. Series test of cluster analysis of differential genes revealed five statistically significant gene expression profiles. Gene ontology annotation and enrichment analysis gave further information about differentially expressed genes, and MapMan analysis revealed expression changes within functional groups during seed development. Metabolic pathway network analysis showed that major and minor metabolic pathways regulate one another to ensure regular seed development and nutritive reserve accumulation. We performed gene co-expression network analysis to identify genes that play vital roles in seed development and identified several key genes involved in important metabolic pathways. The transcriptional expression of eight key genes involved in starch and protein synthesis and stress defense was further validated by qRT-PCR. Our results provide new insight into the molecular mechanisms of wheat seed development and the determinants of yield and quality.

Decomposition of gene expression state space trajectories.

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Jessica C Mar

2009-12-01

Full Text Available Representing and analyzing complex networks remains a roadblock to creating dynamic network models of biological processes and pathways. The study of cell fate transitions can reveal much about the transcriptional regulatory programs that underlie these phenotypic changes and give rise to the coordinated patterns in expression changes that we observe. The application of gene expression state space trajectories to capture cell fate transitions at the genome-wide level is one approach currently used in the literature. In this paper, we analyze the gene expression dataset of Huang et al. (2005 which follows the differentiation of promyelocytes into neutrophil-like cells in the presence of inducers dimethyl sulfoxide and all-trans retinoic acid. Huang et al. (2005 build on the work of Kauffman (2004 who raised the attractor hypothesis, stating that cells exist in an expression landscape and their expression trajectories converge towards attractive sites in this landscape. We propose an alternative interpretation that explains this convergent behavior by recognizing that there are two types of processes participating in these cell fate transitions-core processes that include the specific differentiation pathways of promyelocytes to neutrophils, and transient processes that capture those pathways and responses specific to the inducer. Using functional enrichment analyses, specific biological examples and an analysis of the trajectories and their core and transient components we provide a validation of our hypothesis using the Huang et al. (2005 dataset.

RNA-seq reveals more consistent reference genes for gene expression studies in human non-melanoma skin cancers

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Van L.T. Hoang

2017-08-01

Full Text Available Identification of appropriate reference genes (RGs is critical to accurate data interpretation in quantitative real-time PCR (qPCR experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq to analyse the transcriptome of a panel of non-melanoma skin cancer lesions, identifying genes that are consistently expressed across all samples. Genes encoding ribosomal proteins were amongst the most stable in this dataset. Validation of this RNA-seq data was examined using qPCR to confirm the suitability of a set of highly stable genes for use as qPCR RGs. These genes will provide a valuable resource for the normalisation of qPCR data for the analysis of non-melanoma skin cancer.

Gene Expression Measurement Module (GEMM) - a fully automated, miniaturized instrument for measuring gene expression in space

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Karouia, Fathi; Ricco, Antonio; Pohorille, Andrew; Peyvan, Kianoosh

2012-07-01

The capability to measure gene expression on board spacecrafts opens the doors to a large number of experiments on the influence of space environment on biological systems that will profoundly impact our ability to conduct safe and effective space travel, and might also shed light on terrestrial physiology or biological function and human disease and aging processes. Measurements of gene expression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, determine metabolic basis of microbial pathogenicity and drug resistance, test our ability to sustain and grow in space organisms that can be used for life support and in situ resource utilization during long-duration space exploration, and monitor both the spacecraft environment and crew health. These and other applications hold significant potential for discoveries in space biology, biotechnology and medicine. Accordingly, supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measuring microbial expression of thousands of genes from multiple samples. The instrument will be capable of (1) lysing bacterial cell walls, (2) extracting and purifying RNA released from cells, (3) hybridizing it on a microarray and (4) providing electrochemical readout, all in a microfluidics cartridge. The prototype under development is suitable for deployment on nanosatellite platforms developed by the NASA Small Spacecraft Office. The first target application is to cultivate and measure gene expression of the photosynthetic bacterium Synechococcus elongatus, i.e. a cyanobacterium known to exhibit remarkable metabolic diversity and resilience to adverse conditions

Low pH induces co-ordinate regulation of gene expression in oesophageal cells.

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Duggan, Shane P; Gallagher, William M; Fox, Edward J P; Abdel-Latif, Mohammed M; Reynolds, John V; Kelleher, Dermot

2006-02-01

The development of gastro-oesophageal reflux disease (GORD) is known to be a causative risk factor in the evolution of adenocarcinoma of the oesophagus. The major component of this reflux is gastric acid. However, the impact of low pH on gene expression has not been extensively studied in oesophageal cells. This study utilizes a transcriptomic and bioinformatic approach to assess regulation of gene expression in response to low pH. In more detail, oesophageal adenocarcinoma cell lines were exposed to a range of pH environments. Affymetrix microarrays were used for gene-expression analysis and results were validated using cycle limitation and real-time RT-PCR analysis, as well as northern and western blotting. Comparative promoter transcription factor binding site (TFBS) analysis (MatInspector) of hierarchically clustered gene-expression data was employed to identify the elements which may co-ordinately regulate individual gene clusters. Initial experiments demonstrated maximal induction of EGR1 gene expression at pH 6.5. Subsequent array experimentation revealed significant induction of gene expression from such functional categories as DNA damage response (EGR1-4, ATF3) and cell-cycle control (GADD34, GADD45, p57). Changes in expression of EGR1, EGR3, ATF3, MKP-1, FOSB, CTGF and CYR61 were verified in separate experiments and in a variety of oesophageal cell lines. TFBS analysis of promoters identified transcription factors that may co-ordinately regulate gene-expression clusters, Cluster 1: Oct-1, AP4R; Cluster 2: NF-kB, EGRF; Cluster 3: IKRS, AP-1F. Low pH has the ability to induce genes and pathways which can provide an environment suitable for the progression of malignancy. Further functional analysis of the genes and clusters identified in this low pH study is likely to lead to new insights into the pathogenesis and therapeutics of GORD and oesophageal cancer.

Network analysis of differential expression for the identification of disease-causing genes.

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Daniela Nitsch

Full Text Available Genetic studies (in particular linkage and association studies identify chromosomal regions involved in a disease or phenotype of interest, but those regions often contain many candidate genes, only a few of which can be followed-up for biological validation. Recently, computational methods to identify (prioritize the most promising candidates within a region have been proposed, but they are usually not applicable to cases where little is known about the phenotype (no or few confirmed disease genes, fragmentary understanding of the biological cascades involved. We seek to overcome this limitation by replacing knowledge about the biological process by experimental data on differential gene expression between affected and healthy individuals. Considering the problem from the perspective of a gene/protein network, we assess a candidate gene by considering the level of differential expression in its neighborhood under the assumption that strong candidates will tend to be surrounded by differentially expressed neighbors. We define a notion of soft neighborhood where each gene is given a contributing weight, which decreases with the distance from the candidate gene on the protein network. To account for multiple paths between genes, we define the distance using the Laplacian exponential diffusion kernel. We score candidates by aggregating the differential expression of neighbors weighted as a function of distance. Through a randomization procedure, we rank candidates by p-values. We illustrate our approach on four monogenic diseases and successfully prioritize the known disease causing genes.

Predicting spatial and temporal gene expression using an integrative model of transcription factor occupancy and chromatin state.

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Bartek Wilczynski

Full Text Available Precise patterns of spatial and temporal gene expression are central to metazoan complexity and act as a driving force for embryonic development. While there has been substantial progress in dissecting and predicting cis-regulatory activity, our understanding of how information from multiple enhancer elements converge to regulate a gene's expression remains elusive. This is in large part due to the number of different biological processes involved in mediating regulation as well as limited availability of experimental measurements for many of them. Here, we used a Bayesian approach to model diverse experimental regulatory data, leading to accurate predictions of both spatial and temporal aspects of gene expression. We integrated whole-embryo information on transcription factor recruitment to multiple cis-regulatory modules, insulator binding and histone modification status in the vicinity of individual gene loci, at a genome-wide scale during Drosophila development. The model uses Bayesian networks to represent the relation between transcription factor occupancy and enhancer activity in specific tissues and stages. All parameters are optimized in an Expectation Maximization procedure providing a model capable of predicting tissue- and stage-specific activity of new, previously unassayed genes. Performing the optimization with subsets of input data demonstrated that neither enhancer occupancy nor chromatin state alone can explain all gene expression patterns, but taken together allow for accurate predictions of spatio-temporal activity. Model predictions were validated using the expression patterns of more than 600 genes recently made available by the BDGP consortium, demonstrating an average 15-fold enrichment of genes expressed in the predicted tissue over a naïve model. We further validated the model by experimentally testing the expression of 20 predicted target genes of unknown expression, resulting in an accuracy of 95% for temporal

Characterization of differentially expressed genes using high-dimensional co-expression networks

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Coelho Goncalves de Abreu, Gabriel; Labouriau, Rodrigo S.

2010-01-01

We present a technique to characterize differentially expressed genes in terms of their position in a high-dimensional co-expression network. The set-up of Gaussian graphical models is used to construct representations of the co-expression network in such a way that redundancy and the propagation...... that allow to make effective inference in problems with high degree of complexity (e.g. several thousands of genes) and small number of observations (e.g. 10-100) as typically occurs in high throughput gene expression studies. Taking advantage of the internal structure of decomposable graphical models, we...... construct a compact representation of the co-expression network that allows to identify the regions with high concentration of differentially expressed genes. It is argued that differentially expressed genes located in highly interconnected regions of the co-expression network are less informative than...

Selection and validation of reference genes for quantitative gene expression studies in Erythroxylum coca [v1; ref status: indexed, http://f1000r.es/y1

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Teresa Docimo

2013-02-01

Full Text Available Real-time quantitative PCR is a powerful technique for the investigation of comparative gene expression, but its accuracy and reliability depend on the reference genes used as internal standards. Only genes that show a high level of expression stability are suitable for use as reference genes, and these must be identified on a case-by-case basis. Erythroxylum coca produces and accumulates high amounts of the pharmacologically active tropane alkaloid cocaine (especially in the leaves, and is an emerging model for the investigation of tropane alkaloid biosynthesis. The identification of stable internal reference genes for this species is important for its development as a model species, and would enable comparative analysis of candidate biosynthetic genes in the different tissues of the coca plant. In this study, we evaluated the expression stability of nine candidate reference genes in E. coca (Ec6409, Ec10131, Ec11142, Actin, APT2, EF1α, TPB1, Pex4, Pp2aa3. The expression of these genes was measured in seven tissues (flowers, stems, roots and four developmental leaf stages and the stability of expression was assessed using three algorithms (geNorm, NormFinder and BestKeeper. From our results we conclude that Ec10131 and TPB1 are the most appropriate internal reference genes in leaves (where the majority of cocaine is produced, while Ec10131 and Ec6409 are the most suitable internal reference genes across all of the tissues tested.

Gene expression profiles in BCL11B-siRNA treated malignant T cells

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Grabarczyk Piotr

2011-05-01

Full Text Available Abstract Background Downregulation of the B-cell chronic lymphocytic leukemia (CLL/lymphoma11B (BCL11B gene by small interfering RNA (siRNA leads to growth inhibition and apoptosis of the human T-cell acute lymphoblastic leukemia (T-ALL cell line Molt-4. To further characterize the molecular mechanism, a global gene expression profile of BCL11B-siRNA -treated Molt-4 cells was established. The expression profiles of several genes were further validated in the BCL11B-siRNA -treated Molt-4 cells and primary T-ALL cells. Results 142 genes were found to be upregulated and 109 genes downregulated in the BCL11B-siRNA -treated Molt-4 cells by microarray analysis. Among apoptosis-related genes, three pro-apoptotic genes, TNFSF10, BIK, BNIP3, were upregulated and one anti-apoptotic gene, BCL2L1 was downregulated. Moreover, the expression of SPP1 and CREBBP genes involved in the transforming growth factor (TGF-β pathway was down 16-fold. Expression levels of TNFSF10, BCL2L1, SPP1, and CREBBP were also examined by real-time PCR. A similar expression pattern of TNFSF10, BCL2L1, and SPP1 was identified. However, CREBBP was not downregulated in the BLC11B-siRNA -treated Molt-4 cells. Conclusion BCL11B-siRNA treatment altered expression profiles of TNFSF10, BCL2L1, and SPP1 in both Molt-4 T cell line and primary T-ALL cells.

Regulation of eucaryotic gene expression

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Brent, R.; Ptashne, M.S

1989-05-23

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

A validated battery of vocal emotional expressions

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Pierre Maurage

2007-11-01

Full Text Available For a long time, the exploration of emotions focused on facial expression, and vocal expression of emotion has only recently received interest. However, no validated battery of emotional vocal expressions has been published and made available to the researchers’ community. This paper aims at validating and proposing such material. 20 actors (10 men recorded sounds (words and interjections expressing six basic emotions (anger, disgust, fear, happiness, neutral and sadness. These stimuli were then submitted to a double validation phase: (1 preselection by experts; (2 quantitative and qualitative validation by 70 participants. 195 stimuli were selected for the final battery, each one depicting a precise emotion. The ratings provide a complete measure of intensity and specificity for each stimulus. This paper provides, to our knowledge, the first validated, freely available and highly standardized battery of emotional vocal expressions (words and intonations. This battery could constitute an interesting tool for the exploration of prosody processing among normal and pathological populations, in neuropsychology as well as psychiatry. Further works are nevertheless needed to complement the present material.

Gene expression alterations associated with outcome in aromatase inhibitor-treated ER+ early-stage breast cancer patients

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Gravgaard Thomsen, Karina Hedelund; Lyng, Maria Bibi; Elias, Daniel

2015-01-01

predictive of outcome of ER+ breast cancer patients treated with AIs are needed. Global gene expression analysis was performed on ER+ primary breast cancers from patients treated with adjuvant AI monotherapy; half experienced recurrence (median follow-up 6.7 years). Gene expression alterations were validated...... by qRT-PCR, and functional studies evaluating the effect of siRNA-mediated gene knockdown on cell growth were performed. Twenty-six genes, including TFF3, DACH1, RGS5, and GHR, were shown to exhibit altered expression in tumors from patients with recurrence versus non-recurrent (fold change ≥1.5, p ....05), and the gene expression alterations were confirmed using qRT-PCR. Ten of these 26 genes could be linked in a network associated with cellular proliferation, growth, and development. TFF3, which encodes for trefoil factor 3 and is an estrogen-responsive oncogene shown to play a functional role in tamoxifen...

Identification of a developmental gene expression signature, including HOX genes, for the normal human colonic crypt stem cell niche: overexpression of the signature parallels stem cell overpopulation during colon tumorigenesis.

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Bhatlekar, Seema; Addya, Sankar; Salunek, Moreh; Orr, Christopher R; Surrey, Saul; McKenzie, Steven; Fields, Jeremy Z; Boman, Bruce M

2014-01-15

Our goal was to identify a unique gene expression signature for human colonic stem cells (SCs). Accordingly, we determined the gene expression pattern for a known SC-enriched region--the crypt bottom. Colonic crypts and isolated crypt subsections (top, middle, and bottom) were purified from fresh, normal, human, surgical specimens. We then used an innovative strategy that used two-color microarrays (∼18,500 genes) to compare gene expression in the crypt bottom with expression in the other crypt subsections (middle or top). Array results were validated by PCR and immunostaining. About 25% of genes analyzed were expressed in crypts: 88 preferentially in the bottom, 68 in the middle, and 131 in the top. Among genes upregulated in the bottom, ∼30% were classified as growth and/or developmental genes including several in the PI3 kinase pathway, a six-transmembrane protein STAMP1, and two homeobox (HOXA4, HOXD10) genes. qPCR and immunostaining validated that HOXA4 and HOXD10 are selectively expressed in the normal crypt bottom and are overexpressed in colon carcinomas (CRCs). Immunostaining showed that HOXA4 and HOXD10 are co-expressed with the SC markers CD166 and ALDH1 in cells at the normal crypt bottom, and the number of these co-expressing cells is increased in CRCs. Thus, our findings show that these two HOX genes are selectively expressed in colonic SCs and that HOX overexpression in CRCs parallels the SC overpopulation that occurs during CRC development. Our study suggests that developmental genes play key roles in the maintenance of normal SCs and crypt renewal, and contribute to the SC overpopulation that drives colon tumorigenesis.

Transcriptome-wide survey of mouse CNS-derived cells reveals monoallelic expression within novel gene families.

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Sierra M Li

Full Text Available Monoallelic expression is an integral component of regulation of a number of essential genes and gene families. To probe for allele-specific expression in cells of CNS origin, we used next-generation sequencing (RNA-seq to analyze four clonal neural stem cell (NSC lines derived from Mus musculus C57BL/6 (B6×Mus musculus molossinus (JF1 adult female mice. We established a JF1 cSNP library, then ascertained transcriptome-wide expression from B6 vs. JF1 alleles in the NSC lines. Validating the assay, we found that 262 of 268 X-linked genes evaluable in at least one cell line showed monoallelic expression (at least 85% expression of the predominant allele, p-value<0.05. For autosomal genes 170 of 7,198 genes (2.4% of the total showed monoallelic expression in at least 2 evaluable cell lines. The group included eight known imprinted genes with the expected pattern of allele-specific expression. Among the other autosomal genes with monoallelic expression were five members of the glutathione transferase gene superfamily, which processes xenobiotic compounds as well as carcinogens and cancer therapeutic agents. Monoallelic expression within this superfamily thus may play a functional role in the response to diverse and potentially lethal exogenous factors, as is the case for the immunoglobulin and olfactory receptor superfamilies. Other genes and gene families showing monoallelic expression include the annexin gene family and the Thy1 gene, both linked to inflammation and cancer, as well as genes linked to alcohol dependence (Gabrg1 and epilepsy (Kcnma1. The annotated set of genes will provide a resource for investigation of mechanisms underlying certain cases of these and other major disorders.

Gene expression profiling of two distinct neuronal populations in the rodent spinal cord.

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Jesper Ryge

Full Text Available 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

Shared Gene Expression Alterations in Nasal and Bronchial Epithelium for Lung Cancer Detection.

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2017-07-01

We previously derived and validated a bronchial epithelial gene expression biomarker to detect lung cancer in current and former smokers. Given that bronchial and nasal epithelial gene expression are similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene expression might also be detectable in the more readily accessible nasal epithelium. Nasal epithelial brushings were prospectively collected from current and former smokers undergoing diagnostic evaluation for pulmonary lesions suspicious for lung cancer in the AEGIS-1 (n = 375) and AEGIS-2 (n = 130) clinical trials and gene expression profiled using microarrays. All statistical tests were two-sided. We identified 535 genes that were differentially expressed in the nasal epithelium of AEGIS-1 patients diagnosed with lung cancer vs those with benign disease after one year of follow-up ( P  cancer-associated gene expression alterations between the two airway sites ( P  lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors (age, smoking status, time since quit, mass size) and nasal gene expression (30 genes) had statistically significantly higher area under the curve (0.81; 95% confidence interval [CI] = 0.74 to 0.89, P  = .01) and sensitivity (0.91; 95% CI = 0.81 to 0.97, P  = .03) than a clinical-factor only model in independent samples from the AEGIS-2 cohort. These results support that the airway epithelial field of lung cancer-associated injury in ever smokers extends to the nose and demonstrates the potential of using nasal gene expression as a noninvasive biomarker for lung cancer detection. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Identification and validation of reference genes for quantification of target gene expression with quantitative real-time PCR for tall fescue under four abiotic stresses.

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Zhimin Yang

Full Text Available Tall fescue (Festuca arundinacea Schreb. is widely utilized as a major forage and turfgrass species in the temperate regions of the world and is a valuable plant material for studying molecular mechanisms of grass stress tolerance due to its superior drought and heat tolerance among cool-season species. Selection of suitable reference genes for quantification of target gene expression is important for the discovery of molecular mechanisms underlying improved growth traits and stress tolerance. The stability of nine potential reference genes (ACT, TUB, EF1a, GAPDH, SAND, CACS, F-box, PEPKR1 and TIP41 was evaluated using four programs, GeNorm, NormFinder, BestKeeper, and RefFinder. The combinations of SAND and TUB or TIP41 and TUB were most stably expressed in salt-treated roots or leaves. The combinations of GAPDH with TIP41 or TUB were stable in roots and leaves under drought stress. TIP41 and PEPKR1 exhibited stable expression in cold-treated roots, and the combination of F-box, TIP41 and TUB was also stable in cold-treated leaves. CACS and TUB were the two most stable reference genes in heat-stressed roots. TIP41 combined with TUB and ACT was stably expressed in heat-stressed leaves. Finally, quantitative real-time polymerase chain reaction (qRT-PCR assays of the target gene FaWRKY1 using the identified most stable reference genes confirmed the reliability of selected reference genes. The selection of suitable reference genes in tall fescue will allow for more accurate identification of stress-tolerance genes and molecular mechanisms conferring stress tolerance in this stress-tolerant species.

GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets.

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John Patrick Mpindi

Full Text Available BACKGROUND: Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type ('outlier genes', a hallmark of potential oncogenes. METHODOLOGY: A new statistical method (the gene tissue index, GTI was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29 of these genes, and 17 of these 19 genes (90% showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target. CONCLUSIONS/SIGNIFICANCE: Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is

Identification of the common radiation-sensitive and glucose metabolism-related expressed genes in the thymus of ICR and AKR/J mice

International Nuclear Information System (INIS)

Bong, Jin Jong; Kang, Yumi; Choi, Suk Cjul; Choi, Moo Hyun; Choi, Seung Jin; Kim, Hee Sun

2011-01-01

Our goal was to identify the common radiation-sensitive expressed genes in the thymus of ICR and AKR/J mice on 100 days after irradiation. Thus, we performed microarray analysis for thymus of ICR and AKR/J mice, respectively. We categorized differential expressed genes by the analysis of DAVID Bioinformatics Resources v 6.7 and GeneSpring GX 11.5.1 and validated gene expression patterns by QPCR analysis. Our result demonstrated that radiation-sensitive expressed genes and signaling pathways in the thymus of irradiated ICR and AKR/J mice.

A GMM-IG framework for selecting genes as expression panel biomarkers.

Science.gov (United States)

Wang, Mingyi; Chen, Jake Y

2010-01-01

The limitation of small sample size of functional genomics experiments has made it necessary to integrate DNA microarray experimental data from different sources. However, experimentation noises and biases of different microarray platforms have made integrated data analysis challenging. In this work, we propose an integrative computational framework to identify candidate biomarker genes from publicly available functional genomics studies. We developed a new framework, Gaussian Mixture Modeling-Coupled Information Gain (GMM-IG). In this framework, we first apply a two-component Gaussian mixture model (GMM) to estimate the conditional probability distributions of gene expression data between two different types of samples, for example, normal versus cancer. An expectation-maximization algorithm is then used to estimate the maximum likelihood parameters of a mixture of two Gaussian models in the feature space and determine the underlying expression levels of genes. Gene expression results from different studies are discretized, based on GMM estimations and then unified. Significantly differentially-expressed genes are filtered and assessed with information gain (IG) measures. DNA microarray experimental data for lung cancers from three different prior studies was processed using the new GMM-IG method. Target gene markers from a gene expression panel were selected and compared with several conventional computational biomarker data analysis methods. GMM-IG showed consistently high accuracy for several classification assessments. A high reproducibility of gene selection results was also determined from statistical validations. Our study shows that the GMM-IG framework can overcome poor reliability issues from single-study DNA microarray experiment while maintaining high accuracies by combining true signals from multiple studies. We present a conceptually simple framework that enables reliable integration of true differential gene expression signals from multiple

Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression data [version 2; referees: 2 approved

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Linh Nguyen

2017-03-01

Full Text Available Background: Selected gene mutations are routinely used to guide the selection of cancer drugs for a given patient tumour. Large pharmacogenomic data sets, such as those by Genomics of Drug Sensitivity in Cancer (GDSC consortium, were introduced to discover more of these single-gene markers of drug sensitivity. Very recently, machine learning regression has been used to investigate how well cancer cell line sensitivity to drugs is predicted depending on the type of molecular profile. The latter has revealed that gene expression data is the most predictive profile in the pan-cancer setting. However, no study to date has exploited GDSC data to systematically compare the performance of machine learning models based on multi-gene expression data against that of widely-used single-gene markers based on genomics data. Methods: Here we present this systematic comparison using Random Forest (RF classifiers exploiting the expression levels of 13,321 genes and an average of 501 tested cell lines per drug. To account for time-dependent batch effects in IC50 measurements, we employ independent test sets generated with more recent GDSC data than that used to train the predictors and show that this is a more realistic validation than standard k-fold cross-validation. Results and Discussion: Across 127 GDSC drugs, our results show that the single-gene markers unveiled by the MANOVA analysis tend to achieve higher precision than these RF-based multi-gene models, at the cost of generally having a poor recall (i.e. correctly detecting only a small part of the cell lines sensitive to the drug. Regarding overall classification performance, about two thirds of the drugs are better predicted by the multi-gene RF classifiers. Among the drugs with the most predictive of these models, we found pyrimethamine, sunitinib and 17-AAG. Conclusions: Thanks to this unbiased validation, we now know that this type of models can predict in vitro tumour response to some of these

Gene expression analysis identifies new candidate genes associated with the development of black skin spots in Corriedale sheep.

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Peñagaricano, Francisco; Zorrilla, Pilar; Naya, Hugo; Robello, Carlos; Urioste, Jorge I

2012-02-01

The white coat colour of sheep is an important economic trait. For unknown reasons, some animals are born with, and others develop with time, black skin spots that can also produce pigmented fibres. The presence of pigmented fibres in the white wool significantly decreases the fibre quality. The aim of this work was to study gene expression in black spots (with and without pigmented fibres) and white skin by microarray techniques, in order to identify the possible genes involved in the development of this trait. Five unrelated Corriedale sheep were used and, for each animal, the three possible comparisons (three different hybridisations) between the three samples of interest were performed. Differential gene expression patterns were analysed using different t-test approaches. Most of the major genes with well-known roles in skin pigmentation, e.g. ASIP, MC1R and C-KIT, showed no significant difference in the gene expression between white skin and black spots. On the other hand, many of the differentially expressed genes (raw P-value spots. The gene expression of C-FOS and KLF4, transcription factors involved in the cellular response to external factors such as ultraviolet light, was validated by quantitative polymerase chain reaction (PCR). This exploratory study provides a list of candidate genes that could be associated with the development of black skin spots that should be studied in more detail. Characterisation of these genes will enable us to discern the molecular mechanisms involved in the development of this feature and, hence, increase our understanding of melanocyte biology and skin pigmentation. In sheep, understanding this phenomenon is a first step towards developing molecular tools to assist in the selection against the presence of pigmented fibres in white wool.

Inferring gene expression dynamics via functional regression analysis

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Leng Xiaoyan

2008-01-01

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

Kinase Gene Expression Profiling of Metastatic Clear Cell Renal Cell Carcinoma Tissue Identifies Potential New Therapeutic Targets.

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Pooja Ghatalia

Full Text Available Kinases are therapeutically actionable targets. Kinase inhibitors targeting vascular endothelial growth factor receptors (VEGFR and mammalian target of rapamycin (mTOR improve outcomes in metastatic clear cell renal cell carcinoma (ccRCC, but are not curative. Metastatic tumor tissue has not been comprehensively studied for kinase gene expression. Paired intra-patient kinase gene expression analysis in primary tumor (T, matched normal kidney (N and metastatic tumor tissue (M may assist in identifying drivers of metastasis and prioritizing therapeutic targets. We compared the expression of 519 kinase genes using NanoString in T, N and M in 35 patients to discover genes over-expressed in M compared to T and N tissue. RNA-seq data derived from ccRCC tumors in The Cancer Genome Atlas (TCGA were used to demonstrate differential expression of genes in primary tumor tissue from patients that had metastasis at baseline (n = 79 compared to those that did not develop metastasis for at least 2 years (n = 187. Functional analysis was conducted to identify key signaling pathways by using Ingenuity Pathway Analysis. Of 10 kinase genes overexpressed in metastases compared to primary tumor in the discovery cohort, 9 genes were also differentially expressed in TCGA primary tumors with metastasis at baseline compared to primary tumors without metastasis for at least 2 years: EPHB2, AURKA, GSG2, IKBKE, MELK, CSK, CHEK2, CDC7 and MAP3K8; p<0.001. The top pathways overexpressed in M tissue were pyridoxal 5'-phosphate salvage, salvage pathways of pyrimidine ribonucleotides, NF-kB signaling, NGF signaling and cell cycle control of chromosomal replication. The 9 kinase genes validated to be over-expressed in metastatic ccRCC may represent currently unrecognized but potentially actionable therapeutic targets that warrant functional validation.

Synthetic promoter libraries- tuning of gene expression

DEFF Research Database (Denmark)

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

2006-01-01

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

GECKO: a complete large-scale gene expression analysis platform

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Heuer Michael

2004-12-01

Full Text Available Abstract Background Gecko (Gene Expression: Computation and Knowledge Organization is a complete, high-capacity centralized gene expression analysis system, developed in response to the needs of a distributed user community. Results Based on a client-server architecture, with a centralized repository of typically many tens of thousands of Affymetrix scans, Gecko includes automatic processing pipelines for uploading data from remote sites, a data base, a computational engine implementing ~ 50 different analysis tools, and a client application. Among available analysis tools are clustering methods, principal component analysis, supervised classification including feature selection and cross-validation, multi-factorial ANOVA, statistical contrast calculations, and various post-processing tools for extracting data at given error rates or significance levels. On account of its open architecture, Gecko also allows for the integration of new algorithms. The Gecko framework is very general: non-Affymetrix and non-gene expression data can be analyzed as well. A unique feature of the Gecko architecture is the concept of the Analysis Tree (actually, a directed acyclic graph, in which all successive results in ongoing analyses are saved. This approach has proven invaluable in allowing a large (~ 100 users and distributed community to share results, and to repeatedly return over a span of years to older and potentially very complex analyses of gene expression data. Conclusions The Gecko system is being made publicly available as free software http://sourceforge.net/projects/geckoe. In totality or in parts, the Gecko framework should prove useful to users and system developers with a broad range of analysis needs.

Identification and comprehensive evaluation of reference genes for RT-qPCR analysis of host gene-expression in Brassica juncea-aphid interaction using microarray data.

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Ram, Chet; Koramutla, Murali Krishna; Bhattacharya, Ramcharan

2017-07-01

Brassica juncea is a chief oil yielding crop in many parts of the world including India. With advancement of molecular techniques, RT-qPCR based study of gene-expression has become an integral part of experimentations in crop breeding. In RT-qPCR, use of appropriate reference gene(s) is pivotal. The virtue of the reference genes, being constant in expression throughout the experimental treatments, needs to be validated case by case. Appropriate reference gene(s) for normalization of gene-expression data in B. juncea during the biotic stress of aphid infestation is not known. In the present investigation, 11 reference genes identified from microarray database of Arabidopsis-aphid interaction at a cut off FDR ≤0.1, along with two known reference genes of B. juncea, were analyzed for their expression stability upon aphid infestation. These included 6 frequently used and 5 newly identified reference genes. Ranking orders of the reference genes in terms of expression stability were calculated using advanced statistical approaches such as geNorm, NormFinder, delta Ct and BestKeeper. The analysis suggested CAC, TUA and DUF179 as the most suitable reference genes. Further, normalization of the gene-expression data of STP4 and PR1 by the most and the least stable reference gene, respectively has demonstrated importance and applicability of the recommended reference genes in aphid infested samples of B. juncea. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

NBL1 and anillin (ANLN genes over-expression in pancreatic carcinoma.

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Dariusz Lange

2009-12-01

Full Text Available The aim of the study was to analyze the gene expression profile of pancreatic cancer to derive novel molecular markers of this malignancy. The snap-frozen or RNA-later preserved samples of 18 pancreatic adenocarcinomas, 5 chronic pancreatitis cases and 6 specimens of grossly normal pancreas were used for microarray analysis by HG-U133 Plus 2.0 oligonucleotide Affymetrix arrays. Validation was carried out by real-time quantitative PCR (Q-PCR in the set of 66 samples: 31 of pancreatic cancer, 14 of chronic pancreatitis and 21 of macroscopically unchanged pancreas. By Principal Component Analysis of the microarray data we found a very consistent expression pattern of normal samples and a less homogenous one in chronic pancreatitis. By supervised comparison (corrected p-value 0.001 we observed 11094 probesets differentiating between cancer and normal samples, while only seventy six probesets were significant for difference between cancer and chronic pancreatitis. The only gene occurring within the best 10 genes in both comparisons was S100 calcium binding protein P (S100P, already indicated for its utility as pancreatic cancer marker by earlier microarray-based studies. For validation we selected two genes which appeared as valuable candidates for molecular markers of pancreatic cancer: neuroblastoma, suppression of tumorigenicity 1 (NBL1 and anillin (ANLN. By Q-PCR, we confirmed statistically significant differences in these genes with a 9.5 fold-change difference between NBL1 expression in cancer/normal comparison and a relatively modest difference between cancer and pancreatitis. For ANLN even more distinct differences were observed (cancer/normal 19.8-fold, cancer/pancreatitis 4.0-fold. NBL1 and anillin are promising markers for pancreatic carcinoma molecular diagnostics.

Expression profiling identifies genes involved in neoplastic transformation of serous ovarian cancer

International Nuclear Information System (INIS)

Merritt, Melissa A; Parsons, Peter G; Newton, Tanya R; Martyn, Adam C; Webb, Penelope M; Green, Adèle C; Papadimos, David J; Boyle, Glen M

2009-01-01

The malignant potential of serous ovarian tumors, the most common ovarian tumor subtype, varies from benign to low malignant potential (LMP) tumors to frankly invasive cancers. Given the uncertainty about the relationship between these different forms, we compared their patterns of gene expression. Expression profiling was carried out on samples of 7 benign, 7 LMP and 28 invasive (moderate and poorly differentiated) serous tumors and four whole normal ovaries using oligonucleotide microarrays representing over 21,000 genes. We identified 311 transcripts that distinguished invasive from benign tumors, and 20 transcripts that were significantly differentially expressed between invasive and LMP tumors at p < 0.01 (with multiple testing correction). Five genes that were differentially expressed between invasive and either benign or normal tissues were validated by real time PCR in an independent panel of 46 serous tumors (4 benign, 7 LMP, 35 invasive). Overexpression of SLPI and WNT7A and down-regulation of C6orf31, PDGFRA and GLTSCR2 were measured in invasive and LMP compared with benign and normal tissues. Over-expression of WNT7A in an ovarian cancer cell line led to increased migration and invasive capacity. These results highlight several genes that may play an important role across the spectrum of serous ovarian tumorigenesis

Selection of Reliable Reference Genes for Gene Expression Studies in the Biofuel Plant Jatropha curcas Using Real-Time Quantitative PCR

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Lu Zhang

2013-12-01

Full Text Available Jatropha curcas is a promising renewable feedstock for biodiesel and bio-jet fuel production. To study gene expression in Jatropha in different tissues throughout development and under stress conditions, we examined a total of 11 typical candidate reference genes using real-time quantitative polymerase chain reaction (RT-qPCR analysis, which is widely used for validating transcript levels in gene expression studies. The expression stability of these candidate reference genes was assessed across a total of 20 samples, including various tissues at vegetative and reproductive stages and under desiccation and cold stress treatments. The results obtained using software qBasePLUS showed that the top-ranked reference genes differed across the sample subsets. The combination of actin, GAPDH, and EF1α would be appropriate as a reference panel for normalizing gene expression data across samples at different developmental stages; the combination of actin, GAPDH, and TUB5 should be used as a reference panel for normalizing gene expression data across samples under various abiotic stress treatments. With regard to different developmental stages, we recommend the use of actin and TUB8 for normalization at the vegetative stage and GAPDH and EF1α for normalization at the reproductive stage. For abiotic stress treatments, we recommend the use of TUB5 and TUB8 for normalization under desiccation stress and GAPDH and actin for normalization under cold stress. These results are valuable for future research on gene expression during development or under abiotic stress in Jatropha. To our knowledge, this is the first report on the stability of reference genes in Jatropha.

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

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Meng Sun

Full Text Available 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.

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

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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.

Ecdysone Receptor-based Singular Gene Switches for Regulated Transgene Expression in Cells and Adult Rodent Tissues

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Seoghyun Lee

2016-01-01

Full Text Available Controlled gene expression is an indispensable technique in biomedical research. Here, we report a convenient, straightforward, and reliable way to induce expression of a gene of interest with negligible background expression compared to the most widely used tetracycline (Tet-regulated system. Exploiting a Drosophila ecdysone receptor (EcR-based gene regulatory system, we generated nonviral and adenoviral singular vectors designated as pEUI(+ and pENTR-EUI, respectively, which contain all the required elements to guarantee regulated transgene expression (GAL4-miniVP16-EcR, termed GvEcR hereafter, and 10 tandem repeats of an upstream activation sequence promoter followed by a multiple cloning site. Through the transient and stable transfection of mammalian cell lines with reporter genes, we validated that tebufenozide, an ecdysone agonist, reversibly induced gene expression, in a dose- and time-dependent manner, with negligible background expression. In addition, we created an adenovirus derived from the pENTR-EUI vector that readily infected not only cultured cells but also rodent tissues and was sensitive to tebufenozide treatment for regulated transgene expression. These results suggest that EcR-based singular gene regulatory switches would be convenient tools for the induction of gene expression in cells and tissues in a tightly controlled fashion.

Validation of putative reference genes for normalization of Q-RT-PCR data from paraffin-embedded lymphoid tissue

DEFF Research Database (Denmark)

Green, Tina Marie; de Stricker, Karin; Møller, Michael Boe

2009-01-01

Normalization of quantitative reverse transcription-PCR (Q-RT-PCR) data to appropriate tissue-specific reference genes is an essential part of interpreting the results. This study aimed to determine the most appropriate reference genes for normalizing gene expressions in lymphatic tissue...... was 0.93 (Pnormalization with the appropriate reference genes. Thus, we show that formalin-fixed, paraffin-embedded lymphoid samples are suitable for Q-RT-PCR when using thoroughly validated reference genes....

Gene expression profile of Bombyx mori hemocyte under the stress of destruxin A.

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Liang Gong

Full Text Available Destruxin A (DA is a cyclo-peptidic mycotoxin from the entomopathogenic fungus Metarhizium anisopliae. To uncover potential genes associated with its molecular mechanisms, a digital gene expression (DGE profiling analysis was used to compare differentially expressed genes in the hemocytes of silkworm larvae treated with DA. Ten DGE libraries were constructed, sequenced, and assembled, and the unigenes with least 2.0-fold difference were further analyzed. The numbers of up-regulated genes were 10, 20, 18, 74 and 8, as well as the numbers of down-regulated genes were 0, 1, 8, 13 and 3 at 1, 4, 8, 12 and 24 h post treatment, respectively. Totally, the expression of 132 genes were significantly changed, among them, 1, 3 and 12 genes were continually up-regulated at 4, 3 and 2 different time points, respectively, while 1 gene was either up or down-regulated continually at 2 different time points. Furthermore, 68 genes were assigned to one or multiple gene ontology (GO terms and 89 genes were assigned to specific Kyoto Encyclopedia of Genes and Genomes (KEGG Orthology. In-depth analysis identified that these genes putatively involved in insecticide resistance, cell apoptosis, and innate immune defense. Finally, twenty differentially expressed genes were randomly chosen and validated by quantitative real-time PCR (qRT-PCR. Our studies provide insights into the toxic effect of this microbial insecticide on silkworm's hemocytes, and are helpful to better understanding of the molecular mechanisms of DA as a biological insecticide.

Gene Expression Correlation for Cancer Diagnosis: A Pilot Study

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Binbing Ling

2014-01-01

Full Text Available Poor prognosis for late-stage, high-grade, and recurrent cancers has been motivating cancer researchers to search for more efficient biomarkers to identify the onset of cancer. Recent advances in constructing and dynamically analyzing biomolecular networks for different types of cancer have provided a promising novel strategy to detect tumorigenesis and metastasis. The observation of different biomolecular networks associated with normal and cancerous states led us to hypothesize that correlations for gene expressions could serve as valid indicators of early cancer development. In this pilot study, we tested our hypothesis by examining whether the mRNA expressions of three randomly selected cancer-related genes PIK3C3, PIM3, and PTEN were correlated during cancer progression and the correlation coefficients could be used for cancer diagnosis. Strong correlations (0.68≤r≤1.0 were observed between PIK3C3 and PIM3 in breast cancer, between PIK3C3 and PTEN in breast and ovary cancers, and between PIM3 and PTEN in breast, kidney, liver, and thyroid cancers during disease progression, implicating that the correlations for cancer network gene expressions could serve as a supplement to current clinical biomarkers, such as cancer antigens, for early cancer diagnosis.

Gene expression in gastrointestinal stromal tumors is distinguished by KIT genotype and anatomic site.

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Antonescu, Cristina R; Viale, Agnes; Sarran, Lisa; Tschernyavsky, Sylvia J; Gonen, Mithat; Segal, Neil H; Maki, Robert G; Socci, Nicholas D; DeMatteo, Ronald P; Besmer, Peter

2004-05-15

Gastrointestinal stromal tumors (GISTs) are specific KIT expressing and KIT-signaling driven mesenchymal tumors of the human digestive tract, many of which have KIT-activating mutations. Previous studies have found a relatively homogeneous gene expression profile in GIST, as compared with other histological types of sarcomas. Transcriptional heterogeneity within clinically or molecularly defined subsets of GISTs has not been previously reported. We tested the hypothesis that the gene expression profile in GISTs might be related to KIT genotype and possibly to other clinicopathological factors. An HG-U133A Affymetrix chip (22,000 genes) platform was used to determine the variability of gene expression in 28 KIT-expressing GIST samples from 24 patients. A control group of six intra-abdominal leiomyosarcomas was also included for comparison. Statistical analyses (t tests) were performed to identify discriminatory gene lists among various GIST subgroups. The levels of expression of various GIST subsets were also linked to a modified version of the growth factor/KIT signaling pathway to analyze differences at various steps in signal transduction. Genes involved in KIT signaling were differentially expressed among wild-type and mutant GISTs. High gene expression of potential drug targets, such as VEGF, MCSF, and BCL2 in the wild-type group, and Mesothelin in exon 9 GISTs were found. There was a striking difference in gene expression between stomach and small bowel GISTs. This finding was validated in four separate tumors, two gastric and two intestinal, from a patient with familial GIST with a germ-line KIT W557R substitution. GISTs have heterogeneous gene expression depending on KIT genotype and tumor location, which is seen at both the genomic level and the KIT signaling pathway in particular. These findings may explain their variable clinical behavior and response to therapy.

Adaptive Evolution of Gene Expression in Drosophila.

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

2017-08-08

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

Adaptive Evolution of Gene Expression in Drosophila

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Armita Nourmohammad

2017-08-01

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

Identification and validation of reference genes for quantitative real-time PCR in Drosophila suzukii (Diptera: Drosophilidae.

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Yifan Zhai

Full Text Available To accurately evaluate gene expression levels and obtain more accurate quantitative real-time RT-PCR (qRT-PCR data, normalization relative to reliable reference gene(s is required. Drosophila suzukii, is an invasive fruit pest native to East Asia, and recently invaded Europe and North America, the stability of its reference genes have not been previously investigated. In this study, ten candidate reference genes (RPL18, RPS3, AK, EF-1β, TBP, NADH, HSP22, GAPDH, Actin, α-Tubulin, were evaluated for their suitability as normalization genes under different biotic (developmental stage, tissue and population, and abiotic (photoperiod, temperature conditions. The three statistical approaches (geNorm, NormFinder and BestKeeper and one web-based comprehensive tool (RefFinder were used to normalize analysis of the ten candidate reference genes identified α-Tubulin, TBP and AK as the most stable candidates, while HSP22 and Actin showed the lowest expression stability. We used three most stable genes (α-Tubulin, TBP and AK and one unstably expressed gene to analyze the expression of P-glycoprotein in abamectin-resistant and sensitive strains, and the results were similar to reference genes α-Tubulin, TBP and AK, which show good stability, while the result of HSP22 has a certain bias. The three validated reference genes can be widely used for quantification of target gene expression with qRT-PCR technology in D.suzukii.

Gene expression patterns induced at different stages of rhinovirus infection in human alveolar epithelial cells.

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Mohammad Reza Etemadi

Full Text Available Human rhinovirus (HRV is the common virus that causes acute respiratory infection (ARI and is frequently associated with lower respiratory tract infections (LRTIs. We aimed to investigate whether HRV infection induces a specific gene expression pattern in airway epithelial cells. Alveolar epithelial cell monolayers were infected with HRV species B (HRV-B. RNA was extracted from both supernatants and infected monolayer cells at 6, 12, 24 and 48 hours post infection (hpi and transcriptional profile was analyzed using Affymetrix GeneChip and the results were subsequently validated using quantitative Real-time PCR method. HRV-B infects alveolar epithelial cells which supports implication of the virus with LRTIs. In total 991 genes were found differentially expressed during the course of infection. Of these, 459 genes were up-regulated whereas 532 genes were down-regulated. Differential gene expression at 6 hpi (187 genes up-regulated vs. 156 down-regulated were significantly represented by gene ontologies related to the chemokines and inflammatory molecules indicating characteristic of viral infection. The 75 up-regulated genes surpassed the down-regulated genes (35 at 12 hpi and their enriched ontologies fell into discrete functional entities such as regulation of apoptosis, anti-apoptosis, and wound healing. At later time points of 24 and 48 hpi, predominated down-regulated genes were enriched for extracellular matrix proteins and airway remodeling events. Our data provides a comprehensive image of host response to HRV infection. The study suggests the underlying molecular regulatory networks genes which might be involved in pathogenicity of the HRV-B and potential targets for further validations and development of effective treatment.

Gene expression-based molecular diagnostic system for malignant gliomas is superior to histological diagnosis.

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Shirahata, Mitsuaki; Iwao-Koizumi, Kyoko; Saito, Sakae; Ueno, Noriko; Oda, Masashi; Hashimoto, Nobuo; Takahashi, Jun A; Kato, Kikuya

2007-12-15

Current morphology-based glioma classification methods do not adequately reflect the complex biology of gliomas, thus limiting their prognostic ability. In this study, we focused on anaplastic oligodendroglioma and glioblastoma, which typically follow distinct clinical courses. Our goal was to construct a clinically useful molecular diagnostic system based on gene expression profiling. The expression of 3,456 genes in 32 patients, 12 and 20 of whom had prognostically distinct anaplastic oligodendroglioma and glioblastoma, respectively, was measured by PCR array. Next to unsupervised methods, we did supervised analysis using a weighted voting algorithm to construct a diagnostic system discriminating anaplastic oligodendroglioma from glioblastoma. The diagnostic accuracy of this system was evaluated by leave-one-out cross-validation. The clinical utility was tested on a microarray-based data set of 50 malignant gliomas from a previous study. Unsupervised analysis showed divergent global gene expression patterns between the two tumor classes. A supervised binary classification model showed 100% (95% confidence interval, 89.4-100%) diagnostic accuracy by leave-one-out cross-validation using 168 diagnostic genes. Applied to a gene expression data set from a previous study, our model correlated better with outcome than histologic diagnosis, and also displayed 96.6% (28 of 29) consistency with the molecular classification scheme used for these histologically controversial gliomas in the original article. Furthermore, we observed that histologically diagnosed glioblastoma samples that shared anaplastic oligodendroglioma molecular characteristics tended to be associated with longer survival. Our molecular diagnostic system showed reproducible clinical utility and prognostic ability superior to traditional histopathologic diagnosis for malignant glioma.

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans

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Assaf Gottlieb

2017-11-01

Full Text Available Abstract Background Genome-wide association studies are useful for discovering genotype–phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into “gene level” effects. Methods Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression—on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. Results We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Conclusions Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort

Effects of warm ischemic time on gene expression profiling in colorectal cancer tissues and normal mucosa.

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Valeria Musella

Full Text Available BACKGROUND: Genome-wide gene expression analyses of tumors are a powerful tool to identify gene signatures associated with biologically and clinically relevant characteristics and for several tumor types are under clinical validation by prospective trials. However, handling and processing of clinical specimens may significantly affect the molecular data obtained from their analysis. We studied the effects of tissue handling time on gene expression in human normal and tumor colon tissues undergoing routine surgical procedures. METHODS: RNA extracted from specimens of 15 patients at four time points (for a total of 180 samples after surgery was analyzed for gene expression on high-density oligonucleotide microarrays. A mixed-effects model was used to identify probes with different expression means across the four different time points. The p-values of the model were adjusted with the Bonferroni method. RESULTS: Thirty-two probe sets associated with tissue handling time in the tumor specimens, and thirty-one in the normal tissues, were identified. Most genes exhibited moderate changes in expression over the time points analyzed; however four of them were oncogenes, and two confirmed the effect of tissue handling by independent validation. CONCLUSIONS: Our results suggest that a critical time point for tissue handling in colon seems to be 60 minutes at room temperature. Although the number of time-dependent genes we identified was low, the three genes that already showed changes at this time point in tumor samples were all oncogenes, hence recommending standardization of tissue-handling protocols and effort to reduce the time from specimen removal to snap freezing accounting for warm ischemia in this tumor type.

Prediction of lymphatic metastasis based on gene expression profile analysis after brachytherapy for early-stage oral tongue carcinoma

International Nuclear Information System (INIS)

Watanabe, Hiroshi; Mogushi, Kaoru; Miura, Masahiko; Yoshimura, Ryo-ichi; Kurabayashi, Tohru; Shibuya, Hitoshi; Tanaka, Hiroshi; Noda, Shuhei; Iwakawa, Mayumi; Imai, Takashi

2008-01-01

Background and purpose: The management of lymphatic metastasis of early-stage oral tongue carcinoma patients is crucial for its prognosis. The purpose of this study was to evaluate the predictive ability of lymphatic metastasis after brachytherapy (BRT) for early-stage tongue carcinoma based on gene expression profiling. Patients and methods: Pre-therapeutic biopsies from 39 patients with T1 or T2 tongue cancer were analyzed for gene expression signatures using Codelink Uniset Human 20K Bioarray. All patients were treated with low dose-rate BRT for their primary lesions and underwent strict follow-up under a wait-and-see policy for cervical lymphatic metastasis. Candidate genes were selected for predicting lymph-node status in the reference group by the permutation test. Predictive accuracy was further evaluated by the prediction strength (PS) scoring system using an independent validation group. Results: We selected a set of 19 genes whose expression differed significantly between classes with or without lymphatic metastasis in the reference group. The lymph-node status in the validation group was predicted by the PS scoring system with an accuracy of 76%. Conclusions: Gene expression profiling using 19 genes in primary tumor tissues may allow prediction of lymphatic metastasis after BRT for early-stage oral tongue carcinoma

Cocoa polyphenols and fiber modify colonic gene expression in rats.

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Massot-Cladera, Malen; Franch, Àngels; Castell, Margarida; Pérez-Cano, Francisco J

2017-08-01

Cocoa intake has been associated with health benefits, improving cardiovascular function and metabolism, as well as modulating intestinal immune function. The aim of this study was to take an in-depth look into the mechanisms affected by the cocoa intake by evaluating the colonic gene expression after nutritional intervention, and to ascertain the role of the fiber of cocoa in these effects. To achieve this, Wistar rats were fed for 3 weeks with either a reference diet, a diet containing 10 % cocoa (C10), a diet based on cocoa fiber (CF) or a diet containing inulin (I). At the end of the study, colon was excised to obtain the RNA to evaluate the differential gene expression by microarray. Results were validated by RT-PCR. The C10 group was the group with most changes in colonic gene expression, most of them down-regulated but a few in common with the CF diet. The C10 diet significantly up-regulated the expression of Scgb1a1 and Scnn1 g and down-regulated Tac4, Mcpt2, Fcer1a and Fabp1 by twofold, most of them related to lipid metabolism and immune function. The CF and I diets down-regulated the expression of Serpina10 and Apoa4 by twofold. Similar patterns of expression were found by PCR. Most of the effects attributed to cocoa consumption on genes related to the immune system (B cell and mast cell functionality) and lipid metabolism in the colon tissue were due not only to its fiber content, but also to the possible contribution of polyphenols and other compounds.

In vivo expression of genes in the entomopathogenic fungus Beauveria bassiana during infection of lepidopteran larvae.

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Galidevara, Sandhya; Reineke, Annette; Koduru, Uma Devi

2016-05-01

The entomopathogenic fungus Beauveria bassiana (Bals.) Vuillemin is commercially available as a bio insecticide. The expression of three genes previously identified to have a role in pathogenicity in in vitro studies was validated in vivo in three lepidopteran insects infected with B. bassiana. Expression of all three genes was observed in all the tested insects starting from 48 or 72h to 10d post infection corroborating their role in pathogenicity. We suggest that it is essential to test the expression of putative pathogenicity genes both in vitro and in vivo to understand their role in different insect species. Copyright © 2016 Elsevier Inc. All rights reserved.

Cardiac-Specific Gene Expression Facilitated by an Enhanced Myosin Light Chain Promoter

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Wolfgang Boecker

2004-04-01

Full Text Available Background: Adenoviral gene transfer has been shown to be effective in cardiac myocytes in vitro and in vivo. A major limitation of myocardial gene therapy is the extracardiac transgene expression. Methods: To minimize extracardiac gene expression, we have constructed a tissue-specific promoter for cardiac gene transfer, namely, the 250-bp fragment of the myosin light chain-2v (MLC-2v gene, which is known to be expressed in a tissue-specific manner in ventricular myocardium followed by a luciferase (luc reporter gene (Ad.4 × MLC250.Luc. Rat cardiomyocytes, liver and kidney cells were infected with Ad.4 × MLC.Luc or control vectors. For in vivo testing, Ad.4 × MLC250.Luc was injected into the myocardium or in the liver of rats. Kinetics of promoter activity were monitored over 8 days using a cooled CCD camera. Results: In vitro: By infecting hepatic versus cardiomyocyte cells, we found that the promoter specificity ratio (luc activity in cardiomyocytes per liver cells was 20.4 versus 0.9 (Ad.4 × MLC250.Luc vs. Ad.CMV. In vivo: Ad.4 × MLC250.Luc significantly reduced luc activity in liver (38.4-fold, lung (16.1-fold, and kidney (21.8-fold versus Ad.CMV (p = .01; whereas activity in the heart was only 3.8-fold decreased. The gene expression rate of cardiomyocytes versus hepatocytes was 7:1 (Ad.4 × MLC.Luc versus 1:1.4 (Ad.CMV.Luc. Discussion: This new vector may be useful to validate therapeutic approaches in animal disease models and offers the perspective for selective expression of therapeutic genes in the diseased heart.

A gene expression signature associated with survival in metastatic melanoma

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Mandruzzato, Susanna; Callegaro, Andrea; Turcatel, Gianluca; Francescato, Samuela; Montesco, Maria C; Chiarion-Sileni, Vanna; Mocellin, Simone; Rossi, Carlo R; Bicciato, Silvio; Wang, Ena; Marincola, Francesco M; Zanovello, Paola

2006-01-01

Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells. PMID:17129373

A gene expression signature associated with survival in metastatic melanoma

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Rossi Carlo R

2006-11-01

Full Text Available Abstract Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM to identify genes associated with patient survival, and supervised principal components (SPC to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells.

Multi-organ expression profiling uncovers a gene module in coronary artery disease involving transendothelial migration of leukocytes and LIM domain binding 2: The Stockholm Atherosclerosis Gene Expression (STAGE) study

KAUST Repository

Hägg, Sara

2009-12-04

Environmental exposures filtered through the genetic make-up of each individual alter the transcriptional repertoire in organs central to metabolic homeostasis, thereby affecting arterial lipid accumulation, inflammation, and the development of coronary artery disease (CAD). The primary aim of the Stockholm Atherosclerosis Gene Expression (STAGE) study was to determine whether there are functionally associated genes (rather than individual genes) important for CAD development. To this end, two-way clustering was used on 278 transcriptional profiles of liver, skeletal muscle, and visceral fat (n =66/tissue) and atherosclerotic and unaffected arterial wall (n =40/tissue) isolated from CAD patients during coronary artery bypass surgery. The first step, across all mRNA signals (n =15,042/12,621 RefSeqs/genes) in each tissue, resulted in a total of 60 tissue clusters (n= 3958 genes). In the second step (performed within tissue clusters), one atherosclerotic lesion (n =49/48) and one visceral fat (n =59) cluster segregated the patients into two groups that differed in the extent of coronary stenosis (P=0.008 and P=0.00015). The associations of these clusters with coronary atherosclerosis were validated by analyzing carotid atherosclerosis expression profiles. Remarkably, in one cluster (n =55/54) relating to carotid stenosis (P =0.04), 27 genes in the two clusters relating to coronary stenosis were confirmed (n= 16/17, P<10 -27and-30). Genes in the transendothelial migration of leukocytes (TEML) pathway were overrepresented in all three clusters, referred to as the atherosclerosis module (A-module). In a second validation step, using three independent cohorts, the Amodule was found to be genetically enriched with CAD risk by 1.8-fold (P<0.004). The transcription co-factor LIM domain binding 2 (LDB2) was identified as a potential high-hierarchy regulator of the A-module, a notion supported by subnetwork analysis, by cellular and lesion expression of LDB2, and by the

Selection and validation of appropriate reference genes for quantitative real-time PCR analysis in Salvia hispanica.

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Rahul Gopalam

Full Text Available Quantitative real-time polymerase chain reaction (qRT-PCR has become the most popular choice for gene expression studies. For accurate expression analysis, it is pertinent to select a stable reference gene to normalize the data. It is now known that the expression of internal reference genes varies considerably during developmental stages and under different experimental conditions. For Salvia hispanica, an economically important oilseed crop, there are no reports of stable reference genes till date. In this study, we chose 13 candidate reference genes viz. Actin11 (ACT, Elongation factor 1-alpha (EF1-α, Eukaryotic translation initiation factor 3E (ETIF3E, alpha tubulin (α-TUB, beta tubulin (β-TUB, Glyceraldehyde 3-phosphate dehydrogenase (GAPDH, Cyclophilin (CYP, Clathrin adaptor complex (CAC, Serine/threonine-protein phosphatase 2A (PP2A, FtsH protease (FtsH, 18S ribosomal RNA (18S rRNA, S-adenosyl methionine decarboxylase (SAMDC and Rubisco activase (RCA and the expression levels of these genes were assessed in a diverse set of tissue samples representing vegetative stages, reproductive stages and various abiotic stress treatments. Two of the widely used softwares, geNorm and Normfinder were used to evaluate the expression stabilities of these 13 candidate reference genes under different conditions. Results showed that GAPDH and CYP expression remain stable throughout in the different abiotic stress treatments, CAC and PP2A expression were relatively stable under reproductive stages and α-TUB, PP2A and ETIF3E were found to be stably expressed in vegetative stages. Further, the expression levels of Diacylglycerol acyltransferase (DGAT1, a key enzyme in triacylglycerol synthesis was analyzed to confirm the validity of reference genes identified in the study. This is the first systematic study of selection of reference genes in S. hispanica, and will benefit future expression studies in this crop.

Aging-dependent DNA hypermethylation and gene expression of GSTM1 involved in T cell differentiation.

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Yeh, Shu-Hui; Liu, Cheng-Ling; Chang, Ren-Chieh; Wu, Chih-Chiang; Lin, Chia-Hsueh; Yang, Kuender D

2017-07-25

This study investigated whether aging was associated with epigenetic changes of DNA hypermethylation on immune gene expression and lymphocyte differentiation. We screened CG sites of methylation in blood leukocytes from different age populations, picked up genes with age-related increase of CG methylation content more than 15%, and validated immune related genes with CG hypermethylation involved in lymphocyte differentiation in the aged population. We found that 12 genes (EXHX1、 IL-10、 TSP50、 GSTM1、SLC5A5、SPI1、F2R、LMO2、PTPN6、FGFR2、MMP9、MET) were associated with promoter or exon one DNA hypermethylation in the aged group. Two immune related genes, GSTM1 and LMO2, were chosen to validate its aging-related CG hypermethylation in different leukocytes. We are the first to validate that GSTM1_P266 and LMO2_E128 CG methylation contents in T lymphocytes but not polymorphonuclear cells (PMNs) or mononuclear cells (MNCs) were significantly increased in the aged population. The GSTM1 mRNA expression in T lymphocytes but not PMNs or MNCs was inversely associated with the GSTM1 CG hypermethylation levels in the aged population studied. Further studies showed that lower GSTM1 CG methylation content led to the higher GSTM1 mRNA expression in T cells and knockdown of GSTM1 mRNA expression decreased type 1 T helper cell (Th1) differentiation in Jurkat T cells and normal adult CD4 T cells. The GSTM1_P266 hypermethylation in the aged population associated with lower GSTM1 mRNA expression was involved in Th1 differentiation, highlighting that modulation of aging-associated GSTM1 methylation may be able to enhance T helper cell immunity in the elders.