Gene expression of bovine embryo
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ABSTRACT:
ORGANISM(S): Bos taurus
PROVIDER: GSE1414 | GEO | 2004/11/24
SECONDARY ACCESSION(S): PRJNA89937
REPOSITORIES: GEO
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Project description:The objective of the present study was to use our own fabricated bovine liver cDNA microarray to profile genome-wide expression patterns of genes in the liver of cow throughout pregnancy. Ten-microgram of pooled liver total RNA obtained from nonpregnant cycling cows was reverse transcribed in the presence of cyanine-3-fluorescent dye (Cy3)-conjugated dUTP (Amersham Pharmacia Biotech) by using Superscript II reverse transcriptase (Life Technologies, Rockville, MD) to yield Cy3 fluorescence-labeled control cDNA probe. Similarly, liver total RNA obtained from cows on days 19, 27, 49, 58, 150 and 245 of pregnancy was separately reverse transcribed in the presence of Cy5-conjugated dUTP by using Superscript II reverse transcriptase to yield Cy5 fluorescence-labeled test cDNA probe. After a 2-h reverse transcription reaction at 42oC, RNA was degraded by addition of 1.5 µl of an alkaline solution (1N NaOH / 20 mM EDTA), and neutralized by addition of 1.5 µl 1N HCl. The labeled control cDNA probe and test cDNA probe were then mixed and washed by centrifugation with TE (Tris-EDTA, pH 7.0) first and then with TE, 20 µg Salmon sperm DNA, 20 µg polyA and 20 µg yeast RNA in a Microcon YM-30 column (Millipore, Bedford, MA). The concentrated probe mix was adjusted with TE to a volume of 24.8 µl, denatured at 100oC for 2 min, spun for a few min and made to a final hybridization volume of 31 µl with 5.27 µl 20XSSC and 0.93 µl 10% SDS and kept at room temperature until used. Before hybridization, microarray glass slides were immersed in 0.2% SDS for 2 min followed by two washes each 2 min in autoclaved Milli Q water, and subjected to blocking in 180 ml of Methyl Pyrrolidinone (Aldrich) containing 2.7 g Succinic Anhydride (WAKO, Japan) and 15.3 ml 1M Boric acid (pH 8.0) solution for 20 min. Slides were then washed with autoclaved Milli Q water, and the spotted cDNA targets (microarray) were denatured in boiling water for 2 min. The slides were dehydrated in 100% ethanol for 2 min and air dried by spinning at a low speed. The mixture of labeled probes, for example, the control (Cy3) and test (Cy5), were then applied to the microarray, placed a cover slip carefully and incubated at 65oC for 14 – 16 h in a custom slide chamber with humidity maintained by a small reservoir of 3 x SSC. In addition, 3 - 6 µl of 3 x SSC was spotted at each corner of the slide, as far away from the array as possible. After incubation for 14 – 16 h at 65oC, the slides were washed in 2 x SSC / 0.03% SDS for 2 min, followed by washing in 2 x SSC, 1 x SSC and 0.2 x SSC, each for 2 min with gentle agitation, and air dried by spinning at a low speed. All hybridizations were performed in duplicate except those of days 19 and 27, where no reverse labeling was done. In addition, day 245 of pregnancy had three samples hybridized with two of them being labeled using the same dye combination and the other is reverse labeled. In the reverse labeling procedure, for example, the control liver cDNA and test liver cDNA, which had been first labeled with fluorescent dyes Cy3 and Cy5, respectively, were then labeled with Cy5 and Cy3, respectively. The microarray hybridization images were immediately scanned by GenePix 4000B (Axon Instrument, Union City, CA). The images acquired by scan were analyzed by GenePix Pro 4.0 software. The absolute feature (microarray spot) and background intensity of Cy3 and Cy5 for each feature on the array was obtained for the hybridized images. The local background intensity of each spot was smoothed by the local weight regression smoother (lowess smoother) and subtracted from feature intensity data. The subtracted intensity data were subjected to non-parametric regression and local variance normalization. The non-parametric regression can reduce intensity-depended biases. Compared with the linear regression, the accuracy is improved, if the points in scatter plot of Cy3 vs. Cy5 were not distributed around the straight line. The local variance normalization controls the noise (background) in the raw data to a greater extent where the normalized data, in many cases, did not show significant fold-differences in comparison with background-subtracted raw intensity ratios, which frequently displayed higher fold-differences. Thus, the variance method that we employed to bovine liver array data has produced much reliable normalized ratios. To group liver genes with similar expression patterns throughout bovine pregnancy, two clustering algorithm were employed. The hierarchical clustering algorithm was performed using the software, Cluster 3.0, created and made freely available by Dr. Michiel de Hoon (http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/cluster/software.htm) based on the original version written by Dr. Michael Eisen (http://rana.lbl.gov/), and the software TreeView (http://rana.lbl.gov/). For hierarchical clustering, genes with either 2 or more than 2-fold induction or 2 or more than 2-fold repression at least at one point of the sampling period were selected. All ratio values were log transformed (base 2) to treat inductions or repressions of identical magnitude as numerically equal but with opposite sign, and subjected to centroid linkage clustering. Self-Organizing Maps (SOMs) algorithm was performed using the software GeneCluster 2 made freely available by Whitehead Institute Center for Genome Research (http://www-genome.wi.mit.edu/cancer/software/genecluster2/gc2.html). The SOMs were performed on the present data to better visualization of clusters of genes with their expression patterns plotted on an x-y axis. For SOMs, genes with either 1.5-fold (and above) induction or 1.5-fold (and above) repression at least at one point of the sampling period were selected. The minimum fold difference i.e., 1.5-fold, chosen for the analyses in the present study was based on the calculation that the technical variation contributing to the expression level of each individual gene due either to different labeling efficiencies of cyanine dyes or labeling procedure or both, was found to be within the range of 1.41-fold induction or repression. Therefore, either the induction or the repression of a particular gene by 1.5-fold or above was considered significant. Keywords = differential liver gene expression Keywords = bovine pregnancy Keywords = hierarchical clustering Keywords = self-organizing maps Keywords: time-course
2003-11-14 | GSE458 | GEO
Project description:To identify Six1 target genes, we chose the mK4 cell line that represents later metanephric mesenchyme of the embryonic kidney. The cells were infected with adenovirus vectors (AxCAwt) overexpressing VP16-Six1wt or VP16-Six1W171R and cultured for 24h. Total RNA was extracted using Isogen reagent (Nippon Gene), treated with RNase-free DNase (Roche Diagnostics) and purified with RNeasy Midi Kit (QIAGEN). Poly A+ RNA was selected using Oligotex-dT30 latex beads (TaKaRa). Poly A+ RNA (20 µg) was reverse transcribed using an oligo(dT) primer in the presence of aminoallyl dUTP without the addition of spike-in controls. Then, single-stranded cDNAs were coupled with Cy3 (AxCAwt VP16-Six1wt infected sample) or Cy5 (AxCAwt VP16-Six1W171R infected sample) dyes, and the labeled probes were purified with QIAquick PCR Purification kit (QIAGEN). Hybridization to the microarray was carried out at 65°C for 17h according to the manufacturer's instruction. The arrays were washed, dried and scanned using ScanArray 5000 (GSI Lumonics) at two different PMT voltage settings (high and low) to avoid signal saturation. Cy3 and Cy5 intensities for each spot on the array were determined by QuantArray software (Version 3.0.0.0, GSI Lumonics). The raw data thus obtained was processed and the Cy3 to Cy5 ratios were calculated as follows: 1) subtraction of the fluorescence intensity of negative control spots as background from the intensity of each of the Cy3 and Cy5 spots, 2) normalization of the entire data set using the global normalization method, 3) elimination of spots with high background intensity for either dye, and 4) determination of the Cy3 to Cy5 ratios. To identify Six4 target genes, we chose the mK4 cell line that represents later metanephric mesenchyme of the embryonic kidney. The cells were infected with adenovirus vectors (AxCAwt) overexpressing VP16-Six4wt or VP16-Six4W263R and cultured for 24h. Total RNA was extracted using Isogen reagent (Nippon Gene), treated with RNase-free DNase (Roche Diagnostics) and purified with RNeasy Midi Kit (QIAGEN). Poly A+ RNA was selected using Oligotex-dT30 latex beads (TaKaRa). Poly A+ RNA (20 µg) was reverse transcribed using an oligo(dT) primer in the presence of aminoallyl dUTP without the addition of spike-in controls. Then, single-stranded cDNAs were coupled with Cy3 (AxCAwt VP16-Six4wt infected sample) or Cy5 (AxCAwt VP16-Six4W263R infected sample) dyes, and the labeled probes were purified with QIAquick PCR Purification kit (QIAGEN). Hybridization to the microarray was carried out at 65°C for 17h according to the manufacturer's instruction. The arrays were washed, dried and scanned using ScanArray 5000 (GSI Lumonics) at two different PMT voltage settings (high and low) to avoid signal saturation. Cy3 and Cy5 intensities for each spot on the array were determined by QuantArray software (Version 3.0.0.0, GSI Lumonics). The raw data thus obtained was processed and the Cy3 to Cy5 ratios were calculated as follows: 1) subtraction of the fluorescence intensity of negative control spots as background from the intensity of each of the Cy3 and Cy5 spots, 2) normalization of the entire data set using the global normalization method, 3) elimination of spots with high background intensity for either dye, and 4) determination of the Cy3 to Cy5 ratios. Keywords: other
2005-07-20 | GSE2043 | GEO
Project description:Alterations in gene expression in FVB/NJ mouse liver following 4-nonylphenol (4-NP) treatment for 32 weeks. Mice were treated with 45 mg/kg/day 4-NP for 32 weeks, livers excised and differential gene expression determined. Samples 1 and 2 are controls and samples 3 and 4 are mice treated with 4-NP. Arrays were visualized from the K-screen, and analyzed and quantified with a phosphoimager (Molecular Imager FX, Bio-Rad, Hercules, CA) and the ResGen PathwaysTM Universal Microarray Analysis SoftwareTM (Research Genetics, Carlsbad, CA). Local background was subtracted automatically from the individual spot intensities, and spot intensities were normalized to the mean intensity of all spots on the array. This is called datapoint normalization on the ResGen Pathways Microarray Analysis SoftwareTM. Normalized gene intensities on the arrays probed with 4-NP treated mouse livers and untreated mouse liver cDNA were compared, and fold differences were calculated. Keywords: ordered
2004-03-20 | GSE1083 | GEO
Project description:miRNA profiling of human tonsilar B lymphocytes (naïve B cells, centroblasts and memory B cells) and tonsilar T cells, analyzing the 470 human miRNAs present in miRBase V9.1. B cell subpopulations and T cells were purified using specific antibodies, magnetic beads and the AutoMACS system (Miltenyi Biotec) from reactive tonsils obtained from routine tonsilectomies. Informed consents and the Institutional Review Board approval were obtained. Total RNA was extracted from cell pellets using the mirVana™ miRNA Isolation Kit (Ambion), and sent to LC Sciences facility for microarray hybridization using microfluidics technology. FirstChoice® Human Skeletal Muscle Total RNA (Ambion) was used as common reference for all hybridizations. Background substracted and normalized data from each channel was used to calculate log ratios sample/reference. Keywords: miRNA profiling Dual channel experiments using FirstChoice® Human Skeletal Muscle Total RNA (Ambion) as common reference for all hybridizations. Reference was labeled with Cy5 and the lymphocyte extracted RNA with Cy3. Biological replicates: 4 for each B cell subpopulation (centroblasts, naïve and memory B cells) and 3 for T cells, all of them purified from reactive tonsils with specific antibodies and magnetic beads. Microarray hybridization was performed at LC Sciences, using slides containing in situ synthesized oligonucleotides to detect the 470 miRNAs present in miRBase V9.1. Probes hsa-miR-337 and hsa-miR-542-5p were excluded due to systematic dye bias, according to the manufacturer intructions. Background substracted and normalized detectable data was used to calculate log ratios sample/reference. Background is determined using a regression-based background mapping method. The regression is performed on 5% to 25% of the lowest intensity data points excluding blank spots. Raw data matrix is then subtracted by the background matrix. Normalization was carried out using a LOWESS (Locally-weighted Regression) method on the background-subtracted data. A transcript to be listed as detectable must meets at least two conditions: signal intensity higher than 3×(background standard deviation) and spot CV < 0.5. CV is calculated by (standard deviation)/(signal intensity). When repeating probes are present on an array, a transcript is listed as detectable only if the signals from at least 50% of the repeating probes are above detection level.
2009-01-27 | E-GEOD-12934 | biostudies-arrayexpress
Project description:miRNA profiling of human Diffuse Large B Cell Lymphoma (DLBCL) cell lines derived from the two main subtypes of this disease: Activated B Cell like (ABC-DLBCL) and Germinal Center B cell like (GCB-DLBCL), analyzing the 711 human miRNAs present in miRBase V10.0. Five ABC-like DLBCL cell lines (RIVA, Oci-Ly3, Oci-Ly10, HBL1 and U2932) and three GCB-like DLBCL cell lines (Oci-Ly7, Oci-Ly19 and SUDHL-6) were cultured in IMDM (Cellgro) with 20% human plasma, 1% penicillin/streptomycin/L-glutamine (Cellgro,) and 0,2% beta mercaptoethanol (Invitrogen). Total RNA was extracted from cell pellets using the mirVana™ miRNA Isolation Kit (Ambion), and sent to LC Sciences facility for microarray hybridization using microfluidics technology. FirstChoice® Human Skeletal Muscle Total RNA (Ambion) was used as common reference for all hybridizations. Background substracted and normalized data from each channel was used to calculate log ratios sample/reference. Keywords: miRNA profiling Dual channel experiments using FirstChoice® Human Skeletal Muscle Total RNA (Ambion) as common reference for all hybridizations. Reference was labeled with Cy5 and the cell line extracted RNA with Cy3. Biological replicates: 5 ABC-DLBCL cell lines and 3 GCB-DLBCL cell lines. Microarray hybridization was performed at LC Sciences, using slides containing in situ synthesized oligonucleotides to detect the 711 miRNAs present in miRBase V10.0. Probes hsa-miR-337 and hsa-miR-542-5p were excluded due to systematic dye bias, according to the manufacturer intructions. Background substracted and normalized detectable data was used to calculate log ratios sample/reference. Background is determined using a regression-based background mapping method. The regression is performed on 5% to 25% of the lowest intensity data points excluding blank spots. Raw data matrix is then subtracted by the background matrix. Normalization was carried out using a LOWESS (Locally-weighted Regression) method on the background-subtracted data. A transcript to be listed as detectable must meets at least two conditions: signal intensity higher than 3×(background standard deviation) and spot CV < 0.5. CV is calculated by (standard deviation)/(signal intensity). When repeating probes are present on an array, a transcript is listed as detectable only if the signals from at least 50% of the repeating probes are above detection level.
2009-01-27 | E-GEOD-12933 | biostudies-arrayexpress
Project description:Experiment Design 1) Experiment Type normal vs diseased comparison, time course 2) Experimental Factor response to viral infection - SHIV89.6P 3) Number of hybridizations 60 4) Common Reference No 5) Quality Control Steps 4 technical replicate hybridizations per animal (3 replicate hybridizations for C89115M, C95067F) dual spotting of gene per array multiple spotting of select genes per array 2 biological replicates (2 different animals) per time point dye swaps 6) Experiment Description 4 cynomolgus monkeys (Macaca fascicularis) were infected with TCID50 of SHIV89.6P. Whole blood RNA was collected at 0, 1, 2, 4 and 5 weeks post-infection. Post-infection samples were competitively hybridized with pre-infected samples for each individual animal. Unpublished Data 7) Qualifier, value, source 2.2. Samples: samples used, extract preparation and labeling 2.2.1. Biosource properties 1) Organism (NCBI taxonomy) Macaca fascicularis 2) Contact details for sample Dr Erling W Rud Animal Resources Division, Health Canada. Sir Frederick Banting Research Centre Building 22, Room C308, postal locator 2203E Tunneys' Pasture Ottawa,Ontario, Canada K1A 0L2 Tel:(613) 957-8049 FAX:(613) 941-6625 erling_rud@hc-sc.gc.ca 3) Cell Type not applicable 4) Sex C88015F - female C89115M - male C94071M - male C95067F - female 5) Age C88015F - 13 years C89115M - 12 years C94071M - 7 years C95067F - 6 years 6) Developmental Stage adult 7) Organism Part peripheral whole blood 8) Strain or line not applicable 9) Genetic variation not applicable 10) Individual number C88015F, C89115M, C94071M & C95067F 11) Individual genetic characteristics not applicable 12) Disease state normal, AIDS 13) Targeted cell type blood 14) Cell line not applicable 2.2.2. Biomaterial manipulation 1) Growth conditions not applicable 2) In vivo treatments description - 4 cynomolgus monkeys (Macaca fascicularis) were infected intravenously with TCID50 of SHIV89.6P. 10 ml of peripheral blood was drawn at -2, 0, 1, 2, 4 and 5 weeks post-infection. 3) In vitro treatment not applicable 4) Treatment type infection 5) Compound not applicable 6) Separation technique not applicable 2.2.3. Hybridization extract preparation 1) Extraction method PAXgene peripheral blood RNA preparation 10 ml of peripheral blood was drawn from each animal directly into 4 PAXgene Blood RNA Tubes (QIAGEN #762125) according to manufacturer's protocol (http://www.qiagen.com/literature/Handbooks/PDF/DNA_RNA_isolation_clinical/INT/PAXgene_Blood_RNA/PaxgeneBloodRNAtube.pdf) Total RNA was purified using PAXgene Blood RNA kit (QIAGEN # 762134) according to manufacturer's protocol http://www.qiagen.com/literature/Handbooks/PDF/DNA_RNA_isolation_clinical/INT/PAXgene_Blood_RNA/1017455PAXgeneBloodRNA_prot.pdf) 2) Nucleic acid type total RNA 3) Amplification Method Total RNA was amplified using the Ambion MessageAmp aRNA kit (#1750), an Eberwine based method, with slight modifications to the manufacturer's protocol (http://www.transnet.ca/Amplification%20Protocol.htm). 2.2.3. Sample labeling 1) Amount of nucleic acid labeled 6 micrograms of aRNA was labeled with Cy3/Cy5 for hybridization 2) Label used Cy5 & Cy3 3) Label incorporation method aRNA was labelled by reverse transcription using the standard protocol of the Ontario Cancer Institute with slight modifications (http://www.transnet.ca/Hybridization%20Protocol_2.htm) 2.2.5. Spiking controls 1) Spiking control feature OCI Human 19k3-part1 OCI Human 19k3-part2 2) Spike type and qualifier not applicable 3) Qualifier, value, source not applicable 2.3. Hybridization procedure and parameters 2) Hybridization Protocol Protocol - (http://www.transnet.ca/Hybridization%20Protocol_2.htm) Solution Hybridization buffer: DIG solution (Roche cat.#1603558) supplemented with 0.45 ug/ul yeast tRNA, 0.45 ug/ul salmon sperm DNA Blocking agent not applicable Slide blocking not applicable Probe blocking: 0.45 ug/ul yeast tRNA, 0.45 ug/ul salmon sperm DNA during hybridization Wash procedure 3x15 min with 1xSSC, 0.1% SDS at 50 degrees Celsius, 3 fast washes in 1xSSC at 50 degrees Celsius Quantity of labelled target used all material generated from 6 ug amplified RNA per sample Time 18 hr (overnight) hybridization Concentration 0.2 ug/ul of aRNA per hybridization Volume 60 ul Temperature 30 degrees Celsius Description of the hybridization chamber hybridizations were incubated in a microscope slide box stored within a tissue culture incubator Qualifier, value, source not applicable 2.4. Measurements 2.4.1. Raw data Scanning protocol Scanning hardware: Scanarray Express Microarray Scanner, Packard Biosciences Scanning software: Scanarray Express Microarray Analysis System v1.1 Build #9 Scan Parameters Laser power: see individual image files in section 2.4.1 Spatial resolution:10 microns PMT gain: 60% 2.4.2. Image analysis and quantitation Image analysis software: Quantarray v.3.0, Packard BioSciences Availability: No longer commercially available Quantitation Parameters: Array Pattern: Spot rows: 25 Spot columns: 24 Spot spacing (vertical): 170 microns Spot spacing (horizontal): 170 microns Interstitial spacing: Off Array rows: 8 Array columns: 4 Array spacing (vertical): 4500 microns Array spacing (horizontal): 4500 microns Auto-adjustable Grid: Grid elasticity: 50/100 Spot elasticity: 50/100 Quantitation: Method: Fixed Circle Crosstalk correction: No Normalized to brightest: No Background subtraction: No Gene database file: for OCI Human 19k3-part1- H19k3a.qa (attached) for OCI Human 19k3-part2- H19k3b.qa (attached) Fixed circle quantitation parameters: Spot diameter: 60 microns Inner background diameter: 180 microns Outer background diameter: 200 microns Signal low percentile: 45 Signal high percentile: 95 Background low percentile: 5 Background high percentile: 55 Quantification output: Mean Intensity Quality Criteria Confidence calculation: Minimum Tolerance and weight: None selected Replicates: Combine replicates: no 2.4.3. Normalized and summarized data Data processing protocol Background subtraction and normalization Background subtraction and normalization was performed using the Quantarray Normalization Excel macro on individual quantitation output files. Each channel was background subtracted using the equation: ch Bkg. Subtr. Intensity = ch intensity - ch Bkg. Normalization strategy: total array Normalization algorithm: log ratio median centering Median log ratio = median(log2(ch1 Bkg. Subtr. Intensity) - log2(ch2 Bkg. Subtr. Intensity)) Normalization factor = 2^ median log ratio Normalized ch2 intensity = ch2 intensity*Normalization factor Statistical Analysis The background subtracted normalized intensities were used for statistical analysis. All spot intensities for within-chip, repeat hybridization, fluor-flip hybridization and biological replicates for each time point post-infection were compiled and tested for significance testing using the software package ArrayStat v.1.0, Imaging Research. ArrayStat parameters: Model selection: Manual Model selected: Proportional model with offsets Outlier detection: yes Threshold detection: Manual Threshold detected: p<0.01 Minimum No. of replicates: 12 (for 1 & 5 wks PI), 11 (for 2 & 4 wks PI) Conditions: Dependent Random Error Estimation Method: Small Sample Test: t-test Normalization: By median Nominal alpha: 0.05 Multiple Test correction: False Discovery Rate Keywords = SHIV89.6P Keywords = HIV Keywords = nonhuman primate Keywords = cDNA microarray Keywords = time course Keywords: time-course
2004-11-03 | GSE1854 | GEO
Project description:124 gastric biopsies comprising of Normals, Intestinal Metaplasia, Chronic Gastritis and Carcinomas are profiled. The ratio metric is given by (Biological sample / Universal Reference). The Biological Samples are labeled with Cy5 (Green) and the Pooled Normal Biopsies RNA is always labeled with Cy3 (Red). The arrays were scanned using a ScanArray 5000 scanner (Perkin-Elmer) and data extraction was done using Quantarray (GSI Lumonics). Subsequently, the data was imported into GeneSpring (Silicon Genetics) and intensity dependent LOWESS normalization was performed. The 7383 genes were filtered using an intensity in the reference channel (Cy3) of 300. This corresponded to 2 standard deviations above the mean for the background signal. Background singal was calculated using the empty wells/spots on the array and the average of 4 different positions on the slide were used. Keywords: other
2005-07-25 | GSE2669 | GEO
Project description:Mice used in this study were 129/sv males, 8-15 weeks of age, which were housed individually and received water ad libitum. Normal fed animals were fed before and during the 48h experiment with standard food ad libitum. Sugar fed animals were fed before the experiment with standard food ad libitum and during the 48h experiment with 50% (w/v) sugar solution (40% glucose, 10% sucrose). Mice were killed by CO2 asphyxiation. The livers were snap-frozen in liquid nitrogen and stored at -80 degrees C. Total RNA was prepared using the Nucleospin RNA L kit (Macherey-Nagel, Düren, Germany), with an additional step in which the final eluate was used for a subsequent elution step. PolyA RNA was extracted with the Ambion (Ambion Inc, Austin, USA) Purist kit according to the manufacturer's protocols. Equal amounts of polyA RNA were pooled to generate pools of all animals. Pool1, normal = 3 animals (N1, N2, N3), pool2, normal = 3 animals (N4, N5, N6), pool3, = 4 animals (N7, N8, N9, N10), pool1, sugar = 3 animals (Su1, Su2, Su3), pool2, sugar = 3 animals (Su4, Su5, Su6), pool3, sugar = 4 animals (Su7, Su8, Su9, Su10). Labeled cDNA was synthesized from 1.5 µg polyA RNA using the Amersham (Amersham Europe, Freiburg, Germany) direct cDNA labeling kit. Removal of the unincorporated dyes and concentration of the target were done with Microcon 30 (Millipore, Bedford, MA) spin columns according to the manufacturer's instructions. The concentrated probes were hybridized to the microarray in 1x dig easy hyb buffer (Hoffman-la Roche, Basel, CH) overnight at 42 degrees C. After hybridization the microarrays are washed 5’ in 2x SSC, 0.1% SDS at 42 degrees C; 10’ in 0.1x SSC, 0.1% SDS at RT; 4 times 1’ in 0.1x SSC at RT and shortly dipped into 0.01x SSC. Drying is performed in centrifuge on a microtiterplate holder at 800 rpm for 7’. Slides are stored in dark until they are scanned. Arrays were scanned using the dual laser scanner Axon 4000B and the corresponding software Genepix 4 (Axon Inc., Union City, CA, USA). Both channels (532 nm for Cy3 and 635 nm Cy5) were scanned in parallel and stored as 16 bit tiff files. The absolute intensity values span the range from 0 to 65,535. The scans were performed with a resolution of 10 µm. From each spot with a mean diameter of 100 µm, 100 data pixels were recorded. Individual local background area around the spots were defined, which included approximately 400 pixels and excludes neighboring spots. For each channel, the raw data was calculated as the median intensity of all foreground pixels with respect to all background pixels. Each array was scanned three times (low, medium and high scan) with different signal amplification factors (voltage settings of the photo multiplier tubes), but with the same laser power. The channels for Cy3 and Cy5 were balanced in each scan for approximately the same intensity profile. In the low scan no spot was saturated, in the high scan the signal amplification for Cy5 was set to approximately 80% of maximum and the Cy3 amplification was adjusted to this. The settings used in the medium scan lie between the low and the high scan. This method for scanning has several advantages. In the low scan where no spot is in saturation, it is possible to calculate the real ratio for genes with high expression levels; however, those with a low expression level are most likely not recognized. In order not to lose these, a high scan is made; in this case, the information on the saturated spots is lost, so the two scans complement each other. The medium scan produces additional values for subsequent calculations. By scanning the arrays three times, errors which occur while recording and which might increase the error factor in the normalization are averaged. The data processing was automated in a Visual Basic/Excel (Microsoft) program, which integrates the following steps. Raw data are derived from the result files generated by scanning and picture analysis software Genepix. The spot diameter is to lie in the range from 80 to 120 µm otherwise these spots are not included in analysis. From the pixel to pixel ratios between the foreground values of both colors, the standard deviation (SD) is calculated. Those spots which show a ratio SD of higher than 3 are excluded from analysis due to inconsistency. The foreground signal of each spot is corrected by subtracting the corresponding local background. Resulting values which are lower than the background are replaced by the background value. This defines the minimum measurement threshold as the background and avoids calculations of completely wrong ratios, e.g., if the background corrected value for one channel is close to zero. Spots are marked as saturated in one channel if more than 10% of the foreground pixels are at the highest absolute value. From the unsaturated data points of all three scans, linear regression between the low and medium, and between low and high scans, are calculated for both colors. Taking these regressions, the values of saturated spots are replaced by estimated ones which reflect the real intensity. The generated data set of each scan is normalized afterwards based on the intensity-dependent methods as described by Yang et al (80). The ratios are calculated as log2 transformed values: M=log2 (Cy5/Cy3). Number describing the spot intensity A=log2sqrt (Cy5*Cy3) is calculated according to Yang et al (80). A within pin-tip group loess fit to the MA-plot was made. The loess scatter plot smoother performs robust locally fits using a tricube function to weight the values relative to the median point in the intensity interval. As interval size 20% was chosen, which corresponds to 180 data points in a pin-tip group containing 30 by 30 spots. After combining the normalized data from all blocks the data sets of all scans are additionally normalized using a global approach. The normalization was performed so that the sum of all log transformed ratios (M) is 0. All statistical normalizations are based on the assumption that (1) the majority of genes are not changed in their expression and (2) that the overall up and down regulations statistically compensate each other in sum. Taking this into account, the standard deviation in the ratios of the stable genes (80% of the most unchanged genes) could be seen as the measurement noise of the array experiments. To be able to compare the different scans and different normalized microarrays, the SD of the stable genes ratios was adjusted to a medium estimated value of 0.2, which is dependent on the used array system. This value does not influence the subsequent statistical analysis because the normal distribution of the data is not changed. For each microarray the normalized and adjusted log ratios of the three scans are averaged. Keywords = nutrient response Keywords = starvation Keywords = liver Keywords = anti-aging Keywords = longevity Keywords: repeat sample
2004-02-09 | GSE851 | GEO
Project description:Mice used in this study were 129/sv males, 8-15 weeks of age, which were housed individually and received water ad libitum. Normal fed animals were fed before and during the 48h experiment with standard food ad libitum. Starved animals were fed before the experiment with standard food ad libitum and were starved during the 24h experiment. Mice were killed by CO2 asphyxiation. The livers were snap-frozen in liquid nitrogen and stored at -80 degrees C. Total RNA was prepared using the Nucleospin RNA L kit (Macherey-Nagel, Düren, Germany), with an additional step in which the final eluate was used for a subsequent elution step. PolyA RNA was extracted with the Ambion (Ambion Inc, Austin, USA) Purist kit according to the manufacturer's protocols. Equal amounts of polyA RNA were pooled to generate pools of all animals. Pool1, normal = 3 animals (N1, N2, N3), pool2, normal = 3 animals (N4, N5, N6), pool3, = 6 animals (N1, N2, N3, N4, N5, N6), pool1, sugar = 3 animals (St1, St2, St3), pool2, starved = 3 animals (St4, St5, St6), pool3, starved = 6 animals (St1, St2, St3, St4, St5, St6). Labeled cDNA was synthesized from 1.5 µg polyA RNA using the Amersham (Amersham Europe, Freiburg, Germany) direct cDNA labeling kit. Removal of the unincorporated dyes and concentration of the target were done with Microcon 30 (Millipore, Bedford, MA) spin columns according to the manufacturer's instructions. The concentrated probes were hybridized to the microarray in 1x dig easy hyb buffer (Hoffman-la Roche, Basel, CH) overnight at 42 degrees C. After hybridization the microarrays are washed 5’ in 2x SSC, 0.1% SDS at 42 degrees C; 10’ in 0.1x SSC, 0.1% SDS at RT; 4 times 1’ in 0.1x SSC at RT and shortly dipped into 0.01x SSC. Drying is performed in centrifuge on a microtiterplate holder at 800 rpm for 7’. Slides are stored in dark until they are scanned. Arrays were scanned using the dual laser scanner Axon 4000B and the corresponding software Genepix 4 (Axon Inc., Union City, CA, USA). Both channels (532 nm for Cy3 and 635 nm Cy5) were scanned in parallel and stored as 16 bit tiff files. The absolute intensity values span the range from 0 to 65,535. The scans were performed with a resolution of 10 µm. From each spot with a mean diameter of 100 µm, 100 data pixels were recorded. Individual local background area around the spots were defined, which included approximately 400 pixels and excludes neighboring spots. For each channel, the raw data was calculated as the median intensity of all foreground pixels with respect to all background pixels. Each array was scanned three times (low, medium and high scan) with different signal amplification factors (voltage settings of the photo multiplier tubes), but with the same laser power. The channels for Cy3 and Cy5 were balanced in each scan for approximately the same intensity profile. In the low scan no spot was saturated, in the high scan the signal amplification for Cy5 was set to approximately 80% of maximum and the Cy3 amplification was adjusted to this. The settings used in the medium scan lie between the low and the high scan. This method for scanning has several advantages. In the low scan where no spot is in saturation, it is possible to calculate the real ratio for genes with high expression levels; however, those with a low expression level are most likely not recognized. In order not to lose these, a high scan is made; in this case, the information on the saturated spots is lost, so the two scans complement each other. The medium scan produces additional values for subsequent calculations. By scanning the arrays three times, errors which occur while recording and which might increase the error factor in the normalization are averaged. The data processing was automated in a Visual Basic/Excel (Microsoft) program, which integrates the following steps. Raw data are derived from the result files generated by scanning and picture analysis software Genepix. The spot diameter is to lie in the range from 80 to 120 µm otherwise these spots are not included in analysis. From the pixel to pixel ratios between the foreground values of both colors, the standard deviation (SD) is calculated. Those spots which show a ratio SD of higher than 3 are excluded from analysis due to inconsistency. The foreground signal of each spot is corrected by subtracting the corresponding local background. Resulting values which are lower than the background are replaced by the background value. This defines the minimum measurement threshold as the background and avoids calculations of completely wrong ratios, e.g., if the background corrected value for one channel is close to zero. Spots are marked as saturated in one channel if more than 10% of the foreground pixels are at the highest absolute value. From the unsaturated data points of all three scans, linear regression between the low and medium, and between low and high scans, are calculated for both colors. Taking these regressions, the values of saturated spots are replaced by estimated ones which reflect the real intensity. The generated data set of each scan is normalized afterwards based on the intensity-dependent methods as described by Yang et al (80). The ratios are calculated as log2 transformed values: M=log2 (Cy5/Cy3). Number describing the spot intensity A=log2sqrt (Cy5*Cy3) is calculated according to Yang et al (80). A within pin-tip group loess fit to the MA-plot was made. The loess scatter plot smoother performs robust locally fits using a tricube function to weight the values relative to the median point in the intensity interval. As interval size 20% was chosen, which corresponds to 180 data points in a pin-tip group containing 30 by 30 spots. After combining the normalized data from all blocks the data sets of all scans are additionally normalized using a global approach. The normalization was performed so that the sum of all log transformed ratios (M) is 0. All statistical normalizations are based on the assumption that (1) the majority of genes are not changed in their expression and (2) that the overall up and down regulations statistically compensate each other in sum. Taking this into account, the standard deviation in the ratios of the stable genes (80% of the most unchanged genes) could be seen as the measurement noise of the array experiments. To be able to compare the different scans and different normalized microarrays, the SD of the stable genes ratios was adjusted to a medium estimated value of 0.2, which is dependent on the used array system. This value does not influence the subsequent statistical analysis because the normal distribution of the data is not changed. For each microarray the normalized and adjusted log ratios of the three scans are averaged. Keywords = nutrient response Keywords = starvation Keywords = liver Keywords = anti-aging Keywords = longevity Keywords: repeat sample
2004-02-09 | GSE853 | GEO
Project description:Mice used in this study were 129/sv males, 8-15 weeks of age, which were housed individually and received water ad libitum. Normal fed animals were fed before and during the 48h experiment with standard food ad libitum. Starved animals were fed before the experiment with standard food ad libitum and were starved during the 48h experiment. Mice were killed by CO2 asphyxiation. The livers were snap-frozen in liquid nitrogen and stored at -80 degrees C. Total RNA was prepared using the Nucleospin RNA L kit (Macherey-Nagel, Düren, Germany), with an additional step in which the final eluate was used for a subsequent elution step. PolyA RNA was extracted with the Ambion (Ambion Inc, Austin, USA) Purist kit according to the manufacturer's protocols. Equal amounts of polyA RNA were pooled to generate pools of all animals. Pool1, normal = 3 animals (N1, N2, N3), pool2, normal = 3 animals (N4, N5, N6), pool3, = 4 animals (N7, N8, N9, N10), pool1, sugar = 3 animals (St1, St2, St3), pool2, starved = 3 animals (St4, St5, St6), pool3, starved = 4 animals (St7, St8, St9, St10). Labeled cDNA was synthesized from 1.5 µg polyA RNA using the Amersham (Amersham Europe, Freiburg, Germany) direct cDNA labeling kit. Removal of the unincorporated dyes and concentration of the target were done with Microcon 30 (Millipore, Bedford, MA) spin columns according to the manufacturer's instructions. The concentrated probes were hybridized to the microarray in 1x dig easy hyb buffer (Hoffman-la Roche, Basel, CH) overnight at 42 degrees C. After hybridization the microarrays are washed 5’ in 2x SSC, 0.1% SDS at 42 degrees C; 10’ in 0.1x SSC, 0.1% SDS at RT; 4 times 1’ in 0.1x SSC at RT and shortly dipped into 0.01x SSC. Drying is performed in centrifuge on a microtiterplate holder at 800 rpm for 7’. Slides are stored in dark until they are scanned. Arrays were scanned using the dual laser scanner Axon 4000B and the corresponding software Genepix 4 (Axon Inc., Union City, CA, USA). Both channels (532 nm for Cy3 and 635 nm Cy5) were scanned in parallel and stored as 16 bit tiff files. The absolute intensity values span the range from 0 to 65,535. The scans were performed with a resolution of 10 µm. From each spot with a mean diameter of 100 µm, 100 data pixels were recorded. Individual local background area around the spots were defined, which included approximately 400 pixels and excludes neighboring spots. For each channel, the raw data was calculated as the median intensity of all foreground pixels with respect to all background pixels. Each array was scanned three times (low, medium and high scan) with different signal amplification factors (voltage settings of the photo multiplier tubes), but with the same laser power. The channels for Cy3 and Cy5 were balanced in each scan for approximately the same intensity profile. In the low scan no spot was saturated, in the high scan the signal amplification for Cy5 was set to approximately 80% of maximum and the Cy3 amplification was adjusted to this. The settings used in the medium scan lie between the low and the high scan. This method for scanning has several advantages. In the low scan where no spot is in saturation, it is possible to calculate the real ratio for genes with high expression levels; however, those with a low expression level are most likely not recognized. In order not to lose these, a high scan is made; in this case, the information on the saturated spots is lost, so the two scans complement each other. The medium scan produces additional values for subsequent calculations. By scanning the arrays three times, errors which occur while recording and which might increase the error factor in the normalization are averaged. The data processing was automated in a Visual Basic/Excel (Microsoft) program, which integrates the following steps. Raw data are derived from the result files generated by scanning and picture analysis software Genepix. The spot diameter is to lie in the range from 80 to 120 µm otherwise these spots are not included in analysis. From the pixel to pixel ratios between the foreground values of both colors, the standard deviation (SD) is calculated. Those spots which show a ratio SD of higher than 3 are excluded from analysis due to inconsistency. The foreground signal of each spot is corrected by subtracting the corresponding local background. Resulting values which are lower than the background are replaced by the background value. This defines the minimum measurement threshold as the background and avoids calculations of completely wrong ratios, e.g., if the background corrected value for one channel is close to zero. Spots are marked as saturated in one channel if more than 10% of the foreground pixels are at the highest absolute value. From the unsaturated data points of all three scans, linear regression between the low and medium, and between low and high scans, are calculated for both colors. Taking these regressions, the values of saturated spots are replaced by estimated ones which reflect the real intensity. The generated data set of each scan is normalized afterwards based on the intensity-dependent methods as described by Yang et al (80). The ratios are calculated as log2 transformed values: M=log2 (Cy5/Cy3). Number describing the spot intensity A=log2sqrt (Cy5*Cy3) is calculated according to Yang et al (80). A within pin-tip group loess fit to the MA-plot was made. The loess scatter plot smoother performs robust locally fits using a tricube function to weight the values relative to the median point in the intensity interval. As interval size 20% was chosen, which corresponds to 180 data points in a pin-tip group containing 30 by 30 spots. After combining the normalized data from all blocks the data sets of all scans are additionally normalized using a global approach. The normalization was performed so that the sum of all log transformed ratios (M) is 0. All statistical normalizations are based on the assumption that (1) the majority of genes are not changed in their expression and (2) that the overall up and down regulations statistically compensate each other in sum. Taking this into account, the standard deviation in the ratios of the stable genes (80% of the most unchanged genes) could be seen as the measurement noise of the array experiments. To be able to compare the different scans and different normalized microarrays, the SD of the stable genes ratios was adjusted to a medium estimated value of 0.2, which is dependent on the used array system. This value does not influence the subsequent statistical analysis because the normal distribution of the data is not changed. For each microarray the normalized and adjusted log ratios of the three scans are averaged. Keywords = nutrient response Keywords = starvation Keywords = liver Keywords = anti-aging Keywords = longevity Keywords: repeat sample
2004-02-09 | GSE852 | GEO