CH1I_MEAN = Mean feature pixel intensity at wavelength 532 nm.; Type: integer; Scale: linear_scale

CH2I_MEAN = Mean feature pixel intensity at wavelength 635 nm.; Type: integer; Scale: linear_scale

CH1B_MEDIAN = The median feature background intensity at wavelength 532 nm.; Type: integer; Scale: linear_scale; Channel: Cy3 Channel; Background

CH2B_MEDIAN = The median feature background intensity at wavelength 635 nm.; Type: integer; Scale: linear_scale; Channel: Cy5 channel; Background

CH1D_MEAN = The mean feature pixel intensity at wavelength 532 nm with the median background subtracted.; Type: integer; Scale: linear_scale; Channel: Cy3 Channel

CH2D_MEAN = .The mean feature pixel intensity at wavelength 635 nm with the median background subtracted.; Type: integer; Scale: linear_scale; Channel: Cy5 channel

CH1I_MEDIAN = Median feature pixel intensity at wavelength 532 nm.; Type: integer; Scale: linear_scale

CH2I_MEDIAN = Median feature pixel intensity at wavelength 635 nm.; Type: integer; Scale: linear_scale

CH1B_MEAN = The mean feature background intensity at wavelength 532 nm.; Type: integer; Scale: linear_scale; Background

CH2B_MEAN = The mean feature background intensity at wavelength 635 nm.; Type: integer; Scale: linear_scale; Background

CH1D_MEDIAN = The median feature pixel intensity at wavelength 532 nm with the median background subtracted.; Type: integer; Scale: linear_scale

CH2D_MEDIAN = The median feature pixel intensity at wavelength 635 nm with the median background subtracted.; Type: integer; Scale: linear_scale

CH1_PER_SAT = The percentage of feature pixels at wavelength 532 nm that are saturated.; Type: integer; Scale: linear_scale

CH2_PER_SAT = The percentage of feature pixels at wavelength 635 nm that are saturated.; Type: integer; Scale: linear_scale

CH1I_SD = The standard deviation of the feature intensity at wavelength 532 nm.; Type: integer; Scale: linear_scale; Channel: Cy3 Channel

CH2I_SD = The standard deviation of the feature pixel intensity at wavelength 635 nm.; Type: integer; Scale: linear_scale; Channel: Cy5 channel

CH1B_SD = The standard deviation of the feature background intensity at wavelength 532 nm.; Type: float; Scale: linear_scale; Channel: Cy3 Channel; Background

CH2B_SD = The standard deviation of the feature background intensity at wavelength 635 nm.; Type: integer; Scale: linear_scale; Channel: Cy5 channel; Background

PERGTBCH1I_1SD = The percentage of feature pixels with intensities more than one standard deviation above the background pixel intensity, at wavelength 532 nm.; Type: integer; Scale: linear_scale

PERGTBCH2I_1SD = The percentage of feature pixels with intensities more than one standard deviation above the background pixel intensity, at wavelength 635 nm.; Type: integer; Scale: linear_scale

PERGTBCH1I_2SD = The percentage of feature pixels with intensities more than two standard deviations above the background pixel intensity, at wavelength 532 nm.; Type: integer; Scale: linear_scale

PERGTBCH2I_2SD = The percentage of feature pixels with intensities more than two standard deviations above the background pixel intensity, at wavelength 532 nm.; Type: integer; Scale: linear_scale

SUM_MEAN = The sum of the arithmetic mean intensities for each wavelength, with the median background subtracted.; Type: integer; Scale: linear_scale

SUM_MEDIAN = The sum of the median intensities for each wavelength, with the median background subtracted.; Type: integer; Scale: linear_scale

RAT1_MEAN = Ratio of the arithmetic mean intensities of each spot for each wavelength, with the median background subtracted. Channel 1/Channel 2 ratio, (CH1I_MEAN - CH1B_MEDIAN)/(CH2I_MEAN - CH2B_MEDIAN) or Green/Red ratio.; Type: float; Scale: linear_scale

RAT2_MEAN = The ratio of the arithmetic mean intensities of each feature for each wavelength, with the median background subtracted.; Type: float; Scale: linear_scale

RAT2_MEDIAN = The ratio of the median intensities of each feature for each wavelength, with the median background subtracted.; Type: float; Scale: linear_scale

PIX_RAT2_MEAN = The geometric mean of the pixel-by-pixel ratios of pixel intensities, with the median background subtracted.; Type: float; Scale: linear_scale

PIX_RAT2_MEDIAN = The median of pixel-by-pixel ratios of pixel intensities, with the median background subtracted.; Type: float; Scale: linear_scale

RAT2_SD = The geometric standard deviation of the pixel intensity ratios.; Type: float; Scale: linear_scale

TOT_SPIX = The total number of feature pixels.; Type: integer; Scale: linear_scale

TOT_BPIX = The total number of background pixels.; Type: integer; Scale: linear_scale

REGR = The regression ratio of every pixel in a 2-feature-diameter circle around the center of the feature.; Type: float; Scale: linear_scale

CORR = The correlation between channel1 (Cy3) & Channel 2 (Cy5) pixels within the spot, and is a useful quality control parameter. Generally, high values imply better fit & good spot quality.; Type: float; Scale: linear_scale

DIAMETER = The diameter in um of the feature-indicator.; Type: integer; Scale: linear_scale

X_COORD = X-coordinate of the center of the spot-indicator associated with the spot, where (0,0) is the top left of the image.; Type: integer; Scale: linear_scale

Y_COORD = Y-coordinate of the center of the spot-indicator associated with the spot, where (0,0) is the top left of the image.; Type: integer; Scale: linear_scale

TOP = Box top: int(((centerX - radius) - Xoffset) / pixelSize).; Type: integer; Scale: linear_scale

BOT = Box bottom: int(((centerX + radius) - Xoffset) / pixelSize).; Type: integer; Scale: linear_scale

LEFT = Box left: int(((centerY - radius) - yoffset) / pixelSize).; Type: integer; Scale: linear_scale

RIGHT = Box right: int(((centerY + radius) - yoffset) / pixelSize); Type: integer; Scale: linear_scale

FLAG = The type of flag associated with a feature: -100 = user-flagged null spot; -50 = software-flagged null spot; 0 = spot valid.; Type: integer; Scale: linear_scale

CH2IN_MEAN = Normalized value of mean Channel 2 (usually 635 nm) intensity (CH2I_MEAN/Normalization factor).; Type: integer; Scale: linear_scale; Channel: Cy5 channel

CH2BN_MEDIAN = Normalized value of median Channel 2 (usually 635 nm) background (CH2B_MEDIAN/Normalization factor).; Type: integer; Scale: linear_scale; Channel: Cy5 channel; Background

CH2DN_MEAN = Normalized value of mean Channel 2 (usually 635 nm) intensity with normalized background subtracted (CH2IN_MEAN - CH2BN_MEDIAN).; Type: integer; Scale: linear_scale; Channel: Cy5 channel

RAT2N_MEAN = Type: float; Scale: linear_scale

CH2IN_MEDIAN = Normalized value of median Channel 2 (usually 635 nm) intensity (CH2I_MEDIAN/Normalization factor).; Type: integer; Scale: linear_scale

CH2DN_MEDIAN = Normalized value of median Channel 2 (usually 635 nm) intensity with normalized background subtracted (CH2IN_MEDIAN - CH2BN_MEDIAN).; Type: integer; Scale: linear_scale

RAT1N_MEAN = Ratio of the means of Channel 1 (usually 532 nm) intensity to normalized Channel 2 (usually 635 nm) intensity with median background subtracted (CH1D_MEAN/CH2DN_MEAN). Channel 1/Channel 2 ratio normalized or Green/Red ratio normalized.; Type: float; Scale: linear_scale

RAT2N_MEDIAN = Channel 2/Channel 1 ratio normalized, RAT2_MEDIAN/Normalization factor or Red/Green median ratio normalized.; Type: float; Scale: linear_scale

LOG_RAT2N_MEAN = Log (base 2) of the ratio of the mean of Channel 2 (usually 635 nm) to Channel 1 (usually 532 nm) [log (base 2) (RAT2N_MEAN)].; Type: float; Scale: log_base_2

VALUE = Log (base 2) of the ratio of the median of Channel 2 (usually 635 nm) to Channel 1 (usually 532 nm) [log (base 2) (RAT2N_MEDIAN)].; Type: float; Scale: log_base_2","Image Adquisition - GenePix 4200A","Image Adquisition - Feature Extraction; Software and parameters for feature extraction.; Protocol Type = Feature Extraction; Parameter Datafile type = GenePix Results 3; Parameter Image Origin = 1400, 6320; Software: type: feature extraction; Performer: Andre,,Gerber"],"omics_type":["Unknown","Transcriptomics","Genomics","Proteomics"],"pubmed_abstract":["Trf4p and Trf5p are non-canonical poly(A) polymerases and are part of the heteromeric protein complexes TRAMP4 and TRAMP5 that promote the degradation of aberrant and short-lived RNA substrates by interacting with the nuclear exosome. To assess the level of functional redundancy between the paralogous Trf4 and Trf5 proteins and to investigate the role of the Trf4-dependent polyadenylation in vivo, we used DNA microarrays to compare gene expression of the wild-type yeast strain of S. cerevisiae with either that of trf4Delta or trf5Delta mutant strains or the trf4Delta mutant expressing the polyadenylation-defective Trf4(DADA) protein. We found little overlap between the sets of transcripts with altered expression in the trf4Delta or the trf5Delta mutants, suggesting that Trf4p and Trf5p target distinct groups of RNAs for degradation. Surprisingly, most RNAs the expression of which was altered by the trf4 deletion were restored to wild-type levels by overexpression of TRF4(DADA), showing that the polyadenylation activity of Trf4p is dispensable in vivo. Apart from previously reported Trf4p and Trf5p target RNAs, this analysis along with in vivo cross-linking and RNA immunopurification-chip experiments revealed that both the TRAMP4 and the TRAMP5 complexes stimulate the degradation of spliced-out introns via a mechanism that is independent of the polyadenylation activity of Trf4p. In addition, we show that disruption of trf4 causes severe shortening of telomeres suggesting that TRF4 functions in the maintenance of telomere length. Finally, our study demonstrates that TRF4, the exosome, and TRF5 participate in antisense RNA-mediated regulation of genes involved in phosphate metabolism. In conclusion, our results suggest that paralogous TRAMP complexes have distinct RNA selectivities with functional implications in RNA surveillance as well as other RNA-related processes. This indicates widespread and integrative functions of TRAMP complexes for the coordination of different gene expression regulatory processes."],"study_type":["transcription profiling by array"],"species":["Saccharomyces cerevisiae"],"pubmed_title":["Distinct roles of non-canonical poly(A) polymerases in RNA metabolism."],"pubmed_authors":["Andre Gerber","San Paolo S, Vanacova S, Schenk L, Scherrer T, Blank D, Keller W, Gerber AP"],"view_count":["57"],"additional_accession":[]},"is_claimable":false,"name":"Wild-type versus trf4, trf5, and trf4-DADA mutant cells","description":"Measurement of the relative changes of gene expression of S. cerevisiae cells lacking either trf4 (trf4delta) or trf5 (trf5delta), and trf4delta/TRF4-DADA mutants compared to wild-type (WT) cells using yeast oligo microarrays that contain features representing all annotated yeast ORFs, ncRNAs, introns, rRNA precursors, as well as some intergenic regions (IGRs) and tiled regions downstream of a few genes. Total RNA was isolated by hot phenol extraction from exponentially growing cells, and reverse transcribed with a mixture of random nonamers and oligo(dT) primers in the presence of amino-allyl dUTP/dNTP mixture. Cy5 fluorescently labeled cDNAs derived from total RNA isolated from either the trf4delta or the trf5delta mutants, and the trf4delta/TRF4-DADA mutants were then competitively hybridized with Cy3 labeled cDNAs from WT cells. cDNAs were hybridized on yeast oligo microarrays over night at 42 degrees in formamide-based hybridization buffer. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. mutated gene: paralogous non-canonical poly(A) polymerases Trf4p and Trf5p forming TRAMP4 and TRAMP5 complexes Computed","dates":{},"accession":"E-GEOD-16103","cross_references":{"GEO":["GSE16103"],"pubmed":["19593367"],"EFO":["EFO_0002768"],"doi":["19593367"]}}