Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene expression profiling of 19 cattle tissues reveals unique patterns related to tissue function

ABSTRACT: cDNA microarrays have been shown to be useful for monitoring global gene expression patterns in normal and disease states and in response to various environmental stimuli. In this study we have used a cattle cDNA microarray containing 7653 elements to analyze expression profiles in 19 different cattle tissues. Signal intensities from all tissue sample RNAs were compared to a reference standard RNA created from different tissues and cell lines. Data analysis identified a subset of genes significantly differentially expressed between tissues and the reference standard that were further subdivided according to fold change. Log transformed ratios were normalized using the intensity-based regional Lowess algorithm. A global error model, to account for the dependence of variation on signal intensities, was used to identify lists of genes for effect of tissue on gene expression taking into account an experiment-wise significance of 0.05, using either a Bonferroni correction (663 genes) or Benjamini and Hochbergâ??s False Discovery Rate (3350 genes). Non-supervised cluster analysis revealed groups of genes common to nerve, muscle, immune or digestive tissues. Discriminant analysis was used to support physiological functional categories and embryonic origin of tissues. Unique profiles were constructed with genes preferentially expressed in specific tissues or tissue groups in order to define gene expression for individual tissues. Global expression along a large collection of tissues revealed tissue specific expression of enzyme isomers and utilization in specific metabolic pathways. A comprehensive matrix of all possible pair-wise comparisons for individual genes among tissues was constructed to further identify genes with tissue-specific behavior and possibly unique function. A reference design was used to compare 19 cattle tissues. All tissues were compared to a universal control consisting of a mix of cattle cell lines. All samples were duplicated with a dye swap.

ORGANISM(S): Bos taurus

SUBMITTER: Jonathan Peled

PROVIDER: E-GEOD-3029 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Discovery of eight novel divergent homologs expressed in cattle placenta.

Larson Joshua H JH Kumar Charu G CG Everts Robin E RE Green Cheryl A CA Everts-van der Wind Annelie A Band Mark R MR Lewin Harris A HA

Physiological genomics 20060322 3

Ten divergent homologs were identified using a subtractive bioinformatic analysis of 12,614 cattle placenta expressed sequence tags followed by comparative, evolutionary, and gene expression studies. Among the 10 divergent homologs, 8 have not been identified previously. These were named as follows: cattle cerebrum and skeletal muscle-specific transcript 1 (CSSMST1), cattle intestine-specific transcript 1 (CIST1), hepatitis A virus cellular receptor 1 amino-terminal domain-containing protein (HA ...[more]

PMID: 16554549

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Project description:We used cDNA microarray technology to compare the genome-wide expression profiles of a wild type strain (BY4700) (E02, E04, E06) or the isogenic strain deleted of GLN3 and GAT1 genes (E01, E03, E05) grown in YNB medium with glutamine as nitrogen source (M.Gln) against the wild type strain grown in M.Gln after addition of rapamacyn (20 min) (E01, E02), or M.proline (M.Pro) (E03, E04) or after a two hours shift from M.Gln to M.Pro (E05, E06), all growth conditions known to modify the expression of genes involved in nitrogen utilization. These microarrays allowed to identify the set of genes that were up or down-regulated in response to the quality of the nitrogen source. To evaluate whether the majority of genes responding to the nitrogen source were dependent on Gln3 and Gat1, we compared the expression profiles of the wild type strain and of the isogenic strain deleted of GLN3 and GAT1 genes (03167b: ura3, gln3â, gat1â), when both strains were grown on M.Gln + rapamycin (E07), or M.Pro (E08) or after a shift from M.Gln to M.Pro (E09). We also used an independent means of identifying Gln3-Gat1 regulated genes by comparing the expression profiles in wild type and ure2â (4709âURE2) strains on M.Gln medium (E10). The hybridization signal was measured using a GSM418 laser scanner. Image analysis for each array was processed using the GenePix Pro 4.0 (Axon Instruments, Inc.) software package, which measures fluorescence intensity pairs for each gene. Following image acquisition, a visual inspection of the individual spots on each microarray (size, signal-to-noise ratio, background level, and spot uniformity) completed the flagging (present/not present, good/bad) of the data. To maximize sensitivity two scans were made, one at high laser power and high PMT (Photo Multiplier Tube) gain to detect the faintest spots, and a second one using low laser power and a PMT gain avoiding saturation. The values for spots presenting â¥ 5% saturation in the first scan were calculated based on an extrapolation after linear regression analysis of the intensities from both scans. These data were then imported in the GeneSpring 7.1 (Silicon Genetics) software package, applying a per spot per chip intensity-dependent (Lowess) normalization for further analysis.

Project description:Histone modifications affect DNA-templated processes ranging from transcription to genomic replication. In this study, we examine the cell cycle dynamics of the trimethylated form of histone H3 lysine 4 (H3K4me3), a mark of active chromatin that is viewed as â??long-livedâ?? [1], and that is involved in memory during cell state inheritance in metazoans [2]. We synchronized yeast using two different protocols, then followed H3K4me3 patterns as yeast passed through subsequent cell cycles. While most H3K4me3 patterns were conserved from one generation to the next, we found that methylation patterns induced by alpha factor or high temperature were erased within one cell cycle, during S phase. Early-replicating regions were erased before late-replicating regions, implicating replication in H3K4me3 loss. However, incomplete H3K4me3 erasure occurred at the majority of loci even when replication was prevented, suggesting that most erasure results from an active process. Indeed, deletion of the demethylase Jhd2 slowed erasure at most loci. Together, these results indicate overlapping roles for passive dilution and active enzymatic demethylation in erasing ancestral histone methylation states in yeast. References: [1] Ng HH, Robert F, Young RA, Struhl K (2003) Targeted recruitment of Set1 histone methylase by elongating Pol II provides a localized mark and memory of recent transcriptional activity. Mol Cell 11: 709-719. [2] Ringrose L, Paro R (2004) Epigenetic regulation of cellular memory by the Polycomb and Trithorax group proteins. Annu Rev Genet 38: 413-443. The overall design of the experiment consists of two cell cycle experiments, each consisting of the following subsets: gene expression, ChIP with anti-H3K4Me3 antibody, and ChIP input. The experiments are as follows: CCA - BY4741 bar1- cells synchronized by alpha factor arrest; CCTS - BY4741 cdc28(ts) cells synchronized by arrest at non-permissive temperature. The individual time courses are enumerated as follows: CCA gene expression (array title "Synchronized cells, xxx min, cell cycle CCA"), 18 arrays; CCA ChIP for anti-H3K4Me3 (array title "H3K4Me3 ChIP cell cycle CCA, xxx min"), 17 arrays, 1 replicate; CCA ChIP input (array title "ChIP Input cell cycle CCA, xxx min"), 18 arrays, 1 replicate; CCTS gene expression (appears in a different dataset as biological replicate "I"; array title "Synchronized cells, xxx min, biological replicate I"), 18 arrays; CCTS ChIP for anti-H3K4Me3 (array title "H3K4Me3 cell cycle CCTS, xxx min"), 2 technical replicates, 18 arrays per replicate; CCTS ChIP input (array title "ChIP Input cell cycle CCTS, xxx min"), 2 technical replicates, 18 arrays per replicate. Gene expression arrays were run against a reference of unsynchronized cells, ChIP-chip anti-H3K4Me3 samples were run against an IP (of the same epitope) of unsynchronized cells, and ChIP input samples were run against either a pool of all the time points in the time course (CCTS) or against sonicated DNA isolated from unsynchronized cells (CCA). Four additional experiments have been performed. They are referred to as series X in the title. Series 1: anti H3K4me3 CHIP time course of BY4741 bar1 delete cells (wt) synchronized with alpha factor and released in the cell cycle, 9 arrays, 1 replicate. Series 2: anti H3K4me3 CHIP time course of BY4741 bar1 jhd2 delete cells (jhd2 delete) synchronized with alpha factor and released in the cell cycle, 7 arrays, 1 replicate. Series 3: anti H3K4me3 CHIP time course of CYM36 cells (cdc7ts) synchronized with alpha factor and released in the cell cycle at the permissive 24C or at the restrictive 37C temperature, 22 arrays, 2 replicates. Series 4: anti H3K4me3 CHIP time course of BY4741 bar1 delete cells (wt) grown in galactose and synchronized with alpha factor and either released in the cell cycle in glucose media or alpha factor arrested and switched to glucose media, 6 arrays, 1 replicate.

Project description:Significant insight about biological networks arises from the study of network motifs âoverly abundant network subgraphs, but such wiring patterns do not specify when and how potential routes within a cellular network are used. To address this limitation, we introduce activity motifs, which capture patterns in the dynamic use of a network. Using this framework to analyze transcription in Saccharomyces cerevisiae metabolism, we find that cells use different timing activity motifs to optimize transcription timing in response to changing conditions: forward activation to produce metabolic compounds efficiently, backward shutoff to rapidly stop production of a detrimental product and synchronized activation for co-production of metabolites required for the same reaction Measuring protein abundance over a time course reveals that mRNA timing motifs also occur at the protein level. Timing motifs significantly overlap with binding activity motifs, where genes in a linear chain have ordered binding affinity to a transcription factor, suggesting a mechanism for ordered transcription. Finely timed transcriptional regulation is therefore abundant in yeast metabolism, optimizing the organism's adaptation to new environmental conditions. We generated a set of 13 time courses by measuring gene expression after a metabolic change. Yeast strain KCN118 (MATalpha ade2) was grown at 28 Â°C in 400 ml of synthetic complete media with 2% dextrose (SCD) to an OD600 of 0.6. Synthetic complete was prepared using the standard recipe, except 75 uM inositol was included. At OD600 of 0.6, 100 ml of cells were collected by centrifugation and frozen as a reference sample, and the remaining cells were rapidly collected by filtration, washed with distilled water and resuspended in 300 ml of one of the following media: SCE (SC + 2% ethanol), SCG (SC + 2% galactose), SM1 (SCD lacking amino acids A, R, N, C, Q, G, K, P, S, F and T), SM2 (SCD lacking amino acids L, I, V, W, H and M), S0 (SCD lacking all amino acids), S0G (no amino acids, 2% galactose) or S0E (no amino acids, 2% ethanol). The data appears in Figures 2 and 4 of the manuscript, as it relates to the global analysis of all the arrays used in the dataset. All time courses consist of the following time points (in min): 15, 30, 60, 120, 240, and were hybridized against the t = 0 time point of cells grown in SCD. Each time course was performed as one single biological replicate and one technological replicate, except where noted below. Specifically, the 13 time courses break down into the following groups: Media key: SCD (synthetic complete, not including inositol) SCE (SC + 2% ethanol) SCG (SC + 2% galactose) SM1 (SCD lacking amino acids A, R, N, C, Q, G, K, P, S, F and T) SM2 (SCD lacking amino acids L, I, V, W, H and M) S0 (SCD lacking all amino acids) S0G (no amino acids, 2% galactose) S0E (no amino acids, 2% ethanol). ino = inositol aa = all amino acids supplemented The following group descriptions are the media as described above, followed by the description as indicated in the long title of the individual arrays: 1. S0 (5 arrays) = SD 2. SCD (6 arrays, t = 240 min has 2 tech replicates) = SD+aa 3. SM2 (5 arrays) = SD+aa:ARNCQGKPSDEFTY+ino 4. SM1 + ino (5 arrays) = SD+aa:LIVWHM+ino 5. S0 + ino (6 arrays, t = 240 min has 2 tech replicates) = SD+ino 6. S0E (5 arrays) = SEtOH 7. S0E + aa (7 arrays, t = 240 min and 60 min each have 2 tech replicates) = SEtOH+aa 8. S0E + aa + ino (5 arrays) = SEtOH+aa+ino 9. S0E + ino (8 arrays, t = 240 min, 15 min and 30 min each have 2 tech replicates) = SEtOH+ino 10. S0G (5 arrays) = Sgal 11. S0G + aa (5 arrays) = Sgal+aa 12. S0G + aa + ino (5 arrays) = Sgal+aa+ino 13. S0G + ino (6 arrays, t = 60 min has 2 tech replicates) = Sgal+ino

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Project description:The use of genome-wide RNA abundance profiling by microarrays and deep sequencing has spurred a revolution in our understanding of transcriptional control. However, changes in mRNA abundance reflect the combined effect of changes in RNA production, processing, and degradation, and thus, mRNA levels provide an occluded view of transcriptional regulation. To partially disentangle these issues, we carry out genome-wide RNA Polymerase II (“Pol2”) localization profiling in budding yeast in two different stress response time courses. While mRNA changes largely reflect changes in transcription, there remains a great deal of variation in mRNA levels that is not accounted for by changes in Pol2 abundance. We find that genes exhibiting “excess” mRNA produced per Pol2 are enriched for those with overlapping cryptic transcripts, indicating a pervasive role for nonproductive or regulatory transcription in control of gene expression. Finally, we characterize changes in Pol2 localization when Pol2 is genetically inactivated using the rpb1-1 temperature-sensitive mutation. We find that Pol2 is lost from chromatin after roughly an hour at the restrictive temperature, and that there is a great deal of variability in the rate of Pol2 loss at different loci. Together, these results provide a global perspective on the relationship between Pol2 and mRNA production in budding yeast. The array studies consisted of 4 time courses in which the genome-wide location of RNA Polymerase II was mapped via chromatin immunoprecipitation (ChIP) in BY4741 S. cerevisiae cells or in such cells bearing the temperature sensitive mutation rpb1, in response to heat shock at 37 degrees C and/or 1.5 mM diamide. All samples were hybridized as the ChIP sample (Cy3 labeled, channel 1) versus its cognate ChIP input sample (Cy5 labeled, channel 2). The first time course was a heat shock in wild-type BY4741 cells. The second time course was a heat shock in BY4741 rpd1 cells. The third time course was a diamide treatment of BY4741 rpd1 cells. The fourth time course was a 10 minute heat shock in BY4741 rpd1 cells followed by treatment from 15-60 minutes with diamide (3 samples). In the first three time courses the time range is 0-120 minutes (5 samples). A total of 18 arrays were used in this study. No additional replicates or dye-flip experiments were performed.

Project description:Genetic analyses suggest that alterations in gene expression at the molecular and tissue levels can have profound effects on aging for multi-cellular organisms. However, much remains unknown about the normal pattern of genetic changes in different tissues and how these tissues interact during aging. To investigate tissue-specific aging systematically, we measured expression profiles of aging in Drosophila melanogaster in seven tissues representing nervous, muscular, digestive, renal, reproductive, and storage systems. In each tissue, we identified hundreds of age-related genes mostly showing gradual changes of transcript levels with age. Age-relatedgenes showed clear tissue-specific transcriptional patterns; less than 10% of age-related genes in each tissue shared expression patterns with any other tissue; less than 20% of age-related biological processes were shared between tissues. A significant portion of tissue-specific age-related genes are those involved in physiological functions regulated by the corresponding tissue. However, limited overlaps of age-related function groups among tissues particularly those involved in proteasome function suggest some common mechanisms of transcription regulation in aging across tissues. This study defined global, temporal and spatial changes associated withaging at the molecular and tissue levels. Analyses indicated that different tissues might age in different patterns or at different rates. This study addressed comprehensively the relationship of age-related changes among different tissues in one organism, providing a foundation to address tissue-specific regulation in aging. RNA was then amplified by a one-step linear amplification protocol to generate amplified RNA (aRNA). Experiment aRNA refers to amplified RNA from flies of 15, 20, 30, 45 and 60 days old, and reference aRNA refers to amplified RNA from flies of 3 days old, and experiment and reference aRNAs were labeled with fluorescent dye Cy3 and Cy5, respectively. For each tissue, RNA from the corresponding tissue of 3-day old flies was used as the reference RNA and expression profiles at each of the five age-points was measured twice by using independently prepared duplicated samples. Seven types of tissues or organs of the male fly strain w1118 , accessory gland, testis, brain, gut, malpighian tubule, dorsal thoracic muscle and abdominal fat body were hand dissected out of flies at age of 3, 15, 20, 30, 45 and 60 days old. Tissues or organs from four males of the same age were pooled together and used for each RNA sample preparation.

Project description:Acetylation of histone H3 lysine 56 is a covalent modification best-known as a mark of newly-replicated chromatin, but has also been linked to replication-independent histone replacement. Here, we measured H3K56ac levels at single-nucleosome resolution in asynchronously growing yeast cultures, as well as in yeast proceeding synchronously through the cell cycle. We developed a quantitative model of H3K56ac kinetics, which shows that H3K56ac is largely explained by the genomic replication timing and the turnover rate of each nucleosome, suggesting that cell cycle profiles of H3K56ac should reveal most first-time nucleosome incorporation events. However, since the deacetylases Hst3/4 prevent use of H3K56ac as a marker for histone deposition during M phase, we also directly measured M phase histone replacement rates. We report a global decrease in turnover rates during M phase, and a further specific decrease in turnover among early origins of replication, which switch from rapidly-replaced in G1 phase to stable-bound during M phase. Finally, by measuring H3 replacement in yeast deleted for the H3K56 acetyltransferase Rtt109 and its two co-chaperones Asf1 and Vps75, we find evidence that Rtt109 and Asf1 preferentially enhance histone replacement at rapidly-replaced nucleosomes, whereas Vps75 appears to inhibit histone turnover at those loci. These results provide a broad perspective on histone replacement/incorporation throughout the cell cycle, and suggest that H3K56 acetylation provides a positive feedback loop by which replacement of a nucleosome enhances subsequent replacement at the same location. To characterize incorporation of H3K56ac in yeast, several sets of ChIP-chip experiments were performed, along with a set of gene expression microarrays. The following describes each individual set, the number of biological and array replicates performed, dye-flip replicates if performed, the total number of arrays, and the applicable figures in the manuscript. Except for Item D (gene expression), all arrays were ChIP-chip experiments. A. Mid-log H3K56ac measurement. 3 biological replicates, 1 array replicate each of K56Ac ChIP with Grunstein Lab antibody. 2 biological replicates, 2 array replicates each of K56Ac ChIP with Upstate antibody. 7 total arrays. Figure 1A-C, 3, S1, S2A, S6, S7. B. Cell cycle - H3K56ac measurements. 1 biological replicate, 3 array replicates each of K56Ac ChIP with Upstate antibody. 17 time points (10 min. unavailable in third array replicate). 50 total arrays. Figures 2, 3, 4, S4, S5, S7, S8. C. G1 phase turnover. 1 biological replicate (3 time points) with 1 dye-flip replicate each time point (45 minutes replaced with 60 minutes for dye-flip replicate). 6 total arrays. Tables S2, S3. D. Cell cycle - mRNA measurements. 2 biological replicates, 1 array replicate each. 34 total arrays. Figure S3. E. M phase turnover rates. 2 biological replicates, second biological replicate has one dye-flip replicate. 17 total arrays. Figure 5. F. Deletion mutants in H3K56ac pathway for G1-arrested cells. Strains: wild-type parental strain (PKY4212; 2 biological replicates), asf1D (strain 2 biological replicates), vps75D (3 biological replicates, third biological replicate having two array replicates), rtt109D (2 biological replicates, each with one dye-flip replicate). 12 total arrays. Figure 6.

Dataset Information

Gene expression profiling of 19 cattle tissues reveals unique patterns related to tissue function

Publications

Discovery of eight novel divergent homologs expressed in cattle placenta.

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