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At least 199 records · Page 11Linked to original sources
PubMed2005

Transcriptome analysis and kidney research: toward systems biology.

An enormous amount of data has been generated in kidney research using transcriptome analysis techniques. In this review article, we first describe briefly the principles and major characteristics of several of these techniques. We then summarize the progress in kidney research that has been made by using transcriptome analysis, emphasizing the experience gained and the lessons learned. Several technical issues regarding DNA microarray are highlighted because of the rapidly increased use of this technology. It appears clear from this brief survey that transcriptome analysis is an effective and important tool for question-driven exploratory science. To further enhance the power of this and other high throughput, as well as conventional approaches, in future studies of the kidney, we propose a multidimensional systems biology paradigm that integrates investigation at multiple levels of biologic regulation toward the goal of achieving a global understanding of physiology and pathophysiology.

Animals↗
PubMed2006

Non-human primate fetal kidney transcriptome analysis indicates mammalian target of rapamycin (mTOR) is a central nutrient-responsive pathway.

Developmental programming is defined as the process by which gene-environment interaction in the developing organism leads to permanent changes in phenotype and function. Numerous reports of maternal nutrient restriction during pregnancy demonstrate altered renal development. Typically this alteration manifests as a reduction in the total number of glomeruli in the mature kidney of the offspring, and suggests that predisposition to develop chronic renal disease may include an in utero origin. In a previous study, we defined the transcriptome in the kidney from fetuses of control (CON, fed ad libitum) and nutrient-restricted (NR, fed 70% of CON starting at 0.16 gestation (G)) pregnancies at half-way through gestation (0.5G), and established transcriptome and morphological changes in NR kidneys compared to CON. One goal of the present study was to use transcriptome data from fetal kidneys of CON and NR mothers at 0.5G with histological data to identify the molecular mechanisms that may regulate renal development. A second goal was to identify mechanisms by which NR elicits its affect on fetal baboon kidney. We have used an end-of-pathway gene expression analysis to prioritize and identify key pathways regulating the 0.5G kidney phenotype in response NR. From these data we have determined that the mammalian target of rapamycin (mTOR) signalling pathway is central to this phenotype.

Animal Feed↗
PubMed2002

Bacillus subtilis functional genomics: global characterization of the stringent response by proteome and transcriptome analysis.

The stringent response in Bacillus subtilis was characterized by using proteome and transcriptome approaches. Comparison of protein synthesis patterns of wild-type and relA mutant cells cultivated under conditions which provoke the stringent response revealed significant differences. According to their altered synthesis patterns in response to DL-norvaline, proteins were assigned to four distinct classes: (i) negative stringent control, i.e., strongly decreased protein synthesis in the wild type but not in the relA mutant (e.g., r-proteins); (ii) positive stringent control, i.e., induction of protein synthesis in the wild type only (e.g., YvyD and LeuD); (iii) proteins that were induced independently of RelA (e.g., YjcI); and (iv) proteins downregulated independently of RelA (e.g., glycolytic enzymes). Transcriptome studies based on DNA macroarray techniques were used to complement the proteome data, resulting in comparable induction and repression patterns of almost all corresponding genes. However, a comparison of both approaches revealed that only a subset of RelA-dependent genes or proteins was detectable by proteomics, demonstrating that the transcriptome approach allows a more comprehensive global gene expression profile analysis. The present study presents the first comprehensive description of the stringent response of a bacterial species and an almost complete map of protein-encoding genes affected by (p)ppGpp. The negative stringent control concerns reactions typical of growth and reproduction (ribosome synthesis, DNA synthesis, cell wall synthesis, etc.). Negatively controlled unknown y-genes may also code for proteins with a specific function during growth and reproduction (e.g., YlaG). On the other hand, many genes are induced in a RelA-dependent manner, including genes coding for already-known and as-yet-unknown proteins. A passive model is preferred to explain this positive control relying on the redistribution of the RNA polymerase under the influence of (p)ppGpp.

Bacillus subtilis↗
PubMed2004

Responses of the Rhodobacter sphaeroides transcriptome to blue light under semiaerobic conditions.

Exposure to blue light of the facultative phototrophic proteobacterium Rhodobacter sphaeroides grown semiaerobically results in repression of the puc and puf operons involved in photosystem formation. To reveal the genome-wide effects of blue light on gene expression and the underlying photosensory mechanisms, transcriptome profiles of R. sphaeroides during blue-light irradiation (for 5 to 135 min) were analyzed. Expression of most photosystem genes was repressed upon irradiation. Downregulation of photosystem development may be used to prevent photooxidative damage occurring when the photosystem, oxygen, and high-intensity light are present simultaneously. The photoreceptor of the BLUF-domain family, AppA, which belongs to the AppA-PpsR antirepressor-repressor system, is essential for maintenance of repression upon prolonged irradiation (S. Braatsch et al., Mol. Microbiol. 45:827-836, 2002). Transcriptome data suggest that the onset of repression is also mediated by the AppA-PpsR system, albeit via an apparently different sensory mechanism. Expression of several genes, whose products may participate in photooxidative damage defense, including deoxypyrimidine photolyase, glutathione peroxidase, and quinol oxidoreductases, was increased. Among the genes upregulated were genes encoding two sigma factors: sigmaE and sigma38. The consensus promoter sequences for these sigma factors were predicted in the upstream sequences of numerous upregulated genes, suggesting that coordinated action of sigmaE and sigma38 is responsible for the upregulation. Based on the dynamics of upregulation, the anti-sigmaE factor ChrR or its putative upstream partner is proposed to be the primary sensor. The identified transcriptome responses provided a framework for deciphering blue-light-dependent signal transduction pathways in R. sphaeroides.

Bacterial Proteins↗
PubMed2002

Generation of kidney transcriptomes using serial analysis of gene expression.

Chronic renal disease initiation and progression remain incompletely understood. Genomewide expression monitoring should clarify the mechanisms which cause progressive renal disease by determining how clusters of genes coordinately change their activity. Serial analysis of gene expression (SAGE) is a technique of expression profiling which permits simultaneous and quantitative analysis of 9- to 13-bp sequence tags that correspond to unique mRNAs. Key principles of the technique are use of PCR in a manner to minimize distortion and serial concatenation of tags which facilitates sequencing and permits identification of many expressed genes in a single cDNA molecule. Tags are extracted from many concatenated sequences, counted using software, and identified by comparison with existing gene databases. In aggregate, gene expression profiles generated from a tag library comprise a transcriptome which represents a comprehensive and quantitative profile of genes expressed at the time of analysis. These global snapshots of gene expression patterns can better define basic cell biology and provide insights into disease pathogenesis by simultaneously determining the net consequences of gene-gene and gene-environment interactions on expression of thousands of genes. Rather than applying a priori assumptions (i.e., hypothesis testing), transcriptome analysis is hypothesis generating and requires no prior knowledge of gene expression. SAGE kidney transcriptomes, from normal animals and animals with progressive kidney disease, are being produced and can be analyzed for novel pathogenetic mechanisms. The use of SAGE and other genomic and proteomic tools should result in a better understanding of kidney disease pathogenesis and in identification of new therapeutic targets.

Animals↗
PubMed2007

Transcriptome analysis of temporal regulation of carbon metabolism by CcpA in Bacillus subtilis reveals additional target genes.

The pleiotropic regulator of carbon metabolism in Gram-positive bacteria, CcpA, regulates gene expression by binding to so-called cre elements, which are located either upstream or in promoter regions, or in open-reading frames. In this study we compared the transcriptomes of Bacillus subtilis 168 and its ccpA deletion mutant during growth in glucose-containing rich medium. Although growth was similar, glucose was completely consumed by the wild-type strain in the stationary phase, while it was still present in the culture of the mutant. At that stage, direct and indirect effects on gene expression were observed. During exponential growth, CcpA mainly influences the carbohydrate and energy metabolism, whereas from transition phase onwards its function expands on a broader range of physiological processes including nucleotide metabolism, cell motility and protein synthesis. A genome wide search revealednew putative cre sites, which could function in vivo according to our transcriptome data. Comparison of our data with published transcriptome data of ccpA mutant analysis in the exponential growth phase confirmed earlier identified CcpA regulon members. It also allowed identification of potential new CcpA-repressed genes, amongst others ycgN and the ydh operon. Novel activated members include opuE andthe opuAABC, yhb and man operons, which all have a putative cre site that appears to be dependent on helical topology. A comparative analysis of these genes with the known activated genes i.e.ackA and pta revealed the presence of a possible upstream activating region (UAR) as has been shown to be functional for the activation of ackA. The data suggest that at later growth phases CcpA may regulate gene expression by itself or complexed with other, yet unknown cofactors.

Bacillus subtilis↗
PubMed2005

Transcriptome differences between the frontal cortex and hippocampus of wild-type and humanized presenilin-1 transgenic mice.

OBJECTIVE: The authors investigated the differences between the frontal cortical (Fc) and hippocampal (Hc) transcriptomes of wild type (wt mPS1), humanized presenilin-1 (PS1 [wt hPS1]) and Alzheimer-disease (AD)-linked DeltaE9 hPS1 mutant mice. METHODS: Using high-density oligonucleotide arrays, they recently performed transcriptome profiling of wt mPS1, wt hPS1, and DeltaE9 hPS1 mutant mice. Whereas these studies analyzed the commonalities of gene expression patterns and commonly-regulated genes across the two brain areas and across the animal models, the current study focused on the gene-expression differences across Fc and Hc, two critical AD-affected brain regions. RESULTS: The data revealed that in the wild-type mice, there are significant transcriptome differences between the Fc and the Hc tissue, and these expression differences are maintained in humanized transgenic mice carrying the wt hPS1 gene or DeltaE9 hPS1 mutation. Also, they provide evidence that a subset of genes show disturbed regional Fc-Hc gene-expression ratios in the transgenic mice carrying the DeltaE9 hPS1 mutation. Some of these genes, including stearoyl-Coenzyme A desaturase-2 (Scd2) and Prostaglandin D2 synthase (Ptgds), have been previously implicated in the pathology of AD. CONCLUSIONS: Data suggest that disturbed gene-expression ratios between cortical regions may be an important event in altered brain physiology.

Alzheimer Disease↗
PubMed2004

MiCoViTo: a tool for gene-centric comparison and visualization of yeast transcriptome states.

BACKGROUND: Information obtained by DNA microarray technology gives a rough snapshot of the transcriptome state, i.e., the expression level of all the genes expressed in a cell population at any given time. One of the challenging questions raised by the tremendous amount of microarray data is to identify groups of co-regulated genes and to understand their role in cell functions. RESULTS: MiCoViTo (Microarray Comparison Visualization Tool) is a set of biologists' tools for exploring, comparing and visualizing changes in the yeast transcriptome by a gene-centric approach. A relational database includes data linked to genome expression and graphical output makes it easy to visualize clusters of co-expressed genes in the context of available biological information. To this aim, upload of personal data is possible and microarray data from fifty publications dedicated to S. cerevisiae are provided on-line. A web interface guides the biologist during the usage of this tool and is freely accessible at http://www.transcriptome.ens.fr/micovito/. CONCLUSIONS: MiCoViTo offers an easy-to-read picture of local transcriptional changes connected to current biological knowledge. This should help biologists to mine yeast microarray data and better understand the underlying biology. We plan to add functional annotations from other organisms. That would allow inter-species comparison of transcriptomes via orthology tables.

Cluster Analysis↗
PubMed2005

Chromosomal clustering of a human transcriptome reveals regulatory background.

BACKGROUND: There has been much evidence recently for a link between transcriptional regulation and chromosomal gene order, but the relationship between genomic organization, regulation and gene function in higher eukaryotes remains to be precisely defined. RESULTS: Here, we present evidence for organization of a large proportion of a human transcriptome into gene clusters throughout the genome, which are partly regulated by the same transcription factors, share biological functions and are characterized by non-housekeeping genes. This analysis was based on the cardiac transcriptome identified by our genome-wide array analysis of 55 human heart samples. We found 37% of these genes to be arranged mainly in adjacent pairs or triplets. A significant number of pairs of adjacent genes are putatively regulated by common transcription factors (p = 0.02). Furthermore, these gene pairs share a significant number of GO functional classification terms. We show that the human cardiac transcriptome is organized into many small clusters across the whole genome, rather than being concentrated in a few larger clusters. CONCLUSION: Our findings suggest that genes expressed in concert are organized in a linear arrangement for coordinated regulation. Determining the relationship between gene arrangement, regulation and nuclear organization as well as gene function will have broad biological implications.

Binding Sites↗
PubMed2004

The rehydration transcriptome of the desiccation-tolerant bryophyte Tortula ruralis: transcript classification and analysis.

BACKGROUND: The cellular response of plants to water-deficits has both economic and evolutionary importance directly affecting plant productivity in agriculture and plant survival in the natural environment. Genes induced by water-deficit stress have been successfully enumerated in plants that are relatively sensitive to cellular dehydration, however we have little knowledge as to the adaptive role of these genes in establishing tolerance to water loss at the cellular level. Our approach to address this problem has been to investigate the genetic responses of plants that are capable of tolerating extremes of dehydration, in particular the desiccation-tolerant bryophyte, Tortula ruralis. To establish a sound basis for characterizing the Tortula genome in regards to desiccation tolerance, we analyzed 10,368 expressed sequence tags (ESTs) from rehydrated rapid-dried Tortula gametophytes, a stage previously determined to exhibit the maximum stress induced change in gene expression. RESULTS: The 10, 368 ESTs formed 5,563 EST clusters (contig groups representing individual genes) of which 3,321 (59.7%) exhibited similarity to genes present in the public databases and 2,242 were categorized as unknowns based on protein homology scores. The 3,321 clusters were classified by function using the Gene Ontology (GO) hierarchy and the KEGG database. The results indicate that the transcriptome contains a diverse population of transcripts that reflects, as expected, a period of metabolic upheaval in the gametophyte cells. Much of the emphasis within the transcriptome is centered on the protein synthetic machinery, ion and metabolite transport, and membrane biosynthesis and repair. Rehydrating gametophytes also have an abundance of transcripts that code for enzymes involved in oxidative stress metabolism and phosphorylating activities. The functional classifications reflect a remarkable consistency with what we have previously established with regards to the metabolic activities that are important in the recovery of the gametophytes from desiccation. A comparison of the GO distribution of Tortula clusters with an identical analysis of 9,981 clusters from the desiccation sensitive bryophyte species Physcomitrella patens, revealed, and accentuated, the differences between stressed and unstressed transcriptomes. Cross species sequence comparisons indicated that on the whole the Tortula clusters were more closely related to those from Physcomitrella than Arabidopsis (complete genome BLASTx comparison) although because of the differences in the databases there were more high scoring matches to the Arabidopsis sequences. The most abundant transcripts contained within the Tortula ESTs encode Late Embryogenesis Abundant (LEA) proteins that are normally associated with drying plant tissues. This suggests that LEAs may also play a role in recovery from desiccation when water is reintroduced into a dried tissue. CONCLUSION: The establishment of a rehydration EST collection for Tortula ruralis, an important plant model for plant stress responses and vegetative desiccation tolerance, is an important step in understanding the genome level response to cellular dehydration. The type of transcript analysis performed here has laid the foundation for more detailed functional and genome level analyses of the genes involved in desiccation tolerance in plants.

Arabidopsis↗
PubMed2006

Transcriptome coexpression map of human embryonic stem cells.

BACKGROUND: Human embryonic stem (ES) cells hold great promise for medicine and science. The transcriptome of human ES cells has been studied in detail in recent years. However, no systematic analysis has yet addressed whether gene expression in human ES cells may be regulated in chromosomal domains, and no chromosomal domains of coexpression have been identified. RESULTS: We report the first transcriptome coexpression map of the human ES cell and the earliest stage of ES differentiation, the embryoid body (EB), for the analysis of how transcriptional regulation interacts with genomic structure during ES self-renewal and differentiation. We determined the gene expression profiles from multiple ES and EB samples and identified chromosomal domains showing coexpression of adjacent genes on the genome. The coexpression domains were not random, with significant enrichment in chromosomes 8, 11, 16, 17, 19, and Y in the ES state, and 6, 11, 17, 19 and 20 in the EB state. The domains were significantly associated with Giemsa-negative bands in EB, yet showed little correlation with known cytogenetic structures in ES cells. Different patterns of coexpression were revealed by comparative transcriptome mapping between ES and EB. CONCLUSION: The findings and methods reported in this investigation advance our understanding of how genome organization affects gene expression in human ES cells and help to identify new mechanisms and pathways controlling ES self-renewal or differentiation.

Animals↗
PubMed2006

LocustDB: a relational database for the transcriptome and biology of the migratory locust (Locusta migratoria).

BACKGROUND: The migratory locust (Locusta migratoria) is an orthopteran pest and a representative member of hemimetabolous insects for biological studies. Its transcriptomic data provide invaluable information for molecular entomology and pave a way for the comparative research of other medically, agronomically, and ecologically relevant insects. We developed the first transcriptomic database of the locust (LocustDB), building necessary infrastructures to integrate, organize, and retrieve data that are either currently available or to be acquired in the future. DESCRIPTION: LocustDB currently hosts 45,474 high-quality EST sequences from the locust, which were assembled into 12,161 unigenes. It, through user-friendly web interfaces, allows investigators to freely access sequence data, including homologous/orthologous sequences, functional annotations, and pathway analysis, based on conserved orthologous groups (COG), gene ontology (GO), protein domain (InterPro), and functional pathways (KEGG). It also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, including the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. The website address of LocustDB is http://locustdb.genomics.org.cn/. CONCLUSION: LocustDB starts with the first transcriptome information for an orthopteran and hemimetabolous insect and will be extended to provide a framework for incorporating in-coming genomic data of relevant insect groups and a workbench for cross-species comparative studies.

Animals↗
PubMed2006

Clustering of Pseudomonas aeruginosa transcriptomes from planktonic cultures, developing and mature biofilms reveals distinct expression profiles.

BACKGROUND: Pseudomonas aeruginosa is a genetically complex bacterium which can adopt and switch between a free-living or biofilm lifestyle, a versatility that enables it to thrive in many different environments and contributes to its success as a human pathogen. RESULTS: Transcriptomes derived from growth states relevant to the lifestyle of P. aeruginosa were clustered using three different methods (K-means, K-means spectral and hierarchical clustering). The culture conditions used for this study were; biofilms incubated for 8, 14, 24 and 48 hrs, and planktonic culture (logarithmic and stationary phase). This cluster analysis revealed the existence and provided a clear illustration of distinct expression profiles present in the dataset. Moreover, it gave an insight into which genes are up-regulated in planktonic, developing biofilm and confluent biofilm states. In addition, this analysis confirmed the contribution of quorum sensing (QS) and RpoS regulated genes to the biofilm mode of growth, and enabled the identification of a 60.69 Kbp region of the genome associated with stationary phase growth (stationary phase planktonic culture and confluent biofilms). CONCLUSION: This is the first study to use clustering to separate a large P. aeruginosa microarray dataset consisting of transcriptomes obtained from diverse conditions relevant to its growth, into different expression profiles. These distinct expression profiles not only reveal novel aspects of P. aeruginosa gene expression but also provide a growth specific transcriptomic reference dataset for the research community.

Animals↗
PubMed2006

Deep and comparative analysis of the mycelium and appressorium transcriptomes of Magnaporthe grisea using MPSS, RL-SAGE, and oligoarray methods.

BACKGROUND: Rice blast, caused by the fungal pathogen Magnaporthe grisea, is a devastating disease causing tremendous yield loss in rice production. The public availability of the complete genome sequence of M. grisea provides ample opportunities to understand the molecular mechanism of its pathogenesis on rice plants at the transcriptome level. To identify all the expressed genes encoded in the fungal genome, we have analyzed the mycelium and appressorium transcriptomes using massively parallel signature sequencing (MPSS), robust-long serial analysis of gene expression (RL-SAGE) and oligoarray methods. RESULTS: The MPSS analyses identified 12,531 and 12,927 distinct significant tags from mycelia and appressoria, respectively, while the RL-SAGE analysis identified 16,580 distinct significant tags from the mycelial library. When matching these 12,531 mycelial and 12,927 appressorial significant tags to the annotated CDS, 500 bp upstream and 500 bp downstream of CDS, 6,735 unique genes in mycelia and 7,686 unique genes in appressoria were identified. A total of 7,135 mycelium-specific and 7,531 appressorium-specific significant MPSS tags were identified, which correspond to 2,088 and 1,784 annotated genes, respectively, when matching to the same set of reference sequences. Nearly 85% of the significant MPSS tags from mycelia and appressoria and 65% of the significant tags from the RL-SAGE mycelium library matched to the M. grisea genome. MPSS and RL-SAGE methods supported the expression of more than 9,000 genes, representing over 80% of the predicted genes in M. grisea. About 40% of the MPSS tags and 55% of the RL-SAGE tags represent novel transcripts since they had no matches in the existing M. grisea EST collections. Over 19% of the annotated genes were found to produce both sense and antisense tags in the protein-coding region. The oligoarray analysis identified the expression of 3,793 mycelium-specific and 4,652 appressorium-specific genes. A total of 2,430 mycelial genes and 1,886 appressorial genes were identified by both MPSS and oligoarray. CONCLUSION: The comprehensive and deep transcriptome analysis by MPSS and RL-SAGE methods identified many novel sense and antisense transcripts in the M. grisea genome at two important growth stages. The differentially expressed transcripts that were identified, especially those specifically expressed in appressoria, represent a genomic resource useful for gaining a better understanding of the molecular basis of M. grisea pathogenicity. Further analysis of the novel antisense transcripts will provide new insights into the regulation and function of these genes in fungal growth, development and pathogenesis in the host plants.

DNA, Fungal↗
PubMed2006

Transcriptome-scale similarities between mouse and human skeletal muscles with normal and myopathic phenotypes.

BACKGROUND: Mouse and human skeletal muscle transcriptome profiles vary by muscle type, raising the question of which mouse muscle groups have the greatest molecular similarities to human skeletal muscle. METHODS: Orthologous (whole, sub-) transcriptome profiles were compared among four mouse-human transcriptome datasets: (M) six muscle groups obtained from three mouse strains (wildtype, mdx, mdx5cv); (H1) biopsied human quadriceps from controls and Duchenne muscular dystrophy patients; (H2) four different control human muscle types obtained at autopsy; and (H3) 12 different control human tissues (ten non-muscle). RESULTS: Of the six mouse muscles examined, mouse soleus bore the greatest molecular similarities to human skeletal muscles, independent of the latters' anatomic location/muscle type, disease state, age and sampling method (autopsy versus biopsy). Significant similarity to any one mouse muscle group was not observed for non-muscle human tissues (dataset H3), indicating this finding to be muscle specific. CONCLUSION: This observation may be partly explained by the higher type I fiber content of soleus relative to the other mouse muscles sampled.

Animals↗
PubMed2006

How dietary arachidonic- and docosahexaenoic- acid rich oils differentially affect the murine hepatic transcriptome.

INTRODUCTION: Herein, we expand our previous work on the effects of long chain polyunsaturated fatty acids (LC-PUFA) on the murine hepatic transcriptome using novel statistical and bioinformatic approaches for evaluating microarray data. The analyses focuses on key differences in the transcriptomic response that will influence metabolism following consumption of FUNG (rich in 20:4n6), FISH (rich in 20:5n3, 22:5n3, and 22:6n3) and COMB, the combination of the two. RESULTS: Using a variance-stabilized F-statistic, 371 probe sets (out of 13 K probe sets in the Affymetrix Mu11K chip set) were changed by dietary treatment (P < 0.001). Relative to other groups, COMB had unique affects on murine hepatic transcripts involved in cytoskeletal and carbohydrate metabolism; whereas FUNG affected amino acid metabolism via CTNB1 signaling. All three diets affected transcripts linked to apoptosis and cell proliferation, with evidence FISH may have increased apoptosis and decreased cell proliferation via various transcription factors, kinases, and phosphatases. The three diets affected lipid transport, lipoprotein metabolism, and bile acid metabolism through diverse pathways. Relative to other groups, FISH activated cyps that form hydroxylated fatty acids known to affect vascular tone and ion channel activity. FA synthesis and delta 9 desaturation were down regulated by COMB relative to other groups, implying that a FA mixture of 20:4n6, 20:5n3, and 22:6n3 is most effective at down regulating synthesis, via INS1, SREBP, PPAR alpha, and TNF signaling. Heme synthesis and the utilization of heme for hemoglobin production were likely affected by FUNG and FISH. Finally, relative to other groups, FISH increased numerous transcripts linked to combating oxidative such as peroxidases, an aldehyde dehydrogenase, and heat shock proteins, consistent with the major LC-PUFA in FISH (20:5n3, 22:5n3, 22:6n3) being more oxidizable than the major fatty acids in FUNG (20:4n6). CONCLUSION: Distinct transcriptomic, signaling cascades, and predicted affects on murine liver metabolism have been elucidated for 20:4n6-rich dietary oils, 22:6n3-rich oils, and a surprisingly distinct set of genes were affected by the combination of the two. Our results emphasize that the balance of dietary n6 and n3 LC-PUFA provided for infants and in nutritional and neutraceutical applications could have profoundly different affects on metabolism and cell signaling, beyond that previously recognized.

Animals↗
PubMed2004

Rapid transcriptome responses of maize (Zea mays) to UV-B in irradiated and shielded tissues.

BACKGROUND: Depletion of stratospheric ozone has raised terrestrial levels of ultraviolet-B radiation (UV-B), an environmental change linked to an increased risk of skin cancer and with potentially deleterious consequences for plants. To better understand the processes of UV-B acclimation that result in altered plant morphology and physiology, we investigated gene expression in different organs of maize at several UV-B fluence rates and exposure times. RESULTS: Microarray hybridization was used to assess UV-B responses in directly exposed maize organs and organs shielded by a plastic that absorbs UV-B. After 8 hours of high UV-B, the abundance of 347 transcripts was altered: 285 were increased significantly in at least one organ and 80 were downregulated. More transcript changes occurred in directly exposed than in shielded organs, and the levels of more transcripts were changed in adult compared to seedling tissues. The time course of transcript abundance changes indicated that the response kinetics to UV-B is very rapid, as some transcript levels were altered within 1 hour of exposure. CONCLUSIONS: Most of the UV-B regulated genes are organ-specific. Because shielded tissues, including roots, immature ears, and leaves, displayed altered transcriptome profiles after exposure of the plant to UV-B, some signal(s) must be transmitted from irradiated to shielded tissues. These results indicate that there are integrated responses to UV-B radiation above normal levels. As the same total UV-B irradiation dose applied at three intensities elicited different transcript profiles, the transcriptome changes exhibit threshold effects rather than a reciprocal dose-effect response. Transcriptome profiling highlights possible signaling pathways and molecules for future research.

Acclimatization↗
PubMed2004

Genome2D: a visualization tool for the rapid analysis of bacterial transcriptome data.

Genome2D is a Windows-based software tool for visualization of bacterial transcriptome and customized datasets on linear chromosome maps constructed from annotated genome sequences. Genome2D facilitates the analysis of transcriptome data by using different color ranges to depict differences in gene-expression levels on a genome map. Such output format enables visual inspection of the transcriptome data, and will quickly reveal transcriptional units, without prior knowledge of expression level cutoff values. The compiled version of Genome2D is freely available for academic or non-profit use from http://molgen.biol.rug.nl/molgen/research/molgensoftware.php.

Bacterial Proteins↗