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1.
BMC Bioinformatics ; 8: 195, 2007 Jun 11.
Artigo em Inglês | MEDLINE | ID: mdl-17562008

RESUMO

BACKGROUND: Affymetrix GeneChips are a popular platform for performing whole-genome experiments on the transcriptome. There are a range of different calibration steps, and users are presented with choices of different background subtractions, normalisations and expression measures. We wished to establish which of the calibration steps resulted in the biggest uncertainty in the sets of genes reported to be differentially expressed. RESULTS: Our results indicate that the sets of genes identified as being most significantly differentially expressed, as estimated by the z-score of fold change, is relatively insensitive to the choice of background subtraction and normalisation. However, the contents of the gene list are most sensitive to the choice of expression measure. This is irrespective of whether the experiment uses a rat, mouse or human chip and whether the chip definition is made using probe mappings from Unigene, RefSeq, Entrez Gene or the original Affymetrix definitions. It is also irrespective of whether both Present and Absent, or just Present, Calls from the MAS5 algorithm are used to filter genelists, and this conclusion holds for genes of differing intensities. We also reach the same conclusion after assigning genes to be differentially expressed using t-statistics, although this approach results in a large amount of false positives in the sets of genes identified due to the small numbers of replicates typically used in microarray experiments. CONCLUSION: The major calibration uncertainty that biologists need to consider when analysing Affymetrix data is how their multiple probe values are condensed into one expression measure.


Assuntos
Algoritmos , Artefatos , Perfilação da Expressão Gênica/instrumentação , Perfilação da Expressão Gênica/normas , Análise de Sequência com Séries de Oligonucleotídeos/instrumentação , Análise de Sequência com Séries de Oligonucleotídeos/normas , Calibragem , Interpretação Estatística de Dados , Controle de Qualidade , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Reino Unido
2.
Mol Neurobiol ; 53(6): 3724-3739, 2016 08.
Artigo em Inglês | MEDLINE | ID: mdl-26138449

RESUMO

Although the adult brain contains neural stem cells (NSCs) that generate new neurons throughout life, these astrocyte-like populations are restricted to two discrete niches. Despite their terminally differentiated phenotype, adult parenchymal astrocytes can re-acquire NSC-like characteristics following injury, and as such, these 'reactive' astrocytes offer an alternative source of cells for central nervous system (CNS) repair following injury or disease. At present, the mechanisms that regulate the potential of different types of astrocytes are poorly understood. We used in vitro and ex vivo astrocytes to identify candidate pathways important for regulation of astrocyte potential. Using in vitro neural progenitor cell (NPC)-derived astrocytes, we found that exposure of more lineage-restricted astrocytes to either tumor necrosis factor alpha (TNF-α) (via nuclear factor-κB (NFκB)) or the bone morphogenetic protein (BMP) inhibitor, noggin, led to re-acquisition of NPC properties accompanied by transcriptomic and epigenetic changes consistent with a more neurogenic, NPC-like state. Comparative analyses of microarray data from in vitro-derived and ex vivo postnatal parenchymal astrocytes identified several common pathways and upstream regulators associated with inflammation (including transforming growth factor (TGF)-ß1 and peroxisome proliferator-activated receptor gamma (PPARγ)) and cell cycle control (including TP53) as candidate regulators of astrocyte phenotype and potential. We propose that inflammatory signalling may control the normal, progressive restriction in potential of differentiating astrocytes as well as under reactive conditions and represent future targets for therapies to harness the latent neurogenic capacity of parenchymal astrocytes.


Assuntos
Astrócitos/patologia , Inflamação/patologia , Neurogênese , Animais , Animais Recém-Nascidos , Astrócitos/efeitos dos fármacos , Astrócitos/metabolismo , Proteína Morfogenética Óssea 4/metabolismo , Desdiferenciação Celular/efeitos dos fármacos , Desdiferenciação Celular/genética , Linhagem Celular , Proliferação de Células/efeitos dos fármacos , Sistema Nervoso Central/patologia , Epigênese Genética/efeitos dos fármacos , Perfilação da Expressão Gênica , Regulação da Expressão Gênica/efeitos dos fármacos , Histonas/metabolismo , Inflamação/metabolismo , Camundongos , Modelos Biológicos , NF-kappa B/metabolismo , Células-Tronco Neurais/efeitos dos fármacos , Células-Tronco Neurais/metabolismo , Neurogênese/efeitos dos fármacos , Fenótipo , Regiões Promotoras Genéticas/genética , Processamento de Proteína Pós-Traducional/efeitos dos fármacos , Transdução de Sinais/efeitos dos fármacos , Transdução de Sinais/genética , Fatores de Tempo , Transcriptoma/efeitos dos fármacos , Transcriptoma/genética , Fator de Necrose Tumoral alfa/farmacologia
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