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Use of multiple time points to model parotid differentiation.
Metzler, Melissa A; Appana, Savitri; Brock, Guy N; Darling, Douglas S.
Afiliação
  • Metzler MA; Department of Oral Immunology and Infectious Diseases, University of Louisville, Louisville, KY 40202, United States ; Department of Biochemistry & Molecular Biology, University of Louisville, Louisville, KY 40202, United States.
  • Appana S; Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, United States.
  • Brock GN; Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, United States.
  • Darling DS; Department of Oral Immunology and Infectious Diseases, University of Louisville, Louisville, KY 40202, United States ; Department of Biochemistry & Molecular Biology, University of Louisville, Louisville, KY 40202, United States.
Genom Data ; 5: 82-8, 2015 Sep.
Article em En | MEDLINE | ID: mdl-26484231
In order to understand the process of terminal differentiation in salivary acinar cells, mRNA and microRNA expression was measured across the month long process of differentiation in the parotid gland of the rat. Acinar cells were isolated at either nine time points (mRNA) or four time points (microRNA) in triplicate using laser capture microdissection (LCM). One of the values of this dataset comes from the high quality RNA (RIN > 7) that was used in this study, which can be prohibitively difficult to obtain from such an RNaseI-rich tissue. Global mRNA expression was measured by rat genome microarray hybridization (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE65586), and expression of microRNAs by qPCR array (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE65324). Comparing expression at different ages, 2656 mRNAs and 64 microRNAs were identified as differentially expressed. Because mRNA expression was sampled at many time points, clustering and regression analysis were able to identify dynamic expression patterns that had not been implicated in acinar differentiation before. Integration of the two datasets allowed the identification of microRNA target genes, and a gene regulatory network. Bioinformatics R code and additional details of experimental methods and data analysis are provided.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Genom Data Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Genom Data Ano de publicação: 2015 Tipo de documento: Article