title: Quantification of insulin gene expression during development of pancreatic islet cells.
abstract: OBJECTIVE
  Despite great progress in understanding the transcriptional regulation of the development of insulin-secreting beta cells, the quantitative temporal expression of insulin gene(s) remains largely unknown. We here aimed to quantify insulin gene transcripts during development.
  
  
  METHODS
  We described bioinformatics algorithms to quantify (insulin) gene transcript abundance in sequential microarray data sets at the global level. Several molecular techniques were used to confirm our analyses.
  
  
  RESULTS
  We demonstrated that the expression of insulin genes was up-regulated at approximately 14-fold, 700- to 2000-fold, and 5000- to 6000-fold in Pdx1- and Ngn3-expressing cells and adult islets compared with definitive endodermal or embryonic stem cells, respectively. The expression of multiple genes encoding molecules involved in posttranslational modifications of insulin and glucose sensing was also elevated in the same period. All islet and associated genes determined with microarray data were confirmed not only to be up-regulated by real-time quantitative reverse transcriptase polymerase chain reaction but also that the magnitude of their increase quantified with these 2 methods was statistically highly correlated. Consistent with the above, green fluorescence protein expression under the control of the mouse insulin 1 promoter could be visualized in the pancreas from embryonic day (E) 11.5, increasing progressively through E13.5 to E15.5.
  
  
  CONCLUSIONS
  Our study provides a novel insight into islet developmental biology.
authors.affiliation: Centre for Diabetes Research, Western Australian Institute for Medical Research, Perth, Australia. jiang@waimr.uwa.edu.au
authors.forename: Fang-Xu
authors.initials: FX
authors.lastname: Jiang
authors.forename: Munish
authors.initials: M
authors.lastname: Mehta
authors.forename: Grant
authors.initials: G
authors.lastname: Morahan
mesh_terms: D000367:Age Factors; D000465:Algorithms; D000818:Animals; D051792:Basic Helix-Loop-Helix Proteins / Q000235:genetics; D002454:Cell Differentiation / Q000235:genetics; D049109:Cell Proliferation; D019295:Computational Biology; D030541:Databases, Genetic; D053595:Embryonic Stem Cells / Q000378:metabolism; D020869:Gene Expression Profiling / Q000379:methods*; D018507:Gene Expression Regulation, Developmental; D053263:Gene Regulatory Networks; D005865:Gestational Age; D018398:Homeodomain Proteins / Q000235:genetics; D007328:Insulin / Q000235:genetics*; D007515:Islets of Langerhans / Q000196:embryology / Q000254:growth & development* / Q000378:metabolism; D051379:Mice; D008810:Mice, Inbred C57BL; D008822:Mice, Transgenic; D009419:Nerve Tissue Proteins / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis; D011401:Promoter Regions, Genetic; D012333:RNA, Messenger / Q000378:metabolism; D020133:Reverse Transcriptase Polymerase Chain Reaction; D015534:Trans-Activators / Q000235:genetics
chemical_list: D051792:Basic Helix-Loop-Helix Proteins; D018398:Homeodomain Proteins; D007328:Insulin; D009419:Nerve Tissue Proteins; D012333:RNA, Messenger; D015534:Trans-Activators; C514817:Ins1 protein, mouse; C407737:Neurog3 protein, mouse; C084010:pancreatic and duodenal homeobox 1 protein