Several studies have demonstrated that Dicer-null mouse islet beta cells show up to 90% reduction in insulin gene transcription [1,2,3]. Similar mechanisms are believed to exist in human islet beta cells, but no specific micro(mi)RNAs are yet identified (in humans or mice) to explain the observations made using Dicer-null mouse beta cells. We profiled 758 known and validated miRNAs in ~700 different human tissues (including over 220 human islet preparations) and used machine-learning algorithms to identify a signature of 22 miRNAs that are predictive and associated with insulin gene expression. We generated three sources of Doxycycline-regulated cell lines: human islet-derived progenitor cells (hIPCs), pancreatic ductal cells (PANC-1) and liver cells (HUH7) (not shown), to express each of the 22 different miRNAs. We are assessing the expression of 50 different gene transcripts (islet hormones, transcription factors, key ligands/receptors, glucose transporters) and the selected miRNAs. We aim to generate these data characterising the impact of forced expression of key islet-associated miRNAs on the expression of pancreatic gene transcripts, so as to identify a select set of miRNAs that are necessary and essential for insulin gene transcription. The major aim of this study is to understand if regulated overexpression of key islet miRNAs drives the expression of pancreatic islet transcription factors, key islet-associated genes and major islet hormones. Further studies are planned to identify miRNAs that can be used in a stage-specific regulated overexpression protocol to assess if forced insulin-associated miRNA overexpression could kick-start/boot-up endogenous islet-enriched miRNA expression and if it improves the differentiation potential of hIPCs. If successful, in vitro and in vivo functional studies would be needed to assess their potential for cell replacement therapy in diabetes.