E-MTAB-2816
Whole transcriptome profiling of beta cell development in the mouse
Knowledge of the genetic signatures of specific pancreatic cellular populations, both during development and in the adult animal, provides an objective basis for evaluating genetic signatures of cultured human embryonic stem cells (hESCs) and reprogrammed pancreatic mouse cells.  Previous transcriptome profiling studies have utilized DNA microarrays, which have well-defined limitations, and few have utilized FACS-purified cell populations.  To overcome both of these limitations we utilized a series of mice with fluorescent reporter alleles (Sox17, Pdx1, Ptf1a, Ngn3, Insm1) or transgene (Ins1) to isolate three biological replicates of 12 different  pancreatic progenitor or adult cell populations between embryonic day 8.0 and post-natal day 60.  These RNAs were then used to make 36 libraries which were sequenced to an average depth of 50 million reads each.  After mapping these reads to  mouse genome using a standardized analysis pipeline the resulting datasets were analyzed in several ways.
Knowledge of the genetic signatures of specific pancreatic cellular populations, both during development and in the adult animal, provides an objective basis for evaluating genetic signatures of cultured human embryonic stem cells (hESCs) and reprogrammed pancreatic mouse cells.  Previous transcriptome profiling studies have utilized DNA microarrays, which have well-defined limitations, and few have utilized FACS-purified cell populations.  To overcome both of these limitations we utilized a series of mice with fluorescent reporter alleles (Sox17, Pdx1, Ptf1a, Ngn3, Insm1) or transgene (Ins1) to isolate three biological replicates of 12 different  pancreatic progenitor or adult cell populations between embryonic day 8.0 and post-natal day 60.  These RNAs were then used to make 36 libraries which were sequenced to an average depth of 50 million reads each.  After mapping these reads to  mouse genome using a standardized analysis pipeline the resulting datasets were analyzed in several ways.