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. Due to the very limited number of cells at early timepoints all of these RNAs were amplified prior to generating 36 libraries which were sequenced to an average depth of 50 million reads each. After mapping these reads to the mouse genome using a standardized analysis pipeline the resulting datasets were analyzed in three different ways. First, a series of temporally-relevant pairwise comparisons were obtained. Second, we used Weighted Gene Coexpression Network Analysis to identify 25 modules containing 25 to 2154 genes per module. Collectively, these modules contain 14,819 genes that are reproducibly expressed in at least one of these populations. Third, these modules form the basis for comparisons with hESC-derived populations generated by directed differentiation. For example, we have begun comparing the hESC-derived signatures from Xie et al. (Cell Stem Cells, 2013) with the gene expression signatures associated with specific mouse developmental modules. As an extension to this project we also performed RNA-seq analysis on six unamplified cell populations in order to validate the initial RNA-Seq datasets and to assess gene expression changes that occur during the maturation phase of beta cell development. To accomplish this we generated and sequenced libraries from pancreatic beta cells at P0, P4, P12 and P60, and libraries from Ngn3EGFP/+ and Ngn3EGFP/EGFP cell populations at E15.5. By utilizing genetic signatures from a module containing genes specific to the E16.5 and P60 beta cell populations we have identified several genes that may be essential for beta cell maturation.
Whole transcriptome profiling of beta cell development in the mouse
Sanavia T;
2013-01-01
Abstract
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. Due to the very limited number of cells at early timepoints all of these RNAs were amplified prior to generating 36 libraries which were sequenced to an average depth of 50 million reads each. After mapping these reads to the mouse genome using a standardized analysis pipeline the resulting datasets were analyzed in three different ways. First, a series of temporally-relevant pairwise comparisons were obtained. Second, we used Weighted Gene Coexpression Network Analysis to identify 25 modules containing 25 to 2154 genes per module. Collectively, these modules contain 14,819 genes that are reproducibly expressed in at least one of these populations. Third, these modules form the basis for comparisons with hESC-derived populations generated by directed differentiation. For example, we have begun comparing the hESC-derived signatures from Xie et al. (Cell Stem Cells, 2013) with the gene expression signatures associated with specific mouse developmental modules. As an extension to this project we also performed RNA-seq analysis on six unamplified cell populations in order to validate the initial RNA-Seq datasets and to assess gene expression changes that occur during the maturation phase of beta cell development. To accomplish this we generated and sequenced libraries from pancreatic beta cells at P0, P4, P12 and P60, and libraries from Ngn3EGFP/+ and Ngn3EGFP/EGFP cell populations at E15.5. By utilizing genetic signatures from a module containing genes specific to the E16.5 and P60 beta cell populations we have identified several genes that may be essential for beta cell maturation.
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