Project description:We used two hybrid combinations and their 4 parents as materials. One week after topping the tobacco plant, samples were taken, including three tissues: root, stalk, and leaf. The RNA of these samples was extracted, and transcriptome sequencing analysis was carried out to explore the transcriptional profile differences between hybrids and their parents, and to analyze the gene differential expression between different tissues.
Project description:The mouse trachea is thought to contain two distinct stem cell compartments that contribute to airway repair—basal cells in the surface airway epithelium (SAE) and an unknown submucosal gland (SMG) cell type. Whether a lineage relationship exists between these two stem cell compartments remains unclear. Using lineage tracing of glandular myoepithelial cells (MECs), we demonstrate that MECs can give rise to seven cell types of the SAE and SMGs following severe airway injury. MECs progressively adopted a basal cell phenotype on the SAE and established lasting progenitors capable of further regeneration following reinjury. MECs activate Wnt-regulated transcription factors (Lef-1/TCF7) following injury and Lef-1 induction in cultured MECs promoted transition to a basal cell phenotype. Surprisingly, dose-dependent MEC conditional activation of Lef-1 in vivo promoted self-limited airway regeneration in the absence of injury. Thus, modulating the Lef-1 transcriptional program in MEC-derived progenitors may have regenerative medicine applications for lung diseases.
Project description:A comparative analysis of gene expression of perinate or adult Aire-GFP+ and GFP- MECs in WT or Aire-KO thymus Aire+ and Aire- MECs were sorted from adults (5 weeks old) or perinates (0-3 days old) of Aire-driven Igrp-GFP (Adig) mice in Aire-WT and -KO background. RNA from whole samples was amplified, labeled, and hybridized to Affymetrix Mouse Gene 1.0 ST Arrays.
Project description:Microtoming Coupled with Microarray Analysis to Evaluate Potential Differences in the Metabolic Status of Geobacter sulfurreducens at Different Depths in Anode Biofilms Differences in the Metabolic Status of Geobacter sulfurreducens at Different Depths in A Current Producing Biofilm Further insight into the metabolic status of cells within anode biofilms is essential for understanding the functioning of microbial fuel cells and developing strategies to optimize their power output. In order to further compare the metabolic status of cells growing close to the anode versus cells in the outer portion of the anode biofilm, mature anode biofilms were treated to stop turnover over of mRNA and then encased in resin which was sectioned into 100 nm shavings with a diamond knife and pooled into inner (0-20 µm from anode surface) and outer (30-60 µm) fractions. Whole genome DNA microarray analysis of RNA extracted from the shavings revealed that, at a 2-fold lower threshold, there were 146 genes that had significant (p<0.05), differences in transcript abundance between the inner and outer portions of the biofilm. Only 1 gene, GSU0093, a hypothetical ABC transporter, had significantly higher transcript abundances in the outer biofilm. Genes with lower transcript abundance in the outer biofilm included genes for ribosomal proteins and NADH dehydrogenase, suggesting that cells in the outer biofilm had lower metabolic rates. However, the differences in transcript abundance were relatively low (<3-fold) and the outer biofilm did not have significantly lower expression of the genes for TCA cycle enzymes which previous studies have demonstrated are sensitive indicators of changes in rates of metabolism in G. sulfurreducens. There also was no significant difference in the transcript levels for outer-surface cell components thought to be important in electron transfer in anode biofilms. Lower expression of genes involved in stress responses in the outer biofilm may reflect the development of low pH near the surface of the anode. The results of the metabolic staining and gene expression studies suggest that cells throughout the biofilm are metabolically active and can potentially contribute to current production. The microtoming/microarray strategy described here may be useful for evaluating gene expression with depth in a diversity of microbial biofilms.