ABSTRACT
Human life expectancy is constantly increasing and aging has become a major risk factor for many diseases, although the underlying gene regulatory mechanisms are still unclear. Using transcriptomic and chromosomal conformation capture (Hi-C) data from human skin fibroblasts from individuals across different age groups, we identified a tight coupling between the changes in co-regulation and co-localization of genes. We obtained transcription factors, cofactors, and chromatin regulators that could drive the cellular aging process by developing a time-course prize-collecting Steiner tree algorithm. In particular, by combining RNA-Seq data from different age groups and protein-protein interaction data we determined the key transcription regulators and gene regulatory changes at different life stage transitions. We then mapped these transcription regulators to the 3D reorganization of chromatin in young and old skin fibroblasts. Collectively, we identified key transcription regulators whose target genes are spatially rearranged and correlate with changes in their expression, thereby providing potential targets for reverting cellular aging.
Subject(s)
Chromatin , Transcription Factors , Humans , Chromatin/genetics , Transcription Factors/metabolism , Gene Expression Regulation , Cellular Senescence/genetics , Gene Expression ProfilingABSTRACT
The development of mammary gland as a lactogenic tissue is a highly coordinated multistep process. The epithelial cells of lactiferous tubules undergo profound changes during the developmental window of puberty, pregnancy, and lactation. Several hormones including estrogen, progesterone, glucocorticoids and prolactin act in concert, and orchestrate the development of mammary gland. Understanding the gene regulatory networks that coordinate proliferation and differentiation of HC11 Mammary Epithelial stem-like Cells (MEC) under the influence of lactogenic hormones is critical for elucidating the mechanism of lactogenesis in detail. In this study, we analyzed transcriptome profiles of undifferentiated MEC (normal) and compared them with Murine Embryonic Stem Cells (ESC) using next-generation mRNA sequencing. Further, we analyzed the transcriptome output during lactogenic differentiation of MEC following treatment with glucocorticoids (primed state) and both glucocorticoids and prolactin together (prolactin state). We established stage-specific gene regulatory networks in ESC and MEC (normal, priming and prolactin states). We validated the top up-and downregulated genes in each stage of differentiation of MEC by RT-PCR and found that they are comparable with that of RNA-seq data. HC11 MEC display decreased expression of Pou5f1 and Sox2, which is crucial for the differentiation of MEC, which otherwise ensure pluripotency to ESC. Cited4 is induced during priming and is involved in milk secretion. MEC upon exposure to both glucocorticoids and prolactin undergo terminal differentiation, which is associated with the expression of several genes, including Xbp1 and Cbp that are required for cell growth and differentiation. Our study also identified differential expression of transcription factors and epigenetic regulators in each stage of lactogenic differentiation. We also analyzed the transcriptome data for the pathways that are selectively activated during lactogenic differentiation. Further, we found that selective expression of chromatin modulators (Dnmt3l, Chd9) in response to glucocorticoids suggests a highly coordinated stage-specific lactogenic differentiation of MEC.
Subject(s)
Embryonic Stem Cells/cytology , Animals , Cell Cycle/physiology , Cell Differentiation/genetics , Cell Differentiation/physiology , Cell Line , Embryonic Stem Cells/metabolism , Epithelial Cells/cytology , Epithelial Cells/metabolism , Female , Gene Regulatory Networks/genetics , Gene Regulatory Networks/physiology , Immunoblotting , Lactation/metabolism , Lactation/physiology , Mammary Glands, Animal/cytology , Mice , Pregnancy , Prolactin/metabolism , RNA, Messenger/metabolism , Reverse Transcriptase Polymerase Chain Reaction , X-Box Binding Protein 1/metabolismABSTRACT
OBJECTIVES: Understanding of transcriptional networks specifying HC11 murine mammary epithelial stem cell-like cells (MEC) in comparison with embryonic stem cells (ESCs) and their rewiring, under the influence of glucocorticoids (GC) and prolactin (PRL) hormones, is critical for elucidating the mechanism of lactogenesis. In this data note, we provide RNA sequencing data from murine MECs and ESCs, MECs treated with steroid hormone alone and in combination with PRL. This data could help in understanding temporal dynamics of mRNA transcription that impact the process of lactogenesis associated with mammary gland development. Further integration of these data sets with existing datasets of cells derived from various stages of mammary gland development and different types of breast tumors, should pave the way for effective prognosis and to develop therapies for breast cancer. DATA DESCRIPTION: We have generated RNA-sequencing data representing steady-state levels of mRNAs from murine ESCs, normal MECs (N), MECs primed (P) with hydrocortisone (HC) alone and in combination with PRL hormone by using Illumina sequencing platform. We have generated ~ 58 million reads for ESCs with an average length of ~ 100 nt and an average 115 million good quality mapped reads with an average length of ~ 150 nt for different stages of MECs differentiation.
