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RNA sequencing of murine mammary epithelial stem-like cells (HC11) undergoing lactogenic differentiation and its comparison with embryonic stem cells

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 mech...

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Detalles Bibliográficos
Autores principales: Sornapudi, Trinadha Rao, Nayak, Rakhee, Guthikonda, Prashanth Kumar, Kethavath, Srinivas, Yellaboina, Sailu, Kurukuti, Sreenivasulu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896049/
https://www.ncbi.nlm.nih.gov/pubmed/29642945
http://dx.doi.org/10.1186/s13104-018-3351-4
Descripción
Sumario: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.