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Single-cell RNA-Seq analysis reveals dynamic trajectories during mouse liver development. | LitMetric

Single-cell RNA-Seq analysis reveals dynamic trajectories during mouse liver development.

BMC Genomics

Key Laboratory of Systems Biomedicine (Ministry of Education) and Collaborative Innovation Center of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.

Published: December 2017

AI Article Synopsis

  • The study explores the developmental stages of fetal liver stem/progenitor cells (LSPCs) in mice, aiming to better understand their differentiation and maturation through a marker-free single-cell RNA sequencing approach.
  • Researchers analyzed transcriptional profiles from 507 cells across various stages of liver development, discovering distinct genetic controls guiding LSPCs' developmental trajectories.
  • The findings reveal key insights into LSPCs' fate decisions and suggest potential isolation biomarkers, contributing valuable resources for further study.

Article Abstract

Background: The differentiation and maturation trajectories of fetal liver stem/progenitor cells (LSPCs) are not fully understood at single-cell resolution, and a priori knowledge of limited biomarkers could restrict trajectory tracking.

Results: We employed marker-free single-cell RNA-Seq to characterize comprehensive transcriptional profiles of 507 cells randomly selected from seven stages between embryonic day 11.5 and postnatal day 2.5 during mouse liver development, and also 52 Epcam-positive cholangiocytes from postnatal day 3.25 mouse livers. LSPCs in developing mouse livers were identified via marker-free transcriptomic profiling. Single-cell resolution dynamic developmental trajectories of LSPCs exhibited contiguous but discrete genetic control through transcription factors and signaling pathways. The gene expression profiles of cholangiocytes were more close to that of embryonic day 11.5 rather than other later staged LSPCs, cuing the fate decision stage of LSPCs. Our marker-free approach also allows systematic assessment and prediction of isolation biomarkers for LSPCs.

Conclusions: Our data provide not only a valuable resource but also novel insights into the fate decision and transcriptional control of self-renewal, differentiation and maturation of LSPCs.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5715535PMC
http://dx.doi.org/10.1186/s12864-017-4342-xDOI Listing

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