Unwinding the Novel Genes Involved in the Differentiation of Embryonic Stem Cells into Insulin-Producing Cells: A Network-Based Approach

  • T. Femlin Blessia
  • Sachidanand Singh
  • J. Jannet Vennila
Original Research Article

DOI: 10.1007/s12539-016-0148-9

Cite this article as:
Blessia, T.F., Singh, S. & Vennila, J.J. Interdiscip Sci Comput Life Sci (2017) 9: 88. doi:10.1007/s12539-016-0148-9


Diabetes is one of the main causes of death in the world. Diabetes is marked by high blood glucose levels and develops when the body doesn’t produce enough insulin or is not able to use insulin effectively, or both. Type I diabetes is a chronic sickness caused by lack of insulin due to the autoimmune destruction of pancreatic insulin-producing beta cells. Research on permanent cure for diabetes is in progress with several remarkable findings in the past few decades among which stem cell therapy has turned out to be a promising way to cure diabetes. Stem cells have the remarkable potential to differentiate into glucose-responsive beta cells through controlled differentiation protocols. Discovering novel targets that could potentially influence the differentiation to specific cell type will help in disease therapy. The present work focuses on finding novel genes or transcription factors involved in the human embryonic stem cell differentiation into insulin-producing beta cells using network biology approach. The interactome of 321 genes and their associated molecules involved in human embryonic stem cell differentiation into beta cells was constructed, which includes 1937 nodes and 8105 edges with a scale-free topology. Pathway analysis for the hubs obtained through MCODE revealed that four highly interactive hubs were relevant to embryonic stem cell differentiation into insulin-producing cells. Their role in different pathways and stem cell differentiation was studied. Centrality parameters were applied to identify the potential controllers of the differentiation processes: BMP4, SALL4, ZIC1, NTS, RNF2, FOXO1, AKT1 and GATA4. This type of approach gives an insight to identify potential genes/transcription factors which may play influential role in many complex biological processes.


Diabetes Embryonic stem cells Network biology Interactome Topological parameters 

Supplementary material

12539_2016_148_MOESM1_ESM.xlsx (23 kb)
Supplementary material 1 (XLSX 22 kb)

Copyright information

© International Association of Scientists in the Interdisciplinary Areas and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • T. Femlin Blessia
    • 1
  • Sachidanand Singh
    • 1
  • J. Jannet Vennila
    • 2
  1. 1.Department of Bioinformatics, School of Biotechnology and Health SciencesKarunya UniversityCoimbatoreIndia
  2. 2.Department of Biotechnology, School of Biotechnology and Health SciencesKarunya UniversityCoimbatoreIndia

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