Poster Presentation Australian Diabetes Society and the Australian Diabetes Educators Association Annual Scientific Meeting 2014

Using RNA-Seq to Characterise Adipogenic Networks (#228)

Jingjing He 1 , Kevin Gillinder 1 , Graham Magor 1 , Andrew Perkins 1 , John Prins 1 , Jon Whitehead
  1. Mater Research Institute – University of Queensland, Woolloongabba, QLD, Australia

A proportion of obese people are metabolically healthy demonstrating obesity per se does not compromise metabolism. One explanation for this paradox is that ‘fit fat’ people have a greater capacity for adipogenesis than unhealthy counterparts.  Higher rates of adipogenesis facilitate adipose tissue expansion by increasing adipocyte cell number (hyperplasia) rather than increasing adipocyte cell size (hypertrophy) raising the possibility that promoting adipogenesis may reduce obesity-related diseases.

We identified FGF-1 as a pro-adipogenic factor (1) and microarrays/functional investigations revealed BMP and Activin Membrane-Bound Inhibitor (BAMBI) as a key effector that sits between FGF-1 and the master adipogenic regulator PPARg (2).  In the current study we have used RNA-Seq to define discrete adipogenic FGF-1, BAMBI and PPARg-dependent networks. 

Human SGBS (Simpson Golabi Behmel Syndrome) preadipocytes were incubated -/+ FGF-1; -/+ BAMBI siRNA; -/+ PPARg siRNA for 72 h and harvested at 0 or 24 h post-induction of differentiation (n=4/condition).  RNA-Seq and preliminary analysis revealed significant changes in >1500 genes at 0 h. Of these, 15 genes were FGF-1-responsive and PPARγ-independent/unaffected by BAMBI knockdown; 15 genes were responsive to FGF-1 or BAMBI knockdown independent of PPARg; 14 genes were responsive to FGF-1 or BAMBI knockdown in a PPARg-dependent manner. These findings reveal a number of novel candidate genes, not previously associated with adipogenesis that will allow us to define discrete adipogenic networks.

To rationalise subsequent studies we are screening mRNA levels (qRT-PCR) of 40 candidate genes at the 24 h time point and performing a preliminary functional screen, assessing the effects of candidate gene knockdown (siRNA) on adipogenesis (defined by morphology / genetic markers), before selecting a subset of candidates for detailed functional analyses.  These studies will increase understanding of the pathways governing adipogenesis and may reveal new strategies to reduce obesity-associated diseases.

  1. L. J. Hutley et al., Diabetes 53, 3097 (2004)
  2. X. Luo et al., Diabetes 61, 124 (January 1, 2012, 2012)