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Mammalian Genome

, Volume 27, Issue 9–10, pp 460–468 | Cite as

Heritability of in vitro phenotypes exhibited by murine adipose-derived stromal cells

  • Zixuan Jiang
  • David E. Harrison
  • Makayla E. Parsons
  • Susan McClatchy
  • Lawrence Jacobs
  • Robert Pazdro
Article

Abstract

Adipose-derived stromal cells (ADSCs) exhibit significant potential as therapeutic agents to promote tissue regeneration. Success of ADSC-based therapies is dependent upon efficient cell expansion in vitro as well as postinjection survival in the caustic milieu of damaged tissue. Genetic background regulates ADSC proliferative capacity and stress resistance, but the extent of the genetic effect size is not completely defined. The present study aimed to quantify phenotypic ranges and heritability of in vitro ADSC characteristics. ADSCs were isolated from mice representing 16 genetically diverse inbred mouse strains, including 12 classical inbred strains and four wild-derived strains. Cells were grown in vitro, and proliferative capacity and oxidative stress resistance were assessed. The fold change for ADSC growth ranged from 0.87 (BALB/cByJ) to 23.60 (POHN/DehJ), relative to original seeding density. The heritability of proliferative capacity was estimated to be 0.6462 (p = 9.967 × 10−15), and this phenotype was not associated with other ADSC traits. Cell viability following H2O2 treatment ranged from 39.81 % (CAST/EiJ) to 91.60 % (DBA/2 J), and the heritability of this phenotype was calculated as 0.6146 (p = 1.22 × 10−12). Relationships between cell viability and weight of the donor fat pad were also discovered. Donor genetic background is a major determinant of in vitro ADSC phenotypes. This study supports the development of forward genetics strategies to identify genes that underlie ADSC phenotypic diversity, which will inform efforts to improve cell-based therapies.

Keywords

Osteogenic Differentiation Stress Resistance Proliferative Capacity Total Body Weight Oxidative Stress Resistance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors gratefully thank Joanne Currer, Kathrine Weeks, and Kendall Taylor for reviewing this manuscript, as well as Mike Astle, Vicki Hutchinson, and Nelson Durgin for their helpful assistance. The authors wish to thank Gary Churchill for his support of this project. This work was supported by the following grants from the National Institutes of Health: AG032333 (DEH), GM101723 (RP), and P50 GM076468 (SM, Churchill).

Compliance with ethical standards

Conflict of interest

The authors have no conflicting interests to report.

Supplementary material

335_2016_9655_MOESM1_ESM.pdf (309 kb)
Supplementary material 1 (PDF 308 kb)

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Zixuan Jiang
    • 1
  • David E. Harrison
    • 2
  • Makayla E. Parsons
    • 2
  • Susan McClatchy
    • 2
  • Lawrence Jacobs
    • 2
  • Robert Pazdro
    • 1
  1. 1.Department of Foods and NutritionUniversity of GeorgiaAthensUSA
  2. 2.The Jackson LaboratoryBar HarborUSA

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