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Container-aided integrative QTL and RNA-seq analysis of Collaborative Cross mice supports distinct sex-oriented molecular modes of response in obesity

  • Binenbaum, Ilona1, 2
  • Atamni, Hanifa Abu-Toamih3
  • Fotakis, Georgios4, 5
  • Kontogianni, Georgia6
  • Koutsandreas, Theodoros5, 6
  • Pilalis, Eleftherios5, 6
  • Mott, Richard7
  • Himmelbauer, Heinz8, 9
  • Iraqi, Fuad A.3
  • Chatziioannou, Aristotelis A.5, 6
  • 1 National and Kapodistrian University of Athens, Athens, Greece , Athens (Greece)
  • 2 University of Patras, Patras, Greece , Patras (Greece)
  • 3 Tel-Aviv University, Tel-Aviv, Israel , Tel-Aviv (Israel)
  • 4 Medical University of Innsbruck, Innsbruck, Austria , Innsbruck (Austria)
  • 5 e-NIOS PC, Kallithea, Athens, Greece , Athens (Greece)
  • 6 Center of Systems Biology, Biomedical Research Foundation of the Academy of Athens, Athens, Greece , Athens (Greece)
  • 7 University College of London, London, UK , London (United Kingdom)
  • 8 Institute of Computational Biology, Department of Biotechnology, University of Life Sciences and Natural Resources, Vienna (BOKU), Vienna, Austria , Vienna (Austria)
  • 9 Centre for Genomic Regulation (CRG), Barcelona, Spain , Barcelona (Spain)
Published Article
BMC Genomics
Springer (Biomed Central Ltd.)
Publication Date
Nov 03, 2020
DOI: 10.1186/s12864-020-07173-x
Springer Nature


BackgroundThe Collaborative Cross (CC) mouse population is a valuable resource to study the genetic basis of complex traits, such as obesity. Although the development of obesity is influenced by environmental factors, underlying genetic mechanisms play a crucial role in the response to these factors. The interplay between the genetic background and the gene expression pattern can provide further insight into this response, but we lack robust and easily reproducible workflows to integrate genomic and transcriptomic information in the CC mouse population.ResultsWe established an automated and reproducible integrative workflow to analyse complex traits in the CC mouse genetic reference panel at the genomic and transcriptomic levels. We implemented the analytical workflow to assess the underlying genetic mechanisms of host susceptibility to diet induced obesity and integrated these results with diet induced changes in the hepatic gene expression of susceptible and resistant mice. Hepatic gene expression differs significantly between obese and non-obese mice, with a significant sex effect, where male and female mice exhibit different responses and coping mechanisms.ConclusionIntegration of the data showed that different genes but similar pathways are involved in the genetic susceptibility and disturbed in diet induced obesity. Genetic mechanisms underlying susceptibility to high-fat diet induced obesity are different in female and male mice. The clear distinction we observed in the systemic response to the high-fat diet challenge and to obesity between male and female mice points to the need for further research into distinct sex-related mechanisms in metabolic disease.

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