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Behavior Genetics

, Volume 47, Issue 2, pp 227–243 | Cite as

Genetic and Genomic Response to Selection for Food Consumption in Drosophila melanogaster

  • Megan E. Garlapow
  • Logan J. Everett
  • Shanshan Zhou
  • Alexander W. Gearhart
  • Kairsten A. Fay
  • Wen Huang
  • Tatiana V. Morozova
  • Gunjan H. Arya
  • Lavanya Turlapati
  • Genevieve St. Armour
  • Yasmeen N. Hussain
  • Sarah E. McAdams
  • Sophia Fochler
  • Trudy F. C. Mackay
Original Research

Abstract

Food consumption is an essential component of animal fitness; however, excessive food intake in humans increases risk for many diseases. The roles of neuroendocrine feedback loops, food sensing modalities, and physiological state in regulating food intake are well understood, but not the genetic basis underlying variation in food consumption. Here, we applied ten generations of artificial selection for high and low food consumption in replicate populations of Drosophila melanogaster. The phenotypic response to selection was highly asymmetric, with significant responses only for increased food consumption and minimal correlated responses in body mass and composition. We assessed the molecular correlates of selection responses by DNA and RNA sequencing of the selection lines. The high and low selection lines had variants with significantly divergent allele frequencies within or near 2081 genes and 3526 differentially expressed genes in one or both sexes. A total of 519 genes were both genetically divergent and differentially expressed between the divergent selection lines. We performed functional analyses of the effects of RNAi suppression of gene expression and induced mutations for 27 of these candidate genes that have human orthologs and the strongest statistical support, and confirmed that 25 (93 %) affected the mean and/or variance of food consumption.

Keywords

Realized heritability DNA-seq RNA-seq Feeding behavior CAFE assay 

Notes

Acknowledgments

Stocks obtained from the VDRC and Bloomington Drosophila Stock Center (NIH P40OD018537) were used in this study.

Authors’ contributions

MEG and TFCM conceived and designed the experiments. MEG, AWG and KAF performed the selection experiment. MEG performed the analysis of body size. SZ performed the analyses of molecular metabolites. SZ and SEM obtained all DNA sequence data. GHA, LT, GSA and YNH obtained all RNA sequence data. LJE analyzed the DNA and RNA sequence data and performed the drift simulations. TVM and SF performed functional validations of candidate genes. WH created and maintained the AIP. MEG, LJE, SZ, WH, TVM and TFCM wrote the manuscript.

Funding

This work was funded by National Institutes of Health grants R01 GM45146 and R01 AA016560 to TFCM.

Compliance with ethical standards

Conflict of interest

Megan E. Garlapow, Logan J. Everett, Shanshan Zhou, Alexander W. Gearhart, Kairsten A. Fay, Wen Huang, Tatiana V. Morozova, Gunjan H. Arya, Lavanya Turlapati, Genevieve St. Armour, Yasmeen N. Hussain, Sarah E. McAdams, Sophia Fochler and Trudy F. C. Mackay declare that they have no competing interests.

Human and animal rights and Informed consent

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Megan E. Garlapow
    • 1
    • 2
    • 3
  • Logan J. Everett
    • 1
    • 2
    • 3
    • 4
  • Shanshan Zhou
    • 1
    • 2
    • 3
    • 4
  • Alexander W. Gearhart
    • 2
    • 3
  • Kairsten A. Fay
    • 2
    • 3
  • Wen Huang
    • 1
    • 2
    • 3
    • 4
  • Tatiana V. Morozova
    • 2
    • 3
  • Gunjan H. Arya
    • 2
    • 3
  • Lavanya Turlapati
    • 2
    • 3
  • Genevieve St. Armour
    • 2
    • 3
  • Yasmeen N. Hussain
    • 2
    • 3
  • Sarah E. McAdams
    • 2
    • 3
  • Sophia Fochler
    • 2
    • 3
    • 5
  • Trudy F. C. Mackay
    • 1
    • 2
    • 3
    • 4
  1. 1.Program in GeneticsNorth Carolina State UniversityRaleighUSA
  2. 2.Department of Biological SciencesNorth Carolina State UniversityRaleighUSA
  3. 3.W. M. Keck Center for Behavioral BiologyNorth Carolina State UniversityRaleighUSA
  4. 4.Initiative for Biological ComplexityNorth Carolina State UniversityRaleighUSA
  5. 5.School of Biosciences and Medicine, Faculty of Health and Medical SciencesUniversity of SurreyGuildfordUK

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