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Genetic Analysis of Micro-environmental Plasticity in Drosophila melanogaster

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  • Paper

    Final published version, 61.8 KB, PDF document


  • Fabio Morgante, Department of Biological Sciences, North Carolina State University, Raleigh, Denmark
  • Daniel A Sorensen
  • Peter Sørensen
  • Christian Maltecca, North Carolina State University, Raleigh, United States
  • Trudy F C Mackay, Department of Biological Sciences and Program in Genetics, North Carolina State University, United States
Quantitative genetic models recognize the potential for genotype by environment interaction, whereby different genotypes have different plastic responses to changes in macro-environmental conditions. Recently, it has been recognized that micro-environmental plasticity (‘residual’ variance) may also be genetically variable. This study utilized the Drosophila Genetic Reference Panel (DGRP) to accurately estimate the genetic variance of micro-environmental plasticity for chill coma recovery time and startle response. Estimates of broad sense heritabilities for both traits are substantial (from 0.51 to 0.77), of the same order as the heritability at the level of the trait mean for startle response and even larger for chill coma recovery. Genome wide association analyses identified molecular variants (from 15 to 31 depending on the sex and the trait) associated with micro-environmental plasticity. These findings indicate the potential for response to artificial selection for micro-environmental plasticity
Original languageEnglish
Publication year17 Aug 2014
Number of pages1
Publication statusPublished - 17 Aug 2014
Event10th World Congress on Genetics Applied to Livestock Production (WCGALP) - The Westin Bayshore, 1601 Bayshore Drive, Vancouver, BC V6G 2V4, Vancouver, Canada
Duration: 17 Aug 201422 Aug 2014
Conference number: 10th


Conference10th World Congress on Genetics Applied to Livestock Production (WCGALP)
LocationThe Westin Bayshore, 1601 Bayshore Drive, Vancouver, BC V6G 2V4

    Research areas

  • Environmental plasticity Genetic parameters GWAS

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