@article {Ayroles009027, author = {Julien F. Ayroles and Sean M. Buchanan and Chelsea Jenney and Kyobi Skutt-Kakaria and Jennifer Grenier and Andrew G. Clark and Daniel L. Hartl and Benjamin L. de Bivort}, title = {Behavioral individuality reveals genetic control of phenotypic variability}, elocation-id = {009027}, year = {2014}, doi = {10.1101/009027}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Variability is ubiquitous in nature and a fundamental feature of complex systems. Few studies, however, have investigated variance itself as a trait under genetic control. By focusing primarily on trait means and ignoring the effect of alternative alleles on trait variability, we may be missing an important axis of genetic variation contributing to phenotypic differences among individuals1,2. To study genetic effects on individual-to-individual phenotypic variability (or intragenotypic variability), we used a panel of Drosophila inbred lines3 and focused on locomotor handedness4, in an assay optimized to measure variability. We discovered that some lines had consistently high levels of intragenotypic variability among individuals while others had low levels. We demonstrate that the degree of variability is itself heritable. Using a genome-wide association study (GWAS) for the degree of intragenotypic variability as the phenotype across lines, we identified several genes expressed in the brain that affect variability in handedness without affecting the mean. One of these genes, Ten-a, implicated a neuropil in the central complex5 of the fly brain as influencing the magnitude of behavioral variability, a brain region involved in sensory integration and locomotor coordination6. We have validated these results using genetic deficiencies, null alleles, and inducible RNAi transgenes. This study reveals the constellation of phenotypes that can arise from a single genotype and it shows that different genetic backgrounds differ dramatically in their propensity for phenotypic variability. Because traditional mean-focused GWASs ignore the contribution of variability to overall phenotypic variation, current methods may miss important links between genotype and phenotype.Abbreviations DGRP: Drosophila Genome Reference Panel; ANOMV: Analysis of means for variance; QTL: quantitative trait loci, GWAS: genome wide association study, MAD: median absolute deviation. GWAS: genome wide association study, CI: confidence interval.}, URL = {https://www.biorxiv.org/content/early/2014/09/12/009027}, eprint = {https://www.biorxiv.org/content/early/2014/09/12/009027.full.pdf}, journal = {bioRxiv} }