Numbering the hairs on our heads: The shared challenge and promise of phenomics
David Houle1
+ Author Affiliations
Department of Biological Science, Florida State University, Tallahassee, FL 32306-4295
Edited by Diddahally R. Govindaraju, Boston University School of Medicine, Boston, MA, and accepted by the Editorial Board September 21, 2009 (received for review July 22, 2009)
Abstract
Evolution and medicine share a dependence on the genotype–phenotype map. Although genotypes exist and are inherited in a discrete space convenient for many sorts of analyses, the causation of key phenomena such as natural selection and disease takes place in a continuous phenotype space whose relationship to the genotype space is only dimly grasped. Direct study of genotypes with minimal reference to phenotypes is clearly insufficient to elucidate these phenomena. Phenomics, the comprehensive study of phenotypes, is therefore essential to understanding biology. For all of the advances in knowledge that a genomic approach to biology has brought, awareness is growing that many phenotypes are highly polygenic and susceptible to genetic interactions. Prime examples are common human diseases. Phenomic thinking is starting to take hold and yield results that reveal why it is so critical. The dimensionality of phenotypic data are often extremely high, suggesting that attempts to characterize phenotypes with a few key measurements are unlikely to be completely successful. However, once phenotypic data are obtained, causation can turn out to be unexpectedly simple. Phenotypic data can be informative about the past history of selection and unexpectedly predictive of long-term evolution. Comprehensive efforts to increase the throughput and range of phenotyping are an urgent priority.
diseasegenotype–phenotype mapnatural selectionG matrixdimensionality
Footnotes
1E-mail: dhoule@bio.fsu.eduAuthor contributions: D.H. designed research, performed research, analyzed data, and wrote the paper.
The author declares no conflict of interest.
This article is a PNAS Direct Submission. D.R.G. is a guest editor invited by the Editorial Board.
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