Human Complex Trait Genetics in the 21st Century
View ORCID Profile Peter M. Visscher
GENETICS February 11, 2016 vol. 202 no. 2 377-379; DOI: 10.1534/genetics.115.180513
COMPLEX TRAIT GENOMICS POPULATION GENETICS QUANTITATIVE GENETICS
I moved into the field of human complex trait genetics less than 20 years ago, from a background in quantitative genetics and animal breeding. Even in this period of time, major changes have occurred that were hard to predict back in the 1990s. Driven by enormous advances in DNA sequencing technologies, one can now sequence and analyze an entire human genome for a few thousand dollars. Some may argue that the cost of a sequenced genome is much lower than that, but that usually ignores the expense of storage, analysis, and interpretation. Sequencing technology has facilitated easy and fast discovery of Mendelian disease mutations and coding variants with high penetrance (a high probability of disease given genotype), and has led to precise estimates of the per-generation mutation rate (1000 Genomes Project Consortium et al. 2010). In the same period, development of array genotyping technology has made it possible to genotype hundreds of thousands of DNA variants for less than $100. Millions of samples have been genotyped using such arrays to study the genetic basis of complex traits such as common disease and quantitative traits, which has led to the discovery of many thousands of genes, gene variants, and biological pathways that are associated with one or more complex traits (Visscher et al. 2012). The traits vary widely, from psychiatric disorders to autoimmune disease, cancer, anthropometric traits such as height and weight, traits measured in blood such as platelet size and counts, and behavioral traits such as intelligence and years of schooling. In addition to trait-variant discovery, the technologies have led to new discoveries in human evolution and population genetics.
These mostly unpredicted rapid developments were not just taking place in human complex trait genetics. In plant and animal breeding, a revolution has been taking place in the last 15 years. In 2001, a theoretical paper in this journal showed that with a sufficiently dense marker map, linkage disequilibrium could be exploited to predict breeding values and speed up genetic gain by radically changing the structure of breeding programs (Meuwissen et al. 2001). This paper was published well before the first commercial SNP chips were available, and within 10 years of publication, the method, called “genomic selection” (or “genomic prediction”), was implemented in dairy cattle breeding programs around the world; breeders of other livestock species and crops are following the same route. The update of this technology has led to a doubling of the rate of genetic gain in dairy cattle (Veerkamp 2015), an astounding increase and an incredibly rapid update of new technology.
My main thesis is that the relentless pace of technological innovation will cause a change in how science is conducted. Instead of the model-based hypothesis-testing science that dominated the last century, the next will be hypothesis-generating-discovery science that is driven by data. I believe that this change will not be confined to human complex trait genetics, but will apply to all areas of research in genetics. Genomics will become synonymous with biology, a trend already occurring.
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