Chapter 4: An Introduction to Quantitative Genetics in Fish Biology and Fisheries
Megan V. McPhee
Quantitative genetics is a comprehensive body of theory that seeks to explain how complex traits or phenotypes evolve in response to selection in nature and under domestication (Falconer and Mackay 1996; Lynch and Walsh 1998, 2018). A major empirical focus of the discipline is estimating the amount of standing genetic variation for traits related to growth and marketability in aquaculture populations and to survival and reproductive success in wild populations since only genetically variable traits can evolve, and the rate of evolution is proportional to the amount of genetic variation for a trait under selection. As such, quantitative genetics informs substantial issues in fisheries and fish biology, including how readily desired traits can be bred into aquacultured populations and how readily wild fish populations might evolve in response to environmental change and/or fisheries-induced selection.
The field of quantitative genetics grew out of a need to understand the inheritance of quantitative traits, or characteristics that vary continuously, as opposed to that of qualitative (“either/or,” or categorical) traits that exhibit simple Mendelian inheritance (Figure 4.1). Gregor Mendel, through his experimental breeding of peas, reached the insight that the inheritance of continuously varying traits could be explained by the independent segregation (i.e., Mendelian inheritance) of multiple factors—what we now call genes. But following the rediscovery of Mendel’s work in 1900, adherents of the “biometrician” school of thought refused to accept that quantitative traits followed Mendelian principles of inheritance. Their insistence that quantitative traits were non-Mendelian delayed the fruitful synthesis of genetics with Darwin’s theory of evolution by natural selection (Provine 1971); however, a foundational paper by R. A. Fisher (Fisher 1918) reconciled the two points of view and established the fundamental statistical approaches still used in quantitative genetics today (Lynch and Walsh 1998; Visscher and Goddard 2019).