The Inheritance of Complex Traits

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Look at almost any large group of men or women and you’ll notice a considerable range in their heights—some are short, some tall, and some about average. Kareem Abdul-Jabbar, a star basketball center of the 1970s and 1980s, was a towering 7 feet, 2 inches tall, whereas Willie Shoemaker, a renowned jockey who won the Kentucky Derby four times, was a mere 4 feet, 11 inches. You might also have noticed that in some families, the parents and their adult children are all on the tall side, whereas in other families, the parents and adult children are all fairly short. Such observations suggest that genes play a role in determining our heights. Still, people do not segregate cleanly into tall and short categories as we saw for Mendel’s pea plants. At first inspection, continuous traits, such as height, do not appear to follow Mendel’s laws despite the fact that they are heritable.

Traits such as height that show a continuous range of variation and do not behave in a simple Mendelian fashion are known as quantitative or complex traits. The term complex trait is often preferred because variation for such traits is governed by a “complex” of genetic and environmental factors. How tall you are is partly explained by the genes you inherited from your parents and partly by environmental factors such as how well you were nourished as a child. Teasing apart the genetic and environmental contributions to an individual phenotype is a substantial challenge, but geneticists have a powerful set of tools to meet it.

In the early 1900s, when Mendel’s laws were rediscovered, controversy arose about whether these laws were applicable to continuous traits. A group known as the biometricians discovered that there are correlations between relatives for continuous traits such that tall parents tend to have tall children. However, the biometricians saw no evidence that such traits followed Mendel’s laws. Some biometricians concluded that Mendelian loci do not control continuous traits. On the other hand, some adherents of Mendelism thought continuous variation was unimportant and could be ignored when studying inheritance. By 1920, this controversy was resolved with the formulation of the multifactorial hypothesis. This hypothesis proposed that continuous traits are governed by a combination of multiple Mendelian loci, each with a small effect on the trait, and environmental factors. The multifactorial hypothesis brought quantitative traits into the realm of Mendelian genetics.

Although the multifactorial hypothesis provided a sensible explanation for continuous variation, classic Mendelian analysis is inadequate for the study of complex traits. If progeny cannot be sorted into categories with expected ratios, then the Mendelian approach has little utility for the analysis of complex traits. In response to this problem, geneticists developed a set of mathematical models and statistical methods for the analysis of complex traits. Through the application of these analytical methods, geneticists have made great strides in understanding complex traits. The subfield of genetics that develops and applies these methods to understand the inheritance of complex traits is called quantitative genetics.

At the heart of the field of quantitative genetics is the goal of defining the genetic architecture of complex traits. Genetic architecture is a description of all of the genetic factors that influence a trait. It includes the number of genes affecting the trait and the relative contribution of each gene. Some genes may have a large effect on the trait, while others have only a small effect. As we will see in this chapter, genetic architecture is the property of a specific population and can vary among populations of a species. For example, the genetic architecture of a trait such as systolic blood pressure in humans differs among different populations. This is because different alleles segregate in different populations and different populations experience different environments; therefore, different populations are apt to have different architectures for many traits.

Understanding the inheritance of complex traits is one of the most important challenges facing geneticists in the twenty-first century. Complex traits are of paramount importance in medical and agricultural genetics. For humans, blood pressure, body weight, susceptibility to depression, serum cholesterol levels, and the risk of developing cancer or other disorders are all complex traits. For crop plants, yield, resistance to pathogens, ability to tolerate drought stress, efficiency of fertilizer uptake, and even flavor are all complex traits. For livestock, milk production in dairy cows, muscle mass in beef cattle, litter size in pigs, and egg production in chickens are all complex traits. Despite the importance of such traits, we know far less about their inheritance than we do about the inheritance of simply inherited traits such as cystic fibrosis or sickle-cell anemia.

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In this chapter, we will explore the inheritance of complex traits. We will begin with a review of some basic statistical concepts. Next, we will develop the mathematical model used to connect the action of genes inside the cell with the phenotypes we observe at the level of the whole organism. Using this model, we will then show how quantitative geneticists partition the phenotypic variation in a population into the parts that are due to genetic and environmental factors. We will review the methods used by plant and animal breeders to predict the phenotype of offspring from the phenotype of their parents. Finally, we will see how a combination of the statistical analysis and molecular markers can be used to identify the specific genes that control quantitative traits.