Human Genetics: Concepts and Applications (Lewis), 9th Edition

Chapter 7: Multifactorial Traits

Chapter Outline

CHAPTER OVERVIEW

1. Most traits are determined by multiple genes and environmental effects.
2. Polygenic traits are determined by more than one gene, with each gene providing a small, but additive effect.
3. Multifactorial traits are determined by interactions between a gene or genes and the environment, and do not exhibit Mendelian ratios.
4. Pure polygenic traits (i.e. no environmental influence) are rare.

1. Polygenic traits usually produce a continuum of phenotypes.
2. Individual genes of a polygenic trait follow Mendel's laws, but together do not produce Mendelian ratios.
3. A bell shaped curve often describes the distribution of phenotypic classes of a polygenic trait.

1. Dermatoglyphics is a technique that compares the fingerprint patterns that identify and distinguish individuals.
2. Fingerprint pattern is a multifactorial trait and environmental differences during gestation result in dermatoglyphic differences between identical twins.

1. Human height in a population varies continuously in a bell shape distribution.
2. Diet and health are strong environmental factors in expressing genetic potential for height.
3. Multiple genes affecting height have been identified using genome wide association studies.

1. Differences in skin color arise from the quantity and distribution of the pigment melanin in the uppermost layers of skin cells.
2. Exposure to sunlight is an environmental factor that can affect skin color.
3. Skin color does not effectively indicate a person's genetic ancestry, medical risks or response to medication.
4. In the future, medicine will increasingly rely on genomics to guide prescribing practices.

1. Empiric risk is not calculated, but is an observed population statistic.
2. Incidence refers to the number of new cases of a disease occurring during a given time, such as a year.
3. Prevalence indicates the total number of cases of the disease in a population at a specific time.
4. Empiric Risk is used to predict recurrence of a multifactorial trait in a family.
5. Empiric risk increases with severity of the trait, number of affected relatives, sex of family members, and increasing relatedness to an affected individual.

1. Heritability estimates the proportion of variation in a population for a multifactorial trait that is due to genotype.
2. The coefficient of relatedness indicates the proportion of genes relatives share. It increases as more closely related individuals are compared.
3. Studying multifactorial traits in humans is difficult since data must be pooled from many families.
4. Analysis of multifactorial inheritance has widespread application in agriculture.

1. To assess the influence of heredity and the environment, traits of an adopted child can be compared with those of the adoptive and biological parents.

1. Twin studies have been used to separate genetic and environmental contributions to a phenotype. Monozygotic twins may differ in copy number variants.
2. Traits occurring more frequently in both identical (MZ) twins than in both fraternal (DZ) twins have a significant genetic component.
3. The concordance of a trait is the percentage of pairs in which both members express the trait.
4. The study of monozygotic (MZ) twins separated at birth offers some unique insights into the nature vs. nurture debate. This approach has limitations.

1. Genome-wide association studies examine the whole genome for variations such as SNPs or copy number variants that can be linked to particular phenotypes
2. The phenotype of interest may be presence or absence of a trait, condition or disease
3. Researchers are using genome-wide association studies in conjunction with gene expression data to gain new insight into diseases.
4. Using tag SNPs reduces the total number of SNPS that must be analyzed

1. Researchers use cohort, case-control and homozygosity mapping studies to compare 500,000 tag SNPs between healthy controls and affected individuals.
2. Replication studies in different, independent populations are used to validate the associations discovered by this approach
3. SNP markers are then used to map potential disease causing genes

1. Genome-wide association studies do not reveal cause and effect relationships
2. Genetic heterogeneity, late onset of disease, incomplete penetrance and phenocopy all complicate association studies

1. Body weight, as measured by body mass index (BMI), is a multifactorial trait influenced by genetic and environmental factors.
2. Obesity is a growing problem in the United States. It is a risk factor for developing a number of diseases
3. Genome-wide association studies have been used to reveal genes that influence BMI. These may be useful in developing therapeutic approaches to weight control

1. Leptin, a protein hormone, stimulates the hypothalamus to suppress appetite and increases metabolic rate.
2. Ghrelin, produced in the stomach, increases appetite.
3. Genes controlling leptin, ghrelin and other related proteins exert a significant effect on body weight and are potential targets for therapeutic approaches to weight control

1. Genome-wide association studies are being used to identify potential weight-control genes

1. Studies on the inhabitants of Naura, Pima Indians of Arizona and Mexico, and very low birth weight babies demonstrate the epigenetic role of environment in controlling body weight.
2. Recent studies have also suggested that gut flora can influence the amount of calories extracted from food.