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Complex Traits

Author(s): Nancy Moreno, PhD.

Predicting Genetic Outcomes

Procedure (cont.)

6. During reproduction, every offspring receives a single copy of each gene from each parent. Logically, since every offspring has two parents—in the end, each puppy once again will have two copies of each gene.

Thus, if a parent has the genotype, Ll, half of the offspring will receive an “L” version of the gene, and the other half will receive an “l” version of the gene.

Parent: Ll

Offspring: L or l

This process can be represented using a simple table that allows you to plot the outcomes of any possible cross between two parents with known genotypes. This type of table is known as a Punnett square. The genotype of one parent is written across the top. The genotype of the other parent is written along the left side. The example chart (above) has the genetic contribution of one parent already written across the top, and the contribution of another parent along the side. It is using a hypothetical example of floppy ears (f) vs. straight ears (F).

Next, fill in the boxes by copying the row and column-head letters into each square. The first square is completed for you. Create a similar table and fill in the remaining squares. Each of the squares represents the genotype of a single possible offspring.

Assume that F refers to a fictitious gene for ear type, and “F” signifies straight ears and “f” leads to floppy ears. When two copies of “f” are present are present, a dog will have floppy ears. What are the phenotypes of the offspring?

7. Now, based on what you know about the phenotypes and genotypes of Fido and Fluffy, make one or more tables to estimate what their puppies might look like. If you do not know the genotype of one of the parents, make a separate table for each of the possible genotypes.

Funded by the following grant(s)

Science Education Partnership Award, NIH

Gene U: Inquiry-based Genomics Learning Experiences for Teachers and Students
Grant Number: 5R25OD011134

Robert Wood Johnson Foundation

Using Learning Technology to Build Human Capital
Grant Number: 57363