ENTOM 4700 - Ecological Genetics of Infection and Disease

(crosslisted) BIOEE 4800

Spring (offered alternate years). 4 credits. Student option grading.

Prerequisite: BIOEE 1780. Recommended prerequisite: introductory course in genetics and/or statistics.

B.P. Lazzaro.

Special offering of Ecological Genetics. The standard Ecological Genetics course focuses on the application of population genetic concepts in ecological or applied contexts, with emphases on measuring adaptation in natural populations, detecting the effects of population demography, and determining the genetic basis of quantitative traits. In this special offering, the contextual examples will be related to host-microbe interactions and the establishment and spread of infectious disease in natural populations of animals and plants. Illustrative examples will be drawn from the primary research literature to demonstrate experimental techniques and methods of data analysis on single-gene, multi-locus and genome-wide scales. Although the examples used class will focus on infection, resistance, and host-pathogen co-evolution, the experimental and methodological approaches can also be applied to other ecologically relevant traits and processes.

Outcome 1: 1.1 You will be introduced to basic models of genetic evolution, and shown how they can be applied and tested in real biological scenarios.
1.2 There will be heavy reliance on case examples from the primary scientific literature, in addition to lecture-based presentation of abstract concepts.

Outcome 2: 2.1 You will learn how to conduct population and quantitative genetic tests on real data sets, and to interpret test results to yield plausible biological interpretation.

Outcome 3: 3.1 You will apply a diversity of tests to the same or related example data sets, and will draw logical conclusions from the joint results of all tests applied.
3.2 You will interpret specific data and results in the context of broader concepts covered in the course to reach reasonable biological conclusions.
3.3 You will employ “scientific thinking” to solve problems that mirror real-life experimental scenarios.