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Applied Mathematics & Statistics, and Scientific Computation

ANSC 688Z - Quantitative Genetics

Instructor:
Dr. Frank Siewerdt
siewerdt@umd.edu
http://ansc.umd.edu/siewerdt/Teaching%28en%29.html

Credits: 3
Time: MW 10:00-11:15am

Prerequisites:
ANSC450 (or equivalent agricultural genetics course) and BIOM602 (or equivalent, experimental designs or regression course)

Course Overview:
ANSC688Z (Quantitative Genetics) will be offered this Spring semester. The course meets twice a week, MW 10:00 - 11:15 a.m. and is based on Falconer's text, with emphasis on artificial selection.

Summary:
Population-level changes in gene frequencies, genetic resemblance between individuals, selection theory, advanced statistical methods for prediction of breeding values, incorporation of novel techniques into breeding programs.

Syllabus:
This is a tentative syllabus; the first 19 topics will be covered but the later ones can be adjusted to reflect specific interests from the audience.
  1. Hardy-Weinberg equilibrium, linkage disequilibrium, multiple alleles
  2. Changes in gene and genotypic frequencies by selection; fitness
  3. Gene action and breeding values
  4. Variance and covariance components
  5. Genetic resemblance between individuals
  6. Estimation of genetic parameters: a general framework
  7. Methods for estimation of heritability, maternal effects and repeatability
  8. Methods for estimation of genetic and environmental correlations
  9. Small populations and inbreeding
  10. Predicting crossbreeding performance
  11. Predicting and measuring response to selection: a broad framework
  12. Selection: basic concepts and locus level
  13. Response to selection with overlapping generations
  14. Short-term and long-term selection experiments
  15. Realized genetic parameters
  16. Selection: one trait, simultaneous multiple traits and alternative methods
  17. General selection index theory
  18. Group selection and associative genetic effects
  19. Marker-assisted selection and introgression
  20. Genomic selection
  21. Mixed model theory
  22. Best linear unbiased prediction (BLUP) 23. BLUP under selection and BLUP for maternal and other genetic effects
  23. Random regression models
  24. Design and analysis of selection experiments
  25. Limits to selection
  26. Experimental validation of selection theory
Text:
D.S. Falconer and T.F. Mackay (1996) Introduction to Quantitative, Genetics, 4th ed., Oxon, Longman (older editions acceptable); notes and other minor references

Evaluation:
2 exams (including final) and one review paper.