ASCI 431/831 Advanced Animal Breeding
- Name: Ron Lewis
- Office: A218i Animal Science Building
- Email: firstname.lastname@example.org
- Name: Gota Morota
- Office: A218f Animal Science Building
- Email: email@example.com
Time and Location
- Tues./Thurs. 2:00-3:30pm
- Animal Science Building, Room A221
- The instructors will hold office hours as specified on the course Blackboard site.
- ASCI 330 (Animal Breeding), or its equivalent, is the prerequisites for this course. Please do not enroll in ASCI 431/831until you have successfully completed that prerequisite course.
There is no textbook required for this course. Due to the nature of the course, handouts prepared by the instructors and guest lectures, and reading assignments from the scientific literature, web-based materials and reports will be used to illustrate principles, demonstrate applications, and focus lectures on practical outcomes of advanced breeding programs.
The objective of this course is to provide students with the necessary knowledge, exposure to research results, and explanation of breeding applications to critically evaluate strengths, weaknesses and expected outcomes of present and potential animal breeding strategies.
Upon successful completion of this course, students will be able to:
- Demonstrate an understanding of the state-of-the-art applications of animal breeding and quantitative genetics (including their benefits and limitations) to the genetic improvement of livestock within the United States and elsewhere in the world.
- Demonstrate an ability to locate and interpret research results, and recognize the applications of such research to livestock breeding programs.
- Demonstrate an understanding of sources of variation in performance of animals, and the methods used to control or adjust for this variation.
- Predict responses to selection for a broad array of selection situations, including the use of molecular markers.
- Predict average performance of crossbred populations and mean industry values for breeding systems using crosses of several different breeds.
- Plan future breeding program strategies contingent upon the goals that are established.
Lectures will be delivered using a whiteboard and presentation slides.
- 1/10 (T): Overview of course; Introduction to R, RStudio, and HCC clusters [HTML]
- 1/12 (R): Review of basic statistics
- 1/17 (T): UNL classes canceled due to road conditions
- 1/19 (R): Review of basic statistics in R; Review of allele and genotypic frequencies [HTML]
- 1/24 (T): Review of allele and genotypic frequencies in R; Numerator relationship [HTML]
- 1/26 (R): Genome-wide allele frequencies; Expectation and variance of allelic counts [HTML]
- 1/31 (T): Numerator relationship in R [HTML]
- 2/2 (R): Analysis of variance (ANOVA) - repeatability
- 2/7 (T): Analysis of variance (ANOVA) - heritability
- 2/9 (R): Class discussion & Estimating repeatability and heritability using ANOVA in R [P][HTML]
- 2/14 (T): Estimating repeatability and heritability using ANOVA in R
- 2/16 (R): Predicting response to selection
- 2/21 (T): Solutions for HW3
- 2/23 (R): Class discussion & Predicting response to selection 1 [P][HTML]
- 2/28 (T): Midterm exam in-class portion
- 3/2 (R): Predicting response to selection 2
- 3/7 (T): Ordinary least squares and BLUE [HTML]
- 3/9 (R): Pedigree-based BLUP [HTML]
- 3/14 (T): Class discussion & Pedigree-based BLUP [P]
- 3/16 (R): HW4 review & Pedigree-based BLUP & Genomic BLUP [HTML]
- 3/21 (T): Spring break
- 3/23 (R): Spring break
- 3/28 (T): Genomic BLUP
- 3/30 (R): Mixed model equations (MME) [HTML]
- 4/4 (T): SNP-BLUP [HTML]
- 4/6 (R): Class discussion & Economic selection indices for multiple traits [P]
- 4/11 (T): Guest lecture - Dr. Tom Rathje (DNA Genetics)
- 4/13 (R): Guest lecture - Drs. Benny Mote and Matt Spangler (UNL)
- 4/18 (T): Economic selection indices for multiple traits
- 4/20 (R): Class discussion & Economic selection indices for multiple traits [P]
- 4/25 (T): Economic selection indices for multiple traits [HTML]
- 4/27 (R): Economic selection indices for multiple traits & Population structure [HTML]
- 5/2 (T): Final exam - 3:30 to 5:30 p.m.