Course Description

This course provides theory, methods and procedures required to apply molecular information in plant breeding programs. The course will be based on lectures and multiple hands-on activities that apply what is learned. Frequent evaluations will occur during the semester by topic (see below).

Intended Audience

The course is designed for graduate students working in plant breeding (e.g. agronomy, horticulture, environmental horticulture, and forestry), or any student in biological science who wants to deepen his/her knowledge about the theory and application of molecular breeding.

Course Objectives

The course goal is to familiarize students with the application of molecular information to plant breeding. By the end of the semester students should be able to describe current methods for mapping quantitative trait loci (QTL), Genome-wide association (GWAS), marker-assisted selection (MAS), and Genomic Selection (GS). The course will also review the applications of biotechnology to breeding programs. Students should be able to describe the advantages and disadvantages of the different methods covered in the course. Students should also be able to list the biotechnology methods applied to plant breeding. Ultimately, students should be able to identify what method and what strategy should be applied depending on the species, the breeding goals, the population and the timeframe.

Evaluation

Quizzes

Quizzes will happen in the first 5 minutes of the class. There will be no notice of when quizzes are happening and there is no make up of quizzes, so be on time for class. Paper discussion There will be one paper assigned every two weeks. One student chosen at random at the beginning of the class will lead the paper discussion, this student will randomly chose as many students as figures appear in the paper to be explained and discussed. All students will have a chance to lead the discussion.

Partial Projects

Partial project will be developed while the class is covering the topic and is due by 5 PM the last day the topic is covered. The project will start during class for every topic. The due day will be communicated the day the data is given to students. For example; the QTL analysis will involve creating a linkage map, mapping the QTLs, and presenting a report of the work. Similar projects will be given to the topics GWAS, and GS.

Take-Home Exam

Take home exam will be due one day after it is given to students. These exams will involve developing strategies for application of the methods and techniques under different scenarios. Hands-on Activities Every week during the second period on Thursday students will be handling data to apply what was learn during the week. This means students are required to participate in this activities. Software You will need to bring your own laptop. The main software used will be the statistical software R which can be downloaded from (www.r-project.org). and [Rstudio] (http://www.rstudio.com). It is your responsibility to make sure that your computer has the latest version of R. Prior to the first day of class, please make sure you have removed all old versions of R, and have the most recent version installed. There are numerous online resources available for R; however, if you would like a traditional textbook, The R Book, is widely available and comprehensive.

• Crawley, M. J. (2012). The R book. John Wiley & Sons.

Required and Recommended Literature

This course does not have a required but a recommended textbook, and a series of scientific manuscript that will be assigned for reading and discussion. Additional literature, to deepen student understanding, can also be found below.

• Rex Bernardo. 2014. “Essentials of plant breeding”. Stemma press. Woodbury, Minnesota, USA. ISBN 978-0- 9720724-2-7
• Broman, K W. 2001. “Review of Statistical Methods for QTL Mapping in Experimental Crosses.” Lab Animal 30 (7): 44–52. doi:11469113.
• Collard, B. C Y, M. Z Z Jahufer, J. B. Brouwer, and E. C K Pang. 2005. “An Introduction to Markers, Quantitative Trait Loci (QTL) Mapping and Marker-Assisted Selection for Crop Improvement: The Basic Concepts.” Euphytica 142 (1–2): 169–96. doi:10.1007/s10681-005-1681-5.
• Doerge, Rebecca W. 2002. “Multifactorial Genetics mapping and Analysis of Quantitative Trait Loci in Experimental Populations.” Nature Reviews Genetics 3 (1): 43–52. doi:10.1038/nrg703.
• Holland, Jb. 2004. “Implementation of Molecular Markers for Quantitative Traits in Breeding Programs—challenges and Opportunities.” New Directions for a Diverse Planet: Proceedings, 1–13. http://cropscience.org.au/icsc2004/pdf/203_hollandjb.pdf.
• Xu, Yunbi, and Jonathan H. Crouch. 2008. “Marker-Assisted Selection in Plant Breeding: From Publications to Practice.” Crop Science 48 (2): 391–407. doi:10.2135/cropsci2007.04.0191.
• Korte, Arthur, and Ashley Farlow. 2013. “The Advantages and Limitations of Trait Analysis with GWAS: A Review.” Plant Methods 9 (1): 29. doi:10.1186/1746-4811-9-29.
• Zhu, Chengsong, Michael Gore, Edward S. Buckler, and Jianming Yu. 2008. “Status and Prospects of Association Mapping in Plants.” The Plant Genome Journal 1 (1): 5. doi:10.3835/plantgenome2008.02.0089.
• Meuwissen, T. H E, B. J. Hayes, and M. E. Goddard. 2001. “Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps.” Genetics 157 (4): 1819–29. doi:11290733.
• Heffner, Elliot L., Mark E. Sorrells, and Jean Luc Jannink. 2009. “Genomic Selection for Crop Improvement.” Crop Science 49 (1): 1–12. doi:10.2135/cropsci2008.08.0512.
• Heslot, Nicolas, Jean-Luc Jannink, and Mark E. Sorrells. 2015. “Perspectives for Genomic Selection Applications and Research in Plants.” Crop Science 55 (1): 1. doi:10.2135/cropsci2014.03.0249.
• Gelvin Stanton B. 2003. “Agrobacterium-Mediated Plant Transformation: the Biology behind the “Gene-Jockeying” Tool”. Microbiol Mol Biol Rev 67(1):16-37. doi: 10.1128/MMBR.67.1.16-37.2003
• Doudna Jennifer, and Emmanuelle Charpentier. 2014. “The new frontier of genome engineering with CRISPR- Cas9.” Science 28 Vol 346, Issue 6213. doi: 10.1126/science.1258096
• Fredy Altpeter,a Nathan M. Springer,b Laura E. Bartley,c Ann E. Blechl,d Thomas P. Brutnell,e Vitaly Citovsky,f Liza J. Conrad,g Stanton B. Gelvin,h David P. Jackson,i Albert P. Kausch,j Peggy G. Lemaux,k June I.
• Medford,l Martha L. Orozco-Cárdenas,m David M. Tricoli,n Joyce Van Eck,o - Daniel F. Voytas,p Virginia Walbot,q Kan Wang,r Zhanyuan J. Zhang,s and C. Neal Stewart Jr. 2016. “Advancing Crop Transformation in the Era of Genome Editing”. The Plant Cell 28:1510–1520. doi: https://doi.org/10.1105/tpc.16.00196