[{"Course code":"P000071","Version":1,"English name":"Biometrical methods for analyzing breeding trial data in the omics era","Higher education credits":3.0,"Syllabus":"Finalized by: FUN-LTV, 2024-01-30","Valid from":"2024V","Syllabus approved":"2024-01-30","Level within study regulation":"Third cycle","Subject":[{"Subject":"Biology"}],"Grading scale":"Pass \/ Failed","Language":"Swedish","Entry requirements":"Basic knowledge about genetics, quantitative genetics, linear regression models, analysis of variance and basic experience with R. At least a MSc degree in agronomy, biology, forestry, genetics, horticulture or enrolled as a PhD student.","Objectives":"To provide some basic biometrical and quantitative genetic concepts to be applied in designing and analyzing data from field trials, particularly elite germplasm and cultivar testing
\n\\- To give some basic statistical models and methods for dissecting genotype-by-environment interaction in the omics era
\n\\- To show practical results on multi-environment trials across sites and over years (or seasons) in different breeding contexts.
\n\\- To demonstrate implementations of various stat methods using the R software package
\n\\- To discuss general concepts of genomic prediction for breeding and selection
\n\\- To learn the quantitative genetic basis of genomic prediction in breeding
\n\\- To understand statistical models for genomic prediction and their use in breeding\n\nAt the end of this intensive 1-week course, the participant will\n\n\\- Refresh some basic ideas of Biometrical Methods for Plant Breeding Trial Data
\n\\- Understand the conceptual framework of experimental design, multi-environment testing, use of association genetics and genomic prediction for plant breeding.
\n\\- Know how to design, analyze and handling genotype-by-environment interactions
\n\\- Learn results that clearly show that biometrics works for plant breeding
\n\\- Tell how to prepare phenotypic and genotypic data for analyzing plant breeding data with R
\n\\- Run some R codes for analyzing plant breeding data involving different statistical models.
\n\\- Test if there are differences between breeding lines or populations, and cultivars","Content":"**Target**
\nPost-graduate students and professional doing field research on plant breeding using trials across sites and over years or cropping seasons, particularly those working on the analysis of controlling the inheritance of complex traits.\n\n**Content**\n\n*Theoretical sessions*
\n1\\. Revisiting field plot techniques for variety testing design and analysis: principles of good design, blocking, spatial analysis
\n2\\. Brief overview of mixed models (BLUE, BLUP, REML, variance components)
\n3\\. Linear and other models for analyzing genotype-by-environment (G×E) interactions
\n4\\. Association genetics (GWAS) and genomic estimated breeding values (GEBV) for genetic enhancement
\n5\\. G×E in association mapping (GWAS) and genomic prediction (GEBV). Genomic prediction models for G×E (reaction norm models).\n\n*Practical Sessions*
\n1\\. A brief introduction to R
\n2\\. Spatial analysis, use of incomplete block (a-lattice) and augmented design
\n3\\. Analysis of variance across sites and over years
\n4\\. Modeling multi-environment data under significant G×E
\n5\\. Including G×E in GWAS and GEBV","Examination formats":"Completion of all course assignments (pre-course readings, post-course practices-report), attendance and active participation in all theory lectures and computer practices. Oral exam for SLU PhD students to be taken with course leader. \r\n- If a student has failed an examination, the examiner has the right to issue supplementary assignments. This applies if it is possible and there are grounds to do so.\r\n\r\n- The examiner can provide an adapted assessment to students entitled to study support for students with disabilities following a decision by the university. Examiners may also issue an adapted examination or provide an alternative way for the students to take the exam.\r\n\r\n- If this syllabus is withdrawn, SLU may introduce transitional provisions for examining students admitted based on this syllabus and who have not yet passed the course.\r\n\r\n- For the assessment of an independent project (degree project), the examiner may also allow a student to add supplemental information after the deadline for submission. Read more in the Education Planning and Administration Handbook.\r\n","Organisation":[{"code":"642","Organisation":"Department of Plant Breeding"}],"Other information":"\r\n- The right to participate in teaching and\/or supervision only applies for the course instance the student was admitted to and registered on.\r\n\r\n- If there are special reasons, students are entitled to participate in components with compulsory attendance when the course is given again. Read more in the Education Planning and Administration Handbook.\r\n"}]