Course Description
Horticulture Genomics explores emerging topics, genomic analysis, and technological applications for improving horticulture/ornamental plants. Topics include command-line, genome assembly, population genomics, genetic diversity, breeding methods, and polyploidy. Students gain foundational knowledge of genomic approaches and bioinformatics techniques to analyze plant DNA sequence datasets needed for crop improvement.
Athena Title
Horticulture Genomics
Pre or Corequisite
PBGG(CRSS)(HORT) 4140/6140
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Student learning Outcomes
- The objective of this course is to equip students with the conceptual knowledge, computational skills, and analytical reasoning needed to apply genomics and bioinformatics approaches to horticultural and ornamental plant improvement. Students will develop the ability to work with plant DNA sequence datasets, use command-line and genomic analysis tools, interpret genomic variation and population diversity and evaluate how genome assembly, breeding strategies, and polyploidy can be leveraged to address challenges in horticultural/ornamental crop improvement.
- Students will explain fundamental concepts and terminology in horticultural genomics, including genome structure, sequencing technologies, genome assembly, population genomics, genetic diversity, breeding, and polyploidy.
- Students will use command-line tools and bioinformatics workflows to organize, process, and analyze plant DNA sequence datasets.
- Students will compare and evaluate genomic approaches used to characterize, conserve, and improve horticultural crops.
- Students will communicate genomic analyses and their implications for horticultural crop improvement using scientifically appropriate terminology, visualizations, and interpretations.
Topical Outline
- Introduction to command line
- Methods used in ornamental plant breeding
- Qualitative vs. quantitative traits
- Sequencing Technologies
- Genome Assembly
- Number of chromosomes and polyploidy
- Population Genomics
- Variant calling and diversity analysis
- Analysis of Big Data
