A shiny application to practice genetic mapping

SHORT DESCRIPTION

We have a bottleneck in reaching one of our most central teaching goals, which is the widely used strategy to identify genes or regions on the genome that are responsible for phenotypic variation. Within the course 'PBR32803 DL course Markers in quantitative genetics and plant breeding', but also in the courses 'ABG30806 Modern statistics for the life sciences', 'PBR21803 Pre-breeding' and 'PPH30806 Plant Plasticity and Adaptation', students need to develop skills to construct genetic linkage maps from DNA marker data, to find associations between molecular markers and phenotypic traits of interest and interpret results of such mapping efforts. This is called ‘genetic/linkage mapping’ and ‘analysis of Quantitative Trait Loci (QTLs)’ or ‘QTL mapping’.

In research, collecting and analysing the data takes a long time (not available in a course) and commercial software (also not available) or it requires high-level programming skills of the students (no time for this within a single course) before a student can actually start doing this. A Shiny application https://shiny.rstudio.com/ offers a menu-guided possibility for students to perform complex tasks such as genetic mapping and QTL analysis. This allows for:

  • speed (so that multiple things can be tried within reasonable time and many exercises/questions can be built around the analyses)
  • visualization of results that allows for development of interpretation skills for these types of analyses by the student, which many of them will need later on in their MSc Thesis, internship, or their career after graduation, either in the professional field (plant/animal breeding) and/or in genetic research.

With this education innovation project we will develop, starting from two existing prototypes developed by PhD students for different purposes, a Shiny application for education allowing linkage mapping, QTL analysis and genome-wide association studies with realistic data, but easy to use for students in a course and flexible with respect to the type of populations and input data.

OBJECTIVE

To develop a software tool (‘Shiny application’ using R software) that allows students to practice genetic mapping and detection of quantitative trait loci, using realistic datasets; this first in a distance learning course, but also useful for other on-campus courses.

STRONG POINTS

The most significant result of the project is the possibility for students to practice, hands-on, an important aspect of plant breeding, genetic analysis of phenotypic traits using DNA markers and specialized (but non-commercial) software, has been made possible by the Shiny applications.

  • Two shiny applications (one for constructing of a linkage map, the other for detection of quantitative trait loci) have been made more general, improved and have been implemented in the online course ‘Markers in quantitative genetics and plant breeding’.
  • Two other shiny applications were not originally part of this proposal but have also been developed as a result of this project, one for Genome-Wide Association Studies (GWAS analysis), and the other for linkage mapping in polyploid crops. The GWAS application is ready for testing and could be used in another online course (New trends in Plant Breeding). The Shiny application for genetic analysis of polyploid crops could be used by MSc Thesis students who do a thesis on this topic.
  • Within the online course ‘Markers in quantitative genetics and plant breeding’, the Shiny applications are used and students are doing genetic analyses using realistic datasets.


RECOMMENDATIONS

This project could be of use to others that use R software functions in their education, for exercises and hands-on practicals. If they use the same functionality multiple times in a course or across different courses, it could be worthwhile to have a Shiny application developed. Fore more information or recommendations, please contact Chris Maliepaard.  

PRODUCTS

To get more insight in the shiny applications, please contact Chris Maliepaard.