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Genetics and Breeding Methodology

Goals include:
- To improve efficiency (time and/or money) of genetics and breeding of experiments and subsequent analysis
- To develop new analysis methods
- To better understand the statistical power we have in experiments
- To develop teaching tools to help train graduate students and in continuing education

Methods primarily consist of novel simulations using the R statistical computing environment

 

 

Past and Current Projects:

Selection Mapping/ Methods of Detecting Temporal Selection
In both natural and plant breeding populations allele frequencies change caused by both genetic selection and drift. We are developing and evaluating tests for separating these causes to ultimately map QTL.

Optimization of Population Sizes and Design for QTL fine Mapping
Recently underway to complement the the USDA-National Institute for Food and Agriculture funded project Analysis of Clinal Variation in Maize: Implementation of an Experimental Framework for Studying Crop Adaptation.

Estimation of Genomewide Recombination Rates
There have been few estimates of genomewide recombination, our simulation models coupled with recent next-generation sequencing tools allow us to investigate this.

Optimization of Effective Recombination in Breeding and Genetics Populations
Effective recombination is important for plant breeding progress and genetic mapping resolution.

 

Some of this work is being conducted under the the USDA-National Institute for Food and Agriculture funded project Analysis of Clinal Variation in Maize: Implementation of an Experimental Framework for Studying Crop Adaptation. To learn more about this project visit the project website (http://www.maizeatlas.org/)

 

 


 

 

 

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