Breeding in a Genomics Era Webinar - Live from PAA 2011

Plant Breeding and Genomics March 05, 2013 Print Friendly and PDF

Authors:

David M. Francis, The Ohio State University; Heather L. Merk, The Ohio State University

This webinar was presented at the 2011 Potato Association of America conference by Dr. David Francis, The Ohio State University. Dr. Francis discusses the integration of genome level data into potato and tomato breeding programs, including consideration of population size and experimental design. Dr. Francis emphasizes the importance of collecting standardized, objective, and quantitative phenotypic data.

Introduction

The availability of genome sequence data for potato presents the opportunity to improve varieties using marker-based selection strategies. In this webinar, Dr. David Francis, The Ohio State University, discusses how genome-wide Single Nucleotide Polymorphism (SNP) data may be incorporated into breeding strategies. Dr. Francis stresses that even with abundant SNP resources, plant breeding programs should remain focused on population development and high quality phenotypic evaluation.

During the first video, Dr. Francis reviews equations fundamental to plant breeding and marker-assisted selection (MAS).  Dr. Francis emphasizes the importance of population size and the use of MAS to accelerate the breeding cycle.

If you experience problems veiwing this video connect directly to our YouTube channel or see the YouTube troubleshooting guide.

During the second video, Dr. Francis discusses populations and population structure in the context of mapping and breeding programs. Approaches for data analysis are reviewed.

If you experience problems veiwing this video connect directly to our YouTube channel or see the YouTube troubleshooting guide.

During the third video, Dr. Francis stresses the importance of collecting objective, standardized, and quantiative phenotypic data.  Trends toward standardization and data storage are driving efforts to link phenotypes to ontologies.  The resulting databases facilitate the estimation of  trait heritability from multi-year and multi-location studies.

If you experience problems veiwing this video connect directly to our YouTube channel or see the YouTube troubleshooting guide.

During the fourth video, Dr. Francis discusses rapid changes in genotyping technology. In addition, he stresses that availability of high quality genotypic data should no longer be a limitation for breeding programs. Dr. Francis poses questions to help plant breeders assess how and why they may use genome-wide SNP data.  Strategies for cost-efficient genotyping of breeding populations are presented.

If you experience problems veiwing this video connect directly to our YouTube channel or see the YouTube troubleshooting guide.

During the fifth video, Dr. Francis discusses strategies for integrating genotyping and breeding. Dr. Francis stresses the importance of population size and selection strategy with regards to potential for successful integration of genotyping and breeding.

If you experience problems veiwing this video connect directly to our YouTube channel or see the YouTube troubleshooting guide.

During the sixth video, Dr. Francis demonstrates how to maximize population size using an augmented design. Dr. Francis introduces  sample analysis pipelines considering genotypes as either fixed effects or as random effects.

If you experience problems veiwing this video connect directly to our YouTube channel or see the YouTube troubleshooting guide.

This video contains the full-length recording and is 61 minutes long.

If you experience problems veiwing this video connect directly to our YouTube channel or see the YouTube troubleshooting guide.

 Watch other webinars from the SolCAP workshop at the 2011 Potato Association of America meeting

Funding Statement

Development of this page was supported in part by the National Institute of Food and Agriculture (NIFA) Solanaceae Coordinated Agricultural Project, agreement 2009-85606-05673, administered by Michigan State University. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the United States Department of Agriculture.

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This work is supported by the USDA National Institute of Food and Agriculture, New Technologies for Ag Extension project.