Mapping & QTL Analysis

Plant Breeding and Genomics July 31, 2013 Print Friendly and PDF

Authors:

Heather L. Merk, The Ohio State University; Hamid Ashrafi, University of California, Davis; David Douches, Michigan State University; Trudi Grant, The Ohio State University; Christine Hackett, The James Hutton Institute; David Harry, Oregon State University; Nancy Huarachi, The Ohio State University; Jennifer Kling, Oregon State University; Deana Namuth-Covert, University of Nebraska, Lincoln; Matthew Robbins, The Ohio State University; Allen Van Deynze, University of California, Davis; Nicholas Wheeler, Oregon State University; Scott Wolfe, The Ohio State University; Kelly Zarka, Michigan State University; David Francis, The Ohio State University

This curriculum page provides links to learning modules, tutorials, and case studies relevant to mapping and quantitative trait locus (QTL) analysis. The learning modules provide background information. Tutorials describe experimental designs for field-based phenotyping, scoring molecular markers, mapping, and QTL analysis. Case studies provide in-depth discussion of mapping.

Information Flow

Figure 1. Flow of information from collecting genotypic and phenotypic data to mapping to graphical genotyping and quantitative trait locus analysis. Image credits: Genotyping, Allen Van Deynze, UC Davis; Mapping, Scott Wolfe, The Ohio State University; Graphical Genotyping, Nancy Huarachi, The Ohio State University; Phenotyping, David Francis, The Ohio State University; QTL Analysis, Hamid Ashrafi, UC Davis.

Learning Modules

Tutorials

Phenotyping

Genotyping

Mapping

Graphical Genotyping

QTL Analysis

  • R/QTL                      

Case Studies

Funding Statement

Development of this lesson 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. 

Mention of specific companies is not intended for promotional purposes.

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