Marker Information Breeding - Association Discovery and Evaluation: Conifer Genomics Module 13

Plant Breeding and Genomics April 30, 2013 Print Friendly and PDF

Authors:

Nicholas Wheeler, Oregon State University; Heather L. Merk, The Ohio State University

This is the 13th module in a series of 17 developed by the Conifer Translational Genomics Network (CTGN) and the Conifer Reference Genome Sequencing (PineRefSeq) Project. This module by CTGN explores association discovery and evaluation in the context of marker informed breeding.

Introduction

This module briefly reviews examples of how genomic research tools have been tested and evaluated as operational tools. Though primarily driven by the tree breeder, their application is drawing increasing attention from the natural resource manager, since the information learned is relevant to adaptation in all environments. The module concludes with a summary of the status and future of marker informed breeding (MIB) in tree breeding.

Module Screen Shot and Link

 

Module 13 — Marker Information Breeding – Association Discovery and Evaluation

See other Conifer Genomics Modules

 

You can also watch the video on YouTube

References Cited

  • Brown, G. R., D. L. Bassoni, G. P. Gill, J. R. Fontana, N. C. Wheeler, R. A. Megraw, M. F. Davis, M. M. Sewell, G. A. Tuskan, and D. B. Neale. 2003. Identification of quantitative trait loci influencing wood property traits in loblolly pine (Pinus taeda L) III. QTL verification and candidate gene mapping. Genetics 164: 1537-1546.
  • Eathington, S. R., T. M. Crosbie, M. D. Edwards, R. Reiter, and J. K. Bull. 2007. Molecular markers in a commercial breeding program. Crop Science 47: s154-s163. (Available online at: http://dx.doi.org/10.2135/cropsci2007.04.0015IPBS) (verified 2 June 2011).
  • Gonzalez-Martinez, S. C., N. C. Wheeler, E. Ersoz, C. D. Nelson, and D. B. Neale. 2007. Association Genetics in Pinus Taeda L I. Wood properties. Genetics 175: 399-409. (Available online at: http://dx.doi.org/10.1534/genetics.106.061127) (verified 2 June 2011).
  • Gonzalez-Martinez, S. C., D. Huber, E. Ersoz, J. M. Davis, and D. B. Neale. 2008. Association genetics in Pinus taeda L. II. Carbon isotope discrimination. Heredity 101: 19-26. (Available online at: http://dx.doi.org/10.1038/hdy.2008.21) (verified 2 June 2011).
  • Grattapaglia, D. 2007. Marker–assisted selection in Eucalyptus. p. 251-281. In. E. P. Guimaraes, J. Ruane, B. D. Scherf, A. Sonnino, and J. D. Dargie (ed.) Marker assisted selection: Current status and future perspectives in crops, livestock, forestry and fish. Food and Agriculture Organization of the United Nations (FAO), Rome, Italy.
  • White, T. L., W. T. Adams, and D. B. Neale. 2007. Forest Genetics. CAB International, Oxfordshire, U.K. (Available online at: http://bookshop.cabi.org/?page=2633&pid=2043&site=191) (verified 2 June 2011).

Cite This Learning Module

  •  Wheeler, N. Association discovery and evaluation [Online Learning Module]. Genomics in Tree Breeding and Forest Ecosystem Management, Conifer Translational Genomics Network. eXtension Foundation. Available at http://www.extension.org/pages/61072 (verified April 22, 2013).

Author Contributions

  • Nicholas Wheeler developed the learning module content.
  • Heather Merk developed the webpage.

Funding Statement

Support for the Conifer Translational Genomics Network project and the development of the teaching modules hosted here was provided by the USDA/NRI CSREES CAP Award # 2007-55300-18603, the USDA/NIFA AFRI Applied Plant Genomics Coordinated Agricultural Project Award #2009-85606-05680 and the USDA Forest Service. 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.

Attachments:

QTL_Discovery.pdf (2.36 MB)

PBGworks 1078

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