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An Integrative Approach to Genomic Introgression Mapping
Plant Physiology
  • Andrew J. Severin, Iowa State University
  • Gregory A. Peiffer, Iowa State University
  • Wayne W. Xu, University of Minnesota
  • David L. Hyten, United States Department of Agriculture
  • Bruna Bucciarelli, United States Department of Agriculture
  • Jamie A. O'Rourke, United States Department of Agriculture
  • Yung-Tsi Bolon, United States Department of Agriculture
  • David Grant, United States Department of Agriculture
  • Andrew D. Farmer, National Center for Genome Resources
  • Gregory D. May, National Center for Genome Resources
  • Carol P. Vance, University of Minnesota–Twin Cities
  • Randy C. Shoemaker, United States Department of Agriculture
  • Robert M. Stupar, Iowa State University
Document Type
Article
Publication Version
Published Version
Publication Date
9-1-2010
DOI
10.1104/pp.110.158949
Abstract

Near-isogenic lines (NILs) are valuable genetic resources for many crop species, including soybean (Glycine max). The development of new molecular platforms promises to accelerate the mapping of genetic introgressions in these materials. Here, we compare some existing and emerging methodologies for genetic introgression mapping: single-feature polymorphism analysis, Illumina GoldenGate single nucleotide polymorphism (SNP) genotyping, and de novo SNP discovery via RNA-Seq analysis of next-generation sequence data. We used these methods to map the introgressed regions in an iron-inefficient soybean NIL and found that the three mapping approaches are complementary when utilized in combination. The comparative RNA-Seq approach offers several additional advantages, including the greatest mapping resolution, marker depth, and de novo marker utility for downstream fine-mapping analysis. We applied the comparative RNA-Seq method to map genetic introgressions in an additional pair of NILs exhibiting differential seed protein content. Furthermore, we attempted to optimize the comparative RNA-Seq approach by assessing the impact of sequence depth, SNP identification methodology, and post hoc analyses on SNP discovery rates.We conclude that the comparative RNA-Seq approach can be optimized with sufficient sampling and by utilizing a post hoc correction accounting for gene density variation that controls for false discoveries.

Comments

This article is from Plant Physiology 154 (2010): 3–12, doi:10.1104/pp.110.158949.

Rights
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
Language
en
File Format
application/pdf
Citation Information
Andrew J. Severin, Gregory A. Peiffer, Wayne W. Xu, David L. Hyten, et al.. "An Integrative Approach to Genomic Introgression Mapping" Plant Physiology Vol. 154 Iss. 1 (2010) p. 3 - 12
Available at: http://works.bepress.com/andrew-severin/2/