A bioinformatic and transcriptomic approach to identifying positional candidate genes without fine mapping: an example using rice root-growth QTLs

Gareth J. Norton, Matthew J. Aitkenhead, Farkhanda S. Khowaja, William R. Whalley, Adam H. Price

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

Fine mapping can accurately identify positional candidate genes for quantitative trait loci (QTLs) but can be time consuming, costly, and, for small-effect QTLs with low heritability, difficult in practice. We propose an alternative approach, which uses meta-analysis of original mapping data to produce a relatively small confidence interval for target QTLs, lists the underlying positional candidates, and then eliminates them using whole-genome transcriptomics. Finally, sequencing is conducted on the remaining candidate genes allowing identification of allelic variation in either expression or protein sequence. We demonstrate the approach using root-growth QTLs on chromosomes 2, 5, and 9 of the Bala x Azucena rice mapping population. Confidence intervals of 10.5, 9.6, and 5.4 cM containing 189, 322, and 81 genes, respectively, were produced. Transcriptomics eliminated 40% of candidate genes and identified nine expression polymorphisms. Sequencing of 30 genes revealed that 57% of the predicted proteins were polymorphic. The limitations of this approach are discussed. (C) 2008 Elsevier Inc. All rights reserved.

Original languageEnglish
Pages (from-to)344-352
Number of pages9
JournalGenomics
Volume92
Issue number5
Early online date18 Sep 2008
DOIs
Publication statusPublished - Nov 2008

Keywords

  • affymetrix
  • candidate genes
  • microarray analysis
  • quantitative trait loci
  • rice
  • root morphology
  • wax layer
  • oryza-sativa l.
  • penetration
  • map
  • expression
  • morphology
  • cloning

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