Shared genomic regions between derivatives of a large segregating population of maize identified using bulked segregant analysis sequencing and traditional linkage analysis

Nicholas J. Haase, Timothy Beissinger, Candice N. Hirsch, Brieanne Vaillancourt, Shweta Deshpande, Kerrie Barry, C. Robin Buell, Shawn M. Kaeppler, Natalia de Leon

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Delayed transition from the vegetative stage to the reproductive stage of development and increased plant height have been shown to increase biomass productivity in grasses. The goal of this project was to detect quantitative trait loci using extremes from a large synthetic population, as well as a related recombinant inbred line mapping population for these two traits. Ten thousand individuals from a B73 × Mo17 noninbred population intermated for 14 generations (IBM Syn14) were grown at a density of approximately 16,500 plants ha-1. Flowering time and plant height were measured within this population. DNA was pooled fromthe 46 most extreme individuals from each distributional tail for each of the traits measured and used in bulk segregant analysis (BSA) sequencing. Allelic divergence at each of the ~1.1 million SNP loci was estimated as the difference in allele frequencies between the selected extremes. Additionally, 224 intermated B73 × Mo17 recombinant inbred lines were concomitantly grown at a similar density adjacent to the large synthetic population and were assessed for flowering time and plant height. Using the BSA sequencing method, 14 and 13 genomic regions were identified for flowering time and plant height, respectively. Linkage mapping with the RIL population identified eight and three regions for flowering time and plant height, respectively. Of the regions identified, three colocalized between the two populations for flowering time and two colocalized for plant height. This study demonstrates the utility of using BSA sequencing for the dissection of complex quantitative traits important for production of lignocellulosic ethanol.

Original languageEnglish (US)
Pages (from-to)1593-1602
Number of pages10
JournalG3: Genes, Genomes, Genetics
Volume5
Issue number8
DOIs
StatePublished - 2015

Bibliographical note

Publisher Copyright:
© 2015 Gorrepati et al.

Keywords

  • Biomass
  • Genetic mapping
  • Maize
  • Quantitative trait analysis
  • Whole genome sequencing

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