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Theoretical and Applied Genetics

, Volume 126, Issue 5, pp 1377–1395 | Cite as

Supermodels: sorghum and maize provide mutual insight into the genetics of flowering time

  • E. S. Mace
  • C. H. Hunt
  • D. R. Jordan
Original Paper

Abstract

Nested association mapping (NAM) offers power to dissect complex, quantitative traits. This study made use of a recently developed sorghum backcross (BC)-NAM population to dissect the genetic architecture of flowering time in sorghum; to compare the QTL identified with other genomic regions identified in previous sorghum and maize flowering time studies and to highlight the implications of our findings for plant breeding. A subset of the sorghum BC-NAM population consisting of over 1,300 individuals from 24 families was evaluated for flowering time across multiple environments. Two QTL analysis methodologies were used to identify 40 QTLs with predominately small, additive effects on flowering time; 24 of these co-located with previously identified QTL for flowering time in sorghum and 16 were novel in sorghum. Significant synteny was also detected with the QTL for flowering time detected in a comparable NAM resource recently developed for maize (Zea mays) by Buckler et al. (Science 325:714–718, 2009). The use of the sorghum BC-NAM population allowed us to catalogue allelic variants at a maximal number of QTL and understand their contribution to the flowering time phenotype and distribution across diverse germplasm. The successful demonstration of the power of the sorghum BC-NAM population is exemplified not only by correspondence of QTL previously identified in sorghum, but also by correspondence of QTL in different taxa, specifically maize in this case. The unification across taxa of the candidate genes influencing complex traits, such as flowering time can further facilitate the detailed dissection of the genetic control and causal genes.

Keywords

Sorghum Flowering Time Association Mapping DArT Marker Allele Effect 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors would like to thank Erik van Oosterum, Ian Godwin and Chris Lambrides for their critical review of the manuscript and to acknowledge the Queensland Government and the Grains Research and Development Corporation (GRDC) for providing funding for this research.

Supplementary material

122_2013_2059_MOESM1_ESM.ppt (1.1 mb)
Figure S1. Allele effect graphs for all 40 DTF QTL detected in BC-NAM population (PPT 1117 kb)
122_2013_2059_MOESM2_ESM.ppt (416 kb)
Figure S2. Consensus genetic linkage map of sorghum showing location of previously identified sorghum flowering time QTL in relation to QTL identified in current study (PPT 415 kb)
122_2013_2059_MOESM3_ESM.ppt (252 kb)
Figure S3. Genetic linkage maps of sorghum location of NAM flowering time QTL in maize vs sorghum (PPT 252 kb)
122_2013_2059_MOESM4_ESM.ppt (104 kb)
Figure S4. QTL allele effect size comparison between ABC population and S. arundinaceum BC-NAM population (PPT 104 kb)
122_2013_2059_MOESM5_ESM.doc (43 kb)
File S1. Details of the statistical methods used to analyse the phenotypic data, the single marker analysis and the mpQTL process (DOC 43 kb)
122_2013_2059_MOESM6_ESM.doc (44 kb)
Table S1. The occurrence of the 24 BC-NAM populations across years (DOC 43 kb)
122_2013_2059_MOESM7_ESM.doc (33 kb)
Table S2. Number of markers within each BC-NAM family after excluding monomorphic markers and those with frequency greater than 95% and less than 5% (DOC 33 kb)
122_2013_2059_MOESM8_ESM.xlsx (18 kb)
Table S3. Details of co-locating QTL from previous sorghum and maize flowering time studies. Identifiers of QTL are those detailed in Buckler et al 2009 (for maize) and in Mace and Jordan (2011) for sorghum (XLSX 18 kb)
122_2013_2059_MOESM9_ESM.xlsx (24 kb)
Table S4. Details of candidate genes for flowering time identified in the sorghum genome (XLSX 23 kb)

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Copyright information

© Her Majesty the Queen in Right of Australia 2013

Authors and Affiliations

  1. 1.Department of AgricultureForestry and Fisheries, Hermitage Research StationWarwickAustralia
  2. 2.Queensland Alliance for Agriculture and Food InnovationThe University of QueenslandSt. LuciaAustralia

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