Identification and characterization of Rht25, a locus on chromosome arm 6AS affecting wheat plant height, heading time, and spike development
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This study identified Rht25, a new plant height locus on wheat chromosome arm 6AS, and characterized its pleiotropic effects on important agronomic traits.
Understanding genes regulating wheat plant height is important to optimize harvest index and maximize grain yield. In modern wheat varieties grown under high-input conditions, the gibberellin-insensitive semi-dwarfing alleles Rht-B1b and Rht-D1b have been used extensively to confer lodging tolerance and improve harvest index. However, negative pleiotropic effects of these alleles (e.g., poor seedling emergence and reduced biomass) can cause yield losses in hot and dry environments. As part of current efforts to diversify the dwarfing alleles used in wheat breeding, we identified a quantitative trait locus (QHt.ucw-6AS) affecting plant height in the proximal region of chromosome arm 6AS (< 0.4 cM from the centromere). Using a large segregating population (~ 2800 gametes) and extensive progeny tests (70–93 plants per recombinant family), we mapped QHt.ucw-6AS as a Mendelian locus to a 0.2 cM interval (144.0–148.3 Mb, IWGSC Ref Seq v1.0) and show that it is different from Rht18. QHt.ucw-6AS is officially designated as Rht25, with Rht25a representing the height-increasing allele and Rht25b the dwarfing allele. The average dwarfing effect of Rht25b was found to be approximately half of the effect observed for Rht-B1b and Rht-D1b, and the effect is greater in the presence of the height-increasing Rht-B1a and Rht-D1a alleles than in the presence of the dwarfing alleles. Rht25b is gibberellin-sensitive and shows significant pleiotropic effects on coleoptile length, heading date, spike length, spikelet number, spikelet density, and grain weight. Rht25 represents a new alternative dwarfing locus that should be evaluated for its potential to improve wheat yield in different environments.
J. Dubcovsky acknowledges financial support for this project from the Agriculture and Food Research Initiative Competitive Grant 2017-67007-25939 (WheatCAP) from the USDA National Institute of Food and Agriculture, the International Wheat Yield Partnership (IWYP) and the Howard Hughes Medical Institute. L. Vanzetti acknowledges financial support from the ANPCyT (Prestamo BID 2014, PICT1283), and INTA (PNCyO 1127042). Y. Mo is a Howard Hughes Medical Institute’s International Student Research fellow and a Monsanto’s Beachell-Borlaug International scholar.
Author contribution statement
LSV and IH developed mapping populations and conducted initial QTL mapping experiments. EJS and FG conducted field experiments and QTL analyses. YM, JA, and NO conducted high-resolution mapping experiments and GA sensitivity essays. YM and LSV wrote the first manuscript. SP and MH contributed to data analyses and manuscript revision. JD initiated and coordinated the project, contributed to data analyses, provided extensive revision and wrote the final manuscript. All authors reviewed the manuscript and provided suggestions.
Compliance with ethical standards
Confict of interest
The authors declare that there are no conflicts of interest.
This study does not include human or animal subjects.
- Cavanagh CR, Chao SM, Wang SC, Huang BE, Stephen S, Kiani S, Forrest K, Saintenac C, Brown-Guedira GL, Akhunova A, See D, Bai GH, Pumphrey M, Tomar L, Wong DB, Kong S, Reynolds M, da Silva ML, Bockelman H, Talbert L, Anderson JA, Dreisigacker S, Baenziger S, Carter A, Korzun V, Morrell PL, Dubcovsky J, Morell MK, Sorrells ME, Hayden MJ, Akhunov E (2013) Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars. Proc Natl Acad Sci USA 110:8057–8062CrossRefGoogle Scholar
- Evans LT (1998) Feeding the ten billion. Cambridge University Press, CambridgeGoogle Scholar
- Falconer D (1960) Introduction to quantitative genetics. Oliver and Boyd, LondonGoogle Scholar
- Ford BA, Foo E, Sharwood R, Karafiatova M, Vrána J, MacMillan C, Nichols DS, Steuernagel B, Uauy C, Doležel J, Chandler PM, Spielmeyer W (2018) Rht18 semi-dwarfism in wheat is due to increased expression of GA 2-oxidaseA9 and reduced GA content. Plant Physiol 177:168–180PubMedPubMedCentralGoogle Scholar
- Kertesz Z, Flintham JE, Gale MD (1991) Effects of Rht dwarfing genes on wheat grain yield and its components under Eastern European conditions. Cereal Res Commun 19:297–304Google Scholar
- Konzak CF (1988) Genetic analysis, genetic improvement and evaluation of induced semi-dwarf mutants in wheat. In: Semi-dwarf cereal mutants and their use in cross-breeding III. International Atomic Energy Agency, Vienna, pp 77–94Google Scholar
- Krasileva KV, Vasquez-Gross HA, Howell T, Bailey P, Paraiso F, Clissold L, Simmonds J, Ramirez-Gonzalez RH, Wang XD, Borrill P, Fosker C, Ayling S, Phillips AL, Uauy C, Dubcovsky J (2017) Uncovering hidden variation in polyploid wheat. Proc Natl Acad Sci USA 114:E913–E921CrossRefPubMedPubMedCentralGoogle Scholar
- McIntosh RA, Yamazaki Y, Dubcovsky J, Rogers J, Morris C, Appels R, Xia XC (2013) Catalogue of gene symbols for wheat. https://shigen.nig.ac.jp/wheat/komugi/genes/download.jsp. Accessed 17 Feb 2018
- McIntosh RA, Dubcovsky J, Rogers WJ, Morris C, Xia XC (2017) Catalogue of gene symbols for wheat: 2017 supplement. https://shigen.nig.ac.jp/wheat/komugi/genes/macgene/supplement2017.pdf. Accessed 17 Feb 2018
- Pařenicová L, de Folter S, Kieffer M, Horner DS, Favalli C, Busscher J, Cook HE, Ingram RM, Kater MM, Davies B, Angenent GC, Colombo L (2003) Molecular and phylogenetic analyses of the complete MADS-box transcription factor family in Arabidopsis: new openings to the MADS world. Plant Cell 15:1538–1551CrossRefPubMedPubMedCentralGoogle Scholar
- Spielmeyer W, Hyles J, Joaquim P, Azanza F, Bonnett D, Ellis ME, Moore C, Richards RA (2007) A QTL on chromosome 6A in bread wheat (Triticum aestivum) is associated with longer coleoptiles, greater seedling vigour and final plant height. Theor Appl Genet 115:59–66CrossRefPubMedPubMedCentralGoogle Scholar
- Wang S, Basten CZ, Zeng ZB (2012) Windows QTL cartographer 2.5, Department of Statistics. North Carolina State University, RaleighGoogle Scholar
- Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, Maccaferri M, Salvi S, Milner SG, Cattivelli L, Mastrangelo AM, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, International Wheat Genome Sequencing Consortium, Lillemo M, Mather D, Appels R, Dolferus R, Brown-Guedira G, Korol A, Akhunova AR, Feuillet C, Salse J, Morgante M, Pozniak C, Luo MC, Dvorak J, Morell M, Dubcovsky J, Ganal M, Tuberosa R, Lawley C, Mikoulitch I, Cavanagh C, Edwards KJ, Hayden M, Akhunov E (2014) Characterization of polyploid wheat genomic diversity using a high-density 90,000 single nucleotide polymorphism array. Plant Biotechnol J 12:787–796CrossRefPubMedPubMedCentralGoogle Scholar
- Zhang J, Gizaw SA, Bossolini E, Hegarty J, Howell T, Carter AH, Akhunov E, Dubcovsky J (2018) Identification and validation of QTL for grain yield and plant water status under contrasting water treatments in fall-sown spring wheats. Theor Appl Genet. https://doi.org/10.1007/s00122-018-3111-9 CrossRefPubMedPubMedCentralGoogle Scholar