Interspecific genetic maps in Miscanthus floridulus and M. sacchariflorus accelerate detection of QTLs associated with plant height and inflorescence
Miscanthus is recognized as a promising lignocellulosic crop for the production of bioethanol and bioproducts worldwide. To facilitate the identification of agronomical important traits and establish genetics knowledge, two genetic maps were developed from a controlled interspecific cross between M. floridulus and M. sacchariflorus. A total of 650 SSR markers were mapped in M. floridulus, spanning 19 linkage groups and 2053.31 cM with an average interval of 3.25 cM. The map of M. sacchariflorus comprised 495 SSR markers in 19 linkage groups covering 1684.86 cM with an average interval of 3.54 cM. The estimation on genome length indicated that the genome coverage of parental genetic maps were 93.87% and 89.91%, respectively. Eighty-eight bi-parental common markers were allowed to connect the two maps, and six pairs of syntenic linkage groups were recognized. Furthermore, quantitative trait loci (QTL) mapping of three agronomic traits, namely, plant height (PH), heading time (HT), and flowering time (FT), demonstrated that a total of 66 QTLs were identified in four consecutive years using interval mapping and multiple-QTL model. The LOD value of these QTLs ranged from 2.51 to 10.60, and the phenotypic variation explained varied from 9.50 to 37.10%. QTL cluster in syntenic groups MF19/MS7 contained six stable QTLs associated with PH, HT, and FT. In conclusion, we report for the first time the genetic mapping of biomass traits in M. floridulus and M. sacchariflorus. These results will be a valuable genetic resource, facilitating the discovery of essential genes and breeding of Miscanthus.
KeywordsMiscanthus Genetic map SSR QTL mapping Biomass
This work was supported by the National Natural Sciences Foundation of China (31271352 and 31071471).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflicts of interest.
The authors declare that this study complies with the current laws of the country in which the experiments were performed. This article does not contain any studies with human participants or animals performed by any of the authors.
- Atienza SG, Ramirez MC, Martin A (2003b) Mapping QTLs controlling flowering date in Miscanthus sinensis Anderss. Cereal Res Commun 31:265–271Google Scholar
- Barling A, Swaminathan K, Mitros T, James BT, Morris J, Ngamboma O, Hall MC, Kirkpatrick J, Alabady M, Spence AK, Hudson ME, Rokhsar DS, Moose SP (2013) A detailed gene expression study of the Miscanthus genus reveals changes in the transcriptome associated with the rejuvenation of spring rhizomes. BMC Genom 14:864CrossRefGoogle Scholar
- Bowers JE, Abbey C, Anderson S, Chang C, Draye X, Hoppe AH, Jessup R, Lemke C, Lennington J, Li Z, Lin Y, Liu S, Luo L, Marler BS, Ming R, Mitchell SE, Qiang D, Reischmann K, Schulze SR, Skinner DN, Wang Y, Kresovich S, Schertz KF, Paterson AH (2003) A high-density genetic recombination map of sequence-tagged sites for Sorghum, as a framework for comparative structural and evolutionary genomics of tropical grains and grasses. Genetics 165:367–386Google Scholar
- Buckler ES, Holland JB, Bradbury PJ, Acharya CB, Brown PJ, Browne C, Ersoz E, Flint-Garcia S, Garcia A, Glaubitz JC, Goodman MM, Harjes C, Guill K, Kroon DE, Larsson S, Lepak NK, Li H, Mitchell SE, Pressoir G, Peiffer JA, Rosas MO, Rocheford TR, Romay MC, Romero S, Salvo S, Sanchez Villeda H, da Silva HS, Sun Q, Tian F, Upadyayula N, Ware D, Yates H, Yu J, Zhang Z, Kresovich S, McMullen MD (2009) The genetic architecture of maize flowering time. Science 325:714–718CrossRefGoogle Scholar
- Chakravarti A, Lasher LK, Reefer JE (1991) A maximum likelihood method for estimating genome length using genetic linkage data. Genetics 128:175–182Google Scholar
- Chen SL, Renvoize SA (2006) Miscanthus. In: Wu ZY (ed) Flora of China, 3rd edn. Flora of China, Beijing, pp 581–583Google Scholar
- Fishman L, Kelly AJ, Morgan E, Willis JH (2001) A genetic map in the Mimulus guttatus species complex reveals transmission ratio distortion due to heterospecific interactions. Genetics 159:1701–1716Google Scholar
- Higgins RH, Thurber CS, Assaranurak I, Brown PJ (2014) Multiparental mapping of plant height and flowering time QTL in partially isogenic sorghum families. G3 (Genes Genom Genet) 4:1593–1602Google Scholar
- Hodkinson TR, Chase MW, Lledo MD, Salamin N, Renvoize SA (2002b) Phylogenetics of Miscanthus, Saccharum and related genera (Saccharinae, Andropogoneae, Poaceae) based on DNA sequences from ITS nuclear ribosomal DNA and plastid trnL intron and trnL-F intergenic spacers. J Plant Res 115:381–392CrossRefGoogle Scholar
- Jansen RC, Stam P (1994) High resolution of quantitative traits into multiple loci via interval mapping. Genetics 136:1447–1455Google Scholar
- Lander ES, Botstein D (1989) Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185–199Google Scholar
- Ma XF, Jensen E, Alexandrov N, Troukhan M, Zhang L, Thomas-Jones S, Farrar K, Clifton-Brown J, Donnison I, Swaller T, Flavell R (2012) High resolution genetic mapping by genome sequencing reveals genome duplication and tetraploid genetic structure of the diploid Miscanthus sinensis. PLoS One 7:e33821CrossRefGoogle Scholar
- Manrique-Carpintero NC, Coombs JJ, Veilleux RE, Buell CR, Douches DS (2016) Comparative analysis of regions with distorted segregation in three diploid populations of potato. G3-Genes Genom Genet 6:2617–2628Google Scholar
- Ming R, Liu SC, Lin YR, Silva JD, Wilson W, Braga D, van Deynze A, Wenslaff TF, Wu KK, Moore PH, Burnquist W, Sorrells ME, Irvine JE, Paterson AH (1998) Detailed alignment of Saccharum and sorghum chromosomes: comparative organization of closely related diploid and polyploid genomes. Genetics 150:1663–1682Google Scholar
- Van Ooijen JW (2006) JoinMap4, software for the calculation of genetic linkage maps in experimental populations. Kyazma BV, WageningenGoogle Scholar
- Van Ooijen JW (2009) MAPQTL® 6, software for the mapping of quantitative trait loci in experimental populations of diploid species. Kyazma BV, WageningenGoogle Scholar
- Xu S (2003) Theoretical basis of the beavis effect. Genetics 165:2259–2268Google Scholar