Development of the first consensus genetic map of intermediate wheatgrass (Thinopyrum intermedium) using genotyping-by-sequencing
- 1k Downloads
Development of the first consensus genetic map of intermediate wheatgrass gives insight into the genome and tools for molecular breeding.
Intermediate wheatgrass (Thinopyrum intermedium) has been identified as a candidate for domestication and improvement as a perennial grain, forage, and biofuel crop and is actively being improved by several breeding programs. To accelerate this process using genomics-assisted breeding, efficient genotyping methods and genetic marker reference maps are needed. We present here the first consensus genetic map for intermediate wheatgrass (IWG), which confirms the species’ allohexaploid nature (2n = 6x = 42) and homology to Triticeae genomes. Genotyping-by-sequencing was used to identify markers that fit expected segregation ratios and construct genetic maps for 13 heterogeneous parents of seven full-sib families. These maps were then integrated using a linear programming method to produce a consensus map with 21 linkage groups containing 10,029 markers, 3601 of which were present in at least two populations. Each of the 21 linkage groups contained between 237 and 683 markers, cumulatively covering 5061 cM (2891 cM––Kosambi) with an average distance of 0.5 cM between each pair of markers. Through mapping the sequence tags to the diploid (2n = 2x = 14) barley reference genome, we observed high colinearity and synteny between these genomes, with three homoeologous IWG chromosomes corresponding to each of the seven barley chromosomes, and mapped translocations that are known in the Triticeae. The consensus map is a valuable tool for wheat breeders to map important disease-resistance genes within intermediate wheatgrass. These genomic tools can help lead to rapid improvement of IWG and development of high-yielding cultivars of this perennial grain that would facilitate the sustainable intensification of agricultural systems.
KeywordsLinkage Group Segregation Distortion Barley Chromosome Allele Count Sustainable Intensification
This work was supported by the Malone Family Land Preservation Foundation and The Land Institute through The Perennial Agriculture Project, The Initiative of Renewable Energy & The Environment, University of Minnesota, grant number RL_0015-12, and The Forever Green Initiative, University of Minnesota. The work at Kansas State University was done under the auspices of the Wheat Genetics Resource Center (WGRC) Industry/University Collaborative Research Center (I/UCRC) supported by NSF grant contract (IIP-1338897) and industry partners. Trevor Rife (Kansas State University) provided great assistance with combining the Ion and Illumina data and Jonathan Mitchell (University of Michigan/The Field Museum) provided assistance with early versions of the R scripts for custom genotype calling.
Compliance with ethical standards
The authors declare that the experiments comply with the current laws in the United States of America.
Conflict of interest
The authors declare that they have no conflict of interest.
- Armstead IP, Turner LB, Marshall AH, Humphreys MO, King IP, Thorogood D (2008) Identifying genetic components controlling fertility in the outcrossing grass species perennial ryegrass (Lolium perenne) by quantitative trait loci analysis and comparative genetics. New Phytol 178:559–571CrossRefPubMedGoogle Scholar
- Cattani D (2014) Perennial grains around the world: II. ASA, CSSA, & SSA, Long BeachGoogle Scholar
- DeHaan LR, Wang S, Larson SR, Cattani DJ, Zhang X, Kantarski TR (2014) Current efforts to develop perennial wheat and domesticate Thinopyrum intermedium as a perennial grain. In: Batello C, Wade L, Cox S, Pogna N, Bozzini A, Choptiany J (eds) Perennial crops for food security proceedings of the FAO expert workshop. FAO of the UN, Rome, pp 72–89Google Scholar
- FAO (2014) Perennial crops for food security proceedings of the FAO expert workshop. FAO of the UN, RomeGoogle Scholar
- Glover JD (2014) Perennial grains for food security in a changing world: gene to farm innovations. AAAS, ChicagoGoogle Scholar
- Luo MC, Gu YQ, You FM, Deal KR, Ma Y, Hu Y, Huo N, Wang Y, Wang J, Chen S, Jorgensen CM, Zhang Y, McGuire PE, Pasternak S, Stein JC, Ware D, Kramer M, McCombie WR, Kianian SF, Martis MM, Mayer KFX, Sehgal SK, Li W, Gill BS, Bevan MW, Šimková H, Doležel J, Weining S, Lazo GR, Anderson OD, Dvorak J (2013) A 4-gigabase physical map unlocks the structure and evolution of the complex genome of Aegilops tauschii, the wheat D-genome progenitor. Proc Natl Acad Sci USA 110:7940–7945CrossRefPubMedPubMedCentralGoogle Scholar
- R_Core_Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
- Runck BC, Kantar MB, Jordan NR, Anderson JA, Wyse DL, Eckberg JO, Barnes RJ, Lehman CL, DeHaan LR, Stupar RM, Sheaffer CC, Porter PM (2014) The reflective plant breeding paradigm: a robust system of germplasm development to support strategic diversification of agroecosystems. Crop Sci 54:1939–1948CrossRefGoogle Scholar
- The_International_Barley_Genome_Sequencing_Consortium (2012) A physical, genetic and functional sequence assembly of the barley genome. Nature 491:711–716Google Scholar
- Tsvelev NN (1983) Grasses of the Soviet Union. Oxonian Press Pvt. Ltd., New Delhi, India, pp 196–298Google Scholar
- Van Ooijen J (2006) JoinMap 4, Software for the calculation of genetic linkage maps in experimental populations. Kyazma BV, WageningenGoogle Scholar
- Wagoner P (1990) Perennial grain new use for intermediate wheatgrass. J Soil Water Conserv 45:81–82Google Scholar
- Zhang X, Sallam A, Gao L, Kantarski T, Poland J, DeHaan LR, Wyse DL, Anderson JA (2016) Establishment and optimization of genomic selection to accelerate the domestication and improvement of intermediate wheatgrass. Plant Genome 9. doi: 10.3835/plantgenome2015.07.0059