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Progress and Prospects of Association Mapping in Sugarcane (Saccharum Species Hybrid), a Complex Polyploid Crop

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Abstract

Sugarcane is one of the most important economic crops and contributes more than 80% of the sugar globally. Developing superior sugarcane varieties is a long-term process due to polyploidy, high chromosome numbers, large complex genome size and also many other practical constraints like long breeding cycle, etc. The recent advancements in molecular markers, next-gen sequencing tools and development of robust statistical models have the potential to lead to affordable genomics-assisted breeding in sugarcane. In order to identify genes linked to trait(s) of interest, association mapping has good prospects as a feasible approach in sugarcane. Association mapping (AM) is a recent technique that identifies quantitative trait loci (QTLs) by investigating marker–trait associations that arise due to the linkage disequilibrium between the genotypic polymorphic loci and the phenotypic variation in a diverse panel of genotypes. In last decade, the understanding of association mapping has increased significantly, due to which focussed efforts are now been made in developing association mapping population, genome-wide association studies and detection of QTLs for several important traits in sugarcane. In contrast to linkage mapping, detecting QTLs through AM approach in sugarcane has certain advantages as historical phenotypic data could be used and there is no need to artificially develop a structured segregating population. The last few years have witnessed a more concerted effort in AM studies in sugarcane where a range of marker tools like SSRs, DArT, GBS, targeted sequence enrichment, etc. were exploited to find out QTLs linked to traits of economic importance. In this review, the recent developments in the area of association mapping in sugarcane and the various methodologies and statistical tools that are being adopted have been discussed.

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References

  • Abdurakhmonov, I.Y., and A. Abdukarimov 2008. Application of association mapping to understanding the genetic diversity of plant germplasm resources. International Journal of Plant Genomics 2008: Art. ID 574927. http://dx.doi.org/10.1155/2008/574927.

  • Adhikari, L., and A.M. Missaoui. 2019. Quantitative trait loci mapping of leaf rust resistance in tetraploid alfalfa. Physiological and Molecular Plant Pathology 106: 238–245.

    CAS  Google Scholar 

  • Aitken, K.S., J.C. Li, and P. Jackson. 2006. Using molecular markers to introgress traits from related wild species into sugarcane. Proceedings of the Australian Society of Sugar Cane Technology 187: 448–455.

    Google Scholar 

  • Aitken, K.S., M.D. McNeil, P.J. Berkman, S. Hermann, A. Kilian, P.C. Bundock, and J. Li. 2014a. Comparative mapping in the Poaceae family reveals translocations in the complex polyploid genome of sugarcane. BMC Plant Biology 14(1): 190.

    Google Scholar 

  • Aitken, K.S., M.D. McNeil, S. Hermann, P.C. Bundock, A. Kilian, K. Heller-Uszynska, R.J. Henry, and J. Li. 2014b. A comprehensive genetic map of sugarcane that provides enhanced map coverage and integrates high-throughput Diversity Array Technology (DArT) markers. BMC Genomics 24: 151–152.

    Google Scholar 

  • Al-Janabi, S.M., R.J. Honeycutt, M. McClelland, and B.W.S. Sobral. 1993. A genetic linkage map of Saccharum spontaneum L. ‘SES 208’. Genetics 134: 1249–1260.

    CAS  Google Scholar 

  • Alwala, S., C.A. Kimbeng, J.C. Veremis, and K.A. Gravois. 2009. Identification of molecular markers associated with sugar related traits in a Saccharum inter-specific cross. Euphytica 167: 127–142.

    CAS  Google Scholar 

  • Balsalobre, T.W.A., G.P. daSilva, G.R. Alves, M.R. Gazaffi, F.Z. Barreto, C.O. Anoni, C.B. Cardoso-Silva, E.A. Costa, M.C. Mancini, H.P. Hoffmann, A.P. deSouza, A.A.F. Garcia, and M.S. Carneiro. 2017. GBS-based single dosage markers for linkage and QTL mapping allow gene mining for yield-related traits in sugarcane. BMC Genomics 18: 72. https://doi.org/10.1186/s12864-016-3383-x.

    Article  CAS  Google Scholar 

  • Banerjee, N., A. Siraree, S. Yadav, S. Kumar, J. Singh, S. Kumar, D.K. Pandey, and R.K. Singh. 2015. Marker–trait association study for sucrose and yield contributing traits in sugarcane (Saccharum spp. hybrid). Euphytica 205: 185–201.

    CAS  Google Scholar 

  • Barnes, J.M., R.S. Rutherford, and F.C. Botha. 1997. The identification of potential genetic markers in sugarcane varieties for the prediction of disease and pest resistance ratings. Proceedings of Annual Congress of South African Sugar Technologists Association 71: 57–61.

    Google Scholar 

  • Barreto, F.Z., J.R.B.F. Rosa, T.W.A. Balsalobre, M.M. Pastina, R.R. Silva, H.P. Hoffmann, et al. 2019. A genome-wide association study identified loci for yield component traits in sugarcane (Saccharum spp.). PLoS ONE 14(7): e0219843.

    CAS  Google Scholar 

  • Behrouzi, P., D. Arends, and E.C. Wit. 2017. Netgwas: An R package for network-based genome-wide association studies. arXiv:1710.01236v5 [stat.AP].

  • Bilal, M., M. Saeed, I.A. Nasir, B. Tabassum, M. Zameer, A. Khan, M. Tariq, A.M. Javed, and T. Husnain. 2015. Association mapping of cane weight and tillers per plant in sugarcane. Biotechnology and Biotechnological Equipment 29(4): 617–623.

    CAS  Google Scholar 

  • Bradbury, P.J., Z. Zhang, D.E. Kroon, T.M. Casstevens, Y. Ramdoss, and E.S. Buckler. 2007. TASSEL: Software for association mapping of complex traits in diverse samples. Bioinformatics 23(19): 2633–2635.

    CAS  Google Scholar 

  • Breseghello, F., and M.E. Sorrells. 2006. Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics 172: 1165–1177.

    Google Scholar 

  • Cai, S., D. Wu, Z. Jabeen, Y. Huang, and G. Zhang. 2013. Genome-wide association analysis of aluminum tolerance in cultivated and Tibetan wild barley. PLoS ONE 8: e69776.

    CAS  Google Scholar 

  • Carlson, C.S., M.A. Eberle, L. Kruglyak, and D.K. Nickerson. 2004. Mapping complex disease loci in whole genome association studies. Nature 429: 446–452.

    CAS  Google Scholar 

  • Clark, R.M., G. Schweikert, C. Toomajian, S. Ossowski, G. Zeller, P. Shinn, N. Warthmann, T.T. Hu, G. Fu, D.A. Hinds, and H. Chen. 2007. Common sequence polymorphisms shaping genetic diversity in Arabidopsis thaliana. Science 317(5836): 338–342.

    CAS  Google Scholar 

  • Daniels, J., and B.T. Roach. 1987. Taxonomy and evolution. In Sugarcane improvement through breeding, ed. D.J. Heinz, 7–84. Amsterdam: Elsevier.

    Google Scholar 

  • Daniels, J., P. Smith, N. Paton, and C.A. Williams. 1975. The origin of the genus Saccharum. Sugarcane Breeding Newsletter 36: 24–39.

    Google Scholar 

  • Daugrois, J.H., L. Grivet, D. Roques, J.Y. Hoarau, H. Lombard, J.C. Glaszmann, and A. D’Hont. 1996. A putative major gene for rust resistance linked with a RFLP marker in sugarcane cultivar ‘R570’. Theoretical and Applied Genetics 92(8): 1059–1064.

    CAS  Google Scholar 

  • Debibakas, S., S. Rocher, O. Garsmeur, L. Toubi, D. Roques, A. D’Hont, J.Y. Hoarau, and J.H. Daugrois. 2014. Prospecting sugarcane resistance to sugarcane yellow leaf virus by genome-wide association. Theoretical and Applied Genetics 127(8): 1719–1732.

    CAS  Google Scholar 

  • Diola, V., M.H.P. Barbosa, C.F.M. Veiga, and E.C. Fernandes. 2014. Molecular markers EST-SSRs for genotype-phenotype association in sugarcane. SugarTech 16(3): 241–249.

    CAS  Google Scholar 

  • Dufresne, F., M. Stift, R. Vergilino, and B.K. Mable. 2014. Recent progress and challenges in population genetics of polyploid organisms: An overview of current state-of-the-art molecular and statistical tools. Molecular Ecology 23(1): 40–69.

    Google Scholar 

  • Edme, S.J., N.G. Glynn, and J.C. Comstock. 2006. Genetic segregation of microsatellite markers in Saccharum officinarum and S. spontaneum. Heredity 97(5): 366–375.

    CAS  Google Scholar 

  • Falush, D., M. Stephens, and J.K. Pritchard. 2003. Inference of population structure using multilocus genotype data: Linked loci and correlated allele frequencies. Genetics 164(4): 1567–1587.

    CAS  Google Scholar 

  • Falush, D., M. Stephens, and J.K. Pritchard. 2007. Inference of population structure using multilocus genotype data: Dominant markers and null alleles. Molecular Ecology Notes 7(4): 574–578.

    CAS  Google Scholar 

  • FAOSTAT. 2019. Food and agricultural organisation statistical database. Accessed 10 Aug. 2019.

  • Fickett, N., A. Gutierrez, M. Verma, M. Pontif, A. Hale, C. Kimbeng, and N. Baisakh. 2018. Genome-wide association mapping identifers markers associated with cane yield components and sucrose traits in the Louisiana sugarcane core collection. Genomics 111(6): 1794–1801.

    Google Scholar 

  • Flint-Garcia, S.A., J.M. Thornsberry, and E.S. Buckler. 2003. Structure of linkage disequilibrium in plants. Annual Review of Plant Biology 54(1): 357–374.

    CAS  Google Scholar 

  • Garcia, A.A., E.A. Kido, A.N. Meza, H.M. Souza, L.R. Pinto, M.M. Pastina, C.S. Leite, J.A. DaSilva, E.C. Ulian, A. Figueira, and A.P. Souza. 2006. Development of an integrated genetic map of a sugarcane (Saccharum spp.) commercial cross, based on a maximum-likelihood approach for estimation of linkage and linkage phases. Theoretical and Applied Genetics 112(2): 298–314.

    CAS  Google Scholar 

  • Garcia, A.A., M. Mollinari, T.G. Marconi, O.R. Serang, and R.R. Silva. 2013. SNP genotyping allows an in depth characterisation of the genome of sugarcane and other complex autopolyploids. Nature Scientific Reports 3: 3399.

    Google Scholar 

  • Garsmeur, O., G. Droc, R. Antonise, J. Grimwood, B. Potier, et al. 2018. A mosaic monoploid reference sequence for the highly complex genome of sugarcane. Nature 9: 2638.

    Google Scholar 

  • Gerard, D., L.F.V. Ferrao, A.A.F. Garcia, and M. Stephens. 2018. Genotyping polyploids from messy sequencing data. Genetics 210: 789–807.

    Google Scholar 

  • Gouy, M., Y. Rousselle, A.T. Chane, A. Anglade, S. Royaert, S. Nibouche, and L. Costet. 2015. Genome wide association mapping of agromorphological and disease resistance traits in sugarcane. Euphytica 202: 269–284.

    Google Scholar 

  • Grivet, L., and P. Arruda. 2001. Sugarcane genomics: Depicting the complex genome of an important tropical crop. Current Opinion in Plant Biology 5: 122–127.

    Google Scholar 

  • Guimaraes, C.T., G.R. Sills, and B.W.S. Sobral. 1997. Comparative mapping of Andropogoneae: Saccharum L. (sugarcane) and its relation to sorghum and maize. Proceedings of National Academy of Sciences USA 94: 14262–14266.

    Google Scholar 

  • Gupta, P.K., S. Rustgi, and P.L. Kulwal. 2005. Linkage disequilibrium and association studies in higher plants: Present status and future prospects. Plant Molecular Biology 57: 461–485.

    CAS  Google Scholar 

  • Gutierrez, A.F., J.W. Hoy, C.A. Kimbeng, and N. Baisakh. 2018. Identification of genomic regions controlling leaf scald resistance in sugarcane using a bi-parental mapping population and selective genotyping by sequencing. Frontiers in Plant Science 9: 877.

    Google Scholar 

  • Hardy, O.J., and X. Vekemans. 2002. SPAGeDi: A versatile computer program to analyse spatial genetic structure at the individual or population levels. Molecular Ecology Notes 2(4): 618–620.

    Google Scholar 

  • Hirschhorn, J.N., and M.J. Daly. 2005. Genome-wide association studies for common diseases and complex traits. Nature Review Genetics 6(2): 95.

    CAS  Google Scholar 

  • Hoarau, J.Y., B. Offmann, A. D’Hont, A.M. Risterucci, D. Roques, J.C. Glaszmann, and L. Grivet. 2001. Genetic dissection of a modern cultivar (Saccharum spp.). I. Genome mapping with AFLP. Theoretical and Applied Genetics 103: 84–97.

    CAS  Google Scholar 

  • Huttley, G.A., M.W. Smith, M. Carrington, and S.J. O’Brien. 1999. A scan for linkage disequilibrium across the human genome. Genetics 152(4): 1711–1722.

    CAS  Google Scholar 

  • Jannoo, N., L. Grivet, J. David, A. D’Hont, and J.C. Glaszmann. 2004. Differential chromosome pairing affinities at meiosis in polyploid sugarcane revealed by molecular markers. Heredity 93(5): 460–467.

    CAS  Google Scholar 

  • Kang, H.M., N.A. Zaitlen, C.M. Wade, A. Kirby, D. Heckerman, M.J. Daly, and E. Eskin. 2008. Efficient control of population structure in model organism association mapping. Genetics 178(3): 1709–1723.

    Google Scholar 

  • Klaassen, M.T., P.M. Bourke, C. Maliepaard, and L.M. Trindade. 2019. Multi-allelic QTL analysis of protein content in a bi-parental population of cultivated tetraploid potato. Euphytica 215(14): 1–18.

    CAS  Google Scholar 

  • Lipka, A.E., F. Tian, Q. Wang, J. Peiffer, and M. Li. 2012. GAPIT: Genome association and prediction integrated tool. Bioinformatics 28(18): 2397–2399.

    CAS  Google Scholar 

  • Lippert, C., J. Listgarten, Y. Liu, C.M. Kadie, R.I. Davidson, and D. Heckerman. 2011. FaST linear mixed models for genome-wide association studies. Nature Methods 8(10): 833–835.

    CAS  Google Scholar 

  • Liu, X., M. Huang, B. Fan, E.S. Buckler, and Z. Zhang. 2016. Iterative usage of fixed and random effect models for powerful and efficient genome-wide association studies. PLoS Genetics 12(2): e1005767.

    Google Scholar 

  • Melo, A.T., R. Bartaula, and I. Hale. 2016. GBS-SNP-CROP: A reference-optional pipeline for SNP discovery and plant germplasm characterization using variable length, paired-end genotyping-by-sequencing data. BMC Bioinformatics 17(1): 29.

    Google Scholar 

  • Ming, R., S.C. Lin, Y.R. Lin, J. DaSilva, and W. Wilson. 1998. Detailed alignment of Saccharum and Sorghum chromosomes: Comparative organisation of closely related diploid and polyploid genomes. Genetics 150: 1663–1682.

    CAS  Google Scholar 

  • Ming, R., S.C. Liu, P.H. Moore, J.E. Irvine, and A.H. Paterson. 2001. QTL Analysis in a complex autoploid: Genetic control of sugar content in sugarcane. Genome Research 11: 2075–2084.

    CAS  Google Scholar 

  • Mudge, J., W.R. Anderson, R.L. Kehrer, and D.J. Fairbanks. 1996. A RAPD genetic map of Saccharum officinarum. Crop Science 36: 1362–1366.

    CAS  Google Scholar 

  • Mukherjee, S.K. 1957. Origin and distribution of Saccharum. Botanical Gazette 119(1): 55–61.

    Google Scholar 

  • Nibouche, S., L. Costet, A. Thong-Chen, A. Gouy, D. Luquet, L. Rouan, J.C. Soulie, A. D’Hont, and C. Charron. 2008. Association mapping and model phenotyping for the characterization of molecular markers associated with sugarcane yield formation and limitation. Project Report-Other Species, Edition 2008, CIRAD, France, 10–11.

  • Nibouche, S., L.M. Raboin, J.Y. Hoarau, A. D’Hont, and L. Costet. 2012. Quantitative trait loci for sugarcane resistance to the spotted stem borer Chilo sacchariphagus. Molecular Breeding 29(1): 129–135.

    Google Scholar 

  • Pastina, M.M., M. Malosetti, R. Gazaffi, M. Mollinari, G.R. Margarido, K.M. Oliveira, L.R. Pinto, A.P. Souza, F.A. VanEeuwijk, and A.A. Garcia. 2012. A mixed model QTL analysis for sugarcane multiple-harvest-location trial data. Theoretical and Applied Genetics 124(5): 835–849.

    CAS  Google Scholar 

  • Payne, R.W., S.A. Harding, D.A. Murray, D.M. Soutar, D.B. Baird, A.I. Glaser, I.C. Channing, S.J. Welham, A.R. Gilmour, R. Thompson, and R. Webster. 2008. GenStat release 11, Reference Manual Part 2- Directives. Hemel Hempstead: VSN International.

    Google Scholar 

  • Pinto, L.R., D.C. Leite, T.M. Favero, M.M. Pastina, A.A.F. Garcia, D. Perecin, B.S. Goncalves, S. Creste, M.A. Xavier, M.A.P. Bidoia, and M.G.A. Landell. 2010. Identification of microsatellite markers associated with yield components and quality parameters in sugarcane. Proceedings of International Sugarcane Technologists 27: 1–7.

    Google Scholar 

  • Price, A.H. 2006. Believe it or not, QTLs are accurate. Trends in Plant Science 11(5): 213–216.

    CAS  Google Scholar 

  • Pritchard, J.K., and N.A. Rosenberg. 1999. Use of unlinked genetic markers to detect population stratification in association studies. American Journal of Human Genetics 65(1): 220–228.

    CAS  Google Scholar 

  • Pritchard, J.K., M. Stephens, and P. Donnelly. 2000. Inference of population structure using multilocus genotype data. Genetics 155: 945–959.

    CAS  Google Scholar 

  • Purcell, S., B. Neale, K. Todd-Brown, L. Thomas, M.A. Ferreira, D. Bender, J. Maller, P. Sklar, P.I. DeBakker, M.J. Daly, and P.C. Sham. 2007. PLINK: A tool set for whole-genome association and population-based linkage analyses. American Journal of Human Genetics 81(3): 559–575.

    CAS  Google Scholar 

  • R Core Team. 2013. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.

    Google Scholar 

  • Raboin, L.M., K.M. Oliveira, L. Lecunff, H. Telismart, D. Roques, M. Butterfield, J.Y. Hoarau, and A. D’Hont. 2006. Genetic mapping in the high polyploid sugarcane using a bi-parental progeny: Identification of a gene controlling stalk colour and new rust resistance gene. Theoretical and Applied Genetics 112(7): 1382–1391.

    CAS  Google Scholar 

  • Raboin, L.M., J. Pauquet, M. Butterfield, A. D’Hont, and J.C. Glaszmann. 2008. Analysis of genome-wide linkage disequilibrium in the highly polyploid sugarcane. Theoretical and Applied Genetics 116: 701–714.

    CAS  Google Scholar 

  • Racedo, J., L. Gutierrez, M.F. Perera, S. Ostengo, E.M. Pardo, M.I. Cuenya, B. Welin, and P. Castagnaro. 2016. Genome-wide association mapping of quantitative traits in a breeding population of sugarcane. BMC Plant Biology 16(142): 1–16.

    Google Scholar 

  • Roach, B.T. 1989. Origin and improvement of the genetic base of sugarcane. Proceedings of Australian Society of Sugarcane Technologists 11: 34–47.

    Google Scholar 

  • Rosyara, U.R., W.S. DeJong, D.S. Douches, and J.B. Endelman. 2016. Software for genome-wide association studies in autopolyploids and its application to potato. The Plant Genome 9(2): 1–10.

    CAS  Google Scholar 

  • Santos, F., A. Borem, and C. Caldas. 2015. Sugarcane: Agricultural production, bioenergy and ethanol. London: Academic Press.

    Google Scholar 

  • Selvi, A., and N.V. Nair. 2010. Molecular breeding in sugarcane. International Journal of Agriculture and Environmental Biotechnology 3(1): 115–127.

    Google Scholar 

  • Serang, O., M. Mollinari, and A.A.F. Garcia. 2012. Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids. PLoS ONE 7(2): e30906.

    CAS  Google Scholar 

  • Silva, M.D.A., and P.D.S. Goncalves. 2011. Inbreeding in sugarcane varieties. Ciencia Rural 41(4): 580–586.

    Google Scholar 

  • Singh, B.D., and A.K. Singh. 2015. Marker assisted plant breeding: Principles and practices. New Delhi: Springer.

    Google Scholar 

  • Singh, R.K., N. Banerjee, M.S. Khan, S. Yadav, S. Kumar, S.K. Duttamajumder, R.J. Lal, J.D. Patel, H. Guo, D. Zhang, and A.H. Paterson. 2016. Identification of putative candidate genes for red rot resistance in sugarcane (Saccharum species hybrid) using LD-based association mapping. Molecular Genetics and Genomics 291: 1363–1377.

    CAS  Google Scholar 

  • Siraree, A., N. Banerjee, S. Kumar, M.S. Khan, P.K. Singh, S. Kumar, S. Sharma, R.K. Singh, and J. Singh. 2017. Identification of marker–trait associations for morphological descriptors and yield component traits in sugarcane. Physiology and Molecular Biology of Plants 23(1): 185–191.

    Google Scholar 

  • Smulders, M.J., P. Arens, P.M. Bourke, T. Debener, M. Linde, J. DeRiek, L. Leus, T. Ruttink, S. Baudino, L.H. Saint-Oyant, and J. Clotault. 2019. In the name of the rose: a roadmap for rose research in the genome era. Horticulture Research 6(1): 65–82.

    Google Scholar 

  • Sreenivasan, T.V., B.S. Ahloowalia, and D.J. Heinz. 1987. Cytogenetics. In Sugarcane improvement through breeding, ed. D.J. Heinz, 211–253. Amsterdam: Elsevier.

    Google Scholar 

  • Stich, B., A.E. Melchinger, H.P. Piepho, M. Heckenberger, H.P. Maurer, and J.C. Reif. 2006. A new test for family-based association mapping with inbred lines from plant breeding programs. Theoretical and Applied Genetics 113(6): 1121–1130.

    Google Scholar 

  • Strimmer, K. 2008. fdrtool: A versatile R package for estimating local and tail area-based false discovery rates. Bioinformatics 24(12): 1461–1462.

    CAS  Google Scholar 

  • Syvanen, A.C. 2005. Toward genome-wide SNP genotyping. Nature Genetics 37: S5–S10.

    Google Scholar 

  • Tian, C., K. Peter, P.K. Gregersen, and M.F. Seldin. 2008. Accounting for ancestry: Population substructure and genome-wide association studies. Human Molecular Genetics 17: 143–150.

    Google Scholar 

  • Ukoskit, K., G. Posudsavang, N. Pongsiripat, P. Chatwachirawong, P. Klomsa-ard, P. Poomipant, and S. Tragoonrung. 2019. Detection and validation of EST-SSR markers associated with sugar-related traits in sugarcane using linkage and association mapping. Genomics 111: 1–9.

    CAS  Google Scholar 

  • Uricaru, R., G. Rizk, V. Lacroix, E. Quillery, O. Plantard, R. Chikhi, C. Lemaitre, and P. Peterlongo. 2014. Reference-free detection of isolated SNPs. Nucleic Acids Research 43(2): e11. https://doi.org/10.1093/nar/gku1187.

    Article  CAS  Google Scholar 

  • Varshney, R.K., A. Graner, and M.E. Sorrells. 2005. Genic microsatellite markers in plants: Features and applications. Trends in Biotechnology 23(1): 48–55.

    CAS  Google Scholar 

  • Waclawovsky, A.J., P.M. Sato, C.G. Lembke, P.H. Moore, and G.M. Souza. 2010. Sugarcane for bioenergy production: An assessment of yield and regulation of sucrose content. Plant Biotechnology Journal 8(3): 263–276.

    CAS  Google Scholar 

  • Walker, D.I.T. 1987. Manipulating the genetic base of sugarcane. In: Intl Sugarcane Breed Workshop, Copersucar, Sao Paulo. 321–334.

  • Wei, X., A.J. Phillip, C.L. McIntyre, K.S. Aitken, and C. Barry. 2006. Associations between DNA markers and resistance to diseases in sugarcane and effects of population substructure. Theoretical and Applied Genetics 114: 155–164.

    CAS  Google Scholar 

  • Wei, X., P.A. Jackson, S. Hermann, A. Kilian, K. Heller-Uszynska, and E. Deomano. 2010. Simultaneously accounting for population structure, genotype by environment interaction, and spatial variation in marker–trait associations in sugarcane. Genome 53: 973–981.

    Google Scholar 

  • Wu, K.K., W. Burnquist, M.E. Sorrells, T.L. Tew, P.H. Moore, and S.D. Tanksley. 1992. The detection and estimation of linkage in polyploids using single-dose restriction fragments. Theoretical and Applied Genetics 83(3): 294–300.

    CAS  Google Scholar 

  • Yadav, S., P. Jackson, X. Wei, E.M. Ross, K. Aitken, E. Deomano, F. Atkin, B.J. Hayes, and K.P. Voss-Fels. 2020. Accelerating genetic gain in sugarcane breeding using genomic selection. Agronomy 10(4): 585.

    CAS  Google Scholar 

  • Yang, X., Z. Luo, J. Todd, S. Sood, and J. Wang. 2018. Genome-wide association study of multiple yield components in a diversity panel of polyploid sugarcane (Saccharum spp.). BioRxiv 387001.

  • Yu, J., and E.S. Buckler. 2006. Genetic association mapping and genome organization of maize. Current Opinion in Biotechnology 17(2): 155–160.

    CAS  Google Scholar 

  • Yu, J., G. Pressoir, W.H. Briggs, I.V. Bi, M. Yamasaki, J.F. Doebley, M.D. McMullen, B.S. Gaut, D.M. Nielsen, J.B. Holland, and S. Kresovich. 2006. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics 38(2): 203–208.

    CAS  Google Scholar 

  • Zhao, K., C.W. Tung, G.C. Eizenga, M.H. Wright, M.L. Ali, A.H. Price, G.J. Norton, M.F. Islam, A. Reynolds, J. Mezey, A.M. McClung, C.D. Bustamante, and S.R. McCouch. 2011. Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nature Communications 27: 467.

    Google Scholar 

  • Zhu, C., M. Gore, E.S. Buckler, and J. Yu. 2008. Status and prospects of association mapping in plants. Plant Genome 1(1): 5–20.

    CAS  Google Scholar 

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Acknowledgements

This work was funded by research Grants from Department of Science and Technology, New Delhi to NB (Woman Scientist Scheme) and SK (SERB Research Project). Authors are grateful to Dr. B.D. Singh, Emeritus Professor, School of Biotechnology, Banaras Hindu University, Varanasi for critical reading of the manuscript. Authors are also thankful to the Indian Council of Agricultural Research, New Delhi and Director, ICAR-Indian Institute of Sugarcane Research, Lucknow for providing infrastructure facilities.

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  1. Division of Crop Improvement, ICAR-Indian Institute of Sugarcane Research, Raibareli Road, P.O. Dilkusha, Lucknow, U.P., 226002, India

    Nandita Banerjee, M. Suhail Khan, M. Swapna & Sanjeev Kumar

  2. Division of Crop Science, Indian Council of Agricultural Research, Krishi Bhawan, New Delhi, 110001, India

    R. K. Singh

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  4. R. K. Singh
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  5. Sanjeev Kumar
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Contributions

SK, RKS conceived, designed and supervised this work. NB did the literature search and prepared the draft. MSK and MS edited the manuscript. All authors critically read and approved the final manuscript.

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Correspondence to Sanjeev Kumar.

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Table S1.

Software packages used for estimating linkage disequilibrium and association mapping (DOC 113 kb)

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Banerjee, N., Khan, M.S., Swapna, M. et al. Progress and Prospects of Association Mapping in Sugarcane (Saccharum Species Hybrid), a Complex Polyploid Crop. Sugar Tech 22, 939–953 (2020). https://doi.org/10.1007/s12355-020-00852-9

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