Identification of quantitative trait loci controlling sucrose content based on an enriched genetic linkage map of sugarcane (Saccharum spp. hybrids) cultivar ‘LCP 85-384’
- 376 Downloads
Sucrose content is one of the most important traits considered in sugarcane breeding. Since sugarcane cultivars possess >100 chromosomes (2n = 100–130) and are genetically complex polyploid and aneuploids, identification of quantitative trait loci (QTLs) associated with sucrose content is considered the best option to improve sucrose content through molecular breeding. A preliminary genetic linkage map of Louisiana sugarcane cultivar ‘LCP 85-384’ from a previous study was enriched using 65 additional polymorphism simple-sequence-repeats (SSR) primer-pairs to identify more co-segregated and homologous groups (CGs and HGs) and QTLs controlling sucrose content. Eighty-four SSR primer-pairs produced 456 markers, of which 441 were polymorphic. Both simplex (993) and duplex (225) amplified fragment length polymorphism (AFLP) and target region amplification polymorphism (TRAP) markers reported previously were also included to construct the LCP 85-384 map. These simplex and duplex markers were assigned to 108 CGs successfully using JoinMap®. This map had a cumulative genome length of 7406.3 cM that included 675 AFLP (69.8 %), 90 TRAP (9.3 %), and 202 SSR (20.9 %) markers. The 202 SSR markers were assigned to 65 CGs and 8 HGs. Based on this map, 24 putative QTLs affecting sucrose content were identified. Five QTLs were unlinked and the other 19 QTLs were located on nine CGs within four HGs. Of these QTLs, 11 had an effect in both plant-cane (20.33 %) and first-stubble (25.68 %) crops. A higher efficiency of QTLs’ identification with AFLP, TRAP and SSR markers in such a genetically complex crop, proposes its wider utility in molecular breeding in sugarcane.
KeywordsGenetic linkage map Molecular marker Quantitative trait loci (QTL) Sucrose content Sugarcane
AFLP and TRAP marker data were kindly provided by Collins Kimbeng and Suman Andru. This research was partially funded by grower/processor check-off funds administrated by the American Sugar Cane League of the USA., Inc., Thibodaux, Louisiana, USA. Greenhouse and field technical supports were provided by Jennifer Chiasson, Elta Duet, Brian Duet, Cory Landry, Lionel Lomax, Jeri Maggio, Norris Matherne, Eric Petrie, Clinton Randall, Randy Richard, David Verdun, and Kathy Warnke. SSR-PCR and ABI3730XL-based fragment analysis were conducted by Sheron Simpson at the USDA-ARS, MSA Genomics Laboratory directed by Brian Scheffler. Amaresh Chandra gratefully acknowledges Department of Biotechnology, Government of India for DBT-CREST Fellowship Award.
YBP conceived, designed and directed the study. PL, YQ and YBP collected SSR marker data. PL analyzed the molecular and phenotypic data, constructed the genetic and QTL map, and drafted the manuscript. AC performed phenotypic data analysis, interpreted the data, and participated in manuscript preparation. PHC, MPG, CDD, TLT, WHW, and YBP conducted field trials and collected phenotypic data. PL, AC, YQ, MPG, and YBP participated in manuscript preparation. All authors have read and approved the final manuscript.
Compliance with ethical standards
The authors declare that they have no competing interests.
Product names and trademarks are mentioned to report factually on available data; however, the USDA neither guarantees nor warrants the standard of the product, and the use of the name by USDA does not imply the approval of the product to the exclusion of others that may also be suitable. The experiments reported comply with the current laws of USA.
- Bischoff KP, Gravois KA (2004) The development of new sugarcane varieties at the LSU Ag Center. J Am Soc Sugar Cane Technol 24:142–164Google Scholar
- Cunff LL, Garsmeur O, Raboin LM, Pauquet J, Telismart H, Selvi A, Grivet L, Philippe R, Begum D, Deu M, Costet L, Wing R, Glaszmann JC, D’Hont A (2008) Diploid/polyploidy syntenic shuttle mapping and haplotype-specific chromosome walking toward a rust resistance gene (Bru1) in highly polyploidy sugarcane (2n 12 × 115). Genetics 180:649–660PubMedPubMedCentralCrossRefGoogle Scholar
- Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics. Longman Group, HarlowGoogle Scholar
- Garcia AAF, Kido EA, Meza AN, Souza HMB, Pinto LR, Pastina MM, Leite CS, Da Silva JAG, Ulian EC, Figueira A, Souza AP (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. Theor Appl Genet 112:298–314PubMedCrossRefGoogle Scholar
- Gravois KA, Bischoff KP (2008) New sugarcane varieties to the rescue. La Agric 51:14–16Google Scholar
- Legendre BL, Henderson MT (1972) The history and development of sugar yield calculations. J Am Soc Sugar Cane Technol 2:10–18Google Scholar
- Ming R, Liu SC, Lin YR, Da Silva JAG, Wilson W, Braga D, van Devnze A, Wenslaff F, 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 150:1663–1682PubMedPubMedCentralGoogle Scholar
- Pan Y-B, Cordeiro GM, Richard EP Jr, Henry RJ (2003) Molecular genotyping of sugarcane clones with microsatellite DNA markers. Maydica 48:319–329Google Scholar
- Pan Y-B, Scheffler BS, Richard EP Jr (2007) High throughput genotyping of commercial sugarcane clones with microsatellite (SSR) DNA markers. Sugar Tech 9:176–181Google Scholar
- Pinto LR, Garcia AAF, Pastina MM, Teixeira LHM, Bressiani JA, Ulian EC, Bidoia MAP, Souza AP (2010) Analysis of genomic and functional RFLP derived markers associated with sucrose content, fiber and yield QTLs in a sugarcane (Saccharum spp.) commercial cross. Euphytica 172:313–327CrossRefGoogle Scholar
- SAS Institute Inc (2008) SAS/STAT_ 9.2 user’s guide. SAS Institute Inc, CaryGoogle Scholar
- Sokal RR, Rohlf FJ (1995) Biometry. W.H. Freeman and Co, New YorkGoogle Scholar
- Van Ooijen JW (2006) JoinMap®4, Software for the calculation of genetic linkage maps in experimental populations. Kyazma B. V., WageningenGoogle Scholar