Advertisement

Euphytica

, Volume 207, Issue 3, pp 527–549 | Cite as

Identification of quantitative trait loci controlling sucrose content based on an enriched genetic linkage map of sugarcane (Saccharum spp. hybrids) cultivar ‘LCP 85-384’

  • Pingwu Liu
  • Amaresh Chandra
  • Youxiong Que
  • Ping-Hua Chen
  • Michael P. Grisham
  • William H. White
  • Caleb D. Dalley
  • Thomas L. Tew
  • Yong-Bao Pan
Article

Abstract

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.

Keywords

Genetic linkage map Molecular marker Quantitative trait loci (QTL) Sucrose content Sugarcane 

Notes

Acknowledgments

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.

Authors’ contributions

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

Competing interests

The authors declare that they have no competing interests.

Disclaimer

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.

References

  1. Aitken KS, Jackson PA, McIntyre CL (2005) A combination of AFLP and SSR markers provide extensive map coverage and identification of homo(eo)logous linkage groups in a sugarcane cultivar. Theor Appl Genet 110:789–801PubMedCrossRefGoogle Scholar
  2. Aitken KS, Jackson PA, McIntyre CL (2006) Quantitative trait loci identified for sugar related traits in a sugarcane (Saccharum spp.) cultivar × Saccharum officinarum population. Theor Appl Genet 112:1306–1317PubMedCrossRefGoogle Scholar
  3. Aitken KS, Jackson PA, McIntyre CL (2007) Construction of genetic linkage map for Saccharum officinarum incorporating both simplex and duplex markers to increase genome coverage. Genome 50:742–756PubMedCrossRefGoogle Scholar
  4. Alwala S, Suman A, Arro JA, Veremis JC, Kimbeng CA (2006) Target region amplification polymorphism (TRAP) for assessing genetic diversity in sugarcane germplasm collections. Crop Sci 46:448–455CrossRefGoogle Scholar
  5. Alwala S, Kimbeng CA, Veremis JC, Gravois KA (2008) Linkage mapping and genome analysis in Saccharum interspecific cross using AFLP, SRAP and TRAP markers. Euphytica 164:37–51CrossRefGoogle Scholar
  6. Alwala S, Kimbeng CA, Veremis JC, Gravois KA (2009) Identification of molecular markers associated with sugar-related traits in a Saccharum interspecific cross. Euphytica 167:127–142CrossRefGoogle Scholar
  7. Asnaghi C, Paulet F, Kaye C, Grivet L, Deu M, Glaszmann JC, D’Hont A (2000) Application of synteny across Poaceae to determine the map location of a sugarcane rust resistance gene. Theor Appl Genet 101:962–969CrossRefGoogle Scholar
  8. Asnaghi C, Roques D, Ruffel S, Kaye C, Hoarau JY, Te‘lismart H, Girard JC, Raboin LM, Risterucci AM, Grivet L, D’Hont A (2004) Targeted mapping of a sugarcane rust resistance gene (Bru1) using bulked segregant analysis and AFLP markers. Theor Appl Genet 108:759–764PubMedCrossRefGoogle Scholar
  9. 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
  10. Cheng XM, Xu JS, Xia S, Gu JX, Yang Y, Fu J, Qian XJ, Zhang SC, Wu JS, Liu K (2009) Development and genetic mapping of microsatellite markers from genome survey sequences in Brassica napus. Theor Appl Genet 118:1121–1131PubMedCrossRefGoogle Scholar
  11. Cordeiro GM, Taylor GO, Henry RJ (2000) Characterisation of microsatellite markers from sugarcane (Saccharum spp.), a highly polyploid species. Plant Sci 155:161–168PubMedCrossRefGoogle Scholar
  12. 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
  13. D’Hont A, Ison D, Alix K, Roux C, Glaszmann G (1998) Determination of basic chromosome numbers in the genus Saccharum by physical mapping of ribosomal RNA genes. Genome 41:221–225CrossRefGoogle Scholar
  14. Da Silva JAG (2001) Preliminary analysis of microsatellite markers derived from sugarcane expressed sequence tags (ESTs). Genet Mol Biol 24:155–159CrossRefGoogle Scholar
  15. Daugrois JH, Grivet L, Grivet L, Roques D, Hoarau JY, Lombard H, Glaszmann JC, D’Hont A (1996) Putative major gene for rust resistance linked with a RFLP marker in sugarcane cultivar ‘R570’. Theor Appl Genet 92:1059–1064PubMedCrossRefGoogle Scholar
  16. Dufour P, Grivet L, D’Hont A, Deu M, Trouche G, Glaszmann JC, Hamon P (1996) Comparative genetic mapping between duplicated segments on maize chromosomes 3 and 8 and homoeologous regions in sorghum and sugarcane. Theor Appl Genet 92:1024–1030PubMedCrossRefGoogle Scholar
  17. Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics. Longman Group, HarlowGoogle Scholar
  18. 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
  19. Gravois KA, Bischoff KP (2008) New sugarcane varieties to the rescue. La Agric 51:14–16Google Scholar
  20. Grivet L, D’Hont A, Roques D, Feldmann P, Lanaud C, Glaszmann JC (1996) RFLP mapping in a highly polyploid and aneuploid interspecific hybrid. Genetics 142:987–1000PubMedPubMedCentralGoogle Scholar
  21. Guimaráes CT, Sills GR, Sobral BWS (1997) Comparative mapping of Andropogoneae: Saccharum (sugarcane) and its relation to sorghum and maize. Proc Natl Acad Sci USA 94:14261–14266PubMedPubMedCentralCrossRefGoogle Scholar
  22. Hoarau JY, Offmann B, D’Hont A, Risterucci AM, Roques D, Glaszmann JC, Grivet L (2001) Genetic dissection of a modern sugarcane cultivar (Saccharum spp.). I. Genome mapping with AFLP markers. Theor Appl Genet 103:84–97CrossRefGoogle Scholar
  23. Hoarau JY, Grivet L, Offmann B, Raboin LM, Diorflar JP, Payet J, Hellmann M, D’Hont A, Glaszmann JC (2002) Genetic dissection of a modern sugarcane cultivar (Saccharum spp.). II. Detection of QTLs for yield components. Theor Appl Genet 105:1027–1037PubMedCrossRefGoogle Scholar
  24. Jackson PA (2005) Breeding for improved sugar content in sugarcane. Field Crops Res 92:277–290CrossRefGoogle Scholar
  25. Kosambi DD (1944) The estimation of map distances from recombination values. Ann Eugen 12:172–175CrossRefGoogle Scholar
  26. Lakshmanan P, Geijskes RJ, Aitken KS, Grof CLP, Bonnet GD, Smith GR (2005) Sugarcane biotechnology: the challenges and opportunities. In Vitro Cell Dev Biol Plant 41:345–363CrossRefGoogle Scholar
  27. Legendre BL, Henderson MT (1972) The history and development of sugar yield calculations. J Am Soc Sugar Cane Technol 2:10–18Google Scholar
  28. Liu P, Que Y, Pan Y-B (2011) Highly polymorphic microsatellite DNA markers for sugarcane germplasm evaluation and variety identity testing. Sugar Tech 13:129–136CrossRefGoogle Scholar
  29. Lowe A, Moule C, Trick M, Edwards K (2004) Efficient large-scale development of microsatellites for marker and mapping applications in Brassica crop species. Theor Appl Genet 108:1103–1112PubMedCrossRefGoogle Scholar
  30. 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
  31. Ming R, Liu SC, Moore PH, Irvine JE, Paterson AH (2001) QTL analysis in a complex autopolyploid: genetic control of sugar content in sugarcane. Genome Res 11:2075–2084PubMedPubMedCentralCrossRefGoogle Scholar
  32. Ming R, Liu S-C, Bowers JE, Moore PH, Irvine JE, Paterson AH (2002a) Construction of Saccharum consensus genetic map from two interspecific crosses. Crop Sci 42:570–583CrossRefGoogle Scholar
  33. Ming R, Wang YW, Draye X, Moore PH, Irvine JE, Paterson AH (2002b) Molecular dissection of complex traits in autopolyploids: mapping QTLs affecting sugar yield and related traits in sugarcane. Theor Appl Genet 105:332–345PubMedCrossRefGoogle Scholar
  34. Oliveira KM, Pinto LR, Marconi TG, Margarido GRA, Pastina MM, Teixeira LHM, Figueira AV, Ulian EC, Garcia AAF, Souza AP (2007) Functional integrated genetic linkage map based on EST markers for a sugarcane (Saccharum spp.) commercial cross. Mol Breed 20:189–208CrossRefGoogle Scholar
  35. Oliveira KM, Pinto LR, Marconi TG, Mollinari M, Ulian EC, Chabregas SM, Falco MC, Burnquist WA, Garcia AF, Souza AP (2009) Characterization of new polymorphic functional markers for sugarcane. Genome 52:191–209PubMedCrossRefGoogle Scholar
  36. Pan Y-B (2006) Highly polymorphic microsatellite DNA markers for sugarcane germplasm evaluation and variety identity testing. Sugar Tech 8:246–256CrossRefGoogle Scholar
  37. Pan Y-B, Burner DM, Legendre BL (2000) An assessment of the phylogenetic relationship among sugarcane and related taxa based on the nucleotide sequence of 5S rRNA intergenic spacers. Genetica 108:285–295PubMedCrossRefGoogle Scholar
  38. 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
  39. 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
  40. Parida SK, Kalia SK, Kaul S, Dalal V, Hemprapha G, Selvi A, Pandit A, Singh A, Gaikwad K, Sharma TR, Srivastava PS, Singh NK, Mohapatra T (2009) Informative genomic microsatellite markers for efficient genotyping application in sugarcane. Theor Appl Genet 118:327–338PubMedCrossRefGoogle Scholar
  41. Parida SK, Pandit A, Gaikwad K, Sharma TR, Srivastava PS, Singh NK, Mohapatra T (2010) Functionally relevant microsatellites in sugarcane unigenes. BMC Plant Biol 10:251PubMedPubMedCentralCrossRefGoogle Scholar
  42. 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
  43. Piperidis N, Jackson PA, D’Hont A, Besse P, Hoarau JY, Courtois B, Aitken KS, McIntyre CL (2008) Comparative genetics in sugarcane enables structured map enhancement and validation of marker-trait associations. Mol Breed 21:233–247CrossRefGoogle Scholar
  44. Piquemal J, Cinquin E, Couton F (2005) Construction of an oilseed rape (Brassica napus L.) genetic map with SSR markers. Theor Appl Genet 111:1514–1523PubMedCrossRefGoogle Scholar
  45. Podlich DW, Winkler CR, Cooper M (2004) Mapping as you go: an effective approach for marker-assisted selection of complex traits. Crop Sci 44:1560–1571CrossRefGoogle Scholar
  46. Ripol MI, Churchill GA, da Silva JAG, Sorrells M (1999) Statistical aspects of genetic mapping in autopolyploids. Gene 235:31–41PubMedCrossRefGoogle Scholar
  47. SAS Institute Inc (2008) SAS/STAT_ 9.2 user’s guide. SAS Institute Inc, CaryGoogle Scholar
  48. Schon C, Utz HF, Groh S, Truberg B, Openshaw S, Melchinger AE (2004) Quantitative trait locus mapping based on re-sampling in a vast maize testcross experiment and its relevance to quantitative genetics for complex traits. Genetics 167:485–498PubMedPubMedCentralCrossRefGoogle Scholar
  49. Singh RK, Srivastava S, Singh SP, Sharma ML, Mohopatra T, Singh NK, Singh SB (2008) Identification of new microsatellite DNA markers for sugar and related traits in sugarcane. Sugar Tech 10:327–333CrossRefGoogle Scholar
  50. Singh RK, Singh SP, Tiwari DK, Srivastava S, Singh SB, Sharma ML, Singh R, Mohopatra T, Singh NK (2013) Genetic mapping and QTL analysis for sugar yield-related traits in sugarcane. Euphytica 191:333–353CrossRefGoogle Scholar
  51. Sokal RR, Rohlf FJ (1995) Biometry. W.H. Freeman and Co, New YorkGoogle Scholar
  52. Suman A, Pan Y-B, Thongthawee S, Burner DM, Kimbeng C (2011) Genetic analysis of the sugarcane (Saccharum spp.) cultivar ‘LCP 85-384’. I. Linkage mapping using AFLP, SSR, and TRAP markers. Theor Appl Genet 123:77–93CrossRefGoogle Scholar
  53. Van Ooijen JW (2006) JoinMap®4, Software for the calculation of genetic linkage maps in experimental populations. Kyazma B. V., WageningenGoogle Scholar
  54. Yang J, Hu CC, Hu H, Yu RD, Xia Z, Ye XZ, Zhu J (2008) QTLNetwork: mapping and visualizing genetic architecture of complex traits in experimental populations. Bioinformatics 24:721–723PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht (outside the USA) 2015

Authors and Affiliations

  • Pingwu Liu
    • 1
    • 2
  • Amaresh Chandra
    • 1
    • 3
  • Youxiong Que
    • 4
  • Ping-Hua Chen
    • 4
  • Michael P. Grisham
    • 1
  • William H. White
    • 1
  • Caleb D. Dalley
    • 1
  • Thomas L. Tew
    • 1
  • Yong-Bao Pan
    • 1
  1. 1.USDA-ARS, MSASugarcane Research LaboratoryHoumaUSA
  2. 2.State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Collaborative Innovation Center of Sugar Industry in GuangxiGuangxi UniversityNanningChina
  3. 3.ICAR-Indian Institute of Sugarcane ResearchLucknowIndia
  4. 4.Key Lab of Sugarcane Biology and Genetic Breeding, Ministry of AgricultureFujian Agriculture and Forestry UniversityFuzhouChina

Personalised recommendations