Advertisement

Theoretical and Applied Genetics

, Volume 116, Issue 4, pp 541–553 | Cite as

Marker-assisted selection for early-season cold tolerance in sorghum: QTL validation across populations and environments

  • Joseph Knoll
  • Gebisa Ejeta
Original Paper

Abstract

Sorghum [Sorghum bicolor (L.) Moench] landraces from China generally exhibit excellent emergence and seedling vigor under cool conditions, and are being used as sources of genes for improvement of seedling cold tolerance in other cultivars. Marker-assisted selection (MAS) could expedite the introgression of genes from landraces into elite lines, however, only a few studies have empirically demonstrated efficacy of MAS for quantitatively inherited agronomic traits. In a preceding study we identified quantitative trait loci (QTL) for early-season performance in a recombinant inbred (RI) population, one parent of which was a cold-tolerant Chinese line, ‘Shan Qui Red’ (SQR). In this study, three SSR markers (Xtxp43, Xtxp51, and Xtxp211), each representing a QTL, were tested in two new populations: (Tx2794 × SQR F3) and (Wheatland × SQR BC1F3). Individual families were genotyped, and early-season field performance was measured for two years. Statistical analyses showed that the SQR allele of Xtxp43 had favorable effects on seedling vigor in both populations, and on emergence in the Tx2794 population. A large positive effect of the SQR allele of Xtxp51 was observed in the Tx2794 population for vigor and emergence. Slight genotype by environment interaction was observed for Xtxp51 in the Wheatland population. Marker Xtxp211 had small but significant effects on seedling vigor and emergence in both populations. Various interactions between loci were also significant. This study validated QTL markers in various genetic backgrounds, and demonstrated the utility of MAS for a quantitative trait, early-season cold tolerance, evaluated in the field.

Keywords

Quantitative Trait Locus Sorghum Simple Sequence Repeat Marker Recombinant Inbred Stand Biomass 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We are grateful for the assistance provided by several colleagues. Terry Lemming assisted in planting and grain harvesting. Matthew Erlich, Joe Johnstone, Erica Hoenie, Tina Suen, and Zenbaba Gutema assisted with emergence counts, biomass measurements, and grain harvest and threshing. Funding for this project was provided by International Sorghum and Millets (INTSORMIL)-USAID Grant # DAN254-G-00-002.

References

  1. Ayoub M, Mather DE (2002) Effectiveness of selective genotyping for detection of quantitative trait loci: an analysis of grain and malt quality traits in three barley populations. Genome 45:1116–1124PubMedCrossRefGoogle Scholar
  2. Bhattramakki D, Dong J, Chhabra AK, Hart GE (2000) An integrated SSR and RFLP linkage map of Sorghum bicolor (L.) Moench. Genome 43:988–1002PubMedCrossRefGoogle Scholar
  3. Cisse N, Ejeta G (2003) Genetic variation and relationships among seedling vigor traits in sorghum. Crop Sci 43:824–828CrossRefGoogle Scholar
  4. Conover WJ (1999) Practical nonparametric statistics, 3rd edn. Wiley, New YorkGoogle Scholar
  5. Darvasi A, Soller M (1994) Selective DNA pooling for determination of linkage between a molecular marker and a quantitative trait locus. Genetics 138:1365–1373PubMedGoogle Scholar
  6. Doggett H (1988) Sorghum, 2nd edn. Wiley, New YorkGoogle Scholar
  7. Dudley JW (1993) Molecular markers in plant improvement: manipulation of genes affecting quantitative traits. Crop Sci 33:660–668CrossRefGoogle Scholar
  8. FAO (2004) Food and Agriculture Organization of the United Nations, Statistics Division. http://www.fao.org/es/ess/index_en.asp. (Cited 12 Sept. 2006)
  9. Foolad MR, Zhang LP, Lin GY (2001) Identification and validation of QTLs for salt tolerance during vegetative growth in tomato by selective genotyping. Genome 44:444–454PubMedCrossRefGoogle Scholar
  10. Haussmann BIG, Mahalakshmi V, Reddy BVS, Seetharama N, Hash CT, Geiger HH (2002) QTL mapping of stay-green in two sorghum recombinant inbred populations. Theor Appl Genet 106:133–142PubMedGoogle Scholar
  11. Held PG (2001a) Nucleic acid and protein quantitation in the microplate format. CHIMIA 55:40–42Google Scholar
  12. Held PG (2001b) Quantification of DNA using Hoescht 33258. Bio-Tek Instruments, Inc., Winooski. http://biotek.com/products/tech_res_detail.php?id=39 (Cited Feb 2006)
  13. Kim J-S, Klein PE, Klein RR, Price HJ, Mullet JE, Stelly DM (2005) Chromosome identification and nomenclature of Sorghum bicolor. Genetics 169:1169–1173PubMedCrossRefGoogle Scholar
  14. Knoll JE, Gunaratna N, Ejeta G (2007) QTL analysis of early-season cold tolerance in sorghum. Theor Appl Genet (in review)Google Scholar
  15. Kong L, Dong J, Hart G (2000) Characteristics, linkage-map positions, and allelic differentiation of Sorghum bicolor (L.) Moench DNA simple-sequence repeats (SSRs). Theor Appl Genet 101:438–448CrossRefGoogle Scholar
  16. Lander ES, Botstein D (1989) Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185–199PubMedGoogle Scholar
  17. Maiti RK, Raju PS, Bidinger FR (1981) Evaluation of visual scoring for seedling vigor in sorghum. Seed Sci Technol 9:613–622Google Scholar
  18. Mansouri H, Chang G-H (1995) A comparative study of some rank tests for interaction. Comput Stat Data An 19:85–96CrossRefGoogle Scholar
  19. Michelmore RW, Paran L, Kesseli RV (1991) Identification of markers linked to disease-resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions by using segregating populations. Proc Natl Acad Sci USA 88:9828–9832PubMedCrossRefGoogle Scholar
  20. Micic Z, Hahn V, Bauer E, Melchinger AE, Knapp SJ, Tang S, Schön CC (2005) Identification and validation of QTL for Sclerotinia midstalk rot resistance in sunflower by selective genotyping. Theor Appl Genet 111:233–242PubMedCrossRefGoogle Scholar
  21. Osborn TC, Alexander DC, Fobes JF (1987) Identification of restriction fragment length polymorphisms linked to genes controlling soluble solids content in tomato fruit. Theor Appl Genet 73:350–356CrossRefGoogle Scholar
  22. SAS Institute (2003) SAS for windows, Version 9.1. SAS Inst. Inc., CaryGoogle Scholar
  23. Singh SP (1985) Sources of cold tolerance in grain sorghum. Can J Plant Sci 65:251–257CrossRefGoogle Scholar
  24. Stewart CN, Via LE (1993) A rapid CTAB DNA isolation technique useful for RAPD fingerprinting and other PCR applications. Biotechniques 14(5):748–749PubMedGoogle Scholar
  25. Tanksley SD, Hewitt J (1988) Use of molecular markers in breeding for soluble solids content in tomato—a re-examination. Theor Appl Genet 75:811–823CrossRefGoogle Scholar
  26. Yousef GG, Juvik JA (2002) Enhancement of seedling emergence in sweet corn by marker-assisted backcrossing of beneficial QTL. Crop Sci 42:96–104PubMedCrossRefGoogle Scholar
  27. Zeng Z (1993) Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proc Natl Acad Sci USA 90:10972–10976PubMedCrossRefGoogle Scholar
  28. Zeng Z (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468PubMedGoogle Scholar
  29. Zhou W-C, Kolb FL, Bai G-H, Domier LL, Boze LK, Smith NJ (2003) Validation of a major QTL for scab resistance with SSR markers and use of marker-assisted selection in wheat. Plant Breeding 122:40–46CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  1. 1.Department of AgronomyPurdue UniversityWest LafayetteUSA

Personalised recommendations