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Genetic diversity, population structure and marker trait associations for seed quality traits in cotton (Gossypium hirsutum)

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Abstract

Cottonseed contains 16% seed oil and 23% seed protein by weight. High levels of palmitic acid provides a degree of stability to the oil, while the presence of bound gossypol in proteins considerably changes their properties, including their biological value. This study uses genetic principles to identify genomic regions associated with seed oil, protein and fibre content in upland cotton cultivars. Cotton association mapping panel representing the US germplasm were genotyped using amplified fragment length polymorphism markers, yielding 234 polymorphic DNA fragments. Phenotypic analysis showed high genetic variability for the seed traits, seed oil range from 6.47–25.16%, protein from 1.85–28.45% and fibre content from 15.88–37.12%. There were negative correlations between seed oil and protein content. With reference to genetic diversity, the average estimate of F ST was 8.852 indicating a low level of genetic differentiation among subpopulations. The AMOVA test revealed that variation was 94% within and 6% among subpopulations. Bayesian population structure identified five subpopulations and was in agreement with their geographical distribution. Among the mixed models analysed, mixed linear model (MLM) identified 21 quantitative trait loci for lint percentage and seed quality traits, such as seed protein and oil. Establishing genetic diversity, population structure and marker trait associations for the seed quality traits could be valuable in understanding the genetic relationships and their utilization in breeding programmes.

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References

  • Abdurakhmonov I. Y., Kohel R. J., Yu J. Z., Pepper A. E., Abdullaev A. A., Kushanov F. N., et al. 2008 Molecular diversity and association mapping of fibre quality traits in exotic G. hirsutum L. germplasm. Genomics 92(6), 478–487.

    Article  Google Scholar 

  • Achleitner A., Nicholas A., Tinker Zechner E. and Buerstmayr H. 2008 Genetic diversity among oat varieties of worldwide origin and associations of AFLP markers with quantitative traits. Theor. Appl. Genet. 117 (7), 1041–1053.

    Article  CAS  PubMed  Google Scholar 

  • AOAC 1999 Official methods of analysis. 16th edition. Association of official analytical chemists, Washington, USA.

  • Badigannavar A. M., Myers G. O. and Jones D. C. 2012 Molecular diversity revealed by AFLP markers in upland cotton genotypes. J. Crop Improv. 26, 627–640.

    Article  CAS  Google Scholar 

  • Bert P. F., Jouan I., Tourvieille de Labrouhe D., Serre F., Philippon J., Nicolas J. and Vear P. 2003 Comparative genetic analysis of quantitative traits in sunflower (Helianthus annuus L.). 2. Characterization of QTL involved in developmental and agronomic traits. Theor. Appl. Genet. 107, 181–189.

    CAS  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

  • Chen Z. F., Zhang Z. W. and Cheng H. L. 1986 The analysis of upland cotton quality. Acta Agron. Sin. 12, 195–200.

    Google Scholar 

  • Chung J., Babka H. L., Graef G. L., Staswick P. E., Lee D. J., Cregan P. B., Shoemaker R. C. and Specht J. E. 2003 The seed protein, oil and yield QTL on soybean linkage group I. Crop Sci. 43, 1053–1067.

    Article  CAS  Google Scholar 

  • Dani R. G. and Kohel R. J. 1989 Maternal effects and genera tion mean analysis of seed-oil content in cotton (Gossypium hirsutum). Theor. Appl. Genet. 77, 569–575.

    Article  CAS  PubMed  Google Scholar 

  • Evanno G., Regnaut S. and Goudet J. 2005 Detecting the number of clusters of individuals using the software structure: a simulation study. Mol. Ecol. 14, 2611–2620.

    Article  CAS  PubMed  Google Scholar 

  • Excoffier L., Laval G. and Schneider S. 2005 Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evol. Bioinform. Online 1, 47–50.

    PubMed Central  CAS  Google Scholar 

  • Flint-Garcia S. A., Thuillet A. C., Yu J., Pressoir G., Romero S. M., Mitchell S. E., et al. 2005 Maize association population: a high resolution platform for quantitative trait locus dissection. Plant J. 44, 1054–1064.

    Article  CAS  PubMed  Google Scholar 

  • Gotmare V., Singh P., Mayee C. D., Deshpande V. and Bhagat C. 2004 Genetic variability for seed oil content and seed index in some wild species and perennial races of cotton. Plant Breed. 123, 207–208.

    Article  Google Scholar 

  • Gupta P., Rustgi S. and Kulwal P. 2005 Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Mol. Biol. 57(4), 461–485.

    Article  Google Scholar 

  • Gupta V., Mukhopadhyay A., Arumugam N., Sodhi Y. S., Pental D. and Pradhan A. K. 2004 Molecular tagging of erucic acid trait in oilseed mustard (Brassica juncea) by QTL mapping and single nucleotide polymorphisms in FAE1 gene. Theor. Appl. Genet. 108, 743–749.

    Article  CAS  PubMed  Google Scholar 

  • Hardy O. J. and Vekemans X. 2002 SPAGEDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol. Ecol. Notes 2, 618–620.

    Article  Google Scholar 

  • Heuzé V., Tran G., Bastianelli D., Hassoun P. and Lebas F. 2013 Cottonseed meal. Feedipedia.org. A programme by INRA, CIRAD, AFZ and FAO (http://www.feedipedia.org/node/550 http://www.feedipedia.org/node/550).

  • Hu X., Sullivan-Gilbert M., Gupta M. and Thompson S. A. 2006 Mapping of the loci controlling oleic and linolenic acid contents and development of fad2 and fad3 allele-specific markers in canola (Brassica napus L.) Theor. Appl. Genet. 113, 497–507.

    Article  CAS  PubMed  Google Scholar 

  • Kantartzi S. K. and Stewart J. M. 2008 Association analysis of fibre traits in Gossypium arboreum accessions. Plant Breed. 127, 173–179.

    Article  Google Scholar 

  • Kianian S. F., Egli M. A., Phillips R. L., Rines H. W., Somers D. A., Gengenbach B. G., et al. 1999 Association of a major groat oil content QTL and an acetyl-CoA carboxylase gene in oat. Theor. Appl. Genet. 98, 884–894.

    Article  CAS  Google Scholar 

  • Kohel R. J. 1978. Survey of G. hirsutum germplasm collections for seed oil percentage and seed characteristics. USDA-ARS Report. S-187.

  • Kohel R. J. and Cherry J. P. 1983 Variation of cottonseed quality with stratified harvests. Crop Sci. 23, 1119–1124.

    Article  CAS  Google Scholar 

  • Kohel R. J., Glueck J. and Rooney L. W. 1985 Comparison of cotton germplasm collections for seed protein content. Crop Sci. 25, 961–963.

    Article  Google Scholar 

  • Kumar S., Tamura K. and Nei M. 2004 MEGA4: integrated software for molecular evolutionary genetics analysis and sequence alignment. Brief Bioinform. 5, 150–163.

    Article  CAS  PubMed  Google Scholar 

  • Lacape J. M., Nguyen T. B., Thibivilliers S., Bojinov B., Courtois B., Cantrell R. G., et al. 2003 A combined RFLP–SSR–AFLP map of tetraploid cotton based on a Gossypium hirsutum × Gossypium barbadense backcross population. Genome 46, 612–626.

    Article  CAS  PubMed  Google Scholar 

  • Mansoor S. and Paterson A. H. 2012 Genomes for jeans: cotton genomics for engineering superior fibre. Trends Biotech. 30, 521–527.

    Article  CAS  Google Scholar 

  • Mert M., Akiscan Y. and Gencer O. 2004 Inheritance of oil and protein in some cotton generations. Asian J. Plant Sci. 3, 174–176.

    Article  Google Scholar 

  • Myers G. O., Baogong J., Akash M. W., Badigannavar A. M. and Saha S. 2009 Chromosomal assignment of AFLP markers in upland cotton (Gossypium hirsutum L.) Euphytica 165, 391–399.

    Article  Google Scholar 

  • Nei M. and Li W. H. 1979 Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci. USA 76, 5269–5273.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Panthee D. R., Pantalone V. R., West D. R., Saxton A. M. and Sams C. E. 2005 Quantitative trait loci for seed protein and oil concentration and seed size in soybean. Crop Sci. 45, 2015–2022.

    Article  CAS  Google Scholar 

  • Peakall R. and Smouse P. E. 2012 GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28, 2537–2539.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

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

    PubMed Central  CAS  PubMed  Google Scholar 

  • Rosenberg N., Pritchard J. K., Weber J. L., Cann H. and Kidd K. 2002 Genetic structure of human populations. Science 298, 2381–2385.

    Article  CAS  PubMed  Google Scholar 

  • SAS 2009 SAS Statistical Analysis Software for Windows 9.1.3. Cary, USA.

  • See D., Kanazin V., Kephart K. and Blake T. 2002 Mapping genes controlling variation in barley grain protein concentration. Crop Sci. 42, 680–685.

    Article  CAS  Google Scholar 

  • Singh M., Singh T. H. and Chahal G. S. 1985 Genetic analysis of some seed quality characters in Upland cotton (Gossypium hirsutum L.) Theor. Appl. Genet. 71, 126–128.

    Article  CAS  PubMed  Google Scholar 

  • Sneath P. H. A. and Sokal R. R. 1973 Numerical taxonomy: The principals and practice of numerical classification, pp. 573. Freeman, San Francisco, USA.

    Google Scholar 

  • Song X. and Tian-Zhen Z. 2007 Identification of quantitative trait loci controlling seed physical and nutrient traits in cotton. Seed Sci. Res. 17, 243–251.

    Article  CAS  Google Scholar 

  • Sun S. K., Chen J. H., Xian S. K. and Wei S. J. 1987 Study on the nutritional quality of cotton seeds. Sci. Agric. Sin. 5, 12–16.

    CAS  Google Scholar 

  • Tan Y. F., Sun M., Xing Y. Z., Hua J. P., Sun X. L., Zhang Q. F. and Corke H. 2001 Mapping quantitative trait loci for milling quality, protein content and color characteristics of rice using a recombinant inbred line population derived from an elite rice hybrid. Theor. Appl. Genet. 103, 1037–1045.

    Article  CAS  Google Scholar 

  • Tar’an B., Warkentin T., Somers D. J., Miranda D., Vandenberg A., Blade and Bing D 2004 Identification of quantitative trait loci for grain yield, seed protein concentration and maturity in field pea (Pisum sativum L.) Euphytica 136, 297–306.

    Article  Google Scholar 

  • Vos P., Hogers R., Bleeker M., Reijans M., Van de Lee T., Hornes M., et al. 1995 AFLP: A new technique for DNA fingerprinting. Nucl. Acids Res. 23, 4407–4414.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Wallace T. P., Bowman D., Campbell B. T., Chee P., Gutierrez O. A., Kohel R. J., et al. 2009 Status of the USA cotton germplasm collection and crop vulnerability. Genet. Resour. Crop Evol. 56, 507–532.

    Article  Google Scholar 

  • Weir B. S. 1996 Genetic data analysis II. Sinauer Associates, Sunderland, USA.

    Google Scholar 

  • Wright S. 1951 The genetical structure of populations. Ann. Eugen. 15, 323–354.

    Article  CAS  PubMed  Google Scholar 

  • Wu J., Jenkins J. N., McCarty J. C. and Thaxton P. 2009 Seed trait associations with Gossypium barbadense L. chromosomes/arms in a G. hirsutum L. background. Euphytica 167, 371– 380.

    Article  Google Scholar 

  • Ye Z. H., Lu Z. Z. and Zhu J. 2003 Genetic analysis for developmental behavior of some seed quality traits in Upland cotton (Gossypum hirsutum L.). Euphytica 129, 183– 191.

    Article  CAS  Google Scholar 

  • Yu J., Pressoir G., Briggs W. H., Vroh B. I., Yamasaki M., Doebley J. F., et al. 2006 A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet. 38, 203–208.

    Article  CAS  PubMed  Google Scholar 

  • Yu J., Zhang K., Li S., Yu S., Zhai H., Wu M., et al. 2012 Mapping quantitative trait loci for lint yield and fibre quality across environments in a Gossypium hirsutum × Gossypium barbadense backcross inbred line population. Theor. Appl. Genet. 126, 275–287.

    Article  PubMed  Google Scholar 

  • Zeng L., Meredith W. R. J., Gutiirrez O. A. and Boykin D. L. 2009 Identification of associations between SSR markers and fibre traits in an exotic germplasm derived from multiple crosses among Gossypium tetraploid species. Theor. Appl. Genet. 119(1), 93–103.

    Article  Google Scholar 

  • Zhao J. Y., Becker H. C., Zhang D. Q., Zhang Y. F. and Ecke W. 2006 Conditional QTL mapping of oil content in rapeseed with respect to protein content and traits related to plant development and grain yield. Theor. Appl. Genet. 113, 33– 38.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank the Department of Agricultural Chemistry, LSU, Baton Rouge for seed quality trait analysis and all the RBTN coordinators for providing phenotypic data. Financial support from Cotton Incorporated is highly appreciated.

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Correspondence to ASHOK BADIGANNAVAR.

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Badigannavar A. and Myers G. O. 2015 Genetic diversity, population structure and marker trait associations for seed quality traits in cotton (Gossypium hirsutum). J. Genet. 94, xx–xx

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BADIGANNAVAR, A., MYERS, G.O. Genetic diversity, population structure and marker trait associations for seed quality traits in cotton (Gossypium hirsutum). J Genet 94, 87–94 (2015). https://doi.org/10.1007/s12041-015-0489-x

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