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Diversity and marker association in tropical silkworm breeds of Bombyx mori (Lepidoptera: Bombycidae)

Published online by Cambridge University Press:  28 September 2011

P.P. Srivastava*
Affiliation:
Seribiotech Research Laboratory, Central Silk Board, Carmelram Post, Kodathi, Bangalore560 035, Karnataka, India Central Silk Board, Madivala, Bangalore560 068, Karnataka, India
K. Vijayan
Affiliation:
Central Silk Board, Madivala, Bangalore560 068, Karnataka, India
P.K. Kar
Affiliation:
Central Tasar Research and Training Institute, Piska Nagari, Ranchi835 303, Jharkhand, India
B. Saratchandra
Affiliation:
Central Silk Board, Madivala, Bangalore560 068, Karnataka, India
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Abstract

Inter simple sequence repeats (ISSR) and random amplified DNA polymorphism (RAPD) markers were used to estimate the genetic diversity among 14 tropical silkworm races (Bombyx mori L.) for identifying potential parents to be used for hybrid preparation for commercial exploitation. High polymorphism (70.91 and 74.70%) was revealed by ISSR and RAPD markers. The dendrograms generated, using unweighted pair group method using arithmetic average from these markers, grouped the 14 silkworm races into two major groups, which corroborates the differences in cocoon characteristics. Discriminant function analysis of ISSR and RAPD markers identified three functions for cocoon weight and two functions for shell weights, respectively. Step-wise multiple regression analysis identified six ISSR markers (834500, 8841700, 8841850, 8271500, 8401500 and 7891250) and seven RAPD markers (834500, 885900, 8101400, 884900, 8361500, 7891250 and 7621700) significantly associated with cocoon and shell weights. The genetically divergent parents, identified through this study, can be used for the preparation of hybrids for commercial utilization. Similarly, the DNA markers identified can be utilized for marker-assisted selection along with those identified through quantitative trait locus mapping by others. Thus the information generated in this study is useful in silkworm breeding programmes in the tropical sericulture industry.

Type
Research Paper
Copyright
Copyright © ICIPE 2011

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References

Awasthi, A. K., Kar, P. K., Srivastava, P. P., Rawat, N., Vijayan, K., Pradeep, A. R. and Urs, S. R. (2008) Molecular evaluation of bivoltine, polyvoltine and mutant silkworm (Bombyx mori L.) with RAPD, ISSR and RFLP-STS markers. Indian Journal of Biotechnology 7, 188194.Google Scholar
Bovenhuis, H., van Arendonk, J. A. M., Davis, G., Elsen, J. M., Haley, C. S., Hill, W. G., Baret, P. V., Hetzel, D. J. S. and Nicholas, F. W. (1997) Detection and mapping of quantitative trait loci in farm animals. Livestock Production Science 52, 135144.CrossRefGoogle Scholar
Chatterjee, S. N. and Mohandas, T. P. (2003) Identification of ISSR markers associated with productivity traits in silkworm, Bombyx mori L. Genome 46, 438447.CrossRefGoogle Scholar
Chatterjee, S. N. and Pradeep, A. R. (2003) Molecular markers (RAPD) associated with growth, yield and origin of the silkworm, Bombyx mori L. in India. Genetika 39, 16121624.Google ScholarPubMed
Chatterjee, S. N., Vijayan, K., Roy, G. C. and Nair, C. V. (2004) ISSR profiling of genetic variability in the ecotypes of Antheraea mylitta Drury, the tropical tasar silkworm. Russian Journal of Genetics 40, 152159.CrossRefGoogle ScholarPubMed
Fang, D. Q. and Roose, M. L. (1997) Identification of closely related citrus cultivars with inter-simple sequence repeats markers. Theoretical and Applied Genetics 95, 408417.CrossRefGoogle Scholar
Felsenstein, J. (1993) PHYLIP (Phylogeny Inference Package) Version 3.5c. Department of Genetics, University of Washington, Seattle.Google Scholar
Gaviria, D. A., Aguilar, E., Serrano, H. J. and Alegria, A. H. (2006) DNA fingerprinting using AFLP markers to search for markers associated with yield attributes in the silkworm, Bombyx mori. Journal of Insect Science 6, 15(www.insectscience.org/6.15 ).CrossRefGoogle ScholarPubMed
Gupta, P. K. and Varshney, R. K. (2000) The development and use of microsatellite markers for genetic analysis and plant breeding with emphasis on wheat. Euphatica 113, 5363.Google Scholar
Hoeschele, I., Ulimari, P., Grignola, F. E., Zangh, Q. and Cage, K. M. (1997) Advances in statistical methods to map quantitative trait loci in outbred populations. Genetics 147, 14451457.CrossRefGoogle ScholarPubMed
Kamble, C. K., Rao, P. R. M., Basavaraja, H. K., Joge, P. G., Premletha, V. and Nirmalkumar, S. (2007) Use of bivoltine foundation crosses as male parents in the preparation of F1 cross-breed seed. Indian Journal of Sericulture 46, 16.Google Scholar
Kar, P. K., Vijayan, K., Nair, C. V., Mohandas, T. P., Saratchandra, B. and Thangavelu, K. (2005) Genetic variability and genetic structure of wild and semi-domestic populations of tasar silkworm (Antheraea mylitta) ecorace Daba as revealed through ISSR markers. Genetica 125, 173183.CrossRefGoogle Scholar
Kumaresan, P., Sinha, R. K., Mohan, B. and Thangavelu, K. (2004) Conservation of multivoltine silkworm (Bombyx mori L.) germplasm in India: an overview. International Journal of Industrial Entomology 9, 113.Google Scholar
Lie, Z., Cheng, L., Fang-yin, D. and Shou-min, F. (2010) Mapping of major quantitative trait loci for economic traits of silkworm cocoon. Genetics and Molecular Research 9, 7888.CrossRefGoogle ScholarPubMed
Lu, C., Li, B., Zhao, A. and Xiang, Z. (2004) QTL mapping of economically important traits in silkworm (Bombyx mori). Science in China, Series-C Life Science 47, 477484.CrossRefGoogle ScholarPubMed
Mahalanobis, P. C. (1936) On the generalized distance in statistics. Proceedings of the National Academy of Science (Calcutta) 2, 4955.Google Scholar
Mahendran, B., Padhi, B. K., Ghosh, S. K. and Kundu, S. C. (2006) Genetic variation in ecoraces of tropical tasar silkworm, Antheraea mylitta D. using RFLF technique. Current Science 90, 100103.Google Scholar
Mano, Y., Nirmalkumar, S., Basavaraja, H. K., Malreddy, N. and Datta, R. K. (1993) A new method to select promising silkworm breeds/combinations. Indian Silk 31, 53.Google Scholar
Mohandas, T. P., Sethuraman, B., Saratchandra, B. and Chatterjee, S. N. (2004) Molecular genetic approach for identifying markers associated with yield traits in silkworm, Bombyx mori using RFLP-STS primers. Genetica 122, 185197.Google ScholarPubMed
Nagaoka, T. and Ogihara, Y. (1997) Applicability of inter-simple sequence repeat polymorphism in wheat for use as DNA markers in comparison to RFLP and RAPD markers. Theoretical and Applied Genetics 94, 597602.CrossRefGoogle Scholar
Nagaraju, J. (2002) Application of genetic principles for improving silk production. Current Science 83, 409414.Google Scholar
Nei, M. and Li, W. (1979) Mathematical model for studying genetic variation in terms of restriction endonucleases. Proceedings of the National Academy of Sciences of the USA 74, 52675273.Google Scholar
Press, S. J. and Wilson, S. (1978) Choosing between logistic regression and discriminant analysis. Journal of the American Statistics Association 73, 699705.CrossRefGoogle Scholar
Rafalski, J. A., Tingey, S. V. and Williams, J. G. K. (1991) RAPD markers – a new technology for genetic mapping and plant breeding. Agriculture Biotechnology News and Information 3, 645648.Google Scholar
Reddy, K. D., Nagaraju, J. and Abraham, E. G. (1999) Genetic characterization of silkworm Bombyx mori by simple sequence repeat (SSR)-anchored PCR. Heredity 83, 681687.CrossRefGoogle ScholarPubMed
Roy, S. N. and Bargmann, R. E. (1958) Tests of multiple independence and the associated confidence bounds. The Annals of Mathematical Statistics 29, 491503.CrossRefGoogle Scholar
Sharma, A., Sharma, R. and Machii, H. (2000) Assessment of genetic diversity in a Morus germplasm collection using fluorescence-based AFLP markers. Theoretical and Applied Genetics 101, 10491055.CrossRefGoogle Scholar
Sneath, P. H. A. and Sokal, R. R. (1973) Numerical Taxonomy. W.H. Freeman, San Francisco. 573 pp.Google Scholar
Srivastava, P. P., Kar, P. K., Awasthi, A. K. and Urs, S. R. (2007) Identification and association of inter simple sequence repeat markers for thermal stress in polyvoltine silkworm Bombyx mori. Genetika 43, 858864.Google Scholar
Srivastava, P. P., Vijayan, K., Awasthi, A. K., Kar, P. K., Thangavelu, K. and Saratchandra, B. (2005) Genetic analysis of silkworms (Bombyx mori) through RAPD markers. Indian Journal of Biotechnology 4, 389395.Google Scholar
Vijayan, K. (2007) Molecular markers and their application in mulberry breeding. International Journal of Industrial Entomology 15, 145155.Google Scholar
Vijayan, K., Nair, C. V., Kar, P. K., Mohandas, T. P., Saratchandra, B. and Urs, S. R. (2005) Genetic variability within and among three ecoraces of the tasar silkworm Antheraea mylitta as revealed by ISSR and RAPD markers. International Journal of Industrial Entomology 10, 5159.Google Scholar
Vijayan, K., Nair, C. V. and Urs, S. R. (2010) Assessment of genetic diversity in the tropical mulberry silkworm (Bombyx mori L.) with mtDNA-SSCP and SSR markers. Emirates Journal of Food and Agriculture 22, 7183.CrossRefGoogle Scholar
Vijayan, K., Tikader, A., Kar, P. K., Srivastava, P. P., Awasthi, A. K., Thangavelu, K. and Saratchandra, B. (2006) Assessment of genetic relationships between wild and cultivated mulberry (Morus) species using PCR-based markers. Genetic Resources and Crop Evolution 53, 873882.CrossRefGoogle Scholar
Virk, P. S., Ford-Lloyd, B. V., Jackson, M. T., Pooni, H. S., Clemeno, T. P. and Newbury, H. J. (1996) Predicting quantitative variation within rice germplasm using molecular markers. Heredity 76, 296304.CrossRefGoogle Scholar
Xu, H. M., Wei, C. S., Tang, Y. T., Zhu, Z. H., Sima, Y. F. and Lou, X. Y. (2011) A new mapping method for quantitative trait loci of silkworm. BMC Genetics 12, 19. doi:10.1186/1471-2156-12-19.CrossRefGoogle ScholarPubMed