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Genetic diversity in sorghum mini-core and elite rainy and post-rainy genotypes of India

Published online by Cambridge University Press:  15 January 2016

Kuyyamudi Nanaiah Ganapathy ,
Sujay Rakshit ,
Sunil Shriram Gomashe ,
Suri Audilakshmi ,
Krishna Hariprasanna  and
Jagannath Vishnu Patil
Kuyyamudi Nanaiah Ganapathy
Affiliation:
Indian Institute of Millets Research, Rajendranagar, Hyderabad500 030, India
Sujay Rakshit*
Affiliation:
Indian Institute of Millets Research, Rajendranagar, Hyderabad500 030, India
Sunil Shriram Gomashe
Affiliation:
Indian Institute of Millets Research, Rajendranagar, Hyderabad500 030, India
Suri Audilakshmi
Affiliation:
Indian Institute of Millets Research, Rajendranagar, Hyderabad500 030, India
Krishna Hariprasanna
Affiliation:
Indian Institute of Millets Research, Rajendranagar, Hyderabad500 030, India
Jagannath Vishnu Patil
Affiliation:
Indian Institute of Millets Research, Rajendranagar, Hyderabad500 030, India
*
*Corresponding author. E-mail: sujay@millets.res.in
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Abstract

Knowledge on genetic diversity is necessary to determine the relationships among the genotypes, which allow the selection of individual accessions for crop breeding programmes. The present study aimed at assessing the extent and pattern of genetic diversity within a set of 251 sorghum genotypes using SSR markers. A total of 393 alleles were detected from the 251 genotypes, with the number of alleles ranging from 2 (Xcup11) to 24 (Sb5-206) and an average of 10.07 alleles per primer pair. Pairwise Wright's FST statistic and Nei's genetic distance estimates revealed that the race and geographical origin were responsible for the pattern of diversity and structure in the genetic materials. In addition, the analysis also revealed high genetic differentiation between the rainy and post-rainy sorghum groups. Narrow diversity was observed among the different working groups in the rainy (restorers and varieties) and post-rainy (varieties and advanced breeding lines) sorghum groups. Neighbour-joining and STRUCTURE analysis also classified 44 elite lines broadly into two distinct groups (rainy and post-rainy). However, limited diversity within the rainy and post-rainy sorghum groups warranted an urgent need for the utilization of diverse germplasm accessions for broadening the genetic base of the Indian breeding programme. The diverse germplasm accessions identified from the mini-core accessions for utilization in breeding programmes are discussed.

Keywords

genetic structuremini-corepost-rainyrainysorghumSSR markers
Type
Research Article
Information
Plant Genetic Resources , Volume 15 , Issue 2 , April 2017 , pp. 127 - 137
Copyright
Copyright © NIAB 2016 

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References

Adugna, A (2014) Analysis of in situ diversity and population structure in Ethiopian cultivated Sorghum bicolor (L.) landraces using phenotypic traits and SSR markers. SpringerPlus 3: 212.Google Scholar
Agrama, HA and Tuinstra, MR (2003) Phylogenetic diversity and relationships among sorghum accessions using SSRs and RAPDs. African Journal of Biotechnology 2: 334–340.Google Scholar
Anas and Yoshida, T (2004) Sorghum diversity evaluated by simple sequence repeat (SSR) markers and phenotypic performance. Plant Production Science 7: 301–308.Google Scholar
Andrews DJ, Ejeta G, Gilbert M, Goswami P, Anand Kumar K, Maunder AB, Porter K, Rai KN, Rajewski JF, Reddy BVS, Stegmeier W and Talukdar BS (1997) Breeding hybrid parents. In Proceedings of an International Conference on the Genetic Improvement of Sorghum and Pearl Millet, held at Lubbock, Texas, 22–27 September 1996. International Sorghum and Millet Research (INTSORMIL) – International Crops Research Institute for the Semi-arid Tropics (ICRISAT), pp 173–187.Google Scholar
Aruna, C and Audilakshmi, S (2008) A strategy to identify potential germplasm for improving yield attributes using diversity analysis in sorghum. Plant Genetic Resources: Characterization and Utilization 6: 187–194.Google Scholar
Audilakshmi, S, Aruna, C and Kiran, VVS (2003) Utilization of germplasm for improvement of varieties in India. In: Report of AICSIP, AICSIP Annual Meeting of the Sorghum Group, 1–3 April. Surat, Gujarat: Sorghum Research Station (GAU), pp. 47–53..Google Scholar
Bhosale, SU, Stich, B, Rattunde, HF, Weltzien, E, Haussmann, BI, Hash, CT, Melchinger, AE and Parzies, HK (2011) Population structure in sorghum accessions from West Africa differing in race and maturity class. Genetica 139: 453–463.Google Scholar
Botstein, D, White, RL, Skolnick, M and Davis, RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics 32: 314–331.Google Scholar
Dahlberg, JA, Zhag, X, Hart, GE and Mullet, JE (2002) Comparative assessment of variation among sorghum germplasm accessions using seed morphology and RAPD measurements. Crop Science 42: 291–296.Google Scholar
Deu, M, Sagnard, F, Chantereau, J, Calatayud, C, Herault, D, Mariac, C, Pham, JL, Vigouroux, Y, Kapran, L, Traore, PS, Mamadou, A, Gerard, B, Ndjeunga, J and Bezancon, G (2008) Niger-wide assessment of in situ sorghum genetic diversity with microsatellite markers. Theoretical and Applied Genetics 116: 903–913.Google Scholar
de Wet, JMJ (1977) Domestication of African cereals. African Economic History 3: 15–32.Google Scholar
de Wet, JMJ and Harlan, JR (1971) The origin and domestication of Sorghum bicolor . Economic Botany 25: 128–135.Google Scholar
Dje, Y, Heuertz, M, Lefebvre, C and Vekemans, X (2000) Assessment of genetic diversity within and among germplasm accessions in cultivated sorghum using microsatellite markers. Theoretical and Applied Genetics 100: 918–925.Google Scholar
Doggett, H (1970) Sorghum (Tropical Agriculture Series). London: Longmans.Google Scholar
Earl, DA and vonHoldt, BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetic Resources 4: 359–361.CrossRefGoogle Scholar
Evanno, G, Regnaut, S and Goudet, J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology 14: 2611–2620.Google Scholar
Falush, D, Stephens, M and Pritchard, JK (2007) Inference of population structure using multilocus genotype data: dominant markers and null alleles. Molecular Ecology Notes 7: 574–578.Google Scholar
Fernandez, L, de Haro, LA, Distefano, AJ, Martinez, MC, Lia, V, Papa, JC, Olea, I, Tosto, D and Hopp, HE (2013) Population genetics structure of glyphosate-resistant Johnsongrass (Sorghum halepense L. Pers) does not support a single origin of the resistance. Ecology and Evolution 3: 3388–3400.Google Scholar
Folkertsma, RT, Rattunde, HF, Chandra, S, Raju, GS and Hash, CT (2005) The pattern of genetic diversity of Guinea-race Sorghum bicolor (L.) Moench landraces as revealed with SSR markers. Theoretical and Applied Genetics 111: 399–409.Google Scholar
Ganapathy, KN, Gomashe, SS, Rakshit, S, Prabhakar, B, Ambekar, SS, Ghorade, RB, Biradar, BD, Saxena, U and Patil, JV (2012) Genetic diversity revealed utility of SSR markers in classifying parental lines and elite genotypes of sorghum (Sorghum bicolor L. Moench). Australian Journal of Crop Science 6: 1486–1493.Google Scholar
Ghebru, B, Schmidt, J and Bennetzen, L (2002) Genetic diversity of Eritrean sorghum landraces assessed with simple sequence repeat (SSR) markers. Theoretical and Applied Genetics 105: 229–236.Google Scholar
Harlan, JR and de Wet, JMJ (1972) A simplified classification of cultivated sorghum. Crop Science 12: 172–176.Google Scholar
Hartl, DL and Clark, AG (1997) Principles of population genetics, 3rd edn. Sunderland: Sinauer Associates, Inc. Publishers.Google Scholar
Huang, Y (2004) Evaluation of genetic diversity in sorghum germplasm using molecular markers. International Plant & Animal Genome XII Conference, San Diego, CA. Poster 265, p. 138..Google Scholar
Lekgari, A and Dweikat, I (2014) Assessment of genetic variability of 142 sweet sorghum germplasm of diverse origin with molecular and morphological markers. Open Journal of Ecology 4: 371–393.Google Scholar
Liu, K and Muse, SV (2005) PowerMarker: An Integrated Analysis Environment for Genetic Marker Analysis. Raleigh, NC: Bioinformatics Research Center, North Carolina State University.Google Scholar
Morris, GP, Ramu, P, Deshpande, SP, Hash, CT, Shah, T, Upadhyaya, HD, Riera-Lizarazu, O, Brown, PJ, Acharya, CB, Mitchell, SE, Harriman, J, Glaubitz, JC, Buckler, ES and Kresovich, S (2013) Population genomic and genome-wide association studies of agro-climatic traits in sorghum. Proceedings of National Academy of Science, USA 110: 453–458.Google Scholar
Muraya, MM, Mutegi, E, Geiger, HH, de Villiers, SM, Sagnard, F, Kanyenji, BM, Kiambi, D and Parzies, HK (2011) Wild sorghum from different eco-geographic regions of Kenya display a mixed mating system. Theoretical and Applied Genetics 122: 1631–1639.Google Scholar
Nei, M (1973) The theory and estimation of genetic distance. In: Morton, NE (ed.) Genetic Structure of Populations. Honolulu: University Press of Hawaii, pp. 45–54.Google Scholar
Perrier, X and Jacquemoud-Collet, JP (2006) DARwin software. Available at http://www.darwin.cirad.fr/darwin.Google Scholar
Pritchard, JK, Stephens, M and Donnelly, P (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945–959.Google Scholar
Rakshit, S, Gomashe, SS, Ganapathy, KN, Elangovan, M, Ratnavathi, CV, Seetharama, N and Patil, JV (2012) Morphological and molecular diversity reveal wide variability among sorghum Maldandi landraces from India. Journal of Plant Biochemistry and Biotechnology 21: 145–156.Google Scholar
Ramu, P, Billot, C, Rami, JF, Senthilvel, S, Upadhyaya, HD, Ananda Reddy, L and Hash, CT (2013) Assessment of genetic diversity in the sorghum reference set using EST-SSR markers. Theoretical and Applied Genetics 126: 2051–2064.Google Scholar
Reddy, BVS and Prasada Rao, KE (1993) Varietal improvement: genetic diversification. Cereals Program, ICRISAT Annual Report 1992. Patancheru: ICRISAT, pp. 48–51.Google Scholar
Reddy, BVS, Reddy, PS, Sadananda, AR, Dinakaran, E, Ashok Kumar, A, Deshpande, SP, Srinivasa Rao, P, Sharma, HC, Sharma, R, Krishnamurthy, L and Patil, JV (2012) Postrainy season sorghum: constraints and breeding approaches. Journal of SAT Agricultural Research 10: 1–12.Google Scholar
Rooney, WL and Smith, CA (2000) Techniques for developing new cultivars. In: Smith, CW and Frederiken, RA (eds) Sorghum: Origin, History, Technology and Production. New York: Wiley, pp. 329–347.Google Scholar
Sajjanar, GM, Biradar, BD and Biradar, SS (2011) Evaluation of crosses involving rabi landraces of sorghum for productivity traits. Karnataka Journal of Agricultural Sciences 24: 227–229.Google Scholar
Sharma, R, Upadhyaya, HD, Manjunatha, SV, Rao, VP and Thakur, RP (2013) Resistance to foliar diseases in a mini-core collection of sorghum germplasm. Plant Disease 96: 1629–1633.Google Scholar
Smith, CW and Frederiksen, RA (2000) Sorghum: Origin, History, Technology, and Production. New York: John Wiley and Sons, p. 824.Google Scholar
Thudi, M and Fakrudin, B (2011) Identification of unique alleles and assessment of genetic diversity of rabi sorghum accessions using simple sequence repeat markers. Journal of Plant Biochemistry and Biotechnology 20: 74–83.Google Scholar
Upadhyaya, HD, Yadav, D, Dronavalli, N, Gowda, CLL and Singh, S (2010) Mini core germplasm collections for infusing genetic diversity in plant breeding programs. Electronic Journal of Plant Breeding 1: 1294–1309.Google Scholar
Upadhyaya, HD, Pundir, RPS, Dwivedi, SL, Gowda, CLL, Reddy, VG and Singh, S (2009) Developing a mini core collection of sorghum for diversified utilization of germplasm. Crop Science 49: 1769–1780.Google Scholar
Upadhyaya, HD, Wang, YH, Gowda, CL and Sharma, S (2013 a) Association mapping of maturity and plant height using SNP markers with the sorghum mini core collection. Theoretical and Applied Genetics 126: 2003–2015.Google Scholar
Upadhyaya, HD, Wang, YH, Sharma, R and Sharma, S (2013 b) SNP markers linked to leaf rust and grain mold resistance in sorghum. Molecular Breeding 32: 451–462.Google Scholar
Upadhyaya, HD, Wang, YH, Sharma, R and Sharma, S (2013 c) Identification of genetic markers linked to anthracnose resistance in sorghum using association analysis. Theoretical and Applied Genetics 126: 1649–1657.Google Scholar
Wang, YH, Upadhyaya, HD, Burrell, AM, Sahraeian, SME, Klein, RR and Klein, PE (2013 a) Genetic structure and linkage disequilibrium in a diverse, representative collection of the C4 model plant, Sorghum bicolor . G3: Genes Genomics Genetics 3: 783–793.Google Scholar
Wang, L, Jiao, S, Jiang, Y, Yan, H, Su, D, Sun, G, Yan, X and Sun, L (2013 b) Genetic diversity in parent lines of sweet sorghum based on agronomical traits and SSR markers. Field Crops Research 149: 11–19.Google Scholar
Weir, BS (1996) Genetic Data Analysis II. Sunderland, MA: Sinauer.Google Scholar
Weir, BS and Hill, WG (2002) Estimating F-statistics. Annual Review of Genetics 36: 721–750.Google Scholar
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