Hostname: page-component-8448b6f56d-t5pn6 Total loading time: 0 Render date: 2024-04-15T14:16:54.366Z Has data issue: false hasContentIssue false

Inheritance and mapping of drought tolerance in soybean at seedling stage using bulked segregant analysis

Published online by Cambridge University Press:  19 February 2020

V. Sreenivasa*
Affiliation:
Division of crop Improvement, ICAR-Sugarcane Breeding institute, Coimbatore, India
S. K. Lal
Affiliation:
Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
P. Kiran Babu
Affiliation:
Division of Plant Genetic Resources, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
H. K. Mahadeva Swamy
Affiliation:
Division of crop Improvement, ICAR-Sugarcane Breeding institute, Coimbatore, India
Raju R. Yadav
Affiliation:
Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
A. Talukdar
Affiliation:
Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
Darasing R. Rathod
Affiliation:
Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
*
*Corresponding author. E-mail: seenugpb@gmail.com

Abstract

Occurrence of drought under rainfed conditions is the foremost factor responsible for yield reduction in soybean. Developing soybean cultivars with an inherent ability to withstand drought would immensely benefit the soybean production in rainfed areas. In the present study, F2 derived mapping populations were developed by crossing drought tolerant (PK 1180, SL 46) and susceptible (UPSL 298, PK 1169) genotypes to investigate the inheritance of seedling survival drought mechanisms and to identify simple-sequence repeat (SSR) markers associated with them, using bulked segregant analysis. Parents as well as a F2 derived mapping population were screened for drought tolerance based on seedling survivability under controlled conditions. Segregation analysis of F2 population derived from a cross between PK 1180 × UPSL 298 was previously shown to have a 3:1 tolerant to susceptible ratio and a probability of 0.61 at a χ2(3:1) value of 0.258. This was confirmed in another F2 population derived from a cross between PK 1169 × SL 46 with a χ2(3:1) value of 0.145 obtained at a probability of 0.70. One SSR marker Satt277 showed polymorphism between contracting bulks (tolerant and susceptible) out of 50 polymorphic markers identified during parental polymorphism. Single marker analysis suggested that the marker, Satt277 is linked to seedling survival drought tolerance and is located on chromosome linkage group C2 (chr 6) with a map distance of 3.40 cM. The tolerant genotypes identified could be used as a donor in soybean improvement programs. The marker identified can be used in marker-assisted selection while screening large collection of germplasm.

Type
Research Article
Copyright
Copyright © NIAB 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ahuja, I, de Vos, RC, Bones, AM and Hall, RD (2010) Plant molecular stress responses face climate change. Trends in Plant Sciences 15: 664674.CrossRefGoogle ScholarPubMed
Ali, A, Ali, Z and Quraishi, UM (2014) Integrating physiological and genetic approaches for improving drought tolerance in crops. In: Ahmad, P and Rasool, S (ed.) Emerging Technologies and Management of Crop Stress Tolerance. UK: Elsevier’s Science & Technology, pp. 315345. DOI: 10.1016/B978-0-12- 800875-1.00014-4.CrossRefGoogle Scholar
Altinkut, A and Gozukirmizi, N (2003) Search for microsatellites associated with water stress tolerance in wheat through bulked segregant analysis. Molecular Biotechnology 23: 97106. https://doi.org/10.1385/MB:23:2:97 .CrossRefGoogle ScholarPubMed
Basal, H, Smith, CW, Thaxton, PS and Hemphill, JK (2005) Seedling drought tolerance in upland cotton. Crop Science 45: 766771. http://doi:org/10.2135/cropsci2005.0766.CrossRefGoogle Scholar
Bukhari, SFH, Arshad, S and Azooz, MM (2015) Omics approaches and abiotic stress tolerance in legumes. In: Azooz, MM and Ahmad, P (ed.) Legumes Under Environmental Stress: Yield, Improvement and Adaptations. New Jersey: John Wiley & Sons, pp. 120. DOI: 10.1002/9781118917091.ch13.Google Scholar
Cabello, JV, Lodeyro, AF and Zurbriggen, MD (2014) Novel perspectives for the engineering of abiotic stress tolerance in plants. Current Opinion in Biotechnology 26: 6270.CrossRefGoogle ScholarPubMed
Collard, BCY and Mackill, DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty first century. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 363: 557572. doi: 10.1098/rstb.2007.2170.CrossRefGoogle ScholarPubMed
Deshmukh, RK, Sonah, H, Patil, G, Chen, W, Prince, S, Mutava, R, Vuong, T, Valliyodan, B and Nguyen, HT (2014) Integrating omic approaches for abiotic stress tolerance in soybean. Frontiers in Plant Science 5: 244.CrossRefGoogle Scholar
Dias, FG, Borges, ACN, Viana, AAB, Mesquita, RO, Romano, E, Grossi-de-Sa, MF, Nepomuceno, AL, Loureiro, ME and Ferreira, MA (2012) Expression analysis in response to drought stress in soybean: shedding light on the regulation of metabolic pathway genes. Genetics and Molecular Biology 35: 222232. http://dx.doi.org/10.1590/S1415-47572012000200004.CrossRefGoogle Scholar
Dubey, A, Malla, MA and Khan, F (2019) Soil microbiome: a key player for conservation of soil health under changing climate. Biodiversity and Conservation 28: 24052429. DOI: 10.1007/s10531-019-01760-5.CrossRefGoogle Scholar
El-Kadi, DA, Afiah, SA, Aly, MA and Badran, AE (2006) Bulked segregant analysis to develop molecular markers for salt tolerance in Egyptian cotton. Arab Journal of Biotechnology 9: 129142.Google Scholar
Foyer, CH, Lam, HM, Nguyen, HT, Siddique, KHM, Varshney, RK, Colmer, TD, Cowling, W, Bramley, H, Mori, TA, Hodgson, JM, Cooper, JW, Miller, AJ, Kunert, K, Vorster, J, Cullis, C, Ozga, JA, Wahlqvist, ML, Liang, Y, Shou, H, Shi, K, Yu, J, Fodor, N, Kaiser, BN, Wong, FL, Valliyodan, B and Considine, MJ (2016) Neglecting legumes has compromised human health and sustainable food production. Nature Plants 2: 16112 http://dx.doi.org/10.1038/nplants.2016.112.CrossRefGoogle ScholarPubMed
Gutierrez-Gonzalez, JJ, Guttikonda, SK, Tran, LS, Aldrich, DL, Zhong, R, Yu, O, Nguyen, HT and Sleper, DA (2010) Differential expression of isoflavone biosynthetic genes in soybean during water deficits. Plant Cell Physiology 51(6): 936948. PMID:20430761.CrossRefGoogle ScholarPubMed
Hameed, A, Goher, M and Iqbal, N (2010) Evaluation of seedling survivability and growth response as selection criteria for breeding drought tolerance in wheat. Cereal Research Communication 38: 193202. https://doi.org/10.1556/CRC.38.2010.2.5, http://www.plantstress.com/Articles/index.asp, https://www.soybase.org/cmap/cgibin/cmap/viewer?ref_map_set_aid=GmComposite2003_;refmap_aids=GmComposite2003_A1;comparative_maps=1%3Dmap_aid%3DGmGWAS_A;data_source=sbt_cmap.CrossRefGoogle Scholar
Hyten, DL, Smith, JR, Frederick, RD, Tucker, ML, Song, Q and Cregan, PB (2009) Bulked segregant analysis using the golden gate assay to locate the Rpp3 locus that confers resistance to soybean rust in soybean. Crop Science 49: 265271. https://doi.org/10.2135/cropsci2008.08.0511.CrossRefGoogle Scholar
Kanagaraj, P, Prince, KSJ, Sheeba, JA, Biji, KR, Paul, SB, Senthil, A and Babu, RC (2010) Microsatellite markers linked to drought resistance in rice (Oryza sativa L.). Current Science 98: 836839.Google Scholar
Kim, EH, Ro, HM, Kim, SL, Kim, HS and Chung, IM (2012) Analysis of isoflavone, phenolic, soyasapogenol and tocopherol compounds in soybean [Glycine max (L.) Merrill] germplasms of different seed weights and origins. Journal of Agricultural and Food Chemistry 60: 60456055.CrossRefGoogle Scholar
Longenverger, ES, Smith, CW, Thaxton, PS and McMichael, BL (2006) Development of a screening method for drought tolerance in cotton seedlings. Crop Science 46: 21042110.CrossRefGoogle Scholar
Manavalan, LP, Guttikonda, SK, Tran, LP and Nguyen, HT (2009) Physiological and molecular approaches to improve drought resistance in soybean. Plant Cell Physiology 50: 12601276. http://doi:10.1093/pcp/pcp082.CrossRefGoogle Scholar
Michelmore, RW, Paran, I and 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. Proceedings of National Academy of Sciences USA 88: 98289832. http://DOI:10.1073/pnas.88.21.9828.CrossRefGoogle ScholarPubMed
Monneyeux, P and Belhassen, E (1996) The diversity of drought adaptation in the wide. Plant Growth Regulation 20: 8592. https://doi.org/10.1007/BF00024004.CrossRefGoogle Scholar
Morgan, JM (1991) A gene controlling differences in osmoregulation in wheat. Australian Journal of Plant Physiology 18: 249257. https://doi.org/10.1071/PP9910249.Google Scholar
Muchero, W, Ehlers, JD, Close, TJ and Roberts, PA (2009) Mapping QTL for drought stress-induced premature senescence and maturity in cowpea (Vigna unguiculata (L.) Walp). Theory and Applied Genetics 118: 849863. http://DOI:10.1007/s00122-008-0944-7.CrossRefGoogle Scholar
Munoz, N, Li, MW and Ngai, SM (2016) Use of proteomics to evaluate soybean response under abiotic stresses. In: Miransari, M (ed.) Abiotic and Biotic Stresses in Soybean Production. UK: Elsevier’s Science & Technology, pp 79105. DOI: 10.1016/B978-0-12-801536-0.00004-9.CrossRefGoogle Scholar
Nayak, SN, Zhu, H and Varghese, N (2010) Integration of novel SSR and gene-based SNP marker loci in the chickpea genetic map and establishment of new anchor points with Medicago truncatula genome. Theory and Applied Genetics 120: 14151441. https://doi.org/10.1007/s00122-010-1265-1.CrossRefGoogle ScholarPubMed
Oya, T, Alexandre, LN, Norman, N, Jose, RBF, Satoshi, T and Osamu, I (2004) Drought tolerance characteristics of Brazilian soybean cultivars: evaluation and characterization of drought tolerance of various Brazilian soybean cultivars in the field. Plant Production Science 7: 129137. https://doi.org/10.1626/pps.7.129.CrossRefGoogle Scholar
Quarrie, S, Lazic-jancic, V, Kovacevic, D, Steed, A and Pekic, S (1999) Bulk segregant analysis with molecular markers and its use for improving drought resistance in maize. Journal of Experimental Botany 50: 12991306. https://doi.org/10.1093/jxb/50.337.1299.CrossRefGoogle Scholar
Saghai-Maroof, MA, Soliman, KM, Jorgensen, RA and Allard, RW (1984) Ribosomal DNA spacer-length polymorphisms in barley: mendelian inheritance, chromosomal location, and population dynamics. Proceedings of the National Academy of Sciences of the United States of America 81: 80148018. http://DOI:10.1073/pnas.81.24.8014.CrossRefGoogle ScholarPubMed
Salunkhe, AS, Poornima, R, Prince, SKJ, Kanagaraj, P, Sheeba, JA, Amudha, K, Suji, KK, Senthil, A and Babu, RC (2011) Fine mapping QTL for drought resistance traits in rice (Oryza sativa L.) using bulk segregant analysis. Molecular Biotechnology 49: 9095. http://doi:10.1007/s12033-011-9382-x.CrossRefGoogle ScholarPubMed
Sholihin, HDM (2002) Molecular mapping of drought resistance in mungbean (Vigna Radiate L. Wilczek): 2 QTL linked to drought resistance. Jurnal Bioteknologi Pertanian 7: 5561.Google Scholar
Sinclair, TR (2011) Challenges in breeding for yield increase for drought. Trends in plant science 16: 289293. http://doi:10.1016/j.tplants.2011.02.008.CrossRefGoogle ScholarPubMed
Singh, BB, Mai-Kodomi, Y and Terao, T (1999) A simple screening method for drought tolerance in cowpea. The Indian Journal of Genetics and Plant Breeding 59: 211220.Google Scholar
Singh, D, Dikshit, HK and Singh, R (2013) A new phenotyping technique for screening for drought tolerance in lentil (Lens culinaris Medik). Plant Breeding 132: 185190. https://doi.org/10.1111/pbr.12033.CrossRefGoogle Scholar
Singh, D, Singh, CK, Taunk, S and Tomar, RSS (2016) Genetic analysis and molecular mapping of seedling survival drought tolerance gene in lentil (Lens culinaris Medik). Molecular Breeding 36: 58 DOI 10.1007/s11032-016-0474-y.CrossRefGoogle Scholar
Song, L, Prince, S, Valliyodan, B, Joshi, T, Maldonado dos Santos, JV, Wang, J, Lin Stamatoyannopoulos, J, Bailey, T, Noble, W, Livak, K, Schmittgen, T, Rozen, S and Skaletsky, H (2016) Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions. BMC Genomics 17: 117. http://dx.doi.org/10.1186/s12864-016-2378-y.CrossRefGoogle ScholarPubMed
Specht, JE, Hume, DJ and Kumudini, SV (1999) Soybean yield potential – a genetic and physiological perspective. Crop Science 39: 15601570.CrossRefGoogle Scholar
Sugiyama, A, Ueda, Y, Takase, H and Yazaki, K (2015) Do soybeans select specific species of bradyrhizobium during growth? Communicative & Integrative Biology 8: e992734.CrossRefGoogle ScholarPubMed
Tomar, SMS and Kumar, GT (2004) Seedling survivability as a selection criterion for drought tolerance in wheat. Molecular Breeding 123: 392394. https://doi.org/10.1111/j.1439-0523.2004.00993.x.Google Scholar
Ullah, FMQ, Jun, MS and Kyong, LJ (2018) Bulk segregant analysis (BSA) for the improvement of drought resistance in Maize (Zea Mays L.) inbred lines as revealed by SSR molecular markers. Research Journal of Biotechnology 13: 3451.Google Scholar
USDA (2018) World Agricultural Production. Foreign Agricultural Service/USDA. https://apps.fas.usda.gov/psdonline/circulars/production.pdf.Google Scholar
Venuprasad, R, Dalid, CO, Del Valle, M, Zhao, D, Espiritu, M and Sta Cruz, MT (2009) Identification and characterization of large-effect quantitative trait loci for grain yield under lowland drought stress in rice using bulk-segregant analysis. Theory and Applied Genetics 120: 177190. http://doi:10.1007/s00122-009-1168-1.CrossRefGoogle ScholarPubMed
Vikram, P, Swamy, BPM, Dixit, S, Sta Cruz, MT, Ahmed, HU, Singh, AK and Kumar, A (2011) qDTY1.1, a major QTL for rice grain yield under reproductive-stage drought stress with a consistent effect in multiple elite genetic backgrounds. BMC Genetics 12: 89.CrossRefGoogle Scholar
Vikram, P, Kumar, A, Singh, AK and Singh, NK (2012) Rice: genomics-assisted breeding for drought tolerance. In: Tuteja, N, Gill, SS, Tiburico, AF and Tuteja, R (eds). Improving Crop Resistance to Abiotic Stress. Germany: Wiley-VCH Verlag GmbH & Co. KGaA, pp. 715731.CrossRefGoogle Scholar
Wang, X, Sakata, K and Komatsu, S (2018) An integrated approach of proteomics and computational genetic modification effectiveness analysis to uncover the mechanisms of flood tolerance in soybeans. International Journal of Molecular Sciences 19: 1301. DOI: 10.3390/ijms19051301.CrossRefGoogle ScholarPubMed
Watanabe, S, Chikaharu, TC, Oshita, T, Yamada, T, Anai, T and Kaga, A (2017) Identification of quantitative trait loci for flowering time by a combination of restriction site associated DNA sequencing and bulked segregant analysis in soybean. Breeding Science 67: 277285. http://doi:10.1270/jsbbs.17013.CrossRefGoogle Scholar
Supplementary material: File

Sreenivasa et al. supplementary material

Sreenivasa et al. supplementary material

Download Sreenivasa et al. supplementary material(File)
File 578 KB