Hostname: page-component-848d4c4894-hfldf Total loading time: 0 Render date: 2024-05-18T10:33:08.066Z Has data issue: false hasContentIssue false

Genetic diversity and morpho-physiological assessment of drought tolerance in rapeseed (Brassica napus L.) cultivars

Published online by Cambridge University Press:  02 April 2024

Sara Motallebinia*
Affiliation:
Department of Agronomy and Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
Omid Sofalian
Affiliation:
Faculty of Agricultural and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
Ali Asghari
Affiliation:
Faculty of Agricultural and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
Ali Rasoulzadeh
Affiliation:
Faculty of Agricultural and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
Bahram Fathi Achachlouei
Affiliation:
Faculty of Agricultural and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
*
Corresponding author: Sara Motallebinia; Email: sara.motallebi.nia@gmail.com

Abstract

Water deficit is one of the most important abiotic stresses constraining crop production in rapeseed. Understanding the mechanisms of adaptation to this stress is essential for the development and production of drought-tolerant genotypes. For this reason, this research study aims to investigate the importance of genetic diversity in identifying genotypes with a high degree of drought tolerance through assessing effectiveness of inter simple sequence repeat (ISSR) markers on 14 genotypes of rapeseed in a factorial design. Morphological and physiological characteristics were studied after the early stages of growth; in order to evaluate the genetic diversity among genotypes, 18 different ISSR markers were used. A total of 106 clear and scalable loci were amplified, of which 60 bands (56.6%) were polymorphic. The highest polymorphism information content belonged to marker number 9 with the amount of 0.365 (85.7%). Gene variation ranged from 0.081 to 0.365 and the rapeseed genotypes were divided into three groups by cluster analysis (unweighted pair group method with arithmetic mean method). The analysis of molecular variance showed that 70% of the total variation was observed within populations and 30% of this variation occurred among populations. In addition, t-test was used for comparing oil content percentage among different genotypes in control and stress levels. Adriana had the highest amount of seed oil with 36.47%, whereas Karaj 2 had the lowest amount with 27.28 and Cooper had the highest decrease in oil content percentage under stress conditions. Overall, the genotypes Likord, Hyola 401 and Sarigol 32 were identified as the most drought-tolerant.

Type
Research Article
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press on behalf of National Institute of Agricultural Botany

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

Allen, RG, Pereira, LS, Raes, D and Smith, M (1998) Crop evapotranspiration guidelines for computing crop water requirements. FAO Irrigation and drainage paper 56. Food and Agriculture Organization, Rome.Google Scholar
Amiteye, S (2021) Basic concepts and methodologies of DNA marker systems in plant molecular breeding. Heliyon 7, e08093. doi: 10.1016/j.heliyon.2021.e08093CrossRefGoogle ScholarPubMed
Azadmard-Damirchi, S, Alirezalu, K and Fathi Achachlouei, B (2011) Microwave pretreatment of seeds to extract high quality vegetable oil. World Academy of Science, Engineering and Technology 57, 7275.Google Scholar
Bates, L, Waldren, R and Teare, I (1973) Rapid determination of free proline for water-stress studies. Plant and Soil 39, 205207.CrossRefGoogle Scholar
Batley, J, Hopkins, CJ and Cogan, NOI (2007) Identification and characterization of simple sequence repeat markers from Brassica napus expressed sequences. Molecular Ecology Notes 7, 886889.CrossRefGoogle Scholar
Bradford, MM (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of dye binding. Analytical Biochemistry 72, 248254.CrossRefGoogle ScholarPubMed
Cheng, X, Xu, J and Xia, S (2009) Development and genetic mapping of microsatellite markers from genome survey sequences in Brassica napus. Theoretical Applied Genetics 118, 11211131.CrossRefGoogle ScholarPubMed
Chesnokov, YV and Artemyeva, AM (2015) Evaluation of the measure of polymorphism information of genetic diversity. Agricultural Biology 50, 571578.Google Scholar
Cockram, J, Jones, H, Leigh, FJ, O'Sullivan, D, Powell, W, Laurie, DA and Greenland, AJ (2007) Control of flowering time in temperate cereals: genes, domestication, and sustainable productivity. Journal of Experimental Botany 58, 12311244.CrossRefGoogle ScholarPubMed
Collard, BC and Mackill, DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philosophical Transactions of the Royal Society B. Biological Sciences 363, 557572.CrossRefGoogle ScholarPubMed
Diallo, AO, Ali-Benali, MA, Badawi, M, Houde, M and Sarhan, F (2012) Expression of vernalization responsive genes in wheat is associated with histone H3 trimethylation. Molecular Genetics and Genomics 287, 575590.CrossRefGoogle ScholarPubMed
Diezel, C, Allmann, S and Baldwin, IT (2011) Mechanisms of optimal defense patterns in Nicotiana attenuata: flowering attenuates herbivory-elicited ethylene and jasmonate signaling. Journal of Integrative Plant Biology 53, 971983.CrossRefGoogle ScholarPubMed
Ebrahimi, S, Nikkhah, A and Sadeghi, A (2010) Changes in nutritive value and digestion kinetics of canola seed due to microwave irradiation. Asian-Australasian Journal of Animal Science 23, 347.CrossRefGoogle Scholar
FAO (2021) FAOSTAT. Rome, Italy. Available at www.fao.orgfaostaten%23dataQI.pdfGoogle Scholar
Faraji, A, Latifi, N, Soltani, A and Shirani Rad, AH (2009) Seed yield and water use efficiency of canola (Brassica napus L.) as affected by high temperature stress and supplemental irrigation. Agricultural Water Management 96, 132140.CrossRefGoogle Scholar
Godwin, ID, Aitken, EAB and Smith, LW (1997) Application of inter simple sequence repeat (ISSR) markers to plant genetics. Electrophoresis 18, 15241528.CrossRefGoogle ScholarPubMed
Govindaraj, M, Vetriventhan, M and Srinivasan, M (2015) Importance of genetic diversity assessment in crop plants and its recent advances: an overview of its analytical perspectives. Genetics Research International 2015, 114.CrossRefGoogle ScholarPubMed
Hasan, N, Choudhary, S, Naaz, N, Sharma, N and Laskar, RA (2021) Recent advancements in molecular marker-assisted selection and applications in plant breeding programmes. Journal of Genetic Engineering and Biotechnology 19, 128.CrossRefGoogle Scholar
Hashem, M, Sandhu, KS, Ismail, SM, Börner, A and Sallam, A (2023) Validation and marker-assisted selection of DArT-genomic regions associated with wheat yield-related traits under normal and drought conditions. Frontiers in Genetics 14, 1195566.CrossRefGoogle ScholarPubMed
Havlickova, L, Jozova, E, Rychla, A, Klima, M, Kucera, V and Curn, V (2014) Genetic diversity assessment in winter oilseed rape (Brassica napus L.) collection using AFLP, ISSR and SSR markers. Czech Journal of Genetics and Plant Breeding 50, 216225.CrossRefGoogle Scholar
Hegewald, H, Wensch-Dorendorf, M, Sieling, K and Christen, O (2018) Impacts of break crops and crop rotations on oilseed rape productivity: a review. European Journal of Agronomy 101, 6377.CrossRefGoogle Scholar
Irigoyen, J, Einerich, D and Sánchez-Díaz, M (1992) Water stress induced changes in concentrations of proline and total soluble sugars in nodulated alfalfa (Medicago sativa) plants. Physiologia Plantarum 84, 5560.CrossRefGoogle Scholar
Karimi, B and Vafaeezadeh, M (2012) SBA-15-functionalized sulfonic acid confined acidic ionic liquid: a powerful and water-tolerant catalyst for solvent-free esterifications. Chemical Communications 48, 33273329.CrossRefGoogle ScholarPubMed
Khan, MN, Siddiqui, MH, Mohammad, F, Khan, M and Naeem, M (2007) Salinity induced changes in growth, enzyme activities, photosynthesis, proline accumulation and yield in linseed genotypes. World Journal of Agricultural Sciences 3, 685695.Google Scholar
Khanna-Chopra, R and Singh, K (2015) Drought resistance in crops: physiological and genetic basis of traits for crop productivity. In Tripathi, BN and Müller, M (eds), Stress Responses in Plants: Mechanisms of Toxicity and Tolerance. New York, NY: Springer, pp. 267292.CrossRefGoogle Scholar
Koyro, HW (2006) Effect of salinity on growth, photosynthesis, water relations and solute composition of the potential cash crop halophyte Plantago coronopus (L.). Environmental and Experimental Botany 56, 136146.CrossRefGoogle Scholar
Lichtenthaler, HK (1987) Chlorophylls and carotenoids: pigments of photosynthetic biomembranes. Methods in Enzymology 148, 350382.CrossRefGoogle Scholar
Ling, AE, Kaur, J and Burgess, B (2007) Characterization of simple sequence repeat markers derived in silico from Brassica rapa bacterial artificial chromosome sequences and their application in Brassica napus. Molecular Ecology Notes 7, 273277.CrossRefGoogle Scholar
Nasibi, F, Manuchehri Kalantari, KH and Yaghoobi, MM (2011) Comparison the effects of sodium nitroprusside and arginine pretreatment on some physiological responses of tomato plant (Lycopersicun esculentum) under water stress. Iranian Journal of Biology 24, 833847 (in Persian).Google Scholar
Nasri, M, Khalatbari, M, Zahedi, H, Paknejad, F and Tohidi Moghadam, HR (2008) Evaluation of micro and macro elements in drought stress condition in cultivars of rapeseed (Brassica napus L.). American Journal of Agricultural and Biological Sciences 3, 579583.Google Scholar
Nei, M (1987) Molecular Evolutionary Genetics. New York, USA: Columbia University Press.CrossRefGoogle Scholar
Nemati, M, Asghari, A, Sofalian, O, Rasoulzadeh, A and Mohamaddoust Chamanabad, H (2012) Effect of water stress on rapeseed cultivars using morpho-physiological traits and their relations with ISSR markers. Journal of Plant Physiology & Breeding 2, 5566.Google Scholar
Parida, S, Pandit, A, Gaikwad, K, Sharma, T, Srivastava, P, Singh, N and Mohapatra, T (2010) Functionally relevant microsatellites in sugarcane unigenes. BMC Plant Biology 2010, 251.CrossRefGoogle Scholar
Piquemal, J, Cinquin, E and Couton, F (2005) Construction of an oilseed rape (Brassica napus L.) genetic map with SSR markers. Theoretical and Applied Genetics 111, 15141523.CrossRefGoogle ScholarPubMed
Pu, L, Liu, MS, Kim, SY, Chen, LF, Fletcher, JC and Sung, ZR (2013) EMBRYONIC FLOWER1 and ULTRAPETALA1 act antagonistically on Arabidopsis development and stress response. Plant Physiology 162, 812830.CrossRefGoogle ScholarPubMed
Raman, H, Raman, R, Qiu, Y, Yadav, AS, Sureshkumar, S, Borg, L, Rohan, M, Wheeler, D, Owen, O, Menz, L and Balasubramanian, S (2019) GWAS hints at pleiotropic roles for FLOWERING LOCUS T in flowering time and yield-related traits in canola. BMC G Raman enomics 20, 636.CrossRefGoogle Scholar
Ritchie, SW, Nguyen, HT and Holaday, AS (1990) Leaf water content and gas-exchange parameters of two wheat genotypes differing in drought resistance. Crop Science 30, 105111.CrossRefGoogle Scholar
Sabzevar, MS, Rezaei, A and Khaleghi, B (2021) Incremental adaptation strategies for agricultural water management under water scarcity condition in northeast Iran. Regional Sustainability 2, 224238.CrossRefGoogle Scholar
Safari, S and Mehrabi, AA (2015) Evaluation of genetic diversity in rapeseed genotypes using ISSR markers. Agricultural Biotechnology 5, 3743.Google Scholar
Saghai-Maroof, MA, Soliman, KM, Jorgensen, RA and Allard, R (1984) Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics. Proceedings of the National Academy of Sciences 81, 80148018.CrossRefGoogle ScholarPubMed
Sallam, A, Alqudah, AM, Dawood, MF, Baenziger, PS and Börner, A (2019) Drought stress tolerance in wheat and barley: advances in physiology, breeding and genetics research. International Journal of Molecular Sciences 20, 3137.CrossRefGoogle ScholarPubMed
Schiessl, SV, Quezada-Martinez, D, Orantes-Bonilla, M and Snowdon, RJ (2020) Transcriptomics reveal high regulatory diversity of drought tolerance strategies in a biennial oil crop. Plant Science 297, 110515.CrossRefGoogle Scholar
Shah, S, Weinholdt, C, Jedrusik, N, Molina, C, Zou, J, Große, I, Schiessl, S, Jung, CH and Emrani, N (2018) Whole transcriptome analysis reveals genetic factors underlying flowering time regulation in rapeseed (Brassica napus L.). Plant Cell Environment 41, 19351947.CrossRefGoogle ScholarPubMed
Shaygan, N, Etminan, A, Majidi Hervan, I, Azizinezhad, R and Mohammadi, R (2021) The study of genetic diversity in a minicore collection of durum wheat genotypes using agro-morphological traits and molecular markers. Cereal Research Communications 49, 141147.CrossRefGoogle Scholar
Shi, J, Huang, S, Zhan, J, Yu, J, Wang, X, Hua, W, Liu, S, Liu, G and Wang, H (2013) Genome-wide microsatellite characterization and marker development in the sequenced brassica crop species. DNA Research 21, 5368.CrossRefGoogle ScholarPubMed
Sinaki, JM, Majidi Heravan, E, Shirani, AH, Noormohamadi, G and Zarei, G (2007) The effects of water deficit during growth stages of canola (B. napus L.). American–Eurasian Journal of Agricultural and Environmental Sciences 2, 417422.Google Scholar
Song, YH, Ito, S and Imaizumi, T (2013) Flowering time regulation: photoperiod- and temperature-sensing in leaves. Trends Plant Science 18, 575583.CrossRefGoogle ScholarPubMed
Tabachnick, B and Fidell, LS (2001) Using Multivariate Statistics. Needham Heights, USA: A Pearson Education Company, 966 pp.Google Scholar
Thiyam-Holländer, U, Eskin, NA and Matthäus, B (2012) Canola and Rapeseed: Production, Processing, Food Quality, and Nutrition. Boca Raton, Florida, USA: CRC Press. 374 pp.CrossRefGoogle Scholar
Tian, HY, Channa, SA and Hu, SW (2017) Relationships between genetic distance, combining ability and heterosis in rapeseed (Brassica napus L.). Euphytica 213, 1.CrossRefGoogle Scholar
Tsimilli-Michael, M and Strasser, RJ (2008) In vivo assessment of stress impact on plant's vitality: applications in detecting and evaluating the beneficial role of mycorrhization on host plants. In Varma, A. (ed.), Mycorrhiza. Berlin Heidelberg: Springer, pp. 679703.CrossRefGoogle Scholar
Uquiche, E, Jerez, M and Ortiz, J (2008) Effect of pretreatment with microwaves on mechanical extraction yield and quality of vegetable oil from Chilean hazelnuts (Gevuina avellana Mol). Innovative Food Science and Emerging Technologies 9, 495500.CrossRefGoogle Scholar
Wagner, GJ (1979) Content and vacuole/extravacuole distribution of neutral sugars, free amino acids, and anthocyanin in protoplasts. Plant Physiology 64, 8893.CrossRefGoogle ScholarPubMed
Wang, F, Wang, XF, Chen, X, Xiao, Y, Li, H, Zhang, SH, Xu, J, Fu, J, Huang, L, Liu, CH, Wu, J and Liu, K (2012) Abundance, marker development and genetic mapping of microsatellites from unigenes in Brassica napus. Molecular Breeding 30, 731744.CrossRefGoogle Scholar
Wasternack, C, Forner, S, Strnad, M and Hause, B (2013) Jasmonates in flower and seed development. Biochimie 95, 7985.CrossRefGoogle ScholarPubMed
Zhang, Z, Zhang, S and Zhang, Y (2011) Arabidopsis floral initiator SKB1 confers high salt tolerance by regulating transcription and pre-mRNA splicing through altering histone H4R3 and small nuclear ribonucleoprotein LSM4 methylation. The Plant Cell 23, 396411.CrossRefGoogle ScholarPubMed
Zhu, M, Monroe, JG, Suhail, Y, Villiers, F, Mullen, J, Pater, D, Hauser, F, Jeon, BW, Bader, JS, Kwak, JM, Schroeder, JI, McKay, JK and Assmann, SM (2016) Molecular and systems approaches towards drought-tolerant canola crops. New Phytologist 210, 11691189.CrossRefGoogle ScholarPubMed
Supplementary material: File

Motallebinia et al. supplementary material 1

Motallebinia et al. supplementary material
Download Motallebinia et al. supplementary material 1(File)
File 86.2 KB
Supplementary material: File

Motallebinia et al. supplementary material 2

Motallebinia et al. supplementary material
Download Motallebinia et al. supplementary material 2(File)
File 131.1 KB
Supplementary material: File

Motallebinia et al. supplementary material 3

Motallebinia et al. supplementary material
Download Motallebinia et al. supplementary material 3(File)
File 124.6 KB
Supplementary material: File

Motallebinia et al. supplementary material 4

Motallebinia et al. supplementary material
Download Motallebinia et al. supplementary material 4(File)
File 115.5 KB
Supplementary material: File

Motallebinia et al. supplementary material 5

Motallebinia et al. supplementary material
Download Motallebinia et al. supplementary material 5(File)
File 2.4 MB
Supplementary material: File

Motallebinia et al. supplementary material 6

Motallebinia et al. supplementary material
Download Motallebinia et al. supplementary material 6(File)
File 362 KB
Supplementary material: File

Motallebinia et al. supplementary material 7

Motallebinia et al. supplementary material
Download Motallebinia et al. supplementary material 7(File)
File 649.5 KB
Supplementary material: File

Motallebinia et al. supplementary material 8

Motallebinia et al. supplementary material
Download Motallebinia et al. supplementary material 8(File)
File 430.4 KB
Supplementary material: File

Motallebinia et al. supplementary material 9

Motallebinia et al. supplementary material
Download Motallebinia et al. supplementary material 9(File)
File 87.7 KB