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Elucidation of genetic diversity base in Calotropis procera – a potentially emerging new fibre resource

Published online by Cambridge University Press:  16 July 2020

Aasim Majeed ,
Bhawana Goel ,
Vandana Mishra ,
Ravinder Kohli  and
Pankaj Bhardwaj Open the ORCID record for Pankaj Bhardwaj [Opens in a new window]
Aasim Majeed
Affiliation:
Molecular Genetics Laboratory, Department of Botany, Central University of Punjab, Bathinda, India
Bhawana Goel
Affiliation:
Molecular Genetics Laboratory, Department of Botany, Central University of Punjab, Bathinda, India
Vandana Mishra
Affiliation:
Molecular Genetics Laboratory, Department of Botany, Central University of Punjab, Bathinda, India
Ravinder Kohli
Affiliation:
Molecular Genetics Laboratory, Department of Botany, Central University of Punjab, Bathinda, India
Pankaj Bhardwaj*
Affiliation:
Molecular Genetics Laboratory, Department of Botany, Central University of Punjab, Bathinda, India
*
*Corresponding author. E-mail: pankajihbt@gmail.com, pankajbhardwaj@cup.edu.in
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Abstract

Calotropis procera is emerging as a new, yet undomesticated, resource of fibre comparable to cotton and kapok. Screening of efficient genotypes from its wild populations would be a useful pre-domestication process. The desired genotypes can then be improved through conventional breeding programmes to develop a domesticated variety. Molecular markers play a major role in modern breeding systems. Thus, an efficient marker resource for C. procera would prove useful in germplasm selection during breeding programmes. In this study, we undertook an initial step of Simple sequence repeats (SSR) marker development for C. procera, which could be applied for germplasm selection. Furthermore, using the developed markers, we assessed the genetic diversity base within its wild populations which could be useful to identify the hotspot areas of germplasm collection. Out of 94,636 de novo assembled transcripts, 9148 sequences were found to contain 12,884 SSRs at a density of 5.5 SSRs/Mb. Twelve SSRs were found as polymorphic with a mean polymorphic information content of 0.575. We observed a moderate level of genetic diversity (Na = 3.625, Ho = 0.58) in the studied populations. Mantel's test showed significant correlation between the geographic distance and the genetic distance (r = 0.147, P = 0.010). Sirsa was found as a genetically most diverse population followed by Barnala while Gurdaspur was found with the least genetic diversity. These genetically diverse populations can serve as an important resource for effective germplasm collection for breeding programmes.

Keywords

genetic diversitynorthern plains of IndiaRNAseqSSR markers
Type
Research Article
Information
Plant Genetic Resources , Volume 18 , Issue 3 , June 2020 , pp. 159 - 167
Copyright
Copyright © NIAB 2020

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Footnotes

†

These authors contributed equally.

References

Andrews, S (2010) FastQC: a quality control tool for high throughput sequence data. Available at https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.Google Scholar
Ashori, A and Bahreini, Z (2009) Evaluation of Calotropis gigantea as a promising raw material for fiber-reinforced composite. Journal of Composite Materials 43: 1297–1304.CrossRefGoogle Scholar
Cheema, HMN, Bashir, A, Khatoon, A, Iqbal, N, Zafar, Y and Malik, KA (2010) Molecular characterization and transcriptome profiling of expansin genes isolated from Calotropis procera fibers. Electronic Journal of Biotechnology 13: 10–11.Google Scholar
Choedon, T, Mathan, G, Arya, S, Kumar, VL and Kumar, V (2006) Anticancer and cytotoxic properties of the latex of Calotropis procera in a transgenic mouse model of hepatocellular carcinoma. World Journal of Gastroenterology 12: 2517–2522.CrossRefGoogle Scholar
Choudhary, S, Thakur, S, Najar, RA, Majeed, A, Singh, A and Bhardwaj, P (2018) Transcriptome characterization and screening of molecular markers in ecologically important Himalayan species (Rhododendron arboreum). Genome 61: 417–428.CrossRefGoogle Scholar
Doyle, JJ (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phyto chem Bulletin Botanical Society of America 19: 11–15.Google Scholar
Earl, DA (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetics Resources 4: 359–361.CrossRefGoogle Scholar
El-Bakry, AA, Hammad, IA and Rafat, FA (2014) Polymorphism in Calotropis procera: preliminary genetic variation in plants from different phytogeographical regions in Egypt. Rendiconti Lincei. Scienze Fisiche e Naturali 25: 471–477.CrossRefGoogle Scholar
Feng, SP, Li, WG, Huang, HS, Wang, JY and Wu, YT (2009) Development, characterization and cross-species/genera transferability of EST-SSR markers for rubber tree (Hevea brasiliensis). Molecular Breeding 23: 85–97.CrossRefGoogle Scholar
Ga, DB, Kb, SB and Pc, NK (2014) Tensile and wear behavior of Calotropis gigentea fruit fiber reinforced polyester composites. Procedia Engineering 97: 531–535.Google Scholar
Grabherr, MG, Haas, BJ, Yassour, M, Levin, JZ, Thompson, DA, Amit, I and Chen, Z (2011) Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data. Nature Biotechnology 29: 644–652.CrossRefGoogle Scholar
Hassan, AM, El-Shawaf, IIS, Bekhi, MMM, El-Saied, FM and Masoud, IM (2008) Genetic variation within Ushaar (Calotropis procera (ait) F.) genotypes using SDS-PAGE for protein and isozyme analysis. The fourth Conference of sustainable Agriculture Development, Faculty of Agriculture, Fayoum University, 20–22 Oct: 103–114.Google Scholar
Huang, L, Deng, X, Li, R, Xia, Y, Bai, G, Siddique, KH and Guo, P (2018) A fast silver staining protocol enabling simple and efficient detection of SSR markers using a non-denaturing polyacrylamide gel. Journal of Visualized Experiments 134: e57192.Google Scholar
Islam, MR, Li, ZZ, Gichira, AW, Alam, MN, Fu, PC, Hu, GW and Chen, LY (2019) Population genetics of Calotropis gigantea, a medicinal and fiber resource plant, as inferred from microsatellite marker variation in two native countries. Biochemical Genetics 57: 522–539.CrossRefGoogle ScholarPubMed
Jimenez, HJ, Martins, LSS, Montarroyos, AVV, Silva Junior, JF, Alzate-Marin, AL and Moraes Filho, RM (2015) Genetic diversity of the Neotropical tree Hancornia speciosa Gomes in natural populations in Northeastern Brazil. Genetics & Molecular Research 14: 17749–17757.CrossRefGoogle Scholar
Kalinowski, ST, Taper, ML and Marshall, TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Molecular Ecology 16: 1099–1106.CrossRefGoogle ScholarPubMed
Langmead, B (2010) Current protocols in bioinformatics. In: Aligning Short Sequencing Reads with Bowtie. John Wiley & Sons, Inc., pp. 32:11.7.1-11.7.14.CrossRefGoogle ScholarPubMed
Li, W and Godzik, A (2006) Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics (Oxford, England) 22: 1658–1659.CrossRefGoogle ScholarPubMed
Liewlaksaneeyanawin, C, Ritland, CE, El-Kassaby, YA and Ritland, K (2004) Single-copy, species-transferable microsatellite markers developed from loblolly pine ESTs. Theoretical & Applied Genetics 109: 361–369.CrossRefGoogle ScholarPubMed
Majeed, A, Singh, A, Choudhary, S and Bhardwaj, P (2019) Transcriptome characterization and development of functional polymorphic SSR marker resource for Himalayan endangered species, Taxus contorta (Griff). Industrial Crops & Products 140: 111600.CrossRefGoogle Scholar
Min, XJ, Butler, G, Storms, R and Tsang, A (2005) ORF predictor: predicting protein-coding regions in EST-derived sequences. Nucleic Acids Research 33: 677–680.CrossRefGoogle Scholar
Muriira, NG, Muchugi, A, Yu, A, Xu, J and Liu, A (2018) Genetic diversity analysis reveals genetic differentiation and strong population structure in Calotropis plants. Scientific Reports 8: 7832.CrossRefGoogle ScholarPubMed
Mutwakil, MZ, Hajrah, NH, Atef, A, Edris, S, Sabir, MJ, Al-Ghamdi, AK and El-Domyati, FM (2017) Transcriptomic and metabolic responses of Calotropis procera to salt and drought stress. BMC Plant Biology 17: 231.CrossRefGoogle ScholarPubMed
Olsson, S, Pinosio, S, González-Martínez, SC, Abascal, F, Mayol, M, Grivet, D and Vendramin, GG (2018) De novo assembly of English yew (Taxus baccata) transcriptome and its applications for intra- and inter-specific analyses. Plant Molecular Biology 97: 337–345.CrossRefGoogle ScholarPubMed
Pandeya, SC, Chandra, A and Pathak, PS (2007) Genetic diversity in some perennial plant species with-in short distances. Journal of Environmental Biology 28: 83–86.Google ScholarPubMed
Peakall, R and Smouse, PE (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Resources 6: 288–295.Google Scholar
Peakall, R and Smouse, PE (2012) Genalex 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics (Oxford, England) 28: 2537–2539.CrossRefGoogle ScholarPubMed
Postolache, D, Leonarduzzi, C, Piotti, A, Spanu, I, Roig, A, Fady, B and Vendramin, GG (2014) Transcriptome versus genomic microsatellite markers: highly informative multiplexes for genotyping Abies alba Mill. and congeneric species. Plant Molecular Biology Reporter 32: 750–760.CrossRefGoogle Scholar
Pritchard, JK, Stephens, M and Donnelly, P (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945–959.CrossRefGoogle ScholarPubMed
Priya, TA, Manimekalai, V and Ravichandran, P (2015) Intraspecific genetic diversity studies on Calotropis gigantea (L) R. Br. using RAPD markers. European Journal of Biotechnology & Biosciences 3: 7–9.Google Scholar
Qi, Y, Xu, F, Longdi, C, Ruiyun, Z, Lifang, L, Wenhong, F, Beina, Z and Li, J (2018) Evaluation on a promising natural cellulose fiber – Calotropis gigantea fiber. Trends in Textile Engineering & Fashion Technology 2: 205–211.Google Scholar
Qu, J and Liu, J (2013) A genome-wide analysis of simple sequence repeats in maize and the development of polymorphism markers from next-generation sequence data. BMC Research Notes 6: 403.CrossRefGoogle ScholarPubMed
Rathore, PK, Madihalli, S, Hegde, S, Hegde, HV, Bhagwat, RM, Gupta, VS, Kholkute, SD, Jha, TB and Roy, S (2016) Assessment of genetic diversity of Gymnema sylvestre (Retz.) R.Br. from Western Ghats and Eastern India. India. Journal of Biodiversity & Environmental Sciences 9: 82–92.Google Scholar
Sakthivel, JC, Mukhopadhyay, S and Palanisamy, NK (2005) Some studies on Mudar fibers. Journal of Industrial Textiles 35: 63–76.CrossRefGoogle Scholar
Schaal, BA, Hayworth, DA, Olsen, KM, Rauscher, JT and Smith, WA (1998) Phylogeographic studies in plants: problems and prospects. Molecular Ecology 7: 465–474.CrossRefGoogle Scholar
Silva, MCC, da Silva, AB, Teixeira, FM, de Sousa, PCP, Rondon, RMM, Júnior, JERH and de Vasconcelos, SMM (2010) Therapeutic and biological activities of Calotropis procera (Ait.) R. Br. Asian Pacific Journal of Tropical Medicine 3: 332–336.CrossRefGoogle Scholar
Simão, FA, Waterhouse, RM, Ioannidis, P, Kriventseva, EV and Zdobnov, EM (2015) BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics (Oxford, England) 31: 3210–3212.CrossRefGoogle ScholarPubMed
Sobrinho, MS, Tabatinga, GM, Machado, IC and Lopes, AV (2013) Reproductive phenological pattern of Calotropis procera (Apocynaceae), an invasive species in Brazil: annual in native areas; continuous in invaded areas of caatinga. Acta Botanica Brasilica 27: 456–459.CrossRefGoogle Scholar
Tuntawiroon, N, Samootsakorn, P and Theeraraj, G (1984) The environmental implications of the use of Calotropis gigantea as a textile fabric. Agriculture, Ecosystems & Environment 11: 203–212.CrossRefGoogle Scholar
Varshney, RK, Graner, A and Sorrells, ME (2005) Genic microsatellite markers in plants: features and applications. Trends in Biotechnology 23: 48–55.CrossRefGoogle ScholarPubMed
Yamashiro, T, Yamashiro, A, Inoue, M and Maki, M (2016) Genetic diversity and divergence in populations of the threatened grassland perennial Vincetoxicum atratum (Apocynaceae-Asclepiadoideae) in Japan. Journal of Heredity 107: 455–462.CrossRefGoogle ScholarPubMed
Yao, DARA, Sprycha, Y, Porembski, S and Horn, R (2015) AFLP assessment of the genetic diversity of Calotropis procera (Apocynaceae) in the West Africa region (Benin). Genetic Resources & Crop Evolution 62: 863–878.Google Scholar
You, FM, Huo, N, Gu, YQ, Luo, MC, Ma, Y, Hane, D, Lazo, GR, Dvorak, J and Anderson, OD (2008) Batchprimer3: a high throughput web application for PCR and sequencing primer design. BMC Bioinformatics 253: 1–13.Google Scholar
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