Study genetic structure and diversity of Afghanistan Chalghoza pine (Pinus gerardiana) populations using SCoT and iPBS molecular markers

Document Type : Research Paper

Authors

1 Faculty of Agriculture, Shahrekord University, Shahrekord, Iran

2 Faculty member/ Shahrekord University

10.22092/ijrfpbgr.2023.361428.1433

Abstract

Extended Abstract  
Background and objective:
The Chalghoza pine (Pinus gerardiana) is grown in the eastern and southeastern regions of Afghanistan and has an important role in the socio-economic progress of rural communities. It serves various purposes, such as providing pine nuts, fuel wood, medicinal plants, grazing areas, and shelter for livestock. In this research, the genetic diversity and structure of different Chalghoza pine populations were examined using molecular markers known as start codon targeted (SCoT) and inter primer binding site (iPBS) markers. Due to the excessive harvesting of its nuts and a decline in its population, the IUCN categorizes the Chilgoza pine as a nearing threat.
 
Methodology:
39 Chalghozeh pine genotypes were collected from various regions across five provinces in Afghanistan, namely Khost, Paktia, Laghman, Kunar, and Nuristan. To extract genomic DNA, a modified CTAB procedure was employed, utilizing megagametophyte tissue from 4-5 seeds per genotype. For this research, six primers each for SCoT and iPBS markers were utilized. To analyze the data and determine genetic relationships, cluster analysis was conducted using the unweighted pair-group method arithmetic averages.
 
Results:
In this study, 12 SCoT and iPBS primers were utilized, resulting in the generation of 48 and 55 bands for SCoT and iPBS markers, respectively. The percentage of polymorphism was estimated at 20.8% for SCoT markers and 29.1% for iPBS markers. The average values of PIC (polymorphic information content) were determined as 0.026 for SCoT markers and 0.045 for iPBS markers, indicating a higher differentiation power of iPBS markers compared to SCoT markers. The genetic similarity coefficient revealed a relatively low genetic diversity among the populations examined. The UPGMA dendrogram, based on the similarity coefficient, demonstrated that the genotypes did not cluster according to their collection sites. This outcome can be attributed to the species' highly cross-pollinating nature and limited distribution range in the studied area. The observed number of alleles (NA) was 1.08 and 1.09, while the effective number of alleles (NE) was determined as 1.075 for both SCoT and iPBS markers. The Shannon's information index (I) was calculated as 0.055 and 0.060 for SCoT and iPBS markers, respectively. The expected heterozygosity (HE) values were estimated as 0.039 for SCoT markers and 0.042 for iPBS markers. The analysis of molecular variance (AMOVA) indicated that the genetic diversity within populations was higher than among populations. Through a Bayesian model-based STRUCTURE analysis, two groups (K=2) were identified among the five populations of Pinus gerardiana, and admixture was observed within individuals.
 
Conclusion:
The minimal variations observed in total diversities and levels of population differentiation among the five Chalghoza pine populations suggest that the genetic structure of these populations aligns with the species' long-lived perennial nature and regional distribution. These findings have implications for the conservation and cultivation of this economically significant tree, providing valuable insights for its management and preservation.

Keywords

Main Subjects

References

Alam, M., 2011. Trees and shrubs of Afghanistan: a dendrological guide. Rossolis; Musée botanique cantonal Lausanne, Switzerland. pp. 80-82
Amom, T. and Nongdam, P., 2017. The use of molecular marker methods in plants: a review. International Journal of Current Research and Review, 9: 1-7.
Amom, T., Tikendra, L., Apana, N., Goutam, M., Sonia, P., Koijam, A.S., Potshangbam, A.M., Rahaman, H. and Nongdam, P., 2020. Efficiency of RAPD, ISSR, iPBS, SCoT and phytochemical markers in the genetic relationship study of five native and economical important bamboos of North-East India. Phytochemistry, 174: 112330.
Bhattacharyya, A., Lamarche, V.C.Jr., Telewski, F.W., 1988. Dendrochronological reconnaissance of the 483 conifers of Northwest India. Tree Ring Bulletin, 48: 21-30.
Borna, F., Luo, S., Ahmad, N.M., Nazeri, V., Shokrpour, M. and Trethowan, R., 2017. Genetic diversity in populations of the medicinal plant Leonurus cardiaca L. revealed by inter-primer binding site (iPBS) markers. Genetic Resources and Crop Evolution, 64: 479-492.
Collard, B.C. and Mackill, D.J., 2009. Start codon targeted (SCoT) polymorphism: a simple, novel DNA marker technique for generating gene-targeted markers in plants. Plant molecular biology reporter, 27: 86-93.
Doyle, J.J. and Doyle, J.L., 1987. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochememical Bulletin, 19: 11–15.
Earl, D.A. and VonHoldt, B.M., 2012. Structure Harvester: a website and program for visualizing structure output and implementing the Evanno method. Conservation genetics resources, 4: 359-361.
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(8): 2611-2620.
Excoffier, L., Smouse, P.E. and Quattro, J., 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics, 131(2): 479-491.
Fang-Yong, C. and Ji-Hong, L., 2014. Germplasm genetic diversity of Myrica rubra in Zhejiang Province studied using inter-primer binding site and start codon-targeted polymorphism markers. Scientia Horticulturae, 170: 169-175.
Hamrick, J.L. and Godt, M.J.W., 1989. Allozyme diversity in plant species. In ‘Plant population genetics, breeding and genetic resources’.(Eds AHD Brown, MT Clegg, AL Kahler, BS Weir) pp. 43–63.
Hamrick, J.L., Godt, M.J.W. and Sherman-Broyles, S.L., 1992. Factors influencing levels of genetic diversity in woody plant species. In Population Genetics of Forest Trees: Proceedings of the International Symposium on Population Genetics of Forest Trees Corvallis, Oregon, USA, July 31–August 2, 1990 (pp. 95-124). Springer Netherlands.
Isabel, N., Beaulieu, J. and Bousquet, J., 1995. Complete congruence between gene diversity estimates derived from genotypic data at enzyme and random amplified polymorphic DNA loci in black spruce. Proceedings of the National Academy of Sciences, 92(14): 6369-6373.
Isabel, N., Beaulieu, J., Thériault, P. and Bousquet, J., 1999. Direct evidence for biased gene diversity estimates from dominant random amplified polymorphic DNA (RAPD) fingerprints. Molecular Ecology, 8(3): 477-483.
Jaccard, P., 1908. Nouvelles recherches sur la distribution florale. Bull. Soc. Vaud. Sci. Nat., 44: 223-270.
Kalendar, R., Antonius, K., Smýkal, P. and Schulman, A.H., 2010. iPBS: a universal method for DNA fingerprinting and retrotransposon isolation. Theoretical and Applied Genetics, 121: 1419-1430.
Kalendar, R., Amenov, A. and Daniyarov, A., 2018. Use of retrotransposon-derived genetic markers to analyse genomic variability in plants. Functional Plant Biology, 46(1), 15-29.
Kant, A., Pattanayak, D., Chakrabarti, S.K., Sharma, R., Thakur, M. and Sharma, D. R., 2006. RAPD analysis of genetic variability in Pinus gerardiana Well. In Kinnaur (Himachal Pradesh). Indian Journal of Biotechnology, 5: 52-67
Klobucnik, M., Galgoci, M., Gomory, D. and Kormutak, A., 2022. Molecular Insight into Genetic Structure and Diversity of Putative Hybrid Swarms of Pinus sylvestris× P. mugo in Slovakia. Forests, 13(2): 205.
Kumar, R., Shamet, G.S., Mehta, H., Alam, N.M., Kaushal, R., Chaturvedi, O.P., Sharma, N., Khaki, B.A. and Gupta, D., 2016. Regeneration complexities of Pinus gerardiana in dry temperate forests of Indian Himalaya. Environmental Science and Pollution Research, 23: 7732-7743.
Nagaraju, J., Kathirvel, M., Kumar, R.R., Siddiq, E.A. and Hasnain, S.E., 2002. Genetic analysis of traditional and evolved Basmati and non-Basmati rice varieties by using fluorescence-based ISSR-PCR and SSR markers. Proceedings of the National Academy of Sciences, 99(9): 5836-5841.
Nei, M., 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics, 89(3): 583-590.
Nybom, H., 2004. Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants. Molecular ecology, 13(5): 1143-1155.
Peakall R. and Smouse P.E. 2012. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research – an update. Bioinformatics 28: 2537-2539
Petit, J.R., Duminil, J., Fineschi, S., Hampe, A., Salvini, D. and Ven-dramin, G.G., 2005. Comparative organization of chloroplast, mitochondrial and nuclear diversity in plant populations. Molecular Ecology 14: 689-701.
Powell, W.W., Koput, K.W. and Smith-Doerr, L., 1996. Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly, 41(1): 116-145.
Pritchard, J.K., Stephens, M. and Donnelly, P., 2000. Inference of population structure using multilocus genotype data. Genetics, 155(2): 945-959.
Rohlf, F.J., 2009. NTSYSpc: numerical taxonomy system. Version 2.21c. Exeter Software: Setauket: New York.
Roldan-Ruiz, I., Dendauw, J., Van Bockstaele, E., Depicker, A. and De Loose, M.A.F.L.P., 2000. AFLP markers reveal high polymorphic rates in ryegrasses (Lolium spp.). Molecular breeding, 6: 125-134.
Saboori, S., Noormohammadi, Z., Sheidai, M. and Marashi, S., 2020. SCoT molecular markers and genetic fingerprinting of date palm (Phoenix dactylifera L.) cultivars. Genetic Resources and Crop Evolution, 67: 73-82.
Shimada, K., Fujikawa, K., Yahara, K. and Nakamura, T., 1992. Antioxidative properties of xanthan on the autoxidation of soybean oil in cyclodextrin emulsion. Journal of agricultural and food chemistry, 40(6): 945-948.
Tabasi, M., Sheidai, M., Hassani, D. and Koohdar, F., 2020. DNA fingerprinting and genetic diversity analysis with SCoT markers of Persian walnut populations (Juglans regia L.) in Iran. Genetic Resources and Crop Evolution, 67: 1437-1447.
Tong, Y., Durka, W., Zhou, W., Zhou, L., Yu, D. and Dai, L., 2020. Ex situ conservation of Pinus koraiensis can preserve genetic diversity but homogenizes population structure. Forest Ecology and Management, 465: 117820.
Tyagi, R., Sharma, V., Sureja, A.K., Das Munshi, A., Arya, L., Saha, D. and Verma, M., 2020. Genetic diversity and population structure detection in sponge gourd (Luffa cylindrica) using ISSR, SCoT and morphological markers. Physiology and Molecular Biology of Plants, 26: 119-131.
Vanijajiva, O. and Pornpongrungrueng, P., 2020. Inter-primer binding site (ipbs) markers reveal the population genetic diversity and structure of tropical climbing cissampelopsis (asteraceae) in thailand. Biodiversitas Journal of Biological Diversity, 21(9): 3919-3928.
Varshney, R.K., Marcel, T.C., Ramsay, L., Russell, J., Röder, M.S., Stein, N., Waugh, R., Langridge, P., Niks, R.E. and Graner, A., 2007. A high density barley microsatellite consensus map with 775 SSR loci. theoretical and Applied Genetics, 114: 1091-1103.
Vasilyeva, Y., Chertov, N., Nechaeva, Y., Sboeva, Y., Pystogova, N., Boronnikova, S. and Kalendar, R., 2021. Genetic structure, differentiation and originality of Pinus sylvestris L. populations in the east of the East European Plain. Forests, 12(8): 999.
Yeh, F.C., Yang, R.C., Boyle, T.B., Ye, Z.H. and Mao, J.X., 1997. POPGENE, the user-friendly shareware for population genetic analysis. Molecular biology and biotechnology centre, University of Alberta, Canada, 10: 295-301.
Zhou, L., He, X.H., Yu, H.X., Chen, M.Y., Fan, Y., Zhang, X.J., Fang, Z.B. and Luo, C., 2020. Evaluation of the genetic diversity of mango (Mangifera indica L.) seedling germplasm resources and their potential parents with start codon targeted (SCoT) markers. Genetic Resources and Crop Evolution, 67: 41-58.
Zhang, Z.Y., Chen, Y.Y. and Li, D.Z., 2005. Detection of low genetic variation in a critically endangered Chinese pine, Pinus squamata, using RAPD and ISSR markers. Biochemical Genetics, 43: 239-249.

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