Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-25T05:47:25.683Z Has data issue: false hasContentIssue false

Analysis of genetic diversity and spatial structure in Tunisian populations of Hordeum marinum ssp. marinum based on molecular markers

Published online by Cambridge University Press:  23 October 2019

W. Saoudi*
Affiliation:
Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, B.P. 901, Hammam-Lif 2050, Tunisia
M. Badri
Affiliation:
Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, B.P. 901, Hammam-Lif 2050, Tunisia
M. Gandour
Affiliation:
Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, B.P. 901, Hammam-Lif 2050, Tunisia Faculty of Sciences and Technics of Sidi Bouzid, University of Kairouan, Sidi Bouzid 9100, Tunisia
A. Smaoui
Affiliation:
Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, B.P. 901, Hammam-Lif 2050, Tunisia
C. Abdelly
Affiliation:
Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, B.P. 901, Hammam-Lif 2050, Tunisia
W. Taamalli
Affiliation:
Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, B.P. 901, Hammam-Lif 2050, Tunisia Laboratory of Olive Biotechnology, Centre of Biotechnology of Borj Cedria, B.P. 901, Hammam-Lif 2050, Tunisia
*
Author for correspondence: W. Saoudi, E-mail: [email protected]

Abstract

Hordeum marinum commonly known as sea barley is a salinity-tolerant species of grass. In the current study, 150 lines from ten populations of H. marinum ssp. marinum collected from five Tunisian bioclimatic sites were screened for polymorphism with 13 selected random amplified polymorphic DNA primers. Results exhibited a high level of polymorphism (160 polymorphic bands with an average of 12.46 per primer) and a high level of genetic diversity in all the studied populations (on average UHe = 0.247 and I = 0.358). High discrimination capacity was found for the 13 primers and a combination of three allowed assignation of a unique profile for each of the 150 lines. The partition of genetic diversity with Analysis of Molecular Variance suggested that the majority of genetic variation (67%) was within populations. The components between-populations within ecoregions and between-ecoregions explained 21 and 12%, respectively, of the total genetic variance. There was no significant association of population differentiation (ФPT) with geographical distance or altitudinal difference. Results also showed that the 150 lines grouped into three clusters with no respect to geographic origin. A sub-set of 13 lines was identified, which captured the maximum genetic diversity of the entire collection. The genetic variation found in this collection of H. marinum is deemed to be useful in formulating conservation strategies for this species.

Type
Crops and Soils Research Paper
Copyright
Copyright © Cambridge University Press 2019 

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

Abdellaoui, R, Kadri, K, Ben Naceur, M and Ben Kaab, LB (2010) Genetic diversity in some Tunisian barley Landraces based on RAPD markers. Pakistan Journal of Botany 42, 37753782.Google Scholar
Abdelly, C, Lachaâl, M, Grignon, C, Soltani, A and Hajji, M (1995) Association épisodique d'halophytes strictes et de glycophytes dans un écosystème hydromorphe salé en zone semi-aride. Agronomie 15, 557568.Google Scholar
Alamri, SA, Barrett-Lennard, EG, Teakle, NL and Colmer, TD (2013) Improvement of salt and waterlogging tolerance in wheat: comparative physiology of Hordeum marinum-Triticum aestivum amphiploids with their H. marinum and wheat parents. Functional Plant Biology 40, 11681178.Google Scholar
Arraouadi, S, Badri, M, Abdul Jaleel, C, Djébali, N, Ilahi, H, Huguet, T and Aouani, ME (2009) Analysis of genetic variation in natural populations of Medicago truncatula of southern Tunisian ecological areas using morphological traits and SSR markers. Tropical Plant Biology 2, 122132.Google Scholar
Baek, HJ, Beharav, A and Nevo, E (2003) Ecological-genomic diversity of microsatellites in wild barley, Hordeum spontaneum, populations in Jordan. Theoretical and Applied Genetics 106, 397410.Google Scholar
Baum, BR, Nevo, E, Johnson, DA and Beiles, A (1997) Genetic diversity in wild barley (Hordeum spontaneum C. Koch) in the Near East: a molecular analysis using Random Amplified Polymorphic DNA (RAPD) markers. Genetic Resources and Crop Evolution 44, 147157.Google Scholar
Blattner, FR (2009) Progress in phylogenetic analysis and a new infrageneric classification of the barley genus Hordeum (poaceae: Triticeae). Breeding Science 59, 471480.Google Scholar
Carmona, A, Friero, E, De Bustos, A, Jouve, N and Cuadrado, A (2013) The evolutionary history of sea barley (Hordeum marinum) revealed by comparative physical mapping of repetitive DNA. Annals of Botany 112, 18451855.Google Scholar
Chen, X, Guo, S, Chen, D, Liu, P, Jia, X and Sun, L (2006) Assessing genetic diversity of Chinese cultivated barley by STS markers. Genetic Resources and Crop Evolution 53, 16651673.Google Scholar
Dawson, IK, Chalmers, KJ, Waugh, R and Powell, W (1993) Detection and analysis of genetic variation in Hordeum spontaneum populations from Israel using RAPD markers. Molecular Ecology 2, 151159.Google Scholar
De Bustos, A, Casanova, C, Soler, C and Jouve, N (1998) RAPD variation in wild populations of four species of the genus Hordeum (poaceae). Theoretical and Applied Genetics 96, 101111.Google Scholar
Demissie, A and Bjørnstad, A (1997) Geographical, altitude and agro-ecological differentiation of isozyme and hordein genotypes of landrace barleys from Ethiopia: implications to germplasm conservation. Genetic Resources and Crop Evolution 44, 4355.Google Scholar
Earl, DA and Von Holdt, BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetics Resources 4, 359361.Google 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, 26112620.Google Scholar
Fahima, T, Sun, GL, Beharav, A, Krugman, T, Beiles, A and Nevo, E (1999) RAPD polymorphism of wild emmer wheat populations, Triticum dicoccoides, in Israel. Theoretical and Applied Genetics 98, 434447.Google Scholar
Foll, M and Gaggiotti, O (2008) A genome scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180, 977993.Google Scholar
Friesen, ML, von Wettberg, EJB, Badri, M, Moriuchi, KS, Barhoumi, F, Chang, PL, Cuellar-Ortiz, S, Cordeiro, MA, Vu, WT, Arraouadi, S, Djébali, N, Zribi, K, Badri, Y, Porter, SS, Aouani, ME, Cook, DR, Strauss, SY and Nuzhdin, SV (2014) The ecological genomic basis of salinity adaptation in Tunisian Medicago truncatula. BMC Genomics 15, 1160.Google Scholar
Gandour, M, Hessini, K and Abdelly, C (2008) Understanding the population genetic structure of coastal species (Cakile maritima): seed dispersal and the role of sea currents in determining population structure. Genetics Research 90, 167178.Google Scholar
Geuna, F, Toschi, M and Bassi, D (2003) The use of AFLP markers for cultivar identification in apricot. Plant Breeding 122, 526531.Google Scholar
Gouesnard, B, Bataillon, TM, Decoux, G, Rozale, C, Schoen, DJ and David, JL (2001) MSTRAT: an algorithm for building germplasm core collections by maximizing allelic or phenotypic richness. Journal of Heredity 92, 9394.Google Scholar
Hamrick, JL (1990) Isozymes and the analysis of genetic structure in plant populations. In Soltis, ED, Soltis, PS and Dudley, TR (eds), Isozymes in Plant Biology. London, UK: Chapman and Hall, pp. 87105.Google Scholar
Hewitt, EJ (1966) Sand and Water Culture Methods Used in the Study of Plant Nutrition. Technical Communication no. 22. East Malling, UK: Commonwealth Bureau of Horticultural Plantation Crops, pp. 431446.Google Scholar
Jain, SK (1975) Population structure and the effects of breeding system. In Frankel, OH and Hawkes, JG (eds), Crop Genetics Resources for Today and Tomorrow. Cambridge, UK: Cambridge University Press, pp. 1536.Google Scholar
Jakob, SS, Ihlow, A and Blattner, FR (2007) Combined ecological niche modelling and molecular phylogeography revealed the evolutionary history of Hordeum marinum (Poaceae) – niche differentiation, loss of genetic diversity, and speciation in Mediterranean Quaternary refugia. Molecular Ecology 16, 17131727.Google Scholar
Jaradat, AA and Shahid, M (2006) Population and multilocus isozyme structures in a barley landraces. Plant Genetic Resources 4, 108116.Google Scholar
Jeffreys, H (1961) Theory of Probability. Oxford, UK: Oxford University Press.Google Scholar
Kakeda, K, Taketa, S and Komastuda, T (2009) Molecular phylogeny of the genus Hordeum using thioredoxin-like gene sequences. Breeding Science 59, 595601.Google Scholar
Konnerup, D, Malik, AII, Islam, AKMR and Colmer, TD (2017) Evaluation of root porosity and radial oxygen loss of disomic addition lines of Hordeum marinum in wheat. Functional Plant Biology 44, 400409.Google Scholar
Lazrek, F, Roussel, V, Ronfort, J, Cardinet, G, Chardon, F, Aouani, ME and Huguet, T (2009) The use of neutral and non-neutral SSRs to analyse the genetic structure of a Tunisian collection of Medicago truncatula lines and to reveal associations with eco-environmental variables. Genetica 135, 391402.Google Scholar
Mantel, N (1967) The detection of disease clustering and a generalized regression approach. Cancer Research 27, 209220.Google Scholar
Neji, M, Geuna, F, Taamalli, W, Ibrahim, Y, Chiozzotto, R, Abdelly, C and Gandour, M (2015) Assessment of genetic diversity and population structure of Tunisian populations of Brachypodium hybridum by SSR markers. Flora – Morphology, Distribution, Functional Ecology of Plants 216, 4249.Google Scholar
Ozkan, H, Kafkas, S, Ozer, MS and Brandolini, A (2005) Genetic relationships among southeast Turkey wild barley populations and sampling strategies of Hordeum spontaneum. Theoretical Applied Genetics 112, 1220.Google Scholar
Peakall, R and Smouse, PE (2006) Genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6, 288295.Google Scholar
Pritchard, JK, Stephens, M and Donnelly, P (2000) Inference of population structure using multilocus genotype data. Genetics 155, 945959.Google Scholar
Sanz, JC, Fernández, JA and Jouve, N (1987) Isozymes in Hordeum chilense Brong, var. muticum (Presl.) Hauman. I. Isozyme variation. Cereal Research Communications 15, 4349.Google Scholar
Saoudi, W, Badri, M, Gandour, M, Smaoui, A, Abdelly, C and Tammalli, W (2017) Assessment of genetic variability among Tunisian populations of Hordeum marinum using morpho-agronomic traits. Crop Science 57, 302309.Google Scholar
Saoudi, W, Badri, M, Taamalli, W, Zribi, OT, Gandour, M and Abdelly, C (2019) Variability in response to salinity stress in natural Tunisian populations of Hordeum marinum subsp. marinum. Plant Biology 21, 89100.Google Scholar
Schoen, DJ and Brown, AHD (1991) Intraspecific variation in population gene diversity and effective population size correlates with the mating system in plants. Proceedings of the National Academy of Sciences of the USA 8, 44944497.Google Scholar
Tessier, C, David, J, This, P, Boursiquot, JM and Charrier, A (1999) Optimization of the choice of molecular markers for varietal identification in Vitis vinifera L. Theoretical and Applied Genetics 98, 171177.Google Scholar
Treitler, JT, Drissen, T, Stadtmann, R, Zerbe, S and Mantilla-Contreras, J (2017) Complementing endozoochorous seed dispersal patterns by donkeys and goats in a semi-natural island ecosystem. BMC Ecology 17, 42.Google Scholar
Turpeinen, T, Vanhala, T, Nevo, E and Nissilä, E (2003) AFLP genetic polymorphism in wild barley (Hordeum spontaneum) populations in Israel. Theoretical and Applied Genetics 106, 13331339.Google Scholar
Volis, S, Yakubov, B, Shulgina, I, Ward, D, Zur, V and Mendlinger, S (2001) Tests for adaptive RAPD variation in population genetic structure of wild barley, Hordeum spontaneum Koch. Biological Journal of the Linnean Society 74, 289303.Google Scholar
Volis, S, Mendlinger, S, Turuspekov, Y and Esnazarov, U (2002) Phenotypic and allozyme variation in Mediterranean and desert populations of wild barley, Hordeum spontaneum. Evolution 56, 14031415.Google Scholar
Von Bothmer, R, Flink, J, Jacobsen, N and Jorgensen, RB (1989) Variation and differentiation in Hordeum marinum (Poaceae). Nordic Journal of Botany 9, 110.Google Scholar
Von Bothmer, R, Jacobsen, N, Baden, C, Jorgensen, RB and Linde-Laursen, I (1995) An Ecogeographical Study of the Genus Hordeum. Systematic and Ecogeographic Studies on Crop Gene Pools, vol. 7. 2nd ed. Rome, Italy: IBPGR.Google Scholar
Wolff, K (1991) Analysis of allozyme variability in the three Plantago species and a comparison to morphological variability. Theoretical and Applied Genetics 81, 119126.Google Scholar
Yeh, FC, Yang, R, Boyle, TBJ, Ye, ZH and Mao, JX (1997) POPGENE, the User Friendly Shareware for Population Genetic Analysis. Calgary, Canada: Molecular Biology and Biotechnology Centre, University of Alberta.Google Scholar
Zadoks, JC, Chang, TT and Konzak, CF (1974) A decimal code for the growth stages of cereals. Weed Research 14, 415421.Google Scholar
Zhang, Q, Saghai Maroof, MA and Kleinhofs, A (1993) Comparative diversity analysis of RFLPs and isozymes within and among populations of Hordeum vulgare ssp. spontaneum. Genetics 134, 909916.Google Scholar