Genetic Diversity and Population Structure of Barley Cultivars Released in Turkey and Bulgaria using iPBS-retrotransposon and SCoT markers

Year 2022, Volume: 28 Issue: 2, 239 - 250, 25.04.2022

Hüseyin Güngör , Emre İlhan , Ayşe Gül Kasapoğlu , Ertuğrul Filiz , Arash Hossein Pour , Dragomir Valchev , Darina Valcheva , Kamil Haliloğlu , Ziya Dumlupınar

https://doi.org/10.15832/ankutbd.886221

Abstract

To improve quantitative traits, it is essential to acknowledge genetic structure and diversity of the crop plants. In this study, 54 barley cultivars released from 1963 to date by different institutes in both Turkey and Bulgaria were screened with 18 iPBS and four SCoT markers to evaluate population structure and genetic diversity. According to the results, while total polymorphic band numbers was identified as 560, the polymorphic ones were found as 530 (438 and 92 amplified bands for iPBS and SCoT markers, respectively). In addition, the average polymorphic band number was found as 24.09. While the average polymorphism information content (PIC) value was 0.48, the average PIC value was 0.48 for iPBS and 0.48 for SCoT markers. The highest PIC value was determined as 0.50. The highest effective number of alleles, Shannon’s information index, and Nei’s genetic diversity were detected from the iPBS2271 marker at 1.61, 0.52 and 0.35, respectively among the iPBS markers while the highest values were obtained from SCoT-71 marker as 1.55, 0.32 and 0.48, respectively. As a result of a distribution of the 530 amplified bands in 54 barley cultivars, structure analysis showed that the subpopulations in the barley cultivars as a value of k=5. The average expected heterozygosity and fixation indices were identified as 0.234 and 0.322, respectively. Based on DICE similarity index, Martı and Zahir cultivars were found the most similar barley cultivars with 75% genetic similarity, whereas Özdemir and Karatay 94 and Tosunpaşa and Konevi cultivars were found 73% similar. On the other hand, Bayrak and Avcı-2002 were found the most diverse cultivars with 19.9% genetic similarity. As a result, the barley cultivars released in Turkey and Bulgaria were found varying and, the genetic diversity and statistics index analysis indicated that iPBS and SCoT markers are powerful markers to perform genetic diversity analysis.

Keywords

Barley, genetic diversity, iPBS-retrotransposons, SCoT marker, structure analysis

Supporting Institution

Scientific Research Council of Duzce University

Project Number

2018.11.04.735

Thanks

x

References

• Abdel-Lateif K S & Hewedy O A (2018). Genetic diversity among Egyptian wheat cultivars using SCoT and ISSR markers. SABRAO Journal of Breeding and Genetics 50: 36-45
• Aydemir G, Dumlupinar Z, Yüce I, Baskonus T, Sunulu S & Gungor H (2020). Evaluation of individuals obtained from B28×Kunduru-1149 reciprocal cross population by functional markers. KSU J. Agric Nat 23 (4): 1005-1011
• Baik B-K & Ullrich S E (2008) Barley for food: characteristics, improvement, and renewed interest. Journal of Cereal Science 48(2): 233–242
• Baloch F S, Alsaleh A, Sáenz de Miera L E, Hatipoğlu R, Çiftçi V, Karaköy T, Yıldız M & Özkan H (2015a). DNA based iPBS-retrotransposon markers for investigating the population structure of pea (Pisum sativum) germplasm from Turkey. Biochemical Systematics Ecology 61: 244-252
• Baloch F S, Derya M, Andeden E E, Alsaleh A, Comertpay G, Kilian B & Ozkan H (2015b). Inter primer binding site (iPBS) retrotransposon and ISSR diversity among wild lens species. Biochemical Systematics Ecology 58: 162-168
• Barut M, Nadeem M A, Karakoy T & Baloch F S (2020). DNA fingerprinting and genetic diversity analysis of world quinoa germplasm using iPBS-retrotransposon marker system. Turkish Journal of Agriculture and Forestry 44 (5): 479-491
• Bengtsson T, PPP Barley Consortium, Manninen O, Jahoor A & Orabi J (2017). Genetic diversity, population structure and linkage disequilibrium in Nordic spring barley (Hordeum vulgare L. subsp. vulgare). Genetic Resources and Crop Evolution 64(8): 2021-2033. doi: 10.1007/s10722-017-0493-5
• Bhandari H R, Bhanu A N, Srivastava K, Singh M N, Shreya & Hemantaranjan A (2017). Assessment of genetic diversity in crop plants - an overview. Advances Plants & Agriculture Research 7(3): 279‒286. doi:10.15406/apar.2017.07.00255
• Blake T, Blake V, Bowman J & Abdel-Haleem H (2011). In Barley: Production, Improvement and Uses (ed. S. E. Ullrich) 522–531 (Wiley-Blackwell)
• Collard B C Y & 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(1): 86–93
• Dice L R (1945). Measures of the amount of ecologic association between species. Ecology 26: 297-302
• Dora S A, Mansour M, Aboulila A A & Abdelwahab E (2017). Genetic diversity and relationships among some barley genotypes for Net Blotch Disease Resistance using RAPD, SCoT and SSR Markers. Egyptian Journal of Genetics and Cytology 46(1): 139-165. doi: 10.21608/EJGC.2018.9510
• Dumlupınar Z., Jellen E N, Bonman J M & Jackson E W (2016). Genetic diversity and crown rust resistance of oat landracesfrom various locations throughout Turkey. Turkish Journal of Agriculture and Forestry 40(2): 262-268
• Kiraz H, Yüce İ, Kaya E, Kekilli Ö, Ocaktan H, Topsakal M, Gürocak N Y, Osanmaz H, Kılınç F M, Başkonuş T & Dumlupınar Z (2019). Characterization of M3 mutants of Seri 82 bread wheat cultivar using functional markers. Black Sea Journal of Agriculture 2(4): 194-202
• Earl D A & vonHoldt B M (2012). STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetics Resources, 4 (2): 359-361
• Elakhdar A, Abdelsattar M, Amer K, Assma R & Kumamaru T (2016). Population structure and marker-trait association of salt tolerance in barley (Hordeum vulgare L.). Comptes Rendus Biologies 339 (11-12): 454-461
• Elakhdar A, Kumamaru T, Qualset C O, Brueggeman R S, Amer K & Capo-chichi L (2018). Assessment of genetic diversity in Egyptian barley (Hordeum vulgare L.) genotypes using SSR and SNP markers. Genetic Resources and Crop Evolution, 65(7): 1937-1951. doi: 10.1007/s10722-018-0666-x
• Etminan A, Pour-Aboughadareh A, Mohammadi R, Ahmadi-Rad A, Noori A, Mahdavian Z & Moradi Z (2016). Applicability of start codon targeted (SCoT) and inter-simple sequence repeat (ISSR) markers for genetic diversity analysis in durum wheat genotypes. Biotechnology & Biotechnological Equipment 30(6): 1075-1081. doi: 10.1080/13102818.2016.1228478
• Evanno G, Regnaut S & Goudet J (2005). Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Molecular Ecology 14(8): 2611-2620. doi: 10.1111/j.1365-294X.2005.02553.x
• Falush D, Stephens M & Pritchard J K (2003). Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164(4): 1567–1587
• Flavell A J, Dunbar E, Anderson R, Pearce SR, Hartley R & Kumar A (1992). Ty1-copia group retrotransposons are ubiquitous and heterogeneous in higher plants. Nucleic Acids Research 20(14): 3639–3644. Doi: 10.1093/nar/20.14.3639
• Govindaraj M, Vetriventhan M & 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: 1-14
• Güngör H (2019). Allelic variations and agronomic comparisons of durum wheat cultivars under East-Mediterranean conditions. International Journal of Agriculture And Biology 21(4): 891-898. Doi: 10.17957/IJAB/15.0972
• Hamrick J L, Godt M J W & Sherman-Broyles S L (1992). Factors influencing levels of genetic diversity in woody plant species. New Forests 6: 95–124
• Hossein-Pour A, Haliloglu K, Ozkan G & Tan M (2019). Genetic diversity and population structure of Quinoa (CHENOPODIUM QUINOA Willd.) usıng iPBS-retrotransposons markers. Applied Ecology And Environmental Research 17(2): 1899-1911. Doi: 10.15666/aeer/1702_18991911
• Kalendar R, Antonius K, Smýkal P & Schulman A H (2010). iPBS: a universal method for DNA fingerprinting and retrotransposon isolation. Theoretical and Applied Genetics 121 (8): 1419-1430. doi:10.1007/s00122-010-1398-2
• Karagoz H, Cakmakci R, Hosseinpour A, Ozkan G & Haliloglu K (2020). Analysis of genetic variation and population structure among of oregano (Origanum acutidens L.) accessions revealed by agro-morphological traits, oil constituents and retrotransposon-based inter-primer binding sites (iPBS) markers. Genetic Resources and Crop Evolution, 67: 1367-1384
• Khodayari H, Saeidi H, Roofigar A A, Rahiminejad M R, Pourkheirandish M & Komatsuda T (2012). Genetic diversity of cultivated barley landraces in Iran measured using microsatellites. International Journal of Bioscience, Biochemistry and Bioinformatics 2(4): 287-290. doi: 10.7763/IJBBB.2012.V2.118
• Kimura M & Crow J F (1964). The number of alleles that can be maintained in a finite population. Genetics 49:725-738
• Kimura M (1965). A stochastic model concerning the maintenance of genetic variability in quantitative characters. Proceedings of the National Academy of Sciences of the United States of America 54 (3): 731-736. doi:10.1073/pnas.54.3.731
• Kumar A & Bennetzen J L (1999). Plant retrotransposons. Annu Rev Genet 33: 479-532
• Lewontin R C (1972). Testing the theory of natural selection. Nature 236:181-182
• Luo C, He X-H, Chen H, Ou S-J & Gao M-P (2010). Analysis of diversity and relationships among cultivars using start codon targeted (SCoT) markers. Biochemical Systematics and Ecology 38: 1176-1184
• Mahjbi A, Baraket G, Oueslati A & Salhi-Hannachi A (2015). Start Codon Targeted (SCoT) markers provide new insights into the genetic diversity analysis and characterization of Tunisian Citrus species. Biochemical Systematics and Ecology 61: 390-398
• Moragues M, Moralejo M, Sorrells M E & Royo C (2007). Dispersal of durum wheat [Triticum turgidum L. Ssp. turgidum Convar. Durum (Desf.) MacKey] landraces across The mediterranean basin assessed by AFLPs and Microsatellites. Genetic Resources and Crop Evolution 54: 1133-1144
• Montilla-Bascon G, Sanchez-Martin J, Rispail N, Rubiales D, Mur L, Langdon T, Griffiths I, Howarth C & Parts E (2013). Genetic diversity and population structure among oat cultivars and landraces. Plant Molecular Biology Reporter 31: 1305-1314. Doi:10.1007/s11105-013-0598-8
• Munoz-Amatriain M, Cuesta-Marcos A, Endelman J B, Comadran J, Bonman J M, Bockelman H E, Chao S, Russell J, Waugh R, Hayes P M & Muehlbauer G J (2014). The USDA barley core collection: genetic diversity, population structure, and potential for genome-wide association studies. PLoS ONE 9:e94688. https://doi.org/10.1371/journal.pone.0094688
• Nemli S, Kianoosh T & Tanyolaç M B (2015). Genetic diversity and population structure of common bean (Phaseolus vulgaris L.) accessions through retrotransposon-based interprimer binding sites (iPBSs) markers. Turkish Journal of Agriculture and Forestry 39: 940-948
• Oliver R E, Obert D E, Hu G, Bonman J M, O’Leary-Jepsen E & Jackson E W (2010). Development of oat-based markers from barley and wheat microsatellites. Genome 53 (6): 458-471
• Orabi J, Jahoor A& Backes G (2009). Genetic diversity and population structure of wild and cultivated barley from West Asia and North Africa. Plant Breeding 128(6): 606-614
• Pakseresht F, Talebi R & Karami E (2013). Comparative assessment of ISSR, DAMD and SCoT markers for evaluation of genetic diversity and conservation of landrace chickpea (Cicer arietinum L.) genotypes collected from north-west of Iran. Physiology and Molecular Biology of Plants 19: 563-574
• Pandey M, Wagner C, Friedt W & Ordon F (2006) Genetic relatedness and population differentiation of Himalayan hulless barley (Hordeum vulgare L.) landraces inferred with SSRs. Theoretical and Applied Genetics 113:715–729
• Pasam R K, Sharma R, Walther A, Özkan H, Graner A & Kilian B (2014). Genetic diversity and population structure in a legacy collection of spring barley landraces adapted to a wide range of climates. PLoS One 9(12): e116164
• Pompanon F, Bonin A, Bellemain E & Taberlet P (2005) Genotyping errors: causes, consequences and solutions. Nat Rev Genet 6:846–847. doi:10.1038/nrg1707
• Rohlf F J (1998). NTSYS-pc. Numerical Taxonomy and Multivariate Analysis System. Version 2.02. Setauker, NY, USA: Exeter Pulications.
• Romero M, Sanchez A M M, Pineda E, Ccamapaza Y & Zavalla N (2019). Genetic identity based on simple sequence repeat (SSR) markers for quinoa (Chenopodium quinoa Willd.). Ciencia e Investigación Agraria 46 (2): 166-178
• The International Barley Genome Sequencing Consortium (2012). A physical, genetic and functional sequence assembly of the barley genome. Nature 491:711-6
• Wang N, Ning S, Pourkheirandish M, Honda I & Komatsuda T (2013). An alternative mechanism for cleistogamyin barley. Theoretical and Applied Genetics 126: 2753–2762
• Weir B S (1996). Genetic Data Analysis II, 2nd ed. Sunderland, Massachusetts, USA: Sinauer Associates Inc.
• Yaldız G, Camlica M, Nadeem M A, Nawaz M A & Baloch F S (2018). Genetic diversity assessment in Nicotiana tabacum L. with iPBS-retrotransposons. Turkish Journal of Agriculture and Forestry 42: 154-164
• Yeh F C, Yang R, Boyle T J, Ye Z & Xiyan J M (2000). PopGene32, Microsoft Windows-based freeware for population genetic analysis, version 1.32. Molecular Biology and Biotechnology Centre, University of Alberta, Edmonton, Alberta, Canada.
• Yıldız M, Koçak M & Baloch F S (2015). Genetic bottlenecks in Turkish okra germplasm and utility of iPBS retrotransposon markers for genetic diversity assessment. Genetics and Molecular Research 14(3): 10588-10602
• Yıldız M., Koçak M, Nadeem M A, Cavagnaro P, Barboza K, Baloch F S, Argün D & Keleş D (2020). Genetic diversity analysis in the Turkish pepper germplasm using iPBS retrotransposon-based markers. Turkish Journal of Agriculture and Forestry 44(1): 1-14. doi:10.3906/tar-1902-10
• Zhang M, Mao W, Zhang G & Wu F (2014). Development and characterization of polymorphic EST-SSR and genomic SSR markers for Tibetan annual wild barley. PLoS ONE 9:e94881. https://doi.org/10.1371/journal.pone.0094881