Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-23T09:25:51.478Z Has data issue: false hasContentIssue false
  • English
  • Français

Evolution of a barley composite cross-derived population: an insight gained by molecular markers

Published online by Cambridge University Press:  08 January 2015

L. RAGGI ,
S. CECCARELLI  and
V. NEGRI
L. RAGGI
Affiliation:
Dipartimento di Scienze Agrarie, Alimentari e Ambientali, Università degli Studi di Perugia, Borgo XX Giugno 74, 06121 Perugia, Italy
S. CECCARELLI
Affiliation:
ICARDA, P.O. Box 114/5055, Beirut, Lebanon / 2Via delle Begonie 2, 63100 Ascoli Piceno, Italy
V. NEGRI*
Affiliation:
Dipartimento di Scienze Agrarie, Alimentari e Ambientali, Università degli Studi di Perugia, Borgo XX Giugno 74, 06121 Perugia, Italy
*
*To whom all correspondence should be addressed. Email: valeria.negri@unipg.it
Get access Rights & Permissions [Opens in a new window]

Summary

Many studies have highlighted the continuously increasing need for genetic diversity in the field; nonetheless, plant breeding is still predominantly generating uniform cultivars. Evolutionary plant breeding offers the possibility of reconciling agro-biodiversity, high yields and adaptation to climate change. However, the diversity that can be conserved in heterogeneous populations, its evolution and the potential of ‘evolutionary breeding’ in the actual scenario of climate change is still a matter of debate. In the present study, a total of 147 barley individuals, 56 from seven parental populations (PPs) and 91 from the composite cross-derived population (CCP) resulting from their inter-crossing were genotyped at 22 Simple Sequence Repeat (SSR) loci with the objective of obtaining insights into how genetic diversity evolved in the field during 13 years of multiplication. A total of 92 different alleles were detected in the PP and 100 in the CCP. Results showed that the composite individuals are grouped into five major clusters differing for both the number of individuals and the relative level of genetic diversity. The mean values of the most common descriptors of genetic diversity were not significantly different between the parental and the composite populations. However, analysis of molecular variance showed some degree of differentiation between the two populations suggesting that evolution occurred during the years of multiplication and selection effects were detected for some loci. The SSR loci detected as putatively under selection in the present study have already been reported as co-localized with quantitative trait loci for adaptedness traits or tagging genes related to abiotic stress response. According to the current results, evolving crop populations, which have the capability of adapting to the conditions under which they are grown, can be useful in conserving genetic diversity and as sources of genes for breeding purposes in particular in the actual scenario of climate change.

Type
Crops and Soils Research Papers
Information
The Journal of Agricultural Science , Volume 154 , Issue 1 , January 2016 , pp. 23 - 39
Check for updates
Copyright
Copyright © Cambridge University Press 2015 

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

REFERENCES

Allard, R. W. (1988). Genetic changes associated with the evolution of adaptedness in cultivated plants and their wild progenitors. Journal of Heredity 79, 225–238.CrossRefGoogle ScholarPubMed
Allard, R. W. (1996). Genetic basis of the evolution of adaptedness in plants. Euphytica 92, 1–11.CrossRefGoogle Scholar
Allard, R. W. & Hansche, P. E. (1964). Some parameters of population variability and their implications in plant breeding. Advances in Agronomy 16, 281–325.CrossRefGoogle Scholar
Andris, M., Arias, M. C., Barthel, B. L., Bluhm, B. H., Bried, J., Canal, D., Chen, X. M., Cheng, P., Chiappero, M. B., Coelho, M. M., Collins, A. B., Dash, M., Davis, M. C., Duarte, M., Dubois, M.-P., Françoso, E., Galmes, M. A., Gopal, K., Jarne, P., Kalbe, M., Karczmarski, L., Kim, H., Martella, M. B., McBride, R. S., Negri, V., Negro, J. J., Newell, A. D., Piedade, A. F., Puchulutegui, C., Raggi, L., Samonte, I. E., Sarasola, J. H., See, D. R., Seyoum, S., Silva, M. C., Solaro, C., Tolley, K. A., Tringali, M. D., Vasemägi, A., Xu, L. S. & Zanón-Martínez, J. I. (2012). Permanent genetic resources added to Molecular Ecology Resources Database 1 February 2012–31 March 2012. Molecular Ecology Resources 12, 779–781.Google Scholar
Blijenburg, J. G. & Sneep, J. (1975). Natural selection in a mixture of eight barley varieties, grown in six successive years. 1. Competition between the varieties. Euphytica 24, 305–315.CrossRefGoogle Scholar
Cardinale, B. J., Duffy, J. E., Gonzalez, A., Hooper, D. U., Perrings, C., Venail, P., Narwani, A., Mace, G. M., Tilman, D., Wardle, D. A., Kinzig, A. P., Daily, G. C., Loreau, M., Grace, J. B., Larigauderie, A., Srivastava, D. S. & Naeem, S. (2012). Biodiversity loss and its impact on humanity. Nature 486, 59–67.CrossRefGoogle ScholarPubMed
Cattivelli, L., Baldi, P., Crosatti, C., Di Fonzo, N., Faccioli, P., Grossi, M., Mastrangelo, A. M., Pecchioni, N. & Stanca, A. M. (2002). Chromosome regions and stress-related sequences involved in resistance to abiotic stress in Triticeae. Plant Molecular Biology 48, 649–665.CrossRefGoogle Scholar
Ceccarelli, s. (2014). GM crops, organic agriculture and breeding for sustainability. Sustainability 6, 4273–4286.CrossRefGoogle Scholar
Ceccarelli, S., Galie, A. & Grando, S. (2013). Participatory breeding for climate change-related traits. In Genomics and Breeding for Climate-Resilient Crops, Vol. 1 (Ed. Kole, C.), pp. 331–376. Berlin: Springer-Verlag.CrossRefGoogle Scholar
Chabane, K., Ablett, G. A., Cordeiro, G. M., Valkoun, J. & Henry, R. J. (2005). EST versus genomic derived microsatellite markers for genotyping wild and cultivated barley. Genetic Resources and Crop Evolution 52, 903–909.CrossRefGoogle Scholar
Colwell, R. K. & Coddington, J. A. (1994). Estimating terrestrial biodiversity through extrapolation. Philosophical Transactions of the Royal Society B: Biological Sciences 345, 101–118.Google ScholarPubMed
Comadran, J., Kilian, B., Russell, J., Ramsay, L., Stein, N., Ganal, M., Shaw, P., Bayer, M., Thomas, W., Marshall, D., Hedley, P., Tondelli, A., Pecchioni, N., Francia, E., Korzun, V., Walther, A. & Waugh, R. (2012). Natural variation in a homolog of Antirrhinum centroradialis contributed to spring growth habit and environmental adaptation in cultivated barley. Nature Genetics 44, 1388–1392.CrossRefGoogle Scholar
Cornuet, J. M., Aulagnier, S., Lek, S., Franck, S. & Solignac, M. (1996). Classifying individuals among infra-specific taxa using microsatellite data and neural networks. Comptes Rendus de l'Académie des Sciences. Série III, Sciences de la Vie 319, 1167–1177.Google ScholarPubMed
Cornuet, J. M., Piry, S., Luikart, G., Estoup, A. & Solignac, M. (1999). New methods employing multilocus genotypes to select or exclude populations as origins of individuals. Genetics 153, 1989–2000.CrossRefGoogle ScholarPubMed
Crow, J. F. (1992). An advantage of sexual reproduction in a rapidly changing environment. Journal of Heredity 83, 169–173.CrossRefGoogle Scholar
Döring, T. F., Knapp, S., Kovacs, G., Murphy, K. & Wolfe, M. S. (2011). Evolutionary plant breeding in cereals-into a new era. Sustainability 3, 1944–1971.CrossRefGoogle Scholar
Enjalbert, J., Boeuf, C., Belcram, H. & Leroy, P. (1999 a). Use of multiparental inbred populations to determine allelic relationships of molecular markers. Plant Breeding 118, 88–90.CrossRefGoogle Scholar
Enjalbert, J., Goldringer, I., Paillard, S. & Brabant, P. (1999 b). Molecular markers to study genetic drift and selection in wheat populations. Journal of Experimental Botany 50, 283–290.CrossRefGoogle Scholar
Enjalbert, J., Dawson, J. C., Paillard, S., Rhoné, B., Rousselle, Y., Thomas, M. & Goldringer, I. (2011). Dynamic management of crop diversity: from an experimental approach to on-farm conservation. Comptes Rendus Biologies 334, 458–468.CrossRefGoogle ScholarPubMed
Esquinas-Alcázar, J. (2005). Science and society: protecting crop genetic diversity for food security: political, ethical and technical challenges. Nature Reviews Genetics 6, 946–953.CrossRefGoogle ScholarPubMed
Francia, E., Barabaschi, D., Tondelli, A., Laidò, G., Rizza, F., Stanca, A. M., Busconi, M., Fogher, C., Stockinger, E. J. & Pecchioni, N. (2007). Fine mapping of a HvCBF gene cluster at the frost resistance locus Fr-H2 in barley. Theoretical and Applied Genetics 115, 1083–1091.CrossRefGoogle ScholarPubMed
Gupta, P. K. & Varshney, R. K. (2000). The development and use of microsatellite markers for genetic analysis and plant breeding with emphasis on bread wheat. Euphytica 113, 163–185.CrossRefGoogle Scholar
Hajjar, R. & Hodgkin, T. (2007). The use of wild relatives in crop improvement: a survey of developments over the last 20 years. Euphytica 156, 1–13.CrossRefGoogle Scholar
Hale, M. L., Burg, T. M. & Steeves, T. E. (2012). Sampling for microsatellite-based population genetic studies: 25 to 30 individuals per population is enough to accurately estimate allele frequencies. PLoS ONE 7, e45170.CrossRefGoogle ScholarPubMed
Hammer, Ø., Harper, D. A. T. & Ryan, P. D. (2001). PAST: paleontological statistics software package for education and data analysis. Palaeontologia Electronica 4, 1–9.Google Scholar
Harlan, H. V. & Martini, M. L. (1929). A composite hybrid mixture. Agronomy Journal 21, 487–490.CrossRefGoogle Scholar
Harlan, H. V. & Martini, M. L. (1938). The effect of natural selection in a mixture of barley varieties. Journal of Agricultural Research 57, 189–199.Google Scholar
Hooper, D. U., Adair, E. C., Cardinale, B. J., Byrnes, J. E. K., Hungate, B. A., Matulich, K. L., Gonzalez, A., Duffy, J. E., Gamfeldt, L. & O'Connor, M. I. (2012). A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature 486, 105–108.CrossRefGoogle Scholar
Ibrahim, K. M., Hayter, J. B. R. & Barrett, J. A. (1996). Frequency changes in storage protein genes in a hybrid bulk population of barley. Heredity 77, 231–239.CrossRefGoogle Scholar
Kalia, R. K., Rai, M. K., Kalia, S., Singh, R. & Dhawan, A. K. (2011). Microsatellite markers: an overview of the recent progress in plants. Euphytica 177, 309–334.CrossRefGoogle Scholar
Keneni, G., Bekele, E., Imtiaz, M. & Dagne, K. (2012). Genetic vulnerability of modern crop cultivars: causes, mechanism and remedies. International Journal of Plant Research 2, 69–79.CrossRefGoogle Scholar
Mak, C. & Harvey, B. L. (1982). Exploitable genetic variation in a composite bulk population of barley. Euphytica 31, 85–92.CrossRefGoogle Scholar
Malysheva-Otto, L. V., Ganal, M. W. & Röder, M. S. (2006). Analysis of molecular diversity, population structure and linkage disequilibrium in a worldwide survey of cultivated barley germplasm (Hordeum vulgare L.). BMC Genetics 7, 6.CrossRefGoogle Scholar
Maynard Smith, J. (1978). The Evolution of Sex. Cambridge, UK: Cambridge University Press.Google Scholar
Melo, A. S., Pereira, R. A. S., Santos, A. J., Shepherd, G. J., Machado, G., Medeiros, H. F. & Sawaya, R. J. (2003). Comparing species richness among assemblages using sample units: why not use extrapolation methods to standardize different sample sizes? Oikos 101, 398–410.CrossRefGoogle Scholar
Mohammed, K. A. H. (2004). Improving crop varieties of spring barley for drought and heat tolerance with AB-QTLanalysis. Ph.D. Thesis, University of Bonn, Germany.Google Scholar
Morran, L. T., Parmenter, M. D. & Phillips, P. C. (2009). Mutation load and rapid adaptation favour outcrossing over self-fertilization. Nature 462, 350–352.CrossRefGoogle ScholarPubMed
Negri, V. & Petti, R. (1995). Fonti germoplasma non adattato per la selezione di varietà adatte all'agricoltura biologica: il lavoro dell'Istituto di Miglioramento Genetico Vegetale di Perugia sull'orzo. In Atti del Convegno Agricoltura Biologica in Italia: Aspetti Tecnici, Economici e Normativi (Eds Santucci, F. & Zanoli, R.), pp. 185–196. Ancona, Italy: Centro Stampa Consiglio Regionale delle Marche.Google Scholar
Paetkau, D., Calvert, W., Stirling, I. & Strobeck, C. (1995). Microsatellite analysis of population structure in Canadian polar bears. Molecular Ecology 4, 347–354.CrossRefGoogle ScholarPubMed
Peakall, R. & Smouse, P. E. (2006). GenAlex 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6, 288–295.CrossRefGoogle Scholar
Peakall, R., Smouse, P. E. & Huff, D. R. (1995). Evolutionary implications of allozyme and RAPD variation in diploid populations of dioecious buffalograss Buchloë dactyloides. Molecular Ecology 4, 135–148.CrossRefGoogle Scholar
Phillips, S. L. & Wolfe, M. S. (2005). Evolutionary plant breeding for low input systems. Journal of Agricultural Science, Cambridge 143, 245–254.CrossRefGoogle Scholar
Powell, W., Machray, G. C. & Provan, J. (1996). Polymorphism revealed by simple sequence repeats. Trends in Plant Science 1, 215–222.CrossRefGoogle Scholar
Pritchard, J. K., Stephens, M. & Donnelly, P. (2000). Inference of population structure using multilocus genotype data. Genetics 155, 945–959.CrossRefGoogle ScholarPubMed
Ramsay, L., Macaulay, M., Ivanissevich, D. S., MacLean, K., Cardle, L., Fuller, J., Edwards, K. J., Tuvesson, S., Morgante, M., Massari, A., Maestri, E., Marmiroli, N., Sjakste, T., Ganal, M., Powell, W. & Waugh, R. (2000). A simple sequence repeat-based linkage map of barley. Genetics 156, 1997–2005.CrossRefGoogle ScholarPubMed
Rannala, B. & Mountain, J. L. (1997). Detecting immigration by using multilocus genotypes. Proceedings of the National Academy of Sciences of the United States of America 94, 9197–9201.CrossRefGoogle ScholarPubMed
Raquin, A.-L., Brabant, P., Rhoné, B., Balfourier, F., Leroy, P. & Goldringer, I. (2008). Soft selective sweep near a gene that increases plant height in wheat. Molecular Ecology 17, 741–756.CrossRefGoogle Scholar
Rhoné, B., Remoué, C., Galic, N., Goldringer, I. & Bonnin, I. (2008). Insight into the genetic bases of climatic adaptation in experimentally evolving wheat populations. Molecular Ecology 17, 930–943.CrossRefGoogle ScholarPubMed
Rollins, J. A., Drosse, B., Mulki, M. A., Grando, S., Baum, M., Singh, M., Ceccarelli, S. & von Korff, M. (2013). Variation at the vernalisation genes Vrn-H1 and Vrn-H2 determines growth and yield stability in barley (Hordeum vulgare) grown under dryland conditions in Syria. Theoretical and Applied Genetics 126, 2803–2824.CrossRefGoogle ScholarPubMed
Rousselle, Y., Thomas, M., Galic, N., Bonnin, I. & Goldringer, I. (2011). Inbreeding depression and low between-population heterosis in recently diverged experimental populations of a selfing species. Heredity (Edinburgh) 106, 289–299.CrossRefGoogle ScholarPubMed
Schlötterer, C. (2002). A microsatellite-based multilocus screen for the identification of local selective sweeps. Genetics 160, 753–763.CrossRefGoogle ScholarPubMed
Schlötterer, C. & Dieringer, D. (2005). A novel test statistic for the identification of local selective sweeps based on microsatellite gene diversity. In Selective Sweep (Ed. Nurminsky, D.), pp. 55–64. New York: Kluwer Academic/Plenum Publishers.CrossRefGoogle Scholar
Smouse, P. E. & Peakall, R. (1999). Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure. Heredity (Edinburgh) 82, 561–573.CrossRefGoogle ScholarPubMed
Stebbins, G. L. (1957). Self fertilization and population variability in the higher plants. American Naturalist 91, 337–354.CrossRefGoogle Scholar
Suneson, C. A. (1956). An evolutionary plant breeding method. Agronomy Journal 48, 188–191.CrossRefGoogle Scholar
Suneson, C. A. (1969). Registration of barley composite crosses1 (Reg. Nos. GP 1 to 9, inclusive). Crop Science 9, 395–396.CrossRefGoogle Scholar
Suneson, C. A. & Wiebe, G. A. (1942). Survival of barley and wheat varieties in mixtures. Agronomy Journal 34, 1052–1056.CrossRefGoogle Scholar
Tamura, K., Dudley, J., Nei, M. & Kumar, S. (2007). MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Molecular Biology and Evolution 24, 1596–1599.CrossRefGoogle ScholarPubMed
Thiel, T., Michalek, W., Varshney, R. K. & Graner, A. (2003). Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theoretical and Applied Genetics 106, 411–422.CrossRefGoogle ScholarPubMed
Tondelli, A., Francia, E., Barabaschi, D., Aprile, A., Skinner, J. S., Stockinger, E. J., Stanca, A. M. & Pecchioni, N. (2006). Mapping regulatory genes as candidates for cold and drought stress tolerance in barley. Theoretical and Applied Genetics 112, 445–454.CrossRefGoogle ScholarPubMed
Van Loon, E. E., Cleary, D. F. R. & Fauvelot, C. (2007). ARES: software to compare allelic richness between uneven samples. Molecular Ecology Notes 7, 579–582.CrossRefGoogle Scholar
Varshney, R. K., Grosse, I., Hähnel, U., Siefken, R., Prasad, M., Stein, N., Langridge, P., Altschmied, L. & Graner, A. (2006). Genetic mapping and BAC assignment of EST-derived SSR markers shows non-uniform distribution of genes in the barley genome. Theoretical and Applied Genetics 113, 239–250.CrossRefGoogle ScholarPubMed
Varshney, R. K., Marcel, T. C., Ramsay, L., Russell, J., Röder, M. S., Stein, N., Waugh, R., Langridge, P., Niks, R. E. & Graner, A. (2007). A high density barley microsatellite consensus map with 775 SSR loci. Theoretical and Applied Genetics 114, 1091–1103.CrossRefGoogle ScholarPubMed
Varshney, R. K., Baum, M., Guo, P., Grando, S., Ceccarelli, S. & Graner, A. (2010). Features of SNP and SSR diversity in a set of ICARDA barley germplasm collection. Molecular Breeding 26, 229–242.CrossRefGoogle Scholar
Vitalis, R. (2003). DetSel 1.0: a computer program to detect markers responding to selection. Journal of Heredity 94, 429–431.CrossRefGoogle ScholarPubMed
Vitalis, R., Dawson, K. & Boursot, P. (2001). Interpretation of variation across marker loci as evidence of selection. Genetics 158, 1811–1823.CrossRefGoogle ScholarPubMed