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Correspondence between genetic structure and farmers' taxonomy – a case study from dry-season sorghum landraces in northern Cameroon

Published online by Cambridge University Press:  29 November 2012

Clelia Soler ,
Abdoul-Aziz Saidou ,
Tuong Vi Cao Hamadou ,
Marco Pautasso ,
Jean Wencelius  and
Hélène H. I. Joly
Clelia Soler*
Affiliation:
CIRAD, UMR CEFE, Campus du CNRS, 1919 route de Mende, 34293Montpellier cedex 5, France
Abdoul-Aziz Saidou
Affiliation:
CIRAD, UMR CEFE, Campus du CNRS, 1919 route de Mende, 34293Montpellier cedex 5, France Institut Supérieur du Sahel, Université de Maroua, BP 46, Maroua, Cameroon
Tuong Vi Cao Hamadou
Affiliation:
CIRAD, UMR AGAP, Campus Agropolis, 34398Montpellier, France
Marco Pautasso
Affiliation:
UMR 5175 CNRS CEFE, Campus CNRS, 1919 route de Mende, 34293Montpellier, France FRB, Centre de Synthèse et d'Analyse sur la Biodiversité (CESAB), 13857Aix-en-Provence, France
Jean Wencelius
Affiliation:
CNRS, UMR LESC, Laboratoire d'Ethnologie et de Sociologie Comparative, 21 allée de l'Université, 92023Nanterre, France
Hélène H. I. Joly
Affiliation:
CIRAD, UMR CEFE, Campus du CNRS, 1919 route de Mende, 34293Montpellier cedex 5, France
*
*Corresponding author. E-mail: [email protected]
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Abstract

The study of the genetic structure of cultivated plant populations maintained by farmers is of great importance for evolutionary and conservation biology. Such studies help understand the bases of crop evolution and conservation in relation to farmers' practices. In this study, we assessed the genetic structure underlying landrace diversity of dry-season sorghum. This crop constitutes a historical model of innovation developed by farmers to extend sorghum cultivation to the dry season. Two types of dry-season sorghum are cultivated. We aimed to assess the link between farmers' taxonomy and molecular genetic structure. We collected both types of dry-season sorghum in two villages of northern Cameroon which represented 20 landraces. These landraces were genotyped using eight polymorphic microsatellite markers. This study compared two clustering methods: a Bayesian method (STRUCTURE) which is based on explicit genetic assumptions and the discriminant analysis of principal component method. The latter, more recently proposed, is based on the combination of principal component analysis and discriminant analysis. We noticed a general congruence between these two methods. We also used both methods to infer the genetic structure of our sample. Our results showed strong genetic structuring of the landraces, with K= 14 genetic clusters. We then analysed the fit between farmers' taxonomy and genetic structure. The data suggested that each type and each landrace corresponds to a given genetic entity. This pattern was robust across both villages, despite differences in cultural practices.

Keywords

farmer's practicesgenetic diversitymultivariate analysissimple sequence repeatsorghumstructure inference
Type
Research Article
Information
Plant Genetic Resources , Volume 11 , Issue 1 , April 2013 , pp. 36 - 49
Copyright
Copyright © NIAB 2012

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References

Barnaud, A, Deu, M, Garine, E, McKey, D and Joly, HI (2007) Local genetic diversity of sorghum in a village in northern Cameroon: structure and dynamics of landraces. Theoretical and Applied Genetics 114: 237–248.Google Scholar
Barnaud, A, Deu, M, Garine, E, Chantereau, J, Justin, B, Koïda, OE, McKey, D and Joly, HI (2009) A weed-crop complex in Sorghum: the dynamics of genetic diversity in a traditional farming system. American Journal of Botany 96: 1869–1879.Google Scholar
Barnaud, A, Trigueros, G, McKey, D and Joly, HI (2008) High outcrossing rates in fields with mixed sorghum landraces: how are landraces maintained? Heredity 101: 445–452.Google Scholar
Barro-Kondombo, C, Sagnard, F, Chantereau, J, Deu, M, Vom Brocke, K, Durand, P, Gozé, E and Zongo, D (2010) Genetic structure among sorghum landraces as revealed by morphological variation and microsatellite markers in three agroclimatic regions of Burkina Faso. Theoretical and Applied Genetics 120: 1511–1523.CrossRefGoogle ScholarPubMed
Belkhir, K, Castric, V and Bonhomme, F (2002) IDENTIX, a software to test for relatedness in a population using permutation methods. Molecular Ecology Notes 2: 611–614.CrossRefGoogle Scholar
Bhosale, SU, Stich, B, Rattunde, HFW, Weltzien Rattunde, E, Haussmann, BI, Hash, CT, Melchinger, AE and Parzies, HK (2011) Population structure in sorghum accessions from West Africa differing in race and maturity class. Genetica 139: 453–463. DOI: 10.1007/s10709-011-9564-2.CrossRefGoogle ScholarPubMed
Blair, C, Weigel, DE, Balazik, M, Keeley, ATH, Walker, FM, Landguth, E, Cushman, S, Murphy, M, Waits, L and Balkenhol, N (2012) A simulation-based evaluation of methods for inferring linear barriers to gene flow. Molecular Ecology Resources 12: 822–833. DOI: 10.1111/j.1755-0998.2012.03151.Google Scholar
Bouchet, S, Pot, D, Deu, M, Rami, JF, Billot, C, Perrier, X, Rivallan, R, Gardes, L, Xia, L, Wenzl, P, Kilian, A and Glaszmann, JC (2012) Genetic structure, linkage disequilibrium and signature of selection in Sorghum: lessons from physically anchored DArT markers. PLoS One 7: e33470.Google Scholar
Casa, AM, Mitchell, SE, Hamblin, MT, Sun, H, Bowers, JE, Paterson, AH, Aquadro, CF and Kresovich, S (2005) Diversity and selection in sorghum: simultaneous analyses using simple sequence repeats. Theoretical and Applied Genetics 111: 23–30.Google Scholar
De Garine, I (1993) Coping strategies in case of hunger of the most vulnerable groups among the Massa and Mussey of Northern Cameroon. GeoJournal 30: 159–166.Google Scholar
De Garine, I and De Garine, V (2001) Drinking: Anthropological Approaches. New York, NY: Berghahn Books, pp. 58.Google Scholar
Deu, M, Rattunde, F and Chantereau, J (2006) A global view of genetic diversity in cultivated sorghum using a core collection. Genome 49: 168–180.CrossRefGoogle ScholarPubMed
Deu, M, Sagnard, F, Chantereau, J, Calatayud, C, Hérault, D, Mariac, C, Pham, JL, Vigouroux, Y, Kapran, I, Traore, PS, Mamadou, A, Gerard, B, Ndjeunga, J and Bezançon, G (2008) Niger-wide assessment of in situ sorghum genetic diversity with microsatellite markers. Theoretical and Applied Genetics 116: 903–913.Google Scholar
Deu, M, Sagnard, F, Chantereau, J, Calatayud, C, Vigouroux, Y, Pham, JL, Mariac, C, Kapran, I, Mamadou, A, Gérard, B, Ndjeunga, J and Bezancon, G (2010) Spatio-temporal dynamics of genetic diversity in Sorghum bicolor in Niger. Theoretical and Applied Genetics 120: 1301–1313.Google Scholar
Djè, Y, Heuertz, M, Ater, M, Lefèbre, C and Vekemans, X (2004) In situ estimation of outcrossing rate in sorghum landraces using microsatellite markers. Euphytica 138: 205–212.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: 2611–2620.CrossRefGoogle ScholarPubMed
Excoffier, L, Laval, G and Schneider, S (2005) Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online 1: 47–50.Google Scholar
Falush, D, Stephens, M and Pritchard, JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164: 1567–1587.CrossRefGoogle ScholarPubMed
Francois, O and Durand, E (2010) Spatially explicit Bayesian clustering models in population genetics. Molecular Ecology Resources 10: 773–784.CrossRefGoogle ScholarPubMed
Gao, H, Williamson, S and Bustamante, CD (2007) A Markov chain Monte Carlo approach for joint inference of population structure and inbreeding rates from multilocus genotype data. Genetics 176: 1635–1651.CrossRefGoogle ScholarPubMed
Ghebru, B, Schmidt, RJ and Bennetzen, JL (2002) Genetic diversity of Eritrean sorghum landraces assessed with simple sequence repeat (SSR) markers. Theoretical and Applied Genetics 105: 229–236.Google Scholar
Goudet J (2002) FSTAT: program to estimate and test gene diversities and fixation indices (version 2.9.3.2). Available at http://www2.unil.ch/popgen/softwares/fstat.htm.Google Scholar
Harlan, JR and de Wet, JMJ (1972) A simplified classification of cultivated sorghum. Crop Science 12: 172–176.CrossRefGoogle Scholar
Jombart, T (2008) Adegenet: R package for the multivariate analysis of genetic markers. Bioinformatics 24: 1403–1405.Google Scholar
Jombart, T, Devillard, S and Balloux, F (2010) Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genetics 11: 94.CrossRefGoogle ScholarPubMed
Legendre, P and Legendre, L (1998) Numerical Ecology. 2nd edn.Amsterdam: Elsevier Science BV.Google Scholar
Nei, M (1978) Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89: 583–590.Google Scholar
Ng'uni D (2011) Phylogenetics of the genus sorghum, genetic diversity and nutritional value of its cultivated species. PhD Thesis, University of Alnarp (Sweden), p. 59.Google Scholar
Ollitrault P (1987) Evaluation génétique des sorghos cultivés (Sorghum bicolor L. Moench) par l'analyse conjointe des diversités enzymatique et morphophysiologique. Relations avec les sorghos sauvages. PhD Thesis, University of Montpellier.Google Scholar
Perrier, X, Flori, A and Bonnot, F (2003) Data analysis methods. In: Hamon, P, Seguin, M, Perrier, X and Glaszmann, JC (eds). Genetic diversity of cultivated tropical plants. Montpellier: Enfield, Science Publishers, pp. 43–76.Google Scholar
Petit, R, El Mousadik, A and Pons, O (1998) Identifying populations for conservation on the basis of genetic markers. Conservation Biology 12: 844–855.Google Scholar
Pritchard, JK, Stephens, M and Donnelly, P (2000) Inference of population structure from multilocus genotype data. Genetics 155: 945–959.CrossRefGoogle ScholarPubMed
Rabbi, IY, Geiger, HH, Haussmann, BIG, Kiambi, D, Folkertsm, R and Parzies, HK (2010) Impact of farmers’ practices and seed systems on the genetic structure of common sorghum varieties in Kenya and Sudan. Plant Genetic Resources 8: 116–126.Google Scholar
Ritland, K (2002) Extensions of models for the estimation of mating systems using n independent loci. Heredity 88: 221–228.CrossRefGoogle ScholarPubMed
Saïdou, AA, Mariac, C, Luong, V, Pham, JL, Bezançon, G and Vigouroux, Y (2009) Association studies identify natural variation at PHYC linked to flowering time and morphological variation in pearl millet. Genetics 182: 899–910.CrossRefGoogle ScholarPubMed
Sokal, RR and Rohlf, FJ (1995) Biometry, 3rd edn.New York, NY: WH Freeman and Company.Google Scholar
Seignobos, C and Iyebi-Mandjek, O (2000) Atlas de la province Extrême-Nord Cameroun. Paris: Minrest, INC, IRD.Google Scholar
Teshome, A, Baum, BR, Fahrig, L, Torrance, JK, Arnason, TJ and Lambert, JD (1997) Sorghum [Sorghum bicolor (L.) Moench] landrace variation and classification in North Shewa and SouthWelo, Ethiopia. Euphytica 97: 255–263.Google Scholar
Teshome, A, Fahrig, L, Torrance, JK, Lambert, JD, Arnason, TJ and Baum, BR (1999) Maintenance of sorghum landrace diversity by farmers selection in Ethiopia. Economic Botany 53: 79–88.CrossRefGoogle Scholar
Van Oosterhout, SAM (1996) What does in situ conservation mean in the life of a small-scale farmer? Examples from Zimbabwe's communal areas. In: Sperling, L and Loevinsohn, M (eds) Using Diversity: Enhancing and Maintaining Genetic Resources On-farm. Proceeding of a Workshop held on 19–21 June 1995. New Delhi: IDRC.Google Scholar
Vigouroux, Y, Barnaud, A, Scarcelli, N and Thuillet, AC (2011a) Biodiversity, evolution and adaptation of cultivated crops. Comptes Rendus Biologies 334: 450–457.Google Scholar
Vigouroux, Y, Mariac, C, De Mita, S, Pham, JL, Gérard, B, Kapran, I, Sagnard, F, Deu, M, Chantereau, J, Ali, A, Ndjeunga, J, Luong, V, Thuillet, AC, Saïdou, AA and Bezançon, G (2011b) Selection for earlier flowering crop associated with climatic variations in the Sahel. PLoS One 6: e19563.Google Scholar
Violon C (2011) Intrication des réseaux sociaux d'échanges de semences dans une communauté tupuri (Extrême-Nord Cameroun). Master's Thesis 1, University Paris 10, Nanterre (France), p. 123.Google Scholar
Weir, BS and Cockerham, CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38: 1358–1370.Google ScholarPubMed
Wencelius J (2009) Dynamiques et Structures de l'Agro-biodiversité dans trois ethnies de l'Extrême-Nord du Cameroun. Master's Thesis 2 of Development Studies, IEDES, University Paris 1 Panthéon Sorbonne (France), p. 81.Google Scholar
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