Experimental
Most diversity studies on wheat from the Horn of Africa have dealt with tetraploid wheat (Teklu and Hammer, Reference Teklu and Hammer2006; Hailu et al., Reference Hailu, Johansson and Merker2010; Takenaka et al., Reference Takenaka, Mori and Kawahara2010), but studies on the analyses of diversity of bread wheat (Alamerew et al., Reference Alamerew, Chebotar, Huang, Roder and Borner2004) are extremely rare. A rapid loss of genetic resources has been reported in Ethiopia by Teklu and Hammer (Reference Teklu and Hammer2006), mainly due to an increasing adoption of higher performing varieties coming from abroad. This phenomenon has not yet been investigated in Eritrea and, therefore, analysis of genetic diversity within and between populations of Eritrean wheat is of paramount importance.
Plant material
Accessions of 284 bread wheat (Triticum aestivum) landraces were collected directly from Eritrean farmers' fields (Supplementary Fig. S1, available online only at http://journals.cambridge.org).
DNA isolation and genotyping
DNA of the Eritrean wheat accessions was extracted using the Cetyl Trimetheyl Ammonium Bromide (CTAB) method according to Saghai-Maroof et al. (Reference Saghai-Maroof, Soliman, Jorgensen and Allard1984). All samples were genotyped using 30 microsatellite primers distributed over the whole wheat genome (Supplementary Table S1, available online).
PCR amplification was performed in Thermo-Fast 96-well plates with a final reaction volume of 10 μl containing 50 ng template DNA. The amplification reaction was carried out with a GeneAmp® PCR System 2700 thermal cycler (Applied Biosystems, Foster City, CA, USA). The resulting fragments were detected on an ABI 3130xl DNA Analyser (Applied Biosystems) and analysed using GeneMarker software version 1.85 (Softgenetics, State College, PA, USA).
Statistical analysis
The modified Roger's distance (MRD) was calculated using the Microsoft Excel (Microsoft, Redmond, WA, USA) Visual Basic for Applications program according to the formula of Wright (Reference Wright1978):
$$\begin{eqnarray} MRD = \sqrt {\frac {1}{2 m }{ \sum _{ i = 1}^{ m } }\,{ \sum _{ k = 1}^{ a _{ i }} }\,( p _{ ij } - q _{ ij })^{2}}, \end{eqnarray}$$
where p ij and q ij are the allele frequencies of the jth allele at the ith marker, a i is the number of alleles at the ith marker and m is the number of loci or simple sequence repeats (SSRs).
Gene diversity (GD) was calculated according to the formula of Nei (Reference Nei1973):
$$\begin{eqnarray} GD = 1 - { \sum _{ i = 1}^{ n } }\,( p _{ ij })^{2}, \end{eqnarray}$$
where p ij is the frequency of the jth allele for the ith locus summed across all the alleles for the SSR locus. The polymorphic information content of individual markers was calculated with the formula of Yasuda (Reference Yasuda1988):
$$\begin{eqnarray} PIC = 1 - \sum ( p _{ ij })^{2} - (\sum ( p _{ ij })^{2})^{2} + \sum (( p _{ ij })^{2})^{2}. \end{eqnarray}$$
A total of 539 alleles were obtained (Table 1). The average gene diversity of the Eritrean wheat accessions was 0.66, with values ranging from 0.01 to 0.89 (Supplementary Table S2 available online). The average allele number per locus ranged from 2 to 21, with a mean value of 9.2. Among the three genomes of wheat, the highest gene diversity was found for the B genome (0.69) compared with the A genome (0.67) and D genome (0.61).
Table 1 Different genetic diversity indices split up into the different genomes (A, B and D genomes) for the modified Roger's distances (MRD), the total number of allele observations, the average number of alleles, gene diversity and polymorphic information content (PIC)
a
Genetic distance was calculated based on the MRD formula (Wright, Reference Wright1978):
$$MRD = \sqrt {\frac {1}{2m}{ \sum _{ i = 1}^{ m } }\,{ \sum _{ k = 1}^{ a _{ i }} }\,( p _{ ij } - q _{ ij })^{2}} $$
.
b
Gene diversity was according to the formula of Nei (Reference Nei1973):
$$GD = 1 - { \sum _{ i = 1}^{ n } }\,( p _{ ij })^{2} $$
.
c All genomes indicate the markers employed in the A, B and D genomes
d ‘Er-1’ and ‘Er-2’ represent the Eritrean wheat accessions of groups 1 and 2, respectively, inferred by the STRUCTURE analysis.
Population structure was analysed with a Bayesian model-based clustering approach using ‘STRUCTURE’ v.2.3 software (Pritchard et al., Reference Pritchard, Wen and Falush2009). The number of groups (K) was set from 1 to 12 having 20 replicates of runs with a ‘burn-in’ period of 10,000 iterations and 10,000 Markov chain Monte Carlo (MCMC) iterations (Supplementary Fig. S1, available online) to determine the optimal number of groups according to Evanno et al. (Reference Evanno, Regnaut and Goudet2005). Finally, ten replicates with an optimal number of groups were run at a ‘burn-in’ period and MCMC iterations of 100,000.
Based on the MRD, a non-parametrical multidimensional scaling (npMDS) was used to visualize the similarity between the two Eritrean groups inferred by the STRUCTURE analysis. For this purpose, the R language and environment software (v.2.11.1; R Development Core Team, 2011) including the ‘Modern Applied Statistics with S-plus’ package was employed (Venables and Ripley, Reference Venables and Ripley2002).
The npMDS analysis separated the 284 Eritrean bread wheat accessions into two major groups, which was in agreement with assignments generated by the STRUCTURE analysis (Fig. 1). The two major groups of Eritrean bread wheat consisted of 181 accessions, of which 103 accessions were related to Er-1 and Er-2, respectively (Supplementary Fig. S1 available online only at http://journals.cambridge.org). The genetic distance between the two groups of Eritrean accessions (Er-1 and Er-2) was 0.49 (Table 1).
Fig. 1 (colour online) (a) Stacked bar diagram of the q values of the analysed accessions was generated by the program STRUCTURE (only the name of every tenth accession is shown) for the two Eritrean groups: red bars, Er-1 group; blue bars, Er-2 group. (b) Results of the non-parametric multidimensional scaling (npMDS) with two dimensions. The distance in the 2D space approximates the genetic distance between the accessions. Er-1 refers to Eritrean group 1 indicated by circles and red colour, while Er-2 refers to Eritrean group 2 represented by squares and blue colour. The MDS showed a stress statistic of 18.23%. The arrows indicate the corresponding groups inferred by the STRUCTURE analysis (a) to the accessions in the npMDS graph (b).
Discussion
The clear separation of the Eritrean accessions into two groups (Fig. 1) was rather surprising, as the genetic distance between the Er-1 and Er-2 groups was 0.49 (Table 1). The interpretation of the finding of these two different groups in Eritrean accessions is difficult based on the available data only. As this is the first report on Eritrean bread wheat, no other published data can be consulted to help in the interpretation. Location was not in agreement for the separation of these two groups. It is a usual cropping system in Eritrea to plant mixed varieties as a means of increasing yield stability and risk minimizing strategy (Woldeamlak et al., Reference Woldeamlak, Grando, Maatougui and Ceccarelli2008). One possibility could be that the farmer's conscious selection (for different purposes such as baking quality, disease and pest resistant) might lead to two separate groups within Eritrean wheat landraces. Brown (Reference Brown and Brush2000) described how genetic structure could be formed by selection and population fragmentation, and, again, these can be maintained by selection, isolation and the absence of hybridization. Another possibility could be that germplasm was exchanged among farmers from adjacent countries. Therefore, one of the two groups (perhaps the improved bread wheat cultivar or landrace) might be brought from a neighbouring country such as Ethiopia.
The Eritrean wheat gene pool presents an important genetic resource, as it shows a high genetic diversity compared with the small area where it is grown. The detection of two clearly separated sub-populations in the first report on Eritrean bread wheat makes it clear that conservation efforts (both in situ and ex situ) have to deal with both groups.
Supplementary material
To view supplementary material for this article, please visit http://dx.doi.org/10.1017/S1479262113000324
Acknowledgements
We thank the University of Copenhagen for providing all the necessary logistic support for the laboratory work. We thank the Eritrean farmers who allowed us to sample the wheat spikes from their fields. We thank the editorial board of the Journal of Plant Genetic Resources for providing constructive comments.
