Adaptation and diversity along an altitudinal gradient in Ethiopian barley (Hordeum vulgare L.) landraces revealed by molecular analysis

Abstract

Background: Among the cereal crops, barley is the species with the greatest adaptability to a wide range of environments. To determine the level and structure of genetic diversity in barley (Hordeum vulgare L.) landraces from the central highlands of Ethiopia, we have examined the molecular variation at seven nuclear microsatellite loci.

Results: A total of 106 landrace populations were sampled in the two growing seasons (Meher and Belg; the long and short rainy seasons, respectively), across three districts (Ankober, Mojanawadera and Tarmaber), and within each district along an altitudinal gradient (from 1,798 to 3,324 m a.s.l). Overall, although significant, the divergence (e.g. FST) is very low between seasons and geographical districts, while it is high between different classes of altitude. Selection for adaptation to different altitudes appears to be the main factor that has determined the observed clinal variation, along with population-size effects.

Conclusions: Our data show that barley landraces from Ethiopia are constituted by highly variable local populations (farmer's fields) that have large within-population diversity. These landraces are also shown to be locally adapted, with the major driving force that has shaped their population structure being consistent with selection for adaptation along an altitudinal gradient. Overall, our study highlights the potential of such landraces as a source of useful alleles. Furthermore, these landraces also represent an ideal system to study the processes of adaptation and for the identification of genes and genomic regions that have adaptive roles in crop species.

Figure 1

Map of the collection sites. Collection site coordinates and average q values for clusters S1 (green) and S2 (red) of each of the barley landraces. Landraces that showed an average q > 0.70 were considered completely assigned to one of the two clusters identified by STRUCTURE.

Figure 2

Linear regression analysis for altitude and membership coefficient (q) for cluster S2 identified by STRUCTURE.

Figure 3

Population structure across seasons and altitudes using STRUCTURE. STRUCTURE assignment at K = 2 for the 108 individuals collected during the Belg growing season and the 104 individuals collected during the Meher season, ordered according to crescent altitude levels. Green, cluster S1; red, cluster S2.

Figure 4

Population structure across districts and altitudes using STRUCTURE. STRUCTURE assignment at K = 2 for the individuals collected in the three districts (Ankober, Mojanawadera and Tarmaber), ordered according to crescent altitude levels. Green, cluster S1; red, cluster S2.

Figure 5

Population structure along the altitude gradient using TESS. TESS assignment at K = 6 for the 212 individuals, ordered according to crescent altitude levels. Blue-purple, T1; red, T2; pink, T3; yellow, T4; grey, T5; green, T6.

Figure 6

Average membership coefficient (q) for the six TESS clusters for the three altitude classes. See legend to Figure 5 for colour key.

Figure 7

Autocorrelation analysis. Results of the autocorrelation analysis using all 212 genotypes and all loci. The 99% probability envelopes are indicated: light blue, upper limit; green, lower limit. Dark blue, observed data: for genetic distance vs geographical distance). Inset: the first 20 km from panel a) (40 classes, 500 m each).

Figure 8

'Sliding-window' analysis for the two seasons: Belg (blue) and Meher (orange). a) Genetic diversity (He); b) allelic richness (R_S); c) multilocus linkage disequilibrium (LD) along the altitudinal cline, with P values also shown. The altitude of each window (20 populations, 40 individuals) was determined by averaging the altitude of the populations (farmers' fields); hence, the differences in the average altitudes between the windows are not constant.