Identification of Ethiopian Triticum aestivum, T. turgidum, and Eragrostis tef using morphological, SDS-PAGE and AFLP characterisation
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Hika, Yilma Amenu
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University of the Free State
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Showing abstract in English
English: In this study, morphological, seed storage proteins, and AFLP markers were used to
identify and determine the genetic divergence among 20 Ethiopian wheat varieties. In the
same way, an attempt was also made to characterize 10 Ethiopian tef cultivars using
morphological and AFLP markers. Seed storage proteins were not used to characterize
the tef cultivars, because it was already reported that the low number of protein markers
detected could not distinguish individual tef cultivars.
The morphological traits have uniquely identified all the wheat and tef accessions,
although it is found that morphological distances are not accurate estimate of genetic
distances owing to their limited number and environmental interaction. Thus, results
obtained from morphological data have to be confirmed by biochemical or DNA
markers, depending on the need of identification.
From the protein markers, the gliadins uniquely distinguished all the individual wheat
accessions. Thus, gliadins can be effectively used to discriminate wheat cultivars.
However, some of the wheat cultivars had the same HMW-GS banding patterns, and
therefore, HMW -GS should not be used for cultivar identification. The HMW -GS can
rather be used to determine quality characteristics. In general, compared to
morphological markers, protein markers are more reliable as the effect of environmental
influence is absent or minimal. The limitation with the protein markers is that only part
of the genome that codes for a specific protein can be detected.
With the AFLP markers, more variations were detected among the wheat entries, due to
the potential of the AFLP markers to survey the entire genome and also due to the larger
number of loci assayed. Thus, AFLP markers are more reliable and hence they can be
used to supplement and refine morphological- and protein-based classifications.