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Use of EST database markers from M. truncatula in the transferability to other forage legumes
Authors:Chandra Amaresh
Institution:Crop Improvement Division, Indian Grassland and Fodder Research Institute, Jhansi - 284 003, India. amaresh62@yahoo.com
Abstract:In general tropical forage legumes lack microsatellites or simple sequence repeat (SSR) markers. Development of genic SSR markers from expressed sequence tagged (EST) database is an alternate and efficient approach to generate the standard DNA markers for genome analysis of such crop species. In the present paper a total of 816 EST-SSRs containing perfect repeats of mono (33.5%), di (14.7%), tri (39.3%), tetra (2.7%), penta (0.7%) and hexa (0.4%) nucleotides were identified from 1,87,763 ESTs of Medicago truncatula. Along with, 70 (8.5%) SSRs of a compound type were also observed. Seven primer pairs of tri repeats were tested for cross transferability in 19 accessions of forage legumes comprising 11 genera. At two different annealing temperatures (55 and 60 degreesC) all primer pairs except AJ410087 reacted with many accessions of forage legumes. Atotal of 51 alleles were detected with six M. truncatula EST-SSRs primer-pairs against DNAfrom 19 accessions representing 11 genera where number of alleles ranged from 2 to 13. The cross-transferability of these EST-SSRs was 40.6% at 55 degreesC and 32.3% at 60 degreesC annealing temperature. 24 alleles of the total 50 (48%) at 55 degreesC and 27 of 51 (53%) at 60 degreesC were polymorphic among the accessions. These 27 polymorphic amplicons identified could be used as DNA markers. This study demonstrates the developed SSR markers from M. truncatula ESTs as a valuable genetic markers and also proposes the possibility of transferring these markers between species of different genera of the legumes of forage importance. It was evident from the results obtained with a set of Desmanthus virgatus accessions where SequentialAgglomerative Hierarchical and Nested (SAHN) cluster analysis based on Dice similarity and Unweighted Pair Group Method with Arithmetic mean Algorithm (UPGMA) revealed significant variability (24 to 74%) among the accessions. High bootstrap values (>30) supported the nodes generated by dendrogram analysis of accessions.
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