Genetic characterization of microsporidians infecting Indian non-mulberry silkworms (Antheraea assamensis and Samia cynthia ricini) by using PCR based ISSR and RAPD markers assay
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This study established the genetic characterisation of 10 microsporidian isolates infectingnon-mulberry silkworms (Antheraea assamensis and Samia cynthia ricini) collected from biogeographicalforest locations in the State of Assam, India, using PCR-based markers assays:inter simple sequence repeat (ISSR) and random amplified polymorphic DNA (RAPD). ANosema type species (NIK-1s_mys) was used as control for comparison. The shape ofmature microsporidian spores were observed oval to elongated, measuring 3.80 to 4.90 μmin length and 2.60 to 3.05 μm in width. Fourteen ISSR primers generated reproducible profilesand yielded 178 fragments, of which 175 were polymorphic (98%), while 16 RAPD primersgenerated reproducible profiles with 198 amplified fragments displaying 95% of polymorphism. Estimation of genetic distance coefficients based on dice coefficients method and clusteringwith un-weighted pair group method using arithmetic average (UPGMA) analysis was done tounravel the genetic diversity of microsporidians infecting Indian muga and eri silkworm. Thesimilarity coefficients varied from 0.385 to 0.941 in ISSR and 0.083 to 0.938 in RAPD data. UPGMA analysis generated dendrograms with two microsporidian groups, which appearto be different from each other. Based on Euclidean distance matrix method, 2-dimensionaldistribution also revealed considerable variability among different identified microsporidians. Clustering of these microsporidian isolates was in accordance with their host and biogeographicorigin. Both techniques represent a useful and efficient tool for taxonomicalgrouping as well as for phylogenetic classification of different microsporidians in general andgenotyping of these pathogens in particular
Abstract
This study established the genetic characterisation of 10 microsporidian isolates infectingnon-mulberry silkworms (Antheraea assamensis and Samia cynthia ricini) collected from biogeographicalforest locations in the State of Assam, India, using PCR-based markers assays:inter simple sequence repeat (ISSR) and random amplified polymorphic DNA (RAPD). ANosema type species (NIK-1s_mys) was used as control for comparison. The shape ofmature microsporidian spores were observed oval to elongated, measuring 3.80 to 4.90 μmin length and 2.60 to 3.05 μm in width. Fourteen ISSR primers generated reproducible profilesand yielded 178 fragments, of which 175 were polymorphic (98%), while 16 RAPD primersgenerated reproducible profiles with 198 amplified fragments displaying 95% of polymorphism. Estimation of genetic distance coefficients based on dice coefficients method and clusteringwith un-weighted pair group method using arithmetic average (UPGMA) analysis was done tounravel the genetic diversity of microsporidians infecting Indian muga and eri silkworm. Thesimilarity coefficients varied from 0.385 to 0.941 in ISSR and 0.083 to 0.938 in RAPD data. UPGMA analysis generated dendrograms with two microsporidian groups, which appearto be different from each other. Based on Euclidean distance matrix method, 2-dimensionaldistribution also revealed considerable variability among different identified microsporidians. Clustering of these microsporidian isolates was in accordance with their host and biogeographicorigin. Both techniques represent a useful and efficient tool for taxonomicalgrouping as well as for phylogenetic classification of different microsporidians in general andgenotyping of these pathogens in particular Estimation of genetic distance coefficients based on dice coefficients method and clusteringwith un-weighted pair group method using arithmetic average (UPGMA) analysis was done tounravel the genetic diversity of microsporidians infecting Indian muga and eri silkworm. Thesimilarity coefficients varied from 0.385 to 0.941 in ISSR and 0.083 to 0.938 in RAPD data. UPGMA analysis generated dendrograms with two microsporidian groups, which appearto be different from each other. Based on Euclidean distance matrix method, 2-dimensionaldistribution also revealed considerable variability among different identified microsporidians. Clustering of these microsporidian isolates was in accordance with their host and biogeographicorigin. Both techniques represent a useful and efficient tool for taxonomicalgrouping as well as for phylogenetic classification of different microsporidians in general andgenotyping of these pathogens in particular.
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