Comparative phylogenetic analysis of Apicomplexa based on 18s, 28s and contig 18s+28s rDNA

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Authors

DIAKIN Andrei SIMDYANOV Timur G. BARDŮNEK VALIGUROVÁ Andrea

Year of publication 2018
Type Conference abstract
MU Faculty or unit

Faculty of Science

Citation
Description Apicomplexans form a large and diverse group of unicellular parasites inhabiting invertebrates and vertebrates. Some of them are responsible for important human and animal diseases (e.g. Plasmodium spp., Toxoplasma gondii, and Cryptosporidium spp.), therefore are intensively studied in various aspects of biology and medicine. However, basal groups (e.g. gregarines, agamococcidia, blastogregarines, and protococcidia) that are restricted to invertebrate hosts remain poorly understood. There are a lot of investigations dedicated to intraspecies (relationship between different strains) and intragenus phylogenetic relationships of aforementioned pathogens. Less investigations concern molecular phylogeny of other apicomplexan groups, and even less are dedicated to phylogeny of Apicomplexa as whole. We performed comparative analysis of several phylogenetic trees: 1. 18s that include large most available taxa; 2. 18s tree with reduced number of taxa (the taxa were selected based on 28s set of sequences; 3. 28s phylogenetic tree; 4. 18s+28s phylogenetic trees. Large 18s tree fits to a modern view on presence of the main groups of Apicomplexa, however, as expected, ordering and supports are variously depending on selected analysis. Reduced 18s tree shows another picture: despite the presence of main clades, some species jumped to the other clades; other point is that the ordering does not fit to a large 18s tree. 28s and 18s+28s trees show almost the same results to each other and to 18s tree with a large number of taxa, with flipping of some clades, however. Other consequences is the increasing of clades supports.We can conclude that for better understanding of evolutionary pathways we need to process more data. In addition the use of multigene analysis would improve the results of analysis and data interpretation.
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