Capturing the population structure of microparasites: using ITS‐sequence data and a pooled DNA approach. (12th August 2013)

• Record Type: Journal Article
• Authors: Giessler, Sabine; Wolinska, Justyna
• Is Part Of: Molecular ecology resources. Volume 13:Number 5(2013:Sep.)
• Page Start: 918
• Page End: 928
• Publication Date: 2013-08-12
• Subjects: Caullerya mesnili -- DNA pooling -- Ichthyosporea -- intragenomic variation -- ITS region -- population structure -- statistical parsimony network analysis; Molecular ecology -- Periodicals; 572.8
• DOI: 10.1111/1755-0998.12144
• Languages: English
• ISSNs: 1755-098X

Abstract

Abstract: The internal transcribed spacer (ITS) region of nuclear ribosomal DNA is a common marker not only for the molecular identification of different taxa and strains, but also for the analysis of population structure of wild microparasite communities. Importantly, the multicopy nature of this region allows the amplification of low‐quantity samples of the target DNA, a common problem in studies on unicellular, unculturable microparasites. We analysed ITS sequences from the protozoan parasite Caullerya mesnili (class Ichthyosporea) infecting waterflea ( Daphnia ) hosts, across several host population samples. We showed that analysing representative ITS‐types [as identified by statistical parsimony network analysis (SPN)] is a suitable method to address relevant polymorphism. The spatial patterns were consistent regardless of whether parasite DNA was extracted from individual hosts or pooled host samples. Remarkably, the efficiency in detecting different sequence types was even higher after sample pooling. As shown by simulations, an easily manageable number of sequences from pooled DNA samples are sufficient to resolve the spatial population structure in this system. In summary, the ITS region analysed from pooled DNA samples can provide valuable insights into the spatial and temporal dynamics of microparasites. Moreover, the application of SPN analysis is a good alternative to the well‐established neighbour‐joining method (NJ) for the identification of representative ITS‐types. SPN can even outperform NJ by joining most of the singleton sequences to representative sequence clusters.