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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Experimental Parasit...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Experimental Parasitology
Article . 2012 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Assessment of polymorphic genetic markers for multi-locus typing of Cryptosporidium parvum and Cryptosporidium hominis

Authors: Guy, Robinson; Rachel M, Chalmers;

Assessment of polymorphic genetic markers for multi-locus typing of Cryptosporidium parvum and Cryptosporidium hominis

Abstract

The use of high resolution molecular tools to study Cryptosporidium parvum and Cryptosporidium hominis intra-species variation is becoming common practice, but there is currently no consensus in the methods used. The most commonly applied tool is partial gp60 gene sequence analysis. However, multi-locus schemes are acknowledged to improve resolution over analysis of a single locus, which neglects potential re-assortment of genes during the sexual phase of the Cryptosporidium life-cycle. Multi-locus markers have been investigated in isolates from a variety of sampling frames, in varying combinations and using different assays and methods of analysis. To identify the most informative markers as candidates for the development of a standardised multi-locus fragment size-based typing (MLFT) scheme to integrate with epidemiological analyses, we examined the published literature. A total of 31 MLFT studies were found, employing 55 markers of which 45 were applied to both C. parvum and C. hominis. Of the studies, 11 had sufficient raw data, from three or more markers, and a sampling frame containing at least 50 samples, for meaningful in-depth analysis using assessment criteria based on the sampling frame, study size, number of markers investigated in each study, marker characteristics (>2 nucleotide repeats) and the combinations of markers generating all possible multi-locus genotypes. Markers investigated differed between C. hominis and C. parvum. When each scheme was analysed for the fewest markers required to identify 95% of all MLFTs, some redundancy was identified in all schemes; an average redundancy of 40% for C. hominis and 27% for C. parvum. Ranking markers, based on the most productive combinations, identified two different sets of potentially most informative candidate markers, one for each species. These will be subjected to technical evaluation including typability (percentage of samples generating a complete multi-locus type) and discriminatory power by direct fragment size analysis and analysed for correlation with epidemiological data in suitable sampling frames. The establishment of a group of users and agreed subtyping scheme for improved epidemiological and public health investigations of C. parvum and C. hominis will facilitate further developments and consideration of technological advances in a harmonised manner.

Related Organizations
Keywords

Cryptosporidium parvum, Genetic Markers, Polymorphism, Genetic, Cryptosporidium, Multilocus Sequence Typing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
51
Top 10%
Top 10%
Top 10%
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