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Testing the impact of Whole Genome Amplification on genome comparison using the polyploid flagellated Giardia duodenalis as a model
F. Weisz, M. Lalle, E. Nohynkova, AR. Sannella, J. Dluhošová, SM. Cacciò,
Language English Country United States
Document type Journal Article
- MeSH
- Genome-Wide Association Study MeSH
- Giardia lamblia genetics MeSH
- Giardiasis parasitology MeSH
- Humans MeSH
- Mutation MeSH
- Open Reading Frames genetics MeSH
- Child, Preschool MeSH
- DNA, Protozoan chemistry genetics isolation & purification MeSH
- Genomic Structural Variation MeSH
- Nucleic Acid Amplification Techniques MeSH
- Computational Biology MeSH
- Check Tag
- Humans MeSH
- Child, Preschool MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Czech Republic MeSH
The availability of high quality genomic DNA in sufficient amounts to perform Next Generation Sequencing (NGS) experiments is challenging for pathogens that cannot be cultivated in vitro, as is the case for many parasites. Therefore, Whole Genome Amplification (WGA) of genomic DNA is used to overcome this limitation. In this study, we evaluated the effect of WGA using the intestinal flagellated protozoan Giardia duodenalis as a model, due to its genome compactness (12 Mb), the presence of two diploid nuclei with variable levels of allelic sequence heterogeneity (ASH), and the availability of reference genomes. We selected one isolate (ZX15) belonging to the same genetic group of the reference isolate WB, namely Assemblage A, sub-Assemblage AI. Genomic DNA from the ZX15 isolate (GEN dataset) and that obtained by WGA of 1 ng of the same genomic DNA (WGA dataset) were sequenced on a HiSeq Illumina platform. Trimmed reads from the GEN and WGA experiments were mapped against the WB reference genome, showing the presence of a very small number of mutations (846 and 752, respectively). The difference in the number of mutations is largely accounted by local variation in coverage and not by bias introduced by WGA. No significant difference were observed in the distribution of mutations in coding and non-coding regions, in the proportion of heterozygous mutations (ASH), or in the transition/transversion ratio of Single Nucleotide Variants within coding sequences. We conclude that the quantitative and qualitative impact of WGA on the identification of mutations is limited, and that this technique can be used to conduct comparative genomics studies.
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