Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

Population structure shapes copy number variation in malaria parasites


ABSTRACT: If copy number variants (CNVs) are predominantly deleterious, we would expect them to be more efficiently purged from populations with a large effective population size (Ne) than from populations with a small Ne. Malaria parasites (Plasmodium falciparum) provide an excellent organism to examine this prediction, because this protozoan shows a broad spectrum of population structures within a single species, with large, stable, outbred populations in Africa, small unstable inbred populations in South America and with intermediate population characteristics in South East Asia. We characterized 122 single-clone parasites, without prior laboratory culture, from malaria-infected patients in 7 countries in Africa, SE Asia and S. America using a high density SNP/CNV microarray. We scored 134 high-confidence CNVs across the parasite exome, including 33 deletions and 102 amplifications, which ranged in size from <500bp to 59kb, as well as 10,107 flanking, biallelic SNPs. Overall, CNVs were rare, small and skewed towards low frequency variants, consistent with the deleterious model. Relative to African and SE Asian populations, CNVs were significantly more common in S. America, showed significantly less skew in allele frequencies, and were significantly larger. On this background of low frequency CNV, we also identified several high-frequency CNVs under putative positive selection using an FST outlier analysis. These included known adaptive CNVs containing rh2b and pfmdr1, and several other CNVs (e.g. DNA helicase, and 3 conserved proteins) that require further investigation. Our data are consistent with a significant impact of genetic structure on CNV burden in an important human pathogen. SNP/CGH hybridisation of 175 malaria parasite samples

ORGANISM(S): Plasmodium falciparum

SUBMITTER: Ian Cheeseman 

PROVIDER: E-GEOD-75137 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

Similar Datasets

2015-11-19 | GSE75137 | GEO
2011-12-31 | GSE30481 | GEO
2011-12-31 | E-GEOD-30481 | biostudies-arrayexpress
| EGAO00000000008 | EGA
2008-02-05 | GSE10331 | GEO
2012-04-30 | E-GEOD-33002 | biostudies-arrayexpress
2022-06-30 | GSE197121 | GEO
2011-03-03 | GSE27632 | GEO
2021-01-01 | GSE151767 | GEO
2017-04-27 | E-MTAB-4629 | biostudies-arrayexpress