P. malariae whole genome sequences for population genetics
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ABSTRACT:
PROVIDER: PRJEB79672 | ENA |
REPOSITORIES: ENA
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Project description:Plasmodium malariae selective whole genome amplification development
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Project description:Whole genome sequencing (WGS) of tongue cancer samples and cell line was performed to identify the fusion gene translocation breakpoint. WGS raw data was aligned to human reference genome (GRCh38.p12) using BWA-MEM (v0.7.17). The BAM files generated were further analysed using SvABA (v1.1.3) tool to identify translocation breakpoints. The translocation breakpoints were annotated using custom scripts, using the reference GENCODE GTF (v30). The fusion breakpoints identified in the SvABA analysis were additionally confirmed using MANTA tool (v1.6.0).
2024-02-17 | E-MTAB-12534 | biostudies-arrayexpress
Project description:WGS data for >200 Plasmodium malariae isolates. Sequence data includes Illumina MiSeq, HiSeq and Oxford Nanopore.
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Project description:The genomic diversity of Plasmodium malariae malaria parasites is understudied, partly because infected individuals tend to present with low parasite densities, leading to difficulties in obtaining sufficient parasite DNA for genome analysis. Selective whole genome amplification (SWGA) increases the relative levels of pathogen DNA in a clinical sample, but has not been adapted for P. malariae parasites. Here we design customized SWGA primers which successfully amplify P. malariae DNA extracted directly from unprocessed clinical blood samples obtained from patients with P. malariae-mono-infections from six countries, and further test the efficacy of SWGA on mixed infections with other Plasmodium spp. SWGA enables the successful whole genome sequencing of samples with low parasite density (i.e. one sample with a parasitaemia of 0.0064% resulted in 44% of the genome covered by ≥ 5 reads), leading to an average 14-fold increase in genome coverage when compared to unamplified samples. We identify a total of 868,476 genome-wide SNPs, of which 194,709 are unique across 18 high-quality isolates. After exclusion of the hypervariable subtelomeric regions, a high-quality core subset of 29,899 unique SNPs is defined. Population genetic analysis suggests that P. malariae parasites display clear geographical separation by continent. Further, SWGA successfully amplifies genetic regions of interest such as orthologs of P. falciparum drug resistance-associated loci (Pfdhfr, Pfdhps, Pfcrt, Pfk13 and Pfmdr1), and several non-synonymous SNPs were detected in these genes. In conclusion, we have established a robust SWGA approach that can assist whole genome sequencing of P. malariae, and thereby facilitate the implementation of much-needed large-scale multi-population genomic studies of this neglected malaria parasite. As demonstrated in other Plasmodia, such genetic diversity studies can provide insights into the biology underlying the disease and inform malaria surveillance and control measures.
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Project description:The genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a population's history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyze the separation history between populations. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago.
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Project description:The history of human population size is important for understanding human evolution. Various studies have found evidence for a founder event (bottleneck) in East Asian and European populations, associated with the human dispersal out-of-Africa event around 60 thousand years (kyr) ago. However, these studies have had to assume simplified demographic models with few parameters, and they do not provide a precise date for the start and stop times of the bottleneck. Here, with fewer assumptions on population size changes, we present a more detailed history of human population sizes between approximately ten thousand and a million years ago, using the pairwise sequentially Markovian coalescent model applied to the complete diploid genome sequences of a Chinese male (YH), a Korean male (SJK), three European individuals (J. C. Venter, NA12891 and NA12878 (ref. 9)) and two Yoruba males (NA18507 (ref. 10) and NA19239). We infer that European and Chinese populations had very similar population-size histories before 10-20 kyr ago. Both populations experienced a severe bottleneck 10-60 kyr ago, whereas African populations experienced a milder bottleneck from which they recovered earlier. All three populations have an elevated effective population size between 60 and 250 kyr ago, possibly due to population substructure. We also infer that the differentiation of genetically modern humans may have started as early as 100-120 kyr ago, but considerable genetic exchanges may still have occurred until 20-40 kyr ago.
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Project description:The genome sequences of Plasmodium ovale and Plasmodium malariae
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Project description:There has been much interest in analyzing genome-scale DNA sequence data to infer population histories, but inference methods developed hitherto are limited in model complexity and computational scalability. Here we present an efficient, flexible statistical method, diCal2, that can use whole-genome sequence data from multiple populations to infer complex demographic models involving population size changes, population splits, admixture, and migration. Applying our method to data from Australian, East Asian, European, and Papuan populations, we find that the population ancestral to Australians and Papuans started separating from East Asians and Europeans about 100,000 y ago, and that the separation of East Asians and Europeans started about 50,000 y ago, with pervasive gene flow between all pairs of populations.
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