scholarly journals Use of a Plasmodium vivax genetic barcode for genomic surveillance and parasite tracking in Sri Lanka

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Rajika L. Dewasurendra ◽  
Mary Lynn Baniecki ◽  
Stephen Schaffner ◽  
Yamuna Siriwardena ◽  
Jade Moon ◽  
...  

Abstract Background Sri Lanka was certified as a malaria-free nation in 2016; however, imported malaria cases continue to be reported. Evidence-based information on the genetic structure/diversity of the parasite populations is useful to understand the population history, assess the trends in transmission patterns, as well as to predict threatening phenotypes that may be introduced and spread in parasite populations disrupting elimination programmes. This study used a previously developed Plasmodium vivax single nucleotide polymorphism (SNP) barcode to evaluate the population dynamics of P. vivax parasite isolates from Sri Lanka and to assess the ability of the SNP barcode for tracking the parasites to its origin. Methods A total of 51 P. vivax samples collected during 2005–2011, mainly from three provinces of the country, were genotyped for 40 previously identified P. vivax SNPs using a high-resolution melting (HRM), single-nucleotide barcode method. Minor allele frequencies, linkage disequilibrium, pair-wise FST values, and complexity of infection (COI) were evaluated to determine the genetic diversity. Structure analysis was carried out using STRUCTURE software (Version 2.3.4) and SNP barcode was used to identify the genetic diversity of the local parasite populations collected from different years. Principal component analysis (PCA) was used to determine the clustering according to global geographic regions. Results The proportion of multi-clone infections was significantly higher in isolates collected during an infection outbreak in year 2007. The minor allele frequencies of the SNPs changed dramatically from year to year. Significant linkage was observed in sample sub-sets from years 2005 and 2007. The majority of the isolates from 2007 consisted of at least two genetically distinct parasite strains. The overall percentage of multi-clone infections for the entire parasite sample was 39.21%. Analysis using STRUCTURE software (Version 2.3.4) revealed the high genetic diversity of the sample sub-set from year 2007. In-silico analysis of these data with those available from other global geographical regions using PCA showed distinct clustering of parasite isolates according to geography, demonstrating the usefulness of the barcode in determining an isolate to be indigenous. Conclusions Plasmodium vivax parasite isolates collected during a disease outbreak in year 2007 were more genetically diverse compared to those collected from other years. In-silico analysis using the 40 SNP barcode is a useful tool to track the origin of an isolate of uncertain origin, especially to differentiate indigenous from imported cases. However, an extended barcode with more SNPs may be needed to distinguish highly clonal populations within the country.

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Aner Mesic ◽  
Marija Rogar ◽  
Petra Hudler ◽  
Nurija Bilalovic ◽  
Izet Eminovic ◽  
...  

Abstract Background Single nucleotide polymorphisms (SNPs) in genes encoding mitotic kinases could influence development and progression of gastric cancer (GC). Methods Case-control study of nine SNPs in mitotic genes was conducted using qPCR. The study included 116 GC patients and 203 controls. In silico analysis was performed to evaluate the effects of polymorphisms on transcription factors binding sites. Results The AURKA rs1047972 genotypes (CT vs. CC: OR, 1.96; 95% CI, 1.05–3.65; p = 0.033; CC + TT vs. CT: OR, 1.94; 95% CI, 1.04–3.60; p = 0.036) and rs911160 (CC vs. GG: OR, 5.56; 95% CI, 1.24–24.81; p = 0.025; GG + CG vs. CC: OR, 5.26; 95% CI, 1.19–23.22; p = 0.028), were associated with increased GC risk, whereas certain rs8173 genotypes (CG vs. CC: OR, 0.60; 95% CI, 0.36–0.99; p = 0.049; GG vs. CC: OR, 0.38; 95% CI, 0.18–0.79; p = 0.010; CC + CG vs. GG: OR, 0.49; 95% CI, 0.25–0.98; p = 0.043) were protective. Association with increased GC risk was demonstrated for AURKB rs2241909 (GG + AG vs. AA: OR, 1.61; 95% CI, 1.01–2.56; p = 0.041) and rs2289590 (AC vs. AA: OR, 2.41; 95% CI, 1.47–3.98; p = 0.001; CC vs. AA: OR, 6.77; 95% CI, 2.24–20.47; p = 0.001; AA+AC vs. CC: OR, 4.23; 95% CI, 1.44–12.40; p = 0.009). Furthermore, AURKC rs11084490 (GG + CG vs. CC: OR, 1.71; 95% CI, 1.04–2.81; p = 0.033) was associated with increased GC risk. A combined analysis of five SNPs, associated with an increased GC risk, detected polymorphism profiles where all the combinations contribute to the higher GC risk, with an OR increased 1.51-fold for the rs1047972(CT)/rs11084490(CG + GG) to 2.29-fold for the rs1047972(CT)/rs911160(CC) combinations. In silico analysis for rs911160 and rs2289590 demonstrated that different transcription factors preferentially bind to polymorphic sites, indicating that AURKA and AURKB could be regulated differently depending on the presence of particular allele. Conclusions Our results revealed that AURKA (rs1047972 and rs911160), AURKB (rs2241909 and rs2289590) and AURKC (rs11084490) are associated with a higher risk of GC susceptibility. Our findings also showed that the combined effect of these SNPs may influence GC risk, thus indicating the significance of assessing multiple polymorphisms, jointly. The study was conducted on a less numerous but ethnically homogeneous Bosnian population, therefore further investigations in larger and multiethnic groups and the assessment of functional impact of the results are needed to strengthen the findings.


Meta Gene ◽  
2019 ◽  
Vol 21 ◽  
pp. 100578
Author(s):  
Tooba Yousefi ◽  
Seyed Mostafa Mir ◽  
Jahanbakhsh Asadi ◽  
Mehdi Tourani ◽  
Ansar Karimian ◽  
...  

2013 ◽  
Vol 9 (2) ◽  
pp. 106-111 ◽  
Author(s):  
Thongram Kamala ◽  
◽  
Sarangthem Indira Devi ◽  
Gourshyam Thingnam ◽  
Bharat Gopalrao Somkuwar

Sign in / Sign up

Export Citation Format

Share Document