METHODS: Forty full-length pktrap sequences from clinical isolates of Malaysia along with the reference H-strain were downloaded from published databases. Genetic diversity, polymorphism, haplotype and natural selection were determined using DnaSP 5.10 software. McDonald-Kreitman test was conducted using P. vivax and Plasmodium coatneyi as ortholog sequence in DnaSP 5.10 software. Population genetic differentiation index (FST) of parasite populations was determined using Arlequin v3.5. Phylogenetic relationships between trap ortholog genes were determined using MEGA 5.0 software.
RESULTS: Comparison of 40 full-length pktrap sequences along with the H-strain identified 74 SNPs (53 non-synonymous and 21 synonymous substitutions) resulting in 29 haplotypes. Analysis of the full-length gene showed that the nucleotide diversity was lower compared to its nearest ortholog pvtrap. Domain-wise analysis indicated that the proline/asparagine rich region had higher nucleotide diversity compared to the von Willebrand factor domain and the thrombospondin-type-1 domain. McDonald-Kreitman test identified that the ratio of the number of nonsynonymous to synonymous polymorphic sites within P. knowlesi was significantly higher than that of the number of nonsynonymous to synonymous fixed sites between P. knowlesi and P. vivax. The von Willebrand factor domain also indicated balancing selection using MK test, however, it did not give significant results when tested with P. coatneyi as an outgroup. Phylogenetic analysis of full-length genes identified three distinct sub-clusters of P. knowlesi, one originating from Peninsular Malaysia and two originating from Malaysian Borneo. High population differentiation values was observed within samples from Peninsular Malaysia and Malaysian Borneo.
CONCLUSIONS: This study is the first to report on the genetic diversity and natural selection of full-length pktrap. Low level of genetic diversity was found across the full-length gene of pktrap. Balancing selection of the von Willebrand factor domain indicated that TRAP could be a target in inducing immune response against P. knowlesi infections. However, higher number of samples would be necessary to further confirm the findings.
RESULTS: We used 12 highly polymorphic microsatellite loci to identify 50 individual jaguars. We detected high levels of genetic diversity across loci (HE = 0.61, HO = 0.55, and NA = 9.33). Using Bayesian clustering and multivariate models to assess gene flow and genetic structure, we identified one single group of jaguars (K = 1). We identified critical areas for jaguar movement that fall outside the boundaries of current protected areas in central Belize. We detected two main areas of high landscape permeability in a stretch of approximately 18 km between Sittee River Forest Reserve and Manatee Forest Reserve that may increase functional connectivity and facilitate jaguar dispersal from and to Cockscomb Basin Wildlife Sanctuary. Our analysis provides important insights on fine-scale genetic and landscape connectivity of jaguars in central Belize, an area of conservation concern.
CONCLUSIONS: The results of our study demonstrate high levels of relatively recent gene flow for jaguars between two study sites in central Belize. Our landscape analysis detected corridors of expected jaguar movement between the Cockscomb Basin Wildlife Sanctuary and the Maya Forest Corridor. We highlight the importance of maintaining already established corridors and consolidating new areas that further promote jaguar movement across suitable habitat beyond the boundaries of currently protected areas. Continued conservation efforts within identified corridors will further maintain and increase genetic connectivity in central Belize.
METHOD: Targeted sequencing of fourteen genes panel was performed to identify the mutations in 29 OI patients with type I, III, IV and V disease. The mutations were determined using Ion Torrent Suite software version 5 and variant annotation was conducted using ANNOVAR. The identified mutations were confirmed using Sanger sequencing and in silico analysis was performed to evaluate the effects of the candidate mutations at protein level.
RESULTS: Majority of patients had mutations in collagen genes, 48% (n = 14) in COL1A1 and 14% (n = 4) in COL1A2. Type I OI was caused by quantitative mutations in COL1A1 whereas most of type III and IV were due to qualitative mutations in both of the collagen genes. Those with quantitative mutations had milder clinical severity compared to qualitative mutations in terms of dentinogenesis imperfecta (DI), bone deformity and the ability to walk with aid. Furthermore, a few patients (28%, n = 8) had mutations in IFITM5, BMP1, P3H1 and SERPINF1.
CONCLUSION: Majority of our OI patients have mutations in collagen genes, similar to other OI populations worldwide. Genotype-phenotype analysis revealed that qualitative mutations had more severe clinical characteristics compared to quantitative mutations. It is crucial to identify the causative mutations and the clinical severity of OI patients may be predicted based on the types of mutations.