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Understanding the contrasting spatial haplotype patterns of malaria-protective β-globin polymorphisms.

ABSTRACT: The malaria-protective β-globin polymorphisms, sickle-cell (β(S)) and β(0)-thalassaemia, are canonical examples of human adaptation to infectious disease. Occurring on distinct genetic backgrounds, they vary markedly in their patterns of linked genetic variation at the population level, suggesting different evolutionary histories. β(S) is associated with five classical restriction fragment length polymorphism haplotypes that exhibit remarkable specificity in their geographical distributions; by contrast, β(0)-thalassaemia mutations are found on haplotypes whose distributions overlap considerably. Here, we explore why these two polymorphisms display contrasting spatial haplotypic distributions, despite having malaria as a common selective pressure. We present a meta-population genetic model, incorporating individual-based processes, which tracks the evolution of β-globin polymorphisms on different haplotypic backgrounds. Our simulations reveal that, depending on the rate of mutation, a large population size and/or high population growth rate are required for both the β(S)- and the β(0)-thalassaemia-like patterns. However, whilst the β(S)-like pattern is more likely when population subdivision is high, migration low and long-distance migration absent, the opposite is true for β(0)-thalassaemia. Including gene conversion has little effect on the overall probability of each pattern; however, when inter-haplotype fitness variation exists, gene conversion is more likely to have contributed to the diversity of haplotypes actually present in the population. Our findings highlight how the contrasting spatial haplotype patterns exhibited by β(S) and β(0)-thalassaemia may provide important indications as to the evolution of these adaptive alleles and the demographic history of the populations in which they have evolved.

SUBMITTER: Hockham C

PROVIDER: S-EPMC4653953 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe objective of this study is to analyze the spatial and temporal patterns of malaria incidence as to determine the means by which climatic factors such as temperature, rainfall and humidity affect its distribution in Maputo province, Mozambique.MethodsThis study presents a model of malaria that evolves in space and time in Maputo province-Mozambique, over a ten years period (1999-2008). The model incorporates malaria cases and their relation to environmental variables. Due to incompleteness of climatic data, a multiple imputation technique is employed. Additionally, the whole province is interpolated through a Gaussian process. This method overcomes the misalignment problem of environmental variables (available at meteorological stations--points) and malaria cases (available as aggregates for every district--area). Markov Chain Monte Carlo (MCMC) methods are used to obtain posterior inference and Deviance Information Criteria (DIC) to perform model comparison.ResultsA Bayesian model with interaction terms was found to be the best fitted model. Malaria incidence was associated to humidity and maximum temperature. Malaria risk increased with maximum temperature over 28 °C (relative risk (RR) of 0.0060 and 95% Bayesian credible interval (CI) of 0.00033-0.0095) and humidity (relative risk (RR) of 0.00741 and 95% Bayesian CI 0.005141-0.0093). The results would suggest that additional non-climatic factors including socio-economic status, elevation, etc. also influence malaria transmission in Mozambique.ConclusionsThese results demonstrate the potential of climate predictors particularly, humidity and maximum temperature in explaining malaria incidence risk for the studied period in Maputo province. Smoothed maps obtained as monthly average of malaria incidence allowed to visualize months of initial and peak transmission. They also illustrate a variation on malaria incidence risk that might not be related to climatic factors. However, these factors are still determinant for malaria transmission and intensity in the region.

Project description:The Locus Control Region (LCR) requires intronic elements within beta-globin transgenes to direct high level expression at all ectopic integration sites. However, these essential intronic elements cannot be transmitted through retrovirus vectors and their deletion may compromise the therapeutic potential for gene therapy. Here, we systematically regenerate functional beta-globin intron 2 elements that rescue LCR activity directed by 5'HS3. Evaluation in transgenic mice demonstrates that an Oct-1 binding site and an enhancer in the intron cooperate to increase expression levels from LCR globin transgenes. Replacement of the intronic AT-rich region with the Igmu 3'MAR rescues LCR activity in single copy transgenic mice. Importantly, a combination of the Oct-1 site, Igmu 3'MAR and intronic enhancer in the BGT158 cassette directs more consistent levels of expression in transgenic mice. By introducing intron-modified transgenes into the same genomic integration site in erythroid cells, we show that BGT158 has the greatest transcriptional induction. 3D DNA FISH establishes that induction stimulates this small 5'HS3 containing transgene and the endogenous locus to spatially reorganize towards more central locations in erythroid nuclei. Electron Spectroscopic Imaging (ESI) of chromatin fibers demonstrates that ultrastructural heterochromatin is primarily perinuclear and does not reorganize. Finally, we transmit intron-modified globin transgenes through insulated self-inactivating (SIN) lentivirus vectors into erythroid cells. We show efficient transfer and robust mRNA and protein expression by the BGT158 vector, and virus titer improvements mediated by the modified intron 2 in the presence of an LCR cassette composed of 5'HS2-4. Our results have important implications for the mechanism of LCR activity at ectopic integration sites. The modified transgenes are the first to transfer intronic elements that potentiate LCR activity and are designed to facilitate correction of hemoglobinopathies using single copy vectors.

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Understanding the contrasting spatial haplotype patterns of malaria-protective β-globin polymorphisms.

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