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Symmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparum.

ABSTRACT: It is being increasingly recognized that many important phenotypic traits, including various diseases, are governed by a combination of weak genetic effects and their interactions. While the detection of epistatic interactions that involve a non-additive effect of two loci on a quantitative trait is particularly challenging, this interaction type is fundamental for the understanding of genome organization and gene regulation. However, current methods that detect epistatic interactions typically rely on the existence of a strong primary effect, considerably limiting the sensitivity of the search. To fill this gap, we developed a new method, SEE (Symmetric Epistasis Estimation), allowing the genome-wide detection of epistatic interactions without the need for a strong primary effect. We applied our approach to progeny crosses of the human malaria parasite P. falciparum and S. cerevisiae. We found an abundance of epistatic interactions in the parasite and a much smaller number of such interactions in yeast. The genome of P. falciparum also harboured several epistatic interaction hotspots that putatively play a role in drug resistance mechanisms. The abundance of observed epistatic interactions might suggest a mechanism of compensation for the extremely limited repertoire of transcription factors. Interestingly, epistatic interaction hotspots were associated with elevated levels of linkage disequilibrium, an observation that suggests selection pressure acting on P. falciparum, potentially reflecting host-pathogen interactions or drug-induced selection.

SUBMITTER: Huang Y

PROVIDER: S-EPMC3480327 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Symmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparum.

Huang Yang Y Siwo Geoffrey G Wuchty Stefan S Ferdig Michael T MT Przytycka Teresa M TM

Molecular bioSystems 20120315 5

It is being increasingly recognized that many important phenotypic traits, including various diseases, are governed by a combination of weak genetic effects and their interactions. While the detection of epistatic interactions that involve a non-additive effect of two loci on a quantitative trait is particularly challenging, this interaction type is fundamental for the understanding of genome organization and gene regulation. However, current methods that detect epistatic interactions typically ...[more]

PMID: 22419061

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Project description:BackgroundEfficient allocation of resources to intervene against malaria requires a detailed understanding of the contemporary spatial distribution of malaria risk. It is exactly 40 y since the last global map of malaria endemicity was published. This paper describes the generation of a new world map of Plasmodium falciparum malaria endemicity for the year 2007.Methods and findingsA total of 8,938 P. falciparum parasite rate (PfPR) surveys were identified using a variety of exhaustive search strategies. Of these, 7,953 passed strict data fidelity tests for inclusion into a global database of PfPR data, age-standardized to 2-10 y for endemicity mapping. A model-based geostatistical procedure was used to create a continuous surface of malaria endemicity within previously defined stable spatial limits of P. falciparum transmission. These procedures were implemented within a Bayesian statistical framework so that the uncertainty of these predictions could be evaluated robustly. The uncertainty was expressed as the probability of predicting correctly one of three endemicity classes; previously stratified to be an informative guide for malaria control. Population at risk estimates, adjusted for the transmission modifying effects of urbanization in Africa, were then derived with reference to human population surfaces in 2007. Of the 1.38 billion people at risk of stable P. falciparum malaria, 0.69 billion were found in Central and South East Asia (CSE Asia), 0.66 billion in Africa, Yemen, and Saudi Arabia (Africa+), and 0.04 billion in the Americas. All those exposed to stable risk in the Americas were in the lowest endemicity class (PfPR2-10 < or = 5%). The vast majority (88%) of those living under stable risk in CSE Asia were also in this low endemicity class; a small remainder (11%) were in the intermediate endemicity class (PfPR2-10 > 5 to < 40%); and the remaining fraction (1%) in high endemicity (PfPR2-10 > or = 40%) areas. High endemicity was widespread in the Africa+ region, where 0.35 billion people are at this level of risk. Most of the rest live at intermediate risk (0.20 billion), with a smaller number (0.11 billion) at low stable risk.ConclusionsHigh levels of P. falciparum malaria endemicity are common in Africa. Uniformly low endemic levels are found in the Americas. Low endemicity is also widespread in CSE Asia, but pockets of intermediate and very rarely high transmission remain. There are therefore significant opportunities for malaria control in Africa and for malaria elimination elsewhere. This 2007 global P. falciparum malaria endemicity map is the first of a series with which it will be possible to monitor and evaluate the progress of this intervention process.

Project description:BackgroundTransmission intensity affects almost all aspects of malaria epidemiology and the impact of malaria on human populations. Maps of transmission intensity are necessary to identify populations at different levels of risk and to evaluate objectively options for disease control. To remain relevant operationally, such maps must be updated frequently. Following the first global effort to map Plasmodium falciparum malaria endemicity in 2007, this paper describes the generation of a new world map for the year 2010. This analysis is extended to provide the first global estimates of two other metrics of transmission intensity for P. falciparum that underpin contemporary questions in malaria control: the entomological inoculation rate (PfEIR) and the basic reproductive number (PfR).MethodsAnnual parasite incidence data for 13,449 administrative units in 43 endemic countries were sourced to define the spatial limits of P. falciparum transmission in 2010 and 22,212 P. falciparum parasite rate (PfPR) surveys were used in a model-based geostatistical (MBG) prediction to create a continuous contemporary surface of malaria endemicity within these limits. A suite of transmission models were developed that link PfPR to PfEIR and PfR and these were fitted to field data. These models were combined with the PfPR map to create new global predictions of PfEIR and PfR. All output maps included measured uncertainty.ResultsAn estimated 1.13 and 1.44 billion people worldwide were at risk of unstable and stable P. falciparum malaria, respectively. The majority of the endemic world was predicted with a median PfEIR of less than one and a median PfRc of less than two. Values of either metric exceeding 10 were almost exclusive to Africa. The uncertainty described in both PfEIR and PfR was substantial in regions of intense transmission.ConclusionsThe year 2010 has a particular significance as an evaluation milestone for malaria global health policy. The maps presented here contribute to a rational basis for control and elimination decisions and can serve as a baseline assessment as the global health community looks ahead to the next series of milestones targeted at 2015.

Dataset Information

Symmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparum.

Publications

Symmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparum.

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