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Towards a general, worldwide, Plasmodium population genomics framework


Trends in Parasitology, January 2023

I read with great interest the article by Camponovo et al. [1]. The authors are right in insisting on the necessity of an extensive approach to Plasmodium population genomic diversity. Such a broad picture is sorely needed. This important article inspired me to make the following remarks.

As a population geneticist, it is unexpected that I do have a clear idea of the population structure of bacteria such as Escherichia coli or Neisseria meningitidis, or of parasites such as Trypanosoma cruzi or Leishmania infantum [2]. When sexual organisms are concerned,

I also have a detailed picture of human genetic variability [3]. In spite of so many works spent on the theme, I do not have a similar picture for Plasmodium. For me, this parasite’s population structure is still as clear as mud. The proposal by Camponovo et al. [1] therefore is quite timely.

Plasmodium falciparum population structure has long been considered as panmictic

(widespread random mating) – only because this parasite undergoes an obligatory sexual cycle in the mosquito vector, while one had no precise idea about this parasite’s actual population structure (‘panmictic prejudice’ [4]). Our careful proposal that ‘uniparental and biparental lineages may coexist within this species, for which a sexual cycle has been a classical notion’ [5] resulted in a vehement outcry [6–8]. However, the presence of clonal

lineages in P. falciparum has since been fully confirmed ([1,9]; see also many other

references in [4]). Now the respective contribution of clonality and sexuality in P. falciparum population structure remains very obscure.

It is apparent that this parasite does not meet the expectations of our predominant clonal evolution (PCE) model, which posits that genetic recombination is not frequent enough to counter the effects of clonality, the most typical being the presence of a persistent phylogenetic signal with deep phylogenies and multigene bifurcating trees (MGBTs) at all evolutionary scales [2]. This obviously does not obtain in P. falciparum: genetic clusters, multilocus genotypes, and clones are unstable over space and time in this parasite due

to genetic recombination. A practical consequence of this trait, too often neglected, is that strain typing is irrelevant in P. falciparum since this species features no ‘strains’ as such (= stable multilocus genotypes). However, again, this parasite’s natural populations definitely

are not panmictic. They exhibit clear genetic structurations that are not imputable to geographical and/or spatial separation only [4]. This should be taken into account in all epidemiological surveys dealing with this parasite [2,4].

Clonality and restriction to genetic exchange in P. falciparum have been constantly attributed to self-fertilization or selfing (fertilization of an organism by itself, hence by a genotype that is identical to itself) [1,9]. We have called this ‘passive clonality, or ‘starving sex hypothesis’ [4]. In this case, the parasite mates with itself due to the lack of mating partners. Although this is a very probable hypothesis, alternative explanations should not be ruled out a priori. Let us call them ‘active clonality’ [4]. It would rely on inbuilt biological properties of the parasite rather than on a pure mechanical, demographic effect like passive clonality. The debate is epidemiologically relevant. If passive clonality/starving hypothesis is the only explanation, one would expect to get a strong correlation between transmission rate and selfing [9] to the point that the proportion of selfing would be a reliable reflection of the transmission rate [10]. We have shown that this was not verified in many cases [4]. The work by Camponovo et al. [1] does corroborate this lack of correlation: in several cases, selfing is present in high transmission systems. The hypothesis of active clonality should therefore be explored. Possible cases of active clonality could encompass, for example, strong homogamy (the tendency of an organism to mate with individuals that are genetically very similar or identical to itself) or the unknown presence of mating types.

Lastly, which approach to recommend for designing a general picture of Plasmodium genetic diversity? Camponovo et al. [1] propose the method of ancestral recombination graphs. This is sound and reliable. I would suggest an alternative approach, the two methods not being exclusive of each other. The example could be taken from the many population genomic studies that concern humans. They rely on wholegenome sequencing and the characterization of populations by hundreds of thousands of single-nucleotide polymorphisms [3]. In the case of Plasmodium, since many evolutionary traits of these parasites still are unknown, I would recommend a broad survey of populations worldwide,

with as blind an approach as possible, with a minimum of upstream working hypotheses,

and only basic population genetics tests: F statistics, allelic frequencies, and linkage disequilibrium. Such a vast program could be the object of an international consortium that would be successful only if its participants make a great effort to standardize their genomic methods.

Once this broad population genetics framework is available for Plasmodium it will be adequate to localize on it all relevant medical and epidemiological phenotypes (virulence, resistance to drugs, vector specificity) and their corresponding genotypes through a phylogenetic character mapping approach [11]. Population structure should be clarified before analyzing medically relevant phenotypes [3].

1Maladies Infectieuses et Vecteurs Écologie,Génétique, Évolution et Contrôle, MIVEGEC (IRD 224-CNRS 5290-UM1-UM2), Institut

de recherche pour le développement, BP 6450134394 Montpellier Cedex 5, France

*Correspondence: (M. Tibayrenc).

© 2023 Elsevier Ltd. All rights reserved.


1. Camponovo, F. et al. (2023) Measurably recombining malaria parasites. Trends Parasitol. 39, 17–25

2. Tibayrenc, M. and Ayala, F.J. (2021) Models in parasite and pathogen evolution: genomic analysis reveals predominant clonality and progressive evolution at all evolutionary scales in parasitic protozoa, yeasts and bacteria. Adv. Parasitol. 111, 75–117

3. Tibayrenc, M. (2016) Human population variability and its adaptive significance. In On Human Nature: Biology, Psychology, Ethics, Politics, and Religion (Tibayrenc, M. and Ayala, F., eds), pp. 85–109, Elsevier/Academic Press

4. Tibayrenc, M. and Ayala, F.J. (2014) New insights into clonality and panmixia in Plasmodium and Toxoplasma. Adv. Parasitol. 84, 253–268

5. Tibayrenc, M. et al. (1990) A clonal theory of parasitic protozoa: the population structure of Entamoeba, Giardia, Leishmania, Naegleria, Plasmodium, Trichomonas and Trypanosoma, and its medical and taxonomical consequences. Proc. Natl. Acad. Sci. U. S. A. 87, 2414–2418

6. Dye, C. et al. (1990) When are parasites clonal? Nature 348, 120

7. Walliker, D. et al. (1990) When are parasites clonal? Nature 348, 120

8. Walliker, D. (1991) Malaria parasites: randomly interbreeding or ‘clonal’ populations? Parasitol. Today 7, 232–235

9. Anderson, T.J. et al. (2000) Microsatellite markers reveal a spectrum of population structures in the malaria parasite Plasmodium falciparum. Mol. Biol. Evol. 17, 1467–1482

10. Volkman, S.K. et al. (2012) Application of genomics to field investigations of malaria by the international centers of excellence for malaria research. Acta Trop. 121, 324–332

11. Avise, J.C. (2004) Molecular Markers, Natural History and Evolution (2nd edn), Chapman & Hall

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