Biology subjects

Ruybal-Pesantez, S.

Publications and source records attributed to Ruybal-Pesantez, S..

4 recordsLinked to original sources

bioRxiv2020

A scalable method for identifying recombinants from unaligned sequences

Recombination is a fundamental process in molecular evolution, and the identification of recombinant sequences is of major interest for biologists. However, current methods for detecting recombinants only work for aligned sequences, often require a reference panel, and do not scale well to large datasets. Thus they are not suitable for the analyses of highly diverse genes, such as the var genes of the malaria parasite Plasmodium falciparum, which are known to diversify primarily through recombination. We introduce an algorithm to detect recombinant sequences from an unaligned dataset. Our approach can effectively handle thousands of sequences without the need of an alignment or a reference panel, offering a general tool suitable for the analysis of many different types of sequences. We demonstrate the effectiveness of our algorithm through extensive numerical simulations; in particular, it maintains its accuracy in the presence of insertions and deletions. We apply our algorithm to a dataset of 17,335 DBL types in var genes from Ghana, enabling the comparison between recombinant and non-recombinant types for the first time. We observe that sequences belonging to the same ups type or DBL subclass recombine amongst themselves more frequently, and that non-recombinant DBL types are more conserved than recombinant ones. Author summaryRecombination is a fundamental process in molecular evolution where two genes exchange genetic material, diversifying the genes. It is important to properly model this process when reconstructing evolutionary history, and to do so we need to be able to identify recombinant genes. In this manuscript, we develop a method for this which can be applied to scenarios where current methods often fail, such as where genes are very diverse. We specifically focus on detecting recombinants in the var genes of the malaria parasite Plasmodium falciparum. These genes influence the length and severity of malaria infection, and therefore their study is critical to the treatment and prevention of malaria. They are also highly diverse, primarily because of recombination. Our analysis of genes from a cross-sectional study in Ghana study show fundamental relations between the patterns and prevalence of recombination in these genes and other important biological categorisations.

evolutionary biology↗

bioRxiv2018

Competition for hosts modulates vast antigenic diversity to generate persistent strain structure in Plasmodium falciparum

In their competition for hosts, parasites with antigens that are novel to host immunity will be at a competitive advantage. The resulting frequency-dependent selection can structure parasite populations into strains of limited genetic overlap. For Plasmodium falciparum-the causative agent of malaria-in endemic regions, the high recombination rates and associated vast diversity of its highly antigenic and multicopy var genes preclude such clear clustering; this undermines the definition of strains as specific, temporally-persisting gene variant combinations. We use temporal multilayer networks to analyze the genetic similarity of parasites in both simulated data and in an extensively and longitudinally sampled population in Ghana. When viewed over time, populations are structured into modules (i.e., groups) of parasite genomes whose var gene combinations are more similar within, than between, the modules, and whose persistence is much longer than that of the individual genomes that compose them. Comparison to neutral models that retain parasite population dynamics but lack competition reveals that the selection imposed by host immunity promotes the persistence of these modules. The modular structure is in turn associated with a slower acquisition of immunity by individual hosts. Modules thus represent dynamically generated niches in host immune space, which can be interpreted as strains. Negative frequency-dependent selection therefore shapes the organization of the var diversity into parasite genomes, leaving a persistence signature over ecological time scales. Multilayer networks extend the scope of phylodynamics analyses by allowing quantification of temporal genetic structure in organisms that generate variation via recombination or other non-bifurcating processes. A strain structure similar to the one described here should apply to other pathogens with large antigenic spaces that evolve via recombination. For malaria, the temporal modular structure should enable the formulation of tractable epidemiological models that account for parasite antigenic diversity and its influence on intervention outcomes.\n\nSignificanceMany pathogens, including the causative agent of malaria Plasmodium falciparum, use antigenic variation, obtained via recombination, as a strategy to evade the human immune system. The vast diversity and multiplicity of genes encoding antigenic variation in high transmission regions challenge the notion of the existence of distinct strains: temporally-persistent and specific combinations of genes relevant to epidemiology. We examine the role of human immune selection in generating such genetic population structure in the major blood-stage antigen of Plasmodium falciparum. We show, using simulated and empirical data, that immune selection generates and maintains modules of genomes with higher genetic similarity within, than between, these groups. Selection further promotes the persistence of these modules for much longer times than those of their constituent genomes. Simulations show that the temporal modular structure reduces the speed at which hosts acquire immunity to the parasite. We argue that in P. falciparum modules can be viewed as dynamic strains occupying different niches in human immune space; they are thus relevant to formulating transmission models that encompass the antigenic diversity of the parasite. Our analyses may prove useful to understand the interplay between temporal genetic structure and epidemiology in other pathogens of human and wildlife importance.

ecology↗

bioRxiv2017

Networks of genetic similarity reveal non-neutral processes shape strain structure in Plasmodium falciparum

Pathogens compete for hosts through patterns of cross-protection conferred by immune responses to antigens. In Plasmodium falciparum malaria, the var multigene family encoding for the major blood-stage antigen PfEMP1 has evolved enormous genetic diversity through ectopic recombination and mutation. With 50-60 var genes per genome, it is unclear whether immune selection can act as a dominant force in structuring var repertoires of local populations. The combinatorial complexity of the var system remains beyond the reach of existing strain theory, and previous evidence for non-random structure cannot demonstrate immune selection without comparison to neutral models. We develop two neutral models that encompass malaria epidemiology but exclude competitive interactions between parasites. These models, combined with networks of genetic similarity, reveal non-neutral strain structure in both simulated systems and an extensively sampled population in Ghana. The unique population structure we identify underlies the large transmission reservoir characteristic of highly endemic regions in Africa.

ecology↗

bioRxiv2017

Conservation of single amino-acid polymorphisms in Plasmodium falciparum erythrocyte membrane protein 1 and association with severe pathophysiology

Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) is a parasite protein encoded by a multigene family known as var. Expressed on the surface of infected red blood cells, PfEMP1 plays a central role in parasite virulence. The DBL domain of PfEMP1 contains short sequence motifs termed homology blocks. Variation within homology blocks, at the level of single amino-acid modifications, has not been considered before in association with severe disease. Here we identify a total of 2701 amino-acid polymorphisms within DBL homology blocks, the majority of which are shared between two geographically distant study populations in existing transcription data from Kenya and in a new genomic dataset sampled in Ghana. Parasitemia levels and the transcription levels of specific polymorphisms are as predictive of severe disease (AUC=0.83) and of the degree of rosetting (forecast skill SS=0.45) as the transcription of classic var groups. 11 newly categorized polymorphisms were strongly correlated with grpA var gene expression (SS=0.93) and a different set of 16 polymorphisms was associated with the H3 subset (SS=0.20). These associations provide the basis for a novel method of relating pathophysiology to parasite gene expression levels--one that, being site-specific, has more molecular detail than previous models based on var groups or homology blocks. This newly described variation influences disease outcome, and can help develop anti-malarial intervention strategies such as vaccines that target severe disease. Further replication of this analysis in geographically disparate populations and for larger sample sizes can help improve the identification of the molecular causes of severe disease.

genomics↗