Evolution of the genetic load during biological invasions – GENLOADICS

The measurement of life history traits that is typically considered to test the purge hypothesis is extremely difficult to implement. It requires working on living populations, which is difficult, or even impossible for some species. Today, high-throughput sequencing methods theoretically make it possible to compare the frequencies of deleterious or potentially deleterious mutations between populations on any species. We propose to test the purge hypothesis on a large taxonomic scale - 10 non-model insect species. To do this, we will use a full-genome sequencing approach on several populations of each species. We will then focus on the coding regions of the genome to quantify and compare the genetic load of native, invasive and spatially expanding populations.

The GENLOADICS project has produced, for the first time, high-quality genomes for three invasive insects of economic importance: the box tree moth, the western conifer seed bug, and the Guatemalan potato tuber moth. These genomic resources did not exist prior to the project. They are now available in public databases and provide a valuable tool for research, whether to study the biology of these species, their adaptation, or their control.

GENLOADICS has also made it possible to develop a bioinformatic analysis pipeline to measure the genetic load of populations, that is, the proportion of potentially deleterious mutations they carry. This tool, designed to be applicable to a wide range of species, provides a standardized framework for comparing populations and tracking their evolutionary trajectories. We initially tested it on two well-known invasive insects: the western corn rootworm and the harlequin ladybird. The results showed that the accumulation or purging of deleterious mutations could vary greatly from one species to another, confirming the importance of having a common framework to analyze these dynamics.

One of the major contributions of the project is the creation of a unique sequencing database covering ten invasive insect species and more than fifty populations sampled across all continents. For the first time, these data make it possible to address, in a comparative and large-scale manner, the question of genetic load in biological invasions. The first analyses show that the evolutionary trajectories of genetic load are highly contrasted depending on the species: some populations show signs consistent with the elimination of deleterious mutations, while others, on the contrary, show accumulation. There is therefore no simple or universal pattern.

These results confirm that the dynamics of genetic load is a complex process that cannot be reduced to a single hypothesis. They open new perspectives for understanding why some introductions lead to successful invasions while others fail. The data and tools developed in GENLOADICS will also have an impact beyond the field of invasions: they will be useful for conservation biology, the improvement of domesticated species, and the development of biological control strategies.

One perspective of the GENLOADICS project concerns the study of another type of mutations, called structural variations. Unlike single nucleotide mutations, which affect a single “letter” of DNA, structural variations modify entire sections of the genome (duplications, inversions, deletions, etc.). They can have very significant effects on gene function and the adaptation of organisms. Their study was until recently difficult, but recent advances in sequencing and computing now make it possible to explore them. The approaches developed in GENLOADICS can be adapted to these data, to assess their role in the genetic load and compare their influence with that of point mutations.

A second perspective is the development of dedicated computational tools. Today, sequencing data from “pools” (pool-seq), which consist of analyzing a mixture of individuals rather than each one separately, are increasingly used because they allow many populations to be studied quickly. We are considering creating software, for example in the form of an R package, that would bring together within a single framework all the necessary steps: data preparation and processing, classification of mutations according to their impact, and calculation of genetic load indices. Such a tool would greatly facilitate the use of these methods by the scientific community and ensure reproducible analyses.

The project also highlights a more general methodological need: to compare and evaluate the different ways of classifying mutations according to their potentially deleterious nature. Several approaches exist today (based on gene annotation, sequence comparison across the tree of life, or artificial intelligence), but they sometimes give different results. It is essential to better understand their advantages and limitations, and to link their predictions to concrete data, for example on performance or survival of individuals.

Finally, the project paves the way for very large-scale studies in various contexts. Genetic load can be studied not only in biological invasions, but also in biodiversity conservation, domestication of cultivated or farmed species, and biological control. Depending on the objectives, different sequencing approaches can be combined: pool-seq, well suited to exploring many samples, and individual sequencing, which makes it possible, for example, to directly assess inbreeding.

Ongoing project

Biological invasions are a major component of global change. Yet it is still not understood why some introduced populations are invasive and others are not. Among the most interesting hypotheses is the purging (i.e. elimination) of deleterious mutations during the introduction process. Deleterious mutations constitute what is called the genetic load because they are responsible for a decrease in the fitness of individuals by accumulating in the genome over time. After the introduction of a small number of individuals into the future invaded area, high levels of inbreeding and genetic drift lead to the exposure of deleterious mutations to natural selection. This can have two consequences: the decrease of the average fitness of the population and the purging of deleterious mutations. The assumption we make is that the populations that will actually become invasive are those that have purged part of their deleterious alleles. Indeed, they will have a major evolutionary advantage because they will be less subject to inbreeding depression and will thus better tolerate the low densities encountered during the establishment phase and during any secondary introductions. On the other hand, theory suggests that the genetic load that has not been purged could then become fixed on the fronts of geographic expansion by genetic drift (we use the expression "expansion load"), and thus compromise the success of the invasion in the longer term.
The measurement of life history traits that is typically considered to test such hypotheses is extremely difficult to implement. It requires working on living populations, which is difficult, or even impossible for some species. Today, high-throughput sequencing methods theoretically make it possible to compare the frequencies of deleterious or potentially deleterious mutations between populations on any species. We propose to test the purge hypothesis on a large taxonomic scale - 10 non-model insect species. To do this, we will use an exon capture protocol developed in our laboratory and suited to non-model species, and then we will quantify and compare the genetic load of native, invasive and spatially expanding populations.
The objective of this project will be both a technical and scientific first: (i) application of a protocol to capture exomes and compare genetic loads generalizable to non-model species, (ii) testing the hypotheses of deleterious allele purging and expansion load on key populations of a large number of invasive species. This project will provide an almost definitive answer to the purge hypothesis in invasion biology and will constitute a very important technical opening for studying the evolution of the genetic load in a variety of organisms of interest (e.g. biological control agents, domestic animals, threatened species).