Satellite DNAs (satDNAs) are heterochromatic repetitive sequences that represent a large fraction of eukaryotic genomes. Paradoxically however, their functions remain largely unknown for two main reasons. First, for decades, they were considered as "junk" DNA and therefore were not studied and second their characteristics make them difficult to manipulate. However a growing number of studies is now showing that they may have important cellular functions. They are transcriptionally active in a developmental and tissue-specific manner suggesting that they require a tight transcriptional regulation. Moreover, perturbations of human satDNA organization have been linked to diseases such as Facioscapulohumeral Muscular Dystrophy or cancers, underlying the importance of increasing our knowledge about these regions. The SPERMATOSAT project takes advantage of the Segregation Distorter (SD) system in Drosophila to address the functional relevance of satDNAs. In the SD system, males do not transmit to their progeny a wild-type chromosome that bears a large number of copies (>2000) of a satDNA called Rsp, when the homologous chromosome carries a mutation called Sd. By contrast, this mutation does not affect the transmission of the Rsp satDNA when it contains a few hundred repeats. Thus, in SD males, the strength of the distortion is directly linked to the number of Rsp satDNA repeats. At the cytological level, it has been established that spermatids bearing large Rsp present an abnormally condensed chromatin and are eliminated during the histone-to-protamine transition, a complex chromatin remodeling mechanism that replaces most histones by sperm specific nuclear proteins. Nevertheless, the molecular mechanisms involved in the distortion remain largely unknown. Using genetics, molecular and cellular tools, the SPERMATOSAT project aims at characterizing the chromatin organization of the Rsp satDNA in the male germ cells and at understanding how it impacts the progression of male germ cell differentiation. The SPERMATOSAT project will focus on three major aims. The first one will be to characterize in details the cellular events that leads to the elimination, in SD males, of the spermatids that carry a large number of Rsp satDNA copies. The second aim is to determine the modifications of the Rsp satDNA chromatin that could explain the SD phenomenon. Notably, we will use a battery of approaches to study, in control and SD males, the dynamics of Rsp chromatin condensation through spermatogenesis, the chromatin composition and the transcriptional activity of Rsp in male germ cells. The third aim will explore the hypothesis of a checkpoint during the histone-to-protamine transition that eliminates abnormal spermatid nuclei. For that, we will perform a genetic screen to identify modifiers of the cytological SD phenotype. This screen should also help to understand the molecular mechanisms at play in SD males and to identify new genes involved in the histone-to-protamine transition itself. The SPERMATOSAT project should thus provide new insights into satDNA functions but also help to better understand the constraints of the histone-to-protamine transition on the epigenome of the spermatids.

Humans exert a growing influence over climate characterized by rising temperatures and associated regional changes in weather patterns affecting the quantity and timing of precipitation. This is particularly preoccupying in arid and semi-arid ecosystems, such as southern African savannas, which have experienced a significant decline in rainfall, an increase in the severity of droughts and an extension of the dry season, and for which models generally predict that rainfall will continue decreasing. This increasing aridity is expected to alter the functioning of natural ecosystems. In this context, a key issue is how species interactions will evolve with changes in environmental conditions. The aim of the project FUTURE-PRED is to provide one of the first empirical study to measure the impacts of changes in environmental conditions on predator-prey interactions in a large mammalian system. Whereas cursorial predators chase down their prey over long distances and are therefore more likely to kill weak individuals, ambush predators rely on concealment to hunt by surprise prey moving within a chasing distance, and hence their hunting success is mainly dependent on concealment opportunities. Arid and semi-arid ecosystems are characterized by two contrasting (wet and dry) seasons. As the dry season progresses, there are fewer leaves on woody plants, grass becomes sparser and shorter, and vegetation quality decreases, leading to two major changes likely to affect predator-prey interactions: (i) large herbivores become in poorer body condition and hence are expected to become easier to catch by cursorial predators, and (ii) vegetation provides less concealment opportunities for ambush predators, which should then become less efficient hunters. We will first evaluate how environmental conditions (through comparison of dry and wet seasons, changes as the dry season progresses, and comparison of 2 areas) affect the hunting success of the two most common African apex carnivores characterized by contrasting hunting modes (the African lion - ambush predator - and the spotted hyaena - cursorial predator -). We will equip 15 individuals of each species for 3 years with GPS-collars with satellite transmission of the GPS data and integrated tri-axial accelerometers-magnetometers to test the hypotheses that as the dry season progresses, the hunting success of cursorial predators increases while that of ambush predators decreases. Thanks to the field investigation of feeding sites, we will further assess the type of prey eaten (prey species, age class, livestock vs. wild prey, body condition), the characteristics of the surrounding vegetation, and whether the contribution of scavenging to foraging tactics changes. Finally, we will investigate the consequences of increasing dryness and associated changes in carnivore hunting success on carnivore population dynamics by (i) assessing whether higher carnivore hunting success leads to higher carnivore reproduction success, (ii) studying the role of environmental conditions on carnivore survival and population dynamics through the analysis of a long-term individually based lion dataset (840 individuals in 45 groups since 1999), and (iii) modelling carnivore population dynamics under different scenarios of climate change based on our findings. To our knowledge, such a mechanistic approach to bridge the gap between individual behaviour and population dynamics has never been done for a large carnivore species. FUTURE-PRED will be led and coordinated by Marion Valeix, and carried out in the CNRS LTSER (Zone Atelier) Hwange, Zimbabwe. By combining original new data with long-term individually based monitoring of large mammalian carnivores, the project FUTURE-PRED has the ambition to provide an integrative study of the effect of environmental conditions on large mammalian predator-prey interactions.

Infectious diseases transmitted by mosquitoes, such as dengue or chikungunya, are of worldwide concern. Within a mosquito population, the viral infection rate may be rather low and highly variable, and the causes of this variation remain unknown. All genomes contain genomic parasites called transposable elements (TEs), which resemble viruses, and also display variable amounts and activities. TEs are controlled by small RNAs of the piRNA class, and viruses are fought against by small RNAs of the siRNA class. Considering these similarities in structure and control pathways between TEs and viruses, we propose to use a Drosophila model to study the reciprocal impacts of TE control and antiviral immunity. Our preliminary results indicate that, upon infection, TE transcript amounts are modulated, as well as their controlling small RNAs. In this project, we will 1) identify the effects of viral infection on TE activity, and reciprocally, 2) identify the underlying mechanisms, and 3) assess the extent of the phenomenon in the frame of natural genetic variability. This will allow us to better understand variation in viral load, notably regarding arboviruses, and propose the use of TE activity as a marker for vectorial competence. In addition, if viral infections are associated with TE activation, we will have to consider viral epidemics as a new source of genetic diversification.

The tremendous variability of behaviors observed between individuals, and across populations and species, makes studying the molecular basis of behavioral traits particularly challenging. Little is known on how genes contribute to shape behaviors. Recent progress in genomics represents a fantastic opportunity to tackle this cornerstone question. AVOIDINBRED aims to decipher the genetic basis of kin recognition in the parasitoid Venturia wasp. The kin recognition behavior is critical to animal biology including in the context of mating: by allowing individuals to avoid mating with sibs, kin recognition determines individual fitness in numerous animal species (social and solitary) by reducing the risk of inbreeding depression, consanguinity. Kin recognition has population consequences in terms of genetic diversity, where inbreeding causes erosion of the genetic diversity and can lead ultimately to extinction. In AVOIDINBRED, we will identify and characterize candidate genes involved in kin recognition during mating in the Venturia wasp by genomic approaches, and perform strategic functional validation of candidate genes and pathways using specific genetic manipulations as well as global pharmacological manipulations. The project will provide new knowledge in behavioral ecology where the question of how genes influence behavior is fundamental. Over mid-term, it will contribute to develop new strategies in conservation biology in particular for hymenoptera insects known to have important ecological and economic functions as pollinator or biocontrol agents. The coordinator will benefit from an excellent scientific environment to implement the project and to successfully develop this exciting research axes.

Genetic variation can have causal effects on a variety of phenotypes ranging from human health risks to bacterial drug resistance and crop yield. Unraveling the relationship between genotypes and phenotypes is therefore crucial for both basic and applied science. Genomes have historically been treated as small variations around a reference sequence in computational biology and statistics. Genome Wide Association Studies (GWAS) for example typically start by aligning the genomes of all samples in a panel against a reference genome. Each sample is then represented by its set of point mutations, and typical methods test the statistical association between the presence of a mutation and a phenotype of interest. In many important cases however, alignments are not appropriate. Microbes for examples sometimes have entire genes which are not present in all individuals. Most alignment-free representations rely on the exact presence of sub-sequences in the genomes. However, genomic variants are often better described in terms of sequence motifs, indicating frequencies of each letter at each position. The recently introduced CKN-seq method implicitly defines infinite sets of genomic features akin to sequence motifs, and selects the ones that are most relevant for a learning task. The PIECES project will extend CKN-seq and exploit its ability to represent unaligned sequences through three tasks: * GWAS over infinite sets of sequence motifs CKN-seq selects sequence motifs from an infinite set, based on their ability to predict a phenotype. However, no procedure exists to quantify the significance of the association between the selected motifs and the phenotype. We will propose versions of CKN-seq that are amenable to hypothesis testing, allowing their use for GWAS over sets of sequence motifs. The testing procedure will build on selective inference, a recent and active field in statistics. The resulting GWAS method will be used in several already established collaborations with microbiologists to identify genetic determinants of antimicrobial resistances in bacterial genomes, and with an industrial partner interested to detect determinants of human diseases in gut microbiomes. * Alignment-free, interpretable sequence analysis The rapidly increasing availability of biological sequence data also calls for the development of exploratory methods. Most unsupervised learning methods typically require sequences to be aligned and are often slow. On the other hand, existing kernel methods deal with unaligned sequences and are suited to efficient approximations but lose access to the features used to perform the analysis, only returning cluster memberships for clustering or sample projection for PCA. An important challenge is therefore to provide exploratory methods which are fast and alignment-free while remaining interpretable. Accordingly, we will develop an unsupervised version of CKN-seq performing PCA and clustering, making it possible to interpret clusters or principal components in terms of associated motifs. * Learning from populations of sequences We will explore a supervised learning approach to phylogenetic reconstruction: rather than maximizing the likelihood of a model of sequence evolution, we will generate evolutionary trees and sequences from these models and use them to learn a function transforming (observed) distances between sequences into distances on the (unobserved) evolutionary tree. This novel paradigm could improve over existing phylogenetic reconstruction methods, or lead to similar accuracies on much larger sets of species for which existing methods are computationally prohibitive. The supervised learning will be able to exploit both aligned sequences and a novel alignment-free representation of the gene family relying on the same principle as CKN-seq (which deals with individual sequences). We will deliver user-friendly software to maximize the diffusion and impact of successful methods for all three tasks.