Current terrestrial ecosystems did not develop until plants had colonized the land, a crucial phenomenon for the evolution of global biodiversity. Indeed, it is thought that the evolution of early vegetation triggered major climatic transitions and mass extinctions. EARTHGREEN aims at providing new fundamental evidence about the origin, diversification and dispersion of early landscapes and at quantifying their impact on Earth System. In this project, we propose (1) to characterize the early temporal-spatial dynamics of vegetation (Silurian-Mississippian times, ~430-320 Ma), (2) to revise the key steps of early plant evolution and (3) discern the impact of plant evolution on land biosphere. Expected results will allow elucidating the morphological evolution of early floras, their architectural development, and the timing of first land colonization. New insights will allow to improve our knowledge of the relationship between the early land biosphere and the physical environment.

Transposable elements (TEs) are now widely recognized as major contributors to genome evolution, yet the processes governing their accumulation remain elusive. Mating systems are expected to play a central role, but the net effect of the shift from outcrossing to selfing, which occurs commonly in plants, is not known. Here, we propose to determine the genomic landscape of recent TE insertions in the two outcrossing species Arabidopsis lyrata and A. halleri and to compare it to that of their selfing close relative A. thaliana as well as to that of North American A. lyrata populations that are currently experiencing a shift to selfing. This project is made possible by the advent of long reads sequencing technology, which enables the unambiguous characterization of TEs and other repeat sequences as well as of the complex regions in which they tend to cluster. Specifically, we will produce 100 high-quality genome sequence assemblies for A. lyrata and A. halleri. We will also compare the intensity of natural selection acting on new TE insertions between these three species. Finally, we will analyze the patterns and rate of accumulation of TEs in a key region of the genome, the S-locus, which controls self-incompatibility in outcrossing species. This region shows analogy to sex chromosomes because of a lack of recombination, very low sequence homology among self-incompatibility haplotypes, and high rate of TE accumulation. Our findings should provide major insights into how mating systems impact the accumulation of TEs. This project should also elucidate the role of TEs in driving the evolution of the mating system itself in the Brassicaceae through their rapid accumulation at the S-locus and their potential role in the generation of small RNAs controlling the dominance relationships among S-alleles. The methods and paradigms we will generate should have broad implications for the study of species with high level of heterozygosity and much larger genomes, including humans.

Lack of sexual attraction can directly cause reproductive isolation between individuals from different populations. Divergence of sexual processes between populations is therefore considered one of the most powerful drivers of speciation. However, we do not know exactly how these mechanisms of sexual isolation evolve. One plausible hypothesis is that divergent sexual selection driving sexual signals and preferences in different directions may be at the origin of sexual isolation. Here we propose to test this hypothesis in a complex of marine isopods (Jaera albifrons) in which sexual isolation results from female mate choice based on tactile courtship by males. First, we will simultaneously investigate intraspecific and interspecific sexual processes, asking if competition over mates within species drives selection on the same sexual signals that are involved in sexual isolation between species. Second, we will study the genomic patterns associated with sexual isolation, focusing particularly on the role of sex chromosomes and chromosomal rearrangements. Specifically, we will test if these genomic regions affect reproductive isolation through hybrid fitness effects of recombination arrest. We expect this project to tell us if and how sexual isolation evolves from divergent sexual selection, and improve our understanding of the specific role of sex and rearranged chromosomes in speciation.

Modern evolutionary theory developed with the main objective to explain and predict changes in populations from one generation to the next, and how species evolve. Largely independently, paleontologists have accrued a body of knowledge informed by patterns of organismal diversity in deep time, but with the limitations of the fossil record. How mechanisms causing differentiation between populations ultimately contribute to macroevolution, however, remains a central question in evolutionary biology. I propose to address this question by studying mechanisms of differentiation at various levels of biological organization in evolutionary radiations of freshwater mollusks of the East African Rift System (EARS), an outstanding emerging model system. The EARS is geographically subdivided in a set of quasi-replicate systems to study evolution at various spatial and taxonomic scales; its freshwater mollusks are diverse, with life-history traits that typically correlate well to ecological niches; diversification is currently ongoing so that processes leading to speciation can be reconstructed accurately; and ancestors can be followed over long periods with substantial phylogenetic and time control. We will develop insight into the link between microevolution and macroevolution in two work packages (WPs): in WP1 we will study how processes of population differentiation lead to speciation and in WP2 we will embed our findings of WP1 into their wider taxonomic and geographic context to provide insight into macroevolution. Our approach will be similar in both WPs in that we will integrate data on genetic diversity, morphological disparity and habitat characteristics to examine how diversity originates (WP1) and is maintained (WP2). Methodologically, we will develop a next-generation sequencing (NGS) pipeline with two steps: 1) transcriptome sequencing to construct a reference transcriptome, and 2) the construction of an NGS library from transcriptomic data for gene-capture approaches (which can be used on existing EtOH-preserved collections). Additionally, morphological disparity will be studied with the same geometric morphometric methods across both WPs, and ecological data will be collected from sampling localities. In WP1 we will focus on mechanisms of differentiation in two mollusk clades, i.e. Bellamya [4 nominal species] and Nyassunio [3 nominal species] from the Malawi Basin. We aim to determine which processes (ecological or non-ecological) have caused differentiation and how these processes have interacted in space and time in the multiple speciation events that took place or are ongoing. We will obtain insight into mechanisms by comparing the genetic, morphological and environmental bases of differentiation from as many populations in the basin as possible. Specifically, single-nucleotide polymorphism data will be obtained from NGS, geometric morphometric data from shells, and these data will be subjected to population genomic studies together with habitat information. In WP2 we will establish relations in monophyletic clades of Viviparidae and Unionidae (African Bellamyinae and Coelaturini, to which Bellamya and Nyassunio, respectively, belong) on a rift-wide scale from NGS sequence data. These reconstructions will be used to test hypotheses on biogeographic patterns, parallel and iterative evolution, and trait evolution in relation to diversification. Secondly, we will integrate fossil taxa to study patterns of extinction selectivity and to test whether macroevolutionary conclusions based on the modern fauna hold when fossils are included. Finally, results from WPs 1 & 2 will be integrated to examine to what extent microevolutionary patterns affect macroevolution, and thus how drastic differences in diversity even in closely related clades can be explained. Beyond a profound influence on evolutionary biology, this understanding is vital to understand the implications of environmental changes on modern diversity.

In a just published Opinion paper in Trends in Ecology & Evolution, we advocate that a next-generation, global-scale, ecological approach to biomonitoring will emerge in the coming decade, which can detect ecosystem change accurately, cheaply and generically. Next-generation sequencing (NGS) of DNA sampled from the Earth’s environments, would provide data for the relative abundance of operational taxonomic units or ecological functions. Machine-learning methods would then be used to reconstruct the ecological networks of interactions implicit in the raw NGS data in order to detect and predict ecosystem change. In this Next Generation Biomonitoring (NGB) project, we will examine whether NGS samples from five distinct ecosystems undergoing global change can be used to reconstruct hypothetical networks of interaction using machine learning. We will then compare these reconstructed networks with the current state of knowledge for these systems to test whether NGS and machine learning approaches can be used to reconstruct valid ecological networks. These tests will include examining the NGS networks for specific, established interactions through to detailed comparisons against already-known ecological networks, built using classic network construction approaches. The five systems we will work on represent a cross-section of the organisational scales, drivers of change and data quality we would expect that a NGB approach could be applied to. From microbial interaction networks to macro-biome networks of interacting invertebrates, and across drivers of change such as invasion, disease, conservation, management and climate, the project will determine whether ecosystem change can be detected using an NGB approach. We will troubleshoot many of the technical, methodological and ecological problems facing the development of an NGB approach, such as the variable quality of NGS databases, taxa biases, identification errors, zero-rich data and asymmetric abundance distributions, and develop statistical approaches for detecting change and determining the size and power of biomonitoring programs. Ultimately, we envision the development of autonomous samplers that would sample nucleic acids and upload NGS sequence data to the cloud for network reconstruction, using methods that we will develop in the project. Large numbers of these samplers, in a global array, would allow sensitive automated biomonitoring of the Earth’s major ecosystems at high spatial and temporal resolution, revolutionising our understanding of ecosystem change.