Evolutionary innovations can occur via several mutational paths but an integrated view of novel gene acquisition at the population level is still lacking. The different mechanisms that generate or introduce new genes in a genome act continuously throughout evolution, resulting in genes of different ages. However, most studies on novel genes were conducted at the interspecific level by comparing a single reference genome per species. Population genomics is presently shifting the field of comparative genomics from single reference genomes to population pangenomes, thereby giving access to individual variations in presence/absence of genes at the population level. The collection of genes present in a population is named the pangenome. The pangenome consists of core genes invariably present in all individuals and accessory genes that are segregating in the population at varying frequencies. Here, we define Novel Accessory Genes (NAGs) as the subset of accessory genes that are not vertically inherited from the species ancestor but were gained or emerged during the diversification of the species. NAGs originate mainly from introgression events, horizontal gene transfers (HGTs) and de novo gene emergence. When novel genes first appear, they are present at very low frequency in a population, likely in a single individual, and subsequently can either disappear or eventually raise in frequency. Therefore, we make the hypothesis that the best evolutionary time scale to investigate gene acquisition mechanisms would be at the population level. We propose to use the yeast Saccharomyces cerevisiae as a model organism to explore, at the species level and at the genome scale, the dynamics of gene acquisition at the time they arise and before they are removed by selection. We will directly benefit both from the high quality population genomic dataset available and the possibility to perform large-scale experimental testing to a level not accessible in any other model organism. The main goal of our proposal is to systematically explore the mechanisms of acquisition of NAGs and their relative contributions to the emergence of evolutionary novelties. First, we will analyse the evolutionary trajectories of NAGs based on high quality population genomics datasets and using state of the art computational approaches. Second, we will measure fitness effect of natural and engineered NAGs by combining genome editing, synthetic biology and high throughput phenotyping. Finally, we will investigate how NAGs functionally wire into cellular networks by measuring transcription, translation and post- translational modifications for both natural and engineered NAGs in various environments in order to quantify their level of i cellular integration. Altogether we plan to generate a large pool of heterogeneous data that we will integrate into a single conceptual framework including information on ecological niches and genetic backgrounds. The outcome of this proposal will provide a multi-layered view of the functional and evolutionary impacts of NAGs in the yeast pangenome revealing general rules leading to the evolution of new genes and new functions in eukaryotes.

A key issue hindering discoverability, attribution and reusability of open research software is that its existence often remains hidden within the manuscript of research papers. For these resources to become first-class bibliographic records, they first need to be identified and subsequently registered with persistent identifiers (PIDs) to be made FAIR (Findable, Accessible, Interoperable and Reusable). To this day, much open research software fails to meet FAIR principles and software resources are mostly not explicitly linked from the manuscripts that introduced them or used them. This project will extend the capabilities of critical and widely used open scholarly infrastructures (CORE, Software Heritage, HAL) and tools (GROBID) operated by the consortium partners, delivering and deploying an effective solution for the management of the research software assets lifecycle, including: 1) ML-assisted identification of software assets from within the manuscripts of scholarly papers, 2) validation of the identified assets by authors, 3) registration of software assets with PIDs and their archival. The solution will be optimised for deployment over open content available through the global network of open repositories aggregated by CORE (core.ac.uk), which constitutes with over 32 million full texts and 250m+ metadata records from over 10k repositories currently the world's largest collection of open access documents. Our ML software for extraction and disambiguation of software assets will be realised as an extension of the state-of-the-art GROBID tool. We will build on established protocols, such as OpenAIRE Guidelines v4.0, RIOXX v3 and Codemeta, to encode information about software assets and their links to research manuscripts establishing an interoperable and extensible workflow connecting open repositories (represented by HAL), aggregators (represented by CORE) and software archives (represented by Software Heritage). The efficacy of the developed tools and workflow will be validated in three use cases: 1) social science with links to DARIAH, 2) life sciences demonstrator (Europe PubMed) and 3) a multi-disciplinary demonstrator (HAL).

Research on domesticated animals has important scientific and socio-economic impacts, including contributing to medical research, improving the health and welfare of companion animals, and underpinning improvements in the animal sector of agriculture. Domesticated animals cover a wide evolutionary spectrum and are characterized by a wealth of genetic and phenotypic diversity shaped by natural and artificial selection. Improving the functional annotation of animal genomes is critical to enabling the bridging of the gap between genotype and phenotype, thus enabling predictive biology. Extensive research has been conducted since decades to elucidate the genetic architecture underlying quantitative traits, and deep pedigrees with extensive phenotypic records exist. However, especially in farm species the annotation of the genome sequence is still largely limited to gene models deduced from alignments with expressed sequences (cDNA, ESTs, RNAseq) and some sequence variation (SNPs, CNVs). This lack of knowledge is a significant barrier to understanding the link between genotype and phenotype in these animal species, as well as to exploit their increasingly recognized biological value in comparative and evolutionary genomics. FAANG is a recent international initiative whose aim is to produce comprehensive maps of functional elements in the genomes of domesticated animal species. FAANG benefits from lessons learnt in similar project such as ENCODE and other large consortia e.g. the International Human Epigenome Consortium (IHEC), which have demonstrated how improved functional annotation can be efficiently delivered collaboratively based on common standardized protocols and procedures. The overarching goal of FAANG is the development of predictive models based on the understanding of the underlying biological mechanisms, particularly the epigenetic control of transcription during differentiation / responses to perturbation in systems of relevance to health and production traits, and how such mechanisms are affected by genetic variation. The white paper of the consortium has been published recently (Andersson et al. Genome Biol. 2015; PMID: 25854118); the proposer of this project is the co-corresponding author, and the partners of the current proposal are main contributors. This proposal (FAANG-ForE) is one of the results from the established collaboration between the core European partners in both ongoing and submitted FAANG-related research, in FAANG coordination roles, as well as in disseminating activities at the level of National and European funding agencies. Established contacts with the European Commission allowed us identifying a path for consolidating the European FAANG leadership towards the creation in the longer term of an International Research Consortium (IRC) for FAANG research. An IRC for FAANG is justified by the recognized need of improved reference genomes and epigenetics knowledge, and by the importance of biodiversity for applied (i.e. new tools to choose genetic resources to be preserved) and research purposes (i.e. regulatory genomic variants which can help deciphering the basis of complex traits). This goal is ambitious and requires an adequate structuring strategy at start. FAANG - ForE aims at reinforcing the role of France as a leading partner in implementing this process. The first step is to coordinate a proposal for a FAANG infrastructure at the forthcoming EU Infrastructure call for “Integrating and opening existing national and regional research infrastructure of European interest”, whose publication is expected in early October 2015. The FAANG infrastructure will contribute an essential framework of reference for genomic data and standards for the French and enlarged European animal genomics community for the proposition of specific “FAANG-related” research topics – for both fundamental and applied research - to future H2020 research calls.