Expanding our fundamental knowledge of gene-proximal regions to improve selection models

Consortia results

Building an interdisciplinary community

The consortium, created in 2024, brings together 12 members with complementary profiles (biologists, geneticists, experts in bioinformatics and informatics, and statisticians) across three sites (Ile-de-France, Clermont-Ferrand and Montpellier). It enables members to work together effectively and to share tools. These interactions have encouraged the emergence of a shared language and an improved mutual understanding of discipline-specific constraints and benefits.

Exploration and critical analysis of existing approaches to the detection, characterization and prediction of Cis-regulating elements (CREs)

This collective work enabled the relevance of different methodological approaches to be assessed, data needs to be identified, and the necessary conditions for informed biological modelling to be defined. Initial tests, which involved, in particular, the mapping of CREs in various plant species, provided the evidence base for this assessment.

The bibliographical analysis conducted brought the limitations of current approaches into focus, particularly their lack of biological interpretability, their limited transferability between species, and the difficulty they have in predicting  complex phenotypes. It helped to build a clearer picture of the scientific obstacles that still lie in the path of the effective application of such methods to the improvement of plants. This work enabled an opinion article to be produced, which is currently in press. It proposes a shift in the study of CREs toward approaches that explicitly integrate transcriptional regulatory mechanisms, along with their organization and evolutionary context, in order to move beyond a purely statistical predictive framework and strengthen model interpretability.

Future directions: launch of the Precursor-2 Exploratory Project (2026-2028)

The PRECURSOR network has leveraged the development of new approaches, not least the PRECURSOR-2 exploratory project, which successfully obtained funding through the 2026 DIGIT-BIO AMI. PRECURSOR-2 will make use of recent artificial intelligence methods, including deep learning models and language models applied to DNA sequences, seeking to identify and systematically map CREs. By applying such approaches to multiple genomes (both nuclear and plastidial) and to species, the project intends to assess their  robustness and transferability. A second major line of inquiry for PRECURSOR-2 is the exploration of the functional associations between CREs and transposable elements, in which sequencing data, functional data and adapted modelling frameworks are combined. Last, the project also aims to test the explanatory and predictive capabilities of CREs with regard to gene expression and traits of agronomic interest, particularly under conditions of environmental stress.  The investigatory principle underlying all these actions is the integration of CREs into quantitative genetics and systems genetics approaches, thereby complementing traditional approaches based on anonymous markers.

Contact-coordination

Project participants

INRAE structures

Non-INRAE partners