Who we are

We are the Crop Evolution & Adaptation Lab (De Vega Lab) at the Earlham Institute (Norwich Research Park, UK).

Our lab aims to be a vibrant place for plant evolutionary genomics that addresses fundamental questions about how genomes evolve and tackles the practical breeding challenges posed by polyploidy, interspecific complexity, and asexual reproduction.

Our focus on allopolyploid crops and established breeding partnerships ensures our research remains grounded in agricultural impact and driven by stakeholders’ needs, while advancing the Institute’s vision to predict biology at scale.

Our code and datasets will be released in accordance with FAIR principles to enable reuse and cumulative improvement by the wider community.

Crop Evolution & Adaptation

One of the central questions in biological research is how phenotypes arise. In this context, our research aims to understand how the evolutionary processes of hybridisation and polyploidisation shape genetic diversity across the genome and how this diversity manifests in agronomic traits that could be leveraged in breeding. We work at the interface of genome evolution and crop improvement.

Our research investigates the mechanistic basis of phenotypic variation, predicts phenotypes, and collaborates with others in breeding and gene editing to engineer phenotypes. Our goal is not simply to catalogue diversity but to understand its effects well enough to deliver outcomes in breeding and impacts on sustainable agrifood.

Biological systems

Many major crops are polyploid or of hybrid origin, particularly among cereals, tubers, and fibre crops. We focus on particular allopolyploid systems, especially bananas and several feed crops, and on species with multiple domestication gene pools, including rice and beans. Hybridisation is a common mechanism of diversification and, in plants, is often associated with polyploidisation. Chromosomal duplication can buffer meiotic irregularities and regulatory mismatches more effectively than a diploid background, but can also introduce its own challenges, such as copy number variants and dosage effects.

Hybridisation and polyploidisation usually manifest as extensive structural and epigenetic variation. Using genomics, we quantify the magnitude and persistence of these changes, which vary widely among lineages. Asexual reproduction is also relevant in this context, as apomixis, parthenogenesis, and other modes of asexuality can provide escape routes that bypass fertility constraints and shape how variation is fixed and maintained.

Research objectives

Our first objective is to develop and apply approaches to better understand the mechanistic manifestations and evolutionary consequences of hybridisation, polyploidisation, and asexual reproduction. In practice, this means explaining and predicting how gene flow across lineages, expression dominance, structural variants, and copy number variants arise and influence the evolution of populations and species.

Because hybridisation is widely exploited for crop improvement, for example, in trait introgression and hybrid breeding, our second objective is to translate this knowledge into approaches and resources to improve the efficiency of crop improvement. This provides a clear pathway to impact by linking fundamental questions in genome evolution to strategies that accelerate genetic gain and support sustainable global food production.

How we work

We use genomics and data-driven biology to investigate genome evolution in crops and agronomically important genetic diversity. Our research combines population genomics, genome-wide association analyses, pangenomics, long-read sequencing, quantitative genetics, and phenotype prediction. We are especially interested in the forms of variation that are often poorly captured by single-nucleotide-variant-centred analyses, including structural variation, copy number variation, dosage effects, homoeologous exchange, and epigenetic variation.

We focus on allopolyploid and interspecific crop systems because they are biologically challenging and agriculturally important. Complex crops concentrate the genome-evolution processes — introgression, dosage and structural change, and regulatory remodelling — that most often undermine SNP-centric predictions. Our aim is to develop approaches and resources that are both biologically informative and useful under real breeding conditions, and we continue to release code and data openly to support reuse by the wider community.

Future direction

A longer-term ambition of the lab is to build prediction models that make biological behaviour increasingly predictable from genome, phenotype, and environment, and that improve as new trials, experimental validation, and genomic resources become available. We will explicitly use high-throughput, data-driven biology and AI where appropriate.

We will iterate through discovery, prediction, and experimental validation. The causal findings from our work on genome evolution, together with feature prioritisation, will provide interpretable inputs for modelling. Predictions can then be tested through trials, bioassays, and collaborator-led validation. In this way, the lab aims to move from understanding how crop genomes evolve to developing predictive genomics to improve crops.