Inflorescence architecture, e.g. the number, length and angle of branches and flowers, is a primary determinant of yield, regulating seed number and harvesting ability. Cereal crops display a diverse array of architectures in their inflorescences, which are fundamentally derived from variations on a common, grass-specific morphology. Research in the Eveland lab leverages this diversity among species, as well as that within a species resulting from natural variation or genetic perturbation (mutant alleles), to understand the gene networks controlling inflorescence development in grasses. Approaches include generation and integration of large-scale genomics datasets that capture precise morphological changes during inflorescence development, computational interrogation of these data to derive testable hypotheses and testing these hypotheses with classical genetics and functional genomics experiments. Cross-species network comparisons with maize, sorghum and Setaria, and the natural variation that exists among them, are used to explore conserved and divergent regulation of developmental programs and how this contributes to specific architectures in cereal crops.
This research addresses important agronomic challenges by identifying key genes and pathways as control points for yield, linking developmental and stress networks, and translating across grasses. The latter include orphan grain crops grown in developing countries that have seen little improvement in yield potential.
Predictive models for grass inflorescence evolution and development.
The Eveland lab makes use of dynamic morphologies during inflorescence development, the molecular phenotypes associated with them, and specific defects that arise from mutations in developmental modulators. Maize is a primary model system in the lab for studying developmental genetics since many mutations, both characterized and uncharacterized, have been described that cause specific defects in inflorescence architecture. Genome-scale datasets (e.g. RNAseq-based expression profiles and transcription factor occupancy maps) representing molecular phenotypes that underlie developmental transitions and genetic perturbations, are integrated using computational-based approaches to predict key regulators of transcription, their hierarchies within gene regulatory networks and their spatiotemporal-dependent co-factors during inflorescence development. Information is also leveraged from comparative transcriptomics analyses across grass species with specific inflorescence morphologies to determine conservation and/or divergence of gene regulatory networks, and how this translates to various architectures. A major interest in the lab is the evolution of gene co-expression and regulatory modules within and across species.
Using model systems and cereal crops to study gene regulation and inflorescence architecture.
While maize is an excellent model for developmental genetics, redundancy in its genome, a relatively long life cycle and significant space requirements limit its efficiency for functional genomics studies. The Eveland lab utilizes emerging genomics resources for sorghum and Setaria to test genetic and regulatory interactions predicted from maize, but also to identify novel factors and regulatory elements contributing to variations in inflorescence architecture across grasses. Mutagenesis screens and natural variation are leveraged to identify new alleles that affect inflorescence architecture in these cereal crops, as well as modifiers of known developmental phenotypes. In addition to understanding how differences and commonalities in the developmental networks shape inflorescences, information from these studies can be directly translated to crop improvement efforts in sorghum and millet, which are staple grain crops in developing country agriculture.
Exploring the effects of drought stress on developmental networks.
The Eveland lab is also interested in how and to what extent developmental networks intersect abiotic stress response networks. Drought stress has devastating impacts on grain yield worldwide, including in the U.S., and primarily in developing countries where crops are grown on marginal lands. The threat of drought on food security is amplified in the face of exponential population growth and a changing climate. Work in the lab focuses on early season drought and how it may contribute to developmental abnormalities that result in lower yields, the response of underlying developmental programs to drought stress at the transcriptional level, and how natural variation affects drought tolerance, as part of an NSF-funded Plant Genome Research Project. Insights from these studies in maize will be translated to other grain crops, for example, drought-tolerant sorghum, to evaluate the extent of similarities and differences in stress response during development.