NSF Postdoctoral Fellowship in Biology: Developmental Determinacy as an Adaptation to a Stable Environment: Characterizing Distinct Life History Strategies in the Monkeyflowers

This action funds an NSF Plant Genome Postdoctoral Research Fellowship in Biology for FY 2022. The fellowship supports a research and training plan in a host laboratory for the Fellow who also presents a plan to broaden participation in biology. The title of the research and training plan for this fellowship to Jesús Martínez-Gómez is “Developmental Determinacy as an Adaptation to a Stable Environment: Characterizing Distinct Life History Strategies in the Monkeyflowers”.

The host institution for the fellowship is the University of California, Berkeley and the sponsoring scientists are Drs. Benjamin Blackman and Yun Song.

Biological lineages at all levels, from cancer cells in a tumor to the giant fungi of the late Devonian, are continuously buffeted by evolutionary forces. Predicting how natural populations respond to these forces is a fundamental challenge both for extending our understanding of the principles of life as well as for many applied biological research programs.

Inferences from evolutionary biology inform development of management plans to conserve threatened species in the face of anthropogenic induced climate change. Inferences also have the power to identify causal genomic variants that underlie complex crop traits in plants. This project will employ both natural populations and experimentally evolved populations of the genus Mimulus (monkeyflowers) with novel methods in population genetics and genome sequencing to understand how changes to genomic architecture resulted in transitions between two distinct forms of the annual life history through evolution.

Broader impacts include mentoring and training undergraduate students as well as partnering with the UC Botanical Garden of Berkeley to develop a self-guided tour through the Garden as well as curricula for a new discovery-based undergraduate research course that will introduce students to observation-based research focused on plant-pollinator interactions. Training objectives include obtaining expertise in computational methods, modeling, and ecological and quantitative genomics.

This project will focus on two quantitatively distinct types of the annual life history strategy in the genus Mimulus: opportunistic annuals, where new flowers develop and fruits matures while resources allow, and deterministic annuals, where all flower and fruit develop in tandem. The former is hypothesized to be better suited in more unpredictable environments, and the latter to be better adapted to more predictable environments.

To provide a framework for predicting population responses to climate change, the project will take two complementary approaches. First, novel machine-learning based approaches in population genomics will be applied to jointly infer historic demographic parameters and targets of selection. This work will leverage genome resequencing data obtained for several hundred individuals sampled from populations that differ between these life history strategies to identify putative regions of the genome that underlie this phenotypic variation.

The second aim will take an ‘evolve and resequence’ approach to ‘re-evolve’ the deterministic annual strategy from the opportunistic annual strategy in a greenhouse setting by selecting for both earlier flowering and faster fruit maturation. Selected individuals in each generation will be sequenced, and sequence data will be used to validate machine learning based population genomic models. All project outcomes will be made available through long-term public repositories.

Keywords: Mimulus, experimental evolution, population genomics, life history

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.