The Division congratulates Associate Professor Elizabeth King on her receipt of a $1.9 million grant from the Maximizing Investigators’ Research Award (MIRA) program of the NIH National Institute of General Medical Sciences (NIGMS). The prestigious five-year grant provides flexible, long-term funding for King’s research program, which focuses on designing novel strategies and tools for studying the causal connections between the genome and highly complex traits.
In the project summary, King notes that most complex traits, including human health, are highly complex and hierarchical and the products of the combined effects of a suite of sub-phenotypes. These trait hierarchies are typically influenced by many genetic variants of small effect that interact with one another and with environmental factors. Yet, most research strategies are done in one environment and typically focus on understanding one trait at time.
“Science hasn’t fully grappled with the ‘complex’ part of complex traits and that’s left a significant knowledge gap in our understanding of the genetic basis of these traits,” says King. “Our work embraces this complexity by focusing explicitly on the interconnectedness between multiple high-order traits and the sub-phenotypes that come together to shape them.”
The project takes advantage of King's extensive background studying resource allocation traits using a combination of a large multiparent mapping population (MPP) and experimental evolution in the fruit fly model system.
Per her proposal, “We will use our established experimental evolution system to select on multiple high-level phenotypes that are known to be energetically expensive: flight performance, olfactory learning performance, and late life reproductive ability, using the same admixed MPP base population for each. We will employ largescale phenotyping over time, observing how high-level phenotypes change in each selection regime and how intermediate phenotypes evolve across the hypothesized trait hierarchy, with a focus on energetic phenotypes with additional studies at the transcriptome level and the genomic level.”
By studying a set of complex traits simultaneously, she hopes to test key hypotheses about the evolutionary dynamics of trait hierarchies. Ultimately, the work will provide general insights about how genomes are connected to physiology to produce the interconnected set of traits that affect health across a lifespan.