Published: March 3, 2016

Assisstant Professor, Sam Flaxman was recently awarded a NSF grant for his research on genomic acrchitecture of speciation. See NSF title and abstract below.

Title: How predictable is the evolving genomic architecture of speciation?


Part 1. Non-Technical Description:

Moderneemed impossible to achiev   Currently, one of the biggest challenges is analyzing the data in ways that reliably extract signals from noise.  Specifically, genome sequences from individuals in a population contain information that can be used to unravel the biological history of the population and to discover which genes are adaptive, deleterious, or just along for the ride.  However, extracting this information and using it to draw such conclusions is a far from trivial undertaking due to the massive scale of modern datasets and due to the many complex and interrelated factors that affect how populations change over time.  The proposed research will develop new computational methods for inference from population genomic data.  The development of these new methods aims to improve scientists' abilities to use population genomic data to answer a variety of questions, such as: What are the genetic changes associated with adaptation? How repeatable and predictable are the genetic changes associated with the diversification of an ancestral species into a variety of modern species (i.e., an "adaptive radiation")?  The new methods will be applied to two independent examples of adaptive radiations involving butterflies commonly found in North and Central America because a wealth of excellent data and technical resources already exist for these species.  Beyond making inferences about these particular groups of species, the proposed research will have broader impacts in two main ways.  First, the novel computational methods and software developed in this proposal will be very widely applicable to genetic analysis in a variety of basic and applied scientific disciplines.  This open-source software will be freely disseminated.  Second, the results will form the basis for constructing educational museum exhibits on genomics and the tree of life.


Part 2.  Technical Description:

Natural selection and speciation are the fundamental evolutionary processes responsible for life's fantastic diversity, yet the genes and specific genetic changes responsible for adaptive traits and the genetic mechanisms that cause speciation are largely unknown. Emerging molecular and analytical methods offer great promise to address these issues, but studies of speciation are generally limited by at least two factors. First, studies of a single example of divergence (e.g., in one hybrid zone) suffer from the "n=1" problem: without replication of divergence, the generalities from a single species pair are unclear.  Second, a priori quantitative predictions from multiple, contrasting hypotheses are rarely developed; indeed, there is often little consensus about the patterns expected under a given verbal hypothesis about evolutionary processes. The proposed research will address both issues by using existing empirical data and development of novel theoretical met!

hods to investigate how the species boundary evolves over space and time using multiple species pairs in two independent examples of adaptive diversification among hybridizing lineages of mimetic butterflies: Heliconius and Limenitis. Specifically, the PI will: 1) collaborate to statistically characterize the empirical systems and 2) develop population genomic theory and test quantitative predictions about the accumulation of genomic divergence across the species boundary continuum. The results of this project will provide a uniquely comprehensive portrait of the evolving species boundary in a comparative framework, and will thereby provide a powerful examination of questions about the generalities of evolutionary processes and genomic patterns that characterize speciation at multiple points along the continuum of divergence. These questions include: How porous is the species boundary among hybridizing species? How does divergent selection shape genomic variation among hybridizing lineages? How predictable is the evolving genomic architecture of speciation? In addition to answering these questions, the work will yield broadly applicable computational methods for quantitatively testing hypotheses about the genomic signatures of multiple evolutionary processes acting alone or in concert.