• 1. Biodiversity research using low-cost genomic genotyping.
• 2. Methods and software development: 'recombination-aware' phylogenomics.
• 3. Reproductive and genomic diversity in a biodiversity hotspot.

Decreasing costs have made it relatively easy to generate large genomic datasets

Characterize whole genomes from a subset of sequenced markers.

It is important to examine evolutionary history across the entire genome.

Introgression is common throughout the history of many lineages.

Assemble and analyze RAD-seq type data for phylogenetic datasets.

• 1. Biodiversity research using low-cost genomic genotyping.
• 2. Methods and software development: 'recombination-aware' phylogenomics.
• 3. Reproductive and genomic diversity in a biodiversity hotspot.

"Hack the Planet" course: introduces students to scientific coding skills while guiding them through the process of developing and distributing a software tool.

Shadie: A Python wrapper to perform SLiM simulations of plant life cycles.

Traversome: Hybrid PanGenome Assembler from Mixed Samples

superMCC: Iteratively applies BPP to calibrate node ages on large trees

ipcoal: integrates msprime coalescent simulations with species tree & network inference.

toytree: Python-based Tree object, manipulation, visualization, and evol. analysis library.

Genomes are composed of a mosaic of segments inherited from different ancestors,
each separated by past recombination events.

Consequently, genealogical relationships vary spatially across genomes.

The multispecies coalescent (MSC) describes the expected distribution of unlinked genealogies, as a function of demographic model parameters (N$_e$, $\tau$, topology).

The multispecies coalescent (MSC) describes the expected distribution of unlinked genealogies, as a function of demographic model parameters (N$_e$, $\tau$, topology).

The expected distribution of linked genealogical variation is poorly characterized.

• Subsampling unlinked loci effectively discards >99% genomic info.
• Ignoring linkage introduces bias (concatalescence; Gatesy 2013).
• Local ancestry is informative about selection and introgression.

• Subsampling unlinked loci effectively discards >99% genomic info.
• Ignoring linkage introduces bias (concatalescence; Gatesy 2013).
• Local ancestry is informative about selection and introgression.
• We lack a null expectation for spatial genealogical variation.

• Background: SMC' and waiting distances.
• Our new extension: MS-SMC waiting distances.
• Validation of analytical results to simulations.
• New framework for MSC model likelhoods from linked genealogies.
• Future of 'spatial-genomic' phylogenetics.

An approximation of the coalescent with recombination

Process: recombination occurs w/ uniform probability anywhere on a tree (t$_{1}$), creating a detached subtree, which re-coalesces above t$_{1}$ with an ancestral lineage.

PSMC (Li & Durbin 2011), MSMC (Schiffels & Durbin 2014), use pairwise coalescent times between sequential genealogies to infer changes in N$_e$ through time.

ARGweaver (Rasmussen et al. 2014) and ARGweaver-D (Hubisz & Siepel 2020) use an SMC'-based conditional sampling method to infer ARGs from sequence data.

(a) no-change; (b-c) tree-change; and (d) topology-change.

(Deng et al. 2021)

Expected Tree and Topology Distances represent new spatial genetic information.

Expected Tree and Topology Distances represent new spatial genetic information.

Expected Tree and Topology Distances represent new spatial genetic information.

Barriers to coalescence and variable N$_e$ among species tree intervals.

Genealogy embedding table with piecewise constant coal rates in
all intervals between coal events or population intervals.

Unlike single-pop models which exhibit monotonic probabilities over the length of a branch, MSC models exhibit variable rates (both $k$ and N$_e$ can change).

Expected number of sites until a recombination event is observed.

Analytical results match expectation of stochastic coalescent simulations.

Calculate the likelihood of an ARG given a species tree (S)

Topology-changes are more informative than tree-changes; optima at true sim. values.
Example: loci=50, length=0.1Mb, recomb=2e-9, samples-per-lineage=4.

Metropolis Hastings MCMC converges on correct w/ increasing data.
Example: loci=50, length=0.1Mb, recomb=2e-9, samples-per-lineage=4.

• We extended method of Deng et al. (2021) to MSC models
• New likelihood framework to fit MSC models from waiting distances!
• Enables new continuous recombination-aware phylo. inference.
• Manuscript: McKenzie & Eaton (2023) Biorxiv (In review)
• Implemented at https://github.com/eaton-lab/ipcoal/

• 1. Biodiversity research using low-cost genomic genotyping.
• 2. Methods and software development: 'recombination-aware' phylogenomics.
• 3. Reproductive and genomic diversity in a biodiversity hotspot.

Negative fitness consequences imposed by one organism on another by disrupting successful reproduction.

• We showed evidence of RI: phenotypic overdispersion in >200 assemblages.
• i.e., co-occurring species have more dissimilar flowers than expected.
• Eaton & Ree (2012) Ecology

Have evolved multiple times independently (Ree 2005) and facilitate pollen tube competition (Tong and Huang 2016).

Transcription response in styles and pollen tubes during con- and heterospecific crosses in natural communities at RMBL in Colorado.

• 1. Biodiversity research using low-cost genomic genotyping.
• 2. Methods and software development: 'spatial' phylogenomics.
• 3. Reproductive and genomic diversity in a biodiversity hotspot.

Divergent selection is greater between populations in sympatry than allopatry (e.g., benthic/limnetic sticklebacks) to reduce competition for limited resources.

The challenge/opportunity in Pedicularis is that there are many interacting species, and many have convergent phenotypes. We need a community model of character displacement.

Hypothesis: Differences among populations (within species) are a result of interspecific interactions driving character displacement in local communities.

• 110 individuals from 15 targeted locations.
• RAD-seq (original) PstI enzyme, ~5M reads per sample;
• ipyrad min50 assembly: 20K loci, 21% missing, 286K SNPs

Phenotypic model is a poor fit compared to phylogenetic nearest neighbor.

P. cranolopha tends to have a longer style when co-occurring with a close relative.

P. cranolopha species complex is taxonomically challenging. Split into species/subspecies based on style length, pubescence, and presence of a "forked beak". But variation is relatively continuous.

Hybrid zones: contact between populations with "forked beak" and without.