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\title{Genomic data improve coalescent inference across a range of demographic
parameters and life-histories}



\author[1]{Michael Hart}%
\author[1]{Vanessa Guerra}%
\author[2]{Maria Byrne}%
\author[3]{Jon Puritz}%
\affil[1]{Simon Fraser University}%
\affil[2]{University of Sydney}%
\affil[3]{University of Rhode Island College of Arts and Sciences}%


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  \date{May 07, 2024}


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\begin{abstract}
Understanding the demographic context for population divergence and
speciation in the sea often requires distinguishing the contributions of
mutation, isolation, and gene flow on temporal or geographical scales
where those diverse processes may not achieve equilibrium conditions.
Coalescent isolation-with-migration (IM) models can meet this need for
non-equilibrium modelling of genetic variation, but the quality of IM
model parameter estimation depends on the breadth of genome sampling.
Here, we describe three improvements in IM parameter estimates based on
hundreds of loci from RNA-seq assemblies relative to previously
published results based on few loci in two sea star study systems that
differ in the tempo of population divergence. (1) Precision of all model
parameter value estimates (with narrow posterior distributions) was
vastly better in both study systems and resolved uncertainty around one
key parameter in each. (2) Maximum likelihood estimates of some model
parameters were broadly similar to previously published estimates, but
with greater precision we obtained more realistic values for some
parameters that were consistent with expectations based on the
biogeography of the organisms. (3) We found non-zero but demographically
trivial gene flow in one study system where we previously estimated gene
flow to be zero, and modest symmetrical gene flow (2Nm\textless{}1) in a
second study system where we previously estimated gene flow to be
massive (2Nm\textasciitilde{}10) and asymmetrical. Improved
understanding through judicious application of genome-wide sampling in
replication studies as shown here may improve the information needed for
biodiversity management and conservation.%
\end{abstract}%



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