[Popgenlunch] Uncovering the properties and limitations of models of sequence evolution, Dr. Stephanie J. Spielman, PhD, July 21st

Jesse Bloom jbloom at fredhutch.org
Wed Jul 20 08:15:40 PDT 2016

Stephanie Spielman will be giving a seminar tomorrow at the Hutch on
quantitative phylogenetic models of protein evolution. It should be an
excellent talk! Details are below.


Center for Inference and Dynamics of Infectious Diseases Seminar

*Uncovering the properties and limitations of models of sequence evolution*

*Dr. Stephanie J. Spielman, PhD*

Institute for Genomics and Evolutionary Medicine at Temple University

*Thursday July 21, 2016, 10:30–11:30AM*

Pelton Auditorium, Weintraub Building, B1-065

Fred Hutch

*Refreshments will be served; Registration is not necessary to attend this


Natural selection leaves signatures of its activity in DNA. As sequencing
increasingly assumes a central role in modern biological research, we have
an unprecedented opportunity to elucidate the myriad ways in which
evolution shapes the diversity of life's genomes. Most commonly, we study
these "fingerprints" of natural selection using statistical models of
sequence evolution. In the context of of protein-coding sequence evolution,
two popular complementary models have emerged: dN/dS-based models, which
measure the relative rate of nonsynonymous to synonymous substitutions, and
mutation—selection models, which measure site-specific amino acid
propensities (or "fitness") using population genetics principles.
Importantly, these models have been constructed and studied independently
from one another. As a consequence, it has been entirely unknown whether
different models reveal similar or incompatible information about the
strength and direction of natural selection, in turn hindering our ability
to draw robust conclusions about evolutionary pressures. In this talk, I
will discuss how we can bridge this gap by deriving a precise relationship
between dN/dS-based and mutation—selection models. I use this relationship
to identity previously unappreciated limitations and behaviors of these
models. For example, this work reveals that dN/dS inferences in the popular
software PAML (codeml) are strongly biased, and further that standard
metrics of model selection (AIC and BIC)

may be positively misleading. I offer specific recommendations for how to
most reliably apply models of protein-coding sequence evolution and
interpret their results.

*Seminar Sponsors:*

*To arrange a meeting with *Dr. Spielman,

*Contact: Jesse Bloom */ jbloom at fredhutch.org or *Rebecca Allen */
rebecca at fredhutch.org
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