Young Investigators in Population Genetics
Quantitative Biology Seminar
October 31 and November 1, 2008
University of Arizona
Abstracts and
References
General References
History of
Population Genetics by A.H.
Sturtevant
Stochastic Processes in
Evolutionary and Disease Genetics by Ellen Baake, Don Dawson, Warren Ewens,
and Bruce Rannala
Department
of Human Genetics, University of Chicago
Confounding Effects for Population Genetic Inference
of Demography and Selection
Abstract. Understanding which
evolutionary forces have contributed to modern day patterns of genetic
variation within and between species has long been of interest. However, only recently have we seen the
development of tools capable of disentangling evolutionary signals from the
genetic noise produced by a concert of evolutionary forces. One such avenue of development involves
analysis of the frequency distribution of derived mutations pooled from the
entire genome. Such methods have
been shown to have strong power for detecting recent population size changes as
well as for inferring the strength and abundance of natural selection. Unfortunately, there are many
confounding factors that need to be addressed before a genome-wide frequency
distribution can be used effectively.
I will focus on the effects of two confounding factors: misidentifying
the ancestral state of a mutation when using outgroup information, and the
effect that deleterious mutations have on linked neutral sites. I will show that both of these factors
can contribute to biased estimates of demographic and selective effects if not
handled appropriately.
References
Hernandez
RD, Williamson SH, Bustamante CD.
Context dependence, ancestral misidentification, and spurious signatures
of natural selection. Mol Biol Evol. 2007 Aug;24(8):1792-800
http://mbe.oxfordjournals.org/cgi/content/full/24/8/1792
Hernandez
RD, Williamson SH, Zhu L, Bustamante CD.
Context-dependent mutation rates may cause spurious signatures of a
fixation bias favoring higher GC-content in humans. Mol Biol Evol. 2007 Oct;24(10):2196-202.
http://mbe.oxfordjournals.org/cgi/content/full/24/10/2196
Hernandez
RD, Hubisz MJ, Wheeler DA, Smith DG, Ferguson B, Rogers J, Nazareth L, Indap A,
Bourquin T, McPherson J, Muzny D, Gibbs R, Nielsen R, Bustamante CD. Demographic histories and patterns of
linkage disequilibrium in Chinese and Indian rhesus macaques. Science. 2007 Apr 13;316(5822):240-3.
http://www.sciencemag.org/cgi/content/full/316/5822/240
Department
of Statistics, University of Washington
Bayesian
Coalescent-based Inference of Population Dynamics
Abstract. Kingman's
coalescent process opens the door for estimation of population genetics model parameters
from molecular sequences. One paramount parameter of interest is the effective
population size. Temporal variation of this quantity characterizes the
demographic history of a population. Since canonical deterministic models
describing effective population size dynamics rarely fit observed data, non-parametric curve fitting
methods based on multiple change- point (MCP) models have been developed. We
propose an alternative to
change-point modeling that exploits Gaussian Markov random fields (GMRFs)
to achieve temporal smoothing of the effective population size in a Bayesian
framework. The main advantage of our approach is that, in contrast to MCP
models, the GMRF temporal smoothing does not require strong prior decisions.
Using a simulation study, I will
demonstrate that the proposed temporal smoothing method, named Bayesian skyride, successfully recovers
``true'' population size trajectories in all simulation scenarios with a
consistent gain in accuracy over MCP approaches. Next, I will discuss several applications of the Bayesian skyride to
reconstructing evolutionary dynamics of viral populations. I will finish with
our ongoing work of applying the Bayesian skyride to multiple loci
simultaneously, extending our
framework to hierarchical modeling, and including covariate information into estimation of population
dynamics.
This is joint work with Erik Bloomquist and Marc Suchard.
References
Minin VN,
Bloomquist EW, Suchard MA. Smooth skyride through a rough skyline: Bayesian
coalescent-based inference of population dynamics, Molecular Biology and
Evolution, 25: 1459-1471, 2008.
Drummond
A, Rambaut A, Shapiro B, Pybus O. Bayesian coalescent inference of past
population dynamics from molecular sequences. Molecular Biology and
Evolution, 22, 1185-1192, 2005.
Strimmer
K, Pybus O. Exploring the demographic history of DNA sequences using the
generalized skyline plot. Molecular Biology and Evolution, 18,
2298-2305, 2001.
Pybus,
Rambaut A, Harvery P. An integrated framework for the inference of viral
population history from reconstructed
genealogies. Genetics, 155, 1429-1437, 2000.
School
of Medicine, University of California, San Diego
Evolutionary
Fingerprinting of Genes
Abstract. Over
time, natural selection molds every gene into a unique mosaic of sites evolving
rapidly and resisting change--an 'evolutionary fingerprint' of the gene. We
introduce a metric, called the evolutionary selection distance (ESD), to
identify similarities and idiosyncrasies in selection pressures inferred from
sequence alignments, including a direct comparison of heterologous genes. Using
a broad survey of viral genes, we apply a variety of computational techniques
and machine learning techniques based on ESD to classify genes by the
similarity of their evolutionary fingerprints, identify genes with distinctive
evolutionary features, and correlate evolution with phylogenetic, functional,
and taxonomic information. We demonstrate that the data follow a pattern of
evolutionary continuum rather than a few rigid evolutionary modes; genes within
the same functional group tend to exhibit similar evolutionary patterns, both
within a single viral genome and between different viruses; similarity in
selection pressures mirrors phylogenetic relationships among hepatitis C virus
subtypes, but not HIV-1 subtypes; and that evolutionary patterns in the
hemagglutinin gene of the Influenza A virus are largely determined by the host
with a few notable exceptions. By comparing genes at the level of the
evolutionary processes rather than the pattern of sequence variation, we can
compare both closely and distantly related genes, potentially revealing the
guiding principles underlying the evolution of genetic diversity.
References
Estimating
selection pressures on alignments of coding sequences, Chapter 1
http://www.hyphy.org/pubs/hyphybook2007.pdf
School of Life Science, Arizona State University
Population
Genetic Modeling with Absolute Fitness
Abstract Mathematical theory in population genetics is advancing to incorporate demographic or ecological dynamics in the model. Addressing complex demography is important for theory that aims to provide the accurate inference of evolutionary history of natural selection from DNA sequence data. It is also an important problem in studying infectious diseases. It is desired that epidemiological modeling incorporate both ecological factors (e.g. population dynamics) and population genetic factors (e.g. mutations and selection). However, the traditional framework of population genetics makes it difficult to integrate it into ecological modeling. Here I propose a simple solution to unite population dynamics and allele frequency dynamics using the modeling based on absolute, rather than relative, fitness. I will present how this modeling can be applied to the theory of adaptive niche expansion and the evolution of drug resistance.
References
Yuseob Kim and Wolfgang Stephan, Detecting a Local Signature of Genetic Hitchhiking
Along a Recombining Chromosome Genetics 160:
765–777, 2002.
Hideki Innan and Yuseob Kim, Detecting Local Adaptation Using the Joint Sampling of
Polymorphism Data in the Parental and Derived Populations, Genetics 179: 1713–1720, 2008.
Department of
Mathematics, University of Arizona
Quantitative
Prediction of Molecular Clock Acceleration at Short Time Scales
Abstract. Recent empirical studies of taxa
including humans, fish, and birds have shown elevated rates of molecular evolution
between species that diverged recently. Using the Moran model, we calculate
expected divergence as a function of time, and show that the observed
phenomenon of elevated rates at short time scales is completely consistent with
standard population genetics theory. The apparent acceleration of the molecular
clock at short time scales is due to segregating polymorphisms present at the
time of the ancestral population, both neutral and slightly deleterious, and
not nearly neutral mutations as has been previously hypothesized. We also
demonstrate that the duration of the rate elevation depends on the effective
population size, providing a method to correct time estimates of recent
divergence events. Our model concords with estimates of divergence obtained
from African cichlid fish, and fitting the model to this data allows us to
estimate the effective population size as Ne = 150,000 –
500,000. We also calculate that Ka /Ks is elevated considerably in the short
term before decaying slowly to its long term value. However, this elevation is
not as severe as had been previously predicted.
References
Simon Y. W. Ho, Matthew J. Phillips*, Alan Cooper and
Alexei J. Drummond, Time Dependency of Molecular Rate Estimates and Systematic
Overestimation of Recent Divergence Times, Molecular Biology and Evolution 22: 1561-1568
http://mbe.oxfordjournals.org/cgi/content/abstract/22/7/1561
Martin J. Genner, Ole Seehausen, David H. Lunt, Domino A.
Joyce, Paul W. Shaw, Gary R. Carvalho, and George F. Turner, Age of Cichlids:
New Dates for Ancient Lake Fish Radiations, Molecular Biology and Evolution 24:1269-1282.
http://mbe.oxfordjournals.org/cgi/content/abstract/24/5/1269
Department of
Statistics, University of California
The
Beta Coalescent, Taking into Account Large Family Size
Abstract. Currently
Kingman's coalescent is the basis for performing common statistical tests(e.g.
Tajima(1989)), but it assumes a finite variance for offspring distributions.
However, there appears to be evidence that in some species, such as marine
animals, an individual can produce a very large number of offspring (Hedgecock
(1994)).
This can
be taken into account by using a Beta coalescent(see Mohle(1999),
Sagitov(1999), Pitman(1999)). Here we explore the Beta coalescent which seems
to be a better choice of model than Kingman's coalescent when the family sizes
are large. We take advantage of previous theoretical results from Berestycki,
Berestycki and Schweinberg (2007) to estimate the large family size parameter
of the Beta coalescent model.
This is joint work with Rick
Durrett and Carlos Bustamante.
References
Probability Models for DNA Sequence
Evolution (2nd Edition) Rick Durrett.
Chapter 4 (Section 4.1)
Santa Fe
Institute
Bet-hedging
under Genomic Imprinting: Causes and Consequences of Genetic Conflict over
Risk-tolerance
Abstract. Population-genetic
models that incorporate either environmental fluctuations or stochastic
variation in individual reproductive success demonstrate the importance of
variance reduction, or "bet-hedging." Simply, natural selection favors not only genotypes that increase
mean reproductive success, but also those that reduce the variance in
reproductive success. I will
present theoretical work that extends these bet-hedging results to alleles at
an imprinted locus, where alleles inherit parent-of-origin specific epigenetic
modifications, and therefore take on two distinct expression strategies
depending on whether they are maternally or paternally derived. when males have
a higher variance of reproductive success than females (as is the case for most
mammals), natural selection more strongly favors variance reduction for
paternally than maternally derived alleles. The resulting genetic conflict potentially explains the
behavioral phenotypes associated with imprinted gene expression in the
mammalian brain. Furthermore, the
intragenomic "arms-race" associated with these imprinted gene effects
may explain systematic behavioral biases in humans and other mammals that are
appear maladaptive, and that violate economic notions of
"rationality."
á
Heather Norton/Fernando Mendez
Arizona Research Labs and Department
of Ecology and Evolutionary Biology, University of Arizona
Identifying
the Timing and Strength of Selection to Test Specific Hypotheses in Human Evolution
Abstract. Currently great effort is put forth to identify
targets of natural selection in the human genome. Often large-scale genomic scans
identify long lists of genes that have been potentially shaped by natural
selection during the course of human evolution. While these lists provide a Òbig pictureÓ approach to the
role of selection in shaping human variation, anthropologists may often be
interested in a more detailed approach that focuses on the timing and strength
of natural selection acting on a single gene or group of genes. The goal of such investigations is to
test hypotheses about how and when natural selection has shaped variation in a
particular phenotypic trait. Here
we use empirical sequence data from the gene SLC24A5 and extensive simulations to
determine the timing and strength of selection associated with a gene that has
a major effect on skin pigmentation phenotype. Such data is relevant to hypotheses about the timing of the
evolution of lighter skin color in Europe. This work can be used as a model for testing hypotheses
about the role and timing of natural selection in adaptation to changing
dietary and environmental conditions associated with the expansion of modern
humans around the globe.
|
|
|
|
|
|