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For our Monday reading group we chose to read a series of classic papers in Evolutionary Biology. Each week the discussion leaders chose their paper/book excerpt and often chose to add a companion paper. Below is a complete list of the papers read. Thanks to all of the discussion leaders and everyone who attended. Thanks also to Leslie Turner and others for the conversation that sparked the idea for revisiting the classics (see here for more of the twitter discussion, and this Mendeley group by Leslie).
1. Kreitman’83 Nucleotide polymorphism at the alcohol dehydrogenase locus of Drosophila melanogaster. see also this post by Casey Bergman on 30th anniversary of paper. Alisa Sedghifar.
2. Price 1970 Selection and Covariance & Queller 1992 Quantitative Genetics, Inclusive Fitness, and Group Selection. Jeremy Berg.
3. Mayr ’47 Ecological factors in speciation . Moria Robinson & Meredith Cenzer
4. Kettlewell 1955 SELECTION EXPERIMENTS ON INDUSTRIAL
MELANISM IN THE LEPIDOPTERA accompanied by Majerus 2009 Industrial Melanism in the Peppered Moth, Biston betularia: An Excellent Teaching Example of Darwinian Evolution in Action . Reid Brennan & Ryan Baldini
5. excerpts from Waddington’s “The strategy of the genes” 1957 on the epigenetic landscape & genetic assimilation Judy Wexler & David Luecke
6. Excerpt of Clausen, Keck, & Hiesey 1940 Experimental studies on the nature of species. I. Effects of varied environments on western North American plants. & their “Concept of Species Based on Experiment” 1939. Michelle Stitzer & Mark Taylor.
7. On the origins of reinforcement,Dobzhansky 1940 Speciation as a Stage in Evolutionary Divergence paired with Noor’s Reinforcement and other consequences of sympatry. 1999 Kristin Lee, Micah Freedman, & Philipp Brand.
8. Felsenstein 1985 Phylogenies and the Comparative Method paired with Pennell’s Models and meanings in comparative biology book review. Jiansi Gao & Chenling Antelope
9. Charlesworth, Lande, & Slatkin 1982 A Neo-Darwinian Commentary on Macroevolution. Vince buffalo & Serena Caplins.
10. Dobzhansky ’47 Adaptive Changes Induced by Natural Selection in Wild Populations of Drosophila paired with Grant & Grant 2002 Unpredictable Evolution in a 30-Year Study of Darwin’s Finches. Chris Griesemer,Gideon Bradburd and Jaime Ashander.
Dear population genomicists of the Bay Area,
The tenth Bay Area Population genomics meeting was great, thanks to CEHG Stanford for hosting it. We will be hosting BAPG XI at UC Davis (Storer Hall) on December 6, 2014, and we hope to see you all there!
9.30am-10am Breakfast (Storer Hall)
10am-11am Session 1
10.00am Gideon Bradburd (UC Davis)
The Geography of Genetic Admixture
10.20am Rajiv McCoy (Stanford)
Causes and consequences of aneuploidy in human embryos
10.40am Laurie Stevison (UCSF)
Time-scale of recombination rate evolution in great apes
11.30am-12.30pm Session 2
11.30am Kelley Harris (UC Berkeley)
Recent evolution of the mutation rate and spectrum in Europeans
11.50am Tim Beissinger (UC Davis)
Patterns of demography and selection since maize domestication
12.10pm Yoosook Lee (UC Davis)
Genome evolution of malaria vectors in response to the increased usage of insecticide-treated bed nets
12.30-1.30 pm Lunch
1.30pm Session 3
1.30pm Daniel Weissman (UC Berkeley)
Minimal-assumption inference from genomic data
1.50pm Sandeep Venkataram (Stanford)
The adaptive mutation spectrum from yeast experimental evolution
2.10pm Chris Ellison (UC Berkeley)
Transposable elements have rewired and fine-tuned the dosage compensation gene regulatory network in Drosophila miranda
2.30pm Andres Moreno (Stanford)
Native American genomics and beyond
Registration is free but required, so we can make sure we order enough food and get a big enough room. Registration is now closed (as of November 22nd). Registration list here: google doc.
The Coop Lab: Simon Aeschbacher, Chenling Antelope, Jeremy Berg, Gideon Bradburd, Vince Buffalo, Graham Coop, Ivan Juric, Kristin Lee, Alisa Sedghifar
P.S. the twitter hashtag will be #BAPGXI.
For those bringing posters, there will be wallspace provided on the first two floors of Storer Hall, as well as bluetack and tape for hanging your posters. Posters should be no wider than 48″ (~1.2m), and those bringing posters should try to have their posters set up by 10am (so they can be viewed from the first coffee break). Please contact Gideon Bradburd (firstname.lastname@example.org) with all poster-related questions.
DRIVING From Bay area
Take the I-80 East, merge onto the 113N (to Woodland) at exit 70 (one after Kidwell rd exit)
Take exit 27 to UC Davis, turn right onto Hutchison Rd. Turn left onto Kleiber Hall drive. As you approach the gate, Storer Hall will be to your right.
Parking will be free in the lot to your left (parking structure P27, visible on the campus map after checking the box “Permit Parking”)
Storer hall on a campus map:
AMTRAK to Davis (Bikes are permitted.)
Morning: Eastward bound Weekend schedule, the best train is #720:
8.04am Berkeley (University and 4th st)
8.12am Richmond (next to BART)
arrives in Davis at 9.22am
Storer Hall is just a ~15 min walk from the train station: down 2nd and straight on through campus, by the Quad, then just across California Ave, behind Hutchinson.
Return: 3.50pm or 4.55 train from Davis,
Our paper on a general method to detect divergent selection among populations on quantitative traits was published today in PLOS Genetics (Berg and Coop 2014, code, the paper was previously up on the bioRxiv and Haldane’s sieve). Our method uses the knowledge gained about the genetic basis of a trait from GWAS, which allows us to compare allele frequency patterns across many loci to determine whether there is evidence for that they are all responding in concert to some selective pressure.
The method is, in large part, an attempt to set up the correct null model for the distribution of among population variation, and to circumvent the problem of environmental confounding in trying to determine whether certain differences between human populations may have been caused by selection.
The central idea underlying our tests, as well as many quantitative genetics approaches that have been developed over the last 2 decades (see paper for references), is that we can use genetic marker data to get a good measurement of how much allele frequencies vary among populations. Then, if the environment can be held constant across populations, we ought to be able to use the allele frequency information to predict how large a range of phenotypic differences among populations we would expect under a neutral model of genetic drift. Once we have this prediction in hand, a neutrality test for that phenotype follows.
The difficulty in approaching this question for human populations is that we of course cannot hold the environment constant across human populations, and so we can’t tell from direct phenotypic measurements whether any unusually large differences among populations that are observed are due to a history of natural selection, genetic drift, or entirely due to environmental differences among populations.
To get around this problem, we rely on the GWAS data, which comes in the form of a list of a specific set of SNPs associated with a phenotype, as well an estimate of the additive effect size for each associated variant. Importantly, these alleles were identified as associated with the phenotype in a specific population. We use the estimated effect sizes, in combination with allele frequencies at these loci, to predict the mean value of the trait we would expect to observe in each population, under a model in which all effects are additive and the environment constant. We can then test whether these genetic values differ among populations more than we would expect under a model of genetic drift.
We think that this test is potentially a good way to look for divergent selection pressures acting on traits. We expect that over the coming decade approaches such as ours, and more sophisticated developments, will be applied to many different traits. This offers a fascinating chance to study the role of natural selection in shaping phenotypic diversity among populations, in a range of species including humans.
However, beyond saying that selection, and not merely genetic drift, have acted on the loci involved in the trait, the interpretation of a positive results is challenging. We spend some time in the paper discussing these difficulties. Many of these are not new problems and some of these issues relate more generally to why it is difficult to study adaptation in natural populations. That said, it seems worth reiterating these issues and caveats carefully, as it is easy, and potentially fraught, to over interpret differences among human populations.
To do so, we use our signal of selection involving human height as an example. One of our clearest signals of selection is on height GWAS loci between Northern and Southern Europeans, as previously reported by Turchin et al. Nature Genetics. Turchin et al. and our research shows that alleles involved in height, at least those identified to date, show greater, directional differences between northern and southern European populations than would be expected under a model of genetic drift alone.
The first thing to say is that this signal is really quite subtle, and even where selection has acted, drift and gene flow still undoubtedly contribute to the differences we observe. Moreover, most of these variants are polymorphic in most of these populations, so they say little about an individual, i.e., most the variance is still among individuals within populations rather than among populations.
Nonetheless, average observed height clearly differs among European populations in the direction suggested by Turchin et al. and our results based on genetic data. Therefore, it is plausible that the observed differences in height between European populations are partially genetic in nature and have been subject to selection. We do not know this for certain, however, because of the large environmental contribution, e.g., diet, to traits such as height (as well as most human traits). Certainly the large changes in height over the past centuries in response to changes in nutrition and health highlight the huge role of the environment in height (see graph below). It remains possible that the majority of the observed mean difference among populations is environmental. While the relative order of populations has remained relatively constant, some have changed their ordering substantially, suggesting that we have to be very cautious about interpreting between population differences.
Furthermore, only a small fraction of the variance in height within Europeans populations has been mapped to date (even less of the variance has been explained for many other traits). It is possible that as yet unmapped loci could change our understanding of the genetics of height in Europe. We could, for example find alleles that increase height which are common only in Southern Europe. While this is probably unlikely for height, it is exactly the case for skin pigmentation, where the partially convergent evolution of light skin pigmentation leads to confusing signals of adaptation that would be easy to misinterpret if we did not have a relatively good understanding of the genetics of skin pigmentation (see paper for details).
Also confusing the interpretation of the results is the potential for genotype by environment (GxE) or genotype by genotype interactions. Alleles may have different or even opposite effects in different environments and genetic backgrounds. While this cannot generate a false signal of selection, it does mean that the genetic values calculated for populations should not be treated as reliable phenotypic predictions. For height, it appears that many loci do seem to act in a reasonably additive manner and have consistent effects across populations. However, even given this trait, we have to be careful as we do not know if this holds for the subset of height GWAS loci that are driving our signal. Moreover, it is likely that traits other than height may have substantial GxE and so caution is warranted.
Thus, there is still a huge amount we do not understand about how selection and drift have shaped height, or any phenotype, within Europe. We also do not know that the differences in allele frequencies at variants associated with height reflect direct selection on height, or whether our observations are due to selection on some other phenotype (that may not even be on our radar in current environmental conditions, or may not differ among populations today). Even if selection acted directly on height, we would not know what the specific selection pressure that drove this difference. We also do not know the timing of this selection: whether it represents a long-term trend or is just a snapshot of some fluctuation, or whether selection took place in Europe or is the result of differential gene flow from populations who themselves diverged adaptively in height. While we expect that results from other fields, physical anthropology in particular, will be helpful, integrating these results to paint a more complete portrait of the evolution of human height will likely be challenging.
All of these caveats and concerns may seem overly cautious when expressed about studying the genetics of height differences among human populations. It seems quite likely that observed height differences among populations will be partially genetic in nature, and due in part to differential selection, consist with our and Turchin et al’s results. However, to establish this as a scientific finding, rather than a plausible hunch requires much more work. It is really quite humbling that we are only just beginning to understand the long-term role of selection and drift in shaping a phenotype as well studied as height. Undoubtedly, we will learn a lot over the coming decade about how drift, selection, and migration have shaped the genetic basis of phenotypes across populations, but these insights will only come about by the careful study of these phenotypes and the separation of genetic and environmental components.
While much of this probably seems obvious to most human geneticists, it is clear that there is huge public interest in genetic studies of human evolution and phenotypic differences and an almost equal potential for misunderstanding such studies. A sad case in point is the recent book by Nicholas Wade, which many reviews and blogs have already rightly criticized extensively. We hope that this blog post will help to layout some of the caveats that come with studying adaptation of complex traits even when good methods and GWAS are available.
Jeremy Berg and Graham Coop
Our talks from Evolution are below. Much of the work is unpublished and provisional, so please contact us for updates/details if you are interested in the work.
Alisa’s talk on a Model of Genome-Wide Patterns of Ancestry in a Secondary Contact Zone
Graham’s Evolution talk on adaptation to patchy environments (also given in slightly modified form at SMBE)
the first half is joint work with Peter Ralph, the second is a collaboration with Chenling, Kevin Wright, and John Willis.
Gideon’s poster on a novel method for visualizing spatial structure and admixture (given at SMBE, and as guerrilla poster at Evolution by graham):
Jeremy’s talk on testing for adaptive phenotypic divergence
Yaniv’s talk on why sperm might evolve to help keep female meiosis fair:
We’re looking forward to seeing old friends and meeting new folks at Evolution 2014. Here’s a list of the talks by the Coop lab at the conference.
Jeremy Berg. General extensions of Qst/Fst for detecting adaptation in quantitative traits.
2A_306A Methods for Migration. Sunday, 9:00 AM – 9:15 AM Room: 306 A
Graham Coop. Parallel evolution during local adaptation. ASN Vice Presidential Symposium:Modern approaches to local adaptation. Date: Monday, 3:15 PM – 3:45 PM. Room 402
Alisa Sedghifar. A Model of Genome-Wide Patterns of Ancestry in a Secondary Contact Zone 3C_303 Hybridization. Monday, 2:00 PM – 2:15 PM Room 303
Yaniv Brandvain. Sperm do not evolve to collaborate in female meiotic drive. 4C_306A Sex and Evolution Tuesday, 2:30 PM – 2:45 PM Room: 306 A
Simon Aeschbacher. Exploring genome-wide signals of selection against gene flow 4D_301A Genome Evolution. Tuesday, 3:15 PM – 4:30 PM. Room: 301 A
The theme for the coop lab T-shirt this year is POPGEN IN SPACE!!! A bunch of the research interests in the lab currently focus on spatial population genetics, so it seemed like a great opportunity to bust out a homage to “pigs in space” featuring Fisher, Haldane, and Wright. Images below, we’ll post some pics of the lab in the t-shirts later.
John Novembre and I held a symposium by this name at SMBE a few years ago, we had this idea for the T-shirt then but never quite got around to it.