What we’re reading: Genetics of ecological speciation and translating plant genetics to the farm


In the journals

Arnegard M.E., M.D. McGee, B. Matthews, K.B. Marchinko, G.L. Conte, S. Kabir, N. Bedford, S. Bergek, Y.F. Chan, F.C. Jones, D.M. Kingsley, C.L. Peichel, D. Schluter. 2014. Genetics of ecological divergence during speciation. Nature doi: 10.1038/nature13301.

Here we investigate the genetic architecture of niche differentiation in a sympatric species pair of threespine stickleback fish by mapping the environment-dependent effects of phenotypic traits on hybrid feeding and performance under semi-natural conditions.

Ronald P.C. 2014. Lab to farm: Applying research on plant genetics and genomics to crop improvement. PLoS Biology 12(6): e1001878. doi: 10.1371/journal.pbio.1001878.

In this Essay, I describe how basic research advances have been translated into crop improvement, explore some lessons learned, and discuss the potential for current and future contribution of plant genetic improvement technologies to continue to enhance food security and agricultural sustainability.

In the news

“Everyone is, to some degree, winging it. Your career decisions may be as much serendipity as serious long term planning.”

“In our study, a low-frequency variant in HNF1A — present in 2 percent of type 2 diabetes cases and 0.4 percent of healthy controls — quintupled risk of type 2 diabetes, the largest effect ever observed for a type 2 diabetes variant found in more than 0.1 percent of the population.”

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What we’re reading: Population genetics of an invasive vine, demography and GWAS,


In the journals

Campitelli, B. E., and J. R. Stinchcombe. 2014. Population dynamics and evolutionary history of the weedy vine Ipomoea hederacea in North America. G3: Genes, Genomes, Genetics, doi: 10.1534/g3.114.011700.

We further found significant genetic differentiation at sequenced loci, but nearly 4-fold stronger differentiation at the leaf shape locus, strengthening evidence that the leaf shape locus is under divergent selection.

Lohmueller, K. E. 2014. The impact of population demography and selection on the genetic architecture of complex traits. PLOS Genetics. 10:e1004379. doi: 10.1371/journal.pgen.1004379.

Under a model where a mutation’s effect on a trait is correlated with its effect on fitness, rare variants explain a greater portion of the additive genetic variance of the trait in a population that has recently expanded than in a population that did not recently expand.

In the news

“I would argue then that the need to strive for top-tier non-OA journals is greatest for research-active faculty at institutions that are actually most harmed by predatory scientific publishing structures (see the list above).”

How to write the introduction to an ecology (or any scientific) paper: a flowchart.

“Two months after the implementation of the PLOS journals’ data policy, what have we learned from our authors, reviewers, editors, correspondents, and commenters in the blogosphere?”

Stop wasting your time writing faculty job application packages and just plug your publication stats into this regression-based widget to calculate the odds you’ll become a PI. (But see also.)

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What we’re reading: The evolution of brains versus brawn, ring species genomics, and the deadly fifth stage of publishing

Reading in the tree

In the journals

Bozek K, Wei Y, Yan Z, Liu X, Xiong J, et al. 2014. Exceptional evolutionary divergence of human muscle and brain metabolomes parallels human cognitive and physical uniqueness. PLoS Biology 12(5): e1001871. doi: 10.1371/journal.pbio.1001871.

We found that the evolution of the metabolome largely reflects genetic divergence between species and is not greatly affected by environmental factors. In the human lineage, however, we observed an exceptional acceleration of metabolome evolution in the prefrontal cortical region of the brain and in skeletal muscle.

Alcaide M, Scordato ESC, Price TD, Irwin DE. 2014. Genomic divergence in a ring species complex. Nature 10.1038/nature13285.

These results cast doubt on the hypothesis that the greenish warbler should be viewed as a rare example of speciation by distance, but demonstrate that the greenish warbler displays a continuum from slightly divergent neighbouring populations to almost fully reproductively isolated species.

In the news

“For a career in science you need to combine curiosity and creativity with hard work and stamina, as well salesmanship and confidence …”

“Being quite selective has worked out very well for me so far. I’ve been fortunate enough to attract several really great graduate students. But lately I’m wondering if I need to be less selective.”

“Now, even when I have other newish finds that I’ve yet to present, I submit [conference] abstracts for projects that still lack a rudimentary answer.”

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How A Troublesome Inheritance gets human genetics wrong

World Map - Abstract Acrylic

Image by Lara Mukahirn.

Probably since before the origin of modern Homo sapiens, we have known that people from other places—the next village over, the other side of the mountains, or some distant and unexplored land—were different from us. Some of those differences were obviously innate, and genetically transmissible from parent to offspring. Some of those differences were simply a question of culture. In the course of exploring our world and the people we found in other places, we’ve developed intuitions about which differences are genetic, and which are cultural—but the line between the two has never been universally agreed-upon.

In his new book A Troublesome Inheritance, Nicholas Wade argues that many of the differences between people from different places that we typically attribute to culture are, in fact, due to genetics. These include major social and economic disparities—whether nations are democratic or autocratic, warlike or peaceable, prosperous or poor. Wade argues that these differences arise from different evolutionary histories experienced by people of different races, and backs his claims with extensive citation of modern genetic data.

Many readers are likely to find Wade’s arguments convincing, and many reviewers already have. However, reading A Troublesome Inheritance as a population geneticist, I repeatedly found that Wade misunderstands or misrepresents the original scientific work that he cites.

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Posted in book review, genomics, population genetics | Tagged , , | 12 Comments

Mol Ecol’s best reviewers 2014

As a continuation of our post from last year, Molecular Ecology is publishing a list of our very best referees from the last two years (2012 and 2013). Our hope is that the people listed below will put ‘Top Reviewer for Molecular Ecology 2014′ on their resume, and that this will highlight to search committees and granting agencies that they have made a significant contribution to the community as a reviewer.

Everyone who completed a review for Molecular Ecology between 1st January 2012 and 31st December 2013 was eligible, and people were ranked by an index that included the number of reviews completed, the proportion of accepted review requests that led to a review being returned (excluding unassignments before the two week deadline), and the average time taken per review if this was over two weeks. The top 300 (~ 8%) are listed below the fold – thank you so much for your efforts!

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What we’re reading: The vital importance of mosquitoes’ gut microbes, an app for classroom genetics, and how to fish for p-values without really trying

Reading Place

In the journals

Coon, K. L., K. J. Vogel, M. R. Brown, and M. R. Strand. 2014. Mosquitoes rely on their gut microbiota for development. Molecular Ecology. 2727–2739. doi: 10.1111/mec.12771.

Functional assays showed that axenic larvae of each species failed to develop beyond the first instar. Experiments with Ae. aegypti indi- cated several members of the microbial community and Escherichia coli successfully colonized axenic larvae and rescued development.

Myers, R. B., B. Millman, and M. A. F. Noor. 2014. Genetics and evolution: An iOS application to supplement introductory courses in transmission and evolutionary genetics. G3: Genes, Genomes, Genetics. 4:779–781. doi: 10.1534/g3.114.010215.

The app provides demonstrations of Mendelian inheritance and population genetics, it assists with calculations common in genetics classes associated with these principles (e.g., recombination fraction), and it generates unique practice problems with which students can practice or professors can design assessments.

In the news

“It seems that negative events are necessary and we use them to avoid making the same mistakes again. It doesn’t need to be dramatic, it can be something as apparently positive as constructively worded critical feedback.”

“Wade wants us to cut up human diversity into five races not because that’s what the statistical analyses show, but because thinking about it as a gradient is hard.”

“Our key point here is that it is possible to have multiple potential comparisons, in the sense of a data analysis whose details are highly contingent on data, without the researcher performing any conscious procedure of fishing or examining multiple p-values.”

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Calculating genetic differentiation with R



As molecular ecologists, it is often necessary and useful to calculate some measure of genetic differentiation. This is often accomplished with metrics such as Wright’s Fst an or an unbiased analog (e.g., Weir & Cockerham’s Fst; G’st etc.). In addition to calculating global estimates, we often want to calculate estimates of genetic differentiation between pairs of populations. Furthermore, we often need to calculate similar measures of genetic differentiation despite having different marker types, different levels of polymorphism, different amounts of missing data, different sampling schemes, and vastly different questions. Despite all of these differences, we know that there are many useful metrics for measuring genetic differentiation and we also probably don’t want to write the code for each estimator from the ground up. Many of the estimators for genetic differentiation have been implemented in packages available for R. Each package typically has its own syntax and can take some time to fully work through (particularly without examples).

Thus, we thought it would be useful for the molecular ecology community to share in a communal GitHub repository focused on calculating genetic differentiation in R. Other languages will, of course, be accepted too but it seems like R has the greatest diversity of metrics. Over time, this will hopefully become a valuable resource. As an example, I have posted an R script that calculates ubiased global Fst using the package Hierfstat. The repository is available at The Molecular Ecologist organization on GitHub under the repository ‘Genetic Differentiation’. When testing your code, it would be best to try it out on two standardized input files (one for SNPs and one for microsatellites). The example data sets currently contain individuals from 4 populations at 100 SNPs and 30 microsatellites (they are simulated data). It would be useful to have a submissions of scripts that are: 1.) short and simple, 2.) heavily commented (using ‘#’ in R), and 3.) produce useful output for both of the example data sets.

Because this is a work in progress, please feel free to suggest or submit other ‘standard’ example data sets and other ideas (e.g., currently the test data sets do not have missing data). Please comment below (I can easily update this text) and also please send me your code snippets to my email (and I will curate, test, and upload them) or you should be able to add scripts directly to the repository.

Below is a log of all the current entries:

Global FST: Hierfstat

Posted in population genetics, R, software | 12 Comments

What we’re reading: Dealing with missing sequence data, SNP2GO, and the challenge of replication in bad results


In the journals

Ferretti, L., E. Raineri, and S. Ramos-Onsins. 2012. Neutrality tests for sequences with missing data. Genetics 191:1397–401. doi: 10.1534/genetics.112.139949.

At present, most packages for population genetics analyses like DNAsp (Librado and Rozas 2009) deal with missing data simply by removing individuals and/or positions affected with incomplete data. This is a good strategy as long as missing data represent a very minor fraction of the alleles, since in this case they do not affect the power of the analysis. However, there could be situations in which a large amount of missing data are unavoidable.

Szkiba, D., M. Kapun, A. von Haeseler, and M. Gallach. 2014. SNP2GO: Functional analysis of genome-wide association studies. Genetics 197:285–289. doi: 10.1534/genetics.113.160341.

If candidate genes are significantly overrepresented, then one typically concludes that the GO term also contains an overrepresentation of candidate SNPs. While this may be true in many instances, it is certainly not always the case.

In the news

“Git can be an invaluable tool for researchers. It does, however, have a bit of a high activation energy.”

“What’s more important, you might ask, a nice doctor or a good one? A nice professor, or one who knows what she’s talking about? Well of course the answer is, why can’t she be both?”

“… the presence of male experimenters caused mice to display 35 percent less pain than when filmed remotely or in the presence of a female experimenter.”

“The level of criticism it would take to prove a wrong study wrong is higher than that almost any existing study can withstand. That is not encouraging for existing studies.”

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Selection keeps an extra-close eye on multi-functional genes

Victorinox Swiss Army Knife

More functions, more selective constraint? Photo by James Case.

Genes that have roles in multiple traits—pleiotropic genes—have long been thought to be under stronger selection as a result of those multiple functions. The basic logic is that, when a gene produces a protein that has a lot of different functional roles, there are more functions that will be disrupted by changes to that protein. Which would be more inconvenient: if your smartphone suddenly needed a new type of power connector, or if every electrical outlet in your house suddenly accepted only plugs with four prongs?

As much sense as that makes, we don’t have a lot of direct evidence that pleiotropic genes experience stronger selection. A paper just released online ahead of print at Genetics provides just that, using the suite of genetic resources available for the subject of some of the original experiments in evolutionary genetics, Drosophila.

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Posted in adaptation, genomics, quantitative genetics | Tagged , | 1 Comment

What we’re reading: The Y chromosome, climate change versus forests, and a postdoc’s job description

Caught Reading

In the journals

Cortez, D., R. Marin, D. Toledo-Flores, L. Froidevaux, A. Liechti, P. D. Waters, F. Grützner, and H. Kaessmann. 2014. Origins and functional evolution of Y chromosomes across mammals. Nature 508:488–93. doi: 10.1038/nature13151.

Despite expression decreases in therians, Y/W genes show notable conservation of proto-sex chromosome expression patterns, although various Y genes evolved testis-specificities through differential regulatory decay. Thus, although some genes evolved novel functions through spatial/temporal expression shifts, most Y genes probably endured, at least initially, because of dosage constraints.

Schueler, S., W. Falk, J. Koskela, F. Lefèvre, M. Bozzano, J. Hubert, H. Kraigher, R. Longauer, and D. C. Olrik. 2014. Vulnerability of dynamic genetic conservation units of forest trees in Europe to climate change. Global Change Biology 20:1498–511. doi: 10.1111/gcb.12476.

Compared to the overall climate niche of the analysed target species populations at the warm and dry end of the species niche are underrepresented in the network. However, by 2100, target species in 33–65 %of conservation units, mostly located in southern Europe, will be at the limit or outside the species’ current climatic niche as demonstrated by favourabilities below required model sensitivities of 95%.

In the news

“… the take home message is that there is currently no definitive evidence one way or another about whether most results are false.”

“So in summary, my recommendations are: learn to turn your research outputs into papers, and learn how to produce research outputs in a short space of time; learn skills that are rare and in high demand; and learn how to take projects to completion.”

“As scientists, we like to think that we are measuring things accurately, and tend to be disturbed at the idea that we might be systematically biased in our measurements. So, the idea that we might systematically be underestimating the abilities of a large portion of our students is something most of us would find disturbing.”

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