Peer review, reviewed

Partners in crime

Revise and resubmit.

Rebecca Schuman, who has almost single-handedly turned Slate into one of best big websites for coverage of the many trials and tribulations of academia, turns to peer review for scholarly journals, in which an author’s academic peers volunteer to weigh in on whether a manuscript is worthy of publication. Schuman discusses the problems of of both how long the process takes—routinely more than a year, especially with the back-and-forth of revisions—and tone:

Think of your meanest high school mean girl at her most gleefully, underminingly vicious. Now give her a doctorate in your discipline, and a modicum of power over your future. That’s peer review.

And she suggests something that might sound familiar to those of us who hang out in the evolutionary ecology blog-o-verse: enforced reviewing reciprocity.

… what if in order to be eligible to submit an academic article to a journal, a scholar had first to volunteer to review someone else’s article for that same journal? … You want to publish and not perish? First you have to earn that right by making a punctual, non-petty investment into the publishing enterprise.

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What we’re reading: Sexual selection and fish placentas, SNPs versus observational pedigrees, and the stupidest statement ever on replication


In the journals

Pollux BJA, RW Meredith, MS Springer, DN Reznick. 2014. The evolution of the placenta drives a shift in sexual selection in livebearing fish. Nature. doi: 10.1038/nature13451.

We show that post-zygotic maternal provisioning by means of a placenta is associated with the absence of bright coloration, courtship behaviour and exaggerated ornamental display traits in males. Furthermore, we found that males of placental species have smaller bodies and longer genitalia, which facilitate sneak or coercive mating and, hence, circumvents female choice.

Bérénos C, PA Ellis, JG Pilkington, and JM Pemberton. 2014. Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches. Molecular Ecology, 23: 3434–3451. doi: 10.1111/mec.12827.

We found that the heritability captured by SNP markers asymptoted at about half the SNPs available, suggesting that denser marker panels are not necessarily required for precise and unbiased heritability estimates. Finally, we present guidelines for the use of genomic relatedness in future quantitative genetics studies in natural populations.

In the news

“Whether they mean to or not, authors and editors of failed replications are publicly impugning the scientific integrity of their colleagues.”

“Trying to prevent anyone from replicating your work, however, IS a knock on integrity. On the scientific integrity of that person who does not wish anyone to try to replicate his or her work, that is.”

“We are pleased to report that Molecular Ecology is now the first journal to surpass 1000 data packages in Dryad!”

“It’s okay to be competitive. It’s okay to strive to be the leader. But don’t define your success that way or you will undoubtedly spend more time chasing windmills than developing your career.”

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What we’re reading: Fish gut microbes, Denisovan origins of Tibetan altitude adaptation, and the curious costs of journal subscriptions

Konzentration auf Strand

In the journals

Bolnick, D. I., L. K. Snowberg, P. E. Hirsch, C. L. Lauber, R. Knight, J. G. Caporaso, and R. Svanbäck. 2014. Individuals’ diet diversity influences gut microbial diversity in two freshwater fish (threespine stickleback and Eurasian perch). Ecology Letters. 17:979–987. doi: 10.1111/ele.12301.

Unexpectedly, in most cases individuals with more generalised diets had less diverse microbiota than dietary specialists, in both natural and laboratory populations. This negative association between diet diversity and microbial diversity was small but significant, and most apparent after accounting for complex interactions between sex, size and diet.

Huerta-Sánchez, E., X. Jin, Z. Bianba, B. M. Peter, N. Vinckenbosch, Y. Liang, X. Yi, M. He, M. Somel, P. Ni, B. Wang, X. Ou, J. Luosang, Z. X. P. Cuo, K. Li, G. Gao, Y. Yin, W. Wang, X. Zhang, X. Xu, H. Yang, Y. Li, J. Wang, J. Wang, and R. Nielsen. 2014. Altitude adaptation in Tibetans caused by introgression of Denisovan-like DNA. Nature, doi: 10.1038/nature13408.

… the length of the haplotype, and the fact that it is not found in any other populations, makes it unlikely that the haplotype sharing between Tibetans and Denisovans was caused by incomplete ancestral lineage sorting rather thanintrogression.

In the news

“Typically ‘gene’ is misused most when followed by ‘for.’”

“Some universities are paying nearly twice what universities of seemingly similar size and research output pay for access to the very same journals.”

“[Wright] basically thought that a medium size population would have a balance of drift and selection that it would allow the population to drift away from an adaptive peak and randomly explore the adaptive landscape.”

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Bayesian Markov-chain Monte Carlo in population genetics


Bayes’s Theorem in neon. Photo by Matt Buck.

This is a guest post by Arun Sethuraman, a postdoctoral associate with Jody Hey, studying statistical models for divergence population genetics in the Department of Biology at Temple University. You can also find him on Twitter, and on his short story blog.

Prompted by the great response to my talk at Evolution 2014 on “Parallel MCMC and inference of ancient demography under the IM model”, I wanted to throw together a quick and dirty review of Bayesian MCMC, and why and how it works for the uninitiated, as well as highlight some of the important problems surrounding the method and its implementation.

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Posted in methods, population genetics, software | Tagged , | 1 Comment

#Evol2014 in tweets

I think it’s fair to say that I was a pioneer of Twitter at the Evolution meetings—back when I set up the website for Evolution 2009, I created an account for the conference, and signed up for one myself. I think maybe six unique people ever tweeted the #Evol2009 hashtag, and they mostly used it to exchange notes about where to find better coffee than what the University of Idaho catering service provided.

Five years later, at this year’s iteration of the meeting in Raleigh, North Carolina, Evolution was all over Twitter. Far from being worried about over-publicizing preliminary work, attendees broadcast everything from their talk slides to mockery of the tiny, absurd protest outside the convention center.

When I ran a search for the meeting hashtag, #Evol2014, on ScraperWiki, I ended up with a file containing almost 9,000 tweets (including retweets) from 20 to 24 June. Here’s what they looked like on an hourly basis:


I may play around with some additional analysis of this dataset, but I’m not sure when I’ll have time—so I thought I’d use it as an excuse to (finally) try out Figshare. If your interest is piqued, you can download the original data here, and see what you can do with it.

Yoder, JB. 2014. #Evol2014 in tweets. figshare. doi: 10.6084/m9.figshare.1083874

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#Evol2014: See you in Raleigh!

Morning light Raleigh, NCEvolution 2014, the joint annual meeting of the the American Society of Naturalists, the Society of Systematic Biologists, and the Society for the Study of Evolution, begins this Friday in Raleigh, North Carolina. Many of us are already en route to the biggest regular professional meeting for our field. As you’re building your itinerary, may we suggest some talks given by Molecular Ecologist contributors? You could catch all four, if you move quickly between rooms on Sunday morning.

And once you’ve got our presentations on your list, let us know when yours is in the comments!

  • Kimberly Gilbert and Michael Whitlock. Evaluating methods for estimating effective population size in the presence of migration (372). Sunday, 22 June at 9:15 AM, room 306A. Session 2A_306A Methods for Migration.
  • John Stanton-Geddes, Andrew Nguyen, Nicholas Gotelli, and Sara Helms Cahan. Patterns of thermal stress tolerance vs resistance in genome-wide expression data of sympatric ant species (499). Sunday, 22 June at 9:30 AM, room 305B. Session 2A_305B Gene Expression.
  • Jeremy Yoder and Peter Tiffin. Population genetic and genomic identification of locally adapted loci (480). Sunday, June 22 at 3:15 PM, room 305 B. Session 2D_305B Genomics.
  • Andrea Thomaz, Mark Christie, and L. Lacey Knowles. River Networks and the Genetics of Aquatic Populations (6). Monday, 23 June at 10:55 AM, room 304. Session 3B_304 Lightning Talks: Evolution theory, methods, outreach.
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People behind the Science: Dr. Montgomery Slatkin

To honor his recent election to the National Academy of Sciences, we’re featuring Dr. Montgomery Slatkin of the University of California, Berkeley. Dr. Slatkin is known for his work in theoretical population genetics, in particular with regard to gene flow and range expansion. Recently, he’s also studied the genetics of human disease, and the paleo-genetics of ancestral human populations. Below, I ask Dr. Slatkin about his background, research and dinner parties.

1) Congratulations your election to the National Academy of Sciences! Can you tell us a bit about how you become a population geneticist?

When I was a graduate student in applied math at Harvard, I got to know William Bossert, who had just joined the faculty there. He asked for my help with some mathematical problems that arose in his studies of assortative mating. After I expressed some interest in the general subject, he arranged for me to meet E. O. Wilson and Ernst Mayr, both of whom encouraged me to work in in population genetics and evolution. It seemed like a great opportunity for me and they were all generous in helping me get started.

Dr. Montgomery Slatkin, image courtesy of M. Slatkin.

Dr. Montgomery Slatkin, image courtesy of M. Slatkin.

2) You’ve done considerable work on the estimation of gene flow among populations. Can you generally explain why the study of gene flow is important?

As Bossert first pointed out to me, gene flow is important for evolution because most populations have a broad spatial distribution and experience different conditions in different parts of their ranges. The kind of mathematics I had studied was well suited to the analysis of gene flow combined with other population genetic forces.

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Spontaneous mutations—friend or foe?

Image via.

Image via.

The following is a cross-posting from the Stanford CEHG Blog by Ryo (Ryosuke) Kit, a graduate student in Hunter Fraser’s lab at Stanford University.

Evolution has conflicting opinions about spontaneous mutations. Spontaneous mutations produce the genetic variation that drives evolution in all organisms, but at the same time, most mutations that affect fitness are harmful for the organism. Despite being a pivotal component of evolution, our understanding of mutations is limited.

To understand the role of mutations in evolution, the following basic questions are essential: What types of spontaneous mutations occur? How frequently do they occur?

Such simple questions are surprisingly difficult to answer, but a recent study by Yuan Zhu (Zhu et al. 2014) has harnessed the power of next generation sequencing to get a better answer to these questions for the budding yeast S. cerevisiae.

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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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