The results are in for the journal selection survey

Two weeks ago I wrote a post about a recent paper by Salinas and Munch that presented a model-based method for determining to which journal an author should submit a manuscript for publication. I was curious to know how the readers of The Molecular Ecologist choose where to send their papers so I included a link for a short, informal survey to gauge how people feel about the submission/publication process. Fifty people completed the survey (thank you!) and I have posted the results below.

Career Stage

demographics2The majority of people who responded were postdocs followed by graduate students and faculty members, from assistant to full professors. An industry scientist, a museum research scientist, and an NGO scientist also provided feedback giving the survey some diversity.

At what point in the process do people pick a journal?

when

The majority of people who responded indicated that they decide where to submit a manuscript after they have collected and analyzed the data and before they have started to write the paper. Based on the comments of a few of the respondents, making the decision abut which journal to go with seems to be a fluid process.

“It varies. I usually have ideas of where it might be submitted before or during the experimental stage, but that often shifts as I get closer to the writing stage. Usually by the time I’m seriously working on the manuscript, I have a journal in mind so I can format it the way that journal wants.”

Factors that influence journal choice

factors1

According to the responses, journal reputation, the fit of the manuscript to the journal, and the journal impact factor are the three most important criteria people consider when deciding where to submit a manuscript. Because survey takers could write in any answer (as opposed to choosing from predetermined options), I combined some responses into one category to make displaying the results a little easier. For example, “journal reputation,” “prestige,” and “quality” were lumped into one category. Many people who listed journal reputation as a top-three factor also included journal impact factor. To me this suggests that people view reputation as somewhat separate from impact factor- a journal with a high impact factor may not have a great reputation in the opinion of a researcher (or vice versa). I found it interesting that “likelihood of acceptance” fell in the middle of the pack.

Model-based methods

model

 

 

 

 

 

 

 

The majority of people were on the fence about using a model-based method, such as the one proposed by Salinas and Munch (2015), to select a target journal for a manuscript.

Taking a risk

risk

The survey asked “How likely would you be to submit to a prestigious journal and risk rejection instead of submitting to a solid, but lower ranked journal where you know your paper has a good shot at being accepted quickly?” Respondents were able to write in any answer so, as objectively as possible, I categorized the responses into “yes,” “no,”  and “maybe.” Most respondents were willing to take a risk on getting a paper into a high impact journal although many people said the decision to aim high depended on career stage. Considerations such as the desire to get the data out quickly or avoid time-wasting reformatting for multiple journals were also important.

“As a grad student I would be less inclined to take risks, as quantity of pubs and speed/short review process was a priority. As a postdoc, I’m more inclined to take risks since the expectations are higher.”  

“Depends on the urgency to get the data out, but I will risk rejection at a prestigious journal occasionally.”

“It depends on the turn around time for the higher ranked journal. Something like PNAS where rejection is very fast, yes, but somewhere that is notoriously slow like Systematic Biology, no.”

“Rejection is fine, it just means you have to rewrite; prefer submitting to solid, lower-ranked b/c prefer not to rewrite and reformat.”

Final thoughts?

The last question on the survey asked the respondents if they wanted to say anything else generally about the way in which they choose a target journal. Here are some of the most interesting responses and those that did not fit neatly into a category above…

“The size of my data set and my methods are also important in where I decide to submit a paper.”

“I like to publish in “society-based” journals such as Am Nat, Evolution, etc.”

Word limit is sometimes also a factor.” 

“My priorities and those of my coauthors often differ, so journal selection is often a negotiation (unless it’s very clear-cut from the get-go).”

“The main thing is to get the work into the public domain.”

“I feel the process is quite subjective, depending on recent pubs in the field and in each journal. Depends on appeal of the paper, desired audience. Can’t imagine a model that would capture all that I think needs to go into the decision.”

I enjoyed very much seeing the results of my informal survey and reading the responses of those who took the time give their opinions. The overall impression I get is that the process of choosing where to send a manuscript for publication is subjective, complex, and often a compromise among many factors. Thanks again to those who filled out the survey. May your acceptances be swift and your rejections few and far between. Happy publishing!

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Posted in career, Impact Factors, methods, peer review, science publishing | 1 Comment

Beauty is in the eyes of the beholder

Many animals use visual signals to scope out potential mates. In a new paper in Molecular Ecology, Sandkam et al. (2015) demonstrate that the variation underlying preference in female guppies could be explained by simple changes in expression and coding of opsins. Beauty really may be in the eyes of the beholder.

© greerchicago.com

© greerchicago.com

Populations can diverge rapidly via sexual selection, but there are very few systems in which the variation in female preference is replicated in a consistent manner across populations.  Trinidadian guppies are a classic model system exploring the evolution of female mate choice.  In response to environmental factors, such as predation, female mate preference varies  both within and between populations.

In guppies, there are nine opsin proteins in which each is coded by a single gene and grouped by the light they detect.  Changes in gene sequence and expression could alter the tuning of these sensory systems.

Guppy vision differs across populations in a consistent manner based on the opsin expression and allele frequencies in natural populations.

Guppies in low-predation populations express more long wavelength-sensitive opsins than do guppies from high-predation environments and low-predation populations are almost fixed for an alternative amino avid known to affect retinal tuning.

Their data suggest that much of the variation in female preference can be explained by differences in the visual system.

populations with stronger female preference for red/orange coloration invest a strikingly greater proportion of their color vision in detecting those colors and are strongly differentiated for sequence variants [which are known] to change spectral sensitivity.

Sandkam et al. (2015) Beauty in the eyes of the beholders: colour vision is tuned to mate preference in the Trinidadian guppy (Poecilia reticulata). Mol Ecol 24, 596-609

Posted in Coevolution, evolution, Molecular Ecology, the journal, natural history, population genetics, speciation, Uncategorized | Tagged , , | Leave a comment

Genome-wide effects of artificial selection

Humans have been artificially selecting for favorable traits in crops, pets, and livestock over millennia. Years of theoretical predictions and experimental evolution studies have shown the detrimental effects of increased homozygosity, and the population-wide advantages of artificially maintaining heterozygosity. Two new manuscripts (Hedrick (2015), and Kessner and Novembre (2015)) aim at discussing the genome wide effects of artificial selection, albeit focused on different characteristics.

Expected increase in heterozygosity upon introduction of a new allele at a low frequency, plotted at different levels of artificial selection. Image courtesy: http://jhered.oxfordjournals.org/content/106/2/141/F2.expansion.html

Hedrick (2015) reviews the phenomenon of ‘overdominance’, or heterozygote advantage across 12 different traits. The list includes milk yield in dairy cattle, litter size in pigs, tail length in cats, hairlessness in dogs, among other described cases. Hedrick also discusses some theoretical predictions on the perpetration of heterozygosity in artificially selected populations, importantly the strength of selection on fixation times.

…given very strong selection from an environmental or other change, a new mutant that has an advantage as a heterozygote might increase in frequency. However, if it had a lowered fitness as a homozygote, it would be maintained as a polymorphism due to its overall heterozygote advantage…

Kessner and Novembre (2015) describe an analysis pipeline using forqs, and utilize simulations to predict the effects of artificial selection at QTLs, based on population sizes (drift, efficacy of selection), proportion of individuals chosen to propagate, length of the experiment, and replication. Forward simulations indicate (1) predictable trajectories of fixation of new alleles under constant selection (also predicted by the scenarios described by Hedrick (2015) above), (2) qualitative differences in trajectories of allele frequencies of linked QTLs, (3) increase in power to detect selected QTLs (versus neutrally evolving loci) with increased replication, and starting population sizes, and importantly, (4) the effect of recombination (which reduces the interference, and LD between linked QTLs).

We emphasize that the opportunity for recombination is a key factor in the power to detect and localize QTLs, and that this should be taken into account by future designers of artificial selection experiments.

References:

Hedrick, Philip W. “Heterozygote Advantage: The Effect of Artificial Selection in Livestock and Pets” J Hered (2015) 106 (2): 141-154 http://dx.doi.org/10.1093/jhered/esu070

Kessner, Darren, and John Novembre. “Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits.” Early Online February 10, 2015, http://dx.doi.org/10.1534/genetics.115.175075

Kessner, Darren, and John Novembre. “forqs: forward-in-time simulation of recombination, quantitative traits and selection.” Bioinformatics 30.4 (2014): 576-577. http://dx.doi.org/10.1093/bioinformatics/btt712

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How do you unite the stage and actors of the evolutionary play?

When you are forced to give your one sentence, off-the-cuff response to “what kind of scientist are you?”, who do you become?

A landscape geneticist? Community geneticist? Landscape epidemiologist?

A new opinion in Trends in Ecology and Evolution by Brian HandWinsor Lowe, and others calls for less distinction between these identities to answer contemporary and compelling questions in evolution and ecology.

From Hand et al. 2015

From Hand et al. 2015

The consideration of both biotic (think community genetics/ecology) and abiotic (think landscape genetics) factors and their effects on patterns of genetic variation are often pursued as part of separate investigations. Hand, Lowe, and their coauthors make the comparisons to G. Evelyn Hutchinson’s “Ecological Theater and the Evolutionary Play”, suggesting that the actors (the species and their interactions) and the stage (the abiotic environment) are not considered together often enough.

Landscape genetics and community genetics have developed as largely-independent disciplines, growing in popularity and importance, but without capitalizing on the complementary nature of the two approaches.

The sort of data required to ask questions in the framework proposed is a serious challenge (adaptive and neutral genetic data, geographic information, demographics, etc.). The authors point towards burgeoning field of metagenomics as leading the way in some of these new ways of thinking, but there are certainly labs who read this blog that bridge these interdisciplinary divides already. What remains to be seen is if these researchers can effectively roll all of these techniques together under the common title of “Landscape Community Genetics”.

Hand B.K., Lowe W.H., Kovach R.P., Muhlfeld C.C. & Luikart G. (2015). Landscape community genomics: understanding eco-evolutionary processes in complex environments, Trends in Ecology and Evolution, DOI: http://dx.doi.org/10.1016/j.tree.2015.01.005

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Harry Smith, the founder of Molecular Ecology, has died

We’ve received word that Harry Smith, the founder of Molecular Ecology, passed away yesterday.

Smith had a prolific and well-regarded career studying the molecular basis of plants’ responses to their environments. In particular, he helped to demonstrate how plants perceive the color, and thereby the quality, of light, and adjust their growth in response. In addition to editing Molecular Ecology from its 1992 launch through 2008, Smith was founding editor of the journals Plant, Cell & Environment and Global Change Biology. On his departure from the editorship, he was awarded the 2008 Molecular Ecology prize, and profiled in the journal by Peter Quail, who wrote:

… Harry Smith is a scholar, mentor, internationally renowned researcher, eloquent speaker and author, pioneering journal editor and highly valued colleague who has contributed greatly in multiple ways to plant science and the community.

Our thoughts are with Smith’s friends and family.

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THREAT DOWN! Gene flow from polar bears into brown bears

Bears, perennial toppers of the ThreatDown list on The Colbert Report (copyright Comedy Central)

What do you get when you cross a male polar bear with a female brown bear? Trick question: Nothing, because it doesn’t really happen!* Continue reading

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Breaking free of the guide tree: two new species delimitation methods

Guide trees got you down? Break free with these new species delimitation methods! Picture from http://www.comicbookmovie.com/

Are guide trees your Kryptonite? Break free with these new species delimitation methods! Picture from http://www.comicbookmovie.com/

A couple of weeks ago I wrote about a new method to incorporate morphology and DNA sequences into species delimitation. Including both data types improved the results but a couple of tricky spots remained: 1) correctly assigning individuals to putative species and 2) estimating an accurate guide tree. Two recent papers have developed ways to help us break free from the guide tree and move towards a more objective, robust species delimitation.

Jones et al. 2014 present their method DISSECT (Division of Individuals into Species using Sequences and Epsilon-Collapsed Trees) which does not require the a priori assignment of individuals to clusters/species but instead explores all possible clusterings and species tree topologies.

The basic idea behind DISSECT is to sample trees in which each tip represents a single individual (or a cluster of individuals which definitely belong in one species), but replace the usual prior density on node heights with one which includes a spike near zero. The dimensionality of the parameter space is fixed, but nodes whose heights have a high posterior probability of being within the spike can be interpreted as ‘probably collapsed’

The analysis can be run in BEAST (version 1.8.1 and later) and Jones et al. provide a nice section describing the workflow of the analysis and some advice on how to set the parameters and priors.

The second paper, Yang and Ranala (2014) present an updated version of their program BPP which eliminates the user-defined guide tree in species delimitation and incorporates phylogenetic uncertainty of the gene trees in a Bayesian framework.

A novel MCMC proposal based on the nearest-neighbor interchange (NNI) algorithm for rooted trees is developed here to change the species tree topology, eliminating the need for a user-specified guide tree. The gene trees for multiple loci are altered in the proposal to avoid conflicts with the newly proposed species tree.

One potential drawback to the method is that it may not be practical for a large number of populations- computation time increases much more quickly with an increase in the number of populations than with an increase in the number of sequences per locus. Nevertheless, the introductions of DISSECT and new version of BPP are exciting steps forward in species delimitation and I am excited to see them tested on empirical systems by other researchers.

Jones, G., Aydin, Z., & Oxelman, B. (2014). DISSECT: an assignment-free Bayesian discovery method for species delimitation under the multispecies coalescent. Bioinformatics, btu770. DOI: 10.1093/bioinformatics/btu770

Yang, Z., & Rannala, B. (2014). Unguided species delimitation using DNA sequence data from multiple loci. Molecular Biology and Evolution31 (12):3125-3135. DOI: 10.1093/molbev/msu279

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Rescue me

© wikipedia

© wikipedia

Whiteley et al. (2015) review genetic rescue (GR), or the increase in population fitness (growth) owing to immigration of new alleles, in a new paper in TREE.

Genetic rescue is a controversial and hasn’t been applied to any great extent in conservation efforts.  In small populations of conservation concern, a small number of individuals introduced into an isolated population could restore genetic diversity and mask inbreeding depression. But, debate has centered on:

whether translocation of individuals or alleles into small, imperiled populations will have the desired effect of increasing population growth rates and maintaining a diverse array of local populations, or reduce population fitness through outbreeding depression and decrease biodiversity by homogenizing distinct gene pools.

The authors point to recent work in which re-establishing gene flow among populations that were recently connected will increase fitness (e.g., Hwang et al. 2011).

Genomic approaches will aid in the implementation and effectiveness of GR by improving the ID of the best populations or even individuals for GR and monitoring the outcome of GR attempts with adjustments implemented as necessary.

Hwang AS, Northrup SL, Alexander JK, Vo KT, Edmands S (2011) Long-term experimental hybrid swarms between moderately incompatible Tigriopus californicus populations: hybrid inferiority in early generations yields to hybrid superiority in later generations. Conserv Genet, 12, 895-909

Whiteley AR, Fitzpatrick SW, Funk WC, Tallmon DA (2015) Genetic rescue to the rescue. TREE 30, 42-49.

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Phonemes and Genomes

Human phonemes and genomes are thought to have evolved hand-in-glove out of Africa. Several recent studies have attempted to capture a picture of this global variation in languages and peoples, often supporting (and rejecting) a serial founder model (eg. see Atkinson 2011, Perreault and Mathew 2012, Hunley et al. 2012). In a recent large-scale study of microsatellite loci from 246 human populations and phonemic variation across >3000 languages, Creanza et al. (2015) use a PCA (and tests of correlation) to report several interesting patterns in the co-evolution of phonemes and genomes.

Phonemic diversity decline with distance from Eurasia. Figure 3 from Creanza et al. (2015) Image courtesy: http://www.pnas.org/content/112/5/1265/F3.large.jpg

Of note are the observations that (1) there is no universal concordance in genetic and phonemic diversities despite most diversity in both were observed in Africa, (2) there exists a strong correlation in differences among populations and geographic distance (and a reduction in number of phonemes with distance from Eurasia), but (3) phonemic diversity is informative of more recent divergence history, rather than of ancient divergence (also indicated by spatial autocorrelation), and (4) a Eurasian origin to all languages analyzed.

Importantly, their analyses indicate that phonemes, unlike genomes, don’t necessarily reflect vertical evolutionary descent, warranting newer models to study the evolution of languages.

Reference:

Creanza, Nicole, et al. “A comparison of worldwide phonemic and genetic variation in human populations.” Proceedings of the National Academy of Sciences (2015): 201424033. http://dx.doi.org/10.1073/pnas.1424033112

Posted in bioinformatics, evolution, genomics, phylogenetics, population genetics | Tagged , , , | 1 Comment

Night at the museum

Many population genetic and genomic studies document snapshots of a given population’s genetic diversity. Yet, there are many reasons to document changes over time in population parameters in response to perturbations, such as biological invasions (both in terms of the invader and the invaded).

There is a rich history of long-term ecological monitoring in which the abundance and distribution of species are recorded. For example, the MarClim project has continued efforts by the Marine Biological Association of the United Kingdom of monitoring intertidal zones, in which records date back to the 1950s. However, these monitoring projects tend to be concerned with ecological patterns rather than documenting genetic change through time.

Extension of the leading range edges occurring in the Lusitanian species Perforatus perforatus, Phorcus lineatus, Gibbula umbilicalis, Chthamalus stellatus, Bifurcaria, and then contractions of the southern trailing range edge of the Boreal species Alaria esculenta and Semibalanus balanoides. © Nova Mieszkowska

Extension of the leading range edges occurring in the Lusitanian species Perforatus perforatus, Phorcus lineatus, Gibbula umbilicalis, Chthamalus stellatus, Bifurcaria bifurcata, and then contractions of the southern trailing range edge of the Boreal species Alaria esculenta and Semibalanus balanoides. © Nova Mieszkowska

There are studies in which genetic change through time has been studied, such as Reem et al. (2013) in which limited gene flow associated with high mutation rates was documented in the ascidian Botryllus schlosseri over a 13-year period. But, what about larger scales, both spatial and temporal?

Continue reading

Posted in DNA barcoding, evolution, genomics, natural history, next generation sequencing, phylogenetics, population genetics, speciation, Uncategorized | Tagged , , , | Leave a comment