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Last week the Society of Systematic Biologists hosted its first standalone meeting from May 20-22 at the University of Michigan. The meeting included workshops, panel debates, three sessions of lightning talks, and an evening reception at the UM Museum of Natural History. I had a ton of fun meeting new people and catching up with old FIS (friends in science). I’m certain most of the ~200 attendants would agree the meeting was a huge success and I hope SSB will continue the tradition of the standalone meeting. In my post today I will highlight a subset of the talks I saw during the meeting. You can look back at tweets from the meeting with the hashtag #SSB2015. Continue reading
My posts are about to take on a strong bias towards field work and interviews with the researchers kind enough to offer assistance to our lab as we embark on a Northern Hemisphere tour. Not only will we be sampling seaweeds along both North American coasts, we’ll be jet-setting to Europe and to Japan.
As my thoughts have bent increasingly toward Japan with our departure date looming and thinking about invasions, it seemed appropriate for a last paper review about an invasion. But, this invasion occurred in the opposite direction of the one we’re investigating.
So et al. (2015) examined Daphnia pulex in Japan to determine whether the populations were indigenous or recent colonizer.
Using mitochondrial DNA, they were able to determine that the Japanese populations were colonizers that had hybridized with another Daphnia species prior to arrival across the Pacific.
There were 4 distinct groups, based on mtDNA, but only one unique multilocus microsatellite genotype was found per group, suggesting asexual reproduction.
Interestingly, some clones could not be attributed to recent anthropogenic activities, but might have instead been the result of extremely rare events, such as the disruption of migratory flyways due to a volcanic eruption.
But, if populations are asexual, are they dead-ends? Do they require the influx of new migrants to increase genetic diversity?
Under a divergence, or isolation model, the genomes of individuals in a daughter-population are expected to harbor greater differentiation relative to its sister-population, and lower differentiation within the population (after sufficient time since divergence). Divergence thus is a mechanism of allopatric speciation, with strong selection on regions of the genome that are involved, or implicated in furthering reproductive isolation, and adaptive evolution. These regions would be expected to show low(er) levels of differentiation, compared to the rest of the genome. If secondary contact occurs between diverged sister-populations, regions of relatively lower differentiation are possibly introgressed. In common practice, two measures of differentiation have been used to identify these “genomic islands of speciation” – Fst, and Dxy. While Fst is a relative measure of allele frequency differences between populations, Dxy is a measure of absolute differences in nucleotides (or repeat lengths for short tandem repeat (STR) markers). While both measures have issues with interpretation (see Cruickshank and Hahn (2014) for an excellent review), Fst is particularly sensitive to recent secondary contact.
Geneva et al. (2015) describe a statistic called “Gmin” using haplotype data, which is a relative Dxy measure – a ratio of the minimum Dxy between haplotypes from sampled populations, and the mean Dxy between populations to subvert the issue of misinterpretation of Fst in the event of secondary contact. Through simulations, and the study of a Drosophila dataset (Rwandan populations of D. melanogaster), Geneva et al. show that Gmin (a) increases with divergence time of the two populations, but plateaus faster than Fst, (b) has increased sensitivity and specificity for all compared simulations, with greatest sensitivity if the time of secondary contact is very recent, (c) has an expanded range, compared to Fst, making it easier to delineate the presence of recent introgression, as shown by the ranges detected in D. melanogaster (0.0982 < Gmin < 0.9833, versus 0.0170 < Fst < 0.5107).
However, as cautioned by Cruickshank and Hahn (2014), Geneva et al. also highlight the importance of checking for the presence of unusually low (or high) values of absolute divergence, in regions of low Gmin (or Fst) to avoid misinterpretation.
However, in cases of recent secondary contact, and when the rates of gene flow are not extremely high, we have shown that Gmin performs well and is more reliable than Fst
Geneva, Anthony J., et al. “A new method to scan genomes for introgression in a secondary contact model.” (2015): e0118621. DOI: http://dx.doi.org/10.1371/journal.pone.0118621
Cruickshank, Tami E., and Matthew W. Hahn. “Reanalysis suggests that genomic islands of speciation are due to reduced diversity, not reduced gene flow.” Molecular ecology 23.13 (2014): 3133-3157. DOI: http://dx.doi.org/10.1111/mec.12796
When interpreting the results, it is important to focus more on biological relevance than on statistical significance. That does not mean that significance is unimportant; results that have a straightforward interpretation but are not significant should not be considered. On the other hand, one should not be blinded by results that are strongly significant. In the genomics era, with thousands upon thousands of loci, strong significance is easily obtained even for biologically marginal processes.
Recently accepted to Molecular Ecology, Patrick Merimans’ “Seven common mistakes in population genetics and how to avoid them” was burning down the house on Twitter this past week.
I can definitely see why this sort of paper is both timely and interesting to a wide array of scientists. It’s a quick read, and sure to generate some discussion. One opinion I’ve seen popping up over and over is that this list is just the start of the common mistakes in population genetics, but I’ve seen fewer suggestions as to what actually needs added to the list.
So I ask you, opinionated readers, what mistakes are we making? Why keep them to yourself when you can share?
Meirmans, P. G. (2015). Seven common mistakes in population genetics and how to avoid them. Molecular Ecology.
big. And they get even bigger after they eat a meal: like a mouse or an alligator. Indeed, their guts undergo rapid changes in form and function during and after a feeding bout. And, since everyone everyone and their mothers are doing transcriptomics, a group of researchers decided to see if gene expression changes occurred along with these drastic changes in physiology (spoiler alert: they do). Continue readingBurmese pythons can get pretty
Determining the whens and hows of biological invasions using genetic data is a major goal of molecular ecology. One such tool is approximate Bayesian computation (ABC) which is being used for inferring invasion histories.
In a new paper in Heredity, Benazzo et al. (2015) present a largely unexplored model of multiple introductions from a single source.
Their scenario posits one invasive population that has established at a single site. After a few generations, a new wave of introduced individuals arrive.
The novel aspect of this model is that the second wave originates from the same source as the first; most models of multiple introductions consider a second wave originating from a geographically and genetically different source than the first.
Using simulated microsatellite data, the power of ABC to distinguish between single and multiple introductions from the same source and under a variety of different demographic parameters was evaluated.
[They] demonstrated that it is often possible, using the inferential power of ABC and under a range of realistic demographic conditions, to distinguish between one or two waves of invasion from the same source, and to infer some important parameters.
The transcriptomics field is boomin’. Approaches like RNA-seq have opened the flood gates to hundreds and hundreds of investigations that compare gene expression between biologically-interesting phenotypes, variants, species, etc.
Plastic phenotypes have been a fascinating area of study for decades in ecology, but the molecular mechanisms behind these phenotypes have only recently become more tractable. A good example of this type of investigation by Matsunami et al. appears soon in Molecular Ecology:
The main aim of this study was to compare transcriptomic patterns in the brain and peripheral tissues between predator-exposed and prey- exposed larvae of the Hokkaido salamander by using RNA-seq technologies.
Phenotypic plasticity is well documented from both a predator and prey perspectives, and the Hokkaido Salamander is an example of a taxon that displays both types: a super-sized mouth (“attack morph”) when in habitats with large tadpole prey and a suite of traits (large gills, large tail fin; “defense morph”) when in habitats with potential invertebrate predators.
Matsunami et al. show that there were six times more differentially expressed genes among those salamanders that took on the phenotype induced by an invertebrate predator when compared to those that took on the phenotype induced by the presence of tadpole prey (103 vs 605 differentially expressed genes, respectively).
Because the increase in tail height induced by predation pressure is documented in other amphibian lineages, the authors hypothesize that the evolution of a new (plastic) phenotypes probably involves the co-option of pre-existing molecular mechanisms in combination with novel regulation:
In a species already capable of a certain plastic phenotypic response, some molecular mechanisms involved in the expression of pre-existing phenotype may be recruited for the production of the new plastic phenotype. For example, we found that some genes showed similar expression changes in both evolutionarily old predator-induced phenotypes and in evolutionarily newer prey-induced plastic phenotypes. Thus, the co-option and modification of gene networks already used for the expression of evolutionarily old plasticity may occur during the evolution of a novel plastic phenotypic response.
Matsunami M., Kitano J., Kishida O., Michimae H., Miura T. & Nishimura K. (2015). Transcriptome analysis of predator- and prey-induced phenotypic plasticity in the Hokkaido salamander (Hynobius retardatus), Molecular Ecology, n/a-n/a. DOI: http://dx.doi.org/10.1111/mec.13228
Twitter has been abuzz with Orna Man and Yoav Gilad’s (re)analysis of the data from a recent PNAS paper: “Comparison of the transcriptional landscapes between human and mouse tissues”.
The PNAS paper concluded that the gene expression profiles of different tissues within the same species were more similar than the same tissue across different species. For example, their analysis showed that the gene expression profile of a mouse spleen was more similar to that of a mouse heart than it was to a human spleen. This didn’t seem to mesh with well previous research, so it didn’t make much sense. Well, that is until Man and Gilad decided to probe it a bit further. Continue reading