To sequence a genome or not to sequence a genome, that is the question

In a paper out last month in the Journal of Phycology, Bhattacharya et al. (2015) provide a perspective on the need for more algal genomes.

[A] relevant question on the minds of many phycologists might be: do we really need more algal genomes or, should we stop and focus on the hard job of developing genetic tools and other resources for already sequenced taxa?
Chondrus crispus, one of the first macroalgal genomes (Collén et al. 2013) © SA Krueger-Hadfield

Chondrus crispus, one of the first macroalgal genomes (Collén et al. 2013) © SA Krueger-Hadfield

Algal molecular work has historically lagged a bit behind similar work in other taxonomic groups even though algae are important primary producers in marine environments.

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Posted in bioinformatics, evolution, genomics, horizontal gene transfer, mutation, next generation sequencing, selection | Tagged , , , , | Leave a comment

Just in time for spring break- the phylogenetic and medicinal history of Aloe vera

Aloe vera plant. Photo from www.aloeverahq.com

Aloe vera plant. Photo from www.aloeverahq.com

It’s spring break season across the United States, which means many undergraduates are shedding their winter layers and flocking to warm, tropical destinations. After a week of fun in the sun, I’m sure many of them will rely on  Aloe vera to soothe their sunburns.

In a recent BMC Evolutionary Biology paper, Grace et al. (2015) examined the phylogenetic history of Aloe vera and its relatives, tracing the medicinal use of plants in the genus. The authors collected sequence data from nuclear and plastid loci for 239 taxa in the family Xanthorrhoeaceae, including 197 species in the Aloe, Aloidendron, Aloiampelos, Aristaloe, Gonialoe and Kumara genera. They constructed phylogenetic trees, estimated divergence dates, and obtained information from a dataset of 1400+ records from the literature to test for phylogenetic signal in the use of aloes. Continue reading

Posted in medicine, phylogenetics, plants, Uncategorized | Leave a comment

Mating systems

In a new paper, published online in Molecular Ecology, Pannell (2015) reviews the literature on the evolution of mating systems and dispersal in colonizing species as component of a special issue called Invasion Genetics: The Baker and Stebbins Legacy. 

This issue is also the product of a special symposium at Asilomar in August 2014. I couldn’t resist a painting of that beautiful coastline where I spent my days as a budding molecular ecologist as well as writing about mating systems!

Asilomar Beach © karenwinters.com

Asilomar Beach © karenwinters.com

Self-compatibility should be a common feature among colonizing species (aka Baker’s Law). Colonization of oceanic islands, range expansions, biological invasions and metapopulation dynamics have all  been discussed within the context of Baker’s Law. But as with any law, there has been a lot of debate about its generality.

Models invoking the evolution of mating systems and dispersal seem to be at odds with models invoking Baker’s Law. Indeed, the

overwhelming feeling one gets from the literature on the evolution of reproductive and dispersal traits in colonizing species is one of cryptic complexity. Terms such as colonization, self-fertilization and dispersal roll easily off the tongue (or pen), but each of these terms encompasses a hazardously broad range of possible meanings.

Pannell argues for a more “nuanced consideration of dispersal” and the necessity of outcrossing and selfing rates as opposed to the ability to undergo self-fertilization.

Plants, in particular, are known for the plasticity of plant sexuality. Yet, we have a

poor understanding of the distribution of reproductive and dispersal traits in colonizing species.

Certainly, more empirical and theoretical work is necessary, but this work should also go beyond plants and animals that a diploid-dominant.

Pannell, JR (2015) Evolution of the mating system in colonizing plants. Molecular Ecology DOI: 10.1111/mec.13087

Posted in adaptation, Coevolution, conferences, evolution, Molecular Ecology, the journal, selection | Tagged , , , , , | 1 Comment

Exploring color palettes in R

How often have you had to squint at figures with unpleasant color palettes in a manuscript online or in print, and ultimately given up on distinguishing between fifty (or maybe just around 30) shades of gray? I found the RColorBrewer package extremely helpful when it comes to picking colors for figures – instead of the standard way of letting R decide your palette (using say ‘rainbow’, or ‘topo.colors’ – see this link). Here I describe some uses of RColorBrewer to make neat admixture bar-plots in R. You should be able to use the same color palettes for use in other kinds of plots as well (see my previous posts). Say you have a Q (admixture proportion) matrix obtained from your favorite program (STRUCTURE/ADMIXTURE/FASTRUCT/etc) – named q.txt. Here, I ran multinomial clustering with K = 3 subpopulations, requiring a three color palette from RColorBrewer. The data set that I used was mined from the Tishkoff lab as part of the supplementary material of a paper on microsatellite variation in African populations. Eg: “q.txt” -

0  1   0
0.312204    0.687796    0
0   1   0
0   1   0
0   0.88985 0.11015
0.457319    0.542681    0
0.149153    0.850847    0
0.451845    0.477733    0.070422
0.405077    0.350571    0.244352
0   1   0
0   1   0
0.131876    0.707725    0.1604
...

To read the data file, install libraries:

install.packages(“RColorBrewer”)
library(RColorBrewer)
q<-read.table(“q.txt”)
barplot(t(as.matrix(q)),col=rainbow(3),xlab="Individual #", ylab="Ancestry",border=NA)

This should produce a bar plot with generic colors, picked using the ‘rainbow’ function.

rainbow To use ColorBrewer, I recommend playing around with different accent colors (you should be able to display them all using the display.brewer.pal(n, name) function. Alternately, you should be able to visualize a variety of schemes on the ColorBrewer2 website here.

For example:

display.brewer.pal(3, “Greys”)
display.brewer.pal(6, “Accent”)

Thereon, create your own color palette using:

mypal<-brewer.pal(3, “Accent”)

You could also let ColorBrewer decide red-green colorblind friendly palettes, using:

mypal<-display.brewer.all(3, “Accent”, colorblindFriendly=TRUE)

Now you should be able to plot this directly by plugging your customized palette into the barplot function as:

barplot(t(as.matrix(q)),col=mypal,xlab="Individual #", ylab="Ancestry",border=NA)

Here are two examples – one in grayscale, one using a spectral color scheme.

spectral gray

Speaking of colors, here are some spectacular images from Holi celebrations across the world! Happy Spring, everyone!

Posted in howto, population genetics, R, software, STRUCTURE | Tagged , , | 8 Comments

Phylogenetic dispersion aversion

image source

How biological communities form and are maintained is a complex and fascinating area of molecular ecology. Gerhold et al. offer up an interesting take on community phylogenetics in a recent Functional Ecology paper that argues against the use of phylogenetic dispersion as a proxy for the mechanisms behind community assembly.

The authors take the time to work through some of the assumptions made in these proxy analyses and weigh their real support in the literature. This list of assumptions includes:

  •  (i) phylogenetic dispersion reflects trait dispersion
  • (ii) a given ecological function can be performed only by a single trait state or combination of trait states
  • (iii) trait similarity causes enhanced competition;
  • (iv) competition causes species exclusion
  • (v) communities are at equilibrium with processes of assembly having been completed
  • (vi) assembly through habitat filtering decreases in importance if assembly through competition increases, such that the relative balance of the two can be thus quantified by a single parameter
  • (vii) observed phylogenetic dispersion is driven predominantly by local and present-day processes.

The lack of support for some of these isn’t that surprising (such as ii and vii), but I was surprised to find some of the concepts that I consider well-supported (such as iv) might not be so accepted after all.

Gerhold et al. suggest the way forward is to incorporate more evolution into the first steps of forming questions:

Despite an increasing number of pictures of Charles Darwin in conference presentations of community ecologists, the questions asked in many of these studies do not concern any evolutionary processes.

It turns out that these same assumptions that the authors criticize make for fantastic hypotheses to test using the same types of data. This context shift in how community assembly questions are asked is the true purpose of this paper, and makes it well worth the read:

Phylogenetic dispersion of communities is of limited value for understanding ecological assembly processes, but of high value to address other questions in eco-evolutionary research. The links between ecological assembly processes and trait patterns, and between trait patterns and phylogenetic dispersion of communities, might be too complex and weak. Instead, information on phylogenetic community structure is a potentially valuable tool to answer evolutionary questions, where community ecology can be seen as macroevolution in action.

 

Gerhold P., Cahill J.F., Winter M., Bartish I.V. & Prinzing A. (2015). Phylogenetic patterns are not proxies of community assembly mechanisms (they are far better), Functional Ecology, n/a-n/a. DOI: http://dx.doi.org/10.1111/1365-2435.12425

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Speciation by selection (and drift) in the sea

The orangeband surgeonfish, Acanthurus olivaceus. Photo from reefguide.org

The Orangeband Surgeonfish, Acanthurus olivaceus. Photo from reefguide.org

Marine systems challenge the view that speciation is the result of geographic isolation. Many marine taxa have large effective population sizes, which slows lineage sorting, larval dispersal phases that may extend for days, weeks, and sometimes months, potentially connecting far flung populations, and they exist in an environment that lacks obvious physical isolating barriers. All of these characteristics should theoretically lead to panmictic populations with little chance of divergence and yet marine ecosystems, particularly coral reefs, are among the most species-rich on the planet.

In their recent Molecular Ecology paper, Gaither et al. (2015) used mitochondrial and nuclear intron sequences and 3,700+ genome-wide SNPs to test the mechanism of speciation in two members of the Orangeband Surgeonfish species complex, Acanthurus olivaceus  and  A. reversus. The authors focused on peripheral populations that split from the main central-west Pacific lineage at approximately the same time (~0.5 million years ago; see figure below). The Hawaiian population is morphologically indistinguishable from the main central-west Pacific lineage but the Marquesas population differs morphologically and in its ecological niche.   Continue reading

Posted in genomics, next generation sequencing, selection, speciation | Leave a comment

sedaDNA sleuths: embracing your inner Sherlock

Awhile back fellow TME contributor Rob Denton posted about a recent review on environmental DNA by Pedersen et al. (2015).

Environmental DNA (eDNA) is obtained from samples such as sediments, ice or water and can provide scientific sleuths with tantalizing clues about past and present biodiversity.

© BBC

© BBC

Smith et al. (2015) used sealed sediment cores to combine evidence from microgeomorphology, microfossils and sedimentary ancient DNA (sedaDNA) to reconstruct the biotic changes that occurred during the occupation of the present day Isle of Wight during the Mesolithic to Neolithic transition in which a hunter-gather economy was replaced by agriculture.

Sequence data is traditionally reliant upon discrete sources of material that has come from an individual plant or animal. But, individual plants and animals also leave behind extracellular DNA in the environment.

By using ancient DNA, Smith et al. (2015) detected DNA sequences associated with wheat as well as the proportion of these sequences in the plant profile increased as the soil samples were extracted from sedimentary layers closer to the present day.

As highlighted by Larson (2015), the methodology and results from studies like these are intriguing for arm-chair time traveling, but go beyond that in potentially challenging the chronology of historical events and tracing the dispersal of plants and animals.

References

 Larson G (2015) How wheat came to Britain. Science 347 (6225): 945-946

Pedersen MW (2015). Ancient and modern environmental DNA, Philosophical Transactions of the Royal Society B: Biological Sciences, 370 (1660) 20130383

Smith O et al. (2015) Sedimentary DNA from a submerged site reveals wheat in the British Isles 8000 years ago. Science 347 (6225): 998-1001

Posted in bioinformatics, domestication, genomics, natural history, next generation sequencing, Paleogenomics | Tagged , , , | Leave a comment

dN(eutralist) > dS(electionist)? Part 2

Last week’s post dealt with the debate over differences in the efficacy of purifying selection across human genomes. This week, we’ll look at the differences in de novo mutation rates across populations. The human de novo mutation rate has gone through a lot of recalibrations over the last few years (2.5 x 10-8 mutations per nucleotide per generation – Nachman and Crowell (2000) to 1.2 x 10-8 mutations per nucleotide per generation – Scally and Durbin (2012), Campbell et al. (2012), etc.), with plenty of variation with types of loci, male versus female germlines, and mutation types.

The de novo mutation rate is influenced by environmental changes resulting in DNA damage. The extent to which these de novo mutations arise, and are maintained in a population are also intertwined with (a) the population’s demography, and (b) the selection regimes at these mutated, and linked loci. A comprehensive study of de novo mutations (compared to the ancestral population) that are fixed (also called ‘private alleles’) in a population, but are still segregating in a third population should thus reveal the local dynamics of novel mutations.

harris

Overrepresentation of TCC->TTC within Europe, Figure 1 from Harris (2015) – http://dx.doi.org/10.1073/pnas.1418652112

Harris (2015) in a recent study of the variation in the frequencies of de novo mutations across the Phase 1 of the 1000 Genome Project data reports elevated mutation rates of a certain class (TCC->TTC) of non-synonymous substitutions in Europeans, when compared to Asians and Africans, which have often been linked to UV related damage. Noticeably, this also coincides with the evolution of lighter skin in Europeans after diversification outside of Africa, although no direct correlates (or positive selection for this class of mutations) between the two phenomena have been established or studied. In general, her results indicate (1) elevated C->T transitions in all Europeans, particularly in a class of TCC->TTC, (2) this ‘change’ in mutation rate occurred in the common ancestor of all Europeans, after divergence out of Africa, but prior to diversification inside Europe, around 25,000-60,000 ybp, (3) the non-bioinformatic (i.e. not due to erroneous detection methods) cause of this observation, and (4) a bias in transcription-coupled repair mechanism in “correcting” this class of mutations in European populations.

Some interesting questions arise as a consequence of these results, which feed well into our continuing debate about the dynamics of novel mutations.

  • Seeing that the (1) elevated levels of TCC->TTC mutations in Europeans occurred as a result of some environmental change (here excessive UV damage), (2) there is a bias in the transcription-coupled repair mechanism in correcting these mutations in Europeans, and (3) that these mutations are fixed in the population, one would surmise that this is a definitive consequence of the demography on European populations?
  • The observation that there isn’t any difference in the efficacy of purifying selection across Europeans, and Asians (as reported by Do et al. (2015)), is conditional on the same mutation rate across Europeans and Asians, which as Harris reports, isn’t true across all classes of loci. So perhaps demography (say a population bottleneck, or expansion) did play a role in the efficacy of purifying selection after all?

Feel free to add your comments!

References:

Harris, K. Evidence for recent, population-specific evolution of the human mutation rate, Proceedings of the National Academy of Sciences, DOI:http://dx.doi.org/10.1073/pnas.1418652112

Posted in evolution, mutation, theory | Tagged , , , | Leave a comment

Toying with eigenvectors

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There are few things I enjoy more than when someone takes the time to clearly communicate a complex idea. The whole “you don’t know it until you teach it” phenomenon gives me the utmost respect for those who put effort into bridging the gap to us non-experts. Oftentimes, the clearest way to communicate something complex is visually, and I want to share a cool example with you:

Eigenvectors and eigenvalues: explained visually by Victor Powell and Lewis Lehe

We use eigenvector-based linear algebra for a multitude of analyses in molecular ecology, from the types of clustering analyses offered by adegenet (PCA, CCA, DPCA, YMCA?, ASPCA?) to the estimation of phylogenetic signal. If you stared as hopelessly as I did at the chalk board during undergraduate math courses, learning what the heck an eigenvalue is could have been an uphill battle. If only I would have had these arrows to move around!

Bonus: you can also check out modules on Principal Components and Markov Chains! I know you can’t resist a good Markov Chain.

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Behavioral individuality reveals genetic control of phenotypic variability

High-throughput measure of drosophila "handedness" ; from Buchanan et al (2014), doi:10.1101/008565;

High-throughput measure of drosophila “handedness”. From Buchanan et al (2014), doi:10.1101/008565

Studies of animal personality (or, “behavioral syndromes”, if you choose your words carefully) are so hot right now. One of the assumptions of such studies is that natural selection has somehow favored this behavioral variability/plasticity (and not just differences in means across genotypes). To date, however, no studies have shown a genetic basis underlying such intragenotypic phenotypic variability. Well, no studies until now… Continue reading

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