Not everyone likes it hot … winter or not

On this Boxing Day, many of us may be bracing against winter storms.  For those of us in the Northern Hemisphere, we might all be dreaming of summer weather (including those of us who think a Southern Californian version of winter downright chilly). Blissful summer months of fieldwork which are seemingly filled with ample time to dust off that old dataset or manuscript …
Yet, as we see in a new paper, not everybody likes it hot.
Mota et al. (2014) have described the relationship between the thermal environment and in situ molecular heat shock response (HSR) is investigated at microhabitat scales.  Usually, we study environmental change over large temporal and/or geographical scales.  Yet, microhabitat thermal conditions may be just as important.
Four distinct patches are described in the intertidal fucoid Fucus vesiculosus from a southern range edge population: canopy surface, patch edge, subcanopy and submerged channels. These four patches, or microhabitats, had distinct thermal and water stress profiles during low tide emersion.  And, in fact, the range edge population studied has become extinct.

An intertidal site with patches of fucoids, or rockweeds, at low tide in Brittany, France. © SA Krueger-Hadfield, 2010

An intertidal site with patches of fucoids at low tide. © SA Krueger-Hadfield, 2010


Perhaps surprisingly, the top of the canopy, which is the hottest and driest patch, was the most benign for this species of fucoid. Rapid desiccation may result in a metabolically inactive state in which fronds can’t respond to thermal stress and are thereby protected.
HSR data, accompanied by meteorological and microenvironmental thermal data, indicated that the maximum HSR is met or exceeded at low tides over much of there year, even during daytime immersion in summer. This is critical, as it will prevent fucoids from recovering from thermal stress due to continual HSR even at high tide.
The other important result from this study indicated that microhabitat scales in intertidal zones might best explain the impact of climatic changes.
Mota CF, Engelen AH, Serrão EA, Pearson GA (2014) Some don’t like it hot: microhabitat-dependent thermal and water stresses in a trailing edge population.  Functional Ecology DOI: 10.1111/1365-2435.12373

Posted in adaptation, natural history | Leave a comment

The best of TME (for the last two months)

I’ll admit that I’m a sucker for year-end lists. Ten biggest science discoveries. Fifty best albums of 2014. They make fantastic procrastination fodder, and I’ll comb through each one that crosses my desktop before the New Year.
In the same spirit, I wanted to take a quick reflective look at the past couple months here at The Molecular Ecologist. We are already a third of the way through the tenure of our new influx of contributors (me included), and it might be informative to look at trends in what this diverse group is talking about and think about where the readers of TME would like to see us go in the immediate future.
Since the beginning of November, the new contributors (Arun, Karen, Melissa, Noah, Rob, and Stacy) have authored 36 posts (19,536 words!). Each post averages around 500 words, and is shared on Facebook 37.2 times and gets Tweeted 12.4 times. Speaking of social media, the social media impact awards go to:
Continue reading

Posted in blogging, community | 1 Comment

Rejection, Academics, and Success.

source: http://athleticpoetics.tumblr.com/


With the holiday season in full swing, I thought that I share a link to a recent post on weathering the rejection storm that almost invariably accompanies grant and publication reviews.

those of you getting rejections are in great company. We’re slogging through a historically lean time and this shit is just hard right now.

As a young academic I’ve received my fair share of rejection emails, so these “we’re all in the same boat” posts certainly ease my mind. On top of that, they also provide some valuable advice: The path to success is paved with grit and persistence.

The ONLY reason I’ve been semi-successful is because I got back up every. damn. time. I don’t have better ideas than my colleagues. I’m not smarter than they are. I don’t have the pedigree or awards many of them have. But it turns out I can take a punch pretty well.

I think the great Maury Ballstein said it best:

from: Zoolander


Happy Holidays.

Posted in Uncategorized | Leave a comment

haploidy, diploidy, polyploidy … not a problem

Investigating pairwise relatedness is fundamental to the characterization of the mating system and inferring genetic structure. If no pedigree exists, then relatedness is estimated from genetic markers (e.g., microsatellite loci) using method-of-moment or maximum-likelihood methods.
However, not all individuals in a population have the same ploidy. In ferns, mosses and some seaweeds, haploid gametophytes alternate with diploid sporophytes. In some insect orders, such as the Hymenoptera, haploid males develop from unfertilized eggs. Thus, individuals may be related, but have differing levels of ploidy. Though many estimators exist for diploid organisms, no estimators exist for organisms with multiple ploidy levels.

Cape honey beesat a feeding station. Photograph by Anthony Vaudo, University of Florida

Cape honey bees at a feeding station. Photograph by Anthony Vaudo, University of Florida


That was until the software package recently published online by Huang et al. in Molecular Ecology Resources. Here, a relatedness coefficient, a maximum-likelihood and three coefficient of coancestry estimators are extended to enable the calculation of relatedness coefficients using co-dominant markers between individuals differing in ploidy.
The simulations and comparisons presented should help with the selection of the appropriate estimator for a given question or application.
Estimating pairwise relatedness between individuals with different ploidies will significantly advance our understanding of mating systems and the structuring of populations of organisms with complex life cycles.
Huang K, Ritland K, Guo S, Dunn DW, Chen D, Ren Y, Qi X, Zhang P, He G and Li B (2014, accepted) Estimating pairwise relatedness between individuals with differing levels of ploidy.  Molecular Ecology Resources DOI: 10.1111/1755-0998.12351

Posted in natural history, pedigree, population genetics, software, Uncategorized | Leave a comment

Sweeping for Sweeps

Reduction in genomic diversity around a site has been attributed to one of two mechanisms – (1) sites linked to positively selected mutant alleles are often `swept’ to fixation, in a process often called genetic hitchhiking, and/or (2) background selection at sites linked to deleterious mutants are purged (or purified). Recent selective sweeps are thus characterized by long sequences of homozygous sites, and reduced linkage disequilibrium. Ancient sweeps on the other hand, are difficult to characterize – with several methods being proposed to detect them, often using scaled (with respect to a common ancestor) haplotype diversity, Tajima’s D, number of segregating sites, etc  – see Enard et al. (2014) for an excellent recap.
Two recent studies that analyzed human genomes for ancient and recent recurrent selective sweeps revealed some very interesting results.

Quidditch, anyone?


Racimo et al. (2014) propose a method based on ABC (Approximate Bayesian Computation) to detect ancestral selective sweeps that occurred soon after the split of humans and Neanderthals, and apply it to 26 phased human genomes from the 1000 Genomes Project. Scaled diversity (and other statistics) estimated in 0.02 cM windows around non-synonymous mutations, splice sites, 5’ UTR’s, regulatory motif changes show (1) no significant differences in signatures of positive selection between synonymous and non-synonymous sites, 5’ UTR’s, or regulatory motifs, but (2) significantly reduced differences in diversity in splice sites, and (3) failure of sites in favor of positive selection to lie in regions introgressed from Neanderthals.
Dutheil et al. (2014) take a different approach – they analyze regions of the genome (here X chromosome) that show signatures of Incomplete Lineage Sorting (ILS) – i.e. lower divergence, while reconstructing population histories. Low ILS regions thus would be expected to be either under strong background selection, or have experienced strong selective sweeps. Their analyses of reduction in genomic diversity at low-ILS sites from the 1000 genomes data on the X chromosome reveal (1) greater reduction in genomic diversity in non-African X chromosomes, compared to African X chromosomes, and (2) sites with low-ILS, and reduced genomic diversity do not lie in regions introgressed from Neanderthals.
Two studies, similar conclusions, leading into more questions about complex speciation in great apes. A classic clash of brooms. Quidditch, anyone?
References:
Dutheil, Julien Y., et al. “Strong selection in the human-chimpanzee ancestor links the X chromosome to speciation.” bioRxiv (2014): 011601. http://dx.doi.org/10.1101/011601
Enard, David, Philipp W. Messer, and Dmitri A. Petrov. “Genome-wide signals of positive selection in human evolution.” Genome research (2014). http://dx.doi.org/10.1101/gr.164822.113
Racimo, Fernando, Martin Kuhlwilm, and Montgomery Slatkin. “A test for ancient selective sweeps and an application to candidate sites in modern humans.” Molecular biology and evolution 31.12 (2014): 3344-3358. http://dx.doi.org/10.1093/molbev/msu255
 
 

Posted in Uncategorized | 2 Comments

A molecular how-to for hibernating this winter


As the academic semester ends, I see the tell-tale signs of the upcoming holiday hibernation. The weary eyes of teaching assistants peeking over piles of final exams. Students who may have mentally been on break before finals even started. A little more pep in the faculty step (finally some time for that NSF proposal!).
Upon return to campus after the new year, most are refreshed and excited for a new semester. However, others will return in a slightly, well, degraded state: slowed by the excess of holiday nourishment and mentally lulled by an embarrassingly lengthy Netflix binge.
No matter what group you fall into, take a look at this new paper from Dr. Vadim Federov and colleagues that describes how some of our fellow mammals actually hibernate while still keeping themselves in shape.

In humans and most mammals, physical inactivity leads to loss of muscle strength and mass. In contrast, hibernating bears and ground squirrels demonstrate very limited muscle atrophy over the prolonged periods (6–8 months) of physical inactivity of winter hibernation, suggesting that hibernating mammals have evolved natural mechanisms that prevent disuse muscle atrophy.

Two hypotheses for how these mammals carry out this feat have been proposed. Either a) genes that build proteins are upregulated during hibernation or b) genes that are responsible for breaking down muscle tissue are downregulated during hibernation.
By measuring the expression levels of a host of functional genes from black bears and arctic ground squirrels that were either in the process or hibernation or not, Federov and his colleagues show that the role of genes that increase protein biosynthesis is more pronounced in animals that are hibernating compared to those that aren’t.
At the same time, they found no changes in pathways that result in the catabolism of proteins, indicating little influence of genes that prevent the breakdown of muscle tissue.

These findings imply reduction in amino acid catabolism and suggest, besides possible urea recycling, redirection of amino acids from catabolic pathways to the enhancement of protein biosynthesis.

If only this was applicable to humans. Goodbye hustle and bustle. Hello to sweet, sedentary life.
 
Fedorov V.B., Nathan C. Stewart, Øivind Tøien, Celia Chang, Haifang Wang, Jun Yan, Louise C. Showe, Michael K. Showe & Brian M. Barnes (2014). Comparative functional genomics of adaptation to muscular disuse in hibernating mammals, Molecular Ecology, 23 (22) 5524-5537. DOI: http://dx.doi.org/10.1111/mec.12963

Posted in association genetics, Molecular Ecology, the journal, quantitative genetics, Uncategorized | Tagged , , | Leave a comment

This post is for the birds

Paintings of mourning doves (left) and a flamingo (right) by John Audubon

Paintings of mourning doves (left) and a flamingo (right) by John Audubon


Note: this post was has been corrected to reflect the fact that Flamingoes and Pigeons are not sister species, but members of sister clades.
Darwin’s favorite bird, the pigeon, has a new sister (clade) that includes Flamingoes and Grebes. This somewhat surprising result came from a recent phylogenomic analysis of 48 bird species published last week in Science. This analysis and its 27 companion papers were the culmination of years of work conducted by the Avian Phylogenomics Project, which is led by Erich Jarvis, a Professor of Neurobiology at Duke University, Guojie Zhang of the National Genebank at BGI in China and the University of Copenhagen, and M. Thomas P. Gilbert of Natural History Museum of Denmark.
In this post I take you on a supervised speed date with 12 of the 28 papers:
Continue reading

Posted in Uncategorized | 3 Comments

LSUMNS researchers are at the top of the list for new species discoveries in 2014

2014 was an exciting year for describing new biodiversity for researchers at the Louisiana State University Museum of Natural Science (LSUMNS). Top ten lists are ubiquitous this time of year and two such lists documenting the top new species of 2014 include taxa described by LSU researchers.
A list compiled by Discover Magazine includes a new fish species described by Prosanta Chakrabarty and colleagues and a new rat species described by Jake Esselstyn and colleagues.
The Hoosier Cavefish Amblyopsis hoosieri, the first new cavefish species described from the United States in the last 40 years, is found in subterranean habitats of southern Indiana. Amblyopsis hoosieri is distinct from its congener A. spelaea based on morphological and molecular characters. The Ohio River appears to act as a barrier for these two species with A. hoosieri distributed to the north of the river and A. spelaea to the south.

The Hoosier Cavefish Amblyopsis hoosieri. Photo by M.L. Niemiller.

The Hoosier Cavefish Amblyopsis hoosieri. Photo by M.L. Niemiller


Continue reading

Posted in Uncategorized | Leave a comment

Totally RAD

Puritz et al. (2014) weigh the pros and cons of, the aptly titled, “RAD fad” in a comment recently published online in Molecular Ecology. They challenge:

(1) the assertion that the original RAD protocol minimizes the impact of PCR artifacts relative to that of other RAD protocols, (2) present additional biases in RADseq that are at least as important as PCR artifacts in selecting a RAD protocol, and (3) highlight the strengths and weaknesses of four different approaches to RADseq which are a representative sample of all RAD variants.

Artwork courtesy of chrispiascik.com © Chris Piascik

Artwork courtesy of chrispiascik.com
© Chris Piascik


In Box 1, the authors break down four representative protocols: mbRAD (Miller et al. 2007, Baird et al. 2008), ddRAD (Peterson et al. 2012), ezRAD (Toonen et al. 2013) and 2bRAD (Wang et al. 2012).
Then, the mitigation of PCR artifacts is discussed followed by a summary of the pros and cons of each of the four representative RAD protocols.

The most important consideration when selecting a particular RAD protocol are the facilities and molecular experience of the research applying the approach, as well as the biology of the organisms and the hypotheses being tested … at present, there is no reason to broad-brush paint any method as the superior or default protocol.

 
Miller MR, Dunham JP, Amores A, et al. (2007) Rapid and cost-effective polymorphism identification and genotyping using restriction site associated DNA (RAD) markers.  Genome Research 17: 240-248. doi: 10.1101/gr.5681207
Baird NA, Etter PD, Atwood TS et al. (2008) Rapid SNP discovery and genetic mapping using sequenced RAD markers. PloS ONE, 3, e3376. DOI: 10.1371/journal.pone.0003376
Peterson BK, Weber JN, Kay EH, et al. (2012) Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PloS One, 7, e37135. DOI: 10.1371/journal.pone.0037135
Wang S, Meyer E, McKay JK, et al. (2012) 2b-RAD: a simple and flexible method for genomewide genotyping. Nature methods, 9, 808–10. doi:10.1038/nmeth.2023
Toonen RJ, Puritz JB, Forsman ZH et al. (2013) ezRAD: a simplified method for genomic genotyping in non-model organisms. PeerJ, 1, e203. DOI 10.7717/peerj.203
Andrews, KR, G Luikart (2014) Recent novel approaches for population genomic data analysis. Molecular Ecology 23: 1661-1667. DOI: 10.1111/mec.12686
Puritz, JB, MV Matz, RJ Toonen, JN Weber, DI Bolnck, CE Bird (2014, accepted article) Comment: Demystifying the RAD fad. Molecular Ecology. DOI: 10.1111/mec.12965

Posted in bioinformatics, genomics, methods, next generation sequencing, Uncategorized | 4 Comments

Migration Circos plots in R

We’ve all seen them – colorful, and I daresay, pretty darn informative. Circos plots are fun visualizations of large data-sets. I’ve seen them used in two contexts in comparative genomics – to represent structural variants in homologous chromosome segments in species alignments, and to perhaps represent gene-gene interactions. But there are scores of other interesting applications of these plots to scientific data, a comprehensive list (and yet growing) can be seen here.

circos
Circos plot of source-sink migration dynamics between populations “3” and “4” here, with 8 other populations. Width of migration curves indicates amount of migration.

A relatively recent publication by Abel and Sander (2014) in Science on using Circos plots to represent migration prompted me to explore the migest package in R. Scores of studies in molecular ecology and population genetics utilize methods to estimate ancestral or contemporary migration routes between populations, such as MIGRATE-N, IM/IMa2, IMMANC, BayesAss, etc. I am yet to see a migration visualization that comprehensively describes complex migration routes between populations in pop-gen studies. So putting these two together, I thought I’d use migration estimates from one of the above tools, and represent it as a Circos plot. I am going to skip a few steps in creating the data files required to make these plots, but I refer you to some excellent documentation by Guy Abel.

Continue reading
Posted in bioinformatics, genomics, howto, R, software | Tagged , | 11 Comments