Method summary: Mapping genetic patterns across landscapes with PHYLIN

            The spatial representation of species’ data is needed in most areas of biodiversity related research. In fact, mapping the species’ continuum to guide the prioritization of areas for conservation was the main driver for PHYLIN development, but the possible application is far more vast.

            Spatial representation of distances between georeferenced samples is challenging. The PHYLIN input are distance matrices and a table of samples classified in groups (lineages, for instance) with locations. PHYLIN relates a matrix measuring a particular distance between samples (for example, a genetic distance) with a matrix representing spatial distance between the same samples. PHYLIN then applies a kriging interpolation: models the relation by means of a variogram and uses that information as weights to interpolate to other locations a probability of belonging to each of the groups

Different applications of PHYLIN with randomly generated data. a) using a simple euclidean distance with 3 dimensions is possible to interpolate over 3d environments; b) using a layer of climate as resistance to movement it is possible to analyse the impact of climate change on connectivity; c) using a Jaccard distance matrix instead of genetic distance to map the contact zone between two species (click on the image for source code).

The latest version of PHYLIN adds the possibility of using multiple spatial distance metrics, opening an exciting avenue with different applications. In our recent paper in Molecular Ecology Resources, we showed how different mechanisms of genetic isolation can be represented in space by PHYLIN. The application of the method is not limited to that and we show here three other possible applications: using 3 dimensional distance (similarly to an ocean environment), climate change connectivity and species distributions/contact zone.

Pedro Tarroso, Guillermo Velo-Antón and Silvia Carvalho  

See the full paper here: https://onlinelibrary.wiley.com/doi/abs/10.1111/1755-0998.13010

A step by step tutorial can be found here: https://cran.r-project.org/web/packages/phylin/vignettes/phylin_tutorial.pdf

Using transcriptomics to investigate the Circadian clock

Circadian clocks provide a mechanism that allows organisms to anticipate environmental rhythms, like light-dark cycles. Nematostella vectensis, an estuarine sea anemone, has a surprising degree of overlap in genomic complexity with vertebrates, including circadian clock genes. These genes are predicted to serve a similar role in driving circadian patterns in sea anemones, but we have not worked out the exact mechanism they use.

Photo courtesy of Whitney Leach

In this study, we utilize next-generation sequencing to investigate the time-course transcriptional profiles of animals over 3 days, to dissociate true circadian gene expression vs. photo-responsiveness, by exposing animals to regular light-dark cycles for one month, then abruptly removing the light cue. Hypothesized ‘clock’ genes were rhythmic in the presence of light-dark cycles; however, several of these genes lost their characteristic oscillation after 1 or 2 days in the dark, suggesting lack of endogenous circadian regulation. One would expect a truly circadian gene to continue to cycle in the absence of light, however our results indicate either: 1) the hypothesized ‘clock’ genes simply respond directly to light cues, which implies they are not circadian, or 2) a circadian regulator resides in specific cell types, and the expression signal is too dampened when measuring in the whole animal.

Whitney Leach, Doctoral Candidate, The Reitzel Laboratory, University of North Carolina at Charlotte

Read the full article here: https://onlinelibrary.wiley.com/doi/abs/10.1111/mec.15163