07/7/19

Summer 2019 conferences

Conference season is in full swing and the Aitken lab is travelling near and far to share what we’ve been up to.

Here’s a list of recent and upcoming conference talks by lab members and associates.

Evolution June 21-25

Combining exome capture and pool-seq: Lessons from three conifer species. Brandon Lind.

Evolution of phenology along elevation gradients: insights from different modeling approaches. Ophélie Ronce, Isabelle Chuine, Julie Gauzere, Sylvain Delzon, Luis-Miguel Chevin

Western Forest Genetics Association Conference June 24-26

Phenotypic and genomic patterns of climate adaptation in western larch to assess assisted migration strategies with climate change. Beth Roskilly, Brandon Lind, Mengmeng Lu, Sam Yeaman, Sally N. Aitken

A forest of information: Comparing phenotypic, genomic and climatic data for managing climate adaptation. Colin R. Mahony, Ian R. MacLachlan, Brandon M. Lind, Jeremy B. Yoder, Tongli Wang, Sally N. Aitken

SMBE July 21-25

Patterns of genetic diversity around protein-coding exons and conserved non-coding elements are explained by strong selective sweeps in mice. Tom Booker. Poster session.

Canadian Forest Genetics Association Conference Aug 19-23
Does local adaptation to drought need to be considered in assisted gene flow strategies for Douglas-fir reforestation? Rafael Candido Ribeiro. August 20 5pm poster session.

IUFRO World Congress Sep 29 – Oct 5

Does local adaptation to drought need to be considered in assisted gene flow strategies for Douglas-fir reforestation? Rafael Candido Ribeiro. In session “B2a Trees on the move: range shifts, potential for genetic adaptation and assisted migration”

02/14/19

What will your city be like in 60 years?

When Colin started publishing his papers on calculating climate similarity and novel climates, we wished for

 a tool that lets me plug in coordinates, a year and an emissions scenario and get a map of climate analogs and their associated ecosystems.

Looks like someone else was reading Colin’s papers and thinking along the same lines!

This week, Fitzpatrick and Dunn published an online map that lets you look at cities and their future climate analogues and along with a paper in Nature using the sigma dissimilarity metric that Colin et. al developed.

Be sure to turn on the climate similarity map option when you use Fitzpatrick and Dunn’s tool – it’ll show you how analogous the closest analogue city really is! Seattle is Vancouver’s closest analogue, but it’s not a good one. You’ll have to read this paper by Colin et al. on novel climates in BC forests to find out why!

03/7/18

The Homebrew Series: Inferring demographic history with ABC, by Joane Elleouet and Sally Aitken

Want to know about the history of the populations you’re studying? Joane Elleouet and Sally Aitken see how far Approximate Bayesian Computation (ABC) and your sequencing method of choice can take you in a new paper in Molecular Ecology Resources.

20 years ago, Tavaré et al. used ABC to estimate that the time to coalescence for the human population based on the Y chromosome was about 157,300 years ago (but!) and evolutionary biologists were off to the races. Now ABC is a common tool in the field with many software implementations to choose from. A lot else has happened in the last 20 years – like huge advances in genotyping technology. Even for non-model species, we can now get lots of genomic data for cheaper than ever using reduced representation library sequencing methods like genotyping-by-sequencing and GBS.

But how well does ABC perform with RRL data and different demographic models? What are its limitations? How do you make the best choices for your sequencing efforts? To answer these questions, Jo simulated data sets for 4 kinds of demographic models and 5 types of sequencing efforts and performed ABC on those datasets. She compared different model’s performance with

  • phased and unphased data, (phasing doesn’t help)
  • data from lots of short reads vs fewer, longer sequences (lots of short reads just as good)
  • different times since colonization, (depends on parameter value and demographic model)
  • tradeoffs between number and individuals and sampling depth at different sequencing error rates, (go for more individuals over depth)
  • and compared ABC to an SFS method. (similar)

As far as the different demographic models they consider, they find that ABC can be used with data from reduced representation library sequencing methods to precisely infer very simple demographic models, but not complex ones.

Here’s what Aitken Lab members had to say after reading the paper:

What’s your takeaway from this paper?

Reader 1: This paper provides several rules of thumb for inferring demographic events from incomplete, fragmented genomic data. Demographic models should be kept as simple as possible, and numerous short sequences from many individuals is preferable to fewer long sequences from a small sample of the population.

Reader 2: You’d better know what kind of demographic history your population has before you start trying to estimate parameters!

Reader 3: Estimating demographic parameters with ABC has limitations even with very simple demographic models

What’s the coolest thing about this paper?

R1: Improving techniques to infer the ancient demographic history of any species you like, not just model species.

R2: I didn’t realize how hard inferring demographic history is, even with so much genomic data. The extensive simulations are really impressive and convincing.

R3: Adding a realistic component by testing the effect of sequencing depth and error

What questions are you left with after reading this paper?

R2: How often do researchers know the “right” model of demographic history to try to infer? Whether or not to include migration or how many populations there have been? How do people figure this out?

R3: What if summary statistics lead to a too drastic loss of data? is there a better way to summarize the data while keeping crucial information?

 

08/23/16

Aitken and collaborators talking to the Verge about climate change and forests

Whitebark pines are majestic trees with a whitish, often wind-curled trunk that grow up high in the Rocky and Sierra Mountains, in the Western US. They’re icons of Yellowstone National Park, where they provide high-calorie seeds for many animals, including grizzly bears that eat the seeds before hibernating. Some whitebark pines manage to live for a thousand years, but many of them are now dying.

Source: Uprooted: how climate change may kick off an artificial migration of trees | The Verge