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The Tria Project: Genomics of the Mountain Pine Beetle System
1. The Tria Project: Genomics of the
Mountain Pine Beetle System
Janice Cooke
and the Tria Consortium
2. Outline
State of the mountain pine beetle outbreak: context for
using a genomics approach in combatting the epidemic
Introduction to the Tria Project and the Tria Team
Key outcomes from the Tria Project to date
Filling knowledge gaps and making discoveries
Linking genomics and risk assessment
Using genomics to inform policy makers and forest
managers
Perspectives and future directions
3. Unprecedented spread of mountain pine beetle
during the current outbreak
10 µm
10 µm
Adrianne Rice
Jack Scott, University of Alberta
4. Unprecedented spread of mountain pine beetle
during the current outbreak
Data: Little (1971); S.
Taylor, G. Thandi, D.
Yemshinov (Canadian
Forest Service)
5. The Tria Project:
A large-scale multidisciplinary collaborative effort
MPB vector
How gene Genetic variation
products work across landscapes
Jack Scott
Physiological Stakeholders
Population
& Functional & End Users
Genomics
Genomics
Policy
Genomic Environmental
Pine Fungal development;
Resources & Economic Forest
host pathogen
Risk Models management
and spread
control
programme
Ecology planning
Janice Cooke Adrianne Rice
How organisms function &
interact in nature
6. The Tria Project:
A large-scale multidisciplinary collaborative effort
University of Alberta
University of British Columbia
University of Northern British Columbia
Natural Resources Canada – Canadian Forest Service
Michael Smith Genome Sciences Centre – BC Cancer Agency
University of Minnesota
7. Genomic resources
Bohlmann, Breuil, J
Re
Cooke, Hamelin, Huber, Jones, Keeling,
Murray, Sperling
UBC, UNBC, UA, BCGSC
Functional & Population Ecosystem Risk
physiological genomics ecology modeling, monit
genomics oring &
Sperling, assessment Stakeholders
Mountain Huber, Keeling Erbilgin,
Coltman, and Endusers
pine Bohlmann Evenden
Murray
beetle UNBC, UBC B. Cooke, Policy
UA, UNBC UA, UBC
Aukema, development;
Hauer, Forest
Breuil, Hamelin, Sper Breuil, K Lewis Lewis management
Fungal Bohlmann ling J. Cooke,
Erbilgin and spread
associates
UA, CFS, control
UBC UBC, UA UBC, UNBC, UA
UMinn programme
planning
J Cooke, Coltman, Erbilgin,
Pines Bohlmann J Cooke K Lewis
UA, UBC UA UA, UBC
Huber, Breuil, Coltman, Erbilgin,
J Cooke, Sperling, Evenden
Interactions
Bohlmann Hamelin
UNBC, UBC, UA UA, UNBC UA, UBC
8. Genomes and Genomic Resources
Chromosomes
Genetic linkage map (relative positions
of gene-based or anonymous markers)
Genome sequence
Expressed gene sequences
…AAGAGAGCCTGTCGCTAAATGCAAGCCTTGAGTACC…
(Adapted from Paul & Ferl, 2000)
9. Sequence data enables high-throughput analyses of
many genes and/or many individuals simultaneously
Physiological genomics: monitoring
large numbers of genes simultaneously
for gene activity levels
10. Sequence data enables high-throughput analyses of
many genes and/or many individuals simultaneously
Population genomics: assessing
genetic variation in large numbers
of individuals simultaneously
Gene Markers
A B C … n
A/A A/G G/G 1
Individuals
2
3
…
n
11. Tria-Generated Genomic Resources
Mountain Fungal spp. Pines – lodgepole
Pine Beetle and jack pine
Mountain Pine Beetle
Whole genome Draft High-quality reference plus No
sequence Draft whole genome sequence
additional strains (G.
clavigera); Draft (O. piceae)
Expressed gene sequences
Jack Scott
Expressed gene Yes Yes (G. clavigera, O. piceae) Yes
sequences Expressed gene sequence clones
Expressed gene Microsatellite markers
Yes Yes (G. clavigera) Yes
sequence clones
Single nucleotide polymorphism gene markers
Microsatellite markers
Adrianne Rice
Yes Yes – multiple spp. Yes
Protein “fingerprints”
Single nucleotide Yes Yes – multiple spp. Yes
polymorphism gene
markers
Protein “fingerprints” Yes No No
High-throughput gene
Janice Cooke Ref-Seq Ref-Seq Microarrays
expression tools
13. Lodgepole and jack pine can be difficult to tell from
hybrids, and the hybrid zone was not well-defined
Catherine Cullingham, University of Alberta
14. Using molecular markers to distinguish
lodgepole pine, jack pine and their hybrids
Lodgepole pine
Jack pine
Hybrid
Catherine Cullingham, University of Alberta
15. Pine marker analyses revealed mountain pine
beetle range expansion into jack pine
Catherine Cullingham, University of Alberta
16. Bringing a regional issue to national significance
Data: Little (1971), D. Yemshinov (Canadian Forest Service)
Catherine Cullingham, University of Alberta
17. Defenses differ in lodgepole and jack pine,
and are further altered by drought
Janice Cooke Alberta Sustainable Resources Development Adriana Arango
18. At least some mountain pine beetle fungal
associates can detoxify pine defense compounds
10 µm
http://flickr.com/photos/19964825@N00/2495786445/
10 µm
Adrianne Rice
19. Genetic analyses provided strong evidence of beetle
dispersal from northern BC into northwestern AB
Beetles can
migrate
longer
distances
than
previously
supposed
Samarasekara et al 2012
20. Beetles in novel habitats:
are they becoming more cold tolerant?
Frequency
5%
Selection
(cold winter
temperatures)
Frequency
20%
Cullingham and Janes, unpublished
21. Pines, beetle and fungal associates all show
genetic variation across the landscape
Geographic Ecoregions
Genetic variation features
24. Perspectives
The current MPB outbreak has provided excellent proof of
concept for application of genomics to forest pest management.
MPB, fungal and pine populations are heterogeneous
This landscape-level non-uniformity could affect
MPB spread
Genomics is already informing Risk Assessment
Risk Assessment and risk models also inform
genetics research by identifying knowledge gaps
Genomics is already informing Tree Improvement
Other possibilities for applying genetics to
reforestation and genetic conservation strategies
25. Mountain pine beetle at the leading edge of the
outbreak: new surprises at every turn
Lorraine Maclauchlan, BC Ministry of Forests and Range Rory McIntosh, Saskatchewan Environment
26. Mountain pine beetle at the leading edge of the
outbreak: new surprises at every turn
27. Future Research Needs
East of the Rockies, why isn’t the outbreak unfolding as models
predicted in the mid 2000s? Will the outbreak reach Ontario?
If so, when?
Genomics-enhanced risk models
How much does genetic variation in mountain pine beetle,
pine host and fungal pathogen matter in outbreak dynamics?
Integrated genomic landscape mapping
We are only just beginning to understand how the players in
the mountain pine beetle system interact, and how these
interactions might affect outbreak dynamics
Functional and physiological genomics investigations
have provided novel insights
28. Future Research Needs
Continued integration of mountain pine beetle research
across disciplines and across scales
Complex problems require holistic approaches
Genomics enables integration
29. Postdocs / Research Associates Research Technicians
Eri Adams Neils Jensen Sean Bromilow
Jay Anderson Ljerka Lah Jeremiah Bolstad
Adriana Arango Inka Lusebrink Stephanie Beauseigle
Project Leaders Celia Boone Mario Pineda-Krch Tiffany Bonnet
Janice Cooke (U of A) Catherine Cullingham Isidro Ojeda Marie Bourassa
Walid El Kayal Caitlin Pitt Stephanie Boychuk
Jörg Bohlmann (UBC) Katrin Geisler Adrianne Rice William Clark
Dawn Hall Jeanne Robert Amanda Cookhouse
Sajeet Haridas Amanda Roe Pat Crane
Co-Investigators Uljana Hesse Kishan Sambaraju Sophie Dang
Brian Aukema (U Minn) Kate Hrinkevich Amy Thommasen Christina Elliot
Patrick James Clement Tsui Harpreet Dullat
Colette Breuil (UBC) Jasmine Janes Ye Wang Matt Ferguson
David Coltman (U of A) Joël Fillon
Barry Cooke (CFS) Graduate Students Leonardo Galindo
Sepideh Alamouti Hannah Henderson
Nadir Erbilgin (U of A) Lina Farfan
Nic Bartell Ed Hunt
Jordie Fraser
Maya Evenden (U of A) Christine Chui Chris Hansen
Robert Jagodzinski
Erin Clark Brad Jones
Richard Hamelin (CFS) Lily Khadempour
Chelsea Ju
Scott DiGuistini Euwing Teen
Grant Hauer (U of A) Honey-Marie de la Giroday Ye Wang
Laura Kennedy
Robert Holt (GSC) Susanne King-Jones
Gayathri Weerasuriya
Chris Konchalski
Dezene Huber (UNBC) Jordan Koopmans
Undergraduate Students
Steven Jones (GSC) Simon Allard Jean Linsky
Ben Lai
Maria Li
Christopher Keeling (UBC) Travis Allen Rosalyn Loerke Yisu Li
Marco Marra (GSC) Kyle Artym Fang Yuan Luo Emilia Lim
Kathryn Berry Mehvash Malik Linette Lim
Brent Murray (UNBC) Simren Brar Sophia McClair Miranda Meents
Felix Sperling (U of A) Huang-Ju Chen Genny Michiel Dominik Royko
Tiffany Clarke Rhiannon
Tim Williamson (CFS) Charles Copeland Montgomery
Harpreet Sandhu
Bin Shan
Julia Dam Marcelo Mora Andrea Singh
Shane Doddridge Boyd Mori Bill Sperling
Project Management Patrick Gaudet Mike Prior Talya Truant
Matthew Bryman (U of A) Andrew Ho Ting Pu Tyler Watson
Cierra Hoecher Andrew Sharp Caroline Whitehouse
Karen Reid (UBC) Byron Knoll Patrick Welsh Mack Yuen
Siew Law Christina Wong
Notes de l'éditeur
Spatially delinate adaptive variation on the landscape (associating selected loci with variables, application to other aspects of forest management