1. Association genetics in forest trees
Santiago C. González-Martínez Center of Forest Research, INIA, PO Box Madrid, Spain

2. What is association genetics?

3. Linkage versus Association: finding the molecular variation underlying complex traits
A favourable mutation
several generations X X LG
Mapping pedigree
Natural population (= multiple genetic backgrounds)

4. For which organisms genetic association is a promising approach?
Relatively undomesticated species with outbred mating systems and large natural populations.
Organisms with long life-spam, where generating pedigrees would take several years.
Organisms (such as humans) where artificial crosses are not possible or are difficult to obtain (incompatible species).
In plants: opportunity to test for genetic association of multiple traits and phenotypes: long-term common garden experiments (including clonal tests  high precision in the estimation of phenotypes).
The ‘immortal’ association population

5. Linkage disequilibrium and association
Heuertz et al. 2006
Genetics c)
Rapid decay of LD in conifers, but LD might be stronger in regions under selection (example: LD extends over 800 kb around Y1 gene in maize, Palaisa et al. 2004, which in general shows also a rapid decay of LD with physical distance, Remington et al. 2001)
Stumpf & McVean (2003)
Nature Reviews Genetics

6. Nature Reviews Genetics
Extend of LD and association: higher LD makes easier to detect associations but more difficult to identify the causal mutations
Variation among species
conifers
humans
Variation among genes
Stumpf & McVean (2003)
Nature Reviews Genetics

7. Approaches to genetic association in plants
Natural populations
Breeding populations
Complex demography
unknown
Population structure
GLM GC
MLM SA GC
MLM
TDT
QTDT
GLM GC
Familial relatedness
Based on Yu & Buckler (2006)
Current Opinion in Biotechnology

8. Power considerations: the size of an association population
A single random mating population with mutation, random genetic drift, and recombination
Power
% variation explained by QTN
Long & Langley (1999)
Genome Research

9. Increased rate of false-positives due to population structure…
…but correcting for pop structure produces true negatives!
Drought cline
Postglacial migrations
Hirschhorn & Daly 2005
Nature Reviews Genetics
Zhao et al. (2007)
PLoS Genetics

10. Power considerations: structured populations
% variation explained by QTN
(Small association pop of ~100 accessions)
Zhao et al. (2007)
PLoS Genetics

11. Methods for genetic association in forest trees
Standard general linear models (GLMs), usually with p values computed by permutation.
y =  + mi + eij, where y is the trait value,  is a general mean, mi is the genotype of the i-th SNP and eij is the residual.
Structured Association (Pritchard et al. 2000; Thornsberry 2001) and PCA Association (Price et al. 2006).
Controls for population structure by incorporating a Q matrix. This matrix is an n × p population structure incidence matrix where n is the number of individuals assayed and p is the number of populations defined.
Mixed Linear Models (MLMs; Yu et al. 2006).
They incorporate a Q matrix (fixed effect) but also a pairwise relatedness matrix (K matrix, a random effect), which account for within population structure.

12. FBRC association population in loblolly pine
Family-based methods (Transmission Disequilibrium Test, TDT or QTDT, and its several extensions).
Parents must be heterozygous to be informative.
From few to moderate genetic backgrounds tested.
Partial diallel, including offspring from 61 families. Association with WUE (isotope discrimination in two sites)
FBRC association population in loblolly pine
González-Martínez et al. (2008) Heredity

13. Corrections for multiple testing
Experiment-wise permutation
Bonferroni (/k, with k = the number of tests)
False Discovery Rate (FDR)
FDR: the expected proportion of false positives among all significant tests
Storey & Tibshirani (2003)
PNAS

14. Permutation tests (Hirschhorn and Daly 2005)

15. Some examples Monolignol biosynthesis and cell-wall related genes
González-Martínez et al. (2007)
Genetics
Drought tolerance Collada et al. (in prep.)

16. (also P. sylvestris, Picea abies and oaks)
Pinus taeda L
Pinus pinaster Ait.
Fragmented range, significant population structure
Continuous range, no clear population genetic structure
TREESNIPS project
(also P. sylvestris, Picea abies and oaks)
ADEPT project

17. Genetic association with wood property traits
Phenotypic traits
Earlywood specific gravity (ewsg)
Latewood specific gravity (lwsg)
Percent latewood (lw)
Earlywood microfibril angle (ewmfa)
Lignin & cellulose content (lgn-cel)
Synthetic PCAs for different wood-age types S1 S2 S3
2o wall
1o wall
microfibril
angle
SNP genotyping
FP-TDI platform  58 SNPs from 20 wood- and drought- related candidate genes.
González-Martínez et al. 2007
Genetics

18. cad
Significant genetic association of cad gene with earlywood specific gravity and 4cl with % latewood
4cl

19. Genetic association with WUE
Phenotypic traits
Isotope discrimination (WUE)
Growth (height, diameter, annual increments)
Biomass (total and aerial)
Ontogeny scores
Survival
Provenance-progeny combined tests in two sites: Cálcena (central Spain) & Bordeaux (southwestern France)
SNP genotyping
Pyrosequencing  Relatively high genotyping error.
Collada et al. (in prep.)

20. BLUEs (pop effect removed)
agp4
GLMs, population as a factor
BLUEs (pop effect removed)
Central/marginal pairs
Average for TT:
Average for GT:

21. Tassel demo

22. R SNPassoc package demo

23. Perspectives on genetic association in forest trees
Enormous potential, but still many technical challenges ahead: optimization of SNP genotyping platforms, dealing with recently evolved gene families, building large unstructured association populations, transfer information to non-model species, etc.
Linking genotype-phenotype through association genetics works well for well-known metabolic pathways, and for some species such as loblolly pine genome-wide approaches are now in place. As large-scale association studies are developed, more complex questions will be addressed: gene interactions, heterosis, plasticity (G x E), etc.
Apart from industry applications, given the ecosystem-wide importance of forest trees, genetic association will have a strong influence in evolutionary and ecological research.

24. ABA-and-WDS-induced-gene-3 (lp3-3)
Absence of transpecific SNPs between P. pinaster and P. taeda, two pine species separated by ~120 Myr
ABA-and-WDS-induced-gene-3 (lp3-3)
P. pinaster
P. taeda
Average Ks between P. pinaster and P. taeda of ~2%

25. Acknowledgements and, of course, all you!
TREESNIPS (for maritime pine: C. Collada, E. Eveno, M.A. Guevara, A. Booth, A. Soto, C. Plomion, L. Díaz, S. McCallum, I. Aranda, O. Brendel, R. Alía, V. Leger, J. Brach, J. Russell, P.H. Garnier-Géré, M.T. Cervera)
ADEPT & ADEPT2 (N.C. Wheeler, E. Ersoz, G.R. Brown, G.P. Gill, R.J. Kuntz, J.A. Beal, J. Manares, D. Huber, J. Davis, B. Pande, J. Lee, A. Eckert, J. Wegrzyn, C.D. Nelson)
FUNDING AGENCIES (NSF, CSREES-USDA, EU, MEC-Spain)
and, of course, all you!