Lara romero congreso_restauracion_utpl_2016

1. El rol de las poblaciones marginales en el manejo y
restauración de poblaciones silvestre en un clima cambiante
Lara-Romero C, Morente-López J, García-Fernández
A, Rubio ML, Iriondo JM
Rey Juan Carlos
University
Madrid

2. Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Evolutionary Resilience and Assisted Evolution in restoration practices
• Ability of populations to persist in their current state.
• Undergo evolutionary adaptation in response to changing environmental conditions
Both concepts are a way of
conserving evolutionary
potential of species
and populations
The use of genetically resilient
individuals can restore or
maintain key ecosystem
attributes and processes
Mascarelli, A. 2014. Nature
Sgrò, C. 2010. Evolutionary Applications

3. Marginal populations:
• grow under suboptimal environmental conditions
• great fluctuations and high probability of extinction
Soulé (1973)
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

4. • Genetically
impoverished
populations
• Inbreeding depression
• Maladaptation
• Not necessarily
depauperate for variation
in ecologically relevant
traits.
• Locally adapted
Marginal populations:
• grow under suboptimal environmental conditions
• great fluctuations and high probability of extinction
Soulé (1973)
?
Kawecki, T. J. 2008. Annu. Rev. Ecol. Evol. Syst.
Soulé M. 1973. Annu. Rev. Ecol. Sys.
Lande R. 1994. Evolution
Whitlock MC. 2003. Genetics
Lande (1994), Whitlock (2003) Kawecki (2008)
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

5. Mediterranean alpine environments: highly vulnerable to global
warming
Marginal populations
Central populations
temperature rainfall
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Nogués-Brano et al 2007. Global Environmental Change
Paulí et al 2012. Science

6. Experimental gene flow between populations:
– assessment of inbreeding depression and geneflow of
adaptive/maladaptive value
– management tool to assist marginal populations
Marginal populations
Central populations
Holt RD, Gomulkiewicz R. 1997. Am Nat
Kirkpatrick M, Barton NH. 1997. Am Nat
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

7. Experimental gene flow between populations:
– assessment of inbreeding depression and geneflow of
adaptive/maladaptive value
– management tool to assist marginal populations
Marginal populations
Central populations
central – marginal geneflow:
• Genetic diversity (Holt & Gomulkiewicz, 1997)
• Maladaptive alleles or gene combinations
(Kirkpatrick & Barton, 1997)
Holt RD, Gomulkiewicz R. 1997. Am Nat
Kirkpatrick M, Barton NH. 1997. Am Nat
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

8. Experimental gene flow between populations:
– assessment of inbreeding depression and geneflow of
adaptive/maladaptive value
– management tool to assist marginal populations
Marginal populations
Central populations
marginal-marginal geneflow
• Genetic diversity & adaptive alleles or gene combinations (Sexton et al. 2011)
Sexton JP, Strauss SY, Rice KJ. 2011. PNAS
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

9. Aim:
• To assess whether marginal populations at the lowest elevation of
Mediterranean alpine plants are locally adapted/maladapted to the
environmental conditions that will prevail with global warming
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

10. • Circum-mediterranean alpine chamaephyte
• Central System at the lowest latitude of the
distibution range:
– Sierra de Béjar
– Sierra de Gredos
– Sierra de Guadarrama
• Elevation range: 1900 – 2500 m
Silene ciliata Pourret
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

11. • Central population
• Marginal populations
Central vs. marginal populations
Giménez-Benavides, L., Albert, M.J., Iriondo, J.M. & Escudero, A. Ecography (2011)
GuadarramaGredosBéjar
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
(Giménez-Benavides et al. 2011)

12. Seeds obtained in common garden conditions from artificial crossings simulating
different types of geneflow
Gene flow simulation experiment
Central
population from
same mountain
range
Marginal
population
Marginal
population from
same mountain
range
X 6 marginal populations
C1
C2
C3
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

13. Sowing experiment at the locations of the 6 marginal populations
(mother plant x type of cross x block x pop. = 24 000 seeds)
Gene flow simulation experiment
Marginal populations
Central populations
C1C2
C3
x 2 marginal populations
x 3 mountains
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

14. Sexton JP, Strauss SY, Rice KJ. 2011. PNAS
Evidence of adaptive geneflow between marginal populations (C1 < C2):
Mimulus laciniatus (Sexton et al., 2011)
Marginal populations
Central populations
C1C2
C3
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Gene flow simulation experiment
Survival
Treatment
Survivalproportion
F1 F2 F3
0.00.20.4
Seedling survival
Gene flow
Survival(%)
0
60
40

15. No evidence of maladaptive gene flow from central populations (C1 ≤ C3)
Little evidence of inbreeding load (C1 < C2; C1 ≤ C3)
Marginal populations
Central populations
C1C2
C3
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Gene flow simulation experiment
Survival
Treatment
Survivalproportion
F1 F2 F3
0.00.20.4
Seedling survival
Gene flow
Survival(%)
0
60
40
García-Fernández A, Iriondo JM & Escudero A. 2012 Oikos

16. Reciprocal sowing experiments among central and marginal populations to
test for evidence of local adaptation
(mother plant x type of cross x block x pop. = 7 250 seeds)
Reciprocal sowing experiments
Marginal populations
Central populations
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
x 3 mountains

17. On-going research but…
Reciprocal sowing experiments
Marginal populations
Central populations
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

18. …previous reciprocal sowing experiments found evidence of local adaptation
in seedling survival and growth in central and marginal populations
Reciprocal sowing experiments
Giménez-Benavides L, Escudero A & Iriondo JM
2007. Annals of Botany
Marginal populations
Central populations
Introduction Aims In situ experiments Transcriptomic experiment Conclusions

19. Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Transcriptome analyses
Massive sequencing of the transcriptome of seedlings from central and marginal populations
grown under controlled conditions.
Identification of polymorphisms and differential expression levels in candidate genes between
seedlings from central and marginal populations.
T G T C G G T C T
T G T C G G T C T
T G T C A G T C T
T G T C A G T C T
Single Nucleotide
Polymorphism (SNP)
Central
Marginal
Differential expression

20. Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Transcriptome analyses
Massive sequencing of the transcriptome of seedlings from central and marginal populations
grown under controlled conditions.
Identification of polymorphisms and differential expression levels in candidate genes between
seedlings from central and marginal populations.
Functional annotation & Enrichment analysis
We expect to find some candidate genes codifying proteins involved in responses to
abiotic stimulus, particularly drought stress.
T G T C G G T C T
T G T C G G T C T
T G T C A G T C T
T G T C A G T C T
Single Nucleotide
Polymorphism (SNP)
Central
Marginal
Differential expression

21. RPKM (Reads per kilobase per million mapped reads)
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Comparison of expression levels (RPKM) between central
and marginal populations
129 contigs differentially expressed
GO term & Enrichment analysis
• 114 contigs annotated (i.e.,
protein-coding genes)
• Response to extracellular stimulus
(n=9) & external stimulus (n=19)
overrepresented
Central
Marginal
Differential expression
Differential expression analysis
Contig: pieces of DNA representing overlapping
regions of a particular chromosome

22. Introduction Aims In situ experiments Transcriptomic experiment Conclusions
6 genes overlapped among three approaches
GO TERM: response to stress & metabolic process
163 genes overlapped among two approaches
• 143 annotated genes
• Enrichment analysis (before FDR correction)
- Response to abiotic stimulus (n = 53)
- Response to stress (n = 59)
- Several additional terms related to metabolic
processes and response to stimulus
SNP calling & outlier detection
Dispersal param. Allele freq.
AFD
336 606
275
20
13124
6
Muller et al 2010 Evolutionary Applications, Turner et al 2010 Nature, Stölting et al 2015 New Phytologist
[1] Contingency table and Pearson’s Chi-square test (X2)
[2] Dispersal parameter (m, Muller et al 2010 Evolutionary Applications)
[3] Allelic frequency differentials (AFDs)
Alternative strategies for selection of outlier SNPs

23. 1. Adaptive geneflow between marginal populations at the seedling
stage.
2. No maladaptive geneflow between central and marginal
populations at the seedling stage.
3. Some evidence of inbreeding load in marginal populations.
4. Genes involved in stress responses might play an important role in
the adaptation to marginal environments.
5. Marginal populations might be of high importance to assist
central populations as they can provide alleles or gene
combinations adapted to the environmental conditions that will
prevail with global warming.
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Conclusions

24. Introduction Past studies Current research Future prospects
Acknowledgements:
• C. Diaz, G. Escribano, S. Prieto, P. Tabares, S.
Eleazar, L. Cano, L. Martinez, S. Fior, M. Roumet
• Sierra de Guadarrama National Park
• Sierra de Gredos Regional Park
• Sierras de Béjar y Francia Biosphere Reserve
• AdAptA Project CGL2012-33528,
Spanish National R&D&I Plan
• ESF networking programma
ConGenOmics
Funding: