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Transcriptomic and phenotypic data from common gardens reveal adaptive genetic variation in a Mediterranean alpine plant
Lara-Romero C, Zemp N, García-Fernández A, Morente-Lopez J, Rubio ML,
Widmer A, Iriondo JM
ConGenOmics
Rey Juan Carlos University Madrid
Marginal populations:• grow under suboptimal environmental conditions• great fluctuations and high probability of extinction
Soulé (1973)
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
• 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. EvolutionWhitlock MC. 2003. Genetics
Lande (1994), Whitlock (2003) Kawecki (2008)
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
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
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 NatKirkpatrick M, Barton NH. 1997. Am Nat
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
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 NatKirkpatrick M, Barton NH. 1997. Am Nat
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
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
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
• 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
• 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
• Central population
• Marginal populations
Central vs. marginal populations
(Giménez-Benavides et al. 2011)
Giménez-Benavides, L., Albert, M.J., Iriondo, J.M. & Escudero, A. Ecography (2011)
GuadarramaGredosBéjar
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
• Central population
• Marginal populations
Central vs. marginal populations
(Giménez-Benavides et al. 2011)
Giménez-Benavides, L., Albert, M.J., Iriondo, J.M. & Escudero, A. Ecography (2011)
GuadarramaGredosBéjar
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
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
F1
F2
F3
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
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
F1F2
F3
x 2 marginal populationsx 3 mountains
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Sexton JP, Strauss SY, Rice KJ. 2011. PNAS
Evidence of adaptive geneflow between marginal populations (F1 < F2): Mimulus laciniatus (Sexton et al., 2011)
Marginal populations
Central populations
F1F2
F3
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Gene flow simulation experiment
Survival
Treatment
Sur
viva
l pro
porti
on
F1 F2 F3
0.0
0.2
0.4
Seedling survival
Gene flow
Surv
ival
(%)
0
60
40
No evidence of maladaptive gene flow from central populations (F1 ≤ F3)
Little evidence of inbreeding load (F1 < F2; F1 ≤ F3)
Marginal populations
Central populations
F1F2
F3
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Gene flow simulation experiment
Survival
Treatment
Sur
viva
l pro
porti
on
F1 F2 F3
0.0
0.2
0.4
Seedling survival
Gene flow
Surv
ival
(%)
0
60
40
García-Fernández A, Iriondo JM & Escudero A. 2012 Oikos
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
On-going research but…
Reciprocal sowing experiments
Marginal populations
Central populations
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
…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
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 TT G T C G G T C T
T G T C A G T C TT G T C A G T C T
Single Nucleotide Polymorphism (SNP)
Central
Marginal
Differential expression
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 TT G T C G G T C T
T G T C A G T C TT G T C A G T C T
Single Nucleotide Polymorphism (SNP)
Central
Marginal
Differential expression
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
Differential expression analysisCentral
Marginal
Differential expression
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
Selection of candidate genes
Contig: pieces of DNA representing overlapping regions of a particular chromosome
7 reads needed to infer genotypeDeletion of paralogous SNPsBiallelic SNPs with no missing data
Depth of coverage and posterior probability did not affect outlier detection
147 118 SNPs & 12 688 contigs (mean x contig =13.7)
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
SNP calling & outlier detection
SNP calling (Software Reads2SNP)
SNP: a nucleotide site (base pair) in a DNAsequence that is polymorphic in a population
[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)
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
Alternative strategies for selection of outlier SNPs
Selection of candidate genes
SNP calling & outlier detection
Muller et al 2010 Evolutionary Applications, Turner et al 2010 Nature, Stölting et al 2015 New Phytologist
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
SNP calling & outlier detection
Dispersal param. Allele freq.
AFD
336 606
275
20
131246
Muller et al 2010 Evolutionary Applications, Turner et al 2010 Nature, Stölting et al 2015 New Phytologist
Selection of candidate genes
[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
Introduction Aims In situ experiments Transcriptomic experiment Conclusions
6 genes overlapped among three approaches GO TERM: response to stress & metabolic process
Dispersal param. Allele freq.
AFD
336 606
275
20
13124 6
SNP calling & outlier detection
Muller et al 2010 Evolutionary Applications, Turner et al 2010 Nature, Stölting et al 2015 New Phytologist
Selection of candidate genes
[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
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
131246
Muller et al 2010 Evolutionary Applications, Turner et al 2010 Nature, Stölting et al 2015 New Phytologist
Selection of candidate genes
[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
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
Introduction Past studies Current research Future prospectsAcknowledgements:
• 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: