Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Eef meeting rome 2015 carlos lara romero

26 views

Published on

Eef meeting rome 2015 carlos lara romero

Published in: Science
  • Be the first to comment

  • Be the first to like this

Eef meeting rome 2015 carlos lara romero

  1. 1. 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
  2. 2. Marginal populations: • grow under suboptimal environmental conditions • great fluctuations and high probability of extinction Soulé (1973) Introduction Aims In situ experiments Transcriptomic experiment Conclusions
  3. 3. • 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
  4. 4. 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
  5. 5. 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
  6. 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 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
  7. 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 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
  8. 8. 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
  9. 9. • 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
  10. 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. 11. • 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
  12. 12. • 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
  13. 13. 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
  14. 14. 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 populations x 3 mountains Introduction Aims In situ experiments Transcriptomic experiment Conclusions
  15. 15. 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 Survivalproportion F1 F2 F3 0.00.20.4 Seedling survival Gene flow Survival(%) 0 60 40
  16. 16. 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 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
  17. 17. 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
  18. 18. On-going research but… Reciprocal sowing experiments Marginal populations Central populations Introduction Aims In situ experiments Transcriptomic experiment Conclusions
  19. 19. …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
  20. 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. 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. 21. 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
  22. 22. 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 analysis Central Marginal Differential expression
  23. 23. 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
  24. 24. 7 reads needed to infer genotype Deletion of paralogous SNPs Biallelic 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 DNA sequence that is polymorphic in a population
  25. 25. [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
  26. 26. Introduction Aims In situ experiments Transcriptomic experiment Conclusions 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 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
  27. 27. 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
  28. 28. 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 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
  29. 29. 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
  30. 30. 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:

×