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Eef meeting rome 2015 carlos lara romero

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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:

Editor's Notes

  • I am going to present preliminary results of my postdoc at Rey Juan Carlos University and ETH zurich, which aims to provide an integrated perspective on the local adaptation in marginal alpine populations, combining in situ common garden and transcriptomic experiments.
  • If we consider that marginal populations are those the grow under suboptimal environmental conditions within the ecological range of the species and in terms of population dynamics experience great fluctuations and higher probability of extinction, we can see that marginal populations have traditionally been seen under two perspectives:


    Lande R, 1994: Risk of population extinction from fixation of new deleterious mutations. Evolution 48: 1460–1469.
  • they are populations normally located a the end of the distribution range, genetically impoverished (impoveris) and subject to inbreeding depression, and, therefore, maladapted to the conditions that they are experiencing,

    or, on the contrary, and in spite of some limitations, they are locally adapted to the reigning marginal environmental conditions.
  • Mediterranean alpine environments are highly vulnerable to global warming and in this sense marginal populations may be of interest, because they are currently experiencing the environmental conditions of higher temperatura and lower rainfall that central populations are going to experience in the future.
  • Experimental gene flow between populations can be a way of assessing inbreeding depression in populations and the existence of geneflow of adaptive or maladaptive value and could actually be used as a way to assist wild plant populations affected by global change.
  • Historically the geneflow between central and marginal populations has been proposed to be beneficial for marginal populations as it provides much needed genetic diversity in marginal populations to evolve.

    On the contrary, and based on the theory on the evolution of the limits of distribution (Kirkpatrick & Barton, 1997), central to marginal geneflow can transfer maladaptive alleles or gene combinations.
  • More recently, Sexton et al. have highlighted the possible benefits of geneflow between marginal populations subject to the same environmental conditions as they can provide both genetic diversity and adaptive alleles or gene combinations.



  • Thus, in this context, the aim of our study was… […] For our purpoues we have used a combination of in situ common garden and transcriptomic experiemnts
  • We based our study on Silene ciliata, a mediterranean alpine specialist distributed across the north mediterranean basin (beisin).
  • We worked on the populations of the Central System which have a common evolutionary history. This populations are located at the westernmost lowest latitude of the distribution range on three sierras, covering an elevation range between 19 hundred and 25 hundred meters.
  • We generated an ecological niche model with Maxent to objectively (ofyeftifly) identify the marginal populations we worked on.

    We defined as marginal those populations whose hábitat suitability index was in the lowest quartile. We selected 6 populations, two in each sierra, located at the lowest elevations.

    Previous studies of our group showed that these populations were smaller and had Lower demographic performance and reproductive success than the populations identified as central populations.
  • We generated an ecological niche model with Maxent to objectively identify the marginal populations we worked on.

    We defined as marginal those populations whose hábitat suitability index was in the lowest quartile. We selected 6 populations, two in each sierra, located at the lowest elevations.

    Previous studies of our group showed that these populations were smaller and had Lower demographic performance and reproductive success than the populations identified as central populations.
  • With plant material gathered (gadet) from each of these marginal populations and grown in common garden conditions we obtained seeds from artificial crossings simulating different types of geneflow.

    Specifically and in order to perform a GFSE we cross the plants of our focal marginal population with F1 pollen from the same population., F2 pollen from another marginal population from the same mountain range and F3 pollen from a central population of the same mountain range.

    These was done for the 6 marginal populations we chose.
  • With these seeds we carried out an in situ sowing experiment at the locations of the 6 marginal populations. We considered the identity of the mother plant, type of cross, block and population and used 24000 seeds.

    In situ: 10 seeds/mother plant x 20 mother plants/type of cross x 5 types of cross /block x 4 blocks/population x 6 populations = 24000 seeds
  • Individuals from cross F1 had lower survival than individuals from F2. The higher survival of F2 could be interpreted as an evidence of adaptive geneflow between marginal populations.This is in agreement with Sexton et al taht reported similar reuslts in a experiment with Mimulus laciniatus.

    F1. Pollen form same Pop.

    F2.Pollen from another marginal Pop.

    F3. Pollen form a central Pop.
  • In other hand, cross F3 had similar survial than F1, which are interpreted as no evidence of maladaptive gene flow from central populations.

    Interesting to note that F1 was the cross with lower survival, which point to a situation of inbreeding load at marginal populations. This is in agreement with a previous study of our group reporting that inbreeding depression plays an important role in the fitness of early life stages at marginal populations.
  • We complemented this experiment with a traditional Reciprocal sowing experiments among central and marginal populations to test for evidence of local adaptation. Again, 2e considered the identity of the mother plant, seed origing, block and population and used 7200 seeds.


  • Altough I can’t present the findings of this experiment because we are now performing the field workd,
  • we had detected in previous studies evidences of local adaptation in marginal and central populations wich suggest that individuals from central populations are adapted to optimum environmental conditions that prevail on the top of the mountain, which are expected to be changed as a result global warming.
  • In parallel, to elucidate the genetic basis of the adaptation processes we have conducted a transcriptomic experiment using NGS.

    This experiment have involved the massive sequencing of the transcriptome of seedlings from central and marginal populations grown under controlled conditions.

    Transcriptome analysis, which are in progress, are involving the identification of polymorphisms and differential expression levels in candidate genes between seedlings from central and marginal populations.

    We expect to find some candidate genes codifying proteins involved in responses to abiotic stimulus, particularly drought stress.


  • We expect to find some candidate genes codifying proteins involved in responses to abiotic stimulus, particularly drought stress.


  • Regarding differential expression analysis in the figure is showed the comparison of expression levels between central and marginal populations

    We estimated the mean RPKM per contig and per elevation
  • one hundred and twenty nine genes were differentially expressed between elevations. This genes are represented by Red and blue circles in the figure.

    114 of this genes were succesfully annotated, this means that we can associate a biological function to this DNA sequences.

    We then performed an enrichment analysis to find which Biological proccess were over-represened in this set of candidate genes detecting two terms overrepresented compared with all genes covered by the refence-based assembly.

    Namely, Response to extracellular stimulus (n=9) & external stimulus



  • We used Reads2SNP for SNP calling. After several filtering process we identify about one hundred and fifty thousand of SNPS distributed in twelve thousand seven hundred contis. With an average of fourteen SNPS per contig.


  • We have implemented three alternative strategies for detection of outlier SNPs based on frequency distribution of the SNPS Within and between central and marginal populations.

  • this Venn diagram is showing the extent of overlap among selection approaches based on three alternative stragegies for selction of outlier SNPs


  • As we can obseve in the diagram 6 genes overlapped among all approaches….
    This genes are related with responses to stress and metabolic processes…
  • …and 163 among at least two approaches. Enrichment analysis detected enrichment for biological processes related with response to stress and biotic stimulus and several aditional terms realted to metabolic processes
  • In conclusión, we found….

    Management actions should consider the possible benefits of geneflow between marginal populations subject to the same environmental conditions as they can provide both genetic diversity and adaptive alleles or gene combinations, as shown by our results.

    Our results also shows the advantage of combination transcrptome and phenotypic data in common garden experiments to understand local adaption and its underlying molecular basis.
  • But first of all I would like to acknowledge the help of these fellow collaborators in the study, the support of the authorities and managers of the protected áreas where we conducted the study and the research Project that has funded it.
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