The research of my group focuses on traits with economic value (e.g. growth, wood formation, wood calorimetric content, frost hardiness and pest resistance) and also on traits with clear adaptive value (e. g. shade avoidance, timing of budset). These traits are complex, so called quantitative traits, this means that they are controlled by a large number of genes and gene interactions.

Rosario Garcia 1150(1) Association Mapping: Wood properties and phenology
The main contribution of single nucleotide polymorphisms (SNPs) to conventional tree breeding is the possibility of early selection to shorten the breeding cycle.
Quantitative Trait Loci (QTL) analyses in conifers are typically based on association between quantitative traits and SNPs variation in single full-sib families.Presently we are performing QTL analysis for wood properties (micro fibril angle - MFA -, density, modulus of elasticity - MOE -, ring width...), growth and timing of budset in Scots pine. In Norway spruce, we are currently developing SNP data to identify a major QTL for the pendula phenotype in three full sib crosses between wild and pendula phenotypes.
Association Mapping (AM) is another genetic strategy to unravel the genetics behind complex traits. Typically, this is a gene space based method, which tests for association between candidate genes and phenotypic variation at a population level. We are currently analyzing data for wood formation, growth and phenology based on 500 half-sib families in Norway spruce as part of the spruce genome sequencing project (Wallenberg spruce project), Umeå plant science center, UPSC, SLU-UMU. Genome Wide Selection (GWS) to detect genomic regions harboring sequence variants that affect complex traits requires the development SNP data across the entire genome. Currently, we are developing a dense SNP array in Scots pine for its application in an advance Scots pine breeding pedigree as part of a PhD work, second research school in tree breeding, SLU.

(2) Physiology of light response in gymnosperms
Scots pine southwards transfers lead to increased growth, but not sufficiently to overcome the competitive advantage of the local southern trees. In other words, increased temperature is not to be the only factor promoting growth potential of the northern populations.There are many evidences supporting day length as another major environmental cue shaping the strong adaptive cline in Scots pine. Less attention has been devoted to the study of light composition (wavelength).We are studyingthe effect of light quality on three-month old Scots pine and Norway spruce seedlings. We are currently analyzing the data on hypocotyl morphology, chlorophyll and anthocyanin content, chloroplast development and qPCR on Scots pine as part of a Master thesis work.  

rosario_1 rosario_2 rosario_4
Bud formation in one-year-old Scots pine seedlings under greenhouse conditions. Scots pine trees

rosario_3Single Nucleotidy Polymorphisms (SNPs) scoring(3) Fine and Large genetic structure in Scots pine
Differences in genetic structure between tree species are due mainly to population history, life form and breeding system. The availability of highly variable molecular markers has facil- itated large- and fine-scale genetic structure analysis. Study of large-scale structure is relevant to correct for spatial structure in association studies and to identify new cultivars with desir- able traits (e.g., growth, flowering time...), while fine-scale is related to inbreeding and the consequent inbreeding depression. Currently, we are writing two manuscripts on the large-scale structure that resulted after post-glacial expansion in Scots pine and on the effect of forest management on the fine-scale structure in Scots pine.

4) Comparative evolutionary analysis in Gymnosperm
The majority of gymnosperms posses a large genome size com- pared to other plant groups. In order to understand genome size evolution we are performing in situ fluorescence hybridization (FISH) to investigate genome size evolution comparing Norway spruce and Gnetum (Gnetum, Welwitschia and Ephedra) genomes. In conifers, gene family evolution is also poorly understood. Based on our work on phytochrome gene family found that conifer gene families can be very complex and contribute to the enormous size of the conifer genome. In the light of our recent finding, we are investigating the composition and function of another important gene family (LP3) involved in water deficit stress. In addition, we are currently writing a manuscript on the comparative composition of EST-SSR and UTRs across multiple forestry tree species.

sweden_greySvensk samanfattning

Publications list

  1. Analysis of phenotypic- and Estimated Breeding Values (EBV) to dissect the genetic architecture of complex traits in a Scots pine three-generation pedigree design
    J Theor Biol. 2018 Nov 10 [ Epub ahead of print]
  2. Age and weather effects on between and within ring variations of number, width and coarseness of tracheids and radial growth of young Norway spruce
    EUROPEAN JOURNAL OF FOREST RESEARCH 2018, 137(5):719-743
  3. Differential response of Scots pine seedlings to variable intensity and ratio of R and FR ligh
    Plant, Cell & Environment,  2017, 40(8):1332-1340
  4. Genetic analysis of fiber dimensions and their correlation with stem diameter and solid-wood properties in Norway spruce
    Genetics & Genomes (2016) 12: 123
  5. Comparative in silico analysis of SSRs in coding regions of high confidence predicted genes in Norway spruce (Picea abies) and Loblolly pine (Pinus taeda)
    BMC Genet. 2015, 16(1):149
  6. Application of monochromatic blue light during germination and hypocotyl development improves outplanted Scots pine (Pinus sylvestris L.) trees performance
    Forest Ecology and Management Volume 361, 1 February 2016, Pages 368–374
  7. Present genetic structure is congruent with the common origin of distant Scots pine populations in its Romanian distribution
    Forest Ecology and Management Volume 361, 1 February 2016, Pages 131–143
  8. Non-functional plastid ndh gene fragments are present in the nuclear genome of Norway spruce (Picea abies L. Karsch): insights from in silico analysis of nuclear and organellar genomes
    Molecular Genetics and Genomics 2016, 91(2):935-941
  9. Fungal Infection Increases the Rate of Somatic Mutation in Scots Pine (Pinus sylvestris L.)
    Journal of Heredity 2015, 106 (4):386-394
  10. Development and transferability of two multiplexes nSSR in Scots pine (Pinus sylvestris L.)
    Journal of Forestry Research April 2015
  11. Genetic diversity and inbreeding in natural and managed populations of Scots pine
    Tree Genetics & Genomes March 2015, 11:28
  12. Functional Multi-Locus QTL Mapping of Temporal Trends in Scots Pine Wood Traits
    G3-GENES GENOMES GENETICS, 4 (12):2365-2379
  13. Inheritance of growth and solid wood quality traits in a large Norway spruce population tested at two locations in southern Sweden
    Tree Genetics & Genomes, 2014; 10(5):1291-1303
  14. Ranade SS, Abrahamsson S, Niemi J, García-Gil MR
    Pinus taeda cDNA Microarray as a Tool for Candidate Gene Identification for Local Red/Far-Red Light Adaptive Response in Pinus sylvestris
    American Journal of Plant Sciences, 2013:4, 479-493
  15. Abrahamsson S, Ahlinder J, Waldmann P, García-Gil MR
    Maternal heterozygosity and progeny fitness association in an inbred Scots pine population.
    Genetica 2013141(1-3:41-50
  16. Ecotypic variation in response to light spectra in Scots pine (Pinus sylvestris L.)
    Tree Physiol. 2013; 33(2):195-201
  17. Abrahamsson S, Nilsson JE, Wu H, García-Gil MR, Andersson B
    Inheritance of height growth and autumn cold hardiness based on two generations of full-sib and half-sib families of Pinus sylvestris
    Scandinavian Journal of Forest Research: Available online: 14 Feb 2012
  18. Floran V, Sestras RE, Garcia Gil MR
    Organelle genetic diversity and phylogeography of Scots Pine (Pinus sylvestris L.)
    Notulae Botanicae Horti Agrobotanici Cluj-Napoca: 2011, 39(1):317-322
  19. Sillanpää MJ, Pikkuhookana P, Abrahamsson S, Knürr T, Fries A, Lerceteau E, Waldmann P, Garcia-Gil MR
    Simultaneous estimation of multiple quantitative trait loci and growth curve parameters through hierarchical Bayesian modeling
    Heredity: 2011, 1-13
  20. Garcia-Gil MR, Olivier F, Kamruzzahan S, Waldmann P
    Joint analysis of spatial genetic structure and inbreeding in a managed population of Scots pine
    Heredity: 2009 103:90-96
  21. Garcia-Gil MR
    Evolutionary aspects of functional and pseudogene members of the phytochrome gene family in Scots pine
    Journal of Molecular Evolution: 2008 67:222-232
  22. Pyhajarvi T, Garcia-Gil MR, Knurr T, Mikkonen M, Wachowiak W, Savolainen O
    Demographic history has influenced nucleotide diversity in European Pinus sylvestris populations
    Genetics: 2007 177:1713-1724
  23. Notivol E, Garcia-Gil MR, Alia R, Savolainen O
    Genetic variation of growth rhythm traits in the limits of a latitudinal cline in Scots pine
    Canadian Journal of Forest Research: 2007 37:540-551
  24. Waldmann P, Garcia-Gil MR, Sillanpää MJ
    Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris
    Heredity: 2005 94:623-629
  25. Savolainen O, Bokma F, Garcia-Gil R, Komulainen P, Repo T
    Genetic variation in cessation of growth and frost hardiness and consequences for adaptation of Pinus sylvestris to climatic changes
    Forest Ecology and Management: 2004 197:79-89
  26. Komulainen P, Brown GR, Mikkonen M, Karhu A, Garcia-Gil MR, O'Malley D, Lee B, Neale DB, Savolainen O
    Comparing EST based genetic maps between Pinus sylvestris and Pinus taeda
    Theoretical and Applied Genetics: 2003 107: 667-678
  27. Garcia-Gil MR, Mikkonen M, Savolainen O
    Nucleotide diversity at two phytochrome loci along a latitudinal cline in Pinus sylvestris
    Mol Ecol: 2003 12:1195-1206
  28. Garcia MR, Bernet GP, Puchades J, Gomez I, Carbonell EA, Asins MJ
    Reliable and easy screening technique for salt tolerance of citrus rootstocks under controlled environments
    Australian Journal of Agricultural Research: 2002 53:653-662
  29. Garcia MR, Asins MJ, Carbonell EA
    QTL analysis of yield and seed number in Citrus
    Theoretical and Applied Genetics: 2000 99:487-493
  30. Garcia MR, Asins MJ, Carbonell EA
    QTL analysis of yield and seed number in Citrus
    Theoretical and Applied Genetics: 2000 101:487-493