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Selective Breeding and cDNA Microarrays
 

Selective Breeding and cDNA Microarrays

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    Selective Breeding and cDNA Microarrays Selective Breeding and cDNA Microarrays Presentation Transcript

    • Selective Breeding & cDNA Microarrays Toni Reverter   Bioinformatics Group CSIRO Livestock Industries Queensland Bioscience Precinct 306 Carmody Rd., St. Lucia, QLD 4067, Australia Bribie Island – 26-27 July 2004 Applied quantitative genetics in a genomics world
    • Bribie Island – 26-27 July 2004 Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray The Process cDNA “A” Cy5 cDNA “B” Cy3 Tissue Samples Treat A Treat B mRNA Extraction & Amplification Hybridization Laser 1 Laser 2 Optical Scanner + Image Capture Analysis
    • Bribie Island – 26-27 July 2004
      • Determine genes which are differentially expressed (DE).
      • Connect DE genes to sequence databases to search for common upstream regions.
      • Overlay DE genes on pathway diagrams.
      • Relate expression levels to other information on cells, e.g. tumor types.
      • Identify temporal and spatial trends in gene expression.
      • Seek roles of genes based on patterns of co-regulation.
      • … Applications to Selective Breeding Schemes?
      The Possibilities Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray
    • Bribie Island – 26-27 July 2004 3 Types of Data Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Phenotype + Pedigree Phenotype + Marker Gene Expression How to relate them?
    • Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Bribie Island – 26-27 July 2004 Phenotype + Pedigree Phenotype + Marker Gene Expression Predict Future Performance Mixed-Inheritance Model Wang, Fernando & Grossman, 1998 Many authors and many species NB: Segregation Variance Issues Genetical Genomics Jansen and Nap, 2001 (arabidopsis) Brem et al, 2002 (yeast) Schadt et al., 2003 (mice) Dimension Reduction Chiaromonte & Matinelli, 2002 (leukemia, humans) Infinitesimal Model Henderson, 1975 ANOVA Model Many authors and many species ANOVA Model Cui and Churchill, 2003
    • Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Bribie Island – 26-27 July 2004 Use arrays to identify genes that are DE in relevant tissues of individuals sorted by QTL genotype. If those DE genes map the chromosome region Of interest, they would become very strong candidates for QTL. Source: Jansen and Nap, 2001 Genetical Genomics
    • Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Bribie Island – 26-27 July 2004 Use arrays to identify genes that are DE in relevant tissues of individuals sorted by QTL genotype. If those DE genes map the chromosome region Of interest, they would become very strong candidates for QTL. Genetical Genomics For lots of $, this will find lots of genes affecting a trait of interest. …… .…… Selective Breeding Needs Additivity: High EBV Low EBV GeneStar Marbling Genotype (N Stars/Alleles) 0 1 2 2 1 0 1 2 3 4 5 6 7 8
    • Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Bribie Island – 26-27 July 2004 Use arrays to identify genes that are DE in relevant tissues of individuals sorted by QTL genotype. If those DE genes map the chromosome region Of interest, they would become very strong candidates for QTL. Genetical Genomics
      • ………… particularly useful for:
      • Speed up and enhance power to finding New QTL
      • Developing “ Diagnostic Kits ”
      • Deciphering the genetics of Complex Traits
      A trait that is affected by many, often interacting, environmental and genetic factors such that no factor is completely sufficient nor are all factors necessary. (Andersson and Georges, 2004) Ability to score individuals rapidly (and cheaply) at a very large number of loci. Never enough! …not greed but algebra:
    • Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Where does this leave us ( Quantitative Geneticists )? Where does this leave Phenotypes (the need to measure)? Final Thoughts Very well, ………I’m afraid
      • Quantitative Geneticists:
      • Never enough QTL
      • Association studies
      • Study of variation
      • When QTL not additive, the individual is needed but not so with BLUP
      • Phenotypes:
      • Mutation is continuously generating new variation
      • Selective breeding on genotypes reduces effective population size
      • Integration of the 3 types of data
      Bribie Island – 26-27 July 2004
    • Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray References Bribie Island – 26-27 July 2004 Jansen, R.C. and J.P. Nap (2001) Genetical genomics: the added value from segregation. Trend Genet., 17:388-391. Schadt, E.E., Monks, S.A., Drake, T.A., et al. (2003) Genetics of gene expression surveyed in maize, mouse and man. Nature 422:297-302. Chiaromonte, F., and Martinelli, J. (2002) Dimension reduction strategies for analysing global gene expression data with a response. Math. Biosciences, 176:123-144. Cui, X., and G. A. Churchill. (2003) Statistical tests for differential expression in cDNA microarray experiments. Genome Biol., 4:210. Henderson, C.R. (1975) Best linear unbiased estimation and prediction under a selection model. Biometrics, 31:423. Wang, T., R.L. Fernando, and M. Grossman (1998) Genetic evaluation by best linear unbiased prediction using marker and trait information in a multibreed population. Genetics, 148:507-515. Brem, R.B., G. Yvert, R. Clinton, and L. Kruglyak. (2002) Genetic dissection of transcriptional regulation in budding yeast. Science 296:752-755. Andersson, L. and Georges (2004) Domestic-animal genomics: deciphering the genetics of complex traits. Nature Reviews 5:202-212.