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Selective Breeding & cDNA Microarrays

Selective Breeding & cDNA Microarrays

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Selective Breeding & cDNA Microarrays

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  1. Applied quantitative genetics in a genomics world 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

  2. Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Tissue Samples Treat A Treat B Analysis mRNA Extraction & Amplification + Image Capture cDNA “A” Cy5 cDNA “B” Cy3 Laser 1 Laser 2 Hybridization Optical Scanner The Process Bribie Island – 26-27 July 2004

  3. Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray The Possibilities • 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? Bribie Island – 26-27 July 2004

  4. Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray How to relate them? 3 Types of Data Phenotype + Pedigree Phenotype + Marker Gene Expression Bribie Island – 26-27 July 2004

  5. Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Mixed-Inheritance Model Wang, Fernando & Grossman, 1998 Many authors and many species NB: Segregation Variance Issues Infinitesimal Model ANOVA Model Henderson, 1975 Many authors and many species Dimension Reduction Genetical Genomics Jansen and Nap, 2001 (arabidopsis) Brem et al, 2002 (yeast) Schadt et al., 2003 (mice) Chiaromonte & Matinelli, 2002 (leukemia, humans) ANOVA Model Cui and Churchill, 2003 Predict Future Performance Phenotype + Pedigree Phenotype + Marker Gene Expression Bribie Island – 26-27 July 2004

  6. Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Genetical Genomics 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 Bribie Island – 26-27 July 2004

  7. Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray High EBV Low EBV 1 0 2 2 GeneStar Marbling Genotype (N Stars/Alleles) 3 1 1 7 8 4 5 2 0 6 Genetical Genomics 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. For lots of $, this will find lots of genes affecting a trait of interest. …….……Selective Breeding Needs Additivity: Bribie Island – 26-27 July 2004

  8. Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Never enough! …not greed but algebra: Ability to score individuals rapidly (and cheaply) at a very large number of loci. Genetical Genomics 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. • …………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) Bribie Island – 26-27 July 2004

  9. Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray Final Thoughts Where does this leave us (Quantitative Geneticists)? Where does this leave Phenotypes (the need to measure)? 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

  10. Applied quantitative genetics in a genomics world Selective Breeding & cDNA Microarray References Andersson, L. and Georges (2004) Domestic-animal genomics: deciphering the genetics of complex traits. Nature Reviews 5:202-212. Brem, R.B., G. Yvert, R. Clinton, and L. Kruglyak. (2002) Genetic dissection of transcriptional regulation in budding yeast. Science 296:752-755. 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. 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. 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. Bribie Island – 26-27 July 2004