Bioinformatics Transcriptome Jacques van Helden Jacques vanHeldenunivamu fr
Bioinformatics Transcriptome Jacques van Helden Jacques. van-Helden@univ-amu. fr Aix-Marseille Université (AMU), France Lab. Technological Advances for Genomics and Clinics (TAGC, INSERM Unit U 1090) http: //tagc. univ-mrs. fr/ FORMER ADDRESS (1999 -2011) Université Libre de Bruxelles, Belgique Bioinformatique des Génomes et des Réseaux (Bi. GRe lab) http: //www. bigre. ulb. ac. be/
Bioinformatics Transcriptome Jacques. van. Helden@ulb. ac. be Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (Bi. GRe) http: //www. bigre. ulb. ac. be/
Measuring the expression of all the genes of a genome n de. Risi et al. (1997). Science 278: 680 -686 n In 1997, de. Risi and co-workers develop a method to measure the level of transcription of all the genes of a genome. The method allows to compare the concentrations of m. RNA of each gene between two experimental conditions q q n n Green channel: reference Red channel: test The intensity of a spot indicates the average concentration of the corresponding m. RNA in the two samples. The color of a spot indicates regulation: q q Red: up-regulated in the test, relative to the reference condition Green: down-regulated
DNA chip technology Cell culture, tissue, . . . Sample 1 Sample 2 RNA extraction RNA Synthesis of fluorescent c. DNA Brightness Quantity Color Specificity yellowish reddish greenish not specific sample 1 - specific sample 2 - specific DNA chip Source: de. Risi et al. , Science 1997
Scanning result slide from Peter Sterk
Complete microarray Source: De. Risi et al. (1997) Science, 278(5338), 680 -6. de. Risi et al. (1997). Science 278: 680 -686
DNA chips – raw measurements n Raw measurements q q n Red intensity Red background Green intensity Green background Intensity – background = level of expression q q Red Green in experimental conditions in control
DNA chips – useful metrics n The level of regulation is represented by the ratio r >1 up-regulated r < 1 down-regulated n n The log-ratio provides a more convenient statistic (we will see why during the course) log 2 is even more convenient because the scale is intuitive R < 0 down-regulated R > 0 up-regulated |R| > 1 regulated by a factor of 2 |R| > 2 regulated by a factor of 4 |R| > w regulated by a factor of 2 w
Time series n n At each time point, the expression level is compared to the control (log-ratio) Example: Nitrogen depletion Source: Gasch et al (2000) Molecular Biology of the Cell 11: 4241 -4257
Examples of experimental conditions n Presence/absence of a metabolite q n Transcription factor mutants q q n q rich versus minimal medium diauxic shift (7 time points during the shift) Cell differentiation q q n Yap 1 p over-expression TUP 1 deletion Massive environmental changes q n gal vs glucose sporulation mating type Cell cycle
Temporal profiles of expression n n de. Risi et al measured the level of expression of all the genes at 7 time points during the diauxic shit. The figure shows groups of genes show similar expression profiles, q q de. Risi et al. (1997). Science 278: 680 -686 Some of these groups contain genes with similar function (e. g. coding for ribosomal proteins) Some of these groups have a common regulatory element in their promoter (e. g. stress response element).
Cell cycle n n n In 1998, Spellman and colleagues measure the expression of all yeast genes during the cell cycle. They detect 800 genes showing periodical fluctuations of expression. These genes can be sorted according to the peak of expression, in order to group genes induced during the different phases of the cell cycle (G 1, S, G 2, M). Spellman et al. (1998) Molecular Biology of the Cell 9: 3273 -3297
Gene expression data: hierarchical clustering Alpha cdc 15 cdc 28 Elu n MCM n CLB 2 On the image, genes are clustered according to expression profiles, using Michael Eisen’s software “cluster” (Eisen et al. , PNAS 1998: 95, 14863 -8). Strengths q SIC 1 MAT q n Weaknesses q CLN 2 Y' MET Spellman et al. (1998). Mol Biol Cell 9(12), 3273 -97. The profiles and the clusters are visible together Familiar to biologists (frequently used for phylogeny) q q Isomorphism: each node of the tree can be permuted vertical distance between genes does not reflect the real distance Where to set the cluster boundaries ? The tree does not reflect the combinatorial aspect of regulation
Gasch (2000) - gene response to environmental changes n Gasch et al. (2000) measure the transcriptional response of yeast genes to various environmental changes q q 173 microarrays ~6000 genes per microarray
Classification of cancer types n n Microarrays are also used to select genes which will serve as “molecular signatures” to classify cancer types. These genes can then be used to establish a diagnostic for new patients. Golub et al. (1999). Science 286: 531 -537
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