1. Genome Biology and Biotechnology
Genoom Biologie
Prof. M. Zabeau
Genome Biology and Biotechnology
9. The localizome
Prof. M. Zabeau
Department of Plant Systems Biology
Flanders Interuniversity Institute for Biotechnology (VIB)
University of Gent
International course 2005
Academiejaar

2. Summary DNA localizome or DNA interactome Protein localizome
Genome-wide mapping of DNA binding proteins
Transcription factor binding sites
Localization of replication origins
Protein localizome
High throughput localization of proteins in cellular compartments

3. Functional Maps or “-omes”
Genes or proteins n
“Conditions”
ORFeome
Genes
Phenome
Mutational phenotypes
Transcriptome
Expression profiles
DNA Interactome
Protein-DNA interactions
Localizome
Cellular, tissue location
Interactome
Protein interactions
Proteome
proteins
After: Vidal M., Cell, 104, 333 (2001)

4. Genome-wide Analysis of Regulatory Sequences
Gene expression is regulated by transcription factors selectively binding to regulatory regions
protein–DNA interactions involve sequence-specific recognition
Other factors, such as chromatin structure may be involved
Sequence-specific DNA-binding proteins from eukaryotes generally
recognize degenerate motifs of 5–10 base pairs
Consequently, potential recognition sequences for transcription factors occur frequently throughout the genome
Genome-wide surveys of in vivo DNA binding proteins
provides a platform to answer these questions

5. Genome-wide Analysis of Regulatory Sequences
Methods combine
Large-scale analysis of in vivo protein–DNA crosslinking
microarray technology
ChIP-on-chip
Chromatin Immuno-Precipitation on DNA chips
Reprinted from: Biggin M., Nature Genet. 28, 303 (2001)

6. Genome-Wide Location and Function of DNA Binding Proteins
Ren et. al., Science, 290, 2306 (2000)
Paper presents
proof of principle for microarray-based approaches to determine the genome-wide location of DNA-bound proteins
Study of the binding sites of a couple of well known gene-specific transcription activators in yeast: Gal4 and Ste12
Combines data from
in vivo DNA binding analysis with
expression analysis
to identify genes whose expression is directly controlled by these transcription factors

7. Chromatin Immuno Precipitation (Chip) Procedure
Cells are fixed with formaldehyde, harvested, and sonicated
DNA fragments cross-linked to a protein of interest are enriched by immunoprecipitation with a specific antibody
Immuno-precipitated DNA is amplified and labeled with the fluorescent dye Cy5
Control DNA not enriched by immunoprecipitation is amplified and labeled with the different fluorophore Cy3
DNAs are mixed and hybridized to a microarray of intergenic sequences
The relative binding of the protein of interest to each sequence is calculated from the IP-enriched/unenriched ratio of fluorescence from 3 experiments
Reprinted from: Ren et. al., Science, 290, 2306 (2000)

8. Modified Chromatin Immuno Precipitation (Chip) Procedure
Genoom Biologie
Prof. M. Zabeau
Modified Chromatin Immuno Precipitation (Chip) Procedure
Close-up of a scanned image of a micro-array containing 6361 intergenic region DNA fragments of the yeast genome
ChIP-enriched DNA fragment
Fig. 1. The genome-wide location profiling method. (A) Close-up of a scanned image of a microarray containing DNA fragments representing 6361 intergenic regions of the yeast genome. The arrow points to a spot where the red intensity is over-represented, identifying a region bound in vivo by the protein under investigation. (B) Analysis of Cy3- and Cy5-labeled DNA amplified from 1 ng of yeast genomic DNA using a single-array error model (8). The error model cutoffs for P values equal to 103 and 105 are displayed. (C) Experimental design. For each factor, three independent experiments were performed and each of the three samples were analyzed individually using a single-array error model. The average binding ratio and associated P value from the triplicate experiments were calculated using a weighted average analysis method
Reprinted from: Ren et. al., Science, 290, 2306 (2000)
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9. Proof of concept: Gal4 transcription factor
Identification of sites bound by the transcriptional activator Gal4 in the yeast genome and genes induced by galactose
Gal4 activates genes necessary for galactose metabolism
The best characterized transcription factor in yeast
10 genes were bound by Gal4 and induced in galactose
7 genes in the Gal pathway, previously reported to be regulated by Gal4
3 novel genes: MTH1, PCL10, and FUR4
Reprinted from: Ren et. al., Science, 290, 2306 (2000)

10. Genome-wide location of Gal4 protein
Genes whose promoter regions are bound by Gal4 and whose expression levels were induced at least twofold by galactose
Reprinted from: Ren et. al., Science, 290, 2306 (2000)

11. Role of Gal4 in Galactose-dependent Cellular Regulation
The identification of MTH1, PCL10, and FUR4 as Gal4-regulated genes explains how regulation of several different metabolic pathways can be coordinated
increases intracellular pools of uracil
Fur4
Pcl10
MTH1
reduces levels of glucose transporter
Reprinted from: Ren et. al., Science, 290, 2306 (2000)

12. Conclusions
The genes whose expression is controlled directly by transcriptional activators in vivo
Are identified by a combination of genome-wide location and expression analysis
Genome-wide location analysis provides information
On the binding sites at which proteins reside in the genome under in vivo conditions

13. Genomic Binding Sites of the Yeast Cell-cycle Transcription Factors SBF and MBF
Iyer et al., Nature 409: 533 (2001)
Paper presents
The use of CHIP and DNA microarrays to define the genomic binding sites of the SBF and MBF transcription factors in vivo
The SBF and MBF transcription factors are active in the initiation of the cell division cycle (G1/S) in yeast
A few target genes of SBF and MBF are known but the precise roles of these two transcription factors are unknown
The two transcription factors are heterodimers containing the same Swi6 subunit and a DNA binding subunit
MBF is a heterodimer of Mbp1 and Swi6
SBF is a heterodimer of Swi4 and Swi6

14. Genomic targets of SBF and MBF
Genoom Biologie
Prof. M. Zabeau
Genomic targets of SBF and MBF
Figure 3 Genomic targets of SBF and MBF. Percentile ranks of intergenic fragments that meet selection thresholds are inicated (blue–yellow colour scale). Loci with  70% overall nucleotide sequence identity to another yeast locus (potentially crosshybridizing) are indicated (closed circles). The combination of Cy3 and Cy5 labelled probes, the antibody used for IP (if used) and the culture conditions for each experiment are summarized (left panel). Experiments 9, 10, 17 and 18 involved independent crosslinking and IPs. DNA microarrays that included all yeast ORFs and other features, in addition to the intergenic fragments, were used for experiments 3, 8, 13 and 14.
Reprinted from: Iyer et al., Nature 409: 533 (2001)
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15. In Vivo Targets of SBF and MBF
The CHIP experiments identified
163 possible targets of SBF
87 possible targets of MBF
43 possible targets of both factors
Support for the possible in vivo targets
Most of the genes downstream of the putative binding sites peak in G1/S
Target genes are highly enriched for functions related to DNA replication, budding and the cell cycle
In vivo binding sites are highly enriched for sequences matching the defined consensus binding sites
Reprinted from: Iyer et al., Nature 409: 533 (2001)

16. Expression Profiles of SBF and MBF Targets
Genoom Biologie
Prof. M. Zabeau
Transcriptome data for synchronized cell cultures
Expression Profiles of SBF and MBF Targets
Figure 4 Expression profiles of SBF and MBF targets. a, Expression patterns of SBF and MBF targets are indicated (red–green colour scale). Cell-cycle data are from ref. 12 and sporulation data are from ref. 18. The stages of the cell cycle are: M/G1, yellow; G1, green; S, blue; S/G2l, red; and G2/M, orange. Yellow boxes indicate the presence of consensus binding sites in the intergenic sequences upstream of each ORF (right), and the median percentile rank in IPs of the upstream sequences is also indicated (blue–yellow colour scale), as in Fig. 3. For each set of targets, the top panel contains cell-cycle regulated genes, the bottom panel contains genes that are members of divergently transcribed pairs in which the other member was cell-cycle regulated, and the middle panel contains the remainder of the non-cell-cycle regulated genes. b, Average expression profiles of the cell-cycle regulated targets of SBF and MBF, computed by averaging the log 2 (Cy5/Cy3) ratios. Note the specific induction of MBF targets during sporulation.
Reprinted from: Iyer et al., Nature 409: 533 (2001)
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17. Expression Profiles of SBF and MBF Targets
Why are two different transcription factors used to mediate identical transcriptional programmes during the cell-division cycle in yeast?
A possible answer is suggested by differences in the functions of the genes that they regulate
Many of the targets of SBF have roles in cell-wall biogenesis and budding
25% of the MBF target genes have known roles in DNA replication, recombination and repair
The results support a model in which
SBF is the principal controller of membrane and cell-wall formation
MBF primarily controls DNA replication
The need for DNA replication and membrane / cell-wall biogenesis may be different in the mitotic and meiotic cell cycle
Reprinted from: Iyer et al., Nature 409: 533 (2001)

18. A high-resolution map of active promoters in the human genome
Kim et. al., Nature 436: (2005)
Paper presents
a genome-wide map of active promoters in human fibroblast cells
determined by experimentally locating the sites of RNA polymerase II preinitiation complex (PIC) binding
map defines 10,567 active promoters corresponding to
6,763 known genes
>1,196 un-annotated transcriptional units
Global view of functional relationships in human cells between
transcriptional machinery
chromatin structure
gene expression

19. Identification of active promoters in the human genome
Genoom Biologie
Prof. M. Zabeau
Identification of active promoters in the human genome
Microarrays cover
All non-repeat DNA at 100 bp resolution
Pol II preinitiation complex (PIC)
RNA polymerase II
transcription factor IID
general transcription factors
ChIP of PIC-bound DNA
monoclonal antibody against TAF1 subunit of the complex (TBP associated factor 1 )
FIGURE 1. Identification and characterization of active promoters in the human genome.
a, Outline of the strategy used to map TFIID-binding sites in the genome.
Reprinted from: Kim et. al., Nature 436: (2005)
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20. Results from TFIID ChIP-on-chip analysis
Genoom Biologie
Prof. M. Zabeau
Results from TFIID ChIP-on-chip analysis
FIGURE 1. Identification and characterization of active promoters in the human genome.
b, A representative view of the results from TFIID ChIP-on-chip analysis. Top panel, the logarithmic ratio (log2R) of hybridization intensities between TFIID ChIP DNA and a control DNA. Middle panel, RefSeq gene annotation. Bottom panel, a close-up view of two replicate sets of TFIID ChIP-on-chip hybridization signals around the 5' end of the TCFL1 gene. Arrows indicate the position of the TFIID-binding site determined by a peak-finding algorithm.
Reprinted from: Kim et. al., Nature 436: (2005)
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21. Characterization of active promoters
Genoom Biologie
Prof. M. Zabeau
Characterization of active promoters
Matched the 12,150 TFIID-binding sites to
the 5' end of known transcripts in transcript databases
87% of the PIC-binding sites were within 2.5 kb of annotated 5' ends of known messenger RNAs
8,960 promoters were mapped
within annotated boundaries of 6,763 known genes in the EnsEMBL genes
FIGURE 1. Identification and characterization of active promoters in the human genome.
d, e, Venn diagrams showing the number of identified promoters that matched EnsEMBL genes (d) or promoters annotated in DBTSS (e).
Reprinted from: Kim et. al., Nature 436: (2005)
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22. The chromatin-modification features of the active promoters
Genoom Biologie
Prof. M. Zabeau
The chromatin-modification features of the active promoters
Validation of active promoters
ChIP-on-chip using an anti-RNAP antibody
ChIP-on-chip analysis using
anti-acetylated histone H3 (AcH3) antibodies
anti-dimethylated lysine 4 on histone H3 (MeH3K4) antibodies
known epigenetic markers of active genes
FIGURE 2. The chromatin-modification features of the active promoters.
a, Logarithmic ratios of the ChIP-on-chip hybridization intensities (log2R) of probes from 0.5 kb upstream to 0.5 kb downstream of the identified TFIID-binding sites for TFIID, RNAP, AcH3 and MeH3K4 are plotted in a yellow−blue colour scale for 9,328 transcript-matched promoters. The bottom panel shows the colour scale with corresponding log2R values.
Reprinted from: Kim et. al., Nature 436: (2005)
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23. TFIID, RNAP, AcH3 and MeH3K4 profiles on the promoter of RPS24 gene
Genoom Biologie
Prof. M. Zabeau
TFIID, RNAP, AcH3 and MeH3K4 profiles on the promoter of RPS24 gene
FIGURE 2. The chromatin-modification features of the active promoters.
b, A detailed view of TFIID, RNAP, AcH3 and MeH3K4 profiles on the promoter of RPS24 gene.
Reprinted from: Kim et. al., Nature 436: (2005)
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24. Additional findings Promoters of non-coding transcripts
Genoom Biologie
Prof. M. Zabeau
Additional findings
Promoters of non-coding transcripts
Are very similar to promoters of protein coding genes
Promoters of novel genes
Estimate 13% of human genes remain to be annotated in the genome
Clustering of active promoters
co-regulated genes tend to be organized into coordinately regulated domains
Genes using multiple promoters
Reprinted from: Kim et. al., Nature 436: (2005)
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25. Multiple promoters in human genes
Genoom Biologie
Prof. M. Zabeau
Multiple promoters in human genes
WEE1 gene locus
Two different transcripts with alternative 5’ends
Encoding different proteins
Two different TFIID-binding sites- two promoters
Differential transcription during the cell cycle
FIGURE 3. Use of multiple promoters by human genes.
a, Annotation of the WEE1 gene locus and the corresponding TFIID-binding profile. Black bars over the first and second exons in transcripts indicate the positions of the primers used for analysis of each transcript, using real-time quantitative PCR with reverse transcription (RT−PCR). b, RT−PCR analysis of NM_ and AK transcripts in an asynchronous population of IMR90 cells. c, Real-time quantitative RT−PCR analysis of NM_ and AK transcripts in cell-cycle synchronized populations of IMR90 cells. Transcript levels observed for each cell-cycle phase were normalized to the level observed in the asynchronous population. Error bars represent standard deviation.
Reprinted from: Kim et. al., Nature 436: (2005)
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26. The transcriptome of a cell line
Genoom Biologie
Prof. M. Zabeau
The transcriptome of a cell line
Functional relationship between transcription machinery and gene expression
correlated genome-wide expression profiles with PIC promoter occupancy
Four general classes of promoters
Actively transcribed genes
Weakly expressed genes
Weakly PIC bound genes
Inactive genes
FIGURE 4. Four distinct classes of promoters define the transcriptome of IMR90 cells.
a, A matrix describes the distribution of genes defined by expression and PIC occupancy on the promoter. b, c, Matrices showing the percentages of genes associated with AcH3 (b) or MeH3K4 (c) modification for each of the four classes of genes. Italicized numbers in some boxes represent extrapolation from the 29 ENCODE regions.
Reprinted from: Kim et. al., Nature 436: (2005)
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27. Genome-Wide Distribution of ORC and MCM Proteins in yeast: High-Resolution Mapping of Replication Origins
Wyrick et. al., Science, 294, 2357 (2001)
Paper presents
Genome-wide location analysis to map the DNA replication origins in the 16 yeast chromosomes by determining the binding sites of prereplicative complex proteins

28. Chromosome Replication In Eukaryotic Cells
initiates from origins of replication distributed along chromosomes
Origins of replication comprise autonomously replicating sequences (ARS)
ARS contain an 11-bp ARS consensus sequence (ACS)
Essential for replication initiation
Recognized by the Origin Recognition Complex (ORC)
The majority of sequence matches to the ACS in the genome do not have ARS activity
Prereplicative complexes at replication origins comprise
Origin Recognition Complex (ORC) proteins
Minichromosome Maintenance (MCM) proteins
Reprinted from: Wyrick et. al., Science, 294, 2357 (2001)

29. Prereplicative Complexes At Origins Of Replication
Genoom Biologie
Prereplicative Complexes At Origins Of Replication
Prof. M. Zabeau
The complexities of duplication. The proteins that form the pre-replication complex (pre-RC) required for the initiation of DNA replication. The ORC binds to origins of replication (oris) in the chromosomes and establishes docking sites for the other protein components, such as MCM proteins, of the pre-RC. In metazoan species, geminin, which is degraded during mitosis, inhibits the activity of Cdt1, which is necessary for binding of MCM proteins to the origins of replication.
Reprinted from: Stillman, Science, 294, 2301(2001)
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30. ORC- and MCM-binding sites compared with known ARSs
Genoom Biologie
Prof. M. Zabeau
ORC- and MCM-binding sites compared with known ARSs
High degree of correlation between MCM and ORC binding sites and known ARSs
Correct identification of 88% known ARSs
The method can accurately identify the position of ARSs to a resolution of 1 kb or less
Figure 1. ORC and MCM binding to previously identified replication origins. Average binding ratios (blue/white) of ORC and MCM proteins to the known ARS-containing loci on chromosomes III and VI (ARS308 and ARS604 were not present on the arrays) and some randomly selected loci are shown. Random selection was accomplished with the "randbetween" function in Excel. The "i" preceding the locus name indicates the intergenic region to the right of the gene. Asterisks indicate randomly selected loci adjacent to or within 1 kb of a predicted origin. Data for other known origins are available in Web table 1 (18).
Reprinted from: Wyrick et. al., Science, 294, 2357 (2001)
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31. Genome-wide Location Of Potential Replication Origins
Genoom Biologie
Genome-wide Location Of Potential Replication Origins
Prof. M. Zabeau
Identification of 429 potential origins on the entire genome
Figure 2. Genome-wide location of potential replication origins. The genomic position of each probe present on the arrays is plotted to scale as a green bar (Web table 3) (18). The predicted origin-containing loci (pro-ARS) are plotted to scale as a red bar and named systematically (Web table 2) (18). Variations in width and apparent intensities of green or red color reflect different probe lengths, not hybridization ratios. Probes to Watson and Crick ORFs are plotted on the top and bottom rows; intergenic sequences are plotted on the center rows. Asterisks indicate known ARSs that were not identified.
Reprinted from: Wyrick et. al., Science, 294, 2357 (2001)
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32. Conclusions
The ChIP-based method identified the majority of origins found in the analysis of genome-wide replication timing in yeast
and provides direct, high-resolution mapping of potential origins
Similar approaches identified origins in other organisms
For example: Coordination of replication and transcription along a Drosophila chromosome
MacAlpine et al., Genes & Dev. 18: (2004)
Reprinted from: Wyrick et. al., Science, 294, 2357 (2001)

33. Functional Maps or “-omes”
Genes or proteins n
“Conditions”
ORFeome
Genes
Phenome
Mutational phenotypes
Transcriptome
Expression profiles
DNA Interactome
Protein-DNA interactions
Localizome
Cellular, tissue location
Interactome
Protein interactions
Proteome
proteins
After: Vidal M., Cell, 104, 333 (2001)

34. Global analysis of protein localization in budding yeast
Huh et. al., Nature 425, (2004)
Paper presents
An approach to define the organization of proteins in the context of cellular compartments involving
the construction and analysis of a collection of yeast strains expressing full-length, chromosomally tagged green fluorescent protein fusion proteins

35. Experimental Strategy
Systematic tagging of yeast ORFs with green fluorescent protein (GFP)
GFP is fused to the carboxy terminus of each ORF
Full length fusion proteins are expressed from their native promoters and chromosomal location
The collection of yeast strains expressing GFP fusions was analyzed by
fluorescence microscopy to determine the primary subcellular localization of the fusion proteins
Defines 12 categories
co-localization with red fluorescent protein (RFP) markers to refine the subcellular localization
Defines 11 additional categories
Reprinted from: Huh et. al., Nature 425, (2004)

36. Construction of GFP fusion proteins
For each ORF a pair of PCR primers was designed
Homologous to the chromosomal insertion site
Matching a GFP – selectable marker construct
Yeast was transformed with the PCR products to generate
Strains expressing chromosomally tagged ORFs
Reprinted from: Huh et. al., Nature 425, (2004)

37. Representative GFP Images
Nucleus
Nuclear periphery ER
Bud neck
mitochondrion
Lipid particle
Reprinted from: Huh et. al., Nature 425, (2004)

38. GFP and RFP Co-localization Images
Nucleolar marker
Reprinted from: Huh et. al., Nature 425, (2004)

39. Global results Constructed ~6.000 ORF-GFP fusions
22 categories
Constructed ~6.000 ORF-GFP fusions
4.156 had localizable GFP signals (~75% of the yeast proteome)
Good concordance with data from earlier studies
GFP does not affect the location
Localized 70% of the new proteins
Major compartments: cytoplasm (30%) and the nucleus (25%)
20 other compartments: 44% of the proteins
Most the proteins can be located in discrete cellular compartments
Reprinted from: Huh et. al., Nature 425, (2004)

40. The proteome of the nucleolus
Detected 164 proteins in the nucleolus
Plus 45 identified in other studies
Data are consistent with MS analysis of human Nucleolar proteins
Allows identification of yeast-human orthologs
Reprinted from: Huh et. al., Nature 425, (2004)

41. Transcriptional co-regulation and subcellular localization are correlated
33 transcription modules
Co-regulated genes
Reprinted from: Huh et. al., Nature 425, (2004)

42. Conclusion The high-resolution, high-coverage localization data set
represents 75% of the yeast proteome
classified into 22 distinct subcellular localization categories,
Analysis of these proteins
in the context of transcriptional, genetic, and protein–protein interaction data
provides a comprehensive view of interactions within and between organelles in eukaryotic cells.
helps reveal the logic of transcriptional co-regulation
Reprinted from: Huh et. al., Nature 425, (2004)

43. Recommended reading DNA-interactome
Genome-Wide Location of DNA Binding Proteins
Ren et. al., Science, 290, 2306 (2000)
Map of active promoters in the human genome
Kim et. al., Nature 436: (2005)
Global analysis of protein localization in yeast
Huh et. al., Nature 425, (2004)

44. Further reading Genome-Wide Location of DNA Binding Proteins
Genomic Binding Sites of the Yeast Cell-cycle Transcription Factors SBF and MBF
Iyer et al., Nature 409: 533 (2001)
High-Resolution Mapping of Replication Origins
Wyrick et. al., Science, 294, 2357 (2001)