1. Regulation of transcript stability and post-transcriptional processes – from yeast to human Reut Shalgi Weizmann Institute of Science, Israel RSMD workshop Uppsala 11/2006

2. The central Dogma Transcription mRNA Translation Protein DNA

3. The central Dogma Transcription mRNA Translation Protein DNA Transcription miRNA (ncRNAs) Degradation

4. Post transcriptional control Functional sequence motifs in 3’ UTRs stability associated motifs (Shalgi et al. Genome Biology 2005) miRNA regulation (Xi et al. Clin Cancer Res. 2006) Transcription Translation Protein DNA Transcription miRNA Degrad ation mRNA

5. A catalog of stability-associated sequence elements in 3' UTRs of yeast mRNAs Shalgi R, Lapidot M, Shamir R and Pilpel Y. Genome Biology 2005

6. The cell transcriptome gene expression profile AAATCGGAATTGGAGGTATCGGATCTTGTTGAATATCCACCAATGTCTTACCCCTGTATTTTA… promoter5’ UTRProtein coding region3’ UTR Balance between transcription activation and transcript degradation AAAAAAAAAAA… TGTATAAT time Expression level

7. mRNA transcription and degradation – both determine the cell transcriptome genes conditions Promoter sequence AAATCGGAATTGGAGGTATCGGAT CTTGTTGAATATCCACCAATGTCT TACCCCTGTATTTTAACAAGAGTT TACGGAATACTGTTATATGGTTAA AGGTGTGGACGCCTTGAAGGTTTA CCTTACCGAATGACACCTGAATAT TACAATAGTCAGATCGAATAACGT TCTGGAATATGGCGTTATCCAAAG TTAGCGCAGTTTTCCGATGGTCCA ATGTAATCATTAGAAATAGTAAAA ACTGTGTAATGGTAAAGATTGTGT CACTGGAAAAAAACTGCTACAAAT AATAAATAAATAAAAAAATACGAA AGCACAGTACTACGGGTGCCTCCA CAAATAGATAAGAAACCAAGCGGA GACATGCGTTTAGACTACGGTGAG GATATAAATTATTTATACAACCAG ACCTACGGTATATAAAAGAGCATC TAGTTTACCTGTTATGATGAATGG ACATTCGCTACATCTACGGATCTT ACTCTCTATTTGTTAAAAAAAATT ACAAAGAGAACTACTGCATATATA AATAACATACCTACGGAATAACAT ACCAATCACATCGGTCGCGGAAG CCGTCTGTGTTTCAGCATGATTG AATCTTGAAATTGAAGAGGTGAC TACTGTTTTCGTCTCAGCAGCTC CAGTACTGGTAGTTGTCTCAGCA GCTCCAGTATTGGTTGTTGTCTC ACTGGTAGCACTGTTCATTTTAG AGCTGACAGACTCTTCATTCGTA GTCTGTGGCCTCCATGTTGGATA GACCGTAACAACATCATTCACAG TAGCCGTGGCCGTCGAAACAATG GCAGGTGAAGCAGTTTCGGAACA CACACCAGATTCGCAGGAAGTAA CAGTAACTAGCGTAGTTTGTTGC CTCGATTCTGTGGTGGAAATAGG ACACCATGTCGTGTATTCTGTGG TAACGCCGTTAATAGTAGCAGTG CTTATAGATACAATGACCAATCA CATCGGTCGCGGAAGCCGTCTGT GTTTCAGCATGATTGAATCTTGA AATTGAAGAGGTGACTACTGTTT TCGTCTCAGCAGCTCCAGTACTG GTAGTTGTCTCAGCAGCTCCAGT 3’ UTR sequence ?

8. Functional sequence motifs in 3’ UTRs Finding sequence elements associated with transcript stability derived from 3’ UTRs of yeast mRNAs 3’ UTRs were previously inferred to be involved in controlling: Transcript Stability Sub-cellular localization (Keursten & Goodwin, Nature Reviews Gen. 2003) Why 3’ UTRs ?

9. Discovery of stability-associated motifs in yeast 3’ UTRs The data ACCAATCACATCGGTCGCGGAAG CCGTCTGTGTTTCAGCATGATTG AATCTTGAAATTGAAGAGGTGAC TACTGTTTTCGTCTCAGCAGCTC CAGTACTGGTAGTTGTCTCAGCA GCTCCAGTATTGGTTGTTGTCTC ACTGGTAGCACTGTTCATTTTAG AGCTGACAGACTCTTCATTCGTA GTCTGTGGCCTCCATGTTGGATA GACCGTAACAACATCATTCACAG TAGCCGTGGCCGTCGAAACAATG GCAGGTGAAGCAGTTTCGGAACA CACACCAGATTCGCAGGAAGTAA CAGTAACTAGCGTAGTTTGTTGC CTCGATTCTGTGGTGGAAATAGG ACACCATGTCGTGTATTCTGTGG GGAGTTGTCTCAGCAGCTCCAGT 3’ UTR sequence the “virtual northern” Data by Hurowitz & Brown, Genome Biol., 2003 Yeast mRNA half lives (Calculated from mRNA Decay profiles) Taken from Wang, PNAS 2002 Time (min) Expression level

10. Discovery of stability-associated motifs in yeast 3’ UTRs TCATTGAAAGCTTCCCTTATCCCTTCCA… TCTCCTACAACGCCTGAGGAGGACCAGA… GCACCATCCCTCCTACAACTAACTACCAG… TGAGCTCATTAAGCTTCCCAGCACAACT… AAGCTTCC CCTACAAC 1. Exhaustive kmer enumeration (8<=k<=12)  A List of all kmers in the 3’ UTRs for each kmer, a list of the gene that contain it in their 3’ UTR: AAGCTTCC gene1 AAGCTTCC gene2 AAGCTTCC gene22 AAGCTTCC … # CCTACAAC gene5 CCTACAAC gene9 CCTACAAC … #

11. Functional sequence motifs in 3’ UTRs Finding sequence elements associated with transcript stability derived from 3’ UTRs of yeast mRNAs AAGCTTCC CCTACAAC Genome average half life = 26 min Time (min) Expression level Average half life = 9 min Average half life = 38 min

12. Discovery of stability-associated motifs in yeast 3’ UTRs 2. Kmer Stability p-value calculation: Mean transcript half-life is 26.3 minutes. Do the genes that contain the kmer in their 3’ UTR have a significantly lower/higher mean half-life? 3. Controlling for multiple hypotheses: using the FDR - False Discovery Rate A list of significant kmers Motifmean ½ life#genes p-value AAGCTTCC 26 min 0.3 CCTACAAC 8 min 10 -6 … 200 30 AAAAAAAA 46 min 80 10 -11

13. Discovery of stability-associated motifs in yeast 3’ UTRs 4. Creating motifs from kmers by clustering: AAGGGCTT AAGGCCTC AGGGCTT AAGGGCTC AAGGGCTA AGGCCTT AAGGCCT GGCGCCTT GCACCTT GGCGCCT GGCCCCTT GGCACCTT GCCCCTT TTCCTTCC TTCCATC TTCCATCT TTCCATCC TTCCTTC TCCTTCC

14. A catalog of stability-associated motifs Motif M1 Mean half life: 16 min. Number of genes: 640 P-value: 1.2*10 -50 Motif M11 Mean half life: 46.5 min. Number of genes: 89 P-value: 1*10 -300 time Expression level

15. A catalog of stability-associated motifs Motif M1 Mean half life: 16 min. Number of genes: 640 P-value: 1.2*10 -50 Motif M11 Mean half life: 46.5 min. Number of genes: 89 P-value: 1*10 -300

16. A catalog of stability-associated motifs For the first time, a catalog of stability-associated motifs was assembled 53 motifs: 40 de-stabilizing 13 stabilizing For comparison, the current promoter motif catalog (Harbison et al.) contains 102 motifs. ~1700 genes contain a stability-associated motif Out of those, 850 contain both a stability motif, and a promoter motif

17. Many stability motifs are evolutionary conserved In other yeasts 16 were found to be significantly conserved S. kudriavzevii S. paradoxus S. cerevisiae M24 220 genes 56 105 47 Highly Conserved P-value=0.009

18. Evolutionary conservation remains all the way to human Comparing to mammalian 3’ UTR motifs (Xie et al. Nature, 2005) 11 were significantly similar to a mammalian conserved motif YEAST HUMAN

19. Functional enrichment cell growth and/or maintenance7.32*10 -5 cell organization and biogenesis2.52*10 -5 protein biosynthesis4.22*10 -5 nucleic acid metabolism7.27*10 -6 transcription from Pol II promoter6.47*10 -4 protein modification4.69*10 -4 Processp-value M1 M24 ribosome biogenesis and assembly3.87*10 -7 rRNA processing3.88*10 -6 protein biosynthesis3.03*10 -5 nucleic acid metabolism1.42*10 -4 RNA processing1.32*10 -6 transcription from Pol I promoter1.86*10 -7

20. TypeTranscript regulation Number of genes Enriched biological processes (GO category) ITranscription initiation level regulation 2297(~35%(transport IIDegradation level regulation 793(~12%(RNA modification, protein modification, nucleic-acid metabolism IIITranscription initiation and degradation level regulation 846(~13%)cell growth and maintenance, cell wall organization and biogenesis, protein biosynthesis Stability affecting Motifs are complementary to promoter motifs Integrating Harbison et al.’s data on promoter motifs Three potential modes of regulation: stop M24

21. Stability affecting Motifs are complementary to promoter motifs M24 ribosome biogenesis and assembly3.87*10 -7 rRNA processing3.88*10 -6 protein biosynthesis3.03*10 -5 nucleic acid metabolism1.42*10 -4 RNA processing1.32*10 -6 transcription from Pol I promoter1.86*10 -7 Processp-value Rap1

22. 24 6 2 4 6 Stability affecting Motifs are complementary to promoter motifs 0 1 Time points Normalized expression All protein biosynthesis related genes Checked their steady-state expression profiles in a set of 40 conditions M24 Rap1 1082 282 21 #genes √ √ √ √ X X XX

23. 3’ UTR motifs associated with sub-cellular localization Sub cellular clustering score & p-value Uses GO annotation (cellular component) And a similarity measure by (Lord, Bioinformatics, 2003) The SCC (Sub-Cellular Clustering) score Cellular component SCC=0.5SCC=0.05 mitochondria Mitochondria inner membrane

24. 3’ UTR motifs associated with sub-cellular localization The 3’ UTR yeast motif SCC score: 0.289 SCC p-value: < 10 -6 Associated with 610 genes Out of which 260 genes are known to be Localized to the Mitochondria Example – a putative mitochondrial zipcode Sub Cellular Clustering score:

25. endomembrane system NO 8 3.9E-050.43M13 endoplasmic reticulum YES (p-val<1E-3)721E-060.11M22 enriched termsconservation#targets SCC p- value SCC score logoname mitochondrial inner & outer membrane translocase complex mitochondrial inner & outer membrane mitochondrial membrane mitochondrial ribosome mitochondrial matrix mitochondrial intermembrane space mitochondrion YES (p-val<1E-3) 610<1E-60.289M1 A catalog of 23 motifs associated with sub-cellular localization

26. Very few experimentally verified motifs: M1: CYC1 (Russo, Mol Cell Biol, 93) M24: w as suggested to be the binding site for Puf4p (Gerber, PLOS, 2004) Foat B, PNAS, Dec. 2005 Mitochondrial Motif: was suggested to be the binding site for Puf3p (Gerber, PLOS, 2004, Gerber, PNAS, 2006) the co-translational import model of mitochondrial genes ( Kaltimbacher V, RNA, Jul. 2006) Support from the literature

27. Summary – part 1 A first large scale catalog of 3’ UTR motifs that are directly associated with effects on transcript stability (and sub-cellular localization) in yeast. 53 motifs: 40 de-stabilizers, 13 stabilizers many of them are conserved in other yeasts 11 are significantly similar to recently published mammalian conserved 3’ UTR motifs intricate relationship with promoter motifs http://longitude.weizmann.ac.il/3UTRMotifs/ A first step towards filling the gap of transcript level regulation

28. Post transcriptional control Functional sequence motifs in 3’ UTRs stability associated motifs (Shalgi et al. Genome Biology 2005) miRNA regulation (Xi et al. Clin Cancer Res. 2006) Transcription Translation Protein DNA Transcription miRNA Degrad ation mRNA

29. Differentially Regulated Micro-RNAs by Tumor Suppressor p53 in Colon Cancer Xi Y, Shalgi R, Fodstad O, Pilpel Y, Ju J. Clin Cancer Res. 2006

30. Background – p53 p53 is a tumor suppressor. regulates DNA repair, cell senescence, appoptosis, and more. Is a critical inhibitor of tumour development is the most frequently mutated gene in human cancers p53 is a TF.

31. Background – microRNAs (miRs) Small (~21 nt) RNAs Post-transcriptional silencing: Regulate mRNA degradation and translation inhibition Through RISC (RNA induced silencing complex)

32. Identification of miRNAs regulated by p53: Cancer cells: HCT-116 +/+ and p53 - cells show differential miRNA expression using miRNA microarray: 43 miRs were downregulated 11 were upregulated in the wt (vs. the mutant) miRNAs that are transcriptionally regulated by p53 p53+ p53-

33. Looking for p53 binding sites in miRNA promoters p53 binding site search: 0- 3 miRNAs that are transcriptionally regulated by p53 (Wei CL, Cell, Jan 2006)

34. List of p53 binding sites in promoters of the 10 most highly variable miRNAs 9 out of the 10 had a site in their promoter miRNAs that are transcriptionally regulated by p53 miRNApos.gap len.SiteScore hsa-let-7b8280AGCCATGTCT..CTTCTTGTCT87.56

35. Looking at all known miRNAs in the database (326): 130 (~40%) have a putative p53 binding site in their promoter control: 1000 sets of reshuffled promoters: p-value < 0.001 Global analysis of p53 sites in miRNAs promoters

36. A highly significant enrichment for p53 binding sites in miRNA upstream regions Is there a specific tendency for p53 to regulate miRNAs? p53 as a hub in the signaling network another mechanism of p53 global control of cellular processes under stress p53 regulation of miRNAs

37. Summary – transcript stability mechanisms S. cereviciae de-adenylation dependant degradation Stabilizing/de-stabilizing RNA binding proteins. No Dicer & RISC 3’ UTR motifs (perhaps also 5’ UTR) Higher organisms Both de-adenylation dependant deg. And miRNA Dicer & RISC 3’ UTR motifs Protein DNA miRNA mRNA

38. Thanks ! Tzachi Pilpel Moshe Oren Ron Shamir Michal Lapidot Ophir Shalem and all the other Pilpel lab members Collaborators: P53 miR project: Ju group Cancer Research Institute, Mobile, Alabama