regulation of transcript stability and post-transcriptional processes – from yeast to human reut...

Regulation of transcript stability and post-transcriptional

processes

– from yeast to human

Reut ShalgiWeizmann Institute of Science, Israel

RSMD workshopUppsala11/2006

The central Dogma

Transcription

mRNA

Translation

ProteinDNA

The central Dogma

Transcription

mRNA

Translation

ProteinDNA

Transcrip

tion

miRNA (ncRNAs)

De

gra

da

tion

De

gra

da

tion

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

ProteinDNA

Transcrip

tion

miRNA

Deg

rada

tion

Deg

radatio

n

mRNA

A catalog of stability-associated sequence

elements in 3' UTRs ofyeast mRNAs

Shalgi R, Lapidot M, Shamir R and Pilpel Y. Genome Biology 2005

The cell transcriptome

gene expression profile

AAATCGGAATTGGAGGTATCGGATCTTGTTGAATATCCACCAATGTCTTACCCCTGTATTTTA…

promoter 5’ UTR Protein coding region 3’ UTR

Balance between transcription activation and transcript degradation

AAAAAAAAAAA…TGTATAAT

time

Expre

ssio

n level

mRNA transcription and degradation –

both determine the cell transcriptome

genes

conditionsPromoter sequence

AAATCGGAATTGGAGGTATCGGATCTTGTTGAATATCCACCAATGTCTTACCCCTGTATTTTAACAAGAGTTTACGGAATACTGTTATATGGTTAAAGGTGTGGACGCCTTGAAGGTTTACCTTACCGAATGACACCTGAATATTACAATAGTCAGATCGAATAACGTTCTGGAATATGGCGTTATCCAAAGTTAGCGCAGTTTTCCGATGGTCCAATGTAATCATTAGAAATAGTAAAAACTGTGTAATGGTAAAGATTGTGTCACTGGAAAAAAACTGCTACAAATAATAAATAAATAAAAAAATACGAAAGCACAGTACTACGGGTGCCTCCACAAATAGATAAGAAACCAAGCGGAGACATGCGTTTAGACTACGGTGAGGATATAAATTATTTATACAACCAGACCTACGGTATATAAAAGAGCATCTAGTTTACCTGTTATGATGAATGGACATTCGCTACATCTACGGATCTTACTCTCTATTTGTTAAAAAAAATTACAAAGAGAACTACTGCATATATAAATAACATACCTACGGAATAACAT

ACCAATCACATCGGTCGCGGAAGCCGTCTGTGTTTCAGCATGATTGAATCTTGAAATTGAAGAGGTGACTACTGTTTTCGTCTCAGCAGCTCCAGTACTGGTAGTTGTCTCAGCAGCTCCAGTATTGGTTGTTGTCTCACTGGTAGCACTGTTCATTTTAGAGCTGACAGACTCTTCATTCGTAGTCTGTGGCCTCCATGTTGGATAGACCGTAACAACATCATTCACAGTAGCCGTGGCCGTCGAAACAATGGCAGGTGAAGCAGTTTCGGAACACACACCAGATTCGCAGGAAGTAACAGTAACTAGCGTAGTTTGTTGCCTCGATTCTGTGGTGGAAATAGGACACCATGTCGTGTATTCTGTGGTAACGCCGTTAATAGTAGCAGTGCTTATAGATACAATGACCAATCACATCGGTCGCGGAAGCCGTCTGTGTTTCAGCATGATTGAATCTTGAAATTGAAGAGGTGACTACTGTTTTCGTCTCAGCAGCTCCAGTACTGGTAGTTGTCTCAGCAGCTCCAGT

3’ UTR sequence

?

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 StabilitySub-cellular localization

(Keursten & Goodwin, Nature Reviews Gen. 2003)

Why 3’ UTRs ?

Discovery of stability-associated motifs in yeast 3’ UTRs

The data

ACCAATCACATCGGTCGCGGAAGCCGTCTGTGTTTCAGCATGATTGAATCTTGAAATTGAAGAGGTGACTACTGTTTTCGTCTCAGCAGCTCCAGTACTGGTAGTTGTCTCAGCAGCTCCAGTATTGGTTGTTGTCTCACTGGTAGCACTGTTCATTTTAGAGCTGACAGACTCTTCATTCGTAGTCTGTGGCCTCCATGTTGGATAGACCGTAACAACATCATTCACAGTAGCCGTGGCCGTCGAAACAATGGCAGGTGAAGCAGTTTCGGAACACACACCAGATTCGCAGGAAGTAACAGTAACTAGCGTAGTTTGTTGCCTCGATTCTGTGGTGGAAATAGGACACCATGTCGTGTATTCTGTGGGGAGTTGTCTCAGCAGCTCCAGT

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)

Expre

ssio

n level


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 gene22AAGCTTCC … AAGCTTCC … AAGCTTCC … AAGCTTCC … #CCTACAAC gene5 CCTACAAC gene9 CCTACAAC … CCTACAAC … CCTACAAC … CCTACAAC … #

Functional sequence motifs in 3’ UTRs

Finding sequence elements associated with transcript stability derived from 3’ UTRs of

yeast mRNAs

AAGCTTCCCCTACAAC

Genome average half life = 26 min

Time (min)

Expre

ssio

n level

Average half life = 9 min

Average half life = 38 min


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

Motif mean ½ life #genes p-value

AAGCTTCC

26 min 0.3

CCTACAAC 8 min 10-6

…

20030

AAAAAAAA

46 min 80 10-11


4. Creating motifs from kmers by clustering:

AAGGGCTT

AAGGCCTC

AGGGCTT

AAGGGCTC

AAGGGCTAAGGCCTT

AAGGCCT

GGCGCCTT

GCACCTT

GGCGCCT

GGCCCCTT

GGCACCTT

GCCCCTT

TTCCTTCC

TTCCATC

TTCCATCT

TTCCATCC

TTCCTTC

TCCTTCC

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

Exp

ressio

n level


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


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

Many stability motifs are evolutionary conserved

In other yeasts

16 were found to be significantly conserved

S. kudriavzeviiS. kudriavzevii

S. paradoxusS. paradoxus

S. S. cerevisiaecerevisiae

M24220 genes

56

105

47Highly

ConservedP-value=0.009

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

Functional enrichment

cell growth and/or maintenance7.32*10-5

cell organization and biogenesis 2.52*10-5

protein biosynthesis 4.22*10-5

nucleic acid metabolism 7.27*10-6

transcription from Pol II promoter 6.47*10-4

protein modification 4.69*10-4

Process p-valueM1

M24ribosome biogenesis and assembly 3.87*10-7

rRNA processing 3.88*10-6



RNA processing 1.32*10-6

transcription from Pol I promoter 1.86*10-7

Type Transcript regulation

Number of genes

Enriched biological processes (GO category)

I Transcription initiation level regulation

2297(~35%( transport

II Degradation level regulation

793(~12%( RNA modification, protein modification, nucleic-acid metabolism

III Transcription initiation and degradation level regulation

846(~13%) cell growth and maintenance, cell wall organization and biogenesis, protein biosynthesis

Stability affecting Motifs are Stability affecting Motifs are complementary to promoter complementary to promoter

motifs motifs

Integrating Harbison et al.’s data on promoter motifsThree potential modes of regulation:

stop

stop

stop

M24


motifsmotifs

M24ribosome biogenesis and assembly 3.87*10-7

rRNA processing 3.88*10-6



RNA processing 1.32*10-6

transcription from Pol I promoter 1.86*10-7

Process p-value

Rap1

2 4 62 4 62 4 62 4 6


motifsmotifs

-1

0

1

Time points

No

rmal

ized

exp

ress

ion

All protein biosynthesis related genesChecked their steady-state expression profiles in a set of 40

conditions

M24

Rap1

10 82 282 21#genes

√

√

√√X X

X X

3’ UTR motifs associated 3’ UTR motifs associated with sub-cellular with sub-cellular

localizationlocalization

Sub cellular clustering score & p-value Uses GO annotation (cellular component) And a similarity measure by (Lord, Bioinformatics,

2003) The SCC (Sub-Cellular Clustering) The SCC (Sub-Cellular Clustering) score score

Cellular component Cellular componentSCC=0.5 SCC=0.05

mitochondria

Mitochondria inner membrane

3’ UTR motifs associated 3’ UTR motifs associated with sub-cellular with sub-cellular


The 3’ UTR yeast motif

SCC score: 0.289SCC p-value: < 10-6

Associated with 610 genesOut of which 260 genes are

known to be Localized to the Mitochondria

Example – a putative mitochondrial zipcodeExample – a putative mitochondrial zipcode

Sub Cellular Clustering score:

endomembrane system

NO83.9E-050.43M13

endoplasmic reticulumYES

(p-val<1E-3)721E-060.11M22

enriched termsconservation#targetsSCC 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 A catalog of 23 motifs associated with sub-cellular associated with sub-cellular


Very few experimentally verified motifs:

M1: CYC1 (Russo, Mol Cell Biol, 93)

M24: was suggested to be thebinding 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

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

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

ProteinDNA

Transcrip

tion

miRNA

Deg

rada

tion

Deg

radatio

n

mRNA

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

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.

Background – microRNAs (miRs)

Small (~21 nt) RNAs Post-transcriptional

silencing: Regulate mRNA

degradation and translation

inhibition Through RISC (RNA

induced silencing complex)

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-

Looking for p53 binding sites in miRNA promotersp53 binding site search:

0 -3

miRNAs that are transcriptionally regulated by

p53

(Wei CL, Cell, Jan 2006)

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

miRNA pos. gap len. SiteScorehsa-let-7b 828 0 AGCCATGTCT..CTTCTTGTCT87.56

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

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

Summary – Summary – transcript stability transcript stability mechanisms 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

ProteinDNA

miRNA

mRNA

Thanks !

Tzachi Pilpel Moshe Oren Ron Shamir

Michal Lapidot Ophir Shalem and all the other Pilpel lab

membersCollaborators:

P53 miR project:Ju group

Cancer Research Institute,Mobile, Alabama

regulation of transcript stability and post-transcriptional processes – from yeast to human reut...

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