Traditionally the gene expression pathway was regarded as being composed of independent steps, from RNA transcription to protein translation. To-date there is increasing evidence for coupling between the different processes of the pathway, specifically between transcription and splicing. Given the extensive cross-talk between these processes, we derived a transcription-splicing integrated network. The nodes of the network included experimentally verified human proteins belonging to three groups of regulators: Transcription factors (TFs), splicing factors (SFs) and kinases. The nodes were wired by instances of predicted transcriptional and alternative splicing regulation. Analysis of the network indicated a pervasive cross-regulation among the nodes, specifically; SFs were significantly more often regulated by alternative splicing relative to the two other subgroups, while TFs were more extensively controlled by transcriptional regulation. In particular, we found a significant preference of specific pairs of TF-TF and SF-SF to regulate their target genes, SFs being the most regulated group via independent and combinatorial binding of SFs. Consistent with the extensive cross-regulation among the splicing and transcription factors, the subgroup of kinases within the network had the highest density of predicted phosphorylation sites. The prevalent regulation of the regulatory proteins was further supported by computational analysis of the protein sequences, demonstrating the propensity of these proteins to be highly disordered relative to other proteins in the human proteome. Overall, our systematic study reveals that an organizing principle in the logic of integrated networks favor the regulation of regulatory proteins by the specific regulation they conduct. Based on these results we propose a new regulatory paradigm, postulating that fine-tuned gene expression regulation of the master regulators in the cell is commonly achieved by cross-regulation.

1. A transcription-splicing integrated network
reveals pervasive cross-regulation among
regulatory proteins
Network Biology SIG
ISMB 2012
Long Beach CA
Idit Kosti
Computational Biology Lab
Technion, Haifa, Israel

2. Regulation of the gene expression pathway
DNA Promoter intron exon
Transcription
RNA
Splicing
Alternative Splicing
Protein Translation
P Phosphorylation
Posttranslational modification

3. Transcription
DNA Promoter intron exon
Transcription
• The first step leading to gene expression.
• Transcription is regulated by transcription
factors (TFs) that are bound to the promoter
region of the gene.

4. Alternative splicing
RNA
Alternative Splicing
• Alternative splicing (AS) creates a huge protein
variety from a small number of genes.
• 95% of the genes have at least one AS event.
• AS is regulated by splicing factors (SFs).

5. Phosphorylation
Protein Translation
P Phosphorylation
• Protein phosphorylation plays a significant role in
a wide range of cellular processes
• Phosphorylation occurs at phosphorylation sites
and facilitated by kinases.

6. In our network we focus on
transcription and alternative splicing
regulation in human

7. The splicing-transcription co-regulatory network
SF
20 Splicing Factors Transcription
SF (gene/protein)
regulation
TF
SF TF 90 Transcription Factors
(gene/protein)
K
K
147 Kinases
(gene only)
Kosti I., Radivojac P., Mandel-Gutfreund Y., An integrated regulatory network
reveals pervasive cross-regulation among transcription and splicing factors,
PLoS Computational Biology, in press.

8. Predicting TF binding sites using TRANSFAC
A [13 13 3 1]
TRANSFAC PSSMs C [13 39 5 53]
G [17 2 37 0]
T [11 0 9 0]
Predication of TFBS using PSSM Human TCGACGCCTCACGTGTTCCTCCTGG
and conservation Mouse ATCGCACTGCACGTGGGATCTGATC
Significant hits in promoter
region
TFBS table, UCSC genone broswer

9. The splicing-transcription co-regulatory network
SF
20 Splicing Factors Transcription
SF (gene/protein)
regulation
TF
SF TF 90 Transcription Factors
(gene/protein) Alternative Splicing
regulation
K
K
147 Kinases
(gene only)

10. Predicting SF binding sites using SFmap
sfmap.technion.ac.il
UCUU
Experimentally defined binding YCAY
motifs
YGCUKY
GAAGAA
Human UCGACGCCUUCCUUCUCUUUCCUCCU
Predication of SFBS using motif,
conservation and multiplicity Mouse AUCGCACUGUCUUAUCGGAUCUGAUC
Significant hits in AS region
Paz I. et al., Nucleic Acids Res. 2010

11. Regulation on AS events changes
according to event types
Cassette exon
Alternative 5’ splice site
Alternative 3’ splice site

12. How do we wire the network?
1 2 3 A X
X
3
2
X A
1

13. Our network behaves like a regulatory
network
Highly clustered Sparse
Sparseness=0.046
p-value =1.09e-61 Outdegree Frequency
Power law
outdegree distribution
Outdegree

14. Cross-regulation vs. Cross-talk regulation
TF
TF
SF K
cross-talk regulation (regulation across functional group)
cross-regulation (regulation within the functional group)

16. Transcription regulation is highest among
TFs
Transcription Regulation
pv= 1.2E-3 pv = 3.8E-7
Number of inedges
3654
SF TF Kinase pv < 0.05

18. Splicing regulation is highest among SFs
Splicing Regulation
pv= 2.7E-3
Number of inedges
pv= 2.3E-4
97
SF TF Kinase
P-value < 2.2e-16

19. Similar gene length, number of exons
and number of AS events
Gene length Number of exons per factor
20000 30000 40000
30
Number of exons per factor
25
Gene length (nt)
20
15
10000
10
5
0
0
SF TF Kinase SF TF Kinase
Frequency from target group
SFs
Number of alternative TFs
splicing events per factor Kinases
Number of alternative splicing events

20. Random networks showed insignificant
inedges density
Splicing regulation Transcription regulation
Inedge average
Inedge average
SF TF Kinase SF TF Kinase

21. Experimental binding data supports
splicing regulation trend
RNA
QKI
splicing
Transcription
activity
PTB
FOX2
SF2/ASF
0 2 4 6 8 10 12
-Log10(pvalue)

22. Cross regulation vs. cross-talk regulation
TF
TF
SF K

23. Same trend, different organisms
Transcription regulation
Human Drosophila Yeast
pv= 1.2e-3 pv= 9.2e-10
SF TF SF TF SF TF
Marbach et al. Genome Res. 2011 Pelechano et al., PLoS Genetics 2009

24. Same trend, different organisms
Splicing regulation
Guy Plaut
Human Drosophila
Number of inedges
pv= 2.3e-4 Number of inedges pv= 1.7e-11
SF TF SF TF

25. Screening using expressionshow for
Tissue specific networks data the
muscleregulatory behavior
same and heart tissues

26. Tissue specific networks show the
same regulatory behavior
Splicing Regulation Transcription Regulation
Number of inedges
Number of inedges
SF TF SF TF SF TF SF TF
40 TFs 11 SFs 33 TFs 14 SFs

27. The splicing-transcription co-regulatory network
SF
20 Splicing Factors Transcription
SF (gene/protein)
regulation
TF
SF TF 90 Transcription Factors
(gene/protein) Alternative Splicing
regulation
K
K
147 Kinases
(gene only)

28. is highest
among Kinases
Phosphorylation Regulation
Fraction of protein with predicted
phosphorylation site
Predrag
Radivojac
SF TF Kinase

29. Cross-regulation vs. cross-talk regulation
TF
TF
SF K

30. The role of cross talk between splicing and
transcription regulation
SRP20
SRP55
PAX 6
SC35
SF2ASF
9G8

31. Regulatory proteins tend to be highly
regulated by the specific regulation they
carry out.
TF
TF
SF K

32. Thanks!
Technion
Yael Mandel Gutfreund
Guy Plaut
Inbal Paz
Iris Dror
Martin Akerman
And all lab members
Indiana University
Predrag Radivojac
And you for your attention!