1. Presented by: Matthew Tippin, Bianca Sanchez Mora
RNA Maps Reveal New RNA Classes and a Possible Function for Pervasive Transcription
Philipp Kapranov1, Jill Cheng1, Sujit Dike1, David A. Nix1, Radharani Duttagupta1, Aarron T. Willingham1, Peter F. Stadler2, Jana Hertel2, Jörg Hackermüller3, Ivo L. Hofacker4, Ian Bell1, Evelyn Cheung1, Jorg Drenkow1, Erica Dumais1, Sandeep Patel1, Gregg Helt1, Madhavan Ganesh1, Srinka Ghosh1, Antonio Piccolboni1, Victor Sementchenko1, Hari Tammana1, Thomas R. Gingeras1,*
Presented by: Matthew Tippin, Bianca Sanchez Mora

2. Background
Multiple RNA’s of various lengths have already been discovered
Idea of pervasive transcription existed
Large amount of transcription in genome far beyond only protein genes
No known function for ncRNA (miRNA, piRNA, snoRNA, siRNA etc)
Believed to be an evolutionary relic of RNA world
Purpose of experiment was to investigate lRNA and sRNA

3. Affymetrix Microarray

4. Tiling Array
5bp
35bp
Mismatch/Perfect Match differ by one bp (unstable)
Mismatch: negative control, primer not bound correctly
Perfect Match: binds correctly
HG30 – genome transcript
Probe pairs represent 84% nt of the repeated sequences
Included LINE2
35 bp resolution
Probe pairs represent 91% of the repeat mass sequence with at least 5 probes

5. Generation of RNA Maps Generation of single-sample RNA graphs
Each sample represented by a set of 24 graphs per chromosome (HC version 35)
Separate signals by chromosome integrate to create chromosome wide signal value
Generation of sRNA transcript maps
HepG2/HeLA cells – hybridize to either +/- strand resolution bp sets
Generation of lRNA transcript maps
Transcripts > 200 nt mapped from cytoA+ RNA from 8 lines – 2 nuc 3 replicas repaired, composite signal generated connect adjacent positive probes; discard transfrags overlapping pseudogenes/low complex/repetitive seq

6. Analysis of sRNA
Conserved Long Nuclear Transfrags that Overlap sRNAs are enriched near TSS
Short RNAs can associate with lRNA transripts not detected by transfrags
Human-Mouse syntenic analysis of sRNAs
7 nt resolution of several human and mouse syntenic regions were interogated

7. qtPCR Analysis of lRNA + sRNA
U6: used as a control
Power SYBR greenmaster mix (applied BioSystems)
Gene specific primers used for qRTPCR using one step method where reverse transcription is performed in the same tube as subsequent qPCR
Triplicate reactions were set up for every primer pair
Analysis of expression performed by comparing CT values for a series of nonspecific control genes with primers for genes of interest

8. Subcellular distribution of nuclear and cystolic RNA classes

10. Conserved sRNA Surrounding exon of RYR3 gene
Phastcon: computer algorithm program that shows conservation
RYR3: gene that codes for ryanodine receptor (releases Ca2+ from storage)
Phastcon: program that shows conservation
Scores indicate 1/5 sRNA transfrags were evolutionarily conserved

11. Comparing Phastcon scores of overlapping and nonoverlapping lRNA to sRNA

12. Conservation extends beyond lRNA overlap
Indicates regions outside of overlap may be significant

13. sRNA + lRNA Overlap
More sRNA transfrags overlap with nuclear lRNA transfrags as opposed to lRNA overlapping sRNA
lRNA with overlapping sRNA are more conserved than lRNA without

14. PALRs sRNA overlap lRNA PALRs: promoter-associated lRNAs
lRNA that overlap 5’ end of protein coding genes
Map the same region as PASRs

15. PASRs and TASRs sRNA clusters – 3’ and 5’ ends of genes
Northern Blot: Detects RNA to study gene expression
PASRs: Promoter-associated sRNA
TASRs: Termini-associated RNA
PASRs expressed at similar lvl to genes they overlap

16. Frequency Distribution via Violin Plots
Positive Correlation shown between Density PASRs + Expression level
sRNA have biological significance

17. Distribution of syntenically conserved sRNAs
PASRs and TASRs are most conserved sRNA
Conservation between species
Northern Blot show comparable size

18. Summary of Results Overall the results indicate:
lRNA act as primary transcripts for sRNA
There are three distinct classes of RNA found
Possibly 10% ncRNA appears to have gene regulatory function that was previously unknown

19. Conclusion lRNA can be primary transcripts for the production of sRNA
Three novel potentially functional classes of RNAs were identified (2 are syntenically conserved and correlate with the expression state of protein-encoding genes)
Data supports a model of genome organization – RNA regulation in gene expression

20. Significance Classification of 3 different RNA classes
lRNA and sRNA relationship suggests complex network of ncRNA regulation of gene expression in higher eukaryotes
Regulation possibly due to chromatin remodeling complexes
Expands Central Dogma
Future insights into the human transcriptome

21. Additional Reading Supplemental Reading:
Clarify methods, data collection and analysis
Kapranov et al, (2007) Supplemental Reading
Later Study by Kapranov (2010):
A continuation of the idea brought forth
Most nuclear non rRNA is unannotated
Kapranov et al; BMC Biology, 2010, 8:149, doi: /

22. References ENCODE-Project-Consortium, Nature
J. Cheng et al., Science 308, 1149 (2005).
P. Kapranov et al., Science 296, 916 (2002).
Materials and methods, Science online