Transcript Kapranov

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
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
Affymetrix Microarray
Tiling Array
5bp
• 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
35bp
• Included LINE2
• 35 bp resolution
• Probe pairs represent 91%
of the repeat mass
sequence with at least 5
probes
Generation of RNA Maps
A. Generation of single-sample RNA graphs
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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
B. Generation of sRNA transcript maps
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HepG2/HeLA cells – hybridize to either +/- strand resolution bp sets
C. Generation of lRNA transcript maps
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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
Analysis of sRNA
A. Conserved Long Nuclear Transfrags that
Overlap sRNAs are enriched near TSS
B. Short RNAs can associate with lRNA
transripts not detected by transfrags
C. Human-Mouse syntenic analysis of sRNAs
• 7 nt resolution of several human and mouse syntenic regions were
interogated
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
Subcellular distribution of nuclear and
cystolic RNA classes
Conserved sRNA Surrounding exon of
RYR3 gene
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
Comparing Phastcon scores of overlapping
and nonoverlapping lRNA to sRNA
• Conservation extends beyond lRNA overlap
• Indicates regions outside of overlap may be
significant
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
PALRs
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sRNA overlap lRNA
PALRs: promoter-associated lRNAs
lRNA that overlap 5’ end of protein coding genes
Map the same region as PASRs
PASRs and TASRs
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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
Frequency Distribution via Violin Plots
• Positive Correlation shown between Density PASRs + Expression level
• sRNA have biological significance
Distribution of syntenically conserved
sRNAs
• PASRs and TASRs are most conserved sRNA
• Conservation between species
• Northern Blot show comparable size
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
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
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
Additional Reading
• Supplemental Reading:
– Clarify methods, data collection and analysis
Kapranov et al, (2007) Supplemental Reading
www.sciencemag.org/cgi/content/full/1138341/DC1
• 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:
10.1186/1741-7007-8-149.
References
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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