Upload
adele
View
75
Download
0
Embed Size (px)
DESCRIPTION
ICMB @ Geuvadis achievements and contributions. Robert Häsler , functional genomics. ICMB achievements mRNA & miRNA sequencing. mRNA 72 samples sequenced miRNA 24/72 samples already sequenced high (rank) similarities of results between sites. ICMB potential contributions (I) - PowerPoint PPT Presentation
Citation preview
ICMB @ Geuvadisachievements and contributions
Robert Häsler, functional genomics
2
ICMB achievementsmRNA & miRNA sequencing
mRNA
72 samples sequenced
miRNA
24/72 samples already sequenced
high (rank) similarities of results between sites
3
ICMB potential contributions (I)nTARs workflow (novel transcriptional active region)
covered regions known?mapping no nTaryes
sequence QC
no
discard hitbad
linked to known exon/other nTar?
OK
BLAT of high quality unmapped reads
nodiscard hit
no
RF + start codon
yes
RF no UTR, intron
isoform part
yes
nTar / isoform
yes
duplication? BLAT + unique flag
known elongation?
BLAT blast like alignment toolRF reading frame
ICMB references:Philip et al 2012 Bioinformatics, Klostermeier et al 2011 BMC Genomics
4
ICMB potential contributions (II)detection of splice variation patterns
isoform 1
isoform 2
isoform 3
isoform 4
GYN GYN NAG NAG
GYN GYN NAG NAG
GYN GYN NAG NAG
GYN GYN NAG NAG
expression values by cufflinks
mid
high
low
very low
example scenario
5
ICMB potential contributions (II)detection of splice variation patterns
isoform 1
isoform 2
isoform 3
isoform 4
GYN XYN NAG NAG
GYN XYN NAG NAG
GYN XYN NAG NAG
GYN XYN NAG NAG
expression values by cufflinks
example scenario
none
none
low
very low
variant introduced
ICMB references: Brosch et al 2012 Cell Metab, Häsler et al 2011 Eur J Cell Biol, Kramer et al 2011 Genetics, ElSharawy et al 2009 Human Mutat, Hiller et al 2008 RNA; Szafranski et al 2007 Genome Biol, Hiller et al 2006 Am J Hum Genet, Hiller et al 2004 Nat Genet
6
ICMB potential contributions (III)linking miRNA & miRNA-targets
2% encoding vs. 60-70% non-coding RNA
10-30% of all genes regulated by miRNAs
experimental miR target prediction
expensive, slow
in silico miR target prediction
~3000 targets/miRNA
low/no overlap between different prediction tools
functional effects hard to predict
7
ICMB potential contributions (III)linking miRNA & miRNA-targets
TASSDB (Sinah et al, 2012)tandem splice site data base
how to?
sequence patterndonor/acceptor positionconservationnonsense mediated decay
extract available information:
is there a splice-relevant variant?
is the variant associated to
modified mRNA expression?
expected outcome:
candidates of variants from
the 1000 Genomes project with
potential functional impact
ICMB references: Häsler et al 2012 PLoS One, Keller et al 2011 Nat Methods, Schulte et al 2010 NAR, Sinha et al, 2010 BMC Bioinformatics, Hiller et al 2007 NAR
8
ICMB potential contributionssummary
nTARs
splice variation patterns
linking miRNA to miRNA targets
our position in the analysis pipeline?
team
Philip Rosenstiel
Stefan Schreiber
Robert Häsler
Matthias Barann
Daniela Esser
Markus Schilhabel