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ig Data to Relevant data: Ribo-seq and its appli Pasha Baranov "NGS Data after the Gold Rush“ Norwich, UK, May 2014 time Porridge volume, log

From Big Data to Relevant data: Ribo-seq and its applications

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From Big Data to Relevant data: Ribo-seq and its applications Pasha Baranov "NGS Data after the Gold Rush“ Norwich, UK, May 2014. Porridge volume, log. time. What to sequence?. Lung cancer. Genetics: up to 2.4 higher chance than general population. - PowerPoint PPT Presentation

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Page 1: From Big Data to Relevant data:  Ribo-seq  and its applications

From Big Data to Relevant data: Ribo-seq and its applicationsPasha Baranov "NGS Data after the Gold Rush“ Norwich, UK, May 2014

time

Porr

idge

vol

ume,

log

Page 2: From Big Data to Relevant data:  Ribo-seq  and its applications

Genetics: up to 2.4 higher chance than general population.

What to sequence?Lung cancer

80-90% of lung cancer cases attributed to smoking.

Median age of lung cancer occurrence in US is 70 years.

DNA

RNA

Protein

RNA-seq

?

Page 3: From Big Data to Relevant data:  Ribo-seq  and its applications

Ribosomal profiling (ribo-seq)Ingolia et al (2009) Science 324: 218-23

Lysis, RNA digestion

Page 4: From Big Data to Relevant data:  Ribo-seq  and its applications

Ribosomal profiling (ribo-seq)

Lysis, RNA digestion

Density gradient orcushion separation

Ingolia et al (2009) Science 324: 218-23

Page 5: From Big Data to Relevant data:  Ribo-seq  and its applications

Ribosomal profiling (ribo-seq)

Lysis, RNA digestion

Density gradient orcushion separation

Adaptor ligation RT PCR Circularization

Decircularization

Sequencing

Alignment to a reference sequence

Differential gene expression analysis

Ingolia et al (2009) Science 324: 218-23

Page 6: From Big Data to Relevant data:  Ribo-seq  and its applications

mRNA level is only approximation of protein synthesis

Immediate response to oxidative stress (1 hour)

Andreev et al 2014 submitted

Page 7: From Big Data to Relevant data:  Ribo-seq  and its applications

How do you know what is translated?

CTGGAAGAAGTAAACGCCGAGCTGGAACAGCCGGATGTCTGGAACGAACC G R S K R R A G T A G C L E R T Frame 1 L E E V N A E L E Q P D V W N E P Frame 2 W K K * T P S W N S R M S G T N P Frame 3

Page 8: From Big Data to Relevant data:  Ribo-seq  and its applications

Triplet periodicityCAGCTAGTGCGTGCTGTC123123123123123123

Page 9: From Big Data to Relevant data:  Ribo-seq  and its applications

Triplet periodicityCAGCTAGTGCGTGCTGTC123123123123123123

Page 10: From Big Data to Relevant data:  Ribo-seq  and its applications

Triplet periodicityCAGCTAGTGCGTGCTGTC123123123123123123

Page 11: From Big Data to Relevant data:  Ribo-seq  and its applications

Triplet periodicityCAGCTAGTGCGTGCTGTC123123123123123123

Page 12: From Big Data to Relevant data:  Ribo-seq  and its applications

Triplet periodicityCAGCTAGTGCGTGCTGTC123123123123123123

Page 13: From Big Data to Relevant data:  Ribo-seq  and its applications

Triplet periodicityCAGCTAGTGCGTGCTGTC123123123123123123

Page 14: From Big Data to Relevant data:  Ribo-seq  and its applications

Triplet periodicity

N+1

N+2

N+3

Page 15: From Big Data to Relevant data:  Ribo-seq  and its applications

Switches between reading frames can be seen on ribosome profiles

Human Antizyme 1 mRNA

Michel et al 2012 Genome Res 22:2219-2229

Page 16: From Big Data to Relevant data:  Ribo-seq  and its applications

uORFs & nORFs

Michel et al 2012 Genome Res 22:2219-2229

Page 17: From Big Data to Relevant data:  Ribo-seq  and its applications

GWIPS-viz

http://gwips.ucc.ie

Page 18: From Big Data to Relevant data:  Ribo-seq  and its applications

AcknowledgmentsGWIPS-viz team:Audrey Michel Gearoid Fox Patrick O'Connor Stephen Heaphy Paddy Mullan Claire DonohueRomika SainiZena Abbas

Oxidative stress work:Dmitry Andreev Patrick O’ConnorMoscow State University:Terenin, Dmitriev, ShatskyTrinity College Dublin: Kenny, Fahey, Cormican, Morris

Dual coding:Audrey MichelUniversity College Cork:Choudhury, AtkinsBerkley: IngoliaCambridge: Firth

Financial resources: