RNA-Seq guided gene therapy for

vision loss

Michael H. Farkas

4

The retina is a complex tissue

• Many cell types

• Neural retina vs. RPE

• Each highly dependent on the other

Graw, Nature Reviews Genetics, 2003

Inherited Retinal Degenerations

• 212+ disease genes identified to date

• Genetically and clinically diverse

(Modified from Berger, et al 2010)

Retinitis Pigmentosa (RP)

• RP is the most common form of inherited blindness

– Affects 1:1000-4000 individuals worldwide

• Patients typically present in early adulthood with progressive night blindness and loss of peripheral vision

– Complete vision loss occurs later in life

• Currently, nearly 50 genes implicated in non-syndromic RP

Many expressed specifically in the retina

mRNA Splicing and RP

•6 spliceosome-associated genes identified as important causes of dominant RP:

-PRPF3, PRPF6, PRPF8, PRPF31, RP9, SNRNP200

• All function in the U4/U6/U5 tri-snRNP

RNA Splicing Factor RP

• How do mutations in spliceosome components cause retina-specific disease?

– Hypotheses:

1. via production of specific altered transcripts that are pathogenic in the retina

2. via global alterations in splicing that affect the retina most

• Goals:

– Test these hypotheses in gene targeted Prpf3, Prpf8 and Prpf31 mice, and human RPE cells

– Develop therapeutic strategies for these common forms of RP

RPE and Retinal Degeneration in Prpf Mutant Mice

(Graziotto, et al 2011)

Defective Function of Prpf Mutant RPE

(Farkas, et al AJP, 2014)

RNA-Seq Library Preparation

• RPE is a single cell layer

– Tissue/RNA is limited in

mice

– Have nanogram levels of

total RNA to start

– Traditional protocols use

microgram levels of total

RNA

• Protocol is optimized for

200 ng of total RNA, but

can be adjusted to use less

RNA-Seq Unified Mapper (RUM)

Grant, et al., Bioinformatics, 2011

• Alignment of RNA-Seq reads was problematic when RNA-Seq was first developed

– Requires accurately mapping reads over splice junctions that can span hundreds of kilobases

– Many algorithms have since been developed

• RUM is one of the most accurate in mapping reads

– Provides data for exons, introns,

splice junctions, and transcripts

– Very well suited for detecting novel

splicing variants • novel isoforms and novel genes

Aberrant Splicing - RPE

• How many aberrant transcripts are detected in the mutant

RPE transcriptomes?

• Prpf3 – 179

• Prpf8 – 44

• Prpf31 – 24

• No aberrant transcripts are shared amongst the models,

further suggesting that disease pathogenesis is caused by

different mechanisms.

• 68 – 211 aberrant transcripts are detected in the retina,

brain, and muscle samples, suggesting aberrant splicing is

widespread.

Altered Splicing - Rgr

Altered Splicing - Rgr

Characterization of the Human and Mouse Retinal Transcriptome

• RNA-Seq libraries prepared from human and mouse retina, and mouse

RPE and ARPE-19 cells.

• Approximately 80% of all annotated exons are expressed in the retina.

• An additional 3.5 Mb of novel features were found to be expressed.

• Large number of novel splicing events detected by RUM:

• Human retina – 79,915

• Mouse retina – 47,078

• Mouse RPE – 34,061

• ARPE-19 cells – 32,178

Farkas, et al., BMC Genomics, 2013

10 40 70 100

130

160

190

220

250

280

0

10000

20000

30000

Reads (Millions)

# o

f No

ve

l Fe

atu

res

Novel Exons

Exon Skipping

Alternate 3'/5' Splice Site

Novel Exons in the Retina

Nov

el >

10x

Nov

el 5

-10x

Nov

el 2

-5x

Nov

el =

Ann

otat

ed

Annot

ated

2-5

x

Ann

otat

ed 5

-10x

Annot

ated

> 1

0x0

5

1060

75

% o

f To

tal J

un

ctio

ns

Ratio of Novel to Annotated Junctions

• Nearly 30,000 novel exons identified

in the human retina.

• ~5% of the novel exons compose the

major isoform.

• 14% are predicted to maintain an

open reading frame (ORF).

Farkas, et al., BMC Genomics, 2013

Novel Exon Skipping

• Exon skipping is the most prevalent

alternative splicing event.

• 82% of the novel exon skipping

events skip one exon

• 17% are predicted to maintain the

ORF

Novel Alternate Splice Sites

• Nearly 19,000 novel alternate splice

sites identified.

• ~25% are predicted to maintain an

open reading frame (ORF).

• Conclusion – current transcriptome

annotations are under-represented

and comprehensive annotation can

be important for finding mutations

• Novel exons have been found to harbor

mutations in IRD genes (ABCA4)

What do transcriptome analyses tell us?

• Large number of novel splicing events in neural retinal transcriptomes – Human retina – 79,915

• 19,637 novel internal exons • Including 206 in 99 of the known IRD disease genes • Data are available via OGI website

– Mouse retina – 47,078

• Large number of novel splicing events in the RPE – Mouse RPE – 34,061 – Human ARPE19 cells – 32,178

• 15,000 novel events were chosen from RNA-Seq data

– Exon skipping, novel exons, alternate 3’/5’ splice sites.

• Read depth as low as 1

• Baits developed using Agilent’s SureSelect Targeted RNA Capture System.

• Sequenced on a HiSeq2000

Large Scale Validation of Novel Transcriptome Features

• Evaluated 15,000 novel splicing events by targeted RNA capture

• 99% of the novel events were validated in retinal samples

• 71%, 61%, and 58% events detected in brain, liver, and muscle

• Nearly 2,000 novel splicing events may be restricted to the retina

• Data are available via OGI website

(Farkas et al BMC Genomics 2013)

PRPF31-associated RP • Mutations in PRPF31 are the second most common cause

of adRP

– 50,000-190,000 affected people worldwide

• Pathogenesis of disease due to haploinsufficiency

– Mutations can be nonpenetrant

(Rivolta et al, Human Mutation, 2006)

• Family with adRP

underwent whole exome

sequencing.

• PRPF31 c.-9+1G>C

variant identified as top

candidate for potential

pathogenicity.

– First base of donor site in

intron 1.

Functional validation of PRPF31 variants

X X

Control 330 6230.0

0.5

1.0

Re

lative

Expre

ssio

n

**

*p < 0.05

Functional validation of PRPF31 variant

330 623

A* B

C D

Functional validation of PRPF31 variant

330 623

A* B

C D

A*

B

C

D

• No splice variants produced premature

stop codons.

• Additional studies, including knock-in

and patient iPS cells, are in progress to

study mRNA stability and affect on

phagocytosis.

Functional validation of PRPF31 variants

CRISPR/Cas9 Knockout of PRPF31

• Guide RNAs (gRNA) designed to exon 6 of PRPF31

• iPS cells and ARPE-19 co-transfected with gRNA and Cas9:GFP

• GFP positive cells were single cell sorted into a 96-well plate

• Sanger validated:

• 25% heterozygous sites undergoing non-homologous end joining, which

included 1-13 bp deletions

• No homozygous knockout clones observed – consistent with

haploinsufficiency mechanism

Decreased PRPF31 Expression Levels

Re

lative

PR

PF

31

Exp

ressio

n

Con

trol

GE31

-1

GE31

-2

GE31

-3

GE31

-6

GE31

-70.0

0.5

1.0

1.5

** ****

**

*P < 0.05**P < 0.01

• qPCR primers designed to 3 locations in PRPF31

• γ-tubulin 1 (TUBG1) used as a control due to its similar

expression level in ARPE-19 cells

• 5 lines chosen for analysis

Functional Characterization - Phagocytosis

• Each line plated in triplicate wells of a 48 well plate.

• Assayed 3 weeks after cells reached confluence to ensure

polarization.

• FITC-labeled photoreceptor outer segments phagocytosed

by ARPE-19 were counted using flow cytometry.

Con

trol

GE31

-1

GE31

-2

GE31

-3

GE31

-6

GE31

-7

0

50

100

Rela

tive P

hagocyto

sis

Functional Characterization - Phagocytosis

Incubation Time

Re

lativ

e P

OS

Up

take

1 Hou

r

2 Hou

r

3 Hou

r0

10

20

30

40Control

GE31-1

GE31-2

GE31-3

GE31-6

GE31-7

• While POS uptake begins to reach a maximum after 3

hours, the knockout lines seem to be increasing in the rate

of uptake.

• Is phagocytosis slow, rather than non-existent in PRPF31

models?

AAV-PRPF31 Gene Augmentation

WT

GE31

0.0

0.5

1.0

Re

lative

PO

S U

pta

ke No AAV-PRPF31

MOI = 10,000

MOI = 15,000*

Massachusetts Eye and Ear Pierce Lab Dr. Libby Au Dr. Kinga Bujakowska Dr. Donna Garland Dr. Chari Fernandez Godino Matt Maher Daniel Navarro Dr. Eric Pierce Emily Place Maria Sousa Dr. Scott Greenwald Dr. Joe White Dr. Qi Zhang

Liu Lab Mihoko Leon Dr. Qin Liu

Comander Lab Dr. Jason Comander Ally Lansdorf

Acknowledgements Harvard Stem Cell Institute Cowan Lab Dr. Chad Cowan Dr. Derek Peters Jen Shay Johns Hopkins University

Zack Lab Dr. Melissa Liu Dr. Tomo Masuda Dr. Don Zack

Qian Lab Dr. Jiang Qian Dr. Jun Wan University of Wisconsin-Madison

Gamm Lab Dr. Beth Capowski Dr. David Gamm Anna Petelinsek Jishnu Saha

Institut de la Vision Dr. Shomi Bhattacharya Dr. Emeline Nandrot UCLA Dr. Xiaowu Gai University of Pennsylvania Dr. Greg Grant Funding NEI NRSA Foundation Fighting Blindness MEEI

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