yoon et al, supplementary fig. 1 - images.nature.com · 13 14 92 88 24 25 25 30 2 2 7 7 93 93 56 56...
TRANSCRIPT
Yoon et al, page 1
SUPPLEMENTARY MATERIALS
Supplementary Figure 1. Comparison of HuR PAR-CLIP and AUF1 PAR-CLIP. (a) Summary of
annotation and mapping of the PAR-CLIP libraries for the four different AUF1 isoforms and the combined
dataset using PARalyzer. (b) Number of reads of AUF1 PAR-CLIP tags per transcript. (c) Percentage of
AUF1 PAR-CLIP tags in mature mRNAs, introns, and ncRNAs. (d) Shared target mRNAs and 3’UTRs in
AUF1 and HuR PAR-CLIP (e) Relative distribution of PAR-CLIP tags upstream (‘up’) and downstream
(‘dn’) of the start and stop (‘end’) codons. Density of AUF1, HuR32 and Ago29 PAR-CLIP tags across the
5’UTR, coding region, and 3’UTR of mRNAs. (f) Representative (top three) RNA Recognition Elements
(RREs) from each AUF1 isoform.
Total Common target mRNAs
target mRNAs p37 p40 p42 p45 HuR
p37 (%) 100.0 --- 46.8 48.1 58.8 71.8
Gene (#) 308 144 148 181 221
p40 (%) 100.0 8.7 --- 46.0 59.0 83.0
Gene (#) 1,663 144 765 981 1,380
p42 (%) 100.0 5.3 27.6 --- 37.2 19.9
Gene (#) 2,768 148 765 1,029 552
p45 (%) 100.0 5.2 28.3 29.7 --- 19.9
Gene (#) 3,468 181 981 1,029 690
HuR (%) 100.0 3.6 22.4 9.0 11.2 ---
Gene (#) 6,154 221 1,380 552 690
Total Common target 3`UTR
target 3’UTR p37 p40 p42 p45 HuR
p37 (%) 100.0 --- 49.7 52.5 69.1 84.0
Gene (#) 181 90 95 125 152
p40 (%) 100.0 6.5 --- 44.8 61.0 86.5
Gene (#) 1380 90 618 842 1194
p42 (%) 100.0 6.2 40.2 --- 57.4 82.7
Gene (#) 1535 95 618 881 1269
p45 (%) 100.0 6.5 43.7 45.7 --- 87.9
Gene (#) 1926 125 842 881 1692
HuR (%) 100.0 2.6 20.3 21.5 28.7 ---
Gene (#) 5895 152 1194 1269 1692
Shared target 3’UTRShared target mRNAs
Yoon et al, Supplementary Fig. 1
AUF1 p37
AUF1 p40
AUF1 p42
AUF1 p45
e
Ave
rag
e t
ag
s
pe
r 1
00
-b w
ind
ow
pe
r m
illio
n r
ea
ds
d
f
1000b_up
900b_up
800b_up
700b_up
600b_up
500b_up
400b_up
300b_up
200b_up
100b_up
Coding_Start
100b_dn_start
200b_dn_start
300b_dn_start
400b_dn_start
500b_dn_start
600b_dn_start
700b_dn_start
800b_dn_start
900b_dn_start
1000b_dn_start
1000b_up_end
900b_up_end
800b_up_end
700b_up_end
600b_up_end
500b_up_end
400b_up_end
300b_up_end
200b_up_end
100b_up_end
Coding_End
100b_dn
200b_dn
300b_dn
400b_dn
500b_dn
600b_dn
700b_dn
800b_dn
900b_dn
1000b_dn
Compiled Binding Profile over mRNA
AUF1_p37
AUF1_p40
AUF1_p42
AUF1_p45
AUF1_ALL
HuR
Ago
0.60
0.48
0.36
0.24
0.12
0
5’UTR 3’UTRCoding Region
Distance from Start or Stop codons
p37 p40 p42 p45 Combined
Raw sequence reads 39333766 41501812 34200306 32579514 147615398
Adapter extracted reads 26590962 23849090 17541376 20245876 88227304
Sequence reads mapping to the genome with 0 and 1 mismatch 2250794 2496539 3073255 5017101 12837689
Sequence reads uniquely mapping to genome with 0 and 1 mismatch 467084 502618 643639 1274269 2870020
Sequence reads utilized for group assembly 118367 485028 329163 333140 1392847
Number of groups 2744 11385 35567 33587 86789
% P
AR
-CL
IP t
ag
s
0
2500
2000
1500
1000
500
0
p37
p40
p42
p45
1 2 2.5 3 3.5 4 4.5 5 5.5 6
Log2 (AUF1 sites per transcript)
Co
un
ts
b c
0
10
20
30
40
50
60
70
80
90
p37 p40 p42 p45
5’UTR
CDS
3’UTR
Intron
ncRNA
a
Yoon et al, page 2
Supplementary Figure 2. RNA recognition motifs in AUF1 PAR-CLIP. Representative (top three) RNA
Recognition Elements (RREs) for all four AUF1 isoforms according to the binding region on the mRNA:
5’UTR, coding region (CDS), and 3’UTR.
5’UTR
CDS
3’UTR
Yoon et al, Supplementary Fig. 2
Yoon et al, page 3
Supplementary Figure 3. AUF1 target pre-mRNAs, influence on alternatively spliced transcripts. (a)
Top, relative distribution of tags within each target pre-mRNA. Bottom, shared pre-mRNAs between
combined AUF1 and HuR PAR-CLIP libraries. (b) Number of target pre-mRNAs shared among the four
AUF1 isoforms and HuR. (c) Left, number of PAR-CLIP target pre-mRNAs differentially expressed after
overexpression of each AUF1 isoform, as determined by RNA-Seq. Right, specific relative levels of
different splicing variants (#1, #2, #3) for each alternatively spliced, shared pre-mRNA.
#2#1#1 #2#2#1#2
a
p40(11 transcripts)
p42(291 transcripts)
p37(24 transcripts)
p45(6 transcripts)
ATRX
CLCC1
DENND5A
ESYT2
KIAA0586
ZEB1
EXD2
RTTN
UGGT1
RAPGEF2
53081395 2380
# target pre-mRNAs
in PAR-CLIPs
AUF1 PAR-CLIP HuR PAR-CLIP
75
60
45
30
15
0
b
c # target pre-mRNAs with differential expression
after AUF1 isoform overexpression (RNA-seq)
6
5
4
3
2
1
0
vector
p37
p42
ATRX
Rela
tive levels
CLCC1 DENND5A ESYT2 KIAA0586 ZEB1
#1 #2#1#3#2#1Isoform
#2#1#2
6
5
4
3
2
1
0
vector
p40
p42
EXD2
Rela
tive levels
RTTN UGGT1
#1 #2#1Isoform #2
4
3
2
1
0
vector
p42
p45
RAPGEF2
Rela
tive levels
#1Isoform
% d
istr
ibu
tio
n a
mo
ng
RN
As
wit
h P
AR
-CL
IP t
ag
s
Total Shared target pre-mRNAs
target pre mRNAs p37 p40 p42 p45 HuR
p37 (%) 100.0 - 66.0 84.1 79.4 85.9
Gene (#) 870 574 732 691 747
p40 (%) 100.0 18.3 - 82.4 77.8 85.9
Gene (#) 3,142 574 2,589 2,443 2,698
p42 (%) 100.0 13.6 47.9 - 68.9 82.5
Gene (#) 5,402 732 2,589 3,722 4,455
p45 (%) 100.0 15.1 53.4 81.4 - 86.8
Gene (#) 4,572 691 2,443 3,722 3,968
HuR (%) 100.0 9.7 35.1 57.9 51.6 -
Gene (#) 7,688 747 2,698 4,455 3,968
Shared target Pre-mRNAs
p37 p40 p42 p45 AUF1
(all)
HuR
5’UTR
CDS
3’UTR
Intron
Yoon et al, Supplementary Fig. 3
Yoon et al, page 4
Supplementary Figure 4. Comparison of transcriptomes among HEK293, HeLa, and WI-38 cells. (a)
Pairwise correlations of transcript levels in each cell type (HeLa, HEK293 and WI-38 cells) were calculated
and plotted with log2-transformed FPKM values (fragments per kilobase of exon per million fragments
mapped). The plots show high degree of correlation (0.80 to 0.85), indicating that the transcript abundances
in the three cell types were very highly similar. (b) Western blot analysis of AUF1 levels in HeLa cells,
HEK293 cells, and WI-38 fibroblasts (PDL 15 and PDL 55); 10 μg whole-cell lysate was loaded in each
lane.
-9
-5
-1
3
7
11
15
-9
-5
-1
3
7
11
15
-9
-5
-1
3
7
11
15
-9 -5 -1 3 7 11 15 -9 -5 -1 3 7 11 15 -9 -5 -1 3 7 11 15
HeLa FPKM
(Log2)
HEK293 FPKM
(Log2)
WI38 FPKM
(Log2)
HeLa FPKM (Log2) HEK293 FPKM (Log2) WI38 FPKM (Log2)
HeLa FPKM (Log2) 1.0000 0.8511 0.8069
HEK293 FPKM (Log2) 0.8511 1.0000 0.8312
WI38 FPKM (Log2) 0.8069 0.8312 1.0000
Scatterplot Matrix
Multivariate Correlations
HeLa
HEK293
WI-38
HeLa HEK293 WI-38
AUF1
TUBULIN
a
b
HeLa HEK293
WI-38
PDL15
WI-38
PDL55
Yoon et al, Supplementary Fig. 4
Yoon et al, page 5
Supplementary Figure 5. AUF1 does not affect global poly(A)+ RNA distribution, U2 snRNA, XIST
and MALAT1 function. (a) PCR analysis to analyze the exon inclusion ratio of pre-mRNAs targeted by
MALAT1. (b,c) RNA-FISH analysis to detect the distribution of U2 snRNA (red) (b), poly(A)+ RNA (green)
(b) in HeLa cells and XIST RNA (red) in WI-38 cells (c). The DNA is counterstained with DAPI (blue).
(d,e) In cells expressing normal (Ctrl siRNA) or reduced HuR or AUF1 levels, the steady-state levels of
PAICS, PCCB, and NUP43 mRNAs (normalized to GAPDH mRNA) (d), and the relative abundance of
NEAT1 RNA and GAPDH mRNA in the nucleus and cytoplasm (e) were measured by RT-qPCR. (f) In vitro
assays to test the binding of recombinant His-AUF1 and MBP-HuR to purified biotinylated HOTAIR,
lincRNA-p21, MALAT1, and NEAT1 lncRNAs. Input, recombinant protein used in binding assays; MBP,
negative control protein. (g) Forty-eight hours after silencing AUF1 and HuR, the levels of TOP2A, USP1,
and APP mRNAs in AUF1 IP and in HuR IP were measured by RIP followed by RT-qPCR analysis. Data
were normalized to GAPDH mRNA levels in each IP sample.
Hu
R s
iRN
A
AU
F1
siR
NA
Ctrl s
iRN
A
aC
on
tro
l s
iRN
A
Co
ntr
ol s
iRN
A
Co
ntr
ol s
iRN
A
Co
ntr
ol s
iRN
A
Co
ntr
ol s
iRN
A
Co
ntr
ol s
iRN
A
Co
ntr
ol s
iRN
A
Co
ntr
ol s
iRN
A
Co
ntr
ol s
iRN
A
SAT1
Exon 4
ARHGEF1
Exons 23-24
HMGXB4
Exon 2
HMGXB4
Exon 5
CDK7
Exons 2-3
CDK7
Exons 3-4
CTAGE5
Exon 2
CTAGE5
Exon 19MYBL2
Exon 3
92 8813 14 24 25 25 30 2 2 7 7 93 93 56 56 98 98 % exon
inclusion
Co
ntr
ol s
iRN
AA
UF
1 s
iRN
AH
uR
siR
NA
HeLa
U2 snRNA poly A+ RNA Merge Merge + DAPI XIST
WI-38
XIST + DAPI
Control siRNA AUF1 siRNA HuR siRNAb c
NEAT1 RNA
d
PAICS
Ctrl siRNA
AUF1 siRNA
HuR siRNA
NUP43PCCB
1.25
1.00
0.75
0.50
0.25
0
mR
NA
le
ve
ls (
fold
)
125
100
75
50
25
0
Re
lati
ve
le
ve
ls
GAPDH mRNA
eCytoplasmic
Nuclear
p37
p40
p42
p45
MBP-HuR
MBP
HOTAIR - - - - - +
lincRNA-p21 - - - - + -
MALAT1 - - - + - -
NEAT1 - - + - - -
Input + - - - - -
HOTAIR - - - +
lincRNA-p21 - - + -
MALAT1 - + - -
NEAT1 + - - -
f
Yoon et al, Supplementary Fig. 5
TO
P2
Am
RN
A e
nri
ch
me
nt
0
1
2
3
4
5
6
7
8
US
P1
mR
NA
en
ric
hm
en
t
0
1
2
3
4
5
6
7
8
AP
Pm
RN
A e
nri
ch
me
nt
0
1
2
3
4
5
6
IgG IP AUF1 IP
CtrlsiRNA
AUF1siRNA
+HuR
siRNA
IgG IP HuR IP
CtrlsiRNA
AUF1siRNA
+HuR
siRNA
g
Yoon et al, page 6
Supplementary Figure 6. AUF1 binds to TOP2A mRNA and promotes TOP2A translation. (a) RNP IP
analysis of the interaction of TOP2A mRNA with AUF1 using anti-AUF1 and rabbit IgG antibodies; TOP2A
mRNA was detected by RT-qPCR and normalized to GAPDH mRNA levels. Forty-eight h after transfecting
HeLa cells with Ctrl or AUF1 siRNA, Western blot analysis of the expression levels of TOP2A, AUF1, and
control β-ACTIN was performed and the levels of TOP2A mRNA relative to GAPDH mRNA were
calculated by RT-qPCR analysis. (b) Twenty-four h after transfecting cells with control plasmid pcDNA or
with four plasmids to overexpress each of the isoforms of AUF1 (pcDNA-AUF1), the levels of TOP2A,
AUF1, and control β-tubulin were assessed by Western blot analysis, and the abundance of TOP2A
mRNA/GAPDH mRNA by RT-qPCR analysis. (c) Schematic of TOP2A mRNA, depicting the 5’UTR, CR,
and 3’UTR. The TOP2A 3’UTR was cloned into plasmid pEGFP to generate pEGFP-TOP2A(3’). Cells
were transfected with the plasmids shown in the schematic together with either pcDNA or pooled pcDNA-
AUF1 plasmids; 16 h later, EGFP protein levels were assessed by Western blot analysis (left), quantified by
densitometry, normalized to α-tubulin levels, and plotted (right). (d) In cells that were transfected with the
EGFP reporter plasmids shown in (d), the association of AUF1 with the expressed transcripts (EGFP and
EGFP-TOP2A(3’) mRNAs) was measured 16 h later by RNP IP analysis.
TOP2A (Fold) 1.00 0.27 (0.2)
TOP2A (Fold) 1.00 4.0 (1.5)
a
b
TO
P2
Am
RN
A l
ev
els
pcDNA
AUF1
pcDNA
0.00
0.25
0.50
0.75
1.00
1.25
0.00
0.25
0.50
0.75
1.00
1.25
TO
P2
Am
RN
A l
ev
els
AUF1
siRNA
Ctrl
siRNA
AUF1
siRNA
Ctrl
siRNA
TOP2A (190 kDa)
b-ACTIN (45 kDa)
AUF1
c
pcDNA
AUF1pcDNA
TOP2A (190 kDa)
-TUBULIN (52 kDa)
AUF1
d
0
2
4
6
8
TO
P2
Am
RN
A e
nri
ch
me
nt
AUF1IgGIP:
p45
p42
p40
p37
**
pEGFP-TOP2A(3’)
pEGFP EGFP
EGFP
EGFP (27 kDa)
b-ACTIN (45 kDa)
pcDNAAUF1pcDNA
pcDNAAUF1pcDNA
pEGFP-TOP2A(3’)pEGFP
2.0
pEGFP-TOP2A(3’)
pEGFP
0.5
1.0
1.5
2.0
2.5
0.0
EG
FP
pro
tein
le
ve
ls
pcDNA
pcDNA-AUF1
pEGFP-TOP2A(3’)
0
3
6
9
12
15
EG
FP
mR
NA
in
AU
F1
IP
pEGFP
4722 5698
3’UTR
* **
p45
p42
p40
p37
AUF1
p45
p42
p40
p37
Yoon et al, Supplementary Fig. 6
Yoon et al, page 7
Supplementary Figure 7. Uncropped images for Western blots shown in the main article.
MWM
(kDa)
- 50
- 40
1B Tubulin
MWM
(kDa)
- 70
- 50
1B AUF1
MWM
(kDa)
- 50
- 40
1B Flag
MWM
(kDa)
- 50
- 40
3F Actin
MWM
(kDa)
- 70
- 50
- 40
3F AUF1
MWM
(kDa)
- 40
- 35
3F HuR
MWM
(kDa)
- 50
- 40
5D Tubulin
MWM
(kDa)
- 70
- 50
- 40
5D AUF1
MWM
(kDa)
- 40
- 35
5D HuR
MWM
(kDa)
- 140
- 100
5D APP5D USP1
MWM
(kDa)
- 260
- 140
5D Top2a
MWM
(kDa)
- 260
- 140
Yoon et al, Supplementary Fig. 7
Yoon et al, page 8
Supplementary Figure 7. Uncropped images for Western blots, and protein and DNA gels shown in the
main article.
6B EtBr
MWM
(kbp)
- 3
- 1
6A Coomassie
MWM
(kDa)
- 70
- 50
- 40
6B Coomassie MWM
(kDa)
- 70
- 40
6B Coomassie
6B Coomassie 6B Coomassie
6B Coomassie 6B Coomassie
6B Coomassie 6B Coomassie
MWM
(kDa)
- 70
- 40
MWM
(kDa)
- 70
- 50
- 40
MWM
(kDa)
- 70
- 50
- 40
MWM
(kDa)
- 70
- 50
- 40
MWM
(kDa)
- 70
- 40
MWM
(kDa)
- 70
- 50
- 40
MWM
(kDa)
- 70
- 50
- 40
Yoon et al, Supplementary Fig. 7 (continued)
Yoon et al, page 9
Supplementary Figure 7. Uncropped images for Western blots and protein gels shown in the main
article.
6D CoomassieMWM
(kDa)
-
- 50
- 40
6E Tubulin and RL MWM
(kDa)
- 70
- 50
- 40
- 35
6E Tubulin and RL
6E Tubulin and RL 6E Tubulin and RL
6E Tubulin and RL
6E Tubulin and RL
6D Coomassie
MWM
(kDa)
- 70
- 50
6E Tubulin and RL
MWM
(kDa)
- 70
- 50
- 40
- 35
MWM
(kDa)
- 70
- 50
- 40
- 35
MWM
(kDa)
- 70
- 50
- 40
- 35
MWM
(kDa)
- 70
- 50
- 40
- 35
MWM
(kDa)
- 70
- 50
- 40
- 35
MWM
(kDa)
- 70
- 50
- 40
- 35
Yoon et al, Supplementary Fig. 7 (continued)
Yoon et al, page 10
LEGENDS FOR SUPPLEMENTARY TABLES
Supplementary Table 1 – Analysis of AUF1 target RNAs identified by PAR-CLIP. Table lists AUF1
target RNAs overlapping with HuR PAR-CLIP in HEK293 cells.
Supplementary Table 2 – Analysis of HuR target RNAs identified by PAR-CLIP. Table lists
HuR target RNAs overlapping with AUF1 PAR-CLIP in HEK293 cells.
Supplementary Table 3 – Analysis of transcript abundance after AUF1 overexpression. Table lists
differentially expressed target RNAs after overexpressing AUF1 isoforms in HEK293 cells.
Supplementary Table 4 – Influence of AUF1 and HuR on ribosome profiles. Ribosome profile analyses
after silencing AUF1 or HuR in HeLa cells in HeLa cells.
Supplementary Table 5 – Analysis of transcript abundance after AUF1 silencing. Table lists
differentially expressed target RNAs after silencing AUF1 in HEK293 cells.
Supplementary Table 6 – Analysis of transcript abundance in WI-38 cells. Table lists differentially
expressed target RNAs after AUF1 or HuR silencing in proliferating WI-38 and senescent WI-38 fibroblasts.
Supplementary Table 7 – List of primers used in this study.
Supplementary Table 8 – Influence of AUF1 p37 on the levels of alternative transcripts. Table lists the
levels of alternative transcripts after overexpressing AUF1 p37 in HEK293 cells.
Supplementary Table 9 – Influence of AUF1 p40 on the levels of alternative transcripts. Table lists the
levels of alternative transcripts after overexpressing AUF1 40 in HEK293 cells.
Supplementary Table 10 – Influence of AUF1 p42 on the levels of alternative transcripts. Table lists
the levels of alternative transcripts after overexpressing AUF1 p42 in HEK293 cells.
Supplementary Table 11 – Influence of AUF1 p45 on the levels of alternative transcripts. Table lists
the levels of alternative transcripts after overexpressing AUF1 p45 in HEK293 cells.
Yoon et al, page 11
SUPPLEMENTARY NOTES
SUPPLEMENTARY RESULTS
Analysis of significance of the overlap among AUF1 and HuR sites
After applying tight criteria for inclusion of PAR-CLIP sites (>0.25 T-to-C conversions, >5 crosslinked reads,
and >2 crosslinking sites), 83,289 HuR binding sites and 27,981 AUF1 binding sites were identified. Of
these, 6,550 sites were common to both HuR and AUF1. To test if this overlap occurred by chance, we used
a hypergeometric test employing phyper in R, which returned a highly significant overlap p-value of <10e-22.
Briefly, the observed number of binding sites (6,550) was compared to the total possible binding sites
(57,161,827), which was calculated from the total transcriptome size (1,657,692,975) and median binding
size of 29 nt.
AUF1 binding sites=27981
HuR binding sites=83289
Overlap between AUF1 and HuR binding sites=6550
Total possible binding sites= 57161827
This gives a p-value of < 1.0e-22
Influence of AUF1 on splicing
AUF1 PAR-CLIP tags are most frequently found in introns. Depending on the isoform, intron tags comprise
53-85% independent tags, in the range seen for HuR (59%), which correspond to 64% to73% of all AUF1
target transcripts compared to 52% from HuR target transcripts (Supplementary Fig. 3a,b; pre-mRNAs
shared between AUF1 and HuR are listed in Supplementary Fig. 3b). Since other RBPs analyzed similarly
modulated the abundance of alternative transcripts [e.g., PTB, TDP43, Hu proteins]55-60, we studied if AUF1
affected the production of alternative transcripts from target pre-mRNAs. We overexpressed each AUF1
isoforms in HEK293 cells separately and compared the relative abundance of transcripts on a global scale by
RNA-Seq (Fig. 3c; Supplementary Tables 8-11). This analysis identified 24, 11, 291, and 6 transcripts
alternatively expressed when AUF1 p37, p40, p42, and p45 isoforms were overexpressed, respectively.
These results suggest that AUF1 might alter the abundance of select groups of transcripts, possibly by
affecting the splicing and/or stability of alternative transcripts. Future work to investigate a possible role of
AUF1 in splicing is warranted.
Yoon et al, page 12
SUPPLEMENTARY DISCUSSION
Comparison of transcriptomes and AUF1 levels among three cell types
Pairwise correlations among the three cell types in the study (HeLa, HEK293 and WI-38) were
calculated and plotted with log2-transformed FPKM (fragments per kilobase of exon per million
fragments mapped) values. As shown in Supplementary Fig. 4a, there was very high degree of
correlation (0.80 to 0.85) among all pairs compared, indicating that the transcript abundance in the three
cell types were very highly similar. The levels of AUF1 in HeLa and HEK293 were relatively similar,
as shown in Supplementary Fig. 4b; AUF1 was substantially higher in early-passage (PDL 15) WI-38
cells than in senescent (PDL 55) WI-38 cells, as earlier reported39
.
Limitations of PAR-CLIP
The method used here, PAR-CLIP, also has important limitations that restrict its use. For example, the
procedure is lengthy and has multiple steps requiring optimization and controls, and the sequencing is
costly and requires substantive bioinformatic expertise. The methodology also carries some bias
associated with the choice of crosslinking wavelength, the RNA linkers used in the preparation of the
small-RNA libraries, and the conditions of RNase digestion27,42
. However, as the PAR-CLIP technology
matures, a greater number of bioinformatic tools, including many tools that are more user-friendly, are
emerging (discussed in the main text).
SUPPLEMENTARY REFERENCES
55. Polymenidou, M., et al. Long pre-mRNA depletion and RNA missplicing contribute to neuronal
vulnerability from loss of TDP-43. Nat. Neurosci. 14, 459-468 (2011).
56. Lebedeva, S., et al. Transcriptome-wide analysis of regulatory interactions of the RNA-binding protein
HuR. Mol. Cell 43, 340-352 (2011).
57. Zhou, H. L., et al. Hu proteins regulate alternative splicing by inducing localized histone
hyperacetylation in an RNA-dependent manner. Proc. Natl. Acad. Sci. USA 108, E627-E635 (2011).
58. Tollervey, J. R., et al. Characterizing the RNA targets and position-dependent splicing regulation by
TDP-43. Nat. Neurosci. 14, 452-458 (2011).
59. Ince-Dunn, G., et al. Neuronal Elav-like (Hu) proteins regulate RNA splicing and abundance to control
glutamate levels and neuronal excitability. Neuron 75, 1067-1080 (2012).
Yoon et al, page 13
60. Xue, Y., et al. Direct Conversion of Fibroblasts to Neurons by Reprogramming PTB-Regulated
MicroRNA Circuits. Cell 152, 82-96 (2013).