SUPPLEMENTAL INFORMATION

The supplemental information includes the following material:

Supplemental note: related to supplemental Figure S1

Seven supplemental figures:

Supplemental Figure S1: Related to Materials and Methods

Supplemental Figure S2: Related to Figure 1

Supplemental Figure S3: Related to Figure 2

Supplemental Figure S4: Related to Figure 3 and Figure 4

Supplemental Figure S5: Related to Figure 4 and Figure 5

Supplemental Figure S6: Related to Figure 5

Supplemental Figure S7: Related to Figure 6

Six supplemental tables and one supplemental data file:

Supplemental Table S1: Related to Figure 1

Supplemental Table S2: Related to Figure 2

Supplemental Table S3: Related to Figure 4

Supplemental Table S4: Related to Figure 4

Supplemental Table S5: Related to Figure 4

Supplemental Table S6: Related to Figure 5

Supplemental Data File: Cufflinks-assembled transcriptome based on RNA-seq

data from control, XRN1-, SMG6/XRN1- and UPF1/XRN1-depleted samples.

Additional supplemental material:

Supplemental Materials and Methods

Supplemental References

1

SUPPLEMENTAL NOTE

Analysis of Transcripts in Total, polyA+ and polyA- RNA Preparations

We subjected RNA purified from control-, XRN1-, SMG6/XRN1- and UPF1/XRN1-

depleted HEK293--39 cells to oligo-dT selection and assessed its efficiency on a

set of transcripts. Spike-in RNAs with polyA-tails of 21-25nt in length and with

mono-phosphates at their 5’-ends were added in equal amounts to total RNA

samples before the selection procedure. We observed an efficient depletion of

~8- to ~18-fold from the polyA- fraction of the endogenous GAPDH mRNA and

the -39 nonsense reporter RNA (Supplemental Fig. S1D, first and second plot

from left in the top panel). The spike-in RNA molecules, represented here by T7-

Luc-pA, were similarly depleted (~10-fold) from the poly(A)- fraction

(Supplemental Fig. S1D, second plot from left in the bottom panel). In

comparison, the non-polyadenylated MALAT1 transcript was approximately 2-

fold depleted from the poly(A)- fraction in all samples (Supplemental Fig. S1D,

first plot from left in the bottom panel). Levels of -39 RNA were almost identical

in the total and polyA+ fractions when measured relative to GAPDH - which was

also seen for the spike-in RNAs (Supplemental Fig. S1D, second plot from the

right in the top and bottom panel). Finally, we measured the relative level of

RNA that had been ligated at the 5’-end. T7-Luc-pA served as a control, and the

relative levels of ligated molecules were virtually the same across all twelve

samples (Supplemental Fig. S1D, first plot from right in the bottom panel).

Importantly, the relative levels of ligated -39 molecules appeared very similar

between the polyA+ and the total RNA sample (and even in the polyA- fraction;

Supplemental Fig. S1D, first plot from right in the upper panel). Based on these

2

observations, we concluded that the polyA+ fraction represents well the total

sample when it comes to measuring decapping levels of nonsense RNAs.

Based on the northern blot in Supplemental Fig. S1B and previous observations

(Eberle et al. 2009) it is also clear that the 3’-fragment produced after SMG6-

catalyzed endocleavage can be enriched in the polyA+ fraction.

3

SUPPLEMENTAL FIGURES

4

Supplemental Figure S1. Overview and quality control of the experimental

procedure, Related to Methods

(A) Schematic overview of the principle behind the massive parallel sequencing

approach used in this study (see also Fig. 1A). (B) Northern blotting analyses

monitoring the various steps of the digitonin extraction procedure of HEK293--

39 cells depleted for the indicated factors; (lanes 1-4) whole-cell total RNA,

(lanes 5-8) total RNA from the pellet (enriched for nuclei and other membrane-

bound organelles), (lanes 9-12) total RNA from the digitonin extract (enriched

with soluble cytoplasm), (lanes 13-16) polyA+ RNA from the digitonin extract

and (lanes 17-20) polyA- RNA from the digitonin extract. Northern membranes

were hybridized with probes directed against the 3’-region of the -39 reporter

RNA, 16S mitchondrial rRNA, U3 snRNA and tRNALys (the latter three to verify the

enrichment of mitochondria/nuclei and cytoplasm in the pellet and the digitonin

extract, respectively). 28S and 18S rRNA levels were detected by methylene blue-

staining of the membrane. (C) Western blotting analyses of cell extracts verifying

depletion of the indicated factors. The upper panel corresponds to the samples

used for massive parallel sequencing. The lower panel is representative of all

other presented depletion experiments. Western membranes were probed with

antibodies recognising XRN1, SMG6 and UPF1. Gel loading was controlled by

probing membranes with an anti-U170K antibody (upper panel) or a -actin

antibody (lower panel). (D) qPCR analyses of the indicated transcripts

performed on reverse-transcribed total, polyA+ or polyA- RNA isolated from the

HEK293--39 cell line either control-depleted (red) or depleted for XRN1 (blue),

SMG6/XRN1 (green) or UPF1/XRN1 (orange). Relative ligation (right panel) is

normalized to the XRN1 sample within each fraction.

5

6

Supplemental Figure S2. PTC-Proximal Endocleavages of Endogenous

Nonsense RNAs, Related to Figure 1

(A-E) Overview of the sequencing data used in the analyses of the endogenous

genes MATR3 (A-B), NOP56 (C-D) and ATF4 (E) as examples of detected NMD-

specific endocleavages (A, C and E are as Fig. 1C and B and D are as Fig. 1F). (F)

Northern blotting analyses of total RNA isolated from the HEK293--39 cell line

depleted for the indicated factors. The northern membranes were hybridized

with probes directed against regions downstream of the endocleavage sites in

the MATR3 (upper panel), ATF4 (middle panel) and NOP56 (lower panel) RNAs,

respectively. GAPDH levels were detected as an internal loading standard. (G)

Northern blotting analyses of cycloheximide pulse/actinomycin D-chase

experiments performed in the context of control- or UPF1-depletion on -39,

SNHG15, NOP56, ATF4, GADD45A, GAS5 and EIF5 nonsense RNAs as indicated.

GAPDH levels were detected as an internal loading standard. The estimated half-

lives are indicated in red below the name of the RNA species (ctrl to left and

UPF1 to the right). Similar results were obtained from actinomycin D chase

experiments (data not shown). (H) Positions of NMD-specific endocleavages

mapped to the ‘NMD reference set’ relative to the annotated stop codons.

7

8

Supplemental Figure S3. NMD-Specific Decapping Sites in Endogenous

Nonsense RNAs, Related to Figure 2

(A-G) Overview of the sequencing data used in the analyses of the genes (A-B)

TRA2B, (D-E) RSRC2 and (G) SNHG15 as representative examples of endogenous

genes expressing RNA undergoing NMD-specific decapping (A, D and G are as Fig.

1C and B and E are as Fig. 1F). (C,F,H) Relative decapping (left panel, as Fig. 2B)

and levels of RNA co-immunoprecipitated with endogenous UPF1 (right panel, as

Fig. 2F) of (B) TRA2B nonsense RNA (upper panel) and mRNA (lower panel), (F)

RSRC2 nonsense RNA (upper panel) and mRNA (lower panel) and (H) SNHG15

nonsense RNA. Decapping levels are relative to levels measured upon XRN1-

depletion. All co-IP values are relative to co-IP’ed levels of -39 under control

conditions. Relative decapping and immunoprecipitation measurements are

from four (n=4) and two (n=2) independent experiments, respectively. Error-

bars depict standard deviations.

9

Supplemental Figure S4. Pipelines For Identification of NMD-Targeted

Transcripts/Genes Based on 5’end-seq and RNA-seq, Related to Figure 3

and Figure 4

(A-B) See text in the figure and main manuscript for details..

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11

Supplemental Figure S5. Global Overview of NMD-Specific Endocleavage

and Decapping Events in NMD-sensitive Transcript Isoforms, Related to

Figure 4 and Figure 5

(A-C) The same analysis as in Fig. 3A-B and 4A, but focusing on transcripts rather

than genes. (A-B) See legend for Fig. 3A-B. (C) See legend for Fig. 4A. (D) Same as

Fig. 4B., producing an NMD-substrate set based on the combined analysis of

RNA-seq and 5’end-seq, but using ‘relaxed’ criteria for peak calling in the 5’-end-

seq data. This NMD set is listed in Supplemental Table S4. (E) As Fig. 5A, but

based on ‘relaxed’ criteria for identification of NMD-responsive genes. ***

indicates that snoRNA host genes are significantly enriched compared to protein-

coding genes (Fisher two-sided test, P = 8.9·10-12). (F) Density plot (left panel)

illustrating the significant differences between snoRNA host genes (n=173) and

highly expressed protein-coding genes (n=3000; expression distributions are

shown in the right panel), in terms of the fraction of nonsense isoforms out of the

total number of produced isoforms (defined by RNA-seq). Relative densities from

the given groups are calculated by kernel density estimation (KDE) with

Gaussian kernel. (G) Venn diagrams displaying the number of SRSF-protein

coding genes that produce one or more nonsense isoforms identified

independently by RNA-seq and 5’-end-seq by ‘stringent’ (left) and ‘relaxed’

(right) criteria (based on the NMD-substrate sets in Supplemental Table S3). The

numbers below signify the combined number of NMD-substrates based on both

RNA-seq and 5’-end-seq vs the total number of genes in the category. (H) As G,

but for snoRNA host genes.

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Supplemental Figure S6. NMD-sensitive snoRNA Host Genes In Human and

Mouse Cells, Related to Figure 5

(A) As Fig. 5C, but northerns were probed for the following host/snoRNA-pairs:

C17orf76-AS1/SNORD49A, ZNFX1-AS1/SNORD12, GAS5/SNORD79,

SNHG5/SNORD50A, TAF1D/SNORA32, EIF4A2/SNORD2, EIF5/SNORA28 and

NOP56/SNORD110. The snoRNA host genes are annotated as non-coding and

protein-coding in the left and right panels, respectively. Slowed decay under

UPF1-depletion conditions is demonstrated for the GAS5, EIF5 and NOP56

transcripts in Supplemental Fig. S2G. (B) An artificial ‘double’-snoRNA,

SNORA73A+B, was expressed from the second intron of the stably inserted host

genes -wt-snoHost and -39-snoHost under the indicated conditions.

Uninduced cells were included in the experiment to control for the dependence

of the ‘double’-snoRNA expression on the transcription of the host genes.

Northern blots show the spliced -globin transcripts and GAPDH as a loading

control and the exogenous ‘double’-snoRNA is detected with a probe that also

detects the endogenous individual snoRNAs (SNORA73A/73B). (C) As Fig. 5B, but

the analysis was done on RNA-seq data generated from bone marrow

macrophages (C) and liver cells (D) from control and UPF2-deficient mice. For

both tissues, the snoRNA host genes tend to produce more nonsense isoforms

than protein-coding genes that are expressed at the same or higher levels.

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15

Supplemental Figure S7. Comparison of Protein- and Non-Coding Single-

and Multi-snoRNA Host Genes, Related to Figure 6

(A) histogram displaying the number of single- and multi-snoRNA host genes

used for the analyses in this study. The number of genes annotated as protein-

and non-coding is displayed in blue and red, respectively. (B) Boxplot illustrating

the distributions of the RNA-seq-based gene expression levels (FPKM) of single-

and multi-snoRNA host genes and groups of similar expressed protein-coding

genes (as indicated) that are used for the comparison in Fig. 6B-C. (C) Boxplot

illustrating the distributions of the RNA-seq-based gene expression levels

(FPKM) of protein-coding and non-coding multi- and single-snoRNA host genes

as indicated. (D) As Fig. 6B-C, but here comparing the distributions for protein-

coding and non-coding genes within the single- and multi-snoRNA host gene-

categories.

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SUPPLEMENTAL TABLES

Supplemental Table S1. Sequencing and Mapping Statistics for RNA-seq, 5'-

end-seq and CAGE, Related to Figure 1. Excel-file containing two spreadsheets

that list 1) the Mapping Strategy and Parameters and 2) Mapping Statistics.

Supplemental Table S2. NMD thresholds & NMD and non-NMD Transcript

Reference Sets, Related to Figure 2. Excel-file containing one spreadsheet that

describes the details of how the NMD thresholds are calculated and two

spreadsheets that list all ensembl transcript IDs and corresponding gene symbol

of transcripts belonging to the ‘NMD reference set’ and the ‘non-NMD reference

set’. Note that the de novo settings were not used for analysis of this set.

Supplemental Table S3. NMD Substrates Based on Independent Methods,

Related to Figure 4. Excel-file containing two spreadsheets that list the NMD

sets identified independently by RNA-seq and 5’-end-seq, respectively. The sets

are represented in the Venn diagrams in Fig. 4B.

Supplemental Table S4. NMD Substrates Based on Combined Analysis of

RNA-seq and 5'-end-seq, Related to Figure 4. Excel-file containing two

spreadsheets that list the genes and transcripts found by combined analysis of

5’-end-seq and RNA-seq, using stringent and ‘relaxed’ 5’-end-seq peak

identification, respectively (presented in Fig. 4B and Supplemental Fig. 5D).

Supplemental Table S5. SRSF-Protein Coding Genes, Related to Figure 4.

Excel-file containing one spreadsheet that lists the current members of the SRSF-

protein family and corresponding gene and transcript IDs (based on Long and

Caceres 2009). The genes identified as NMD-responsive in the paper by Lareau

et al. (2007) are highlighted in yellow. GenCode names for these are SRSF1 -

SRSF11.

Supplemental Table S6. snoRNA Host Genes and Their Intron-Encoded

snoRNAs, Related to Figure 5. Excel-file containing one spreadsheet that lists

the snoRNA host genes and their ‘active’ intron-encoded snoRNAs that were

used for the analyses in this manuscript.

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18

SUPPLEMENTAL MATERIALS AND METHODS

Cloning of Artificial -globin snoRNA Host Genes

Inspired by a study by Kiss and Filipowicz (1995), we used standard cloning

procedures to insert a ‘double-snoRNA gene’ consisting of the complete

sequences encoding SNORA73A and SNORA73B into the second intron of the -

globin-wt and -PTC39 reporter genes in the context of the pcDNA5 FRT/TO

vector. Subsequently, we created stable HEK293 Flp-In T-Rex cell lines, -wt-

snoHost and -39-snoHost, as previously described (Eberle et al. 2009). Upon

transcription and splicing of the host gene precursor RNA, the hybrid double-

snoRNA is expressed, whereas the individual snoRNAs are not produced. The

exogenous double-snoRNA (SNORA73A+B) can be distinguished from

endogenous SNORA73A and SNORA73B (SNORA73A/B) due to their difference in

size.

Determination of RNA Decay Rates

HEK293--39 cells either control- or UPF1-depleted were treated for 5 hours

with 25 µg/mL cycloheximide in DMEM/10%FBS to accumulate endogenous

nonsense RNAs to detectable levels. Thereafter, cycloheximide was washed out

and cells were allowed to recover for 1 hour in DMEM/10%FBS. Subsequently,

transcription was stopped by addition of 1 µg/mL actinomycin D in

DMEM/10%FBS and cells were harvested at time points 0, 30, 60, 90, 120, 240

and 360 minutes and analyzed by northern blotting.

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Probes Used For Northern Blotting Analyses

The following 5’-end labeled DNA oligonucleotide northern probes were used:

Target SequenceSNORA9 TTC AAA ACT GTT CTA GCA AGC ACT GAA GGA ATG CAT AGG GSNORA28 TTG TCT CAT GGG AGA GAG AAC ACC GGA ATA GGT TAG ACT TSNORA32 CCC AAT AAG CTG ATT GCT AGC AAA GTA GCA GAT AGA AAA CSNORA73 GAC TCT GGG AAG CTG TAG GAA TAT GCA GGC GCA GAC ACG ASNORD2 TAT TCT CTT CAT TTC AGG TCA GTC CCG AAA GAT GAT TGC CSNORD12 CAA TAG TGT AGA GAT CAA CAG GGT CGA TCT GAT GGG GAA ASNORD49A AGT TAT CGC TTC TGA CGG CAC TTC CTA TTA GTG ATT TCA TSNORD49B CAG TTA TCG CTT CTG ACG GCA CTT CCT ATT ACA AGT ATC ASNORD50A TTT TCA ACA GAA GTT CAG GTT CGG GAT AAG ATC ATC ACA GSNORD79 ATC TCC ATT TTC TTT CTC AGA GAG ATT CCC ATC TGC TTT ASNORD110 AGA GAC ATG GAG ACA TCA GTG ATT GCA CTC AGG GGA TTG ASNORD126 TCA GGC TGA TCA GCT GAA ACA CGG ACT TAA CAT GCA TTT CtRNALys CTG ATG CTC TAC CGA CTG AGC TAT CCG GGCU3 snoRNA ACC ACT CAG ACC GCG TTC TCT CCC TCT CACU6 snRNA GAA TTT GCG TGT CAT CCT TGC GCA GGG GCC ATG CTA A

The following labeled riboprobes were used for detection by northern blotting:

16S rRNA (mitochondrial):GCUAAACCUAGCCCCAAACCCACUCCACCUUACUACCAGACAACCUUAGCCAAACCAUUUACCCAAAUAAAGUAUAGGCGAUAGAAAUUGAAACCUGGCGCAAUAGAUAUAGUACCGCAAGGGAAAGAUGAAAAAUUAUAACCAAGCAUAAUAUAGCAAGGACUAACCCCUAUACCUUCUGCAUAAUGAAUUAACUAGAAAUAACUUUGCAAGGAGAGCCAAAGCUAAGACCCCCGAAACCAGACGAGCUACCUAAGAACAGCUAAAAGAGCACACCCGUCUAUGUAGCAAAAUAGUGGGAAGAUUUAUAGGUAGAGGCGACAAACCUACCGAGCCUGGUGAUAGCUGGUUGUCCAAGAUAGAAUCUUAGUUCAACUUUAAAUUUGCCCACAGAACCCUCUAAAUCCCCUUGUAAAUUUAACUGUUAGUCCAAAGAGGAACAGCUCUUUGGACACUAGGAAAAAACCUUGUAGAGAGAGUAAAAAAUUUAACACCCAUAGUAGGCCUAAAAGCAGCCACCAAUUAAGAAAGCGUU

ATF4:UAUACCCAACAGGGCAUCCAAGUCGAACUCCUUCAAAUCCAUUUUCUCCAACAUCCAAUCUGUCCCGGAGAAGGCAUCCUCCUUGCUGUUGUUGGAGGGACUGACCAACCCAUCCACAGCCAGCCAUUCGGAGGAGCCCGCCUUAGCCUUGUCGCUGGAGAACCCAUGAGGUUUGAAGUGCUUGGCCACCUCCAGGUAAU

20

-globin:UCUGAUAGGCAGCCUGCACUGGUGGGGUGAAUUCUUUGCCAAAGUGAUGGGCCAGCACACAGACCAGCACGUUGCCCAGGAGCCUGAAGUUCUCAGGAUCCACGUGCAGCUUGUCACAGUGCAGCUCACUCAGUGUGGCAAAGGUGCCCUUGAGGUUGUCCAGGUGAGCCAGGCCAUCACUAAAGGCACCGAGCACUUUCUUGCCAUGAGCCUUCACCUUAGGGUUGCCCAUAACAGCAUCAGGAGUGGACAGAUCCCCAAAGGACUCAAAGAACCUCUAGGUCCAAGGGUAGACCACCAGCAGCCUGCCCAGGGCCUCA

C17orf76-AS1:GGUAUAGAACCUCUUGUUGGGCAUGAUGGCAAGGGACAAAGCUACAACUUGGCCUGUGCCUUUGGAAGCUGAGGCAGGAGGACCAUCUGAGCCCAGGAGCCUGAGACCAGCCUGGGCAACAUAGAGAAUCCGUCUCAACAAAAAAAAAAUUUUAGCCAGGUGUGCUGUGAGCUGUAGUCCCAGCUACAAGGUGGGAGGAUUGCUUAGGCCUGGGUGAUUGAGGAUGCAAUGAGCUGUGAUUGUGCCACCACACUCCAGCCUGGGCAAUACAGCAAGACUGUCUCAAAAAAAAAAAAAAAAACCCAAAAAAACUCAAGAAUGUAAUGAAUGAUACCCAAUGUGCCUUUUCUAGAAAAAGUUGCCAAAUAUAUCUCUUGGAUCUGCUGAGCAUGUCCUCUGAUACAUAAGGCAAGCAUGUUUCUACACCCAGUGUUGAUGCCAGUUAGUU

CCNB1IP1:GUGCAGUGGCAUGAUCUUAGAUCACUAAAGCCUCAGACUCCUGGGCUCAAGUGAUCCUCCCAGCCUCAACCUCCUAAGUAGCUGGGAUCACAGGUGCGUGACACUAUGCGUGGCUCAAAUUCUUUUUACUUUGAAGGCCCUGCUAGAAACUUGCUGCUGCUCUAAUUCACGACUUGGAGAGACAAAACUAAAAAAGCUGUUGCUGGGUUCAGGUGCUGUGGGAGAACCCGCAAAAAAUGGUCUGAACUGAAAAUCUCCAUCUCCAUCGCCCCGAUUUCGAACAGGUGUAUUAUCCAAAGGAAACUUGGAGUUGUUACCUAAUGGGAAGCCAAGAACACCAGACUGUGCAAUCAUGGAUGGUUCAAGGGUGCCUUCAUGGUUAGCAAUAGUGAUGUUUCGUAGCCUAAGGCUAUCAUAGAGGCCUUGGAGCUUUUGAU

EIF4A2:CAAUGUCACGAAGAAUCCUCUUGUCUUCUUCAGUAACAAAGUUUAUAGCCACACCUUUCCUCCCAAAUCGACCCCCUCUGCCAAUUUCGCUCUUUAUUCAAACAGUGUGCUGUUUCGCUUAUGAUUCCACGUCCUAAAUUACGUCAACGCCGUUUCUGAGUGCCAUCUCGUCACCAACUGCUGCUAUCGACUCCUGUGAAU

EIF5:GGUGAUGCUCUUGUAAACAGUGUAUUGCUAGACCUAAAAAUCCAAGCUUACAACUUGUCCUUUACCUGAUACAUUUAUUCCAUUUACUUUCAUUUGGAUUUUUAAAAAUGUUAACUUAAUACGUCUCUUUCAGAUGUCCCUGCUUUUUAGUUAAUUGUGUUUUCUACUCUCCUAAAGACUUGAUUUUUAUUUUUUAGUUAACUGACCGUUUUUAAAGAGGUUUUAGGCUCAUAGCAAAAUUGGGUGGAAUUUCCCCUACUGCCCCAGCCAGGCAUUGCUUCUGACUGCAGCAUUAGGCUUCCAGUGGGAUUGAGUGCUGCACAUAAGGGUCUCCACCCCCAGCAGAUAUGGAAAGGCAAUCCCCUAGUUUUACAGUAAGGCCUGGGACAGAAUCCAAAUUUGAUCCCAACACCCAAGUGAAUCCUCCUCCUCUUAAAAAGAAAUAAUUGACUGCAUAACCGAACUGCAGGGUCAACUCAGAUCCUACCAUUCACC

21

GADD45A:CCAAACUAUGGCUGCACACUUAAACUUUAACAUAUUUGGUUUAUUUUAAUGUAACUCAACCAUUCUAAAUUAAUACAUAGUUUUCCUUCCUGCAUGGUUCUUUGUAAUUUUUGUUCCUUUUGACUUAUUUUUCUGUUUCAACACAGCUUCCUUCUUCAUUUUCACCUCUUUCCAUCUGCAAAGUCAUCUAUCUCCGGGCCCCCAGAACAUGUAGUUGAACUCACUCAGCCCCUU

GAPDH:CAUGUGGGCCAUGAGGUCCACCACCCUGUUGCUGUAGCCAAAUUCGUUGUCAUACCAGGAAAUGAGCUUGACAAAGUGGUCGUUGAGGGCAAUGCCAGCCCCAGCGUCAAAGGUGGAGGAGUGGGUGUCGCUGUUGAAGUCAGAGGAGACCACCUGGUGCUCAGUGUAGCCCAGGAUGCCCUUGAGGGGGCCCUCCGACGCCUGCUUCACCACCUUCUUGAUGUCAUCAUAUUUGGCAGGUUUUUCUAGACGGCAGGUCAGGUCCACCACUGACACGUUGGCAGUGGGGACACGGAAGGCCAUGCCAGUGAGCUUCCCGUUCAGCUCAGGGAUGACCUUGCCCACAGCCUUGGCAGCGCCAGUAGAGGCAGGGAUGAUGUUCUGGAGAGCCCCGCGGCCAUCACGCCACAGUUUCCCGGAGGGGCCAUCCACAGUCUUCUGGGUGGCAGUGAUGGCAUGGACUGUGGUCAUGAGUCCUUCCACGAUACCAAAGUUGUCAUGGAUGACCUUGGCCAGGGGUGCUAAGCAGUUGGUGGUGCAGGAGGCAUUGCUGAUGAUCUUGAGGCUGUUGUCAUACUUCUCAUGGUUCACACCCAUGACGAACAUGGGGGCAUCAGCAGAGGGGGCAGAGAUGAUGACCCUUUUGGCUCCCCCCUGCAAAUGAGCCCCAGCCUUCUCCAUGGUGGUGAAGACGCCAGUGGACUCCACGACGUACUCAGCGCCAGCAUCGCCCCACUUGAUUUUGGAGGGAUCUCGCUCCUGGAAGAUGGUGAUGGGAUUUCCAUUGAUGACAAGCUUCCCGUUCUCAGCCUUGACGGUGCCAUGGAAUUUGCCAUGGGUGGAAUCAUAUUGGAACAUGUAAACCAUGUAGUUGAGGUCAAUGAAGGGGUCAUUGAUGGCAACAAUAUCCACUUUACCAGAGUUAAAAGCAGCCCUGGUGACCAGGCGCCCAAUACGACCAAAUCCGUUGACUCCGACCUUCA

GAS5:CCAUCAGGCAGUCUACAAAGACCACUGGGAGGCUGAGGAUCACUUGAGCCCAGAAGUUUGAGGCUGUAGUAAGCUUCAAAGGCCACUGCACUCUAGCUUGGGUGAGGCAAGACCCUUUCAAGCAGUAAGCUGCAUGCUUGCUUGUUGUGGUCAUUAAAAACCCUAGUUUAGGAUAACAGGUCUGCCUGCAUUUCUUCAAUCAUGAAUUCUGAGUCCUUUGCUUCUUUAAAACUUGCUCCACACAGUGUAGUCAAGCCGACUCUCCAUACCUUUAAAAGGUAUGACAGGAACUGUCUUCAUGUCCUUACCCAAGCAAGUCAUCCAUGGAUAAAAACGUUACCAGGAGCAGAACCAUUAAGCUGGUCCAGGCAAGUUGGACUCCACCAUUUCAACUUC

22

HNRNPH3:CUUUAGACAUGGCAGCUACUGCAUCUUCAUGUGUCACAAACUCUACAUCUGCUUCUCCUGUGGCUCUGCCAUCAGCUCCAAUAUCAAUAUGAACUCGUAUUGGAUUUAGUGGUGAGAAGAAAUUAGCAAUGUCAUUUUCAGUUGCACGAAAAGGCAACCCUCUCAUAUGUACGAAAUGACCACCAUGAAAACCUGAACUUGCAUCACCAGCUCCACCAUAGCCAUGUCCUCCCAUACCUCUUCCAUCUCUCAUUCUGUCAUCAAAGCCAUCAUUCCCAUAGCCGUAAUUAUUAUAGCCACCAUAGUCAUCAAAACCUCCAUAACCACCAUCAUAUCCAUCACCUCCUCGUCGCAUUCUGUCAUACAUACUUCCACGCCCAGCUCCAUAAUAACCCCCUCUUCCUCCUAUUGGUCUAUCAUAUGGUCCCGGUCGC

MATR3:GGUAGAACCAUUUGGAGUCAUUUCAAAUCAUCUGAUUCUAAAUAAAAUUAAUGAGGCAUUUAUUGAAAUGGCAACCACAGAGGAUGCUCAGGCCGCAGUGGAUUAUUACACAACCACACCAGCGUUAGUAUUUGGCAAGCCAGUGAGAGUUCAUUUAUCCCAGAAGUAUAAAAGAAUAAAGAAACCUGAAGGAAAGCCAGAUCAGAAGUUUGA

NOP56:GAAACUUGGUCCCUUUGCUGGGCCCUGGGAAUCACUCAGACACCAGGACUGGCCAUCACCCCCAUAGCAGAGGCCUGUAUAGGUCAGGGAGCCCUGGUCAGCCAUCACCGUGAUCCCCCAACAAGCAGUGGGCACCAGAAGUGGCACCUGAUU

SNHG5:GAAGAGCUUUUUUCUGGAUGGUUUUCUUAUCAGCUUUUCACACAACAGUCAAGUAAACCUCGUGGCACUAGCCAGAAAUCGUUGCAACUUUGGAACUUCCAAGACAAUCUGGCCUCUAUCAAUGGGCAGACAGCGACCCUCAUUCAAAAUGAAGCUGCUAGUCAGUCACAUUCGACAUUCAUUAUCUUCACUGGCUACUCGUCCACACUCAGAACGCUGUUCACUGUUAAAAGUGUCAGGUUUUAACCAAGCGAUUUUCCAUUAAAUAUUCUCCCAGAUGUUCUGGAAGUUUUUUCGUGUAUCUUUGCAUCUUCAGAGCUGCUCCACUGUGCCACUGAAGACAGCGCCAUUGUUCCUACCACCC

SNHG15:GAGAUACCAGAAGGGCCCAGGUCCUGGUGCACAGCAAAGCUUCUCAUUCUGGAAGCAGAGAACCUGGCACCCAAACCUAGGGCCAGAGGUCUGUCUGCCAGACCCACAGCCCAGGCCCAGAACUGGAAAUUCCUGACUCCUUCCAGAAGGGCAACAAGCGAGGUUUCAAACUUGCUCAAUUAAGGUGCCAAGGCUUGCAUUCAAAUUCAGCUCCACUCCUCACUAGGUGUAUUAACACAGGCAGGCCUCAUCCCUGCACAGGUUCCAAGGAACAGCCUGGCAGCCACUGAAGGUAUCUUCUCUCAGGUCAGGUCCCCUCUAGCUCCAGCAUCUUGGGAUUGCUGCUGUAGAAACACUGACGGAUGGCAGGCACUCUUGUGCCAUGUGCUGGG

TAF1D:GUGAUUUCUUCCACUGUCCAUCAAGGUCACUUUAGAUCCUCUAAAGAGCUGGAGUCAAAAGAUUUAUCUUCAAGUUUGCCCUUUUUAAUGAAACUGAUCCAGUUGUCCUGUCAGCCCAUAAUUACUUUGGCUUCUGUCAUCUCGUUUUAAUAUGGAUAUACUGAUGAAGACUUCAAAAUUCACCAAGAAUCUUUGGGAUCUAAUUUCUUCAACCAAUUUACUUUAGGGUCCUUUUUACUGUAGGUGGUGGGGAUCUACCUGGUUCUCAAUUUGACACC

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CUCUCAACAUGAAUGAGUUCAAAUCACAUUCAUUCCUAAGCGAUCACUCAAGAAUGGUACAGAUGUGUGG

ZNFX1-AS1:GCAGGUAGGCAGUUAGAAAUUUCAAAGUCUAACAAUGACAUUCUUGAAGUGGGCACAGCCUUUUAAACUCAGGCUAUGUAUACAGUAACCUUGUGGAACUGGUUCAGCCAGAUCUUCACUUUCAUGAAAGCACAGGGUCUGUCCUUUUCUUUCCAGAGGGCUCCUCUCAUAUUCCAUCGCCAGUUUCAAUUUUAUAUGUAUAUAUAUAUUCUACUUCCAACACCCGCAUUCAUCCUGGUUCAAUCAAAGCCUGGUUUUGGCCAACAAUAAACUCGUCAGGAGAUCGAAGGUUGUAGAUGUCUGCACGUGGCUUCCUUGGAGGUCCAGUGGUGACUCCCUCUUCCAAAAUCCAUUCUGUACCCGCUGGCUGCUCUAACGGGCAGGACAAUAGCGUAUGAAGCCUGACUG

Spike-In RNA Sequences

T7_Luc_pA:UGGGAGAUGGAAGACGCCAAAAACAUAAAGAAAGGCCCGGCGCCAUUCUAUCCGCUGGAAGAUGGAACCGCUGGAGAGCAACUGCAUAAGGCCAUGAAGAGAUACGCCCUGGUUCCUGGAACAAUUGCUUUUACAGAUGCACAUAUCGAGGUGGACAUCACUUACGCUGAGUACUUCGAAAUGUCCGUUCGGUUGGCAGAAGCUAUGAAACGAUAUGGGCUGAAUACAAAUCACAGAAUCGUCGUAUGCAGUGAAAACUCUCUUCAAUUCUUUAUGCCGGUGUUGGGCGCGUUAUUUAUCGGAGUUGCAGUUGCGCCCGCGAACGACAUUUAUAAUGAACGUGAAUUGCUCAACAGUAUGGGCAUUUCGCAGCCUACCGUGGUGUUCGUUUCCAAAAAGGGGUUGCAAAAAAUUUUGAACGUGCAAAAAAAAAAAAAAAAAAAAAAAAAAAGGGCGAAUUCGCGGCC

T7_EGFP_pA:GGGAGACCCAAGCUUGUCGCCACCAUGGUGAGCAAGGGCGAGGAGCUGUUCACCGGGGUGGUGCCCAUCCUGGUCGAGCUGGACGGCGACGUAAACGGCCACAAGUUCAGCGUGUCCGGCGAGGGCGAGGGCGAUGCCACCUACGGCAAGCUGACCCUGAAGUUCAUCUGCACCACCGGCAAGCUGCCCGUGCCCUGGCCCACCCUCGUGACCACCCUGACCUACGGCGUGCAGUGCUUCAGCCGCUACCCCGACCACAUGAAGCAGCACGACUUCUUCAAGUCCGCCAUGCCCGAAGGCUACGUCCAGGAGCGCACCAUCUUCUUCAAGGACGACGGCAACUACAAGACCCGCGCCGAGGUGAAGUUCGAGGGCGACACCCUGGUGAACCGCAUCGAGCUGAAGGGCAUCAAAAAAAAAAAAAAAAAAAAAAAAAAAGGGCGAAUUCGCGGCC

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T3_Luc_pA:GGGAGACACGGCGAUCUUUCCGCCCUUCUUGGCCUUUAUGAGGAUCUCUCUGAUUUUUCUUGCGUCGAGUUUUCCGGUAAGACCUUUCGGUACUUCGUCCACAAACACAACUCCUCCGCGCAACUUUUUCGCGGUUGUUACUUGACUGGCGACGUAAUCCACGAUCUCUUUUUCCGUCAUCGUCUUUCCGUGCUCCAAAACAACAACGGCGGCGGGAAGUUCACCGGCGUCAUCGUCGGGAAGACCUGCGACACCUGCGUCGAAGAUGUUGGGGUGUUGGAGCAAGAUGGAUUCCAAUUCAGCGGGAGCCACCUGAUAGCCUUUGUACUUAAUCAGAGACUUCAGGCGGUCAACGAUGAAGAAGUGUUCGUCUUCGUCCCAGUAAGCUAUGUCUCCAGAAUGUAGCCAUCCAUCCUUGUCAAUCAAGGCGUUGGUCGCUUCCGGAUUGUUUACAUAACCGGACAUAAUCAUAGGACCUCUCACACACAGUUCGCCUCUUUGAUUAACGCCCAGCGUUUUCCCGGUAUCCAGAUCCACAACCUUCGCUUCAAAAAAAAAAAAAAAAAAAAAAAAAAAGGGCGAAUUCGCGGCC

T3_Neo_pA:GGGAGAUCUCGUGAUGGCAGGUUGGGCGUCGCUUGGUCGGUCAUUUCGAACCCCAGAGUCCCGCUCAGAAGAACUCGUCAAGAAGGCGAUAGAAGGCGAUGCGCUGCGAAUCGGGAGCGGCGAUACCGUAAAGCACGAGGAAGCGGUCAGCCCAUUCGCCGCCAAGCUCUUCAGCAAUAUCACGGGUAGCCAACGCUAUGUCCUGAUAGCGGUCCGCCACACCCAGCCGGCCACAGUCGAUGAAUCCAGAAAAAAAAAAAAAAAAAAAAAAAAAAAGGGCGAAUUCGCGGCC

Sp6_Neo_pA:GAAGAGACAGGAUGAGGAUCGUUUCGCAUGAUUGAACAAGAUGGAUUGCACGCAGGUUCUCCGGCCGCUUGGGUGGAGAGGCUAUUCGGCUAUGACUGGGCACAACAGACAAUCGGCUGCUCUGAUGCCGCCGUGUUCCGGCUGUCAGCGCAGGGGCGCCCGGUUCUUUUUGUCAAGACCGACCUGUCCGGUGCCCUGAAUGAACUGCAGGACGAGGCAGCGCGGCUAUCGUGGCUGGCCACGACGGGCGUUCCUUGCGCAGCUGUGCUCGACGUUGUCACUGAAGCGGGAAGGGACUGGCUGCUAUUGGGCGAAGUGCCGGGGCAGGAUCUCCUGUCAUCUCACCUUGCUCCUGCCGAGAAAGUAUCCAUCAUGGCUGAUGCAAUGCGGCGGCUGCAUACGCUUGAUCCGGCUACCUGCCCAUUCGACCACCAAGCGAAACAUCGCAUCGAGCGAGCACGUACUCGGAUGGAAGCCGGUCUUGUCGAUCAGGAUGAUCUGGACGAAGAGCAUCAGGGGCUCGCGCCAGCCGAACUGUUCGCCAGGCUCAAGGCGCGCAUGCCCGACGGCGAGGAUCUCGUCGUGACCCAUGGCGAUGCCUGCUUGCCGAAUAUCAUGGUGGAAAAAAAAAAAAAAAAAAAAAAAGGGCGAAUUCGUUUAAACCUGCAGGACUAG

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Primers Used For RT-qPCR Analyses

The following primers were used for RT-qPCR analyses:

GAPDH mRNAFW GTC AGC CGC ATC TTC TTT TGRE GCG CCC AAT ACG ACC AAA TC

MALAT1* lncRNAFW AAA GCA AGG TCT CCC CAC AAGRE GGT CTG TGC TAG ATC AAA AGG CA

-globin mRNAFW ACG TGG ATG AAG TTG GTG GTGRE TCT GAT AGG CAG CCT GCA CTG

-globin decapped mRNAFW CGA CGC TCT TCC GAT CTA GAGRE CCG GTG TCT TCT ATG GAG GTC

HNRNPH3 nonsense RNAFW CTC CCT TCT TTG AAC TGG ACRE TAC TTC TGA AGA TCT CAA TAT ACC TTG

HNRNPH3decapped nonsense RNA

FW ACG CTC TTC CGA TCT GTCRE TAC TTC TGA AGA TCT CAA TAT ACC TTG

HNRNPH3 mRNAFW CTC CCT TCT TTG AAC TGG ACRE GGC ACG ATT TCC AAC C

HNRNPH3 decapped mRNAFW ACG CTC TTC CGA TCT GTCRE GGC ACG ATT TCC AAC C

TRA2B nonsense RNAFW GGA GCA TTT CGG CTC TGARE ATG ACG ACT TCC GCA TTT TC

TRA2Bdecapped nonsense RNA

FW CGA CGC TCT TCC GAT CTA GAGRE ATG ACG ACT TCC GCA TTT TC

TRA2B mRNAFW GGA GCA TTT CGG CTC TGARE GAA GCA GAA CGG GAT TCC

TRA2B decapped mRNAFW CGA CGC TCT TCC GAT CTA GAGRE GAA GCA GAA CGG GAT TCC

RSRC2 nonsense RNAFW TAT GGC GGC TAG TGA TAC AGRE GTT CAG TCT CTT CGC GCA

RSRC2decapped nonsense RNA

FW GCT CTT CCG ATC TGC CTRE GTT CAG TCT CTT CGC GCA

RSRC2 mRNAFW TAT GGC GGC TAG TGA TAC AGRE GGA TTC ATG TCT TCT TCC CTC

RSRC2 decapped mRNAFW GCT CTT CCG ATC TGC CTRE GGA TTC ATG TCT TCT TCC CTC

SNHG15 nonsense RNAFW CTC CGT ACT CCG TAC TTC GTRE GGG GTG TTC AGC AAC TAT TC

SNHG15decapped nonsense RNA

FW ACG CTC TTC CGA TCT GTCRE GGG GTG TTC AGC AAC TAT TC

T7_Luc_pA spike-in RNAFW GCC CGG CGC CAT TCT ATC CGRE GCC AAC CGA ACG GAC ATT TCG A

T7_Luc_pAdecapped spike-in RNA

FW CCT ACA CGA CGC TCT TCC GARE GCC AAC CGA ACG GAC ATT TCG A

* (Gutschner et al. 2011)

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SUPPLEMENTAL REFERENCES

Gutschner T, Baas M, Diederichs S. 2011. Noncoding RNA gene silencing through

genomic integration of RNA destabilizing elements using zinc finger nucleases.

Genome Res 21: 1944-1954.

Kiss T, Filipowicz W. 1995. Exonucleolytic processing of small nucleolar RNAs

from pre-mRNA introns. Genes Dev 9: 1411-1424.

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