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Received 7 Nov 2013 | Accepted 10 Mar 2014 | Published 22 Apr 2014

Jimena Giudice1, Zheng Xia2,3, Eric T. Wang4,5, Marissa A. Scavuzzo1, Amanda J. Ward1,2,w, Auinash Kalsotra1,w, Wei Wang6, Xander H.T. Wehrens6,7, Christopher B. Burge4, Wei Li2,3 & Thomas A. Cooper1,2,6

During postnatal development the heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). Here we perform deep RNA-sequencing on RNA from cardiomyocytes and cardiac broblasts to conduct a high-resolution analysis of transcriptome changes during postnatal mouse heart development. We reveal extensive changes in gene expression and AS that occur primarily between postnatal days 1 and 28. Cardiomyocytes and cardiac broblasts show reciprocal regulation of gene expression reecting differences in proliferative capacity, cell adhesion functions and mitochondrial metabolism. We further demonstrate that AS plays a role in vesicular trafcking and membrane organization. These AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated changes in expression. Vesicular trafcking genes affected by AS during normal development (when Celf1 is downregulated) show a reversion to neonatal splicing patterns after Celf1 re-expression in adults. Short-term Celf1 induction in adult animals results in disrupted transverse tubule organization and calcium handling. These results identify potential roles for AS in multiple aspects of postnatal heart maturation, including vesicular trafcking and intracellular membrane dynamics.

1 Department of Pathology and Immunology, Baylor College of Medicine, Houston, Texas 77030, USA. 2 Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA. 3 Division of Biostatistics, Dan L Duncan Cancer Center, Baylor College of Medicine, Houston, Texas 77030, USA. 4 Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. 5 Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. 6 Department of Molecular Physiology and Biophysics, Baylor College of Medicine, Texas 77030, USA. 7 Department of Medicine, Baylor College of Medicine, Houston, Texas 77030, USA. w Present addresses:

Isis Pharmaceuticals, Carlsbad, California 92010, USA (A.J.W.); Departments of Biochemistry and Medical Biochemistry, University of Illinois, Urbana-Champaign, Illinois 61801, USA (A.K.). Correspondence and requests for materials should be addressed to T.A.C. (email: mailto:[email protected]

Web End [email protected] ).

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DOI: 10.1038/ncomms4603

Alternative splicing regulates vesicular trafcking genes in cardiomyocytes during postnatal heart development

ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms4603

The heart is the rst organ to form and function during vertebrate embryogenesis1. The rst 4 postnatal weeks involve a period of extensive physiological remodelling

with dynamic changes as the fetal heart adapts to birth and converts to adult function. This transition occurs through transcriptional and post-transcriptional mechanisms, including coordinated networks of alternative splicing (AS)14.

Human and rat hearts are composed of 66% cardiac broblasts (CF), 30% cardiomyocytes (CM) and 4% endothelial and vascular smooth muscle cells57. Studies differ regarding adult mouse heart composition. While Soonpaa et al.8 reported that CF account for 86% of cells, a recent analysis demonstrated a composition of 26% CF, 56% CM and 18% non-CM and non-CF9. However, CM comprise B75% of the tissue volume in mammals7. CM generate the contraction force and CF form the mechanical scaffold required for effective pumping10. CM and CF communicate through multiple signalling mechanisms and through extracellular matrix (ECM)11. Other CF functions include response to cardiac injury12 and electrical isolation of different regions of the cardiac conduction system13. By postnatal day 7 (PN7), CM lose proliferative capacity and heart size increases due to CM hypertrophy1415. Limited microarray analysis of messenger RNA expression in freshly isolated CM and CF showed that while certain genes are highly expressed in CM, many growth factors, cytokines and ECM genes are more highly expressed in CF16. Overall, the published data address a limited number of gene expression changes in CM and CF during development and, notably, do not provide AS information.

High-throughput studies of AS and gene expression regulation have primarily focused on differences between tissues, normal versus pathological conditions or cultured cells. A small set of reports have addressed AS and gene expression changes during normal physiological transitions1721. Development provides an outstanding opportunity to identify coordinated AS regulation critical for physiological transitions from embryonic to adult functions. Previously, we showed that genes that undergo AS regulation during heart development produce transitions from embryonic to adult protein isoforms largely without changes in overall transcript levels, presenting a new paradigm for understanding developmentally regulated gene expression in the heart3. Nearly half of the AS transitions identied in mouse are conserved during post-hatch chicken heart development, suggesting highly conserved functions for splicing-mediated isoform transitions3.

In the present study, we analysed AS and gene expression transitions regulated during postnatal mouse heart development using mRNA deep sequencing (RNA-seq)22. To gain insight into the diversity of cell type-specic transitions, we performed RNA-seq using freshly isolated CF and CM from a developmental time course. The results reveal that most gene expression and AS changes occur within the rst 4 weeks after birth, and that CM and CF exhibit reciprocal transitions in expression of specic functional categories (proliferation, cell adhesion, cytokines-chemotaxis, metabolism and transcription regulation). Interestingly, we found that genes involved in vesicular trafcking and membrane organization are regulated by AS during postnatal CM development. These AS changes are enriched as targets of the CUGBP, ELAV-like family (Celf) and Muscleblind-like (Mbnl) RNA-binding protein families, both of which are involved in AS and are regulated during postnatal heart development3,23,24. In the heart, vesicular trafcking-related AS transitions probably impact ligand/growth factor uptake, ion channels dynamics and/or postnatal formation of the sarcoplasmic reticulum (SR) and transverse tubules (T-tubules), crucial processes for excitation-contraction coupling (ECC) that are established by PN30 (ref. 25). We show that re-expression of CELF1 in adults

specically in CM results in altered T-tubule structure and misregulated calcium handling consistent with alterations associated with re-expression of fetal splicing patterns.

ResultsExtensive transcriptome changes during postnatal development. RNA-seq was performed using RNA from mouse ventricles isolated at ve time points: E17, PN1, PN10, PN28 and adult (PN90). Complementary DNA libraries were prepared after ribosomal RNA (rRNA) depletion for 100 bp paired-end reads using the Illumina HiSeq2000. We obtained 4150 million read pairs per sample, 480% of which mapped the mouse genome (Supplementary Table 1).

We identied 2,568 differentially expressed genes (Z2.0-fold, false discovery rate: 0.01, see Methods) between E17-adult: 747 were upregulated and 1,821 were downregulated (Fig. 1a). Analysis of mRNA isoforms whose percent spliced in (PSI)26 values changed Z20% (DPSIZ20%) between E17-adult identied 927 AS events, 190 alternative 30-untranslated regions (UTRs) and 210 alternative rst exons (Fig. 1b). Postnatal AS transitions were predominantly cassette exons (62%), while alternative 30-and 50-splice sites each represented 9%. We observed a relatively high proportion of transitions (20%) involving intron retention with roughly equal proportions of events exhibiting increased inclusion or exclusion of the variable regions during development (Fig. 1c,d).

Extensive remodelling within the rst 4 weeks after birth. Gene ontology (GO) analysis of downregulated genes between E17-adult in ventricles showed a clear enrichment (Po1E 10,

Fisher exact test) in categories related with cell cycle and DNA replication (Fig. 2a, left). As B75% of ventricular RNA originates from CM7, this is consistent with the loss of CM proliferative activity by PN7 (refs 14,15). Upregulated genes between E17-adult showed enrichment in categories related to mitochondria, fatty-acid metabolism and oxidation-reduction processes (Fig. 2a, right) consistent with increased mitochondrial number and the metabolic switch from carbohydrates to fatty acids, a hallmark of the fetal to adult CM metabolic transition27,28.

Analysis of three time windows (E17PN10, PN1PN28 and PN28PN90) revealed that the majority of gene expression transitions occurred before PN28 (Fig. 2b). Enrichment analysis in each period showed that downregulation of cell cycle-related genes occurred before PN28 ( log P dropped off after PN28;

Fig. 2c, left) in agreement with the loss of CM proliferative capacity early after birth. Similarly, upregulated genes related to mitochondria, fatty-acid metabolism and oxidation-reduction were more enriched before PN28 (Fig. 2c, right). In contrast, categories such as focal adhesion and ECM-receptor interaction were more enriched after PN28 in downregulated genes ( log

P increased after PN28; Fig. 2c, left). Detailed analysis of individual cell cycle and ECM genes conrmed temporal differences in downregulation. The majority of ECM-related genes maintained high mRNA levels within the rst 10 days after birth, dropped off at PN28 and decreased further in adults, while 81% of cell cycle genes were strongly downregulated before PN10 (Supplementary Fig. 1a,b). The 30-UTRs of downregulated

ECM- and cell cycle-related genes were computationally analysed for putative microRNA (miRNA) miR-15 and miR-29 seed sequences. While 41% of the downregulated ECM genes were predicted to be miR-29 targets, 33% of the downregulated cell cycle genes were predicted to be miR-15 targets. These results suggest that a possible mechanism for the distinct patterns of cell cycle and ECM downregulation could involve miRNAs since

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these transcripts are well-established targets of developmentally

upregulated miRNAs such as miR-15 and miR-29 families2932.

Celf1 loss correlates with increased expression of gene sets. To investigate a mechanism of upregulation during postnatal development, we explored a potential role for Celf1, a RNA-binding protein downregulated 10-fold during the rst 2 weeks after birth3. Celf1 binds to GU-rich motifs within introns regulating AS3,33 and within 3-UTRs promoting mRNA decay34,35. To identify genes that are responsive to Celf1 expression during postnatal development, we used previously described tetracyclineinducible transgenic mice (TRECUGBP1/MHC) to induce human CELF1 expression in CM33. RNA-seq was performed using ventricles of adult TRECUGBP1/MHC and control (MHC; myosin heavy chain) littermates after 12, 24, 72 h or 7 days of induction. A high fraction (41%) of the developmentally upregulated genes was downregulated within 72 h of exogenous CELF1 re-expression in adults (Fig. 2d, left). While a large number of genes are downregulated after CELF1 induction (5,499), the majority (93%) of them shows a relatively small change (r2.0-fold, after 72 h). In contrast, a high fraction (78%) of the 306 overlapping genes (upregulated during development and downregulated by CELF1 expression) shows a fold change Z2.5, suggestive of a physiological response.

Developmentally upregulated genes responsive to CELF1 (306 genes) were enriched in oxidation-reduction pathways, fatty-acid metabolism, mitochondria and sarcomere related categories. By contrast, only 14% of developmentally downregulated genes were affected by CELF1 re-expression (Fig. 2d), suggesting that a percentage of the developmentally upregulated mRNAs are destabilized by CELF1. A high proportion of the developmentally downregulated genes overlapped with the downregulated genes after CELF1 induction (Fig. 2d, bottom right). However, CELF1-downregulated genes show only 31% overlap with developmental downregulated genes compared with 41% overlap with developmentally upregulated genes suggesting that Celf1 postnatal downregulation stabilizes a large subset of

mRNAs. It is also likely that there are secondary consequences to CELF1 re-expression (such as effects on transcription factor expression) resulting in both positive and negative effects on mRNA levels. To further investigate the potential CELF1 role in regulating mRNA stability during postnatal development, we analysed the 30-UTRs of 58 genes in the oxidation-reduction and mitochondria categories for CELF1-binding motifs (Supplementary Fig. 1c,d). The GU-rich motif shown in Supplementary Fig. 1c was signicantly enriched (E 2.5E 05) and present in

24% of the analysed 30-UTRs. A similar GU-rich motif was found by CLIPZ with a high level of enrichment (Supplementary Fig. 1d). CLIPZ and MEME (Multiple Em Motif Elicitation) analysis also identied enrichment of polyA and GGA motifs (Supplementary Fig. 1c,d). These results suggest that postnatal Celf1 downregulation promotes upregulation of genes within specic functional pathways through mRNA stabilization.

Transcriptome changes in CM and CF during development. To identify cell type-specic transitions, we isolated CM and CF from ventricles of PN13, PN2830 and adult (PN6067) animals. RNA was extracted from CM and CF cell populations within 3 h of animal euthanasia to reduce post-mortem and cell manipulation effects. CF from all developmental stages and neonatal CM were isolated by an enzymatic digestion/pre-plating method. Adult and PN30 CM were isolated by Langendorff perfusion (see Methods). Morphology, binucleation (CM) and positive immunostaining for alpha-actinin (CM) and vimentin (CF) from adult animals were conrmed by confocal and differential interference contrast microscopy (Fig. 3a). Reverse transcriptionPCR (RTPCR) analysis of cell-specic markers in adult CM and CF demonstrated a high degree of purity (Fig. 3b). Analysis of cell-specic markers in RNA-seq data conrmed these results demonstrating similar purity levels for early and late postnatal stages (see below).

RNA-seq (paired-end 100 nucleotide reads) was performed on CM and CF polyA-selected RNA producing 4160 million read pairs per sample with 8590% mapping to the mouse genome

2,000

927

1,821

1,000

Number of genes

1,000

747

Number of events

500

190 210

Upregulated

0 Downregulated

Alternative

Alternative first exon

3-UTR

499 (54%)

428 (46%)

Type of AS events

85 (9%)

578 (62%)

183 (20%)

AS region

Alternative 3-splice site

Increased inclusion Increased skipping

Figure 1 | Extensive gene expression and RNA processing changes occur during heart development. (a,b) Differentially expressed genes (a) and alternative RNA processing between E17-adult (b). (c) AS events categorized by pattern. (d) Proportion of skipping/inclusion of the AS regions. AS, alternative splicing.

81 (9%)

Alternative 5-splice site

Cassette exon

Intron retention

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Downregulated

Upregulated

Downregulated Upregulated

Tight junction

-Alanine metabolism

2,000

Number of differentially

expressed genes

Oocyte meiosis

Tryptophan metabolism

1,667

Base excision repair

Oxidative phosphorylation

Purine metabolism

1,470

Coagulation cascades

p53 signalling

Hypertrophic cardiomyopathy

Homologous recombination

Pyrimidine metabolism

Cardiac muscle contraction

Ribosome

Dilated cardiomyopathy

1,000

Focal adhesion

Propanoate metabolism

570

Mismatch repair

Fatty-acid metabolism

448

ECM-receptor interaction

ABC transporters

Cell cycle

Val, Leu, Iso degradation

148

DNA replication

PPAR signalling

0 10

20 log P

0 5 10

log P

E17-PN10

PN28-PN90

PN1-PN28

Downregulated Up-regulated

Cell cycle

ECM interaction

Focal adhesion

Oxidationreduction Contraction regulation Mitochondria Contractile fibreIon transport

log P

0 E17-PN10

PN1-PN28

PN28-PN90

0 E17-PN10

PN1-PN28

Downregulated in

Upregulated CELF1-expressing mice

development

Upregulated in

Downregulated CELF1-expressing mice

development

1,573

441 306

(41%) 248

(14%)

5,193

1,602

- Oxidationreduction- Fatty-acid metabolism- Ion transport- Heart contraction, sarcomere- Glucose metabolism- Hypertrophy- Mitochondria

682 65

(9%) 1,785 1,260

Upregulated in

Upregulated CELF1-expressing mice

development

Downregulated in

Downregulated CELF1-expressing mice

development

561(31%) 4,983

Figure 2 | Gene expression regulation occurs primarily before PN28. (a) GO analysis (Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways) of down- and upregulated genes between E17-adult (ventricles). (b) Differentially expressed genes between E17PN10, PN1PN28 and PN28PN90 (ventricles). (c) Signicance of KEGG pathways ( log P) were plotted against time windows for specic categories. (d) Venn diagrams with

developmentally regulated genes and those regulated after CELF1 re-expression on adult mice (RNA-seq data). GO analysis of the intersected genes (summary). ECM, extracellular matrix; P, Fisher exact P value.

(Supplementary Table 1). Biological replicates generated highly reproducible results in neonatal CF and CM populations with high Pearson coefcients (R) for both gene expression (RCM 0.98, RCF 0.99) and AS (RCM 0.96, RCF 0.94). In

addition, gene expression from CM and ventricle RNA-seq data highly correlated (R 0.81) while CF-ventricle correlation was

low (R 0.33) (Supplementary Fig. 2ac). These results are

consistent with the fact that B75% of the ventricular volume is formed by CM7.

To evaluate CM and CF separation at all developmental stages, we used the fragments per kilobase per million mapped (FPKM)

to estimate CM enrichment (CME) and CF enrichment (CFE) values dened as the ratios CMexpression/CFexpression and

CFexpression/CMexpression, respectively16,36 (Fig. 3c). This analysis

provided several conclusions. First, while several CF-enriched transcripts showed constant ratios during development, CM-enriched transcripts showed a dramatic increase in CME values from PN13 to PN28. This reects an active burst of CM maturation after birth compared with a less robust change during CF maturation (see below). Second, PN13 CME values were Z10 for CM-enriched transcripts in PN13 and much higher for

PN30 and adult indicating highly pure CM populations at all

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Alpha-actinin / DAPI Vimentin / DAPI

DIC DIC

Ventricle CF CM

Ddr2

Vim

Tnnt2

Nkx2.5

Gapdh

217 201

254

309

254

110

404

309

CFE

CME

mRNA

PN1-3 PN28-30 Adult

mRNA

PN1-3 PN28-30 Adult

11 10 17

16 6 11

3 14 20

7 14 10

11 15,334 8,481

14 1,365 1,273

14 3,634 5,557

10 1,069 4,66

Vim

Postn Myh6

Ryr2

Ttn

Nkx2.5

Nppa

Thy1

Ddr2

46 1,365 735

CM CF

Downregulation /Upregulation Cytokine - chemotaxis

Nucleus Nucleus

Mitochondria metabolism

Upregulated

genes

1,680 (85%)

627

301 (68%)

550 1,095

(67%)

Transcription regulation

Nucleus

Adhesion

Endocytosis

Mitochondria metabolism

Downregulated

genes

Adhesion

Cytokine - chemotaxis

2,514 (82%)

Transcription regulation Splicing

Slc2a4 Cs Pdk2

2-fold 15-fold 3-fold 3-fold 4-fold 6-fold

150

8,000

5,000

25,000

250

9,000

125

6,000

4,000

20,000

200

100

FPKM

3,000

6,000

15,000

150

4,000

2,000

10,000

100

3,000

2,000

1,000

5,000

0 PN1-3

Adult PN1-3 Adult

0 PN1-3 Adult

CF CM

0 PN1-3 Adult

0 PN1-3 Adult PN1-3 Adult

Figure 3 | Reciprocal gene expression transitions between CM and CF. (a) Isolated adult ventricular CM and CF stained with anti-vimentin or anti-alpha-actinin. Scale bar, 10 mm. (b) RTPCR assays of CF (Vim, Ddr2) and CM (Tnnt2, Nkx2.5) markers on RNA from adult ventricles, CM and CF.

Experiments were repeated with at least three independent samples. (c) CF enrichment (CFE) for CF-enriched transcripts (blue) and CM enrichment (CME) for CM-enriched transcripts (red) calculated from RNA-seq data. (d) Postnatal gene expression transitions in CM and CF (PN13 versus adult) by RNA-seq. (e) GO analysis of down- and upregulated genes in CM and CF (Supplementary Table 2). (f) Postnatal expression of three metabolic genes (RNA-seq data) showing reciprocal CMCF regulation. bp, base pairs; DIC, differential interference contrast microscopy; FPKM, fragments per kilobase per million mapped.

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100

Ndrg4 ex 39 nt (protein NDRG4)

Adult

PN1

PN1 Adult

147

PSI RNA-seq

Pearson = 0.93 P = 2E-16n = 35 events

127 110

+ ex

- ex

PSI

100 50

50 100

90 42 44 77 78

-50

Tnnt2 ex 9 nt (troponin T, cardiac muscle)

-100

PSI RT-PCR

234

217

190 180

PN1 Adult

Adult

PN1

201 190 180

+ ex

- ex

PSI

41 41 71 72

AS genes

(x: PN28) versus (y: E17)

(x: adult) versus (y: PN28)

DE genes

Kif3a ex 9 nt (kinesin-like protein KIF3A)

Adult

PN1

PN1 Adult

636 (82%) 137

2,431 (95%)

+ ex

- ex

PSI

51 47 11 5

Tmed2 ex 21 nt (transmembrane emp24 domain trafficking protein 2)

Adult

PN1

PN1 Adult

+ ex

- ex

PSI

100 Inclusion

27 27 59 58

Aak1 ex 111 nt (AP2 associated kinase 1)

Adult PN1 Adult

PSI

309

217 180 160

+ ex

- ex

PSI

PN1

Inclusion

0 0 50 100 PSI

43 43 29 29

Figure 4 | Extensive postnatal AS transitions occur primarily without changes in gene expression. (a) RNA-seq data (UCSC browser) and RTPCR assays (n 2 biological replicates) for AS events developmentally regulated ( ex: exon included; ex: exon skipped). See Supplementary Fig. 3 and

Supplementary Table 3. (b) Correlation between RNA-seq and RTPCR DPSI values. P, Student Tdistribution. (c) Genes undergoing postnatal AS transitions (|DPSI|Z20%) were intersected with differentially expressed (DE) genes in ventricles (E17-adult). (d) AS transitions (|DPSI|Z20%; E17-adult) were plotted comparing their change between E17PN28 (red) and PN28-adult (green). Diagonal line: no difference between time points. Dots above/below the diagonal: increased/decreased inclusion. AS, alternative splicing; bp, base pairs; PSI, percent spliced in.

developmental stages. Third, the lower CFE values for some CF-enriched mRNAs at PN13 compared with PN30 and adult could reect a low level of contamination as well as incomplete cell maturation. To evaluate possible contamination of the CF population with CM in PN13, we examined Nppa that is highly expressed in neonatal CM28. We found Nppa to be highly enriched in CM compared with CF populations and estimate contamination of CF preparations (PN13) with CM to be o2%.

Reciprocal gene expression transitions between CM and CF. RNA-seq revealed 3,064 downregulated genes in CM and 1,645 in CF from PN13 to adult. Upregulated genes numbered 1,981 in CM and 928 in CF. Interestingly, 482% of the differentially expressed genes in CM were not differentially expressed in CF (Fig. 3d). Postnatal gene expression transitions in CM and CF showed a reciprocal regulation of enriched functional categories such as mitochondrial metabolism, chemotaxis, cell adhesion and proliferation among others (Fig. 3e, Supplementary Table 2). To validate reciprocal expression at the level of individual genes, we analysed expression of three previously published CM-specic genes involved in mitochondrial metabolism. RNA-seq data from

CM and CF for Slc2a4 (solute carrier family 2, facilitated glucose), Cs (citrate synthase) and Pdk2 (pyruvate dehydrogenase kinase 2) transcripts showed postnatal upregulation for CM and down-regulation for CF (Fig. 3f). The fold induction observed by RNA-seq in CM for these metabolic transcripts was comparable to quantitative PCR (qPCR) data previously reported in total mouse heart28.

AS transitions in ventricles occur mainly before PN28. We next focused on AS transitions during postnatal heart development. AS assayed by either RNA-seq or RTPCR was quantied as the PSI of the variable region and the change in splicing is DPSI26. To validate postnatal transitions detected by RNA-seq in ventricular RNA, we performed RTPCR analysis of 36 events, 17 with DPSIZ20% predicted from RNA-seq, 8 with DPSIr 20% and

11 with intermediate changes. A high Pearson correlation (R 0.93) between DPSI values from RTPCR and RNA-seq

experiments demonstrated the accuracy of our RNA-seq data for both strongly and weakly regulated transitions (Fig. 4a,b, Supplementary Fig. 3 and Supplementary Table 3).

We identied 927 AS transitions during development (|DPSI|Z20%) in 773 genes, 82% occurring in genes for which

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PN1-3 to adult PN1-3 to PN28-30 PN28-30 to adult

Upregulated Downregulated

1,000

4,000

809

844

3,064

3,052

Number of AS events

500

Number of genes

2,056

2,238

2,000

377

1,645

326

928

1,041

175

469

422

144

113

CM CF

DE genes AS genes

AS events

1,981

CF and CM

CM 4,866

(95%)

492

242 (67%)

93 258

(74%)

Pearson = 0.98 P = 5E09; n = 12

CF (PSI adult-PN1/3)

Pearson = 0.92P = 5E24; n = 55

259

80 40

40 80

80 CM (PSI adult-PN1/3)

742

3,186 (97%)

Fnip1

Tnrc6b

Fnip2

PSI=53

PSI=93

PSI=21

PSI=60

PSI=45

PSI=20

PSI=56

PSI=88

PN1-3 CF

Adult

PSI=62

PSI=36

PSI=64

PSI=91

PN1-3

Figure 5 | Postnatal gene expression and AS transitions in CM and CF. (a) AS transitions (|DPSI|Z20%) and gene expression changes in CMand CF. (b) Genes developmentally regulated by splicing (|DPSI|Z20%) in CM and CF were intersected with differentially expressed (DE) genes (PN13 versus PN2830). (c) Postnatal AS transitions (between PN13 and adult) specically in CM, CF or both. (d) Analysis of the 67 events regulated in CF and CM. P, Student T distribution. (e) Three postnatal AS transitions occurring in opposite directions in CM and CF. AS, alternative splicing; PSI, percent spliced in.

transcript levels changed less than twofold (Fig. 4c). These results are consistent with previous evidence from a smaller set of AS transitions3. Therefore, a substantial impact of AS during development occurs through changes in protein isoform levels rather than total gene expression variations. As observed for gene expression transitions, the majority of the developmental AS changes occurred before PN28 (Fig. 4d).

Temporal dynamics of AS transitions in CM and CF. RNA-seq revealed that during postnatal development, more AS events changed in CM (809) than in CF (326) between neonatal and adult stages (Fig. 5a). Six transitions were validated in neonatal and adult CM and CF populations, showing high correlation (R 0.84) between RTPCR and RNA-seq DPSI values

(Supplementary Fig. 2d,e). In both cell types, the majority of the events were cassette exons (8283%) and the rest of them were alternative 30-splice sites (6%), 50-splice sites (79%) and intron retention (34%). There was a slight preference for inclusion of the variable region in both CM (65%) and CF (59%) during development (Supplementary Fig. 2f,g).

Consistent with the AS analysis from ventricular RNA, 490% of postnatal transitions in CM occurred by PN30 (844 versus 78 after PN30). In CF, less than half of the postnatal transitions

occurred before PN28 (377 versus 175 after PN28; Fig. 5a, left). These results suggest that AS primarily affects CM maturation during the rst 4 weeks after birth while in CF splicing changes are distributed throughout postnatal life. Gene expression patterns showed a similar burst of expression before PN2830 that was more pronounced in CM than in CF (Fig. 5a, right).

More than half of the genes undergoing postnatal AS transitions in either CM (67%) or CF (74%) did not change expression Z2.0-fold and the majority of postnatal transitions were specic to either CM or CF populations (Fig. 5b,c). Only 67 events were developmentally regulated in both cell types, 82% of them (55 events) occurred in the same direction and 12 events showed opposite transitions in CF and CM with a strong negative correlation (R 0.98; Fig. 5d,e).

Taken together, these data conrmed that, as in ventricles, AS transitions occur primarily by PN28 in CM and are mainly cell-type specic.

Postnatal regulation of vesicular trafcking genes by AS. The AS transitions in ventricles (E17-adult) showed that vesicular trafcking, protein localization transport, endocytosis, membrane organization and invagination were the most represented categories (Po5E 03, Fisher exact test) including the largest

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Biological processes (ventricle)

KEGG pathways

Heart development

Cell motion reg.

Cell cycle Protein localization Microtubule-based tprocess Substrate junction assembly

Cell migration reg.

Cell cycle arrest Muscle cell differentiation

Cell adhesion Bioloical adhesion Gene expression, epigenetic

Muscle contraction

Vesicle-mediated transport

Membrane invagination

E17-PN1

PN1-PN28

PN28-adult

Ubiquitin-mediated proteolysis

CM development

Actin cytoskeleton organization Macromolecule biosynthesis reg.

Axon guidance

Vascular smooth muscle contraction

In utero embyonic development

Striated muscle contraction

Striated muscle cell differentiation

Oocyte meiosis

Intracellular transport. Protein localization

Myofibril assembly Heart contraction reg.

Cell junction assembly

Chromation silencing

Myofibril assembly Heart development

Calcium signalling

Focal adhesion

mTOR signalling

GnRH signalling

Microtubule-based transport

MAPK signalling

Cytoskeleton organization

Insulin signalling

Sarcomere organization

Endocytosis

Cytoskeleton-dependent transport

Microtubule-based movement

Actin cytoskeleton regulation

Endocytosis

Hypertrophic cardiomyopathy

Membrane invagination Muscle cell development

Dilated cardiomyopathy

Membrane organization

Vesicle-mediated transport

log P

Muscle contraction

Tyrosine metabolism

CELF1 oe

Wnt signalling

Pathways in cancer

Hypertrophic cardiomyopathy

MAPK signalling

Dilated cardiomyopathy

Spliceosome

RNA degradation

Ubiquitin mediated proteolysis

Aminoacyl-tRNA biosynthesis

Endocytosis

Membrane organization

Phosphorylation

Heart morphogenesis

Vesicle-mediated transport

Mbnl1E3/E3

Renal cell carcinoma

log P

Gene expression, epigenetic

Amino acid phosphorylation

Pathways in cancer

Gene expression reg.

Phosphate metabolism

Adherens junction

Cell size reg.

Transcription reg. by RNA pol.

Wnt signalling

Cell proliferation reg.

Regulation of growth

MAPK signalling

Neurogenesis reg.

RNA metabolism reg.

Endocytosis

Negative regulation of growth

Transcription reg. DNA dependent

RNA degradation

Chromatin modification

Membrane organization

Spliceosome

Chromosome organization

Transcription reg.

Ubiquitin-mediated proteolysis

1.5

3.0

4.5

log P

Vesicular trafficking membrane organization

Others

Junctions, adhesions

lines: P=0.05

Transcritption, chromatin

E17

Transcription,

Vesicular trafficking, chromatin

membrane organization

PN1 Adult

PN28

c d

Mbnl1 and CELF1 regulation on AS events

Direction

57 (7%) 31 (4%)

5 (1%)

93 events (12%)

= Direction

Events regulated by:

22 (39%)

35 (61%)

714 (88%)

CELF1 and Mbnl1

CELF1, not Mbnl1 Mbnl1, not CELF1

Only development (CM)

Figure 6 | Vesicular trafcking genes are regulated by AS during development. (a) GO analysis on AS genes (|DPSI|Z20%) in three time windows: E17PN1, PN1PN28 and PN28-adult (ventricles). P, Fisher exact test. (b) The Kyoto Encyclopedia of Genes and Genomes pathway analysis on AS genes detected by RNA-seq during wild-type CM development (|DPSI|Z20%) in adult CELF1-expressing hearts (CELF1 oe) and adult Mbnl1DE3/DE3 hearts (|DPSI|Z10%). P, Fisher exact test. (c) AS transitions (|DPSI|Z20%) during CM development (between PN13 and adult): regulation by Mbnl1 and/or

CELF1. (d) The 57 events regulated by Mbnl1 and CELF1 were analysed in terms of antagonistic/non-antagonistic effects (Supplementary Table 4). AS, alternative splicing.

numbers of genes (1027). Analysis of three time windows (E17 PN1, PN1PN28 and PN28-adult) revealed that categories related to vesicular trafcking and membrane organization were enriched and highly signicant before PN28. In contrast, categories related to transcription regulation and chromatin organization were predominant after PN28 (Fig. 6a). In general, GO analysis of AS and differentially expressed genes showed little overlap, further

suggesting independence of AS and gene expression regulation (Figs 2a,c, 3e and 6a,b).

Vesicular trafcking categories were also highly predominant during CM development (Fig. 6b) while transitions during CF development were enriched for other Kyoto Encyclopedia of Genes and Genomes pathways (adherens junction, P 1E 02;

actin-cytoskeleton regulation, P 5E 02; ECM-receptor

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interaction, P 8E 02, Fisher exact test). Therefore, AS

regulates different processes in each cell type.

AS regulation of trafcking genes by Celf1 and Mbnl1. Celf1 and Mbnl1 have been shown to regulate AS during mouse heart development3,37,38. We used the RNA-seq data obtained from adult TRECUGBP1/MHC animals after 12, 24, 72 h or 7 days of doxycycline induction and MHC littermates (72 h on doxycycline) to identify CELF1-responsive AS transitions. Published RNA-seq data from hearts of Mbnl1 knockout mice (Mbnl1DE3/DE3)39 allowed the identication of Mbnl1-sensitive events among postnatal AS transitions. From the 88 developmental transitions responsive to CELF1 re-expression in adults, 71 (81%) reverted to neonatal patterns. Of the 62 Mbnl1-sensitive transitions, 38 (61%) reverted to neonatal patterns in adult Mbnl1DE3/DE3 animals. Overall, 93 postnatal AS transitions (12%) were regulated by CELF1 and/or Mbnl1 and more than half of them (57 events) were regulated by both (35 events antagonistically, 22 events in the same direction; Fig. 6c,d, Supplementary Table 4).

Genes with postnatal AS transitions affected by CELF1 and/or Mbnl1 were enriched for vesicular trafcking, endocytosis and membrane organization-invagination processes (Fig. 6b). Reversion to neonatal splicing pattern in trafcking genes by CELF1 expression was conrmed by RTPCR analysis of 17 events (Fig. 7ac, Supplementary Fig. 4). A high correlation was observed between RNA-seq and RTPCR DPSI values and between developmental change (DPSIadult-PN1) and reversion

after CELF1 expression (DPSIMHC-CELF1oe) (Fig. 7b,c). The

vesicular trafcking genes regulated by AS during development and responsive to CELF1 re-expression in adults are linked with each other after testing network connections using GeneMANIA software (Fig. 7d).

We analysed the direct involvement of CELF1 in regulating AS during CM development by performing a motif analysis within the up- and downstream anking introns (300 bp) of the exons regulated during development that responded to CELF1 re-expression in adults (88 events). GU-rich motifs were enriched (Pr1E 08, hypergeometric test) in downstream regions of AS

exons (Supplementary Fig. 5a). Upstream anking regions of AS exons were enriched in U- or C-rich motifs (P 1E 14,

hypergeometric test) when the variable regions were more skipped after CELF1 induction and GU-rich sequences (Pr1E 09, hypergeometric test) when the exons were more

included in response to CELF1 (Supplementary Fig. 5b). iCLIP-seq data are available for Celf1 in C2C12 muscle cell differentiation40 and were used for evidence of direct binding of Celf1 to the 71 transcripts regulated by AS during heart development that show a reversion to the neonatal pattern after CELF1 re-expression in adults. We evaluated the presence of iCLIP-tags within the up- and/or downstream 500 bp of the intron sequences anking the AS exons and observed that 54% of them (38 out of71) contain iCLIP-tags within these regions (Supplementary Table 5; Fishers test: 1.7E 11 compared with whole gene exon

iCLIP binding). When iCLIP-tags were evaluated for AS exons of vesicular trafcking genes, we found that 50% of them contain iCLIP-tags within 500 bp of their anking regions; two examples are shown in Supplementary Fig. 5c.

Taken together, these results support the hypothesis that vesicular trafcking is regulated at the splicing level during postnatal CM development and that CELF1 directly regulates a substantial fraction of these transitions.

T-tubule and calcium release disruption by CELF1 induction. Membrane organization and vesicular trafcking are particularly

dynamic during postnatal CM development. The assembly of the excitation-contraction apparatus starts at birth and ends within 4 weeks involving T-tubule invagination from the sarcolemma, SR formation and vesicular trafcking of ion channels and adaptor proteins to specialized membrane regions41,42. We hypothesized that the splicing transitions regulated by Celf1 play a role in assembly and maintenance of these structures. To test this hypothesis, we determined the effect of CELF1 induction on adult T-tubule structure and function. CELF1 was re-expressed in adult mice for 4 days specically in CM (Fig. 8a). CELF1-expressing animals showed altered electro- and echocardiograms exhibiting lower fractional shortening, ejection fraction and heart rate compared with MHC controls (Fig. 8b, Supplementary Tables 6 and 7). The animals with higher exogenous CELF1 expression (#4) showed more affected cardiac parameters than the animal with lower exogenous CELF1 expression (#3). T-tubules were stained and imaged in living CM (Fig. 8c) and T-tubule structure was studied by three approaches. First, we delimited a rectangular region within the cell excluding nuclei and we performed the fast Fourier transform (FFT), an algorithm to convert a function of time/space into a frequency function and vice versa. With the FFT, we obtained the normalized T-tubule power by measuring the ratio between the pick power (rst pick of the FFT) and the baseline power. Normalized T-tubule power after FFT measures the global regularity of the T-tubule network, and densities of transverse and longitudinal elements of T-tubules41,43 (see Methods). CELF1-expressing CM showed lower T-tubule power than MHC controls (Fig. 8d). Second, we quantied the average T-tubule area within CM28. T-tubule area is dened as the percentage of the area containing T-tubule staining28 (see Methods). While MHC mice showed 183% (n 12 cells) of

CM area as T-tubules, CELF1-expressing CM showed 91% (n 16 cells; P 0.02, Students t-test; Fig. 8e). When analysed

separately, CM from mice expressing higher CELF1 levels showed less T-tubule area compared with mice expressing lower CELF1 levels (mouse #3: 121%, mouse #4: 71%). Third, we devised an approach to estimate the proportion of individual cells with disorganized T-tubule structure (T-tubule irregularity; see Methods). Control CM showed lower T-tubule irregularity (102%; n 13 cells) than CELF1-expressing CM (365%;

n 16 cells; P 4E 05, Students t-test; Fig. 8f).

Next, we addressed whether T-tubule disruption correlated with defective calcium release. Calcium spark frequency was higher in CELF1-expressing CM than in controls (7.91.9 versus1.40.4 sparks (100 mm) 1 sec 1; n 11 cells each genotype;

P 6E 03, Students t-test; Fig. 8g). Similar to T-tubule

disruption, CELF1-expressing mouse #4 (sicker) presented more frequent calcium sparks than CM from mouse #3 (healthier; 103 versus 62 sparks (100 mm) 1 sec 1). Spontaneous calcium sparks are due to the opening rate of ryanodine receptors and frequency changes reect alterations in ryanodine receptor itself, its association with other proteins, receptor cluster spatial organization, inter-cluster distance and/or calcium content in the SR44. Overall, T-tubule organization observed in CELF1-expressing CM resembles PN1015 structure41, suggesting reversion to earlier developmental stages.

DiscussionWe used RNA-seq to identify transcriptome dynamics from late embryonic to adult mouse heart development. While multiple studies have focused on specic genes or gene sets during heart development, this study presents a global analysis of postnatal gene expression and AS transitions in ventricles and freshly isolated CM and CF. The strong correlations of global postnatal

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a Tmed2 ex 21 nt (transmembrane emp24 domain trafficking protein 2)

Ap1b1 ex 21 nt (adaptor protein complex beta subunit 1)

PN1

Adult CELF1 oe MHC

Adult

PN1

Adult

PN1

190

180

201

254

217

309

238

309

180

217

Pearson = 0.91 P = 3E-8n = 19 events

PSI RNA-seq

27 25 55 55 20 18 53 53

PSI

Snap23 ex 33 nt (synaptosomal-associated protein 2)

Adult

PN1

Adult

PN1

35 70

PN1

Adult CELF1 oe MHC

+ ex

70 PSI RT-PCR

22 26 40 48 14 12 35 36

PSI

Pearson = 0.92 P = 8E-8n = 17 events

PN1

Adult CELF1 oe MHC

+ ex

PSI (MHC-CELF1 oe)

217 27 29 57 45 9 12 43 42

PSI

Clta ex 36 nt (clathrin light chain a)

40 20

PN1

Adult CELF1 oe MHC

+ ex

238

+ ex

40 PSI (adult - PN1)

11 12 24 25 10 11 25 24

PSI

Predicted functional relationship Shared protein domains

Co-localized

Co-expression

Sirt3

Tmed2

Nedd4l

Ap2s1

Dnm1l

Tmed10

Ttyh2

Fis1

Ap2a1

Copa

Ap1b1

Arhgap17

Arfgap2

Pde6g

Arfgap1

Traf6

Picalm

Fnbp1

Trafd1

Cltc

Gapvd1 Gorasp

Kidelr1

Snap23

Trip10

Scgn

Cltb

Ap1g1

Zranb1

Asap1

Scyl2

Mdm2

Clta

Tip2

Mtbp

Itsn2

Scrib

Lpp

Figure 7 | Vesicular trafcking genes revert to neonatal splicing patterns after CELF1 re-expression in adult hearts. (a) RTPCR (ventricles) of vesicular trafcking AS events during development and in CELF1-expressing hearts. Bar graphs: means.e.m (n 2 biological replicates).

(b) Correlation between RNA-seq and RTPCR data in vesicular trafcking genes (PN1-adult). P, Student T distribution. (c) Correlation between developmental transitions in vesicular trafcking genes and reversion after CELF1 re-expression in adults (RTPCR). P, Student Tdistribution. (d) Network of vesicular trafcking genes developmentally regulated by splicing and responsive to CELF1 (black circles). Grey circles: linking genes. CELF1 oe: TRECUGBP1/ MHC animals. MHC: control animals. bp, base pairs; PSI, percent spliced in.

changes between CM and ventricles ash frozen immediately after the euthanasia supports our contention that transcriptome transitions identied in isolated CM and CF are largely representative of those occurring in tissue. The similarity between ventricle and CM RNA-seq data is particularly striking, given that

CM RNA was polyA selected and ventricular RNA was prepared by rRNA depletion. Overall, we revealed novel insight into strikingly different postnatal gene expression and AS transitions that occur in distinct but highly interacting cell populations within ventricles.

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b P = 5E02

MHC CELF1 oe

kDa

#1 #4

50 75

50 150 100

CELF1

Flag

Sarcomeric alpha-actinin

Fractional shortening (%)

MHC CELF1 oe

MHC (#2)

CELF1 oe (#3)

CELF1 oe (#4)

T-tubule DIC FFT Normalized intensity

Zoom

100

0 0 5 10 15 20 25 30Distance (m)

e f

1.4

P = 5E14 P = 2E02 P = 4E05

T-tubule area (%)

Normalized T-tubule

power

T-tubule irregularity (%)

1.2

1.0

0.8

0.6

0.4

0.2

0.0

MHC CELF1 oe

0 MHC CELF1 oe

MHC (#2)

CELF1 oe (#3)

CELF1 oe (#4)

P = 6E-03

Sparks / 100 m s1

20 m

1 s

MHC CELF1 oe

Figure 8 | T-tubule disorganization after CELF1 re-expression in adults. (a) Western blot analysis from adult hearts after CELF1 induction.(b) Fractional shortening was measured in MHC (n 6 animals) and TRECUGBP1/MHC mice (n 3 animals) that were given doxycycline (4 days).

Results are expressed as the means.e.m. (c) Confocal imaging of T-tubules on living CM from MHC (#12; n 2 animals) and CELF1-expressing

(#34, n 2 animals) mice. Scale bar, 10 mm. Third row: uorescence plot over the white line on the rst row. (dg) T-tubule and calcium spark analysis:

normalized T-tubule power (d) (n 13 cells for MHC animals, n 16 cells for TRCUGBP1/MHC animals), T-tubule area (e) (n 12 cells for MHC

animals, n 16 cells for TRCUGBP1/MHC animals), T-tubule irregularity (f) (n 13 cells for MHC animals, n 16 cells for TRCUGBP1/MHC animals),

calcium spark frequency (g) (n 11 cells per genotype). *Pr0.05, Students t-test. Results are expressed as the means.e.m. CELF1 oe: TRECUGBP1/MHC

animals. MHC: controls. DIC, differential interference contrast microscopy; FFT, fast Fourier transform; T-tubules, transverse tubules.

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The largest transitions between E17-adult occur before PN28, a period in which extensive physiological changes take place as the fetal heart adapts to birth and converts to adult function1,2. In CM, 90% of the gene expression and AS transitions occur before PN28 while in CF nearly 50% occur later. Gene expression and AS follow the same patterns in each cell type suggesting a general tendency for CM to set an adult pattern of gene output within the rst 4 weeks after birth while CF undergo a more gradual transition. We hypothesize that this reects the maturation required in CM in response to cell proliferation loss, cellular hypertrophy and rapidly increasing workload during the rst 4 weeks after birth. By contrast, CF would not require as dramatic physiological maturation.

Our data reveal a high level of specicity in CM and CF gene expression and a reciprocal expression changes in the two cell types. While genes involved in critical CM functions such as mitochondrial metabolism are developmentally upregulated, they are downregulated in CF. Similarly, focal adhesions and chemotaxis genes are upregulated during CF development but downregulated in CM.

We examined potential mechanisms for post-transcriptional regulation of gene expression during development and identied a likely role for the 10-fold downregulation of Celf1 in the developmental upregulation of a subset of genes. While our previous analysis focused on the Celf1 role in a set of splicing transitions3, Celf1 has also been shown to destabilize mRNAs by binding to GU-rich motifs within 30-UTRs34,35. We showed that 41% of the genes normally upregulated during development were downregulated on CELF1 induction and from those GU-rich motifs are enriched in 30-UTRs of mitochondrial metabolism genes. Therefore, our results implicate Celf1 in coordinated upregulation of genes involved in the postnatal metabolic transition of CM.

Consistent with our previous smaller-scale study3, the majority of AS transitions detected during postnatal heart development occurs without changes in total gene output, indicating that protein isoform switches are important regulatory components during postnatal development. Categories highly regulated by AS in heart, specically in CM, are vesicular trafcking, endocytosis, membrane organization invagination. A link between trafcking and AS is novel, although several individual AS events in trafcking genes (for example, Snap25, Dab2 and Mdm2) have been reported45,46. In addition, categories relevant to trafcking were enriched among genes modulated by AS by CELF1 and Mbnl1, suggesting that these developmentally regulated RNA-binding proteins play a role in vesicle-mediated transport and membrane remodelling in CM.

Membrane remodelling and endocytosis are crucial in eukaryotic cells for a variety of functions, some of which are cell-type specic47. Recently, it was reported that AS has an impact on endocytosis during brain development, suggesting that vesicular trafcking functions are coordinated by AS21. Our results are similar in heart and the impact of vesicular trafcking on cardiac functions is not known. Although many differences exist between the heart and brain, parallels between neuroscience and cardiac elds are growing, particularly with regard to ion channels and vesicular trafcking processes48.

We hypothesize several non-exclusive scenarios for vesicular trafcking roles during postnatal heart development. First, AS regulation of vesicle-mediated transport could reect changes in ligand/growth factor uptake during development. Second, after PN7, CM stop dividing and undergo cellular hypertrophy14,15. The most rapid increase in CM volume occurs between PN4 and PN20, after which CM volume increases only slightly49. Therefore, cells must maintain the appropriate internalization-recycling balance while membrane exposure to the extracellular

environment is rapidly increasing. Third, vesicular trafcking regulation by AS could control the dynamics of ion channel production and localization. Ion channels are continuously formed, trafcked within vesicles for insertion and anchoring to specic subregions of the plasma membrane, and removed for degradation or recycling. Ion channel function is, therefore, dependent in part on surface density, which is tightly regulated by vesicular trafcking. The last scenario is supported by our analysis of T-tubule organization and function after CELF1 re-expression in adults. Maturation and assembly of SR and T-tubules in CM occur within the rst 34 weeks after birth41 producing the machinery for ECC. These maturation processes involve extensive cell architecture transitions, including membrane re-organization and vesicular-mediated protein transport. Membrane invagination and vesicular trafcking are regulated by AS during postnatal development and this may have an impact on CM functions such as ECC and uptake, distribution and recycling of key molecules (ion channels, growth factors and receptors). Importantly, both upregulation of CELF1 and loss of MBNL1 function are involved in the pathogenic mechanisms of myotonic dystrophy type 1 in which the best characterized molecular feature is expression of fetal AS splicing patterns50. The alterations in T-tubule structure and function we demonstrated strongly correlate with the nding that 80% of individuals with myotonic dystrophy type 1 exhibit cardiac arrhythmias51.

Methods

Materials. Cell culture reagents were obtained from GIBCO, Life Technologies. Liberase TH Research Grade and Collagenase/Dispase enzymes were from Roche Applied Science.

Animals. Ventricles, CM and CF were isolated from FvB wild-type mice. TRECUGBP1/Myh6-rtTA (TRECUGBP1/MHC) mice were used for human CELF1 overexpression in CM (tetracycline inducible) as described3,33. Bitransgenic and Myh6-rtTA (MHC) control adult animals were fed 2 g kg 1 doxycycline (BioServ) for 12, 24, 72 h and 7 days (RNA-seq), 8 days (RTPCR) or 4 days (T-tubule/calcium experiments). We followed the NIH guidelines for use and care of laboratory animals approved by Baylor College of Medicine Institutional Animal Care and Use Committee.

Ventricle heart isolation. Animals were anaesthetized and after cervical dislocation (older than PN10) or decapitation (neonatal) hearts were removed. Blood and atria were removed; ventricles were frozen in liquid nitrogen or freshly used for CM and CF isolation.

CF and CM isolation. PN28 and adult CF isolation by pre-plating method. Minced ventricles were digested in DMEM containing 0.1 U ml 1 Collagenase, 0.8 U ml 1

Dispase and 0.1% EDTA-free Tripsin for 10 min at 37 C (with stirring). After sedimentation the remaining tissue was similarly digested for 10 min. The suspension was centrifuged for 5 min at 3,000g, cells were re-suspended in MEM-a supplemented with 10% fetal bovine serum and kept on ice. This procedure was repeated 34 times, cells were centrifuged for 5 min at 3,000g, the pellet was re-suspended in MEM-a/20% fetal bovine serum and cells were seeded on cell culture dishes. Cells were plated for 2 h at 37 C under 5% CO2. Adherent cells were washed 10 times with PBS and RNA was immediately extracted. Neonatal CF and CM isolation. The neonatal CM isolation kit (Cellutron Life Technology) was used with 2035 ventricles accordingly to the manufacturers protocols. PN30 and adult CM isolation by Langendorff perfusion. The heart was removed with the lungs without touching the heart, rinsed in Ca2 free Tyrodes solution (140 mM NaCl,5.4 mM KCl, 1 mM MgCl2, 10 mM glucose, 5 mM HEPES pH 7.4) and cleaned from fat tissue. The heart was cannulated through the aorta and perfused on a Langendorff apparatus with Ca2 -free Tyrodes solution for 35 min, and then with Ca2 -free Tyrodes solution containing 20 mg ml 1 (0.104 Wnschunits ml 1) Liberase for B1525 min at 37 C and then with KB solution(90 mM KCl, 30 mM K2HPO4, 5 mM MgSO4, 5 mM pyruvic acid, 5 mM b-hydroxybutyric acid, 5 mM creatinine, 20 mM taurine, 10 mM glucose, 0.5 mM EGTA, 5 mM HEPES pH 7.2) to wash out the enzyme. Atria were removed, the heart was minced in KB solution, cells were gently pipeted up and down (on ice) and ltered through Nylon mesh 210 mm open 155 mm thread, 240 120 mesh

(Small Parts Inc). The sample was centrifuged for 5 min at 3,000 g and RNA was immediately extracted, or fresh CM were used for T-tubule experiments or immunouorescences, or were frozen in liquid nitrogen for western blot assays.

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RNA extraction. RNeasy brous tissue mini-kit (ventricles and CM) and RNeasy micro-kit (CF) were used (QIAGEN).

RNA-seq analysis of CM and CF during development. RNA-seq samples showed the following parameters: A260nm/A280nmZ1.8, A260nm/A230nmZ1.4, r28S:16SZ1.5

and RNA integrated number Z8.6. Illumina TruSeq RNA sample preparation protocols were used for CM (PN12, PN1, PN30 and PN67) and CF (PN13, PN12, PN28 and PN60). In brief, a double-stranded DNA library was created using 1 mg total RNA. First, cDNA was created using the fragmented 30-poly(A)-selected portion of total RNA and random primers. Libraries were generated from the cDNA by blunt ending the fragments, attaching an adenosine to the 30-end and nally ligating unique adapters to the ends. The ligated products were amplied by PCR (15 cycles). Libraries were quantied using the NanoDrop spectrophotometer and fragment size assessed with the Agilent Bioanalyzer. A qPCR was performed on the libraries to determine the concentration of adapter-ligated fragments using a Bio-Rad iCycler iQ Real-Time PCR Detection System and a KAPA Library Quant Kit. Using the concentration from the Bio-Rad qPCR, 11 pM library was loaded onto a ow cell and amplied by bridge amplication using the Illumina cBot equipment. A paired-end 100 cycle run was used to sequence the ow cell on a HiSeq Sequencing System.

RNA-seq. Illumina TruSeq protocols were used for wild-type CM (PN12, PN1, PN30 and PN67) and CF (PN13, PN12, PN28 and PN60), and ventricles from TRECUGBP1/MHC or MHC animals (n 3 animals each time point). For devel

opmental ventricle analysis, RNA was rRNA depleted and libraries were prepared by Ribo-Zero Magnetic Gold and ScriptSeq-v2 RNA-seq library preparation kits (Epicentre Biotechnologies). In brief, total RNA (2 mg) from ventricles of E17, PN1,

PN10, PN28 and PN90 (adult) animals was rRNA depleted using the Ribo-Zero Magnetic Gold Kit following the manufacturers protocols. The rRNA-reduced samples (B30 ng) were fragmented and primed with random hexamers containing a 50-tagging sequence for RT priming. The 50-tagged rst-strand cDNA was then generated. During the second-strand cDNA generation, the RNA templates were removed leaving the 50-tagged strand. Terminal-tagging oligos were annealed to the 50-tagged strand and terminal-tagging oligos were blocked at the 30-end preventing the synthesis of a secondary strand. Resulting cDNA strand was single stranded and tagged at both ends. The di-tagged cDNA was puried using Agencourt AMPure XP system (Beckman Coulter). Single-stranded cDNA generated for each sample was used for library construction. Using PCR amplication (10 cycles), the second cDNA strand was generated and the Illumina adapter sequences were added simultaneously to the single-stranded di-tagged cDNA fragments. Illumina sequencing libraries were puried using Agencourt AMPure XP system. Libraries were validated on an Agilent Bioanalyzer High Sensitivity DNA chip checking the purity of the sample and the size of the insert. Libraries were within 1502000 bp on the electropherogram. A second round of purication using Agencourt AMPure XP system was required for removal of primer-dimer and adapter-dimer contamination. Libraries were quantied using KAPA SYBR Fast qPCR kit from KAPA Biosystem. Libraries were diluted to 2 nM (based on cT values), alkali denatured for 5 min, diluted to a nal concentration of 11 pM and dispensed into thin-walled PCR tubes to be loaded into the Illumina cBot. Clusters were generated on the ow cell by PCR with the Illumina cluster generation kit. The ow cell containing clustered libraries were loaded on the Illumina HiSeq instrument along with the kitted sequencing reagents for a paired-end (PE) 100 bp run. During each sequencing cycle, a dye-terminated nucleotide was incorporated into the single-stranded DNA strand and uorescence was monitored. Fluorescent dye was cleaved to allow next nucleotide incorporation. CASAVA software converted the uorescence measurements into sequence les.

Computational processing of developmental RNA-seq data. RNA-seq alignment. Paired-end RNA-seq reads were aligned to the mouse genome (mm9) using TopHat 2.0.5 (ref. 52). Differentially expressed gene analysis and FPKM. RSEM53 was used to count the number of fragments mapped into Ensembl gene models, followed by edgeR54 to call differentially expressed genes with false discovery rate less than 0.01. The gene expression was quantied by FPKM55. Differential AS events. On the basis of the Ensembl 65 gene model, SpliceTrap56 was employed to identify differential exon skipping, intron retention events, alternative 50- or 30-splice site. AS was quantied by the percentage of mRNAs that contain an alternative region as PSI value. The events with PSI changes between two conditions |DPSI|Z20% were called differential splicing events.

Computational processing of the CELF1 RNA-seq data. Estimation of gene and isoform expression levels was performed in a manner similar to previously described39. In brief, reads were mapped to the mouse genome (mm9) and a database of splice junctions using the Bowtie tool57. Gene expression. Gene expression was measured as following: (i) the number of reads mapping to constitutive exons for each gene was measured and (ii) that measurement was divided by the number of kilobases of constitutive exon model per million uniquely mapped reads. AS events. Isoform levels and Bayes factors were measured by MISO58 (single end mode).

Bioinformatic analysis of 30-UTRs. The Database for Annotation, Visualization and Integrated Discovery v6.7 (refs 59,60) was used for GO analysis considering Pr0.05 signicant. miRNA prediction analysis was performed using TargetScan (http://www.targetscan.org/

Web End =http://www.targetscan.org/) and motif analysis with CLIPZ (SIB) and MEME version 4.9.0 (ref. 61) (motif4618 bp) softwares. The E-value (MEME) is the enrichment of a motif based on its log likelihood ratio, width, sites, background frequencies and the training set size. The P value of a site is computed from the match score of the site with the position-specic scoring matrix for the motif. The P value gives the probability of a random string (generated from the background letter frequencies) having the same match score or higher. Gene network of AS genes involved in vesicular trafc, developmentally regulated and sensitive to CELF1 induction was performed using GeneMANIA62.

Bioinformatic analysis of AS events. The analysis involved the 88 developmental transitions responsive to CELF1 re-expression in adults. The 300 nucleotide upstream and downstream of the alternative spliced exons were used for de novo motif analysis, excluding the last 30 nucleotides of the upstream intron and rst 9 nucleotides of the downstream intron of the alternative exons that contain the conserved 50- and 30-splice sites, respectively. Then motif analysis tool HOMER (v4.3)63 was employed for RNA motif analysis with the background sequences generated by the rst-order Markov model the parameters of which were estimated based on hg19.

Celf1 HITS-Clip data analysis. C2C12 Celf1 HITS-CLIP data were downloaded from the European Nucleotide Archive (accession code ERP000789)64. As described by authors64, the 4-bp tags were trimmed and sequences composed primarily of Illumina adapter were removed. The pre-processed reads were mapped to the mouse genome (mm9) using the alignment tool Bowtie57 with allowed two mismatch. Finally, reads with identical 50 starts were further collapsed into a single read to avoid potential PCR duplicates effects and only uniquely mapped reads were kept as nal Celf1-binding tags.

AS validations by RTPCR. RTPCR was performed (High Capacity cDNA RT Kit, Applied Biosystems; and GoTaq DNA Polymerase, Promega) in biological duplicates and products were analysed by 6% PAGE. PCR reactions involved the following steps: (i) 95 C for 3 min, (ii) 2027 cycles of 95 C for 30 s, 58 C for 30 s and 72 C for 30 s, (iii) 72 C for 7 min and (iv) 25 C for 5 min. RNA-seq data were used to design primers annealing in the constitutive anking exons of the AS region. Sequences of the primers (SIGMA) used for validation in ventricles are shown in Supplementary Table 8. Sequences of the primers (SIGMA) used for validation of AS events on vesicular trafcking-related genes are shown in Supplementary Table 9. Densitometry measurements were performed using Kodak Gel logic 2200 and Molecular Imaging Software. PSI26 was calculated by densitometry following equation (1).

PSI 100

Inculusion bandInculusion band Skippng band

Analysis of CM and CF markers by RTPCR. RTPCR assays were performed using the following primers (SIGMA): vimentin-F (50-TGAAGGAAGAGATG GCTCGT-30), vimentin-R (50-TTGAGTGGGTGTCAACCAGA-30), Ddr2-F (50-CAAGATCATGTCTCGGCTCA-30), Ddr2-R (50-GCCCTGGATCCGGTAGT AAT-30), Nkx2.5-F (50-AAGCAACAGCGGTACCTGTC-30), Nkx2.5-R (50-GGGT AGGCGTTGTAGCCATA-30), Tnnt2-F (50-CGGAAGAGTGGGAAGAGACA-30), Tnnt2-R (50-TTCCCACGAGTTTTGGAGAC-30), mGadph-F (50-CGTCCCGTA GACAAAATGGT-30) and mGadph-R (50-TTGATGGCAACAATCTCCAC-30). PCR reactions involved the following steps: (i) 95 C for 75 s, (ii) 2027 cycles of 95 C for 45 s, 57 C for 45 s and 72 C for 1 min, (iii) 72 C for 10 min and (iv) 25 C for 5 min. PCR products were analysed by 6% PAGE.

Immunouorescence. After adult CM and CF isolation, cells were seeded onto coverslips overnight (CM) or for 70 h (CF). Coverslips were pre-coated with20 mg ml 1 laminin for 1 h at 37 C for CM. Cells were xed in 3.7% paraformaldehyde on ice for 20 min, blocked with PBS/0.3% TritonX-100/1% BSA for 1 h at 37 C and incubated overnight at 4 C with primary antibodies (rabbit monoclonal anti-vimentin (D21H3; Cell Signaling, #5741; 1:100) or mouse monoclonal (clone BM-75.2) anti-alpha-actinin (SIGMA, #A5044; 1:50). After washes, samples were incubated with secondary antibodies conjugated with Alexa-uor-488 (Invitrogen; 1:500) for 1 h at 37 C, washed, stained with 2 mM 40,6-diamidino-2-phenylindole (DAPI) for 5 min and mounted (Slow Fade Gold Antifade Reagent, Invitrogen). Confocal microscopy was performed with a Nikon A1-Rs inverted laser scanning microscope with a 40 Plan-Fluor/1.3 numerical

aperture oil-immersion objective. Excitation: argon multiline laser at 488 nm (Alexa-uor-488) or a 404-nm diode at 38 mW (DAPI). Emission lters: band-pass 525/50 nm (Alexa-uor-488), band-pass 450/50 nm (DAPI). Confocal images were processed with ImageJ. Background was subtracted and a median lter was applied (radius 1 pixel) for presentation.

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T-tubules analysis. Isolated CM (adult TRECUGBP1/MHC or MHC doxycycline fed, n 2 animals each) were stained with 10 mM Di-8-ANEPPS (Invitrogen,

#D3167) in KB solution for 15 min, washed and imaged by confocal microscopy (Zeiss LSM-510 microscope, 40 oil-immersion objective). Excitation: argon

multiline laser, 488 nm. Emission lter: long-pass 505 nm. Quantications were performed using ImageJ: 1) a region of interest was selected covering longitudinally the CM avoiding the nuclei, FFT was obtained, power spectrum was computed and normalized (normalized T-tubule power)41; 2) a threshold (MaxEntropy) was applied (ImageJ), cell interior was manually delimitated (excluding plasma membrane), areas with green signal were summed within the threshold and normalized to the total area (T-tubule area); 3) CM from MHC animals showed four to six T-tubules (10 mm) 1 (ImageJ); therefore, regions with four to six

T-tubules (10 mm) 1 were considered regular-regions otherwise irregular-regions. Three lines were drawn along each CM, plots were obtained, normalized to its maximum, a cutoff (15 units above the baseline) was determined and each line was analysed by the number of picks (T-tubules) above the cutoff (between 0 and 10, 5 and 15, 10 and 20, 15 and 25 mm and so on) computing the regular-regions and the irregular-regions (in mm). For each CM, the total length of the three lines and the total irregular-regions were summed and T-tubule irregularity was calculated.

Calcium sparks analysis. The same samples were incubated with 3.5 mM uo-4-acetoxymethyl ester (Invitrogen, #F14201) in Tyrodes solution (1.8 mM Ca2 ; 1 h, room temperature), washed (15 min) and transferred to a chamber containing parallel platinum electrodes. Fluorescence images were recorded after pacing (10 V, 0.5 ms) from CM showing clear striation and normal contractility. Sparks were analysed using SparkMaster plugin (ImageJ).

Western blots. After perfusion, a portion of the ventricles from TRECUGBP1/ MHC or MHC control animals were lysed in HEPES-sucrose buffer (10 mM HEPES pH 7.4, 0.32 M sucrose, 1 mM EDTA and proteases inhibitors) using Bullet blender (Next Advance) equipment and SDS was added (nal concentration: 1% SDS). Samples were sonicated (3 min at 75 V: 30 s on and 30 s off) and centrifuged for 10 min at 14,000 r.p.m. at 4 C. Supernatants were transferred to new tubes and protein concentration was estimated with Pierce BCA protein assay kit (Thermo Scientic). Samples were diluted in loading buffer (100 mM TrisHCl pH 6.8, 4% SDS, 0.2% bromophenol blue, 20% glycerol, 200 mM b-mercaptoethanol), boiled for 5 min and total proteins (40 mg) were assayed by 10% SDSPAGE. After transfer, membranes were blocked in 5% non-fat-dried milk/0.1% Tween-TBS buffer for 1 h, washed and incubated overnight at 4 C with primary antibodies diluted in 5% milk/Tween-TBS buffer: mouse monoclonal anti-CUG-BP1, clone 3B1 (Milipore, #05-621; 1:1,000), rabbit polyclonal anti-sarcomeric alpha-actinin (Abcam, #ab72592; 1:2,000). The following day, membranes were incubated with secondary antibodies (1:5,000) for 1 h at room temperature: peroxidase-conjugated goat anti-mouse IgG light chain-specic (Jackson Immunoresearch, #115-035-174), goat anti-rabbit IgG horseradish peroxidase conjugated (Invitrogen, # 621234). Flag-tag was detected by monoclonal anti-FLAG M2 peroxidase (Sigma, #A8592; 1:1,000; 1 h at room temperature). Super Signal West Pico Chemiluminescent Substrate kit (Thermo Scientic) was used for developing.

ECG and echocardiogram recording. Echocardiograms were performed using a Vevo 770 Ultrasound equipment with a 707B probe for the cardiac analysis.

The animals were sedated with 2% isourane for imaging. The m-mode images were analysed for data acquisition using the Vevo analysis package. The electrocardiograms (ECGs) were recorded using a Mouse Monitor made by Indus Instruments. Mice were lightly anaesthetized using 1.5% isourane and the paws were taped to the ECG leads. ECGs were recorded for leads I, II and III for each animal and analysed. Both ECGs and ultrasounds were performed in the Mouse Phenotyping Core at the Baylor College of Medicine.

Statistic. Results were expressed as the means.e.m, P values were estimated using Students t-test (two tailed) and Pr0.05 was considered signicant.

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Acknowledgements

We thank Donnie Bundman (Baylor College of Medicine) for technical assistance, Rebecca L. Thornton (Baylor College of Medicine) for help with RNA-seq details, Corey L. Reynolds and Mouse Phenotyping Core (Baylor College of Medicine) for electro- and echocardiograms, Gloria Vittone-Echeverria, Simona Pedrotti and Ravi Singh (Baylor College of Medicine) for critical reading of the manuscript. This project was funded by the NIH (R01HL045565, R01AR060733 and R01AR045653) and Muscular Dystrophy Association (MDA 276796) grants to T.A.C. RNA-seq was performed in the Genomic and RNA Proling Core (Baylor College of Medicine) with the assistance of the Core Director (L.D. White, PhD). J.G. is a Pew Latin American Fellow in the Biomedical Sciences supported by The Pew Charitable Trusts (#2933). E.T.W. was funded by a post-doctoral fellowship from Myotonic Dystrophy Foundation. A.K. is funded by the American Heart Association (scientist development Grant-11SDG4980011). A.J.W. was funded by National Institute of Neurological Disorders and Stroke (NINDS-F31NS067740). W.L. is funded by CPRIT (RP110471), DOD (W81XWH-10-1-0501) and NIH (R01HG007538) grants. X.H.T.W. is funded byNIH (HL089598, HL091947 and HL117641), the American Heart Association (13EIA14560061), Muscular Dystrophy Association (186530) and Fondation Leducq (08CVD01) grants.

Author contributions

J.G. designed research, performed the experiments, analysed the data and wrote the manuscript. Z.X. and W.L. performed computational analysis of sequencing reads from RNA-seq data, iCLIP and motif analysis of splicing events and contributed to the manuscript. E.T.W. and C.B.B. performed computational analysis of sequencing reads from RNA-seq data and contributed to the manuscript. M.A.S. performed RTPCR validations and contributed with manuscript suggestions. A.J.W. isolated CELF1-expressing hearts and controls for RNA-seq. A.K. provided suggestions for initial cell isolation set-up and contributed to the manuscript. W.L. and X.H.T.W. collaborated in T-tubule/calcium experiments. T.A.C. supervised and designed research, analysed the data and wrote the manuscript.

Additional information

Accession codes: RNA-Seq data have been deposited at NCBI Gene Expression Omnibus under accession code GSE49906 (developmental series: ventricles, cardiomyocytes and cardiac broblasts) and GSE56185 (CELF1 data).

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How to cite this article: Giudice, J. et al. Alternative splicing regulates vesicular trafcking genes in cardiomyocytes during postnatal heart development. Nat. Commun. 5:3603 doi: 10.1038/ncomms4603 (2014).

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During postnatal development the heart undergoes a rapid and dramatic transition to adult function through transcriptional and post-transcriptional mechanisms, including alternative splicing (AS). Here we perform deep RNA-sequencing on RNA from cardiomyocytes and cardiac fibroblasts to conduct a high-resolution analysis of transcriptome changes during postnatal mouse heart development. We reveal extensive changes in gene expression and AS that occur primarily between postnatal days 1 and 28. Cardiomyocytes and cardiac fibroblasts show reciprocal regulation of gene expression reflecting differences in proliferative capacity, cell adhesion functions and mitochondrial metabolism. We further demonstrate that AS plays a role in vesicular trafficking and membrane organization. These AS transitions are enriched among targets of two RNA-binding proteins, Celf1 and Mbnl1, which undergo developmentally regulated changes in expression. Vesicular trafficking genes affected by AS during normal development (when Celf1 is downregulated) show a reversion to neonatal splicing patterns after Celf1 re-expression in adults. Short-term Celf1 induction in adult animals results in disrupted transverse tubule organization and calcium handling. These results identify potential roles for AS in multiple aspects of postnatal heart maturation, including vesicular trafficking and intracellular membrane dynamics.

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Title

Alternative splicing regulates vesicular trafficking genes in cardiomyocytes during postnatal heart development

Author

Giudice, Jimena; Xia, Zheng; Wang, Eric T; Scavuzzo, Marissa A; Ward, Amanda J; Kalsotra, Auinash; Wang, Wei; Wehrens, Xander H T; Burge, Christopher B; Li, Wei; Cooper, Thomas A

Pages

3603

Publication year

2014

Publication date

Apr 2014

Publisher

Nature Publishing Group

e-ISSN

20411723

Source type

Scholarly Journal

Language of publication

English

DOI

https://doi.org/10.1038/ncomms4603

ProQuest document ID

1518062395

Alternative splicing regulates vesicular trafficking genes in cardiomyocytes during postnatal heart development

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