Transcriptome alterations of vascular smooth muscle ...

Data in Brief ∎ (∎∎∎∎) ∎∎∎–∎∎∎

1 Contents lists available at ScienceDirect 2 3 4 5 6 journal homepage: www.elsevier.com/locate/dib 7 8 9 Data Article 10 11 12 Q1 13 14 15 16 17 Thidathip Wongsurawat a,b, Chin Cheng Woo c, 18 Antonis Giannakakis a, Xiao Yun Lin d, 19 Esther Sok Hwee Cheow e, Chuen Neng Lee c,d, 20 Mark Richards f,g, Siu Kwan Sze e, Intawat Nookaew b, 21 Vladimir A. Kuznetsov a,h, Vitaly Sorokin c,d,n 22 23 Q2 a Department of Genome and Gene Expression Data Analysis, Bioinformatics Institute, Agency for Science, 24 Technology and Research (A*STAR), Singapore 138671, Singapore 25 Q3 b Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA 26 c Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 27 119228, Singapore 28 d Department of Cardiac, Thoracic and Vascular Surgery, National University Heart Centre, Singapore, 29 National University Health System, Singapore 119228, Singapore e School of Biological Sciences, Nanyang Technological University, Singapore 639798, Singapore 30 f Cardiovascular Research Institute, National University Heart Centre, Singapore, 119228, Singapore 31 g Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 32 119228, Singapore h 33 School of Computer Science and Engineering, Nanyang Technological University, Singapore 639798, 34 Singapore 35 36 37 a r t i c l e i n f o abstract 38 39 Article history: This article contains further data and information from our pubReceived 23 January 2018 40 lished manuscript [1]. We aim to identify significant transcriptome Accepted 30 January 2018 alterations of vascular smooth muscle cells (VSMCs) in the aortic 41 wall of myocardial infarction (MI) patients. Microarray gene 42 analysis applied to evaluate VSMCs of MI and non-MI patients. 43 Prediction Analysis of Microarray (PAM) identified genes that sig44 nificantly discriminated the two groups of samples. Incorporation 45 of gene ontology (GO) identified a VSMCs-associated classifier that 46 47 48 DOI of original article: https://doi.org/10.1016/j.atherosclerosis.2018.01.024 n 49 Corresponding author at: Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore. 50 E-mail address: [email protected] (V. Sorokin). 51 52 https://doi.org/10.1016/j.dib.2018.01.108 53 2352-3409/& 2018 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license 54 (http://creativecommons.org/licenses/by/4.0/).

Data in Brief

Transcriptome alterations of vascular smooth muscle cells in aortic wall of myocardial infarction patients

Please cite this article as: T. Wongsurawat, et al., Transcriptome alterations of vascular smooth muscle cells in aortic wall of myocardial infarction patients, Data in Brief (2018), https://doi.org/ 10.1016/j.dib.2018.01.108i

T. Wongsurawat et al. / Data in Brief ∎ (∎∎∎∎) ∎∎∎–∎∎∎

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discriminated between the two groups of samples. Mass spectrometry-based iTRAQ analysis revealed proteins significantly differentiating these two groups of samples. Ingenuity Pathway Analysis (IPA) reveals top pathways associated with hypoxia signaling in cardiovascular system. Enrichment analysis of these proteins suggests an activated pathway, and an integrated transcriptome-proteome pathway analysis reveals that it is the most implicated pathway. The intersection of the top candidate molecules from the transcriptome and proteome highlighted overexpression. & 2018 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Specifications Table Subject area More specific subject area Type of data How data was acquired

Data format Experimental factors Experimental features Data source location Data accessibility

Biology Genomics, Proteomics, Bioinformatics, Cardiovascular Tables, figures Microarray (Gene Titan Instrument, Affymetrix), mass spectrometry (LC-MS/ MS system comprised of a Dionex Ultimate 3000 RSLC nano-HPLC system, coupled to an online Q-Exactive hybrid quadrupole-Orbitrap mass spectrometer (Thermo Scientific, Hudson, NH, USA)), RT-qPCR (QuantStudio™ 12K Flex system (Life Technologies; Thermo Fisher Scientific Inc, USA)) Raw, analyzed Laser-captured microdissection, total RNA extraction and protein extraction from aortic tissues from surgical patients Data analysis with Principal Component Analysis (PCA), Prediction Analysis of Microarray (PAM), Gene Ontology (GO), Ingenuity Pathway Analysis (IPA) Singapore Data is with this article

Value of the data

Combination of multiple technologies and bioinformatics analysis performed in this study reveals the molecular changes induced by myocardial infarction on aortic smooth cells in humans.

The alterations of the VSMCs transcriptome are congruent with alterations at the protein levels.

Both levels show notably the up-regulation of the superoxide dismutase (SOD) with the activation of superoxide radical degradation pathway. Differentially expressed genes and pathways identified in these comparisons may be used in future experiments investigating response in myocardial infarction.

1. Data 1.1. Clinical analysis The characteristics of the myocardial infarction (MI) and non-MI samples undergoing transcriptomics and proteomic studies are presented in Tables 1(A) and 1(B) respectively. The baseline demographic and clinical characteristics of samples undergoing transcriptomics study were Please cite this article as: T. Wongsurawat, et al., Transcriptome alterations of vascular smooth muscle cells in aortic wall of myocardial infarction patients, Data in Brief (2018), https://doi.org/ 10.1016/j.dib.2018.01.108i


109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162

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Table 1A Demographic characteristics of MI and non-MI groups undergoing transcriptomics analysis. Characteristics

Ethnic

Gender Age (Mean 7 SD) Ejection Fraction

Smoking Renal Impairment Diabetes Mellitus Hypertension Hyperlipidaemia Antihyperlipidemic Medication

Chinese Malay Indian Others Male Female Good ( 445%) Fair (30–45%) Poor ( o 30%) No Yes No Yes No Yes No Yes No Yes No Yes

Troponin I (µg/L) Mean (SD)

Transcriptomics MI (n ¼17)

Transcriptomics Non-MI (n¼ 19)

p-value

12 2 2 1 14 3 59.53 7 8.28 11 4 2 8 9 15 2 9 8 1 16 0 17 0 17 12.20 7 20.86 (n ¼ 15)

10 6 2 1 16 3 59.68 7 8.85 13 6 0 9 10 19 0 7 12 3 16 0 19 0 19 0.01 7 0.004 (n¼ 4)

0.557

0.881 0.957 0.292

0.985 0.124 0.332 0.345 – – o 0.05

Table 1B Demographic characteristics of MI and non-MI proteomics groups. Characteristics

Ethnic


Smoking Renal Impairment Diabetes Mellitus Hypertension Hyperlipidaemia Antihyperlipidemic Medication Troponin I (µg/L) (Mean 7 SD)


Proteomics MI n ¼ 25

Proteomics Non-MI n ¼25

p-value

11 8 5 1 20 5 60.88 7 12.34 14 9 2 12 13 25 0 10 15 3 22 1 24 4 21 19.54 7 19.24 n ¼ 22

13 7 5 0 18 7 61.687 8.26 16 9 0 12 13 25 0 9 16 1 24 0 25 1 24 0.015 7 0.006 n ¼9

0.745

0.508 0.789 0.344

1 NA 0.771 0.297 0.312 0.157 o 0.05



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163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 Q4 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216

Table 2 Comparative demographic characteristics of transcriptomics and proteomics groups. Characteristics

Ethnic



Chinese Malay Indian Others Male Female Good (4 45%) Fair (30–45%) Poor ( o30%) No Yes No Yes No Yes No Yes No Yes No Yes

Transcriptomics n ¼36

Proteomics n ¼50

p-value

22 8 4 2 30 6 59.61 7 8.47 24 10 2 17 19 34 2 16 20 4 32 0 36 0 36 9.63 7 19.09 n ¼19

24 15 10 1 38 12 61.28 7 10.40 30 18 2 24 26 50 0 19 31 4 46 1 49 5 45 13.87 7 18.45 n ¼31

0.404

0.41 0.431 0.708

0.943 0.092 0.548 0.624 0.393 0.051 0.445

compared with those of the samples from the proteomics study (Table 2). In addition, the characteristics of the transcriptomic MI and non-MI samples with those of the independent cohorts comprising additional MI and non-MI patients undergoing RT-qPCR were compared (Tables 3 and 4).

1.2. Gene expression data analysis and class prediction by Prediction Analysis of Microarray (PAM) The samples were preprocessed through several steps, including quality assessment and outlier identification, normalization, batch effect correction and evaluation (Fig. 1). To interrogate differentially expressed genes between MI and non-MI we conducted gene-expression profiling using the Affymetrix U219 microarray platform. Based on this set of gene, we performed principal component analysis (PCA) (Fig. 1). To determine subgroup of genes distinguishing MI from non-MI subjects, we performed supervised PAM [2] and identified a set of differentially expressed genes (DEGs) that discriminated between the two subtypes (Table 5). Gene Ontology (GO) analysis of the DEGs was performed using DAVID Bioinformatics tools [3] (http://david.abcc.ncifcrf.gov/). The GO results for the down-regulated transcripts were not enriched for any GO terms. The GO analysis revealed biological processes (Table 6). Clustering of genes were done by two methods, hierarchical and k-mean clustering. Hierarchical clustering with multiscale bootstrap resampling was done by Pvclust, an R statistical software package [4]. The Pvclust is an R package for assessing the uncertainty in hierarchical cluster analysis. For each cluster in hierarchical clustering, quantities called p-values are calculated via multiscale bootstrap resampling. The parameters (https://cran.r-project.org/web/packages/pvclust/pvclust.pdf) used here were 10000 bootstrap replications, cluster method: Ward algorithm and distance method: Euclidean. For the heat maps plot, we used log2 scale.



217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270

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Table 3 Demographic characteristics of MI study group and MI validation group. Characteristics

Ethnic


Smoking Renal Impairment Diabetes Mellitus Hypertension Hyperlipidaemia Antihyperlipidemic Medication

Chinese Malay Indian Others Male Female Good ( 445%) Fair (30–45%) Poor (o 30%) No Yes No Yes No Yes No Yes No Yes No Yes

Troponin I (µg/L) (Mean 7 SD)

MI Microarray (n ¼17)

MI Validation (n ¼20)

p-value

12 2 2 1 14 3 59.53 7 8.28 11 4 2 8 9 16 1 9 8 1 16 0 17 0 17 12.20 7 20.86 n ¼ 15

14 4 2 0 17 3 61.40 7 7.88 10 7 3 8 12 20 0 6 14 4 16 1 19 1 19 20.94 7 27.80 n ¼ 17

0.662

0.828 0.487 0.661

0.666 0.272 0.157 0.211 0.35 0.35 0.319

The k-mean clustering was performed by R (https://stat.ethz.ch/R-manual/R-devel/library/stats/ html/kmeans.html), showing that the selection of features gave a higher accuracy than PAM alone. The genes were discriminated between the MI and non-MI vascular smooth muscle cells (VSMCs) samples (Table 7). A clustered result is shown in Fig. 2 of Ref. [1].

1.3. Protein processing, electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) and LC-MS/MS analysis using Q-Exactive mass spectrometer Differential expressed proteins identified are shown in Table 8. Only peptides identified with strict spectral false discovery rate of less than 1% (q-value r 0.01) were considered.

1.4. Hierarchical cluster analysis of RT-qPCR-based detected genes Using six RT-qPCR-supported genes as a representative gene classifier characterizing the differences between MI and non-MI aortic samples, hierarchical clustering was performed with multiscale bootstrap resampling by Pvclust. The result is shown in Fig. 2.

1.5. Transcriptomic and proteomic pathways analysis Systemic evaluation was performed using IPA (www.ingenuity.com) to identify transcriptomic and proteomic pathways, and significantly enriched canonical pathways are shown in Table 9. An integrated transcriptome-proteome correlation is performed to identify common enriched pathway and molecule (Table 10).



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271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324

Table 4 Demographic characteristics of non-MI study group and non-MI validation group. Characteristics

Ethnic




Non-MI Microarray (n¼ 19)

Non-MI Validation (n ¼20)

p-value

10 6 2 1 16 3 59.68 7 8.85 13 6 0 9 10 18 1 7 12 3 16 0 19 0 19 0.01 7 0.004 n¼4

12 6 2 0 17 3 59.95 7 8.34 13 3 4 11 9

0.763

15 5 8 12 4 16 0 20 0 20 NA

0.946 0.924 0.083

0.634 0.088 0.839 0.732 – – NA

2. Experimental design, materials and methods 2.1. Sample collection Aortic tissue samples were obtained from patients who presented with coronary artery disease undergoing coronary artery bypass graft (CABG) surgery at the National University Hospital of Singapore from 2009 to 2013. Patients underwent CABG either after a recent myocardial infarction (MI group) or as stable angina patients (non-MI group). An aortic punch tissue was collected at the time of proximal anastomosis between the aorta and saphenous vein grafts. The tissues from the aortic punch were immediately preserved on dry ice, and stored in liquid nitrogen tank. The study was approved by the National Healthcare Group Domain Specific Review Board (Tissue Bank registration: NUH/2009-0073), and written informed consent was obtained from all patients. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki.

2.2. Sample grouping 17 MI and 19 non-MI samples were recruited for laser-captured microdissection (LCM) and microarray profiling. The proteomic study included 25 MI and 25 non-MI samples. Four MI and six non-MI samples overlapped between the microarray and proteomic studies. RT-qPCR was done on an independent cohort of samples, including an additional 20 MI and 20 non-MI samples. A schematic of the design and workflow is presented in Fig. 3.



325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378

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Fig. 1. (A) Normalized data. (B) Pseudo three dimensional plot of PCA analysis of the 4357 differentially expressed genes between MI (red) and non-MI (blue). The sizes of the dot represent the loading values of the Comp.3 that perpendicular on the Comp.1 and Comp.2 plane. (C) Scree plot shows the variances explained by the individual principle component. (D) Volcano plot of expression data. Green dot represents differentially expressed genes.

2.3. Sample processing The protocols for (1) cryosectioning and staining of aortic tissue, (2) LCM of VSMCs, total RNA isolation and complementary DNA (cDNA) synthesis, and (3) protein processing, ERLIC and LC-MS/MS analysis using Q-Exactive mass spectrometer are described in our manuscript [1].

2.4. RT-qPCR on an independent cohort of MI and non-MI samples The RT-qPCR protocol is described in our manuscript [1]. The primers for ARF6, ATP1A2, GUCY1A3, HIF-1A, KLHL1, MYOCD, SOD1, and UBB were obtained from the Primer Bank: ARF6 forward primer 5′GGGAAGGTGCTATCCAAAATCTT-3′ and reverse primer 5′-CACATCCCATACGTTGAACTTGA-3′; ATP1A2 forward primer 5′-TCTATCCACGAGCGAGAAGAC-3′ and reverse primer 5′-CCATGTAGGCATTTTGAAAGGC-3′; GUCY1A3 forward primer 5′-TCAGCCCTACTTGTTGTACTCC-3′ and reverse primer 5′CAGAATAGCGATGTGGGAATCAC-3′; HIF-1A forward primer 5′-GAACGTCGAAAAGAAAAGTCTCG-3′ and reverse primer 5′-CCTTATCAAGATGCGAACTCACA-3′; KLHL1 forward primer 5′-TCAGGCTCTGGGCGAAAAG-3′ and reverse primer 5′-AAAGTGCTCACACCGCTTCTC-3′; MYOCD forward primer 5′-ACGGATGCTTTTGCCTTTGAA-3′ and reverse primer 5′- AACCTGTCGAAGGGGTATCTG-3′; SOD1 forward primer 5′-AAAGATGGTGTGGCCGATGT-3′ and reverse primer 5′-CAAGCCAAACGACTTCCAGC-3′; UBB forward primer 5′-GGTCCTGCGTCTGAGAGGT-3′ and reverse primer 5′-GGCCTTCACATTTTCGATGGT-3′.



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379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432

Table 5 List of differentially expressed transcripts. Probe ID

Gene symbol

Up/down regulated in MI

wilcox

wilcox FDR

11760204_x_at 11760991_a_at 11718483_s_at 11752082_a_at 11744327_x_at 11735320_a_at 11743116_s_at 11716989_s_at 11761378_at 11754075_s_at 11718123_at 11721001_at 11759202_s_at 11758784_at 11764120_at 11729194_s_at 11757837_x_at 11721747_a_at 11753179_s_at 11757794_s_at 11732126_x_at 11729661_a_at 11717422_s_at 11758158_s_at 11743098_a_at 11715501_s_at 11725969_a_at 11760913_at 11718344_a_at 11735389_at 11747800_a_at 11721215_a_at 11755052_s_at 11763519_a_at 11717433_a_at 11752628_a_at 11747485_a_at 11715657_a_at 11757402_s_at 11730368_at 11718577_s_at 11732339_at 11744873_a_at 11763952_at 11726870_at 11727433_s_at 11726614_at 11744433_x_at 11720250_a_at 11724140_a_at 11754192_s_at 11758666_s_at 11764171_s_at 11751513_a_at 11758715_s_at 11755681_x_at 11737234_s_at 11751041_x_at 11720954_s_at 11732933_a_at

CKMT1B CKMT1B UBE2N CDH12 UBB RBMS3 KPNB1 PNRC2 NAALADL2 KRT222 AIMP1 HEXIM1 C9orf41 UBE3A – MYNN HNRNPA1 ANKRD12 FAM134B PAPD5 UBB GLB1 RBM8A FOXP1 TARSL2 IGFBP7 THUMPD1 ASAH2 CNOT7 CYLC2 HIF1A TMEM106B GYPE SLC4A4 ECHDC1 SYNCRIP SR140 GLB1 MED13 ZNF557 NET1 BCL11A KLKP1 – SETBP1 NUTF2 CDH2 AMY2B RWDD1 CRIPAK SFRS11 LOC284861 DCUN1D1 TXNDC6 DEFB126 HMGB1 LOC162632 PCMTD2 RPL30 RUNX1

Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated

0.00035204 0.00101536 0.0001261 0.00010799 1.4127E-06 4.8014E-05 4.2217E-06 0.00053133 0.0006064 0.00053077 0.00010799 0.00456914 0.00019823 0.00053077 0.00017084 9.2259E-05 0.00078736 0.00115015 0.00046374 0.00505725 0.00014694 0.00069158 0.0001261 0.00078736 0.00687991 9.2259E-05 0.0026334 2.0029E-05 0.00146865 0.0036725 0.04043046 0.00019823 0.00130072 0.17461682 4.8014E-05 0.00376444 0.00019823 0.00130072 0.00026521 0.02104398 0.00409148 0.02493936 0.00089487 0.00030585 0.0006064 0.02423264 0.00505725 3.4121E-05 0.00010799 0.00053077 2.3988E-05 0.0006064 0.00687991 0.0026334 0.00502731 9.4442E-06 0.04365745 0.00146865 0.0026334 0.00115015

0.00224576 0.00364739 0.00150508 0.00137774 0.00026136 0.00093501 0.0003841 0.00252042 0.00276999 0.00252042 0.00137774 0.00871434 0.0016669 0.00252042 0.0016669 0.00137774 0.0030992 0.00390417 0.00245118 0.00926328 0.0016669 0.00284317 0.00150508 0.0030992 0.01183985 0.00137774 0.00636836 0.00061757 0.0044541 0.00780935 0.0488865 0.0016669 0.00422165 0.18199499 0.00093501 0.00791387 0.0016669 0.00422165 0.00192411 0.028626 0.00813896 0.03283831 0.00334446 0.00205755 0.00276999 0.03248578 0.00926328 0.00084164 0.00137774 0.00252042 0.00068274 0.00276999 0.01183985 0.00636836 0.00926328 0.00038514 0.05177326 0.0044541 0.00636836 0.00390417

inMI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI in MI



433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486

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Table 5 (continued ) 11750545_a_at 11716615_s_at 200037_PM_s_at 11749445_a_at 11719713_a_at 11725073_s_at 11715490_s_at 11757108_a_at 11758637_x_at 11743386_s_at 11719932_x_at 11750815_s_at 11761866_at 11762842_s_at 11758021_s_at 11755779_a_at 11734919_s_at 11741476_x_at 11745795_s_at 11746794_a_at 11758181_s_at 11758811_x_at 11761671_a_at 11758000_s_at 11733216_s_at 200012_PM_x_at 11722616_at 11743186_a_at 11758697_x_at 11758663_s_at 11739605_a_at 11718654_s_at 11740007_at 11723448_x_at 11720481_s_at 11725386_a_at 11725355_at 11721237_a_at 11740255_x_at 11763843_a_at 11755332_a_at 11731400_s_at 11755203_x_at 11748647_a_at 11751975_a_at 11739563_a_at 11719614_a_at 11722359_x_at 11754410_s_at 11739606_x_at 11737468_a_at 11732569_at 11733180_a_at 11741826_a_at 11742053_a_at 11732720_a_at 11722645_s_at 11722842_s_at 11746051_a_at 11758520_s_at 11751517_a_at 11757817_s_at 11719053_s_at

CNOT7 REEP5 CBX3 ARHGAP15 PPM1B PHF17 AMY1A GSTTP1 AMY1A PRPF40A KIAA0319L DDX5 NCOA7 PLEKHB2 DDX3× ADAMTS20 TCEA1 MAP3K7 DDX5 C5orf33 HMGB1 HNRNPA1 ETV7 CXADR USP53 RPL21 UBLCP1 KIAA1430 RPL10A MATR3 CCDC88A PKD2 POLR3G MALL ABCD3 HOMER1 EPM2AIP1 LHFPL2 UBE2NL UACA TJAP1 TMCO1 RPL21 PTPRR SGIP1 ITPR1 LARP4 EPB41L2 APLNR CCDC88A PDC SLCO1B3 ETV1 GSTZ1 COG5 EREG ZNHIT6 ENAH HP1BP3 GUCY1A3 PRKAA1 BASP1 CEP350

Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated Upregulated

in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in in

MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI MI

0.01229819 0.01477913 0.00561109 0.00053077 0.00455191 0.02104398 0.0026334 0.0036725 0.0147944 0.00010799 0.01229819 0.03190866 0.01229819 0.0036725 0.00146865 0.00294638 0.00053077 0.00455191 0.01018421 0.01617252 0.01119828 0.00329182 0.00186355 0.0036725 0.01348981 5.1905E-06 0.00329182 0.01018421 0.00294638 0.00062978 0.00839186 0.01119828 0.00839186 0.0026334 0.50979055 0.00329182 0.10143592 0.00925052 0.00069158 0.00069158 0.00019528 0.00089487 7.8646E-05 0.02710422 0.0036725 0.00010799 0.00030585 0.00146865 0.00235021 0.00505725 0.00409148 0.04365745 0.02493936 0.12256136 0.05074665 0.00376444 0.02104398 1.145E-05 0.00666163 0.00209437 0.00235021 0.00165565 0.0062173

0.01880302 0.02163607 0.01012733 0.00252042 0.00871434 0.028626 0.00636836 0.00780935 0.02163607 0.00137774 0.01880302 0.04002103 0.01880302 0.00780935 0.0044541 0.00689976 0.00252042 0.00871434 0.01603471 0.0232834 0.01740908 0.00729325 0.00526347 0.00780935 0.02012593 0.0003841 0.00729325 0.01603471 0.00689976 0.00284168 0.01392372 0.01740908 0.01392372 0.00636836 0.51395778 0.00729325 0.11136881 0.01488126 0.00284317 0.00284317 0.0016669 0.00334446 0.00137774 0.03543661 0.00780935 0.00137774 0.00205755 0.0044541 0.00608096 0.00926328 0.00813896 0.05177326 0.03283831 0.13220905 0.05885975 0.00791387 0.028626 0.00038514 0.01173715 0.00574011 0.00608096 0.00486183 0.0110067


10

487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540


Table 5 (continued ) 11763534_x_at 11752766_x_at 11715329_at 11761881_at 11723314_x_at 11758802_a_at 11758108_s_at 11739011_s_at 11749062_a_at 11761958_s_at 11753646_x_at 11723447_at 11725729_s_at 11725658_a_at 11725496_a_at 11735535_at 11754898_a_at 11719509_a_at 11729721_s_at 11728429_a_at 11750795_a_at 11754487_x_at 11727856_s_at 11732303_a_at 11738720_s_at 11731542_at 11718993_at 11727390_a_at 11728769_at 11742385_s_at 11756285_s_at 11722814_s_at 11751269_a_at 11763119_x_at 11721835_s_at 11736501_x_at 11717574_s_at 11757274_s_at 11729916_s_at 11721216_s_at 11759049_at 11736190_a_at 11734314_at AFFX-HUMGAPDH/M33197_ 11753680_x_at 11738693_at 11727597_at 11746970_at 11722149_a_at 11748766_a_at 11744244_a_at 11759047_x_at 11733995_x_at 11719660_at 11746552_s_at 11732982_at 11720945_x_at 11736107_at 11759697_at 11757257_at 11728052_s_at 11728076_at 11722848_a_at

CNTNAP3 BTN2A2 SLC6A15 ZNF33A PXMP2 ENY2 EFEMP1 PAFAH1B1 ERG TRA@ CFL1 MALL C1orf56 MTFR1 AGPAT9 ZNF660 ZNF573 CSRP2BP LILRB3 LCOR KLHL1 C5orf33 NUP50 CREB1 OR2T3 SESTD1 CRKL STEAP2 ST6GALNAC3 OR8B2 IGF2BP3 RANBP2 SUPT3H – TMEM14B SS18 PFN1 ARGLU1 ARL5B TMEM106B ACSS3 OGN SPTA1 GAPDH RPL21 OR13C3 PADI2 NPY6R YTHDC2 FBXW7 MASP1 ABCB1 C5orf33 ATP1A2 FLJ77644 OR2J2 SNRPA1 ENTPD4 SLITRK3 PISRT1 FAM126B HDAC9 PPP3CA




0.00235021 0.1384029 0.00069158 0.00146865 2.476E-07 0.00069158 0.0027968 0.0026334 0.00103627 0.01348981 0.00455191 0.00053077 0.00040442 0.00925052 0.00687991 0.00186355 0.00839186 0.00039848 5.1905E-06 4.053E-05 1.145E-05 0.01018421 0.00069158 0.00035204 0.00209437 0.22006648 0.00409148 0.00121855 0.00760327 0.00240361 0.02292193 0.00046374 0.00455191 0.01617252 0.00186355 0.02292193 0.00165565 0.00030585 0.01929797 0.00017084 0.08324897 0.01929797 0.00089487 0.02942452 4.053E-05 0.01348981 0.14959518 0.04365745 0.05462796 0.00022952 0.00235021 0.00146865 0.00046374 0.00069158 0.14687776 0.0026334 0.05534295 0.14687776 0.00209437 0.04365745 0.01929797 0.01980258 0.1384029

0.00608096 0.14715251 0.00284317 0.0044541 9.1611E-05 0.00284317 0.00667624 0.00636836 0.00368673 0.02012593 0.00871434 0.00252042 0.00241348 0.01488126 0.01183985 0.00526347 0.01392372 0.00241348 0.0003841 0.00088212 0.00038514 0.01603471 0.00284317 0.00224576 0.00574011 0.22680946 0.00813896 0.00406184 0.0128457 0.00617593 0.03084041 0.00245118 0.00871434 0.0232834 0.00526347 0.03084041 0.00486183 0.00205755 0.0270464 0.0016669 0.09305777 0.0270464 0.00334446 0.03767153 0.00088212 0.02012593 0.15769292 0.05177326 0.06316358 0.00176918 0.00608096 0.0044541 0.00245118 0.00284317 0.15527077 0.00636836 0.06379094 0.15527077 0.00574011 0.05177326 0.0270464 0.02764888 0.14715251



541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594

11

Table 5 (continued ) 11758915_a_at 11742048_at 11758636_s_at 11756080_s_at 11730843_a_at 11739731_s_at 11719476_at 11722845_s_at 11752838_s_at 11753282_a_at 11759361_at 11742378_a_at 11757489_x_at 11720443_s_at 11756351_x_at 11716368_x_at 11727131_at 11741875_x_at 11749630_a_at 11758560_s_at 11730146_at 11738204_a_at 11757384_x_at 11721520_at 11753061_a_at 11728110_at 11722667_a_at 11718781_s_at 11734321_at 11750759_at 11737583_s_at 11727015_s_at 11728682_at 11737293_at 11746047_x_at 11734530_x_at 11723507_s_at 11742902_s_at 11741095_at 11724290_x_at 11738606_a_at 11739229_a_at 11735483_at 11739334_a_at 11738613_at 11740133_a_at 11735206_at 11741856_s_at 11735379_a_at 11719268_at 11763439_s_at 11732224_a_at 11730746_s_at 11744413_x_at 11744535_s_at 11728719_a_at 11741101_a_at 11723042_at 11716750_a_at 11754732_a_at 11740403_at 11761250_x_at 11763585_s_at

YY1 ITGB1 ASPN NUS1 MXI1 CSNK1G1 C20orf108 UBE2R2 CIDEB CMTM4 SHOX AKR1B10 RPL22 BAZ1A SOD1 PRR13 CPD AKTIP KRR1 HERC4 KLHL31 SPAM1 UROD ZDHHC17 SLFN5 GRIP1 MAPT SSBP2 BMP3 CES4 SGCD PAPPA KRR1 TACR3 KGFLP2 HLA-F ZNF609 AP3S1 CORO2A ZNF641 KCTD16 FBXW11 LANCL3 PTPRC OR2J3 CALD1 MMAA LOC653501 KIAA1009 TNNC1 HNRNPU ZNF664 PAIP2 HSPA1A TCEB1 LTBP1 ZNF655 UBE2D1 CD99L2 CNDP1 C12orf69 ARL5A TMPO




0.19511269 0.00329182 0.00409148 0.05074665 0.00265809 0.00505725 0.02837207 0.03066104 0.05074665 0.02493936 0.00030585 0.01348981 0.00078736 0.03740276 0.00069158 0.00019823 0.19511269 0.02104398 0.02493936 0.00101536 0.13030036 0.07779419 0.00022952 0.04709299 0.0026334 0.00505725 0.00687991 2.865E-05 0.10813841 0.00760327 0.00046374 0.00186355 0.00329182 0.02104398 0.00409148 9.4442E-06 0.05074665 0.08324897 0.00839186 0.01119828 0.00115015 0.10143592 0.00925052 0.0062173 0.12256136 0.28020216 0.00053077 0.00235021 0.00329182 0.03456513 0.00040442 0.02942452 0.00035204 0.01348981 0.00925052 0.0357177 0.00505725 0.00455191 0.01348981 0.00019823 0.0176765 0.00455191 0.08900096

0.20165278 0.00729325 0.00813896 0.05885975 0.00638632 0.00926328 0.03696361 0.03911925 0.05885975 0.03283831 0.00205755 0.02012593 0.0030992 0.04597682 0.00284317 0.0016669 0.20165278 0.028626 0.03283831 0.00364739 0.13933853 0.08775564 0.00176918 0.05549174 0.00636836 0.00926328 0.01183985 0.00075718 0.11733494 0.0128457 0.00245118 0.00526347 0.00729325 0.028626 0.00813896 0.00038514 0.05885975 0.09305777 0.01392372 0.01740908 0.00390417 0.11136881 0.01488126 0.0110067 0.13220905 0.28560551 0.00252042 0.00608096 0.00729325 0.04306093 0.00241348 0.03767153 0.00224576 0.02012593 0.01488126 0.04434747 0.00926328 0.00871434 0.02012593 0.0016669 0.02515502 0.00871434 0.09859388


12

595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648


Table 5 (continued ) 11738200_a_at 11718702_a_at 11747428_a_at 11745483_s_at 11730250_a_at 11716587_at 11758860_at 11734908_a_at 11734244_a_at 11743110_at 11728312_at 11739159_at 11740664_a_at 11757874_x_at 11756150_at 11757936_s_at 11745750_a_at 11715593_s_at 11728966_s_at 11729688_s_at 11742446_s_at 11762760_at 11759938_a_at 11754680_a_at 11717578_a_at 11744671_x_at 11751834_a_at 11751946_a_at 11729687_at 11715301_s_at 11750160_a_at 11727125_a_at 11722445_a_at 11757916_s_at 11739487_s_at 11756151_x_at 11743427_at 11760591_at 11733078_a_at 11760812_at 11758911_at 11724018_a_at 11753232_a_at 11729110_s_at 11757659_x_at 11724952_a_at 11754221_s_at 11754489_a_at 11753454_a_at 11715662_x_at 11760194_at 11759885_at 11724801_a_at 11761070_at 11719353_s_at 11750330_a_at 11728272_x_at 11743661_a_at 11763034_at 11722531_a_at 11731899_s_at 11725485_at 11758273_s_at

CCDC102B ARFIP1 CDK20 BECN1 LNX1 AXL HNRNPU CADPS2 ATG10 NAMPT ZNF148 FAM8A1 GPRC6A PFDN1 B2M GCSH PNPLA8 YWHAH ZNF28 LYRM7 FOXD4L2 – ITFG2 MAP3K2 VPS26A CTBP2 CLEC2A ARHGAP21 LYRM7 NOP16 LSM14A PVRL3 TRAPPC5 TBX3 SUZ12 B2M AHCYL1 C9orf84 PPP1R12A C10orf46 DYRK2 LDHC NDRG1 ADAMDEC1 RPL12 CPEB2 FAM104B C20orf7 PRKG1 TMEM189 LRRIQ3 RIMS1 CCDC55 MRPL20 GCC2 MYOCD ZNF330 MBNL1 – CALD1 PPAT DIRC2 ARF6




0.02942452 0.0631128 0.00329182 0.00026521 0.03190866 0.00409148 0.01229819 0.00329182 0.01617252 0.17461682 0.03190866 0.00146865 0.00209437 0.00760327 0.02493936 0.00046374 0.10813841 0.04043046 0.35414949 0.00046374 0.00186355 0.13030036 0.0062173 0.00235021 0.03190866 0.0631128 0.10143592 0.00130072 0.02104398 0.18465989 0.02942452 0.03456513 1.145E-05 0.0036725 0.00395253 0.01477913 0.03190866 0.49497983 0.00925052 0.04709299 0.08900096 0.00019823 0.00115015 0.05074665 0.00101536 0.10813841 0.00235021 0.10813841 0.03740276 0.00409148 0.00329182 0.22898888 0.33847537 0.01018421 0.15573308 0.01477913 0.00561109 0.00414689 0.51442081 0.55443055 0.08883741 0.0176765 0.00046374

0.03767153 0.0718515 0.00729325 0.00192411 0.04002103 0.00813896 0.01880302 0.00729325 0.0232834 0.18199499 0.04002103 0.0044541 0.00574011 0.0128457 0.03283831 0.00245118 0.11733494 0.0488865 0.35900085 0.00245118 0.00526347 0.13933853 0.0110067 0.00608096 0.04002103 0.0718515 0.11136881 0.00422165 0.028626 0.19192179 0.03767153 0.04306093 0.00038514 0.00780935 0.00813896 0.02163607 0.04002103 0.50038945 0.01488126 0.05549174 0.09859388 0.0016669 0.00390417 0.05885975 0.00364739 0.11733494 0.00608096 0.11733494 0.04597682 0.00813896 0.00729325 0.23534968 0.34405463 0.01603471 0.16369671 0.02163607 0.01012733 0.00820508 0.51721658 0.55593308 0.09859388 0.02515502 0.00245118



649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702

13

Table 5 (continued ) 11751364_a_at 11762968_a_at 11763313_at 11740734_a_at 11743792_a_at AFFX-r2-Ec-bioB-5_at 11752951_x_at 11720802_s_at 11760353_at 11754373_a_at 11730830_x_at 11737523_x_at 11759492_at 11728009_at 11730408_a_at 11728044_a_at 11763618_a_at 11716415_s_at 11737238_s_at 11760953_x_at 11758469_s_at 11746163_a_at 11724561_x_at 11735855_at 11757649_a_at 11732524_a_at 11736945_a_at 11716547_s_at 11746635_a_at 11744612_a_at 11731356_a_at 11728896_a_at 11759458_at 11758179_s_at 11762010_a_at 11757381_x_at 11743193_a_at 11726367_a_at 11750342_a_at 11744231_a_at 11724255_a_at 11737305_a_at 11733958_a_at 11739429_a_at 11751172_a_at 11737677_at 11725393_s_at 11744029_a_at 11743134_x_at 11745187_a_at 11737856_a_at 11759126_a_at 11722129_at 11762149_at 11734407_a_at 11730872_x_at 11758126_s_at 11753413_x_at

SLC47A1 MEI1 SEPHS1 A2BP1 TTC39C – RPL15 BIN3 SAFB2 MARK3 AMPD2 VSIG8 RPS27L VPREB3 C19orf33 C14orf126 SNAPC4 NDUFB8 EOMES UBXN11 C7orf16 LARP4B TSR2 TNP2 TIMM16 CHKB-CPT1B HIPK4 TLR9 LEF1 NUDCD1 IP6K3 LRP8 LOC285501 ZNF175 GRAMD1B GTF2A2 PARD6G ERICH1 FRMPD1 MAPK7 OAS1 FAM166A GTPBP3 ZDHHC24 TRIB3 BTBD18 MAK16 BBS4 FKBP8 BET1L OPCML THRA FAM102B C18orf45 MATN4 RASSF5 EAF1 DLK1

Upregulated in MI Upregulated in MI Upregulated in MI Upregulated in MI Upregulated in MI Upregulated in MI Upregulated in MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI Downregulatedin MI

0.0026334 0.13030036 0.17461682 0.02942452 0.02710422 0.00019823 0.04365745 9.2259E-05 0.00687991 0.00046374 0.00505725 1.145E-05 0.00235021 0.00146865 0.0385022 0.00875884 0.00026521 0.00165565 0.0062173 0.00022952 0.26971625 0.04043046 0.02292193 0.00409148 7.8646E-05 0.00358451 0.00040442 0.01477913 0.00089487 0.00121855 0.00078736 0.01018421 0.01617252 0.26674073 0.00019823 0.0728868 0.00019823 0.03740276 0.08324897 0.00294638 0.0176765 0.00561109 0.00089487 0.01900683 0.05732237 0.02104398 0.0631128 0.04043046 0.00022952 0.00925052 0.00101536 0.04365745 0.00165565 0.00115015 0.00760327 0.00409148 0.59586665 0.07262653

0.00636836 0.13933853 0.18199499 0.03767153 0.03543661 0.0016669 0.05177326 0.00137774 0.01183985 0.00245118 0.00926328 0.00038514 0.00608096 0.0044541 0.04717157 0.01446773 0.00192411 0.00486183 0.0110067 0.00176918 0.27567683 0.0488865 0.03084041 0.00813896 0.00137774 0.00780935 0.00241348 0.02163607 0.00334446 0.00406184 0.0030992 0.01603471 0.0232834 0.27339077 0.0016669 0.0824713 0.0016669 0.04597682 0.09305777 0.00689976 0.02515502 0.01012733 0.00334446 0.02694455 0.06586732 0.028626 0.0718515 0.0488865 0.00176918 0.01488126 0.00364739 0.05177326 0.00486183 0.00390417 0.0128457 0.00813896 0.59586665 0.08242889


703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 14

Category

Term

Count

%

p-value

Genes

List Total

Pop Hits

Pop Total

Fold Enrichmen

tBonferroni

Benjamini

FDR

GOTERM_BP_FAT

GO:0070647~protein modification by small protein conjugation or removal

12

4.109589

4.96E-05

216

160

13528

4.697222222

0.08427547

0.084275

0.084054

GOTERM_BP_FAT

GO:0032446~protein modification by small protein conjugation

10

3.4246575

2.56E-04

216

132

13528

4.744668911

0.365690828

0.203565

0.433849

GOTERM_BP_FAT

GO:0016567~protein ubiquitination

9

3.0821918

6.19E-04

216

119

13528

4.736694678

0.666812995

0.30674

1.044247

GOTERM_BP_FAT

GO:0006940~regulation of smooth muscle contraction GO:0051147~regulation of muscle cell differentiation GO:0006414~translational elongation GO:0006937~regulation of muscle contraction GO:0048742~regulation of skeletal muscle fiber development GO:0007507~heart development

5

1.7123288

0.00299912

216

38

13528

8.240740741

0.995162875

0.736278

4.964734

5

1.7123288

0.00330086

216

39

13528

8.029439696

0.99717351

0.690793

5.451184

7

2.3972603

0.00544585

216

101

13528

4.3406674

0.999938274

0.801202

8.842269

6

2.0547945

0.00571597

216

72

13528

5.219135802

0.999961887

0.766265

9.261108

4

1.369863

0.00703496

ENY2, UBE2N, SUZ12, SUPT3H, ATG10, FBXW7, UBE3A, UBB, UBE2D1, TMEM189, FBXW11, LNX1 UBE2N, SUZ12, ATG10, FBXW7, UBE3A, UBB, UBE2D1, TMEM189, FBXW11, LNX1 UBE2N, SUZ12, FBXW7, UBE3A, UBB, UBE2D1, TMEM189, FBXW11, LNX1 TACR3, MYOCD, GUCY1A3, ATP1A2, SOD1 TBX3, MYOCD, EREG, UBB, HDAC9 RPL30, RPL22, RPL21, RPL15, UBB, RPL10A, RPL12 TACR3, MYOCD, TNNC1, GUCY1A3, ATP1A2, SOD1 TBX3, MYOCD, UBB, HDAC9

216

25

13528

10.02074074

0.999996388

0.791204

11.28038

10

3.4246575

0.00750053

216

215

13528

2.913006029

0.999998429

0.773463

11.98298

GO:0016202~regulation of striated muscle tissue development GO:0048634~regulation of muscle development GO:0048534~hemopoietic or lymphoid organ development

5

1.7123288

0.00807194

216

50

13528

6.262962963

0.999999435

0.762736

12.83814

5

1.7123288

0.00865211

216

51

13528

6.140159768

0.9999998

0.753948

13.69842

11

3.7671233

0.00874561

216

260

13528

2.6497151

0.999999831

0.727281

13.83632

GOTERM_BP_FAT

GO:0030036~actin cytoskeleton organization

10

3.4246575

0.01017938

216

226

13528

2.77122255

0.999999987

0.752662

15.92501

GOTERM_BP_FAT

GO:0048641~regulation of skeletal muscle tissue development

4

1.369863

0.01066911

CRKL, TBX3, MYOCD, HEXIM1, TNNC1, PKD2, HDAC9, CXADR, ITGB1, FOXP1 TBX3, MYOCD, UBB, HDAC9, CXADR TBX3, MYOCD, UBB, HDAC9, CXADR PTPRC, CRKL, RPL22, BCL11A, TCEA1, SPTA1, HDAC9, SOD1, RUNX1, ITGB1, FOXP1 EPB41L2, PFN1, CALD1, CFL1, PAFAH1B1, ARF6, SPTA1, PRKG1, ITGB1, KLHL1 TBX3, MYOCD, UBB, HDAC9

216

29

13528

8.638569604

0.999999995

0.743329

16.62747

19

6.5068493

0.01072364

ENY2, BMP3, PTPRC, TBX3, GRIP1, CREB1, MED13,

216

624

13528

1.906991928

0.999999995

0.720797

16.70534

GOTERM_BP_FAT GOTERM_BP_FAT GOTERM_BP_FAT GOTERM_BP_FAT GOTERM_BP_FAT

GOTERM_BP_FAT GOTERM_BP_FAT GOTERM_BP_FAT

GOTERM_BP_FAT



Table 6 Gene ontology of upregulated genes.

757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 19

6.7857143

9.63E-04

GOTERM_CC_FAT

GO:0005829~cytosol

36

12.857143

9.94E-04

GOTERM_CC_FAT

GO:0031981~nuclear lumen

37

13.214286

0.00232476

GOTERM_CC_FAT

GO:0005794~Golgi apparatus

25

8.9285714

0.00378136

GOTERM_CC_FAT

GO:0005654~nucleoplasm

25

8.9285714

0.00436162

GOTERM_CC_FAT

GO:0030864~cortical actin cytoskeleton GO:0005635~nuclear envelope

4

1.4285714

0.0087726

9

3.2142857

0.01377595

GOTERM_CC_FAT

GO:0070013~intracellular organelle lumen

39

13.928571

0.02000434

GOTERM_CC_FAT

GO:0044451~nucleoplasm part

16

5.7142857

0.02385422

GOTERM_CC_FAT

GO:0031965~nuclear membrane 5

1.7857143

0.02568978

GOTERM_CC_FAT

GO:0043233~organelle lumen

13.928571

0.0276102

GOTERM_CC_FAT

39

197

515

12782

2.393750924

0.246766301

0.246766

1.275853

197

1330

12782

1.756238312

0.253459145

0.135974

1.315771

197

1450 12782

1.655641519

0.495544858

0.203949

3.053045

197

872

12782

1.860184883

0.671699641

0.243049

4.921769

197

882

12782

1.839094352

0.72338246

0.22665

5.656882

197

28

12782

9.269035533

0.925019331

0.350631

11.07554

197

205

12782

2.848532871

0.983063526

0.441562

16.87269

197

1779

12782

1.42239837

0.997370329

0.524131

23.60067

197

555

12782

1.870508072

0.99917336

0.545557

27.50364

197

73

12782

4.444058132

0.999524672

0.534736

29.29883

197

1820

12782

1.39035533

0.999733881

0.526841

31.13293

15

DDX5, CNOT7, UBE2N, YWHAH, HIF1A, MYOCD, EREG, ZNF148, GU KRR1, SNRPA1, ERG, RPL15, SYNCRIP, HSPA1A, DDX5, HNRNPA1, HNRNPU, MRPL20, RPL30, RBM8A, RPL22, PNRC2, R NAMPT, ENAH, UBE3A, GRIP1, RPL15, MAP3K7, RPL30, MAP3K2, MAPT, GSTZ1, GUCY1A3, PAFAH1B1, PPP3CA, RPL12 ENY2, SUPT3H, HMGB1, SYNCRIP, ZNF655, CNOT7, ZNF330, CORO2A, DDX3×, RBM8A, ZNF148, NUP50, TCEA1, UBE2D CCDC88A, AIMP1, BECN1, PTPRR, AP3S1, ARF6, ARFIP1, CXADR, PRKG1, GCC2, TJAP1, B2M, ARHGAP21, PNPLA8, ZDHH ENY2, HMGB1, SUPT3H, SYNCRIP, CNOT7, CORO2A, DDX3×, RBM8A, NUP50, TCEA1, UBE2D1, KPNB1, PRPF40A, POLR EPB41L2, CALD1, CFL1, SPTA1 UACA, NUP50, CBX3, PAFAH1B1, TMPO, RANBP2, KPNB1, MATR3, ITPR1 ENY2, SUPT3H, HMGB1, SYNCRIP, ZNF655, CNOT7, ZNF330, MRPL20, CORO2A, DDX3×, RBM8A, ZNF148, NUP50, TCEA ENY2, POLR3G, SUPT3H, CTBP2, CREB1, YY1, MED13, CNOT7, SUZ12, CORO2A, PHF17, HIF1A, DDX3×, RBM8A, HDAC9 CBX3, PAFAH1B1, TMPO, MATR3, ITPR1 ENY2, SUPT3H, HMGB1, SYNCRIP, ZNF655, CNOT7, ZNF330, MRPL20, CORO2A,



GOTERM_CC_FAT

GO:0045935~positive regulation of nucleobase, nucleoside, nucleotide and nuc GO:0030529~ribonucleoprotein complex

811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 16

Category

Term

Count

%

p-value

GOTERM_CC_FAT

GO:0030054~cell junction

15

5.3571429

0.02854188

GOTERM_CC_FAT

GO:0044445~cytosolic part

7

2.5

0.02964735

GOTERM_CC_FAT

GO:0005912~adherens junction

7

2.5

0.03218777

GOTERM_CC_FAT

GO:0031974~membraneenclosed lumen

39

13.928571

0.03603007

GOTERM_MF_FAT

GO:0003723~RNA binding

23

8.2142857

0.0016071

GOTERM_MF_FAT

GO:0016881~acid-amino acid ligase activity

10

3.5714286

0.00396374

GOTERM_MF_FAT

GO:0019787~small conjugating protein ligase activity

9

3.2142857

0.00418513

GOTERM_MF_FAT

GO:0003702~RNA polymerase II transcription factor activity

11

3.9285714

0.00457311

GOTERM_MF_FAT

GO:0016879~ligase activity, forming carbon-nitrogen bonds

10

3.5714286

0.00955683

GOTERM_MF_FAT

GO:0003735~structural constituent of ribosome

8

2.8571429

0.01527537

Genes

DDX3×, RBM8A, ZNF148, NUP50, TCEA ARHGAP21, PTPRC, ENAH, CTBP2, CADPS2, GRIP1, PVRL3, CD99L2, ABCB1, CDH2, HOMER1, CXADR, ITGB1, RIMS1, TJA RPL30, PFDN1, UACA, RPL22, RPL21, GUCY1A3, UBB PTPRC, ENAH, PVRL3, ABCB1, CDH2, CXADR, ITGB1 ENY2, SUPT3H, HMGB1, SYNCRIP, ZNF655, CNOT7, ZNF330, MRPL20, CORO2A, DDX3×, RBM8A, ZNF148, NUP50, TCEA KRR1, SNRPA1, AIMP1, CPEB2, RPL15, SYNCRIP, MBNL1, IGF2BP3, DDX5, HNRNPA1, HNRNPU, MRPL20, RPL30, LARP4 UBE2N, AKTIP, UBE3A, HERC4, UBE2NL, UBE2D1, TMEM189, FBXW11, LNX1, UBE2R2 UBE2N, AKTIP, UBE3A, UBE2NL, UBE2D1, TMEM189, FBXW11, LNX1, UBE2R2 SUPT3H, ETV7, HIF1A, TBX3, ZNF148, CREB1, TCEA1, MED13, TCEB1, LCOR, FOXP1 UBE2N, AKTIP, UBE3A, HERC4, UBE2NL, UBE2D1, TMEM189, FBXW11, LNX1, UBE2R2 RPL30, RPL22, RPL21, RPL15, UBB, RPL10A, RPL12, MRPL20

List Total

Pop Hits

Pop Total

Fold Enrichmen

tBonferroni

Benjamini

FDR

197

518

12782

1.878858554

0.999799239

0.508085

32.00679

197

152

12782

2.988044349

0.999856352

0.4937

33.03034

197

155

12782

2.930211233

0.999933536

0.496948

35.32875

197

1856

12782

1.363387231

0.999979362

0.512871

38.66672

201

718

12983 2.069104339

0.477004104

0.477004

2.220802

201

201

12983 3.213534318

0.798217111

0.550797

5.394694

201

166

12983 3.501978061

0.815507665

0.43072

5.687888

201

244

12983 2.911936221

0.842320571

0.36985

6.199674

201

231

12983 2.796192199

0.979140063

0.538828

12.54851

201

168

12983 3.075811419

0.997977614

0.644387

19.34096



Table 6 (continued )

865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 GO:0016566~specific transcriptional repressor activity GO:0030528~transcription regulator activity

4

1.4285714

0.01770409

34

12.142857

0.02428221

GOTERM_MF_FAT

GO:0003712~transcription cofactor activity

12

4.2857143

0.02515659

GOTERM_MF_FAT

GO:0004842~ubiquitin-protein ligase activity

7

2.5

0.0262357

GOTERM_MF_FAT

GO:0008134~transcription factor binding

15

5.3571429

0.02754274

GOTERM_MF_FAT

GO:0003779~actin binding

11

3.9285714

0.02969715

GOTERM_MF_FAT

GO:0019899~enzyme binding

15

5.3571429

0.03171181

GOTERM_MF_FAT

GO:0008092~cytoskeletal protein binding

14

5

0.04821415

GOTERM_MF_FAT

GO:0016564~transcription repressor activity

10

3.5714286

0.05535048

GOTERM_MF_FAT

HEXIM1, YY1, HDAC9, FOXP1 ENY2, SUPT3H, ETV7, GRIP1, CBX3, CNOT7, MXI1, MYOCD, HEXIM1, ZNF148, BCL11A, ETV1, TCEA1, ERG, ZNF33A, SSB ENY2, SUPT3H, CTBP2, MYOCD, GRIP1, YY1, CREB1, BCL11A, MED13, HDAC9, DDX5, MXI1 UBE2N, UBE3A, UBE2NL, UBE2D1, FBXW11, LNX1, UBE2R2 ENY2, SUPT3H, HMGB1, CTBP2, GRIP1, YY1, CREB1, MED13, MXI1, DDX5, HIF1A, MYOCD, BCL11A, LCOR, HDAC9 EPB41L2, PFN1, CORO2A, ENAH, YWHAH, CCDC88A, TNNC1, CALD1, CFL1, SPTA1, KLHL1 PTPRC, CCDC88A, PTPRR, CBX3, CDH2, SOD1, RIMS1, PFN1, YWHAH, HIF1A, MAPT, PKD2, PAFAH1B1, RANBP2, HDAC9 ENAH, CCDC88A, TNNC1, CALD1, KLHL1, EPB41L2, PFN1, CORO2A, YWHAH, MAPT, CFL1, PKD2, PAFAH1B1, SPTA1 CTBP2, TBX3, HEXIM1, ZNF148, YY1, BCL11A, CBX3, HDAC9, MXI1, FOXP1

201

36

12983 7.176893311

0.999252415

0.642414

22.07479

201

1512

12983 1.452466503

0.99995015

0.710127

29.05338

201

363

12983 2.135274043

0.999965267

0.680458

29.936

201

147

12983 3.075811419

0.999977772

0.657477

31.01122

201

513

12983 1.888656135

0.999987063

0.640565

32.29303

201

326

12983 2.179486006

0.999994708

0.636668

34.3577

201

523

12983 1.852544163

0.99999771

0.631749

36.23541

201

504

12983 1.794223328

0.999999998

0.758878

49.84218

201

316

12983 2.044051892

1

0.783426

54.84568

T. Wongsurawat et al. / Data in Brief ∎ (∎∎∎∎) ∎∎∎–∎∎∎ 17


GOTERM_MF_FAT


18

919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972

Table 7 Contingency table of prediction results from 21 genes. Reference

Prediction

MI Non-MI Total

MI

Non-MI

Total

16 1 17

2 18 20

18 19 37

Event

No-Event

Total

A C A þC 0.941176 0.9 0.918919

B D B þD 94 90 92

A þB C þD A þB þCþ D

Reference

Prediction

Event No-Event Total Sensitivity ¼ A/(Aþ C) Specificity ¼ D/(B þD) Accuracy ¼ (A þD)/(A þB þC þD)

Fig. 2. Hierarchical clustering on six RT-qPCR-based validation genes.


973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026

19

Table 8 Differentially expressed proteins.


20

1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080





1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134

21



22

1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188


Table 9 Pathway mapping of 370 transcripts (highlighted in light blue) and 94 proteins (highlighted in yellow).

Table 10 Pathway mapping of combined 21 gene signature and 94 proteins. Ingenuity Canonical Pathways

-log(p-value)

Ratio

Molecules

Superoxide Radicals Degradation RhoGDI Signaling Acetyl-CoA Biosynthesis III (from Citrate) Clathrin-mediated Endocytosis Signaling Amyotrophic Lateral Sclerosis Signaling Paxillin Signaling Regulation of eIF4 and p70S6K Signaling Actin Cytoskeleton Signaling Mitochondrial Dysfunction Crosstalk between Dendritic Cells and Natural Killer Cells NRF2-mediated Oxidative Stress Response

3.1 2.11 2.04 1.9 1.82 1.82 1.69 1.64 1.63 1.61 1.57

0.4 0.046 1 0.04 0.052 0.052 0.035 0.033 0.033 0.074 0.032

CAT,SOD1 ITGB1,RACK1,GDI2,ACTG1 ACLY ITGB1,UBB,ARF6,ACTG1 CAT,BID,SOD1 ITGB1,ARF6,ACTG1 ITGB1,EIF3G,EIF3F,RPS4X ITGB1,PFN1,SSH3,ACTG1 NDUFA9,NDUFV2,CAT,COX5A CAMK2D,ACTG1 UBB,CAT,SOD1,ACTG1



1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242

23

Fig. 3. Work flow and study design.

Acknowledgements This work was supported by the National University Health System Clinician Scientist Program, Singapore and Biomedical Institutes of A*STAR, Singapore. We thank Ms Chan Yang Sun (Genomic Institute of Singapore, A*STAR, Singapore) for laboratory support and tissue processing. We thank Dr. Zhiqun Tang (Bioinformatics Institute, A*STAR, Singapore) for bioinformatics suggestions. We also thank Dr. Yenamandra S.P. for useful discussion of the experimental design and optimization of the experimental study protocols.


24

1243 1244 1245 1246 1247 1248 1249 1250 1251


References

Q5

[1] T. Wongsurawat, C. Woo, A. Giannakakis, X. Lin, E. Cheow, C. Lee, M. Richards, S. Sze, V. Nookaew, K. Kuznetsov, V. Sorokin, Distinctive molecular signature and activated signaling pathways in aortic smooth muscle cells of patients with myocardial infarction, Atherosclerosis (2018) (in press). [2] R. Tibshirani, T. Hastie, B. Narasimhan, G. Chu, Diagnosis of multiple cancer types by shrunken centroids of gene expression, Proc. Natl. Acad. Sci. USA 99 (2002) 6567–6572. http://dx.doi.org/10.1073/pnas.082099299. [3] W. Huang, B.T. Sherman, R.A. Lempicki, Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources, Nat. Protoc. 4 (2009) 44–57. http://dx.doi.org/10.1038/nprot.2008.211. [4] R. Suzuki, H. Shimodaira, Pvclust: an R package for assessing the uncertainty in hierarchical clustering, Bioinformatics. 22 (2006) 1540–1542. http://dx.doi.org/10.1093/bioinformatics/btl117.
