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Supplementary Table 5A

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CE2/+ f/f CA/+ CE2/+ f/f Supplementary Table 5A: Pathway enrichment analysis for differentially expressed genes between Nkx3.1 ; Pten ; Braf and Nkx3.1 ; Pten mouse prostate tumors Pathway Gene Number Enrichment Normalized p-value False Family-wise Rank Leading Edge Genes Set of genes Score enrichment Discovery Error Rate at Details in the score Rate p-value Max pathway q-value TPM2 ACTG2 MYL9 ACTA2 VCL DES MYLK ITGA1 Details TPM4 SORBS1 CALM2 ITGB5 PXN LMOD1 TNNC2 1 REACTOME_MUSCLE_CONTRACTION ... 30 0.78 2.58 0 0 0 2180 MYL1 MYH11 Details TPM2 ACTG2 MYL9 ACTA2 VCL MYLK ITGA1 2 REACTOME_SMOOTH_MUSCLE_CONTRACTION ... 20 0.81 2.39 0 0 0 1609 TPM4 SORBS1 CALM2 ITGB5 PXN LMOD1 MYH11 ITGA3 LAMB3 ITGB4 THBS1 LAMA3 CD44 ITGA6 ITGAV ITGB1 SPP1 LAMC2 ITGA1 SDC1 RELN LAMC1 FN1 ITGB5 THBS2 COL1A2 ITGA9 ITGB6 SDC2 HSPG2 TNC COL6A1 COL4A2 COL6A2 Details COL4A6 ITGA5 COL4A1 LAMA1SV2B COL5A1 3 KEGG_ECM_RECEPTOR_INTERACTION ... 59 0.63 2.32 0 0 0 3812 COL6A3 COL3A1 ITGA11 COL5A2 ITGA10 Details ACTIN1 FLNC FBLIM1 ITGB1 FLNA RSU1 FERMT2 4 REACTOME_CELLEXTRACELLULAR_MATRIX_INTERACTIONS ... 13 0.81 2.16 0 0 0.001 1193 PXN ILK ITGA3 ITGB4 THBS1 ITGA6 ITGAV ITGB1 SPP1 ITGA1 LAMC1 FN1 ITGB5 COL1A2 CDH1 BCRAR1 ITGA9 ITGB6 COL4A5 TNC COL4A2 ITGA5 COL4A1 Details LAMA1 PTPN1 FGG PECAM1 FGA FBN1 ITGA11 5 REACTOME_INTEGRIN_CELL_SURFACE_INTERACTIONS ... 62 0.57 2.09 0 0 0.002 3812 ITGA10 COL1A1 LAMA2 LAMB2 ITGA3 CCND1 LAMB3 ITGB4 THBS1 FLNB LAMA3 ACTN1 IGF1R CCND2 ITGA6 ITGAV FLNC MYL9 CAV1 ITGB1 VEGF1 PDGFRA SPP1 FLNA MAP2K1 PDGFC VCL PPP1CC MYLK LAMC2 CAPN2 CDC42 ITGA1 RELN LAMC1 AKT3 FN1 CAV2 PDGFRB ITGB5 PXN ILK PDGFB THBS2 DOCK1 COL1A2 FLT1 FIGF BCAR1 ITGA9 ITGB6 PAK3 TNC COL6A1 COL4A2 COL6A2 COL4A6 ITGA5 COL4A1 LAMA1 Details BCL2 COL5A1 PGF ZYX COL6A3 COL3A1 ITGA11 6 KEGG_FOCAL_ADHESION ... 148 0.5 2.08 0 0.001 0.006 3001 COL5A2 Details TPM2 DES TPM4 TNNI1 TPM1 TNNT1 TNNC2 7 REACTOME_STRIATED_MUSCLE_CONTRACTION ... 14 0.76 2.06 0 0.001 0.009 1911 TNNC1 MYL1 LAMB3 ITGB4 LAMA3 ACTN1 ITGA6 FLNC FBLIM1 ITGB1 FLNA CLDN6 RSU1 FERMT2 LAMC2 CLDN2 CLDN7 PXN ILK PVRL3 COL17A1 CDH1 CLDN5 DST Details PVRL1 CD151 CLDN23 CLDN4 PVR CLDN1 LIMS2 8 REACTOME_CELL_JUNCTION_ORGANIZATION ... 54 0.56 2.03 0 0.002 0.016 3502 CDH15 CDH5 CDH3 ITGA3 ITGB4 ACTN1 ITGA6 PKP2 ITGAV ITGB1 Details DES ITGA1 ITGB5 ITGA9 ITGB6 LMNA ITGA5 GJA1 9 KEGG_ARRHYTHMOGENIC_RIGHT_VENTRICULAR_CARDIOMYOPATHY_ARVC ... 41 0.57 1.97 0 0.005 0.044 3108 ITGA11 ITGA10 ITGA3 ITGB4 TPM2 ITGA6 ITGAV ITGB1 DES Details ITGA1 TPM4 TGFB3 ITGB5 ITGA9 ITGB6 LMNA 10 KEGG_HYPERTROPHIC_CARDIOMYOPATHY_HCM ... 46 0.54 1.89 0 0.015 0.15 2281 ITGA5 HSP90AA1 SRGAP3 MYL9 ITGB1 MAP2K1 ROBO1 PRNP CDC42 ITGA1 DPYSL3 GDNF SEMA7A Details MYH10 RGOC SLIT2 COL1A2 GPC1 KRAS PAK3 11 REACTOME_AXON_GUIDANCE ... 110 0.45 1.83 0 0.032 0.338 3156 COL4A5 RRAS COL6A1 COL4A2 COL6A2 MYH11 COL4A1 SEMA5A COL5A1 CNTN2 COL6A3 COL3A1 MYH9 NCAM1 COL5A2 CDK5R1 LIMK1 PLXNA2 SEMA6D PPP1R14A ITPR3 ADCY3 ADCY2 GUCY1A3 PLCB4 Details PLCB2 MYH11 RAMP3 GNA12 PRKG1 ITPR1 12 KEGG_VASCULAR_SMOOTH_MUSCLE_CONTRACTION ... 69 0.47 1.8 0 0.037 0.435 3110 PLA2G2F PLA2G12B EDNRA CALML3 ITGA3 ITGB4 TPM2 ITGA6 ITGAV ITGB1 DES ITGA1 TPM4 TGFB3 SGCB ITGB5 TPM1 ADCY3 Details ADCY2 ITGA8 ITGA9 ITGB6 ATP2A2 TNNC1 LMNA 13 KEGG_DILATED_CARDIOMYOPATHY ... 52 0.49 1.76 0 0.049 0.634 2281 ITGA5 CDKN2B CCND1 CCND2 YWHAQ SMAD3 YWHAE CDKN1A SMC3 PCNA CUL1 CDC16 SFN TGFB3 Details MCM7 STAG1 YWHAG HDAC2 GADD45A YWHAH 14 KEGG_CELL_CYCLE ... 92 0.43 1.67 0 0.08 0.953 2721 CDC6 TFDP1 CDKN2B ITGA3 FZD1 CCND1 LAMB3 LAMA3 HSP90AA1 FGF10 IGF1R VHL OTGA6 ITGAV SMAD3 ITGB1 VEGFA PDGFRA MAP2K1 CDKN1A LAMC2 RUNX1T1 WNT10A CDC42 JAK1 TGFB3 EGLN3 LAMC1 AKT3 EST1 WNT5B RET FN1 PDGFRB RALB PDGFB FIGF CCDC6 RALA CDH1 CBLB RARB KRAS DAPK2 HDAC2 PTGS2 NFKB2 Details MMP2 WNT5A COL4A2 COL4A6 RAD51 FOXO1 15 KEGG_PATHWAYS_IN_CANCER ... 235 0.38 1.66 0 0.086 0.971 2587 COL4A1 FGF13 LAMA1 ITGA3 ITGB4 ACTN1 FGF10 F2R ITGA6 ITGAV RRAS2 MYL9 SCIN ITGB1 PDGFRA MAP2K1 PDGFC VCL PPP1CC MYLK ARPC5L CDC42 ITGA1 ARPC2 FN1 PDGFRB MYH10 ITGB5 PXN PDGFB Details DOCK1 BCAR1 ITGA9 ITGB6 KRAS PAK3 RRAS 16 KEGG_REGULATION_OF_ACTIN_CYTOSKELETON ... 148 0.4 1.65 0 0.085 0.974 2082 WASF2 WASF1 CDKN2B ITGA3 CCND1 LAMB3 LAMA3 ITGA6 Details ITGAV ITGB1 LAMC2 LAMC1 AKT3 FN1 RARB 17 KEGG_SMALL_CELL_LUNG_CANCER ... 67 0.43 1.64 0 0.089 0.982 2492 PTGS2 COL4A2 COL4A6 COL4A1 LAMA1 BCL2 ITGA3 THBS1 HSPA5 ACTIN1 F2R CFD ITGA6 MGLL ITGAV THBD CAV1 ITGB1 VEGFA FLNA VCL SLC3A2 SERPING1 PLAT TGFB3 GNG13 AKT3 FN1 CALM2 PLAU PDGFB ITPR3 GNB4 THBS2 KNG1 Details COL1A2 SPARC GNB1 FIGF TEK BCAR1 KRAS 18 REACTOME_HEMOSTASIS ... 190 0.38 1.64 0 0.089 0.983 1718 P3RY1 GNG11 TFP1 Details CDKN2B CCND1 CDKN2A SMAD3 CDKN1A TGFB3 19 BIOCARTA_G1_PATHWAY ... 19 0.64 1.86 0.001 0.023 0.233 743 Details CCND1 THBS1 BBC3 CCND2 CCNG1 GTSE1 20 KEGG_P53_SIGNALING_PATHWAY ... 51 0.51 1.82 0.001 0.034 0.383 2121 CDKN1A ZMAT3 OGFBP3SFN RCHY1 Details HSP90AA1 IGF1R MYC KRAS PPP2CA AKT1 BCL2 21 BIOCARTA_TEL_PATHWAY ... 12 0.69 1.79 0.001 0.043 0.507 2492 CDKN2B THBS1 CHRD SMAD3 SP1 CUL1 ID2 BMPR1A MYC TGFB3 INHBA ACVR2B ROCK2 SMURF1 THBS2 ACVR1 PPP2CA ID3 TFDP1 Details ACVR2A FST PPP2CB ZFYVE16 ID4 E2F4 BMP4 22 KEGG_TGF_BETA_SIGNALING_PATHWAY ... 53 0.49 1.76 0.001 0.049 0.615 4040 SMAD5 BMP5 CCND1 THBS1 CDKN2A VEGFA MAP2K1 CDKN1A Details VEGFC MYC FIGF CDH1 KRAS DAPK2 MMP2 23 KEGG_BLADDER_CANCER ... 37 0.51 1.75 0.001 0.049 0.662 2817 MDM2 RASSF1 TYMP E2F3 PGF EPHB4 SRGAP3 ITGB1 ROBO1 EPHB2 RHOD CDC42 EFNB2 SEMA7A NFATC4 CXCL12 SLIT2 EFNA5 EPHB1 KRAS EFNB1 PAK3 PPP3R1 RGS3 Details PPP3CA SEMA5A LIMK1 PLXNA2 SEMA6D EFNA4 24 KEGG_AXON_GUIDANCE ... 84 0.44 1.75 0.001 0.047 0.664 4608 NTN4 RAC1 SLIT3 EPHA2 THBS1 HSPA5 ACTN1 CFD VEGFA FLNA VCL Details SERPING1 TGFB3 FN1 CALM2 PDGFB THBS2 25 REACTOME_PLATELET_DEGRANULATION ... 57 0.48 1.74 0.001 0.051 0.741 1412 KNG1 SPARC FIGF PRNP GDNF COL1A2 COL4A5 COL6A1 COL4A2 COL6A2 GFRA1 COL4A1 COL5A1 ST8SIA2 CNTN2 Details COL6A3 COL3A1 NCAM1 COL5A2 CACNA1G 26 REACTOME_NCAM1_INTERACTIONS ... 26 0.56 1.73 0.001 0.05 0.747 3506 COL1A1 PPP2R2B VAPA TJP1 ACTN1 RRAS2 MYL9 CLDN6 CLDN2 CSDA CDC42 AMOTL1 AKT3 TJP2 CLDN7 Details MYH10 CLDN5 KRAS RRAS MYH11 CLDN23 CLDN4 27 KEGG_TIGHT_JUNCTION ... 82 0.43 1.66 0.001 0.084 0.964 4779 MYH9 PPP2CB CLDN1 THBS1 HSPA5 ACTN1 F2R CFD MGLL ITGB1 VEGFA FLNA VCL SERPING1 TGFB3 GNG13 AKT3 Details FN1 CALM2 PDGFB ITPR3 GNB4 THBS2 KNG1 28 REACTOME_FORMATION_OF_PLATELET_PLUG ... 129 0.39 1.61 0.001 0.109 0.997 1631 COL1A2 SPARC GNB1 FIGF BCAR1 P2RY1 GNG11 THBS1 HSPA5 ACTN1 F2R CFD MGLL VEGFA FLNA VCL SERPING1 TGFB3 GNG13 AKT3 FN1 CALM2 Details PDGFB ITPR3 GNB4 THBS2 KNG1 COL1A2 SPARC 29 REACTOME_PLATELET_ACTIVATION ... 118 0.39 1.61 0.001 0.11 0.998 1631 GNB1 FIGF P2RY1 GNG11 Details ITGA3 ITGA6 CAV1 ITGB1 SLC3A2 30 REACTOME_BASIGIN_INTERACTIONS ... 15 0.69 1.86 0.003 0.022 0.236 524 Details F2R PLAT TFPI COL4A5 COL4A2 COL4A6 COL4A1 31 BIOCARTA_AMI_PATHWAY ... 12 0.69 1.77 0.003 0.051 0.611 2799 FGG FGA Details CDKN2B CCND1 CCND2 CDKN1A 32 BIOCARTA_CELLCYCLE_PATHWAY ... 19 0.6 1.75 0.003 0.05 0.658 481 Details ACTN1 CAV1 ITGB1 MAP2K1 VCL ITGA1 PXN 33 BIOCARTA_INTEGRIN_PATHWAY ... 30 0.54 1.74 0.003 0.052 0.736 1791 BCAR1 ACTA1 Details FGF10 RPS3A RPL7A RPL13A AKT3 RPL30 HNF4A 34 REACTOME_REGULATION_OF_BETA_CELL_DEVELOPMENT ... 34 0.51 1.7 0.003 0.069 0.896 2762 FOXO1 NOTCH1 RPL24 RPS3A RPL7A SRP72 SPCS3 RPL13A RPL30 STX1A SRP14 SLC30A6 RPL18A CPE RPL36A SRP19 RPL21 RPL24 SEC61G RPS25 DDOST SEC11A RPL14 RPLP0 GNAI2 SSR2 SSR3 RPL29 Details RPL4 RPS27A RPS3 SRPRB SEC61A1 RPS15 35 REACTOME_INSULIN_SYNTHESIS_AND_SECRETION ... 57 0.45 1.65 0.003 0.083 0.976 5792 SEC61A2 FZD1 CCND1 SFRP2 CCND2 SMAD3 TCF7 FZD2 WNT10A NKD2 CUL1 LRP5 MYC WNT7A WNT5B NFATC4 ROCK2 CACYBP PRICKLE1 MAP3K7 NKD1 PLCB4 CSNK1E PPP2CA PLCB2 WNT5A PPP3R1 Details CAMK2D PPP3CA WNT9A SFRP1 PORCN WNT6 36 KEGG_WNT_SIGNALING_PATHWAY ... 97 0.39 1.55 0.003 0.145 1 3085 PPP2CB AXIN2 FZD7 SFRP4 Details IGF1R NGFR ITGB1 PDGFRA MAP2K1 37 BIOCARTA_ERK_PATHWAY ... 20 0.59 1.77 0.004 0.054 0.609 1802 Details CCT2 TUBA1A CCT8 CCT5 CCT7 TCP1 CCT6A 38 REACTOME_FORMATION_OF_TUBULIN_FOLDING_INTERMEDIATES_BY_CCT_TRIC ... 15 0.63 1.74 0.004 0.052 0.719 2204 TUBB6 TUBB2B Details F2R SERPING1 KNG1 COL4A5 COL4A2 COL4A6 39 BIOCARTA_INTRINSIC_PATHWAY ... 12 0.66 1.68 0.004 0.079 0.941 2799 COL4A1 FGG FGA.
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  • Defining Functional Interactions During Biogenesis of Epithelial Junctions

    Defining Functional Interactions During Biogenesis of Epithelial Junctions

    ARTICLE Received 11 Dec 2015 | Accepted 13 Oct 2016 | Published 6 Dec 2016 | Updated 5 Jan 2017 DOI: 10.1038/ncomms13542 OPEN Defining functional interactions during biogenesis of epithelial junctions J.C. Erasmus1,*, S. Bruche1,*,w, L. Pizarro1,2,*, N. Maimari1,3,*, T. Poggioli1,w, C. Tomlinson4,J.Lees5, I. Zalivina1,w, A. Wheeler1,w, A. Alberts6, A. Russo2 & V.M.M. Braga1 In spite of extensive recent progress, a comprehensive understanding of how actin cytoskeleton remodelling supports stable junctions remains to be established. Here we design a platform that integrates actin functions with optimized phenotypic clustering and identify new cytoskeletal proteins, their functional hierarchy and pathways that modulate E-cadherin adhesion. Depletion of EEF1A, an actin bundling protein, increases E-cadherin levels at junctions without a corresponding reinforcement of cell–cell contacts. This unexpected result reflects a more dynamic and mobile junctional actin in EEF1A-depleted cells. A partner for EEF1A in cadherin contact maintenance is the formin DIAPH2, which interacts with EEF1A. In contrast, depletion of either the endocytic regulator TRIP10 or the Rho GTPase activator VAV2 reduces E-cadherin levels at junctions. TRIP10 binds to and requires VAV2 function for its junctional localization. Overall, we present new conceptual insights on junction stabilization, which integrate known and novel pathways with impact for epithelial morphogenesis, homeostasis and diseases. 1 National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. 2 Computing Department, Imperial College London, London SW7 2AZ, UK. 3 Bioengineering Department, Faculty of Engineering, Imperial College London, London SW7 2AZ, UK. 4 Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK.
  • Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins

    Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins

    International Journal of Molecular Sciences Article Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins M. Quadir Siddiqui 1,† , Maulik D. Badmalia 1,† and Trushar R. Patel 1,2,3,* 1 Alberta RNA Research and Training Institute, Department of Chemistry and Biochemistry, University of Lethbridge, 4401 University Drive, Lethbridge, AB T1K 3M4, Canada; [email protected] (M.Q.S.); [email protected] (M.D.B.) 2 Department of Microbiology, Immunology and Infectious Disease, Cumming School of Medicine, University of Calgary, 3330 Hospital Drive, Calgary, AB T2N 4N1, Canada 3 Li Ka Shing Institute of Virology, University of Alberta, Edmonton, AB T6G 2E1, Canada * Correspondence: [email protected] † These authors contributed equally to the work. Abstract: Members of the human Zyxin family are LIM domain-containing proteins that perform critical cellular functions and are indispensable for cellular integrity. Despite their importance, not much is known about their structure, functions, interactions and dynamics. To provide insights into these, we used a set of in-silico tools and databases and analyzed their amino acid sequence, phylogeny, post-translational modifications, structure-dynamics, molecular interactions, and func- tions. Our analysis revealed that zyxin members are ohnologs. Presence of a conserved nuclear export signal composed of LxxLxL/LxxxLxL consensus sequence, as well as a possible nuclear localization signal, suggesting that Zyxin family members may have nuclear and cytoplasmic roles. The molecular modeling and structural analysis indicated that Zyxin family LIM domains share Citation: Siddiqui, M.Q.; Badmalia, similarities with transcriptional regulators and have positively charged electrostatic patches, which M.D.; Patel, T.R.
  • Human Periprostatic Adipose Tissue: Secretome from Patients With

    Human Periprostatic Adipose Tissue: Secretome from Patients With

    CANCER GENOMICS & PROTEOMICS 16 : 29-58 (2019) doi:10.21873/cgp.20110 Human Periprostatic Adipose Tissue: Secretome from Patients With Prostate Cancer or Benign Prostate Hyperplasia PAULA ALEJANDRA SACCA 1, OSVALDO NÉSTOR MAZZA 2, CARLOS SCORTICATI 2, GONZALO VITAGLIANO 3, GABRIEL CASAS 4 and JUAN CARLOS CALVO 1,5 1Institute of Biology and Experimental Medicine (IBYME), CONICET, Buenos Aires, Argentina; 2Department of Urology, School of Medicine, University of Buenos Aires, Clínical Hospital “José de San Martín”, Buenos Aires, Argentina; 3Department of Urology, Deutsches Hospital, Buenos Aires, Argentina; 4Department of Pathology, Deutsches Hospital, Buenos Aires, Argentina; 5Department of Biological Chemistry, School of Exact and Natural Sciences, University of Buenos Aires, Buenos Aires, Argentina Abstract. Background/Aim: Periprostatic adipose tissue Prostate cancer (PCa) is the second most common cancer in (PPAT) directs tumour behaviour. Microenvironment secretome men worldwide. While most men have indolent disease, provides information related to its biology. This study was which can be treated properly, the problem consists in performed to identify secreted proteins by PPAT, from both reliably distinguishing between indolent and aggressive prostate cancer and benign prostate hyperplasia (BPH) disease. Evidence shows that the microenvironment affects patients. Patients and Methods: Liquid chromatography-mass tumour behavior. spectrometry-based proteomic analysis was performed in Adipose tissue microenvironment is now known to direct PPAT-conditioned media (CM) from patients with prostate tumour growth, invasion and metastases (1, 2). Adipose cancer (CMs-T) (stage T3: CM-T3, stage T2: CM-T2) or tissue is adjacent to the prostate gland and the site of benign disease (CM-BPH). Results: The highest number and invasion of PCa.
  • Circular RNA Hsa Circ 0005114‑Mir‑142‑3P/Mir‑590‑5P‑ Adenomatous

    Circular RNA Hsa Circ 0005114‑Mir‑142‑3P/Mir‑590‑5P‑ Adenomatous

    ONCOLOGY LETTERS 21: 58, 2021 Circular RNA hsa_circ_0005114‑miR‑142‑3p/miR‑590‑5p‑ adenomatous polyposis coli protein axis as a potential target for treatment of glioma BO WEI1*, LE WANG2* and JINGWEI ZHAO1 1Department of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033; 2Department of Ophthalmology, The First Hospital of Jilin University, Jilin University, Changchun, Jilin 130021, P.R. China Received September 12, 2019; Accepted October 22, 2020 DOI: 10.3892/ol.2020.12320 Abstract. Glioma is the most common type of brain tumor APC expression with a good overall survival rate. UALCAN and is associated with a high mortality rate. Despite recent analysis using TCGA data of glioblastoma multiforme and the advances in treatment options, the overall prognosis in patients GSE25632 and GSE103229 microarray datasets showed that with glioma remains poor. Studies have suggested that circular hsa‑miR‑142‑3p/hsa‑miR‑590‑5p was upregulated and APC (circ)RNAs serve important roles in the development and was downregulated. Thus, hsa‑miR‑142‑3p/hsa‑miR‑590‑5p‑ progression of glioma and may have potential as therapeutic APC‑related circ/ceRNA axes may be important in glioma, targets. However, the expression profiles of circRNAs and their and hsa_circ_0005114 interacted with both of these miRNAs. functions in glioma have rarely been studied. The present study Functional analysis showed that hsa_circ_0005114 was aimed to screen differentially expressed circRNAs (DECs) involved in insulin secretion, while APC was associated with between glioma and normal brain tissues using sequencing the Wnt signaling pathway. In conclusion, hsa_circ_0005114‑ data collected from the Gene Expression Omnibus database miR‑142‑3p/miR‑590‑5p‑APC ceRNA axes may be potential (GSE86202 and GSE92322 datasets) and explain their mecha‑ targets for the treatment of glioma.
  • RESEARCH ARTICLE Body Weight-Dependent Troponin T Alternative Splicing Is Evolutionarily Conserved from Insects to Mammals and I

    RESEARCH ARTICLE Body Weight-Dependent Troponin T Alternative Splicing Is Evolutionarily Conserved from Insects to Mammals and I

    1523 The Journal of Experimental Biology 214, 1523-1532 © 2011. Published by The Company of Biologists Ltd doi:10.1242/jeb.051763 RESEARCH ARTICLE Body weight-dependent troponin T alternative splicing is evolutionarily conserved from insects to mammals and is partially impaired in skeletal muscle of obese rats Rudolf J. Schilder1,*, Scot R. Kimball1, James H. Marden2 and Leonard S. Jefferson1 1Department of Cellular and Molecular Physiology, The Pennsylvania State University College of Medicine, 500 University Drive, Hershey, PA 17033, USA and 2Department of Biology, The Pennsylvania State University, 208 Mueller Lab, University Park, PA 16802, USA *Author for correspondence ([email protected]) Accepted 19 January 2011 SUMMARY Do animals know at a physiological level how much they weigh, and, if so, do they make homeostatic adjustments in response to changes in body weight? Skeletal muscle is a likely tissue for such plasticity, as weight-bearing muscles receive mechanical feedback regarding body weight and consume ATP in order to generate forces sufficient to counteract gravity. Using rats, we examined how variation in body weight affected alternative splicing of fast skeletal muscle troponin T (Tnnt3), a component of the thin filament that regulates the actin–myosin interaction during contraction and modulates force output. In response to normal growth and experimental body weight increases, alternative splicing of Tnnt3 in rat gastrocnemius muscle was adjusted in a quantitative fashion. The response depended on weight per se, as externally attached loads had the same effect as an equal change in actual body weight. Examining the association between Tnnt3 alternative splicing and ATP consumption rate, we found that the Tnnt3 splice form profile had a significant association with nocturnal energy expenditure, independently of effects of weight.