2 Theory and methodology
2.2 Valuation models
O estudo da expressão gênica global de animais fenotipicamente divergentes para maciez da carne revelou genes relacionados ao metabolismo das ubiquitinas, transporte de moléculas como o cálcio e o oxigênio, equilíbrio ácido-base, produção de colágeno, actina e miosina e acumulo de gordura. Esses resultados contribuem para o entendimento dos mecanismos moleculares envolvidos no processo de amaciamento da carne e para o desenvolvimento de estratégias para a seleção de animais com carne mais macia.
6. Referências
ABIEC, Associação Brasileira das Indústrias Exportadoras de Carne. Disponível em: <http://www.abiec.com.br/>. Acessado em 08 de fevereiro de 2016.
BAILEY, A.J.; PAUL, R.G., KNOTT; L. KNOTT. Mechanisms of maturation and aging of collagen. Mechanism of Aging and Development, v. 106, pp. 1–56, 1998.
BATE-SMITH, E.C; BENDALL, J.R. Factors determining the time course of rigor mortis. The Journal of Physiology, London, v. 110, p.47-65, 1949.
BATRA, T.R.; LEE, A.J.; GAVORA, J.S.; STEAR, M.J. CLASS I alleles of the bovine major histocompatibility system and their association with economic traits.
Journal Dairy Science, v. 72, p. 2115–2124, 1989.
BENDALL, J.R. Posmortem changes in muscle. In: BOURNE, G.H. (Ed.) The structure and function of muscle. Academic Press: New York, v.2, p.244-309, 1973.
BINDEA G, MLECNIK B, HACKL H, CHAROENTONG P, TOSOLINI M. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics. v. 25, n. 8, p. 1091-1093, 2009. BONGIORNI, S.; GRUBER, C. E. M.; BUENO, S.; CHILLEMI. G.; FERR, F.; FAILLA,S.; MOIOLI, B.; VALENTINI, A. Transcriptomic investigation of meat tenderness in two Italian cattle breeds. Animal Genetics, DOI: 10.1111/age.12418.
BULFONEA, A.; CACCIOPPOLIB, C.; PARDINIA, C.; FAEDOA, A.; MARTINEZ, S; BANFIB, S. Pcp4l1, a novel gene encoding a Pcp4-like polypeptide, is expressed in specific domains of the developing brain. Gene Expression
Patterns, v. 4, p.297–301, 2004.
CAMPO, M. M; SAÑUDO, C.; PANEA, B.; ALBERTI, P.; SANTOLARIA, P. Breed type and aging time effects on sensory characteristics of beef strip loin steaks.
Meat Science, v. 51, p. 383-391, 1999.
CARBON, S.; IRELAND, A.; MUNGALL, C.J.; SHU, S.; MARSHALL, B.; LEWIS, S. AmiGO: online access to ontology and annotation data. Bioinformatics, v.25, n.2, p.288–289, 2009.
CHAPPLE, R.H.; TIZIOTO, P.C.; WELLS, K.D. Characterization of the rat developmental liver transcriptome. Physiological Genomics, v.45, n.8, p.301- 311, 2013.
CRC: cooperative Resersh Centre for Beef Genetic Technologies. Annual Report of CRC for Beef Genetics Tecnologies. High Quality beef for Global Consumers. Armidale, Australia, 2008.
CummeRbund – Manual: Exploration, analysis and visualization of Cufflinks high-
http://compbio.mit.edu/cummeRbund/manual_2_0.html >. Acessado em 12/08/2015.
DARREL, E.; GOLL, D.E.; VALERY, F.; THOMPSON, V.F.; HONGOI LI.; WEI WEI., JINYANG CONG. The calpain system. Physiological Reviews, v.83, p.731-801, 2003.
DE ROBERTIS, Eduardo M.F., Hib, José. Bases da Biologia Celular e Molecular. Editora Guanabara Koogan. Rio de Janeiro, 2010.
DRICKAMER, K. C-type lectin-like domains". Current Opinion in Structural
Biology, n.9, p.5, n.585–90, 1999.
DUSTON, T.R.; HOSTETLER, R.L.; CARPENTER, Z.L. Effect of collagen levels and sarcomere shortening on muscle tenderness. Journal of Food Science, v.41, n.4, p.863-866, 1976.
EXPRESSION SUITE SOFTWARE v 1.0.3 - MANUAL; Expression Suite Software Versionv.1.0, Life Technologies Corporation, Carlsbad, CA, USA, 2012. Disponível em: <http://www.invitrogen.com/site/us/en/home/Global/forms/expres sion.suitesoftware-registration.html>. Acessado em 13 de fevereiro de 2016. FERGUSON, D. M. et al. Effect of electrical stimulation on protease activity and tenderness of M. longissimus from cattle with different proportions of Bos indicus content. Meat Science, v. 55, n. 3, p. 265–72, 2000.
FOX, C.S.; LIU, Y.; WHITE, C.C.; FEITOSA, M.; SMITH, A.V.; et al. Genome- Wide Association for Abdominal Subcutaneous and Visceral Adipose Reveals a Novel Locus for Visceral Fat in Women. PLoS Genetics, v.8, n.5, 2012.
GOFF, S. A.; VAUGHN, M.; McKAY, S. et al. The iPlant collaborative: cyberinfrastructure for plant biology. Frontiers in Plant Science, v. 2, n. 34, 2011.
GONÇALVES, T. M. Differential expression of genes related with meat tenderness in Nellore Cattle. Dissertação, ESALQ, USP, 97p, 2015.
HUANG, W.; SHERMAN, B. T.; LEMPICK, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature
Protocols, v.4, p.44 – 57, 2009.
ISHIHARA, Y. M.; MADRUGA, M. S. Indicadores de maciez em carnes salgadas e dessecadas: uma revisão. Semina: Ciências Agrárias, Londrina, v. 34, n. 6, suplemento 2, p. 3721-3738, 2013.
JONG, O. G.; BALKOM, B.W.M; GREMMELS, H.; VERHAAR, M.C. Exosomes from hypoxic endothelial cells have increased collagen crosslinking activity through up-regulation of lysyl oxidase-like 2. Journal of cellular and molecular
medicine, v. XX, n.X, p. 1-9, 2015.
JUNQUEIRA, L. C.U.; CARNEIRO, J. Biologia Celular e Molecular. 8a edição. Editora Guanabara Koogan.Rio de Janeiro, 2005, 340 p.
KANEHISA, M.; GOTO, S. KEGG: Kyoto Encyclopedia of Genes and Genomes.
Nucleic Acids Research, v.28, p.27-30, 2000.
KANEHISA, M.; SATO, Y.; KAWASHIMA, M.; FURUMICHI, M.; TANABE, M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids
Research, v.44, p.D457-D462, 2016.
KLEIN, J.; BONTROP, R.E.; DAWKINS, R.L.; ERLICH, H.A.; GYLLENSTEN, U.B., HEISE, E.R.; JONES, P.P.; PARHAM, P.; WAKELAND, E.K.; WATKINS, D.I. Nomenclature for the major histocompatibility complexes of different species: a proposal. Immunogenetics, n.31, v. 4, p.217-219, 1990.
KOOHMARAIE, M. The biological basis of meat tenderness and potential genetic approaches for its control and prediction. Proceedings of the Reciprocal Meat
Conference, v.48, p.69-75, 1995.
KOOHMARAIE, M. Biochemical factors regulating the toughening and tenderization process of meat. Meat Science, v.43, n.S, p.S193-S201, 1996. KOOHMARAIE, M.; KENT, M.P.; SHACKELFORD, S.D.; VEISETH, E.; WHEELER, T.L. Meat tenderness and muscle growth: is there any relationship?
Meat Science, v. 62, n. 3, p345-52, 2002.
LAMP: Library of Apicomplexan Metabolic Pathways. Nicotinate and nicotinamide metabolism.<http://www.llamp.net/?q=Nicotinate%20metabolism> acessado em 29 de dezembro de 2015.
LEE, N.P.; TONG, M.K.; LEUNG, P.P. Kidney claudin-19: localization in distal tubules and collecting ducts and dysregulation in polycystic renal disease. FEBS
Letters. v. 580, n. 3, p.923–31, 2006.
LEHNINGER, A. L.; NELSON, L. D.; COX, M. M. Princípios de bioquímica. 3 ed., São Paulo: SARVIER, 2002, 1009p.
LIVAK, K.J.; SCHMITTGEN, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods, v.25, p.402-408, 2001.
LUCKI, N.C.; SEWER, M.B. Genistein stimulates MCF-7 breast cancer cell growth by inducing acid ceramidase (ASAH1) gene expression. The Journal of
Biological Chemistry, v. 286, n. 22, p. 19399-19409, 2011.
MAGALHÃES, A. F. B. Utilização de informações genômicas para o melhoramento genético de características da carne em bovinos da raça Nelore. Tese, FCAV, UNESP, 60p, 2015.
MALONE, J. H.; OLIVER, B. Microarrays, deep sequencing and the true measure of the transcriptome. BMC Biology, v.9, n. 34, 2011.
MANSO, C. M. C. P. ; NERI, C. R. ; VIDOTO, E. A. ; SACCO, H. C. ; CIUFFI, K. J. ; IWAMOTO, L. S. ; IAMAMOTO, Y ; NASCIMENTO, O. R. ; SERRA, O A . Characterization of iron(III) porphyrin-hidroxo complexes in organic media through Uv-Vis and EPR spectroscopies. Journal of Inorganic Biochemistry, v. 73, p. 85-93, 1999.
OTTERBEIN, L.E.; SOARES, M.P.; YAMASHITA, K.; BACH, F.H. Heme oxygenase-1: unleashing the protective properties of heme. Trends in
Immunology, v. 24, p.449–455, 2003.
OUALI, A.; GAGAOUA, M.; BOUDIDA, Y.; BECILA, S.; BOUDJELLAL, A.; HERRERA-MENDEZ, C.H.; SENTANDREU, M.A. Biomarkers of meat tenderness: presente knowledge and perspectives in regards to our current understanding of the mechanisms involved. Meat Science, v.95, n.4, p.854-870, 2013.
PARK, J.H.; SCHUCHMAN, E.H. Acid ceramidase and human disease.
Biochimica et Biophysica Acta, v. 1758, p. 2133–2138, 2006.
PIORKOWSKA, K.; ŻUKOWSKI, K.; NOWAK, J.; POŁTOWICZ, K.; ROPKA- MOLIK, K.; GURGUL, A. Genome-wide RNA-Seq analysis of breast muscles of two broiler chicken groups differing in shear force. Animal Genetics, v.47, n.1, p. 68-80, 2015.
RHOADS, A.R.; FRIEDBERG, F. Sequence motifs for calmodulin recognition.
FASEB Journal: Official Publication of the Federation of American Societies for Experimental Biology, v.11, n.(5), p.331-340, 1997.
RINGNÉR, M. What is principal component analysis? Nature Biotechnology, v. 26, n. 3, p. 303–4, 2008.
RUBENSAM, J.M. TRANSFORMAÇÕES POST MORTEM E QUALIDADE DA CARNE SUÍNA. 1ª Conferência Internacional Virtual sobre Qualidade de Carne Suína. 16 de novembro a 16 de dezembro de 2000, Concórdia, SC. <http://www.cnpsa.embrapa.br/sgc/sgc_publicacoes/anais00cv_jane_pt.pdf> acessado em 30/12/2015.
RUBENSTEIN, J.L.; GREENGARD, P.; CZERNIK, A.J. Calcium-dependent serine phosphorylation of synaptophysin. Synapse, v.13, n.2, p.161-172, 1993. SANDER, T. L.; Stringer, K. F.; Maki, J. L.; Szauter, P.; Stone, J.R., Collins, T. The SCAN domain defines a large family of zinc finger transcription factors.
Gene, v. 310, p. 29 – 38, 2003.
SCOLLAN, N. HOCQUETTE, J. NUERNBERG, K. DANNENBERGER, D. IAN, R. MOLONEY, A. Innovations in beef production systems that enhance the nutritional and health value of beef lipids and their relationship with meat quality.
Meat Science, v. 74 p. 17–33. 2006.
SEKIKAWA, M.; SENO, K.; MIKAMI, M. Degradation of Ubiquitin in beef during storage. Meat Science, v.48, p. 201-204, 1998.
SGARBIERI, V.C. Proteínas em alimentos protéicos. São Paulo, SP: Varela, 1996, 517 p.
STEAR, M.J.; POKORNY, T.S.; MUGGLI, N.E.; STONE, R.T. The relationships of birth weight, preweaning gain and postweaning gain with the bovine major histocompatibility system. Journal of Animal Science, v. 67, p. 641–649, 1989. THIRKILDSEN, M.; MELCHIOR LARSEN, L.; BANG, H.G.; VESTERGAARD, M. effect of growth rate on tenderness rate on tenderness development and final
tenderness of meat from Friesian calves. Journal of Animal Science, v.74, p.253-264, 2002.
TIZIOTO, P. C; DECKER, J. E; TAYLOR, J. F; SCHNABEL, R. D.; MUDADU, M. A.; SILVA, F. L. MOURÃO, G. B. COUTINHO, L. L. THOLON, P; SONSTEGARD, T. S.; ROSA, A. N.; ALENCAR, M. M. TULLIO, R. R. MEDEIROS, S. R.; NASSU, R. T.; FEIJÓ, G. L. D.; SILVA, L. O. C.; TORRES, R. A. SIQUEIRA, F. HIGA, R. H.; REGITANO, L. C. A. Genome scan for meat quality traits in Nelore beef cattle. Physiological Genomics, v.45. p.1012-1020, 2013.
TIZIOTO, P.C.; COUTINHO, L.L.; DECKER, J. E.; SCHNABEL, R. D.; ROSA, K.O.; OLIVEIRA, P.S.N.; SOUZA, M.M.; MOURÃO, G.B.; TULLIO, R.R.; CHAVES, A.S.; LANNAD.P.D.; ZERLOTINI-NETO, A.; MUDADU, M.A.; TAYLOR, J.F.; REGITANO, L.C.A. Global liver gene expression differences in Nelore steers with divergent residual feed intake phenotypes. BMC Genomics, v.16, p. 216, 2015.
TRAPNELL C, PACHTER L, SALZBERG SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics.v.25, n.9, p.1105–1111, 2009.
TRAPNELL C, ROBERTS A, GOFF L, PERTEA G, KIM D, KELLEY DR. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nature Protocols.v.7, n.3, p.562–78, 2012.
TRAPNELL C, HENDRICKSON DG, SAUVAGEAU M, GOFF L, RINN JL, PACTHER L. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nature Biotechnology, v.31, p.:46–53, 2013.
VANDESOMPELE, J.; DE PRETER, K.; PATTYN, F.; POPPE, B.; VAN ROY, N.; DE PAEPE, A.; SPELEMAN, F. Accurate normalization of real-time quantitative
RT-PCR data by geometric averaging of multiple internal control genes. Genome
Biology, 2002.
WANG, Z.; GERSTEIN, M.; SNYDER, M. RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics. Advance Online Plublication, 2008. WHEELER, T.L. Meat tenderness and muscle growth: is there any relationship?
Meat Science, v. 62, n. 3, p345-52, 2002.
ZHAO, C.; TIAN, F.; YU, Y.; LIU, G.; ZAN, L.; SCOTT, M.; SONG, J. miRNA- dysregulation associated with tenderness variation induced by acute stress in Angus cattle. Journal of Animal Science and Biotechnology, v.3, n. 12, 2012. ZHONG-LIANG, H.U.; XING J. L., XIAO-FENG, Y.E. Effects of Angiotensin II on Beef Quality. Acta Agriculturae Jiangxi, v.11, 2009.
Anexo 1: Categorias Funcionais (“Annotation Clusters”) dos genes diferencialmente expressos para maciez da carne.
Annotation
Cluster 1 Enrichment Score: 1.4008439340240422
Category Term Count % PValue Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR
GOTERM_
CC_FAT GO:0005624~membrane fraction 3 20.0 0.016264529520811248 SYP, HMOX1, CTNNB1 8 204 6966 12.805.147.058.823.500 0.7518820783348589 0.5018856339502532 16.173.778.319.889.400 GOTERM_
CC_FAT GO:0005626~insoluble fraction 3 20.0 0.017500654972065547 SYP, HMOX1, CTNNB1 8 212 6966 1.232.193.396.226.410 0.7770318091356184 0.3936161351995756 17.300.103.870.681.800 GOTERM_
CC_FAT GO:0000267~cell fraction 3 20.0 0.021619449009001507 SYP, HMOX1, CTNNB1 8 237 6966 11.022.151.898.734.100 0.8439858734537067 0.3715206957307683 20.954.689.933.459.800 GOTERM_
CC_1 GO:0043226~organelle 6 40.0
0.405026868
97787354 SYP, HMOX1, EXOSC2, TCF7L1, ASAH1, CTNNB1 10
440 5 9553 13.012.031.7 82.065.800 0.98429713 75127357 0.98429713 75127357 9.417.264.31 5.823.240 Annotation
Cluster 2 Enrichment Score: 1.085335395710343
Category Term Count % PValue Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR
SP_PIR_KE
YWORDS cell junction 3 20.0
0.006910937 590713447 SYP, CLDN19, CTNNB1 8 138 7349 19.970.108.6 95.652.100 0.25268388 66234652 0.25268388 66234652 6.216.630.58 0.377.850 GOTERM_
CC_FAT GO:0030054~cell junction 3 20.0 0.01596182191159523 SYP, CLDN19, CTNNB1 8 202 6966 12.931.930.693.069.300 0.745307826057144 0.745307826057144 15.895.846.648.039.400 GOTERM_
CC_FAT GO:0044459~plasma membrane part 4 26.666.666.666.666.600 0.02747734462734352 SYP, CLDN19, BOLA-DQB, CTNNB1 8 715 6966 4.871.328.671.328.670 0.9063566778007617 0.3772763460484262 25.900.301.404.640.800 GOTERM_
CC_FAT GO:0005886~plasma membrane 4 26.666.666.666.666.600 0.10078699314177889 SYP, CLDN19, BOLA-DQB, CTNNB1 8 1186 6966 2.936.762.225.969.640 0.9998802379232556 0.7779828348314323 6.811.253.512.256.820 SP_PIR_KE
YWORDS Transmembrane 4 26.666.666.666.666.600 0.18972013834815435 SYP, AGTR2, CLDN19, BOLA-DQB 8 1639 7349 2.241.915.802.318.480 0.9998545640066901 0.9879403153727023 8.573.016.531.225.270 GOTERM_
CC_FAT GO:0016021~integral to membrane 4 26.666.666.666.666.600 0.6467928569950351 SYP, AGTR2, CLDN19, BOLA-DQB 8 3006 6966 11.586.826.347.305.300 1.0 0.9999967507246433 9.999.862.794.496.080 GOTERM_
CC_FAT GO:0031224~intrinsic to membrane 4 26.666.666.666.666.600 0.6741785034391582 SYP, AGTR2, CLDN19, BOLA-DQB 8 3101 6966 11.231.860.690.099.900 1.0 0.9999933102532798 9.999.942.418.784.120
Annotation
Cluster 3 Enrichment Score: 0.8006912969665784
Category Term Count % PValue Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR
GOTERM_B
P_ALL GO:0009966~regulation of signal transduction 3 20.0 0.035341438541226226 AGTR2, HMOX1, CTNNB1 8 417 9430 848.021.582.733.813 0.9999985686856404 0.9999985686856404 39.161.988.578.188.700 GOTERM_B
P_ALL GO:0010646~regulation of cell communication 3 20.0 0.04235692167562698 AGTR2, HMOX1, CTNNB1 8 460 9430 76.875 0.9999999066371547 0.9996944466570321 4.499.616.153.916.370 GOTERM_B
P_ALL GO:0065008~regulation of biological quality 3 20.0 0.07562058953367994 AGTR2, HMOX1, CTNNB1 8 634 9430 5.577.681.388.012.610 0.9999999999998309 0.9993587909612914 6.624.500.049.564.770 GOTERM_B
P_ALL GO:0048522~positive regulation of cellular process 3 20.0 0.08293091312546627 AGTR2, HMOX1, CTNNB1 8 668 9430 5.293.787.425.149.700 0.9999999999999913 0.9954669061176425 6.975.087.056.270.650 GOTERM_B
GOTERM_B
P_ALL GO:0050794~regulation of cellular process 3 20.0 0.6963258171860183 AGTR2, HMOX1, CTNNB1 8 2946 9430 1.200.356.415.478.610 1.0 1.0 9.999.999.290.040.200 GOTERM_B
P_ALL GO:0050789~regulation of biological process 3 20.0 0.7339112389224045 AGTR2, HMOX1, CTNNB1 8 3129 9430 11.301.534.036.433.300 1.0 1.0 9.999.999.885.526.050 GOTERM_B
P_ALL GO:0065007~biological regulation 3 20.0 0.776548328457862 AGTR2, HMOX1, CTNNB1 8 3358 9430 1.053.082.191.780.820 1.0 1.0 9.999.999.989.738.850
Annotation Cluster 4
Enrichment Score:
0.45045506452655387
Category Term Count % PValue Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR
GOTERM_B
P_ALL GO:0034641~cellular nitrogen compound metabolic process 4 26.666.666.666.666.600 0.07428280384430033 HMOX1, EXOSC2, DMGDH, CTNNB1 8 1419 9430 33.227.625.088.090.200 0.9999999999997097 0.9999337836406873 6.556.399.867.271.640 GOTERM_B
P_ALL GO:0006807~nitrogen compound metabolic process 4 26.666.666.666.666.600 0.08127100234637105 HMOX1, EXOSC2, DMGDH, CTNNB1 8 1471 9430 3.205.302.515.295.710 0.9999999999999829 0.998236321886345 6.898.583.583.537.170 GOTERM_B
P_ALL GO:0008152~metabolic process 5 3.333.333.333.333.330 0.417405001426098 HMOX1, EXOSC2, DMGDH, ASAH1, CTNNB1 8 4357 9430 13.527.082.855.175.500 1.0 0.9999999999892627 9.994.254.291.336.850 GOTERM_B
P_ALL GO:0044237~cellular metabolic process 4 26.666.666.666.666.600 0.48122689784003614 HMOX1, EXOSC2, DMGDH, CTNNB1 8 3356 9430 14.049.463.647.199.000 1.0 0.9999999999985687 999.884.285.544.254 GOTERM_B
P_ALL GO:0044238~primary metabolic process 4 26.666.666.666.666.600 0.5486139423583953 EXOSC2, DMGDH, ASAH1, CTNNB1 8 3637 9430 12.963.981.303.271.900 1.0 0.9999999999998798 9.999.830.658.564.870 GOTERM_
MF_1 GO:0003824~catalytic activity 4 26.666.666.666.666.600 0.651651623213489 HMOX1, EXOSC2, DMGDH, ASAH1 10 3854 11163 11.585.884.795.018.100 0.9982131720094433 0.9982131720094433 9.935.711.099.739.390 GOTERM_
MF_ALL GO:0003824~catalytic activity 4 26.666.666.666.666.600 0.651651623213489 HMOX1, EXOSC2, DMGDH, ASAH1 10 3854 11163 11.585.884.795.018.100 1.0 0.9999999999999818 9.999.742.831.794.870 GOTERM_B
P_ALL GO:0009987~cellular process 4 26.666.666.666.666.600 0.881719069950273 HMOX1, EXOSC2, DMGDH, CTNNB1 8 5457 9430 0.8640278541323072 1.0 1.0 9.999.999.999.998.430
Annotation
Cluster 5 Enrichment Score: 0.3171755306274035
Category Term Count % PValue Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR
GOTERM_
CC_1 GO:0043226~organelle 6 40.0 0.40502686897787354 SYP, HMOX1, EXOSC2, TCF7L1, ASAH1, CTNNB1 10 4405 9553 13.012.031.782.065.800 0.9842971375127357 0.9842971375127357 9.417.264.315.823.240 GOTERM_
CC_1 GO:0044464~cell part 10 6.666.666.666.666.660 0.5254057080624969 SYP, AGTR2, CLDN19, HMOX1, EXOSC2, DMGDH, BOLA-DQB, TCF7L1, ASAH1, CTNNB1 10 8894 9553 10.740.948.954.351.200 0.9974261686620745 0.8629559993939919 9.830.953.074.631.170 GOTERM_
CC_1 GO:0005623~cell 10 6.666.666.666.666.660 0.5254057080624969 SYP, AGTR2, CLDN19, HMOX1, EXOSC2, DMGDH, BOLA-DQB, TCF7L1, ASAH1, CTNNB1 10 8894 9553 10.740.948.954.351.200 0.9974261686620745 0.8629559993939919 9.830.953.074.631.170
Annotation Cluster 6
Enrichment Score:
0.2893368552145528
Category Term Count % PValue Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR
GOTERM_
CC_1 GO:0043226~organelle 6 40.0 0.40502686897787354 SYP, HMOX1, EXOSC2, TCF7L1, ASAH1, CTNNB1 10 4405 9553 13.012.031.782.065.800 0.9842971375127357 0.9842971375127357 9.417.264.315.823.240 GOTERM_
CC_1 GO:0044422~organelle part 3 20.0 0.5415822564156612 SYP, EXOSC2, CTNNB1 10 1841 9553 1.556.708.310.700.700 0.998049745210165 0.7898531723670433 9.860.184.800.595.410 SP_PIR_KE
Annotation
Cluster 7 Enrichment Score: 0.20835978753466686
Category Term Count % PValue Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR
GOTERM_
CC_1 GO:0043226~organelle 6 40.0 0.40502686897787354 SYP, HMOX1, EXOSC2, TCF7L1, ASAH1, CTNNB1 10 4405 9553 13.012.031.782.065.800 0.9842971375127357 0.9842971375127357 9.417.264.315.823.240 GOTERM_ MF_1 GO:0005488~binding 7 46.666.666.6 66.666.600 0.765100351 2343213
SYP, AGTR2, CLEC12A, HMOX1, EXOSC2,
TCF7L1, CTNNB1 10 799 1 1116 3 0.977862595 4198472 0.99983200 58323299 0.98703874 35921457 9.990.247.34 9.254.470 GOTERM_