The relationships among MicroRNA regulation, intrinsically disordered regions, and other indicators of protein evolutionary rate

TY - JOUR

T1 - The relationships among MicroRNA regulation, intrinsically disordered regions, and other indicators of protein evolutionary rate

AU - Chen, Chun-Chang

AU - Chuang, Trees-Juen

AU - Li, Wen-Hsiung

N1 - 被引用次數：15 Export Date: 21 March 2016 CODEN: MBEVE 通訊地址: Li, W.-H.; Biodiversity Research Center, Academia Sinica, Taipei 115, Taiwan; 電子郵件： whli@sinica.edu.tw 化學物質/CAS: MicroRNAs; Proteins 參考文獻: Bloom, J.D., Adami, C., Evolutionary rate depends on number of protein-protein interactions independently of gene expression level: Response (2004) BMC Evol Biol, 4, p. 14; Bossi, A., Lehner, B., Tissue specificity and the human protein interaction network (2009) Mol Syst Biol, 5, p. 260; Brown, C.J., Johnson, A.K., Daughdrill, G.W., Comparing models of evolution for ordered and disordered proteins (2010) Mol Biol Evol, 27, pp. 609-621; Brown, C.J., Takayama, S., Campen, A.M., Vise, P., Marshall, T.W., Oldfield, C.J., Williams, C.J., Keith Dunker, A., Evolutionary rate heterogeneity in proteins with long disordered regions (2002) Journal of Molecular Evolution, 55 (1), pp. 104-110. , DOI 10.1007/s00239-001-2309-6; Chen, F.C., Chen, C.J., Li, W.H., Chuang, T.J., Gene family size conservation is a good indicator of evolutionary rates (2010) Mol Biol Evol, 27, pp. 1750-1758; Chen, F.C., Chuang, T.J., The effects of multiple features of alternatively spliced exons on the K(A)/K(S) ratio test (2006) BMC Bioinformatics, 7, p. 259; Chen, J., Liang, H., Fernandez, A., Protein structure protection commits gene expression patterns (2008) Genome Biol, 9, pp. R107; Chen, S.C., Chen, F.C., Li, W.H., Phosphorylated and non-phosphorylated serine and threonine residues evolve at different rates in mammals (2010) Mol Biol Evol, 27, pp. 2548-2554; Cheng, C., Bhardwaj, N., Gerstein, M., The relationship between the evolution of microRNA targets and the length of their UTRs (2009) BMC Genomics, 10, p. 431; Cohen, P., The regulation of protein function by multisite phosphorylation-a 25 year update (2000) Trends Biochem Sci, 25, pp. 596-601; Diella, F., Gould, C.M., Chica, C., Via, A., Gibson, T.J., Phospho.ELM: A database of phosphorylation sites - Update 2008 (2008) Nucleic Acids Research, 36 (SUPPL. 1), pp. D240-D244. , DOI 10.1093/nar/gkm772; Drummond, D.A., Bloom, J.D., Adami, C., Wilke, C.O., Arnold, F.H., Why highly expressed proteins evolve slowly (2005) Proceedings of the National Academy of Sciences of the United States of America, 102 (40), pp. 14338-14343. , DOI 10.1073/pnas.0504070102; Drummond, D.A., Wilke, C.O., Mistranslation-Induced Protein Misfolding as a Dominant Constraint on Coding-Sequence Evolution (2008) Cell, 134 (2), pp. 341-352. , DOI 10.1016/j.cell.2008.05.042, PII S0092867408007058; Edwards, Y.J., Lobley, A.E., Pentony, M.M., Jones, D.T., Insights into the regulation of intrinsically disordered proteins in the human proteome by analyzing sequence and gene expression data (2009) Genome Biol, 10, pp. R50; Fernandez, A., Chen, J., Human capacitance to dosage imbalance: Coping with inefficient selection (2009) Genome Res, 19, pp. 2185-2192; Fraser, H.B., Hirsh, A.E., Evolutionary rate depends on number of protein-protein interactions independently of gene expression level (2004) BMC Evol Biol, 4, p. 13; Fraser, H.B., Hirsh, A.E., Steinmetz, L.M., Scharfe, C., Feldman, M.W., Evolutionary rate in the protein interaction network (2002) Science, 296 (5568), pp. 750-752. , DOI 10.1126/science.1068696; Gromiha, M.M., Selvaraj, S., Importance of long-range interactions in protein folding (1999) Biophysical Chemistry, 77 (1), pp. 49-68. , DOI 10.1016/S0301-4622(99)00010-1, PII S0301462299000101; Gromiha, M.M., Selvaraj, S., Inter-residue interactions in protein folding and stability (2004) Progress in Biophysics and Molecular Biology, 86 (2), pp. 235-277. , DOI 10.1016/j.pbiomolbio.2003.09.003, PII S0079610703000816; Gsponer, J., Futschik, M.E., Teichmann, S.A., Babu, M.M., Tight regulation of unstructured proteins: From transcript synthesis to protein degradation (2008) Science, 322 (5906), pp. 1365-1368. , DOI 10.1126/science.1163581; Guo, H., Ingolia, N.T., Weissman, J.S., Bartel, D.P., Mammalian microRNAs predominantly act to decrease target mRNA levels (2010) Nature, 466, pp. 835-840; Haynes, C., Iakoucheva, L.M., Serine/arginine-rich splicing factors belong to a class of intrinsically disordered proteins (2006) Nucleic Acids Research, 34 (1), pp. 305-312. , DOI 10.1093/nar/gkj424; Haynes, C., Oldfield, C.J., Ji, F., Klitgord, N., Cusick, M.E., Radivojac, P., Uversky, V.N., Iakoucheva, L.M., Intrinsic disorder is a common feature of hub proteins from four eukaryotic interactomes (2006) PLoS Comput Biol, 2, pp. e100; He, X., Zhang, J., Toward a molecular understanding of pleiotropy (2006) Genetics, 173 (4), pp. 1885-1891. , http://www.genetics.org/cgi/reprint/173/4/1885, DOI 10.1534/genetics.106.060269; Iakoucheva, L.M., Radivojac, P., Brown, C.J., O'Connor, T.R., Sikes, J.G., Obradovic, Z., Dunker, A.K., The importance of intrinsic disorder for protein phosphorylation (2004) Nucleic Acids Research, 32 (3), pp. 1037-1049. , DOI 10.1093/nar/gkh253; Keshava Prasad, T.S., Goel, R., Kandasamy, K., Human Protein Reference Database-2009 update (2009) Nucleic Acids Res, 37, pp. D767-D772. , (30 co-authors); Kim, P.M., Sboner, A., Xia, Y., Gerstein, M., The role of disorder in interaction networks: A structural analysis (2008) Molecular Systems Biology, 4, p. 179. , DOI 10.1038/msb.2008.16, PII MSB200816; Liang, H., Li, W.-H., MicroRNA regulation of human protein-protein interaction network (2007) RNA, 13 (9), pp. 1402-1408. , http://www.rnajournal.org/cgi/reprint/13/9/1402, DOI 10.1261/rna.634607; Liao, B.-Y., Scott, N.M., Zhang, J., Impacts of gene essentiality, expression pattern, and gene compactness on the evolutionary rate of mammalian proteins (2006) Molecular Biology and Evolution, 23 (11), pp. 2072-2080. , DOI 10.1093/molbev/msl076; Liao, B.Y., Weng, M.P., Zhang, J., Impact of extracellularity on the evolutionary rate of mammalian proteins (2010) Genome Biol Evol, 2, pp. 39-43; Lin, D.I., Barbash, O., Kumar, K.G.S., Weber, J.D., Harper, J.W., Klein-Szanto, A.J., Rustgi, A., Diehl, J.A., Phosphorylation-dependent ubiquitination of cyclin D1 by the SCF(FBX4-alphaB crystallin) complex (2006) Molecular Cell, 24 (3), pp. 355-366. , DOI 10.1016/j.molcel.2006.09.007, PII S1097276506006356; Lin, W.H., Liu, W.C., Hwang, M.J., Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks (2009) BMC Syst Biol, 3, p. 32; Liu, J., Perumal, N.B., Oldfield, C.J., Su, E.W., Uversky, V.N., Dunker, A.K., Intrinsic disorder in transcription factors (2006) Biochemistry, 45 (22), pp. 6873-6888. , DOI 10.1021/bi0602718; Makino, T., Gojobori, T., The evolutionary rate of a protein is influenced by features of the interacting partners (2006) Mol Biol Evol, 23, pp. 784-789; Manna, B., Bhattacharya, T., Kahali, B., Ghosh, T.C., Evolutionary constraints on hub and non-hub proteins in human protein interaction network: Insight from protein connectivity and intrinsic disorder (2009) Gene, 434, pp. 50-55; Moult, J., Fidelis, K., Kryshtafovych, A., Rost, B., Hubbard, T., Tramontano, A., Critical assessment of methods of protein structure prediction - Round VII (2007) Proteins: Structure, Function and Genetics, 69 (SUPPL. 8), pp. 3-9. , DOI 10.1002/prot.21767; Pal, C., Papp, B., Lercher, M.J., An integrated view of protein evolution (2006) Nat Rev Genet, 7, pp. 337-348; Park, S.G., Choi, S.S., Expression breadth and expression abundance behave differently in correlations with evolutionary rates (2010) BMC Evol Biol, 10, p. 241; Su, A.I., Wiltshire, T., Batalov, S., Lapp, H., Ching, K.A., Block, D., Zhang, J., Hogenesch, J.B., A gene atlas of the mouse and human protein-encoding transcriptomes (2004) Proceedings of the National Academy of Sciences of the United States of America, 101 (16), pp. 6062-6067. , DOI 10.1073/pnas.0400782101; Uversky, V.N., Oldfield, C.J., Dunker, A.K., Showing your ID: Intrinsic disorder as an ID for recognition, regulation and cell signaling (2005) Journal of Molecular Recognition, 18 (5), pp. 343-384. , DOI 10.1002/jmr.747; Uversky, V.N., Oldfield, C.J., Dunker, A.K., Intrinsically disordered proteins in human diseases: Introducing the D2 concept (2008) Annu Rev Biophys, 37, pp. 215-246; Vavouri, T., Semple, J.I., Garcia-Verdugo, R., Lehner, B., Intrinsic protein disorder and interaction promiscuity are widely associated with dosage sensitivity (2009) Cell, 138, pp. 198-208; Ward, J.J., Sodhi, J.S., McGuffin, L.J., Buxton, B.F., Jones, D.T., Prediction and Functional Analysis of Native Disorder in Proteins from the Three Kingdoms of Life (2004) Journal of Molecular Biology, 337 (3), pp. 635-645. , DOI 10.1016/j.jmb.2004.02.002, PII S0022283604001482; Xing, Y., Ouyang, Z., Kapur, K., Scott, M.P., Wong, W.H., Assessing the conservation of mammalian gene expression using high-density exon arrays (2007) Molecular Biology and Evolution, 24 (6), pp. 1283-1285. , DOI 10.1093/molbev/msm061; Yanai, I., Benjamin, H., Shmoish, M., Chalifa-Caspi, V., Shklar, M., Ophir, R., Bar-Even, A., Shmueli, O., Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification (2005) Bioinformatics, 21 (5), pp. 650-659. , DOI 10.1093/bioinformatics/bti042; Yang, J.R., Zhuang, S.M., Zhang, J., Impact of translational error-induced and error-free misfolding on the rate of protein evolution (2010) Mol Syst Biol., 6, p. 421; Yang, X., Welch, J.L., Arnold, J.J., Boehr, D.D., Long-range interaction networks in the function and fidelity of poliovirus RNA-dependent RNA polymerase studied by nuclear magnetic resonance (2010) Biochemistry, 49, pp. 9361-9371

PY - 2011

Y1 - 2011

N2 - Many indicators of protein evolutionary rate have been proposed, but some of them are interrelated. The purpose of this study is to disentangle their correlations. We assess the strength of each indicator by controlling for the other indicators under study. We find that the number of microRNA (miRNA) types that regulate a gene is the strongest rate indicator (a negative correlation), followed by disorder content (the percentage of disordered regions in a protein, a positive correlation); the strength of disorder content as a rate indicator is substantially increased after controlling for the number of miRNA types. By dividing proteins into lowly and highly intrinsically disordered proteins (L-IDPs and H-IDPs), we find that proteins interacting with more H-IDPs tend to evolve more slowly, which largely explains the previous observation of a negative correlation between the number of protein-protein interactions and evolutionary rate. Moreover, all of the indicators examined here, except for the number of miRNA types, have different strengths in L-IDPs and in H-IDPs. Finally, the number of phosphorylation sites is weakly correlated with the number of miRNA types, and its strength as a rate indicator is substantially reduced when other indicators are considered. Our study reveals the relative strength of each rate indicator and increases our understanding of protein evolution. © 2011 The Author.

AB - Many indicators of protein evolutionary rate have been proposed, but some of them are interrelated. The purpose of this study is to disentangle their correlations. We assess the strength of each indicator by controlling for the other indicators under study. We find that the number of microRNA (miRNA) types that regulate a gene is the strongest rate indicator (a negative correlation), followed by disorder content (the percentage of disordered regions in a protein, a positive correlation); the strength of disorder content as a rate indicator is substantially increased after controlling for the number of miRNA types. By dividing proteins into lowly and highly intrinsically disordered proteins (L-IDPs and H-IDPs), we find that proteins interacting with more H-IDPs tend to evolve more slowly, which largely explains the previous observation of a negative correlation between the number of protein-protein interactions and evolutionary rate. Moreover, all of the indicators examined here, except for the number of miRNA types, have different strengths in L-IDPs and in H-IDPs. Finally, the number of phosphorylation sites is weakly correlated with the number of miRNA types, and its strength as a rate indicator is substantially reduced when other indicators are considered. Our study reveals the relative strength of each rate indicator and increases our understanding of protein evolution. © 2011 The Author.

KW - disordered proteins

KW - microRNA regulation

KW - phosphorylation

KW - protein evolution

KW - protein-protein interaction

KW - microRNA

KW - article

KW - correlation coefficient

KW - gene control

KW - human

KW - molecular evolution

KW - nonhuman

KW - protein analysis

KW - protein phosphorylation

KW - protein protein interaction

KW - Amino Acid Substitution

KW - Animals

KW - Computational Biology

KW - Evolution, Molecular

KW - Gene Expression Regulation

KW - Genome, Human

KW - Humans

KW - Mice

KW - MicroRNAs

KW - Protein Conformation

KW - Protein Folding

KW - Proteins

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-80052183299&origin=inward&txGid=478ad246f281822f6085ebbfc1b90841

UR - https://www.scopus.com/results/citedbyresults.uri?sort=plf-f&cite=2-s2.0-80052183299&src=s&imp=t&sid=9251756b722ba02ce0d6c0962fc3e200&sot=cite&sdt=a&sl=0&origin=recordpage&editSaveSearch=&txGid=39b244d75855d7637e937b94f1c82b47

U2 - 10.1093/molbev/msr068

DO - 10.1093/molbev/msr068

M3 - Article

VL - 28

SP - 2513

EP - 2520

JO - Molecular Biology and Evolution

JF - Molecular Biology and Evolution

SN - 0737-4038

IS - 9

ER -