Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation

. 2020 Mar ; 16 (3) : e9170.

Jazyk angličtina Země Německo Médium print

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid32175694

Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post-translational turnover, we devised a strategy combining pulse stable isotope-labeled amino acids in cells (pSILAC), data-independent acquisition mass spectrometry (DIA-MS), and a novel data analysis framework that resolves protein degradation rate on the level of mRNA alternative splicing isoforms and isoform groups. We demonstrated our approach by the genome-wide correlation analysis between mRNA amounts and protein degradation across different strains of HeLa cells that harbor a high grade of gene dosage variation. The dataset revealed that specific biological processes, cellular organelles, spatial compartments of organelles, and individual protein isoforms of the same genes could have distinctive degradation rate. The protein degradation diversity thus dissects the corresponding buffering or concerting protein turnover control across cancer cell lines. The data further indicate that specific mRNA splicing events such as intron retention significantly impact the protein abundance levels. Our findings support the tight association between transcriptome variability and proteostasis and provide a methodological foundation for studying functional protein degradation.

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Abascal F, Ezkurdia I, Rodriguez‐Rivas J, Rodriguez JM, del Pozo A, Vazquez J, Valencia A, Tress ML (2015) Alternatively spliced homologous exons have ancient origins and are highly expressed at the protein level. PLoS Comput Biol 11: e1004325 PubMed PMC

Adusumalli S, Ngian ZK, Lin WQ, Benoukraf T, Ong CT (2019) Increased intron retention is a post‐transcriptional signature associated with progressive aging and Alzheimer's disease. Aging Cell 18: e12928 PubMed PMC

Aebersold R, Mann M (2016) Mass‐spectrometric exploration of proteome structure and function. Nature 537: 347–355 PubMed

Albert FW, Muzzey D, Weissman JS, Kruglyak L (2014) Genetic influences on translation in yeast. PLoS Genet 10: e1004692 PubMed PMC

Altman N, Krzywinski M (2015) Association, correlation and causation. Nat Methods 12: 899 PubMed

Amon S, Meier‐Abt F, Gillet LC, Dimitrieva S, Theocharides APA, Manz MG, Aebersold R (2019) Sensitive quantitative proteomics of human hematopoietic stem and progenitor cells by data‐independent acquisition mass spectrometry. Mol Cell Proteomics 18: 1454–1467 PubMed PMC

Bader DM, Wilkening S, Lin G, Tekkedil MM, Dietrich K, Steinmetz LM, Gagneur J (2015) Negative feedback buffers effects of regulatory variants. Mol Syst Biol 11: 785 PubMed PMC

Battle A, Khan Z, Wang SH, Mitrano A, Ford MJ, Pritchard JK, Gilad Y (2015) Genomic variation. Impact of regulatory variation from RNA to protein. Science 347: 664–667 PubMed PMC

Becher I, Andres‐Pons A, Romanov N, Stein F, Schramm M, Baudin F, Helm D, Kurzawa N, Mateus A, Mackmull MT et al (2018) Pervasive protein thermal stability variation during the cell cycle. Cell 173: 1495–1507 e1418 PubMed PMC

Beck M, Schmidt A, Malmstroem J, Claassen M, Ori A, Szymborska A, Herzog F, Rinner O, Ellenberg J, Aebersold R (2011) The quantitative proteome of a human cell line. Mol Syst Biol 7: 549 PubMed PMC

Bhattacharyya S, Yu H, Mim C, Matouschek A (2014) Regulated protein turnover: snapshots of the proteasome in action. Nat Rev Mol Cell Biol 15: 122–133 PubMed PMC

Blencowe BJ (2017) The relationship between alternative splicing and proteomic complexity. Trends Biochem Sci 42: 407–408 PubMed

Boisvert FM, Ahmad Y, Gierlinski M, Charriere F, Lamont D, Scott M, Barton G, Lamond AI (2012) A quantitative spatial proteomics analysis of proteome turnover in human cells. Mol Cell Proteomics 11: M111 011429 PubMed PMC

Braunschweig U, Barbosa‐Morais NL, Pan Q, Nachman EN, Alipanahi B, Gonatopoulos‐Pournatzis T, Frey B, Irimia M, Blencowe BJ (2014) Widespread intron retention in mammals functionally tunes transcriptomes. Genome Res 24: 1774–1786 PubMed PMC

Bruderer R, Bernhardt OM, Gandhi T, Miladinovic SM, Cheng LY, Messner S, Ehrenberger T, Zanotelli V, Butscheid Y, Escher C et al (2015) Extending the limits of quantitative proteome profiling with data‐independent acquisition and application to acetaminophen‐treated three‐dimensional liver microtissues. Mol Cell Proteomics 14: 1400–1410 PubMed PMC

Bruderer R, Bernhardt OM, Gandhi T, Reiter L (2016) High‐precision iRT prediction in the targeted analysis of data‐independent acquisition and its impact on identification and quantitation. Proteomics 16: 2246–2256 PubMed PMC

Bruderer R, Bernhardt OM, Gandhi T, Xuan Y, Sondermann J, Schmidt M, Gomez‐Varela D, Reiter L (2017) Optimization of experimental parameters in data‐independent mass spectrometry significantly increases depth and reproducibility of results. Mol Cell Proteomics 16: 2296–2309 PubMed PMC

Cambridge SB, Gnad F, Nguyen C, Bermejo JL, Kruger M, Mann M (2011) Systems‐wide proteomic analysis in mammalian cells reveals conserved, functional protein turnover. J Proteome Res 10: 5275–5284 PubMed

Chaudhary S, Jabre I, Reddy ASN, Staiger D, Syed NH (2019) Perspective on alternative splicing and proteome complexity in plants. Trends Plant Sci 24: 496–506 PubMed

Claydon AJ, Beynon R (2012) Proteome dynamics: revisiting turnover with a global perspective. Mol Cell Proteomics 11: 1551–1565 PubMed PMC

Cox J, Mann M (2012) 1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high‐throughput data. BMC Bioinformatics 13(Suppl 16): S12 PubMed PMC

Dephoure N, Hwang S, O'Sullivan C, Dodgson SE, Gygi SP, Amon A, Torres EM (2014) Quantitative proteomic analysis reveals posttranslational responses to aneuploidy in yeast. Elife 3: e03023 PubMed PMC

Di Y, Zhang Y, Zhang L, Tao T, Lu H (2017) MdFDIA: a mass defect based four‐plex data‐independent acquisition strategy for proteome quantification. Anal Chem 89: 10248–10255 PubMed

Doherty MK, Hammond DE, Clague MJ, Gaskell SJ, Beynon RJ (2009) Turnover of the human proteome: determination of protein intracellular stability by dynamic SILAC. J Proteome Res 8: 104–112 PubMed

Ebhardt HA, Sabido E, Huttenhain R, Collins B, Aebersold R (2012) Range of protein detection by selected/multiple reaction monitoring mass spectrometry in an unfractionated human cell culture lysate. Proteomics 12: 1185–1193 PubMed

Edfors F, Danielsson F, Hallstrom BM, Kall L, Lundberg E, Ponten F, Forsstrom B, Uhlen M (2016) Gene‐specific correlation of RNA and protein levels in human cells and tissues. Mol Syst Biol 12: 883 PubMed PMC

Eichelbaum K, Krijgsveld J (2014) Rapid temporal dynamics of transcription, protein synthesis, and secretion during macrophage activation. Mol Cell Proteomics 13: 792–810 PubMed PMC

Floor SN, Doudna JA (2016) Tunable protein synthesis by transcript isoforms in human cells. Elife 5: e10921 PubMed PMC

Fortelny N, Overall CM, Pavlidis P, Freue GVC (2017) Can we predict protein from mRNA levels? Nature 547: E19–E20 PubMed

Franks A, Airoldi E, Slavov N (2017) Post‐transcriptional regulation across human tissues. PLoS Comput Biol 13: e1005535 PubMed PMC

Garcia‐Blanco MA, Baraniak AP, Lasda EL (2004) Alternative splicing in disease and therapy. Nat Biotechnol 22: 535–546 PubMed

Gillet LC, Navarro P, Tate S, Röst H, Selevsek N, Reiter L, Bonner R, Aebersold R (2012) Targeted data extraction of the MS/MS spectra generated by data‐independent acquisition: a new concept for consistent and accurate proteome analysis. Mol Cell Proteomics 11: O111.016717 PubMed PMC

Gonzàlez‐Porta M, Brazma A (2014) Identification, annotation and visualisation of extreme changes in splicing from RNA‐seq experiments with SwitchSeq. bioRxiv 10.1101/005967 [PREPRINT] DOI

Gonzalez‐Porta M, Frankish A, Rung J, Harrow J, Brazma A (2013) Transcriptome analysis of human tissues and cell lines reveals one dominant transcript per gene. Genome Biol 14: R70 PubMed PMC

Greber BJ, Ban N (2016) Structure and function of the mitochondrial ribosome. Annu Rev Biochem 85: 103–132 PubMed

Greig MJ, Niessen S, Weinrich SL, Feng JL, Shi M, Johnson TO (2015) Effects of activating mutations on EGFR cellular protein turnover and amino acid recycling determined using SILAC mass spectrometry. Int J Cell Biol 2015: 798936 PubMed PMC

Hart T, Komori HK, LaMere S, Podshivalova K, Salomon DR (2013) Finding the active genes in deep RNA‐seq gene expression studies. BMC Genom 14: 778 PubMed PMC

Hinkson IV, Elias JE (2011) The dynamic state of protein turnover: It's about time. Trends Cell Biol 21: 293–303 PubMed

Huang DW, Sherman BT, Lempicki RA (2008) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4: 44 PubMed

Huang GW, Zhang YL, Liao LD, Li EM, Xu LY (2017) Natural antisense transcript TPM1‐AS regulates the alternative splicing of tropomyosin I through an interaction with RNA‐binding motif protein 4. Int J Biochem Cell Biol 90: 59–67 PubMed

Jovanovic M, Rooney MS, Mertins P, Przybylski D, Chevrier N, Satija R, Rodriguez EH, Fields AP, Schwartz S, Raychowdhury R et al (2015) Immunogenetics. Dynamic profiling of the protein life cycle in response to pathogens. Science 347: 1259038 PubMed PMC

Kahles A, Lehmann KV, Toussaint NC, Huser M, Stark SG, Sachsenberg T, Stegle O, Kohlbacher O, Sander C, Cancer Genome Atlas Research Network et al (2018) Comprehensive analysis of alternative splicing across tumors from 8,705 patients. Cancer Cell 34: 211–224 e216 PubMed PMC

Larochelle S (2017) The proof of splicing is in the proteome. Nat Methods 14: 940

Lau E, Han Y, Williams DR, Thomas CT, Shrestha R, Wu JC, Lam MPY (2019) Splice‐junction‐based mapping of alternative isoforms in the human proteome. Cell Rep 29: 3751–3765 e3755 PubMed PMC

Li W, Chi H, Salovska B, Wu C, Sun L, Rosenberger G, Liu Y (2019) Assessing the relationship between mass window width and retention time scheduling on protein coverage for data‐independent acquisition. J Am Soc Mass Spectrom 30: 1396–1405 PubMed

Liang Y, Song J, He D, Xia Y, Wu Y, Yin X, Liu J (2019) Systematic analysis of survival‐associated alternative splicing signatures uncovers prognostic predictors for head and neck cancer. J Cell Physiol 234: 15836–15846 PubMed PMC

Liu Y, Beyer A, Aebersold R (2016) On the dependency of cellular protein levels on mRNA abundance. Cell 165: 535–550 PubMed

Liu Y, Borel C, Li L, Muller T, Williams EG, Germain PL, Buljan M, Sajic T, Boersema PJ, Shao W et al (2017a) Systematic proteome and proteostasis profiling in human Trisomy 21 fibroblast cells. Nat Commun 8: 1212 PubMed PMC

Liu Y, Gonzalez‐Porta M, Santos S, Brazma A, Marioni JC, Aebersold R, Venkitaraman AR, Wickramasinghe VO (2017b) Impact of alternative splicing on the human proteome. Cell Rep 20: 1229–1241 PubMed PMC

Liu Y, Mi Y, Mueller T, Kreibich S, Williams EG, Van Drogen A, Borel C, Frank M, Germain PL, Bludau I et al (2019) Multi‐omic measurements of heterogeneity in HeLa cells across laboratories. Nat Biotechnol 37: 314–322 PubMed

Mallick P, Schirle M, Chen SS, Flory MR, Lee H, Martin D, Ranish J, Raught B, Schmitt R, Werner T et al (2006) Computational prediction of proteotypic peptides for quantitative proteomics. Nat Biotechnol 25: 125 PubMed

Maniatis T, Tasic B (2002) Alternative pre‐mRNA splicing and proteome expansion in metazoans. Nature 418: 236–243 PubMed

Martin‐Perez M, Villen J (2017) Determinants and regulation of protein turnover in yeast. Cell Syst 5: 283–294 e285 PubMed PMC

Mathieson T, Franken H, Kosinski J, Kurzawa N, Zinn N, Sweetman G, Poeckel D, Ratnu VS, Schramm M, Becher I et al (2018) Systematic analysis of protein turnover in primary cells. Nat Commun 9: 689 PubMed PMC

McAlister GC, Nusinow DP, Jedrychowski MP, Wuhr M, Huttlin EL, Erickson BK, Rad R, Haas W, Gygi SP (2014) MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal Chem 86: 7150–7158 PubMed PMC

McShane E, Sin C, Zauber H, Wells JN, Donnelly N, Wang X, Hou J, Chen W, Storchova Z, Marsh JA et al (2016) Kinetic analysis of protein stability reveals age‐dependent degradation. Cell 167: 803–815 e821 PubMed

Mehnert M, Li W, Wu C, Salovska B, Liu Y (2019) Combining rapid data independent acquisition and CRISPR gene deletion for studying potential protein functions: a case of HMGN1. Proteomics 19: e1800438 PubMed

Milenkovic VM, Bader S, Sudria‐Lopez D, Siebert R, Brandl C, Nothdurfter C, Weber BHF, Rupprecht R, Wetzel CH (2018) Effects of genetic variants in the TSPO gene on protein structure and stability. PLoS One 13: e0195627 PubMed PMC

Mollet IG, Ben‐Dov C, Felicio‐Silva D, Grosso AR, Eleuterio P, Alves R, Staller R, Silva TS, Carmo‐Fonseca M (2010) Unconstrained mining of transcript data reveals increased alternative splicing complexity in the human transcriptome. Nucleic Acids Res 38: 4740–4754 PubMed PMC

Morgan JT, Fink GR, Bartel DP (2019) Excised linear introns regulate growth in yeast. Nature 565: 606–611 PubMed PMC

Mueller S, Wahlander A, Selevsek N, Otto C, Ngwa EM, Poljak K, Frey AD, Aebi M, Gauss R (2015) Protein degradation corrects for imbalanced subunit stoichiometry in OST complex assembly. Mol Biol Cell 26: 2596–2608 PubMed PMC

Nagaraj N, Wisniewski JR, Geiger T, Cox J, Kircher M, Kelso J, Paabo S, Mann M (2011) Deep proteome and transcriptome mapping of a human cancer cell line. Mol Syst Biol 7: 548 PubMed PMC

Navarro P, Kuharev J, Gillet LC, Bernhardt OM, MacLean B, Rost HL, Tate SA, Tsou CC, Reiter L, Distler U et al (2016) A multicenter study benchmarks software tools for label‐free proteome quantification. Nat Biotechnol 34: 1130–1136 PubMed PMC

Parenteau J, Maignon L, Berthoumieux M, Catala M, Gagnon V, Abou Elela S (2019) Introns are mediators of cell response to starvation. Nature 565: 612–617 PubMed

Perez‐Riverol Y, Csordas A, Bai J, Bernal‐Llinares M, Hewapathirana S, Kundu DJ, Inuganti A, Griss J, Mayer G, Eisenacher M et al (2019) The PRIDE database and related tools and resources in 2019: improving support for quantification data. Nucleic Acids Res 47: D442–D450 PubMed PMC

Pratt JM, Petty J, Riba‐Garcia I, Robertson DH, Gaskell SJ, Oliver SG, Beynon RJ (2002) Dynamics of protein turnover, a missing dimension in proteomics. Mol Cell Proteomics 1: 579–591 PubMed

Pugh TJ, Kelly MA, Gowrisankar S, Hynes E, Seidman MA, Baxter SM, Bowser M, Harrison B, Aaron D, Mahanta LM et al (2014) The landscape of genetic variation in dilated cardiomyopathy as surveyed by clinical DNA sequencing. Genet Med 16: 601–608 PubMed

R Core Team (2018) R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing;

Reiter L, Rinner O, Picotti P, Huttenhain R, Beck M, Brusniak MY, Hengartner MO, Aebersold R (2011) mProphet: automated data processing and statistical validation for large‐scale SRM experiments. Nat Methods 8: 430–435 PubMed

Reumers J, Schymkowitz J, Ferkinghoff‐Borg J, Stricher F, Serrano L, Rousseau F (2005) SNPeffect: a database mapping molecular phenotypic effects of human non‐synonymous coding SNPs. Nucleic Acids Res 33: D527–D532 PubMed PMC

Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26: 139–140 PubMed PMC

Romanov N, Kuhn M, Aebersold R, Ori A, Beck M, Bork P (2019) Disentangling genetic and environmental effects on the proteotypes of individuals. Cell 177: 1308–1318 e1310 PubMed PMC

Rosenberger G, Koh CC, Guo T, Rost HL, Kouvonen P, Collins BC, Heusel M, Liu Y, Caron E, Vichalkovski A et al (2014) A repository of assays to quantify 10,000 human proteins by SWATH‐MS. Sci Data 1: 140031 PubMed PMC

Rosenberger G, Bludau I, Schmitt U, Heusel M, Hunter CL, Liu Y, MacCoss MJ, MacLean BX, Nesvizhskii AI, Pedrioli PGA et al (2017) Statistical control of peptide and protein error rates in large‐scale targeted data‐independent acquisition analyses. Nat Methods 14: 921–927 PubMed PMC

Rost HL, Rosenberger G, Navarro P, Gillet L, Miladinovic SM, Schubert OT, Wolski W, Collins BC, Malmstrom J, Malmstrom L et al (2014) OpenSWATH enables automated, targeted analysis of data‐independent acquisition MS data. Nat Biotechnol 32: 219–223 PubMed

Rost HL, Malmstrom L, Aebersold R (2015) Reproducible quantitative proteotype data matrices for systems biology. Mol Biol Cell 26: 3926–3931 PubMed PMC

Rost HL, Liu Y, D'Agostino G, Zanella M, Navarro P, Rosenberger G, Collins BC, Gillet L, Testa G, Malmstrom L et al (2016) TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics. Nat Methods 13: 777–783 PubMed PMC

Savitski MM, Zinn N, Faelth‐Savitski M, Poeckel D, Gade S, Becher I, Muelbaier M, Wagner AJ, Strohmer K, Werner T et al (2018) Multiplexed proteome dynamics profiling reveals mechanisms controlling protein homeostasis. Cell 173: 260–274 e225 PubMed PMC

Schreiner D, Simicevic J, Ahrne E, Schmidt A, Scheiffele P (2015) Quantitative isoform‐profiling of highly diversified recognition molecules. Elife 4: e07794 PubMed PMC

Schwanhausser B, Gossen M, Dittmar G, Selbach M (2009) Global analysis of cellular protein translation by pulsed SILAC. Proteomics 9: 205–209 PubMed

Schwanhausser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, Chen W, Selbach M (2011) Global quantification of mammalian gene expression control. Nature 473: 337–342 PubMed

Sheynkman GM, Johnson JE, Jagtap PD, Shortreed MR, Onsongo G, Frey BL, Griffin TJ, Smith LM (2014) Using Galaxy‐P to leverage RNA‐Seq for the discovery of novel protein variations. BMC Genom 15: 703 PubMed PMC

Silva GM, Vogel C (2016) Quantifying gene expression: the importance of being subtle. Mol Syst Biol 12: 885 PubMed PMC

Smith LM, Kelleher NL, Consortium for Top Down P (2013) Proteoform: a single term describing protein complexity. Nat Methods 10: 186–187 PubMed PMC

Stingele S, Stoehr G, Peplowska K, Cox J, Mann M, Storchova Z (2012) Global analysis of genome, transcriptome and proteome reveals the response to aneuploidy in human cells. Mol Syst Biol 8: 608 PubMed PMC

Teo G, Kim S, Tsou CC, Collins B, Gingras AC, Nesvizhskii AI, Choi H (2015) mapDIA: preprocessing and statistical analysis of quantitative proteomics data from data independent acquisition mass spectrometry. J Proteomics 129: 108–120 PubMed PMC

Tran TT, Bollineni RC, Strozynski M, Koehler CJ, Thiede B (2017) Identification of alternative splice variants using unique tryptic peptide sequences for database searches. J Proteome Res 16: 2571–2578 PubMed

Tress ML, Abascal F, Valencia A (2017a) Alternative splicing may not be the key to proteome complexity. Trends Biochem Sci 42: 98–110 PubMed PMC

Tress ML, Abascal F, Valencia A (2017b) Most alternative isoforms are not functionally important. Trends Biochem Sci 42: 408–410 PubMed PMC

Tyanova S, Temu T, Sinitcyn P, Carlson A, Hein MY, Geiger T, Mann M, Cox J (2016) The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat Methods 13: 731–740 PubMed

Vogel C, Marcotte EM (2012) Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet 13: 227–232 PubMed PMC

Volkening JD, Stecker KE, Sussman MR (2019) Proteome‐wide analysis of protein thermal stability in the model higher plant Arabidopsis thaliana . Mol Cell Proteomics 18: 308–319 PubMed PMC

Wang Z, Moult J (2001) SNPs, protein structure, and disease. Hum Mutat 17: 263–270 PubMed

Wang ET, Sandberg R, Luo S, Khrebtukova I, Zhang L, Mayr C, Kingsmore SF, Schroth GP, Burge CB (2008) Alternative isoform regulation in human tissue transcriptomes. Nature 456: 470–476 PubMed PMC

Wang SH, Hsiao CJ, Khan Z, Pritchard JK (2018a) Post‐translational buffering leads to convergent protein expression levels between primates. Genome Biol 19: 83 PubMed PMC

Wang X, Codreanu SG, Wen B, Li K, Chambers MC, Liebler DC, Zhang B (2018b) Detection of proteome diversity resulted from alternative splicing is limited by trypsin cleavage specificity. Mol Cell Proteomics 17: 422–430 PubMed PMC

Weatheritt RJ, Sterne‐Weiler T, Blencowe BJ (2016) The ribosome‐engaged landscape of alternative splicing. Nat Struct Mol Biol 23: 1117–1123 PubMed PMC

Welle KA, Zhang T, Hryhorenko JR, Shen S, Qu J, Ghaemmaghami S (2016) Time‐resolved analysis of proteome dynamics by tandem mass tags and stable isotope labeling in cell culture (TMT‐SILAC) hyperplexing. Mol Cell Proteomics 15: 3551–3563 PubMed PMC

Wickramasinghe VO, Gonzalez‐Porta M, Perera D, Bartolozzi AR, Sibley CR, Hallegger M, Ule J, Marioni JC, Venkitaraman AR (2015) Regulation of constitutive and alternative mRNA splicing across the human transcriptome by PRPF8 is determined by 5′ splice site strength. Genome Biol 16: 201 PubMed PMC

Wong JJ, Au AY, Ritchie W, Rasko JE (2016) Intron retention in mRNA: no longer nonsense: known and putative roles of intron retention in normal and disease biology. BioEssays 38: 41–49 PubMed

Wu Y, Wang F, Liu Z, Qin H, Song C, Huang J, Bian Y, Wei X, Dong J, Zou H (2014) Five‐plex isotope dimethyl labeling for quantitative proteomics. Chem Commun (Camb) 50: 1708–1710 PubMed

Wu P, Pu L, Deng B, Li Y, Chen Z, Liu W (2019) PASS: a proteomics alternative splicing screening pipeline. Proteomics 19: e1900041 PubMed

Zecha J, Meng C, Zolg DP, Samaras P, Wilhelm M, Kuster B (2018) Peptide level turnover measurements enable the study of proteoform dynamics. Mol Cell Proteomics 17: 974–992 PubMed PMC

Zhu Y, Hultin‐Rosenberg L, Forshed J, Branca RM, Orre LM, Lehtio J (2014) SpliceVista, a tool for splice variant identification and visualization in shotgun proteomics data. Mol Cell Proteomics 13: 1552–1562 PubMed PMC

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