A Quantitative Proteome Map of the Human Body
Name
nihms-1624446.pdf
Description
Accepted version
Size
2.66 MB
Format
Adobe PDF
Checksum (MD5)
f0ab32cbc528f34c76bf23a45b7b9b89
Date Issued
October 2020
Journal
Cell
Publisher
Elsevier BV
Citation
Lihua Jiang, Meng Wang, Shin Lin, Ruiqi Jian, Xiao Li, Joanne Chan, Guanlan Dong, Huaying Fang, Aaron E. Robinson, François Aguet, Shankara Anand, Kristin G. Ardlie, Stacey Gabriel, Gad Getz, Aaron Graubert, Kane Hadley, Robert E. Handsaker, Katherine H. Huang, Seva Kashin, Daniel G. MacArthur, Samuel R. Meier, Jared L. Nedzel, Duyen Y. Nguyen, Ayellet V. Segrè, Ellen Todres, Brunilda Balliu, Alvaro N. Barbeira, Alexis Battle, Rodrigo Bonazzola, Andrew Brown, Christopher D. Brown, Stephane E. Castel, Don Conrad, Daniel J. Cotter, Nancy Cox, Sayantan Das, Olivia M. de Goede, Emmanouil T. Dermitzakis, Barbara E. Engelhardt, Eleazar Eskin, Tiffany Y. Eulalio, Nicole M. Ferraro, Elise Flynn, Laure Fresard, Eric R. Gamazon, Diego Garrido-Martín, Nicole R. Gay, Roderic Guigó, Andrew R. Hamel, Yuan He, Paul J. Hoffman, Farhad Hormozdiari, Lei Hou, Hae Kyung Im, Brian Jo, Silva Kasela, Manolis Kellis, Sarah Kim-Hellmuth, Alan Kwong, Tuuli Lappalainen, Xin Li, Yanyu Liang, Serghei Mangul, Pejman Mohammadi, Stephen B. Montgomery, Manuel Muñoz-Aguirre, Daniel C. Nachun, Andrew B. Nobel, Meritxell Oliva, YoSon Park, Yongjin Park, Princy Parsana, Ferran Reverter, John M. Rouhana, Chiara Sabatti, Ashis Saha, Andrew D. Skol, Matthew Stephens, Barbara E. Stranger, Benjamin J. Strober, Nicole A. Teran, Ana Viñuela, Gao Wang, Xiaoquan Wen, Fred Wright, Valentin Wucher, Yuxin Zou, Pedro G. Ferreira, Gen Li, Marta Melé, Esti Yeger-Lotem, Mary E. Barcus, Debra Bradbury, Tanya Krubit, Jeffrey A. McLean, Liqun Qi, Karna Robinson, Nancy V. Roche, Anna M. Smith, Leslie Sobin, David E. Tabor, Anita Undale, Jason Bridge, Lori E. Brigham, Barbara A. Foster, Bryan M. Gillard, Richard Hasz, Marcus Hunter, Christopher Johns, Mark Johnson, Ellen Karasik, Gene Kopen, William F. Leinweber, Alisa McDonald, Michael T. Moser, Kevin Myer, Kimberley D. Ramsey, Brian Roe, Saboor Shad, Jeffrey A. Thomas, Gary Walters, Michael Washington, Joseph Wheeler, Scott D. Jewell, Daniel C. Rohrer, Dana R. Valley, David A. Davis, Deborah C. Mash, Philip A. Branton, Laura K. Barker, Heather M. Gardiner, Maghboeba Mosavel, Laura A. Siminoff, Paul Flicek, Maximilian Haeussler, Thomas Juettemann, W. James Kent, Christopher M. Lee, Conner C. Powell, Kate R. Rosenbloom, Magali Ruffier, Dan Sheppard, Kieron Taylor, Stephen J. Trevanion, Daniel R. Zerbino, Nathan S. Abell, Joshua Akey, Lin Chen, Kathryn Demanelis, Jennifer A. Doherty, Andrew P. Feinberg, Kasper D. Hansen, Peter F. Hickey, Farzana Jasmine, Rajinder Kaul, Muhammad G. Kibriya, Jin Billy Li, Qin Li, Sandra E. Linder, Brandon L. Pierce, Lindsay F. Rizzardi, Kevin S. Smith, John Stamatoyannopoulos, Hua Tang, Latarsha J. Carithers, Ping Guan, Susan E. Koester, A. Roger Little, Helen M. Moore, Concepcion R. Nierras, Abhi K. Rao, Jimmie B. Vaught, Simona Volpi, Michael P. Snyder, A Quantitative Proteome Map of the Human Body, Cell, Volume 183, Issue 1, 2020
Version
Author's final manuscript
Abstract
© 2020 Elsevier Inc. Determining protein levels in each tissue and how they compare with RNA levels is important for understanding human biology and disease as well as regulatory processes that control protein levels. We quantified the relative protein levels from over 12,000 genes across 32 normal human tissues. Tissue-specific or tissue-enriched proteins were identified and compared to transcriptome data. Many ubiquitous transcripts are found to encode tissue-specific proteins. Discordance of RNA and protein enrichment revealed potential sites of synthesis and action of secreted proteins. The tissue-specific distribution of proteins also provides an in-depth view of complex biological events that require the interplay of multiple tissues. Most importantly, our study demonstrated that protein tissue-enrichment information can explain phenotypes of genetic diseases, which cannot be obtained by transcript information alone. Overall, our results demonstrate how understanding protein levels can provide insights into regulation, secretome, metabolism, and human diseases.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/J.CELL.2020.08.036
