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1. A single-cell transcriptomic atlas characterizes ageing tissues in the mouse

Author

Almanzar, Nicole, Antony, Jane, Baghel, Ankit S, Bakerman, Isaac, Bansal, Ishita, Barres, Ben A, Beachy, Philip A, Berdnik, Daniela, Bilen, Biter, Brownfield, Douglas, Cain, Corey, Chan, Charles KF, Chen, Michelle B, Clarke, Michael F, Conley, Stephanie D, Darmanis, Spyros, Demers, Aaron, Demir, Kubilay, de Morree, Antoine, Divita, Tessa, du Bois, Haley, Ebadi, Hamid, Espinoza, F Hernán, Fish, Matt, Gan, Qiang, George, Benson M, Gillich, Astrid, Gòmez-Sjöberg, Rafael, Green, Foad, Genetiano, Geraldine, Gu, Xueying, Gulati, Gunsagar S, Hahn, Oliver, Haney, Michael Seamus, Hang, Yan, Harris, Lincoln, He, Mu, Hosseinzadeh, Shayan, Huang, Albin, Huang, Kerwyn Casey, Iram, Tal, Isobe, Taichi, Ives, Feather, Jones, Robert C, Kao, Kevin S, Karkanias, Jim, Karnam, Guruswamy, Keller, Andreas, Kershner, Aaron M, Khoury, Nathalie, Kim, Seung K, Kiss, Bernhard M, Kong, William, Krasnow, Mark A, Kumar, Maya E, Kuo, Christin S, Lam, Jonathan, Lee, Davis P, Lee, Song E, Lehallier, Benoit, Leventhal, Olivia, Li, Guang, Li, Qingyun, Liu, Ling, Lo, Annie, Lu, Wan-Jin, Lugo-Fagundo, Maria F, Manjunath, Anoop, May, Andrew P, Maynard, Ashley, McGeever, Aaron, McKay, Marina, McNerney, M Windy, Merrill, Bryan, Metzger, Ross J, Mignardi, Marco, Min, Dullei, Nabhan, Ahmad N, Neff, Norma F, Ng, Katharine M, Nguyen, Patricia K, Noh, Joseph, Nusse, Roel, Pálovics, Róbert, Patkar, Rasika, Peng, Weng Chuan, Penland, Lolita, Pisco, Angela Oliveira, Pollard, Katherine, Puccinelli, Robert, Qi, Zhen, Quake, Stephen R, Rando, Thomas A, Rulifson, Eric J, Schaum, Nicholas, Segal, Joe M, Sikandar, Shaheen S, Sinha, Rahul, Sit, Rene V, and Sonnenburg, Justin

Subjects
Biochemistry and Cell Biology, Biological Sciences, Human Genome, Genetics, Aging, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Generic health relevance, Animals, Cellular Senescence, DNA Mutational Analysis, Female, Gene Expression Regulation, Developmental, Genomic Instability, Immunity, Liver, Male, Mice, Models, Animal, Organ Specificity, Single-Cell Analysis, T-Lymphocytes, Transcriptome, Tabula Muris Consortium, General Science & Technology
Abstract

Ageing is characterized by a progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death1. Despite rapid advances over recent years, many of the molecular and cellular processes that underlie the progressive loss of healthy physiology are poorly understood2. To gain a better insight into these processes, here we generate a single-cell transcriptomic atlas across the lifespan of Mus musculus that includes data from 23 tissues and organs. We found cell-specific changes occurring across multiple cell types and organs, as well as age-related changes in the cellular composition of different organs. Using single-cell transcriptomic data, we assessed cell-type-specific manifestations of different hallmarks of ageing-such as senescence3, genomic instability4 and changes in the immune system2. This transcriptomic atlas-which we denote Tabula Muris Senis, or 'Mouse Ageing Cell Atlas'-provides molecular information about how the most important hallmarks of ageing are reflected in a broad range of tissues and cell types.

Published
2020

2. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris

Author

Schaum, Nicholas, Karkanias, Jim, Neff, Norma F, May, Andrew P, Quake, Stephen R, Wyss-Coray, Tony, Darmanis, Spyros, Batson, Joshua, Botvinnik, Olga, Chen, Michelle B, Chen, Steven, Green, Foad, Jones, Robert C, Maynard, Ashley, Penland, Lolita, Pisco, Angela Oliveira, Sit, Rene V, Stanley, Geoffrey M, Webber, James T, Zanini, Fabio, Baghel, Ankit S, Bakerman, Isaac, Bansal, Ishita, Berdnik, Daniela, Bilen, Biter, Brownfield, Douglas, Cain, Corey, Cho, Min, Cirolia, Giana, Conley, Stephanie D, Demers, Aaron, Demir, Kubilay, de Morree, Antoine, Divita, Tessa, du Bois, Haley, Dulgeroff, Laughing Bear Torrez, Ebadi, Hamid, Espinoza, F Hernán, Fish, Matt, Gan, Qiang, George, Benson M, Gillich, Astrid, Genetiano, Geraldine, Gu, Xueying, Gulati, Gunsagar S, Hang, Yan, Hosseinzadeh, Shayan, Huang, Albin, Iram, Tal, Isobe, Taichi, Ives, Feather, Kao, Kevin S, Karnam, Guruswamy, Kershner, Aaron M, Kiss, Bernhard M, Kong, William, Kumar, Maya E, Lam, Jonathan Y, Lee, Davis P, Lee, Song E, Li, Guang, Li, Qingyun, Liu, Ling, Lo, Annie, Lu, Wan-Jin, Manjunath, Anoop, May, Kaia L, May, Oliver L, McKay, Marina, Metzger, Ross J, Mignardi, Marco, Min, Dullei, Nabhan, Ahmad N, Ng, Katharine M, Noh, Joseph, Patkar, Rasika, Peng, Weng Chuan, Puccinelli, Robert, Rulifson, Eric J, Sikandar, Shaheen S, Sinha, Rahul, Szade, Krzysztof, Tan, Weilun, Tato, Cristina, Tellez, Krissie, Travaglini, Kyle J, Tropini, Carolina, Waldburger, Lucas, and van Weele, Linda J

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, 1.5 Resources and infrastructure (underpinning), Generic health relevance, Animals, Cell Biology, Endothelial Cells, Female, Flow Cytometry, Gene Expression Profiling, Male, Mice, Mice, Inbred C57BL, Microfluidics, Organ Specificity, Single-Cell Analysis, T-Lymphocytes, Transcription Factors, Transcriptome, Tabula Muris Consortium, Overall coordination, Logistical coordination, Organ collection and processing, Library preparation and sequencing, Computational data analysis, Cell type annotation, Writing group, Supplemental text writing group, Principal investigators, General Science & Technology
Abstract

Here we present a compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, reveal gene expression in poorly characterized cell populations and enable the direct and controlled comparison of gene expression in cell types that are shared between tissues, such as T lymphocytes and endothelial cells from different anatomical locations. Two distinct technical approaches were used for most organs: one approach, microfluidic droplet-based 3'-end counting, enabled the survey of thousands of cells at relatively low coverage, whereas the other, full-length transcript analysis based on fluorescence-activated cell sorting, enabled the characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology.

Published
2018

3. Ageing hallmarks exhibit organ-specific temporal signatures

Author

Schaum, Nicholas, Lehallier, Benoit, Hahn, Oliver, Pálovics, Róbert, Hosseinzadeh, Shayan, Lee, Song E., Sit, Rene, Lee, Davis P., Losada, Patricia Morán, Zardeneta, Macy E., Fehlmann, Tobias, Webber, James T., McGeever, Aaron, Calcuttawala, Kruti, Zhang, Hui, Berdnik, Daniela, Mathur, Vidhu, Tan, Weilun, Zee, Alexander, Tan, Michelle, Almanzar, Nicole, Antony, Jane, Baghel, Ankit S., Bakerman, Isaac, Bansal, Ishita, Barres, Ben A., Beachy, Philip A., Bilen, Biter, Brownfield, Douglas, Cain, Corey, Chan, Charles K. F., Chen, Michelle B., Clarke, Michael F., Conley, Stephanie D., Darmanis, Spyros, Demers, Aaron, Demir, Kubilay, de Morree, Antoine, Divita, Tessa, du Bois, Haley, Ebadi, Hamid, Espinoza, F. Hernán, Fish, Matt, Gan, Qiang, George, Benson M., Gillich, Astrid, Gòmez-Sjöberg, Rafael, Green, Foad, Genetiano, Geraldine, Gu, Xueying, Gulati, Gunsagar S., Haney, Michael Seamus, Hang, Yan, Harris, Lincoln, He, Mu, Huang, Albin, Huang, Kerwyn Casey, Iram, Tal, Isobe, Taichi, Ives, Feather, Jones, Robert, Kao, Kevin S., Karkanias, Jim, Karnam, Guruswamy, Keller, Andreas, Kershner, Aaron M., Khoury, Nathalie, Kim, Seung K., Kiss, Bernhard M., Kong, William, Krasnow, Mark A., Kumar, Maya E., Kuo, Christin S., Lam, Jonathan Y., Leventhal, Olivia, Li, Guang, Li, Qingyun, Liu, Ling, Lo, Annie, Lu, Wan-Jin, Lugo-Fagundo, Maria F., Manjunath, Anoop, May, Andrew P., Maynard, Ashley, McKay, Marina, McNerney, M. Windy, Merrill, Bryan, Metzger, Ross J., Mignardi, Marco, Min, Dullei, Nabhan, Ahmad N., Neff, Norma F., Ng, Katharine M., Nguyen, Patricia K., Noh, Joseph, Nusse, Roel, Patkar, Rasika, Peng, Weng Chuan, Penland, Lolita, Pisco, Angela Oliveira, Pollard, Katherine, Puccinelli, Robert, Qi, Zhen, Quake, Stephen R., Rando, Thomas A., Rulifson, Eric J., Segal, Joe M., Sikandar, Shaheen S., Sinha, Rahul, Sonnenburg, Justin, Staehli, Daniel, Szade, Krzysztof, Tato, Cristina, Tellez, Krissie, Torrez Dulgeroff, Laughing Bear, Travaglini, Kyle J., Tropini, Carolina, Tsui, Margaret, Waldburger, Lucas, Wang, Bruce M., van Weele, Linda J., Weinberg, Kenneth, Weissman, Irving L., Wosczyna, Michael N., Wu, Sean M., Wyss-Coray, Tony, Xiang, Jinyi, Xue, Soso, Yamauchi, Kevin A., Yang, Andrew C., Yerra, Lakshmi P., Youngyunpipatkul, Justin, Yu, Brian, Zanini, Fabio, Zhao, Chunyu, Zhang, Fan, Zhang, Martin Jinye, Zhou, Lu, and Zou, James

Subjects
0301 basic medicine, Male, Aging, Time Factors, T-Lymphocytes, Plasma Cells, RNA-Seq, Biology, Article, Transcriptome, 03 medical and health sciences, Mice, 0302 clinical medicine, Gene expression, Animals, RNA, Messenger, Gene, Regulation of gene expression, Multidisciplinary, Blood Proteins, Cell biology, 030104 developmental biology, Proteostasis, Gene Expression Regulation, Ageing, Organ Specificity, Immunoglobulin J-Chains, Unfolded protein binding, Female, Single-Cell Analysis, 030217 neurology & neurosurgery
Abstract

Ageing is the single greatest cause of disease and death worldwide, and understanding the associated processes could vastly improve quality of life. Although major categories of ageing damage have been identified—such as altered intercellular communication, loss of proteostasis and eroded mitochondrial function1—these deleterious processes interact with extraordinary complexity within and between organs, and a comprehensive, whole-organism analysis of ageing dynamics has been lacking. Here we performed bulk RNA sequencing of 17 organs and plasma proteomics at 10 ages across the lifespan of Mus musculus, and integrated these findings with data from the accompanying Tabula Muris Senis2—or ‘Mouse Ageing Cell Atlas’—which follows on from the original Tabula Muris3. We reveal linear and nonlinear shifts in gene expression during ageing, with the associated genes clustered in consistent trajectory groups with coherent biological functions—including extracellular matrix regulation, unfolded protein binding, mitochondrial function, and inflammatory and immune response. Notably, these gene sets show similar expression across tissues, differing only in the amplitude and the age of onset of expression. Widespread activation of immune cells is especially pronounced, and is first detectable in white adipose depots during middle age. Single-cell RNA sequencing confirms the accumulation of T cells and B cells in adipose tissue—including plasma cells that express immunoglobulin J—which also accrue concurrently across diverse organs. Finally, we show how gene expression shifts in distinct tissues are highly correlated with corresponding protein levels in plasma, thus potentially contributing to the ageing of the systemic circulation. Together, these data demonstrate a similar yet asynchronous inter- and intra-organ progression of ageing, providing a foundation from which to track systemic sources of declining health at old age. Bulk RNA sequencing of organs and plasma proteomics at different ages across the mouse lifespan is integrated with data from the Tabula Muris Senis, a transcriptomic atlas of ageing mouse tissues, to describe organ-specific changes in gene expression during ageing.

Published
2020

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