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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, du Bois, Tessa Divita Haley, Ebadi, Hamid, Espinoza, F Hernan, Fish, Matt, Gan, Qiang, George, Benson M, Gillich, Astrid, Gomez-Sjoberg, 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, Palovics, Robert, 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, Sonnenburg, Justin, and Staehli, Daniel

Subjects
Biochemistry and Cell Biology, Biological Sciences, Genetics, Underpinning research, 1.1 Normal biological development and functioning, Generic health relevance, Aging, 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. Targeted alveolar regeneration with Frizzled-specific agonists

Author

Nabhan, Ahmad N., Webster, Joshua D., Adams, Jarret J., Blazer, Levi, Everrett, Christine, Eidenschenk, Celine, Arlantico, Alexander, Fleming, Isabel, Brightbill, Hans D., Wolters, Paul J., Modrusan, Zora, Seshagiri, Somasekar, Angers, Stephane, Sidhu, Sachdev S., Newton, Kim, Arron, Joseph R., and Dixit, Vishva M.

Published
2023
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3. 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 Hernan, 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, Sikandar, Shaheen S, Sinha, Rahul, Szade, Krzysztof, Tan, Weilun, Tato, Cristina, Tellez, Krissie, Travaglini, Kyle J, Tropini, Carolina, Waldburger, Lucas, van Weele, Linda J, Wosczyna, Michael N, Xiang, Jinyi, Xue, Soso, Youngyunpipatkul, Justin, Zardeneta, Macy E, Zhang, Fan, Zhou, Lu, Castro, Paola, Croote, Derek, DeRisi, Joseph L, Kuo, Christin S, and Lehallier, Benoit

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

4. Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics

Author

Muus, Christoph, Luecken, Malte D., Eraslan, Gökcen, Sikkema, Lisa, Waghray, Avinash, Heimberg, Graham, Kobayashi, Yoshihiko, Vaishnav, Eeshit Dhaval, Subramanian, Ayshwarya, Smillie, Christopher, Jagadeesh, Karthik A., Duong, Elizabeth Thu, Fiskin, Evgenij, Torlai Triglia, Elena, Ansari, Meshal, Cai, Peiwen, Lin, Brian, Buchanan, Justin, Chen, Sijia, Shu, Jian, Haber, Adam L., Chung, Hattie, Montoro, Daniel T., Adams, Taylor, Aliee, Hananeh, Allon, Samuel J., Andrusivova, Zaneta, Angelidis, Ilias, Ashenberg, Orr, Bassler, Kevin, Bécavin, Christophe, Benhar, Inbal, Bergenstråhle, Joseph, Bergenstråhle, Ludvig, Bolt, Liam, Braun, Emelie, Bui, Linh T., Callori, Steven, Chaffin, Mark, Chichelnitskiy, Evgeny, Chiou, Joshua, Conlon, Thomas M., Cuoco, Michael S., Cuomo, Anna S. E., Deprez, Marie, Duclos, Grant, Fine, Denise, Fischer, David S., Ghazanfar, Shila, Gillich, Astrid, Giotti, Bruno, Gould, Joshua, Guo, Minzhe, Gutierrez, Austin J., Habermann, Arun C., Harvey, Tyler, He, Peng, Hou, Xiaomeng, Hu, Lijuan, Hu, Yan, Jaiswal, Alok, Ji, Lu, Jiang, Peiyong, Kapellos, Theodoros S., Kuo, Christin S., Larsson, Ludvig, Leney-Greene, Michael A., Lim, Kyungtae, Litviňuková, Monika, Ludwig, Leif S., Lukassen, Soeren, Luo, Wendy, Maatz, Henrike, Madissoon, Elo, Mamanova, Lira, Manakongtreecheep, Kasidet, Leroy, Sylvie, Mayr, Christoph H., Mbano, Ian M., McAdams, Alexi M., Nabhan, Ahmad N., Nyquist, Sarah K., Penland, Lolita, Poirion, Olivier B., Poli, Sergio, Qi, CanCan, Queen, Rachel, Reichart, Daniel, Rosas, Ivan, Schupp, Jonas C., Shea, Conor V., Shi, Xingyi, Sinha, Rahul, Sit, Rene V., Slowikowski, Kamil, Slyper, Michal, Smith, Neal P., Sountoulidis, Alex, Strunz, Maximilian, Sullivan, Travis B., Sun, Dawei, Talavera-López, Carlos, Tan, Peng, Tantivit, Jessica, Travaglini, Kyle J., Tucker, Nathan R., Vernon, Katherine A., Wadsworth, Marc H., Waldman, Julia, Wang, Xiuting, Xu, Ke, Yan, Wenjun, Zhao, William, and Ziegler, Carly G. K.

Published
2021
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5. A molecular cell atlas of the human lung from single-cell RNA sequencing

Author

Travaglini, Kyle J., Nabhan, Ahmad N., Penland, Lolita, Sinha, Rahul, Gillich, Astrid, Sit, Rene V., and Chang, Stephen

Subjects
RNA sequencing -- Methods, Molecular biology -- Analysis, Lungs -- Physiological aspects, Cells -- Identification and classification, Atlases -- Usage, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Although single-cell RNA sequencing studies have begun to provide compendia of cell expression profiles.sup.1-9, it has been difficult to systematically identify and localize all molecular cell types in individual organs to create a full molecular cell atlas. Here, using droplet- and plate-based single-cell RNA sequencing of approximately 75,000 human cells across all lung tissue compartments and circulating blood, combined with a multi-pronged cell annotation approach, we create an extensive cell atlas of the human lung. We define the gene expression profiles and anatomical locations of 58 cell populations in the human lung, including 41 out of 45 previously known cell types and 14 previously unknown ones. This comprehensive molecular atlas identifies the biochemical functions of lung cells and the transcription factors and markers for making and monitoring them; defines the cell targets of circulating hormones and predicts local signalling interactions and immune cell homing; and identifies cell types that are directly affected by lung disease genes and respiratory viruses. By comparing human and mouse data, we identified 17 molecular cell types that have been gained or lost during lung evolution and others with substantially altered expression profiles, revealing extensive plasticity of cell types and cell-type-specific gene expression during organ evolution including expression switches between cell types. This atlas provides the molecular foundation for investigating how lung cell identities, functions and interactions are achieved in development and tissue engineering and altered in disease and evolution. Expression profiling on 75,000 single cells creates a comprehensive cell atlas of the human lung that includes 41 out of 45 previously known cell types and 14 new ones., Author(s): Kyle J. Travaglini [sup.1] [sup.2] , Ahmad N. Nabhan [sup.1] [sup.2] [sup.12] , Lolita Penland [sup.3] [sup.13] , Rahul Sinha [sup.4] [sup.5] , Astrid Gillich [sup.1] [sup.2] , Rene [...]

Published
2020
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7. Molecular hallmarks of heterochronic parabiosis at single-cell resolution

Author

Pálovics, Róbert, Keller, Andreas, Schaum, Nicholas, Tan, Weilun, Fehlmann, Tobias, Borja, Michael, Kern, Fabian, Bonanno, Liana, Calcuttawala, Kruti, Webber, James, McGeever, Aaron, 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 K. F., Chen, Michelle B., Clarke, Michael F., Conley, Stephanie D., 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., Karnam, Guruswamy, 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, McKay, Marina, McNerney, M. Windy, Merrill, Bryan, Metzger, Ross J., Mignardi, Marco, Min, Dullei, Nabhan, Ahmad N., Ng, Katharine M., Nguyen, Patricia K., Noh, Joseph, Nusse, Roel, Patkar, Rasika, Peng, Weng Chuan, Penland, Lolita, Pollard, Katherine, Puccinelli, Robert, Qi, Zhen, Rando, Thomas A., Rulifson, Eric J., Segal, Joe M., Sikandar, Shaheen S., Sinha, Rahul, Sit, Rene V., Sonnenburg, Justin, Staehli, Daniel, Szade, Krzysztof, Tan, Michelle, 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., Xiang, Jinyi, Xue, Soso, Yamauchi, Kevin A., Yang, Andrew C., Yerra, Lakshmi P., Youngyunpipatkul, Justin, Yu, Brian, Zanini, Fabio, Zardeneta, Macy E., Zee, Alexander, Zhao, Chunyu, Zhang, Fan, Zhang, Hui, Zhang, Martin Jinye, Zhou, Lu, Zou, James, Luo, Jian, Pisco, Angela Oliveira, Karkanias, Jim, Neff, Norma F., Darmanis, Spyros, Quake, Stephen R., and Wyss-Coray, Tony

Subjects
Aging, Multidisciplinary, Parabiosis, Mesenchymal Stem Cells, Hematopoietic Stem Cells, Article, Organ Specificity/genetics, Mitochondria, Electron Transport, Electron Transport/genetics, Organ Specificity, Aging/genetics, Adipocytes, Hepatocytes, Rejuvenation, RNA-Seq, Single-Cell Analysis
Abstract

The ability to slow or reverse biological ageing would have major implications for mitigating disease risk and maintaining vitality1. Although an increasing number of interventions show promise for rejuvenation2, their effectiveness on disparate cell types across the body and the molecular pathways susceptible to rejuvenation remain largely unexplored. Here we performed single-cell RNA sequencing on 20 organs to reveal cell-type-specific responses to young and aged blood in heterochronic parabiosis. Adipose mesenchymal stromal cells, haematopoietic stem cells and hepatocytes are among those cell types that are especially responsive. On the pathway level, young blood invokes new gene sets in addition to reversing established ageing patterns, with the global rescue of genes encoding electron transport chain subunits pinpointing a prominent role of mitochondrial function in parabiosis-mediated rejuvenation. We observed an almost universal loss of gene expression with age that is largely mimicked by parabiosis: aged blood reduces global gene expression, and young blood restores it in select cell types. Together, these data lay the groundwork for a systemic understanding of the interplay between blood-borne factors and cellular integrity.

Published
2022

8. 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

10. A molecular cell atlas of the human lung from single cell RNA sequencing

Author

Travaglini, Kyle J., primary, Nabhan, Ahmad N., additional, Penland, Lolita, additional, Sinha, Rahul, additional, Gillich, Astrid, additional, Sit, Rene V., additional, Chang, Stephen, additional, Conley, Stephanie D., additional, Mori, Yasuo, additional, Seita, Jun, additional, Berry, Gerald J., additional, Shrager, Joseph B., additional, Metzger, Ross J., additional, Kuo, Christin S., additional, Neff, Norma, additional, Weissman, Irving L., additional, Quake, Stephen R., additional, and Krasnow, Mark A., additional

Published
2019
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11. Single-cell transcriptomic characterization of 20 organs and tissues from individual mice creates a Tabula Muris

Author

Schaum, Nicholas, primary, Karkanias, Jim, additional, Neff, Norma F, additional, May, Andrew P., additional, Quake, Stephen R., additional, Wyss-Coray, Tony, additional, Darmanis, Spyros, additional, Batson, Joshua, additional, Botvinnik, Olga, additional, Chen, Michelle B., additional, Chen, Steven, additional, Green, Foad, additional, Jones, Robert, additional, Maynard, Ashley, additional, Penland, Lolita, additional, Sit, Rene V., additional, Stanley, Geoffrey M., additional, Webber, James T., additional, Zanini, Fabio, additional, Baghel, Ankit S., additional, Bakerman, Isaac, additional, Bansal, Ishita, additional, Berdnik, Daniela, additional, Bilen, Biter, additional, Brownfield, Douglas, additional, Cain, Corey, additional, Cho, Min, additional, Cirolia, Giana, additional, Conley, Stephanie D., additional, Demers, Aaron, additional, Demir, Kubilay, additional, Morree, Antoine de, additional, Divita, Tessa, additional, Bois, Haley du, additional, Dulgeroff, Laughing Bear Torrez, additional, Ebadi, Hamid, additional, Espinoza, F. Hernan, additional, Fish, Matt, additional, Gan, Qiang, additional, George, Benson M., additional, Gillich, Astrid, additional, Genetiano, Geraldine, additional, Gu, Xueying, additional, Gulati, Gunsagar S., additional, Hang, Yan, additional, Hosseinzadeh, Shayan, additional, Huang, Albin, additional, Iram, Tal, additional, Isobe, Taichi, additional, Ives, Feather, additional, Kao, Kevin S., additional, Karnam, Guruswamy, additional, Kershner, Aaron M., additional, Kiss, Bernhard, additional, Kong, William, additional, Kumar, Maya E., additional, Lam, Jonathan, additional, Lee, Davis P., additional, Lee, Song E., additional, Li, Guang, additional, Li, Qingyun, additional, Liu, Ling, additional, Lo, Annie, additional, Lu, Wan-Jin, additional, Manjunath, Anoop, additional, May, Kaia L., additional, May, Oliver L., additional, McKay, Marina, additional, Metzger, Ross J., additional, Mignardi, Marco, additional, Min, Dullei, additional, Nabhan, Ahmad N., additional, Ng, Katharine M., additional, Noh, Joseph, additional, Patkar, Rasika, additional, Peng, Weng Chuan, additional, Puccinelli, Robert, additional, Rulifson, Eric J., additional, Schaum, Nicholas, additional, Sikandar, Shaheen S., additional, Sinha, Rahul, additional, Sit, Rene V, additional, Szade, Krzysztof, additional, Tan, Weilun, additional, Tato, Cristina, additional, Tellez, Krissie, additional, Travaglini, Kyle J., additional, Tropini, Carolina, additional, Waldburger, Lucas, additional, Weele, Linda J. van, additional, Wosczyna, Michael N., additional, Xiang, Jinyi, additional, Xue, Soso, additional, Youngyunpipatkul, Justin, additional, Zardeneta, Macy E., additional, Zhang, Fan, additional, Zhou, Lu, additional, Neff, Norma F., additional, Castro, Paola, additional, Croote, Derek, additional, DeRisi, Joseph L., additional, Pisco, Angela, additional, Kiss, Bernhard M., additional, Kuo, Christin S., additional, Lehallier, Benoit, additional, Nguyen, Patricia K., additional, Tan, Serena Y., additional, Wang, Bruce M., additional, Yousef, Hanadie, additional, Beachy, Philip A., additional, Chan, Charles K. F., additional, Huang, Kerwyn Casey, additional, Weinberg, Kenneth, additional, Wu, Sean, additional, Barres, Ben A., additional, Clarke, Michael F., additional, Kim, Seung K., additional, Krasnow, Mark A., additional, Neff, Norma, additional, Nusse, Roel, additional, Rando, Thomas A., additional, Sonnenburg, Justin, additional, Weissman, Irving L., additional, and Wu, Sean M., additional

Published
2017
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12. Index switching causes “spreading-of-signal” among multiplexed samples in Illumina HiSeq 4000 DNA sequencing

Author

Sinha, Rahul, primary, Stanley, Geoff, additional, Gulati, Gunsagar S., additional, Ezran, Camille, additional, Travaglini, Kyle J., additional, Wei, Eric, additional, Chan, Charles K.F., additional, Nabhan, Ahmad N., additional, Su, Tianying, additional, Morganti, Rachel M., additional, Conley, Stephanie D., additional, Chaib, Hassan, additional, Red-Horse, Kristy, additional, Longaker, Michael T., additional, Snyder, Michael P., additional, Krasnow, Mark A., additional, and Weissman, Irving L., additional

Published
2017
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13. Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics

Author

Christoph, Muus, Luecken , Malte D., Gökcen, Eraslan, Lisa, Sikkema, Avinash, Waghray, Graham, Heimberg, Yoshihiko, Kobayashi, Eeshit Dhaval Vaishnav, Ayshwarya, Subramanian, Christopher, Smillie, Jagadeesh, Karthik A., Elizabeth Thu Duong, Evgenij, Fiskin, Elena Torlai Triglia, Meshal, Ansari, Peiwen, Cai, Brian, Lin, Justin, Buchanan, Sijia, Chen, Jian, Shu, Haber, Adam L., Hattie, Chung, Montoro, Daniel T., Taylor, Adams, Hananeh, Aliee, Allon, Samuel J., Zaneta, Andrusivova, Ilias, Angelidis, Orr, Ashenberg, Kevin, Bassler, Christophe, Bécavin, Inbal, Benhar, Joseph, Bergenstråhle, Ludvig, Bergenstråhle, Liam, Bolt, Emelie, Braun, Bui, Linh T., Steven, Callori, Mark, Chaffin, Evgeny, Chichelnitskiy, Joshua, Chiou, Conlon, Thomas M., Cuoco, Michael S., Cuomo, Anna S. E., Marie, Deprez, Grant, Duclos, Denise, Fine, Fischer, David S., Shila, Ghazanfar, Astrid, Gillich, Bruno, Giotti, Joshua, Gould, Minzhe, Guo, Gutierrez, Austin J., Habermann, Arun C., Tyler, Harvey, Peng, He, Xiaomeng, Hou, Lijuan, Hu, Yan, Hu, Alok, Jaiswal, Lu, Ji, Peiyong, Jiang, Kapellos, Theodoros S., Kuo, Christin S., Ludvig, Larsson, Leney-Greene, Michael A., Kyungtae, Lim, Monika, Litviňuková, Ludwig, Leif S., Soeren, Lukassen, Wendy, Luo, Henrike, Maatz, Elo, Madissoon, Lira, Mamanova, Kasidet, Manakongtreecheep, Sylvie, Leroy, Mayr, Christoph H., Mbano, Ian M., Mcadams, Alexi M., Nabhan, Ahmad N., Nyquist, Sarah K., Lolita, Penland, Poirion, Olivier B., Sergio, Poli, Cancan, Qi, Rachel, Queen, Daniel, Reichart, Ivan, Rosas, Schupp, Jonas C., Shea, Conor V., Xingyi, Shi, Rahul, Sinha, Sit, Rene V., Kamil, Slowikowski, Michal, Slyper, Smith, Neal P., Alex, Sountoulidis, Maximilian, Strunz, Sullivan, Travis B., Dawei, Sun, Carlos, Talavera-López, Peng, Tan, Jessica, Tantivit, Travaglini, Kyle J., Tucker, Nathan R., Vernon, Katherine A., Wadsworth, Marc H., Julia, Waldman, Xiuting, Wang, Ke, Xu, Wenjun, Yan, William, Zhao, Ziegler, Carly G. K., The NHLBI LungMap Consortium, Zerti, Darin, The Human Cell Atlas Lung Biological Network, and Groningen Research Institute for Asthma and COPD (GRIAC)

Subjects
0301 basic medicine, Male, Cathepsin L, Respiratory System, Datasets as Topic, Lung/metabolism, Sequence Analysis, RNA/methods, Organ Specificity/genetics, 0302 clinical medicine, 80 and over, Respiratory system, Lung, COVID-19/epidemiology, Aged, 80 and over, Serine Endopeptidases, General Medicine, respiratory system, Middle Aged, Host-Pathogen Interactions/genetics, 3. Good health, Angiotensin-Converting Enzyme 2/genetics, medicine.anatomical_structure, Datasets as Topic/statistics & numerical data, Respiratory System/metabolism, Organ Specificity, Cathepsin L/genetics, 030220 oncology & carcinogenesis, Host-Pathogen Interactions, Tumor necrosis factor alpha, Female, Angiotensin-Converting Enzyme 2, Single-Cell Analysis, RNA/methods, Sequence Analysis, Adult, Alveolar Epithelial Cells/metabolism, Serine Endopeptidases/genetics, Biology, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Immune system, Viral entry, Parenchyma, medicine, Humans, Gene Expression Profiling/statistics & numerical data, Aged, Demography, SARS-CoV-2, Sequence Analysis, RNA, Gene Expression Profiling, Single-Cell Analysis/methods, COVID-19, Virus Internalization, Gene expression profiling, 030104 developmental biology, Alveolar Epithelial Cells, Immunology, Tissue tropism, SARS-CoV-2/physiology
Abstract

Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.

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