scholarly journals Mosaic loss of chromosome Y in aged human microglia.

2021 ◽  
Author(s):  
Michael C Vermeulen ◽  
Richard Pearse ◽  
Tracy Young-Pearse ◽  
Sara Mostafavi
Keyword(s):  
Antigen Processing ◽  
Gene Expression Analysis ◽  
Lipoprotein Metabolism ◽  
Cell Types ◽  
Chromosome Y ◽  
Human Microglia ◽  
Age Related ◽  
Aging Men ◽  
Cell Type Specific ◽  
Differential Gene

Mosaic loss of chromosome Y (LOY) is a particularly common acquired structural mutation in the leukocytes of aging men and it has been shown to correlate with several age-related diseases including Alzheimer's disease (AD). To derive the molecular basis of LOY in brain cells, we create an integrated resource by aggregating data from 21 single-cell and single-nuclei RNA brain studies, yielding 763,410 cells to investigate the presence and cell-type specific burden of LOY. We created robust quantification metrics for assessing LOY, which were validated using a multi-modal dataset. Using this new resource and LOY-quantification approach, we found that LOY frequencies differed widely between CNS cell-types and individual donors. Among five common neural cell types, microglia were most affected by LOY (7.79%, n=41,949), while LOY in neurons was rare (0.48%, n=220,010). Differential gene expression analysis in microglia found 188 autosomal genes, 6 X-linked genes, and 11 pseudoautosomal genes, pointing to broad dysregulation in lipoprotein metabolism, inflammatory response, and antigen processing that coincides with loss of Y. To our knowledge, we provide the first evidence of LOY in the microglia, and highlight its potential roles in aging and the pathogenesis of neurodegenerative disorders such as AD.

scholarly journals Transcriptional profiling predicts running promotes cerebrovascular remodeling in young but not midlife mice

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Kate E. Foley ◽  
Hongtian Stanley Yang ◽  
Leah C. Graham ◽  
Gareth R. Howell
Keyword(s):  
Cognitive Decline ◽  
Transcriptional Profiling ◽  
Cell Types ◽  
Brain Health ◽  
New Approach ◽  
Age Related ◽  
Voluntary Running ◽  
Differential Gene ◽  
Age Related Cognitive Decline ◽  
Potential Therapeutic Intervention

Abstract Background The incidence of dementia and cognitive decline is increasing with no therapy or cure. One of the reasons treatment remains elusive is because there are various pathologies that contribute to age-related cognitive decline. Specifically, with Alzheimer’s disease, targeting to reduce amyloid beta plaques and phosphorylated tau aggregates in clinical trials has not yielded results to slow symptomology, suggesting a new approach is needed. Interestingly, exercise has been proposed as a potential therapeutic intervention to improve brain health and reduce the risk for dementia, however the benefits throughout aging are not well understood. Results To better understand the effects of exercise, we preformed transcriptional profiling on young (1–2 months) and midlife (12 months) C57BL/6 J (B6) male mice after 12 weeks of voluntary running. Data was compared to age-matched sedentary controls. Interestingly, the midlife running group naturally broke into two cohorts based on distance ran - either running a lot and more intensely (high runners) or running less and less intensely (low runners). Midlife high runners had lower LDL cholesterol as well as lower adiposity (%fat) compared to sedentary, than midlife low runners compared to sedentary suggesting more intense running lowered systemic markers of risk for age-related diseases including dementias. Differential gene analysis of transcriptional profiles generated from the cortex and hippocampus showed thousands of differentially expressed (DE) genes when comparing young runners to sedentary controls. However, only a few hundred genes were DE comparing either midlife high runners or midlife low runners to midlife sedentary controls. This indicates that, in our study, the effects of running are reduced through aging. Gene set enrichment analyses identified enrichment of genes involved in extracellular matrix (ECM), vascular remodeling and angiogenesis in young runners but not midlife runners. These genes are known to be expressed in multiple vascular-related cell types including astrocytes, endothelial cells, pericytes and smooth muscle cells. Conclusions Taken together these results suggest running may best serve as a preventative measure to reduce risk for cerebrovascular decline. Ultimately, this work shows that exercise may be more effective to prevent dementia if introduced at younger ages.

scholarly journals Transcriptional profiling reveals running promotes cerebrovascular remodeling in young but not aged mice

2019 ◽  
Author(s):  
Kate E. Foley ◽  
Stanley Yang ◽  
Leah C. Graham ◽  
Gareth R. Howell
Keyword(s):  
Cognitive Decline ◽  
Transcriptional Profiling ◽  
Cell Types ◽  
Brain Health ◽  
New Approach ◽  
Age Related ◽  
Voluntary Running ◽  
Differential Gene ◽  
Age Related Cognitive Decline ◽  
Potential Therapeutic Intervention

AbstractBackgroundThe incidence of dementia and cognitive decline is increasing with no therapy or cure. One of the reasons treatment remains elusive is because there are various pathologies that contribute to age-related cognitive decline. Specifically, with Alzheimer’s disease, targeting to reduce amyloid beta plaques and phosphorylated tau aggregates in clinical trials has not yielded results to slow symptomology, suggesting a new approach is needed. Interestingly, exercise has been proposed as a potential therapeutic intervention to improve brain health and reduce the risk for dementia, however the benefits throughout aging are not well understood.ResultsTo better understand the effects of exercise, we preformed transcriptional profiling on young (1-2 months) and midlife (12 months) C57BL/6J (B6) male mice after 12 weeks of voluntary running. Data was compared to age-matched sedentary controls. Interestingly, the midlife running group naturally broke into two cohorts based on distance ran - either running a lot and more intensely (high runners) or running less and less intensely (low runners). Midlife high runners had lower LDL cholesterol as well as lower adiposity (%fat) compared to sedentary, than midlife low runners compared to sedentary suggesting more intense running lowered systemic markers of risk for age-related diseases including dementias. Differential gene analysis of transcriptional profiles generated from the cortex and hippocampus showed thousands of differentially expressed (DE) genes when comparing young runners to sedentary controls. However, only a few hundred genes were DE comparing either midlife high runners or midlife low runners to midlife sedentary controls. This indicates that, in our study, the effects of running are reduced through aging. Gene set enrichment analyses identified enrichment of genes involved in extracellular matrix (ECM), vascular remodeling and angiogenesis in young runners but not midlife runners. These genes are known to be expressed in multiple vascular-related cell types including astrocytes, endothelial cells, pericytes and smooth muscle cells.ConclusionsTaken together these results suggest running may best serve as a preventative measure to reduce risk for cerebrovascular decline. Ultimately, this work shows that exercise may be more effective to prevent dementia if introduced at younger ages.

scholarly journals A Single Cell Transcriptomic Atlas Characterizes Aging Tissues in the Mouse

2019 ◽  
Author(s):  
◽  
Angela Oliveira Pisco ◽  
Aaron McGeever ◽  
Nicholas Schaum ◽  
Jim Karkanias ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Cell Type ◽  
Cellular Processes ◽  
Progressive Loss ◽  
Age Related ◽  
Multiple Cell ◽  
Cell Type Specific ◽  
Molecular Information ◽  
Insight Into

AbstractAging 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 which underlie progressive loss of healthy physiology are poorly understood2. To gain a better insight into these processes we have created a single cell transcriptomic atlas across the life span of Mus musculus which includes data from 23 tissues and organs. We discovered 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 were able to assess cell type specific manifestations of different hallmarks of aging, such as senescence3, genomic instability4 and changes in the organism’s immune system2. This Tabula Muris Senis provides a wealth of new molecular information about how the most significant hallmarks of aging are reflected in a broad range of tissues and cell types.

scholarly journals Mouse Aging Cell Atlas Analysis Reveals Global and Cell Type Specific Aging Signatures Revision 1

2019 ◽  
Author(s):  
Martin Jinye Zhang ◽  
Angela Oliveira Pisco ◽  
Spyros Darmanis ◽  
James Zou
Keyword(s):  
Cell Types ◽  
Tissue Cell ◽  
Rna Seq ◽  
Cell Type ◽  
Cellular Processes ◽  
Age Related ◽  
Cell Type Specific ◽  
Global Aging ◽  
Mammalian System ◽  
Aging Cell

ABSTRACTAging is associated with complex molecular and cellular processes that are poorly understood. Here we leveraged the Tabula Muris Senis single-cell RNA-seq dataset to systematically characterize gene expression changes during aging across diverse cell types in the mouse. We identified aging-dependent genes in 76 tissue-cell types from 23 tissues and characterized both shared and tissue-cell-specific aging behaviors. We found that the aging-related genes shared by multiple tissue-cell types also change their expression congruently in the same direction during aging in most tissue-cell types, suggesting a coordinated global aging behavior at the organismal level. Scoring cells based on these shared aging genes allowed us to contrast the aging status of different tissues and cell types from a transcriptomic perspective. In addition, we identified genes that exhibit age-related expression changes specific to each functional category of tissue-cell types. All together, our analyses provide one of the most comprehensive and systematic characterizations of the molecular signatures of aging across diverse tissue-cell types in a mammalian system.

scholarly journals Mouse aging cell atlas analysis reveals global and cell type-specific aging signatures

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Martin Jinye Zhang ◽  
Angela Oliveira Pisco ◽  
Spyros Darmanis ◽  
James Zou
Keyword(s):  
Cell Types ◽  
Tissue Cell ◽  
Rna Seq ◽  
Data Set ◽  
Cellular Processes ◽  
Age Related ◽  
Cell Type Specific ◽  
Global Aging ◽  
Mammalian System ◽  
Aging Cell

Aging is associated with complex molecular and cellular processes that are poorly understood. Here we leveraged the Tabula Muris Senis single-cell RNA-seq data set to systematically characterize gene expression changes during aging across diverse cell types in the mouse. We identified aging-dependent genes in 76 tissue-cell types from 23 tissues and characterized both shared and tissue-cell-specific aging behaviors. We found that the aging-related genes shared by multiple tissue-cell types also change their expression congruently in the same direction during aging in most tissue-cell types, suggesting a coordinated global aging behavior at the organismal level. Scoring cells based on these shared aging genes allowed us to contrast the aging status of different tissues and cell types from a transcriptomic perspective. In addition, we identified genes that exhibit age-related expression changes specific to each functional category of tissue-cell types. Altogether, our analyses provide one of the most comprehensive and systematic characterizations of the molecular signatures of aging across diverse tissue-cell types in a mammalian system.

scholarly journals Bayesian Modeling of Epigenetic Variation in Multiple Human Cell Types

2015 ◽  
Author(s):  
Yu Zhang ◽  
Feng Yue ◽  
Ross C. Hardison
Keyword(s):  
High Throughput Sequencing ◽  
Cell Types ◽  
Differential Regulation ◽  
Epigenetic Variation ◽  
Data Sets ◽  
Sequencing Data ◽  
High Throughput Sequencing Data ◽  
Multiple Cell ◽  
Cell Type Specific ◽  
Differential Gene

With high-throughput sequencing data generated for multiple epigenetic features in many cell types, a chief challenge is to explain the dynamics in multiple epigenomes that lead to differential regulation and phenotypes. We introduce a Bayesian framework for jointly annotating multiple epigenomes and detecting differential regulation among multiple cell types. Our method, IDEAS (integrative and discriminative epigenome annotation system), achieves superior power by modeling both position and cell type specific epigenetic activities. Using ENCODE data sets in 6 cell types, we identified epigenetic variation strongly associated with differential gene expression. The detected regions are significantly enriched in disease genetic variants with much stronger enrichment scores than achievable by existing methods, and the enriched phenotypes are highly relevant to the corresponding cell types. IDEAS is a powerful tool for integrative epigenome annotation and detection of variation, which could be of important utility in elucidating the interplay between genetics, gene regulation and diseases.

scholarly journals Cell type-specific differential expression for spatial transcriptomics

2021 ◽  
Author(s):  
Dylan M Cable ◽  
Evan Murray ◽  
Vignesh Shanmugam ◽  
Simon Zhang ◽  
Michael Z Diao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Differential Gene Expression ◽  
Cell Types ◽  
Specific Cell ◽  
Cell Type ◽  
Unified Framework ◽  
Wide Range ◽  
Cell Type Specific ◽  
Differential Gene

Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. There is a pressing need for computational tools to enable the detection of genes that are differentially expressed across tissue context for cell types of interest. However, changes in cell type composition across space and the fact that measurement units often detect transcripts from more than one cell type introduce complex statistical challenges. Here, we introduce a statistical method, Robust Cell Type Differential Expression (RCTDE), that estimates cell type-specific patterns of differential gene expression while accounting for localization of other cell types. By using general log-linear models, we provide a unified framework for defining and identifying gene expression changes for a wide-range of relevant contexts: changes due to pathology, anatomical regions, physical proximity to specific cell types, and cellular microenvironment. Furthermore, our approach enables statistical inference across multiple samples and replicates when such data is available. We demonstrate, through simulations and validation experiments on Slide-seq and MERFISH datasets, that our approach accurately identifies cell type-specific differential gene expression and provides valid uncertainty quantification. Lastly, we apply our method to characterize spatially-localized tissue changes in the context of disease. In an Alzheimer's mouse model Slide-seq dataset, we identify plaque-dependent patterns of cellular immune activity. We also find a putative interaction between tumor cells and myeloid immune cells in a Slide-seq tumor dataset. We make our RCTDE method publicly available as part of the open source R package https://github.com/dmcable/spacexr.

Neuronal mRNA Translation in Addiction

2018 ◽  
Author(s):  
Emma Puighermanal ◽  
Emmanuel Valjent
Keyword(s):  
Structural Changes ◽  
Drugs Of Abuse ◽  
Mrna Translation ◽  
Cell Types ◽  
Behavioral Changes ◽  
Translational Machinery ◽  
Addictive Drugs ◽  
Specific Mrnas ◽  
Cell Type Specific ◽  
Future Work

Addictive drugs trigger persistent synaptic and structural changes in the neuronal reward circuits that are thought to underlie the development of drug-adaptive behavior. While transcriptional and epigenetic modifications are known to contribute to these circuit changes, accumulating evidence indicates that altered mRNA translation is also a key molecular mechanism. This chapter reviews recent studies demonstrating how addictive drugs alter protein synthesis and/or the translational machinery and how this leads to neuronal circuit remodeling and behavioral changes. Future work will determine precisely which neuronal circuits and cell types participate in these changes. The chapter summarizes current methodologies for identifying cell type-specific mRNAs whose translation is affected by drugs of abuse and gives recent examples of the mechanistic insights into addiction they provide.

Sign in / Sign up

Export Citation Format

Share Document