Cross-Sectional Transcriptional Analysis of the Aging Murine Heart
Cardiovascular disease accounts for millions of deaths each year and is currently the leading cause of mortality worldwide. The aging process is clearly linked to cardiovascular disease, however, the exact relationship between aging and heart function is not fully understood. Furthermore, a holistic...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2020-09-01
|
| Series: | Frontiers in Molecular Biosciences |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fmolb.2020.565530/full |
| _version_ | 1818208211405111296 |
|---|---|
| author | Matthew Greenig Andrew Melville Derek Huntley Mark Isalan Mark Isalan Michal Mielcarek Michal Mielcarek |
| author_facet | Matthew Greenig Andrew Melville Derek Huntley Mark Isalan Mark Isalan Michal Mielcarek Michal Mielcarek |
| author_sort | Matthew Greenig |
| collection | DOAJ |
| description | Cardiovascular disease accounts for millions of deaths each year and is currently the leading cause of mortality worldwide. The aging process is clearly linked to cardiovascular disease, however, the exact relationship between aging and heart function is not fully understood. Furthermore, a holistic view of cardiac aging, linking features of early life development to changes observed in old age, has not been synthesized. Here, we re-purpose RNA-sequencing data previously-collected by our group, investigating gene expression differences between wild-type mice of different age groups that represent key developmental milestones in the murine lifespan. DESeq2's generalized linear model was applied with two hypothesis testing approaches to identify differentially-expressed (DE) genes, both between pairs of age groups and across mice of all ages. Pairwise comparisons identified genes associated with specific age transitions, while comparisons across all age groups identified a large set of genes associated with the aging process more broadly. An unsupervised machine learning approach was then applied to extract common expression patterns from this set of age-associated genes. Sets of genes with both linear and non-linear expression trajectories were identified, suggesting that aging not only involves the activation of gene expression programs unique to different age groups, but also the re-activation of gene expression programs from earlier ages. Overall, we present a comprehensive transcriptomic analysis of cardiac gene expression patterns across the entirety of the murine lifespan. |
| first_indexed | 2024-12-12T04:41:13Z |
| format | Article |
| id | doaj.art-dc2ee6487edd43af951ea85a6e437964 |
| institution | Directory Open Access Journal |
| issn | 2296-889X |
| language | English |
| last_indexed | 2024-12-12T04:41:13Z |
| publishDate | 2020-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Molecular Biosciences |
| spelling | doaj.art-dc2ee6487edd43af951ea85a6e4379642022-12-22T00:37:49ZengFrontiers Media S.A.Frontiers in Molecular Biosciences2296-889X2020-09-01710.3389/fmolb.2020.565530565530Cross-Sectional Transcriptional Analysis of the Aging Murine HeartMatthew Greenig0Andrew Melville1Derek Huntley2Mark Isalan3Mark Isalan4Michal Mielcarek5Michal Mielcarek6Department of Life Sciences, Imperial College London, London, United KingdomDepartment of Mathematics, Imperial College London, London, United KingdomDepartment of Life Sciences, Imperial College London, London, United KingdomDepartment of Life Sciences, Imperial College London, London, United KingdomImperial College Center for Synthetic Biology, Imperial College London, London, United KingdomDepartment of Life Sciences, Imperial College London, London, United KingdomImperial College Center for Synthetic Biology, Imperial College London, London, United KingdomCardiovascular disease accounts for millions of deaths each year and is currently the leading cause of mortality worldwide. The aging process is clearly linked to cardiovascular disease, however, the exact relationship between aging and heart function is not fully understood. Furthermore, a holistic view of cardiac aging, linking features of early life development to changes observed in old age, has not been synthesized. Here, we re-purpose RNA-sequencing data previously-collected by our group, investigating gene expression differences between wild-type mice of different age groups that represent key developmental milestones in the murine lifespan. DESeq2's generalized linear model was applied with two hypothesis testing approaches to identify differentially-expressed (DE) genes, both between pairs of age groups and across mice of all ages. Pairwise comparisons identified genes associated with specific age transitions, while comparisons across all age groups identified a large set of genes associated with the aging process more broadly. An unsupervised machine learning approach was then applied to extract common expression patterns from this set of age-associated genes. Sets of genes with both linear and non-linear expression trajectories were identified, suggesting that aging not only involves the activation of gene expression programs unique to different age groups, but also the re-activation of gene expression programs from earlier ages. Overall, we present a comprehensive transcriptomic analysis of cardiac gene expression patterns across the entirety of the murine lifespan.https://www.frontiersin.org/article/10.3389/fmolb.2020.565530/fullRNAseqtranscriptomicsheartagingcardiomyocytegene expression |
| spellingShingle | Matthew Greenig Andrew Melville Derek Huntley Mark Isalan Mark Isalan Michal Mielcarek Michal Mielcarek Cross-Sectional Transcriptional Analysis of the Aging Murine Heart Frontiers in Molecular Biosciences RNAseq transcriptomics heart aging cardiomyocyte gene expression |
| title | Cross-Sectional Transcriptional Analysis of the Aging Murine Heart |
| title_full | Cross-Sectional Transcriptional Analysis of the Aging Murine Heart |
| title_fullStr | Cross-Sectional Transcriptional Analysis of the Aging Murine Heart |
| title_full_unstemmed | Cross-Sectional Transcriptional Analysis of the Aging Murine Heart |
| title_short | Cross-Sectional Transcriptional Analysis of the Aging Murine Heart |
| title_sort | cross sectional transcriptional analysis of the aging murine heart |
| topic | RNAseq transcriptomics heart aging cardiomyocyte gene expression |
| url | https://www.frontiersin.org/article/10.3389/fmolb.2020.565530/full |
| work_keys_str_mv | AT matthewgreenig crosssectionaltranscriptionalanalysisoftheagingmurineheart AT andrewmelville crosssectionaltranscriptionalanalysisoftheagingmurineheart AT derekhuntley crosssectionaltranscriptionalanalysisoftheagingmurineheart AT markisalan crosssectionaltranscriptionalanalysisoftheagingmurineheart AT markisalan crosssectionaltranscriptionalanalysisoftheagingmurineheart AT michalmielcarek crosssectionaltranscriptionalanalysisoftheagingmurineheart AT michalmielcarek crosssectionaltranscriptionalanalysisoftheagingmurineheart |