Literature DB >> 35930447

Proteogenomics reveals sex-biased aging genes and coordinated splicing in cardiac aging.

Yu Han1, Sara A Wennersten1, Julianna M Wright1, R W Ludwig1, Edward Lau, Maggie P Y Lam1,2.   

Abstract

The risks of heart diseases are significantly modulated by age and sex, but how these factors influence baseline cardiac gene expression remains incompletely understood. Here, we used RNA sequencing and mass spectrometry to compare gene expression in female and male young adult (4 mo) and early aging (20 mo) mouse hearts, identifying thousands of age- and sex-dependent gene expression signatures. Sexually dimorphic cardiac genes are broadly distributed, functioning in mitochondrial metabolism, translation, and other processes. In parallel, we found over 800 genes with differential aging response between male and female, including genes in cAMP and PKA signaling. Analysis of the sex-adjusted aging cardiac transcriptome revealed a widespread remodeling of exon usage patterns that is largely independent from differential gene expression, concomitant with upstream changes in RNA-binding protein and splice factor transcripts. To evaluate the impact of the splicing events on cardiac proteoform composition, we applied an RNA-guided proteomics computational pipeline to analyze the mass spectrometry data and detected hundreds of putative splice variant proteins that have the potential to rewire the cardiac proteome. Taken together, the results here suggest that cardiac aging is associated with 1) widespread sex-biased aging genes and 2) a rewiring of RNA splicing programs, including sex- and age-dependent changes in exon usages and splice patterns that have the potential to influence cardiac protein structure and function. These changes contribute to the emerging evidence for considerable sexual dimorphism in the cardiac aging process that should be considered in the search for disease mechanisms.NEW & NOTEWORTHY Han et al. used proteogenomics to compare male and female mouse hearts at 4 and 20 mo. Sex-biased cardiac genes function in mitochondrial metabolism, translation, autophagy, and other processes. Hundreds of cardiac genes show sex-by-age interactions, that is, sex-biased aging genes. Cardiac aging is accompanied with a remodeling of exon usage in functionally coordinated genes, concomitant with differential expression of RNA-binding proteins and splice factors. These features represent an underinvestigated aspect of cardiac aging that may be relevant to the search for disease mechanisms.

Entities:  

Keywords:  aging; alternative splicing; proteoforms; proteogenomics; sex difference

Mesh:

Substances:

Year:  2022        PMID: 35930447      PMCID: PMC9448281          DOI: 10.1152/ajpheart.00244.2022

Source DB:  PubMed          Journal:  Am J Physiol Heart Circ Physiol        ISSN: 0363-6135            Impact factor:   5.125


  100 in total

1.  Sample preparation and digestion for proteomic analyses using spin filters.

Authors:  Linda L Manza; Sheryl L Stamer; Amy-Joan L Ham; Simona G Codreanu; Daniel C Liebler
Journal:  Proteomics       Date:  2005-05       Impact factor: 3.984

2.  Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt.

Authors:  Steffen Durinck; Paul T Spellman; Ewan Birney; Wolfgang Huber
Journal:  Nat Protoc       Date:  2009-07-23       Impact factor: 13.491

3.  Transcriptome and Functional Profile of Cardiac Myocytes Is Influenced by Biological Sex.

Authors:  Christa L Trexler; Aaron T Odell; Mark Y Jeong; Robin D Dowell; Leslie A Leinwand
Journal:  Circ Cardiovasc Genet       Date:  2017-10

4.  Determining Alternative Protein Isoform Expression Using RNA Sequencing and Mass Spectrometry.

Authors:  Yu Han; Julianna M Wright; Edward Lau; Maggie Pui Yu Lam
Journal:  STAR Protoc       Date:  2020-10-21

5.  Large Scale Gene Expression Meta-Analysis Reveals Tissue-Specific, Sex-Biased Gene Expression in Humans.

Authors:  Benjamin T Mayne; Tina Bianco-Miotto; Sam Buckberry; James Breen; Vicki Clifton; Cheryl Shoubridge; Claire T Roberts
Journal:  Front Genet       Date:  2016-10-13       Impact factor: 4.599

6.  MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics.

Authors:  Andy T Kong; Felipe V Leprevost; Dmitry M Avtonomov; Dattatreya Mellacheruvu; Alexey I Nesvizhskii
Journal:  Nat Methods       Date:  2017-04-10       Impact factor: 28.547

7.  The ProteomeXchange consortium in 2020: enabling 'big data' approaches in proteomics.

Authors:  Eric W Deutsch; Nuno Bandeira; Vagisha Sharma; Yasset Perez-Riverol; Jeremy J Carver; Deepti J Kundu; David García-Seisdedos; Andrew F Jarnuczak; Suresh Hewapathirana; Benjamin S Pullman; Julie Wertz; Zhi Sun; Shin Kawano; Shujiro Okuda; Yu Watanabe; Henning Hermjakob; Brendan MacLean; Michael J MacCoss; Yunping Zhu; Yasushi Ishihama; Juan A Vizcaíno
Journal:  Nucleic Acids Res       Date:  2020-01-08       Impact factor: 16.971

8.  The failing heart utilizes 3-hydroxybutyrate as a metabolic stress defense.

Authors:  Julie L Horton; Michael T Davidson; Clara Kurishima; Rick B Vega; Jeffery C Powers; Timothy R Matsuura; Christopher Petucci; E Douglas Lewandowski; Peter A Crawford; Deborah M Muoio; Fabio A Recchia; Daniel P Kelly
Journal:  JCI Insight       Date:  2019-02-21

9.  IUPred3: prediction of protein disorder enhanced with unambiguous experimental annotation and visualization of evolutionary conservation.

Authors:  Gábor Erdős; Mátyás Pajkos; Zsuzsanna Dosztányi
Journal:  Nucleic Acids Res       Date:  2021-07-02       Impact factor: 16.971

10.  Fast and Accurate Protein False Discovery Rates on Large-Scale Proteomics Data Sets with Percolator 3.0.

Authors:  Matthew The; Michael J MacCoss; William S Noble; Lukas Käll
Journal:  J Am Soc Mass Spectrom       Date:  2016-08-29       Impact factor: 3.109

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.