A combination of differential expression and network connectivity analyses identifies a common set of RNA splicing and processing genes altered with age across human tissues

Although transcriptomic changes are known to occur with age, the extent to which these are conserved across tissues is unclear. Previous studies have identified little conservation in age-modulated genes in different tissues. Here, we sought to identify common transcriptional changes with age in humans (aged 20 to 70) across tissues using differential network analysis, assuming that differential expression analysis alone cannot detect all changes in the transcriptional landscape that occur in tissues with age. Our results demonstrate that differential connectivity analysis reveals significant transcriptional alterations that are not detected by differential expression analysis. Combining the two analyses, we identified gene sets modulated by age across all tissues that are highly enriched in terms related to "RNA splicing" and "RNA processing". The identified genes are also highly interconnected in protein-protein interaction networks. Co-expression module analyses demonstrated that other genes that show tissue-specific variations with age are enriched in pathways that combat the accumulation of aberrant RNAs and proteins, likely caused by defective splicing. Additionally, with convergent connectivity patterns, most tissues significantly reorganized their gene connectivity with age. Our results identified genes and processes whose age-associated transcriptional changes are conserved across tissues, demonstrating a central role for RNA splicing and processing genes and highlighting the importance of differential network analysis for understanding the ageing transcriptome.

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Publication Details

Journal
Aging
Published
2025-12-22
DOI
https://doi.org/10.18632/aging.206347
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

A combination of differential expression and network connectivity analyses identifies a common set of RNA splicing and processing genes altered with age across human tissues

André Fujita, Caio M.P.F. Batalha, Nadja C. de Souza-Pinto
Aging
Bioinformatics and Genomic Networks
article

A combination of differential expression and network connectivity analyses identifies a common set of RNA splicing and processing genes altered with age across human tissues

André Fujita, Caio M.P.F. Batalha, Nadja C. de Souza-Pinto
article en

Abstract

Although transcriptomic changes are known to occur with age, the extent to which these are conserved across tissues is unclear. Previous studies have identified little conservation in age-modulated genes in different tissues. Here, we sought to identify common transcriptional changes with age in humans (aged 20 to 70) across tissues using differential network analysis, assuming that differential expression analysis alone cannot detect all changes in the transcriptional landscape that occur in tissues with age. Our results demonstrate that differential connectivity analysis reveals significant transcriptional alterations that are not detected by differential expression analysis. Combining the two analyses, we identified gene sets modulated by age across all tissues that are highly enriched in terms related to "RNA splicing" and "RNA processing". The identified genes are also highly interconnected in protein-protein interaction networks. Co-expression module analyses demonstrated that other genes that show tissue-specific variations with age are enriched in pathways that combat the accumulation of aberrant RNAs and proteins, likely caused by defective splicing. Additionally, with convergent connectivity patterns, most tissues significantly reorganized their gene connectivity with age. Our results identified genes and processes whose age-associated transcriptional changes are conserved across tissues, demonstrating a central role for RNA splicing and processing genes and highlighting the importance of differential network analysis for understanding the ageing transcriptome.

AgingVol. 17(12)
Kyushu University (JP), Universidade de São Paulo (BR), Institute of Mathematics and Computer Science (MD)
Fundação de Amparo à Pesquisa do Estado de São Paulo, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Life in Land
Openalex Percentile: Top 37%
Bioinformatics and Genomic Networks
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