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Biology subjects

dos Santos, G. A.

Publications and source records attributed to dos Santos, G. A..

4 recordsLinked to original sources

Processed pseudogenes as dynamic substrates of vertebrate genome evolution

Pseudogenes, gene copies presumed nonfunctional, are widespread products of genome evolution, yet their retention under selection and functional significance across vertebrate diversity remain poorly understood. Here, by analyzing 244 high-quality, chromosome-scale genomes from the Vertebrate Genomes Project spanning seven major vertebrate lineages, we show that the most abundant class of pseudogenes, processed pseudogenes (retrocopies), is a dynamic substrate for evolutionary innovation rather than an inert relic. Retrocopy abundance varies by more than an order of magnitude across lineages, closely tracks autonomous retrotransposon content, and a considerable fraction retains intact open reading frames under purifying selection. We establish a two-stage model in which a conserved formation bias toward highly expressed housekeeping genes is followed by lineage-specific selective filtering that shapes distinct functional repertoires. Testing this model, we show that the mammalian X chromosome exports retrocopies to autosomes at significantly elevated rates enriched for functionally constrained copies, establishing meiotic sex chromosome inactivation as the selective driver. Furthermore, tumor suppressor gene retrocopies accumulate preferentially over oncogene retrocopies in large-bodied and long-lived mammalian lineages, identifying retrocopy-mediated tumor suppressor dosage expansion as a previously unrecognized genomic correlate of Petos paradox. Beyond cancer-related dynamics, retrocopy abundance itself correlates with key mammalian life-history traits, including brain mass, generation length, and reproductive timing, which suggests that retrocopy turnover is broadly coupled to organismal pace-of-life. These findings recast retrocopies as a major axis of vertebrate genome evolution and provide a comprehensive resource for studying gene duplicate innovation.

genomics↗

Transcriptomic entropy reveals tissue-specific patterns in aging and predicts cancer progression

ABSTRACTAging and cancer share complex molecular mechanisms, yet distinguishing between causative factors and byproducts remains challenging. Here, we investigated the role of transcriptomic entropy in aging and cancer processes by analyzing RNA-sequencing data from thousands of human and mouse samples. We found that entropy changes during aging are highly tissue-specific, with some tissues showing increased entropy while others exhibit decreased or stable entropy levels. Transcriptomic entropy strongly correlates with age-related processes, showing positive associations with proliferation, cellular senescence, and somatic mutation burden, while negatively correlating with stemness. Surprisingly, cellular reprogramming also increases transcriptomic entropy. In cancer, we observed that primary tumors generally display higher entropy than normal tissue, with entropy levels further increasing in metastatic stages. Notably, treatment-resistant tumors showed distinct entropy patterns, with acquired resistance associated with increased entropy, while primary resistance and immediate post-treatment responses showed decreased entropy. Higher entropy levels predicted poor survival outcomes in multiple cancer types, suggesting its potential as a prognostic marker. Furthermore, differential expression analysis revealed that entropy-associated genes are enriched in developmental processes and depleted in metabolic pathways, indicating a possible link to cellular dedifferentiation. Finally, we found increased entropy in various age-related diseases beyond cancer, suggesting that transcriptomic disorder may be a common feature in age-related pathologies. Our findings establish transcriptomic entropy as a fundamental parameter in aging and cancer progression, offering new insights into disease mechanisms and challenging the current view that increased disorder is always detrimental.

genomics↗

Evidence of a pan-tissue decline in stemness during human aging

Despite their biological importance, the role of stem cells in human aging remains to be elucidated. In this work, we applied a machine learning methodology to GTEx transcriptome data and assigned stemness scores to 17,382 healthy samples from 30 human tissues aged between 20 and 79 years. We found that [~]60% of the studied tissues present a significant negative correlation between the subjects age and stemness score. The only significant exception to this pattern was the uterus, where we observed an increased stemness with age. Moreover, we observed a global trend of positive correlations between cell proliferation and stemness. When analyzing the tissues individually, we found that [~]50% of human tissues present a positive correlation between stemness and proliferation and 20% a negative correlation. Furthermore, all our analyses show negative correlations between stemness and cellular senescence, with significant results in [~]80% of the tissues analyzed. Finally, we also observed a trend that hematopoietic stem cells derived from old patients might have more stemness. In short, we assigned stemness scores to human samples and show evidence of a pan-tissue loss of stemness during human aging, which adds weight to the idea that stem cell deterioration contributes to human ageing.

genomics↗

Pan-cancer transcriptomic analysis reveals a tissue-specific loss of identity

Understanding changes in cell identity in cancer and ageing is of great importance. In this work, we analyzed how gene expression changes in human tissues are associated with tissue specificity during cancer and ageing using transcriptome data from TCGA and GTEx. We found a loss of cell identity during ageing in around 40% of tissues. In cancer, we observed a pattern of downregulation of genes specific to the tissue of origin of the tumor for most cancer types. Moreover, we observed an activation of genes not usually expressed in a tissue as well as an upregulation of genes specific to other tissues in cancer. These patterns in cancer were associated with patient survival. The age of the patient, however, does not influence these patterns. Thus, we identified a moderate but statistically significant pattern of loss of cell identity in ageing, and a clear pattern in cancer, where during tumorigenesis, cells express genes specific to other organs while suppressing the expression of genes from their original tissue. The loss of cellular identity observed in cancer is associated with prognosis and is not influenced by age, suggesting that it is a crucial stage in carcinogenesis.

bioinformatics↗