Evolutionary paths to mammalian longevity through the lens of gene expression.

The natural variation in mammalian longevity and its underlying mechanisms remain an active area of aging research. In the latest issue of The EMBO Journal, Liu et al (2023) analyze gene expression levels in 103 mammalian species across three tissues, revealing tissue-specific associations between gene expression patterns and longevity. Remarkably, the study suggests that methionine restriction, a strategy shown to increase lifespan, may extend beyond artificial interventions and is similarly employed by natural selection.

Functional conservation in genes and pathways linking ageing and immunity.

At first glance, longevity and immunity appear to be different traits that have not much in common except the fact that the immune system promotes survival upon pathogenic infection. Substantial evidence however points to a molecularly intertwined relationship between the immune system and ageing. Although this link is well-known throughout the animal kingdom, its genetic basis is complex and still poorly understood. To address this question, we here provide a compilation of all genes concomitantly known to be involved in immunity and ageing in humans and three well-studied model organisms, the nematode worm Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and the house mouse Mus musculus. By analysing human orthologs among these species, we identified 7 evolutionarily conserved signalling cascades, the insulin/TOR network, three MAPK (ERK, p38, JNK), JAK/STAT, TGF-ß, and Nf-κB pathways that act pleiotropically on ageing and immunity. We review current evidence for these pathways linking immunity and lifespan, and their role in the detrimental dysregulation of the immune system with age, known as immunosenescence. We argue that the phenotypic effects of these pathways are often context-dependent and vary, for example, between tissues, sexes, and types of pathogenic infection. Future research therefore needs to explore a higher temporal, spatial and environmental resolution to fully comprehend the connection between ageing and immunity.

Using the drug-protein interactome to identify anti-ageing compounds for humans.

Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and healthspan in animal models, suggesting that there is scope for drug repurposing in humans. New bioinformatic methods to identify and prioritise potential anti-ageing compounds for humans are therefore of interest. In this study, we first used drug-protein interaction information, to rank 1,147 drugs by their likelihood of targeting ageing-related gene products in humans. Among 19 statistically significant drugs, 6 have already been shown to have pro-longevity properties in animal models (p < 0.001). Using the targets of each drug, we established their association with ageing at multiple levels of biological action including pathways, functions and protein interactions. Finally, combining all the data, we calculated a ranked list of drugs that identified tanespimycin, an inhibitor of HSP-90, as the top-ranked novel anti-ageing candidate. We experimentally validated the pro-longevity effect of tanespimycin through its HSP-90 target in Caenorhabditis elegans.

Archaeogenomic analysis of the first steps of Neolithization in Anatolia and the Aegean.

The Neolithic transition in west Eurasia occurred in two main steps: the gradual development of sedentism and plant cultivation in the Near East and the subsequent spread of Neolithic cultures into the Aegean and across Europe after 7000 cal BCE. Here, we use published ancient genomes to investigate gene flow events in west Eurasia during the Neolithic transition. We confirm that the Early Neolithic central Anatolians in the ninth millennium BCE were probably descendants of local hunter-gatherers, rather than immigrants from the Levant or Iran. We further study the emergence of post-7000 cal BCE north Aegean Neolithic communities. Although Aegean farmers have frequently been assumed to be colonists originating from either central Anatolia or from the Levant, our findings raise alternative possibilities: north Aegean Neolithic populations may have been the product of multiple westward migrations, including south Anatolian emigrants, or they may have been descendants of local Aegean Mesolithic groups who adopted farming. These scenarios are consistent with the diversity of material cultures among Aegean Neolithic communities and the inheritance of local forager know-how. The demographic and cultural dynamics behind the earliest spread of Neolithic culture in the Aegean could therefore be distinct from the subsequent Neolithization of mainland Europe.

Inter-tissue convergence of gene expression during ageing suggests age-related loss of tissue and cellular identity.

Developmental trajectories of gene expression may reverse in their direction during ageing, a phenomenon previously linked to cellular identity loss. Our analysis of cerebral cortex, lung, liver, and muscle transcriptomes of 16 mice, covering development and ageing intervals, revealed widespread but tissue-specific ageing-associated expression reversals. Cumulatively, these reversals create a unique phenomenon: mammalian tissue transcriptomes diverge from each other during postnatal development, but during ageing, they tend to converge towards similar expression levels, a process we term Divergence followed by Convergence (DiCo). We found that DiCo was most prevalent among tissue-specific genes and associated with loss of tissue identity, which is confirmed using data from independent mouse and human datasets. Further, using publicly available single-cell transcriptome data, we showed that DiCo could be driven both by alterations in tissue cell-type composition and also by cell-autonomous expression changes within particular cell types.

Lessons from a ten-year-long journey: building a student-driven computational biology society across Turkey.

The Regional Student Group Turkey (RSG-Turkey) is officially associated with the International Society for Computational Biology (ISCB) Student Council (SC). At the RSG-Turkey, we aim to contribute to the early-career researchers in computational biology and bioinformatics fields by providing opportunities for improving their academic and technical skills in the field. Over the last ten years, we have built a well-known student-driven academic society in Turkey that organizes numerous events every year and continues to grow with over 650 current members. Celebrating the 10th anniversary of RSG-Turkey, in this communication, we share our experiences, five main lessons we learned, and the steps to establish a long-standing academic community: having a clear mission, building a robust structure, effective communication, turning challenges into opportunities, and building collaborations. We believe that our experiences can help students and academics establish long-standing communities in fast-developing areas like bioinformatics.

Common genetic associations between age-related diseases.

Age is a common risk factor in many diseases, but the molecular basis for this relationship is elusive. In this study we identified 4 disease clusters from 116 diseases in the UK Biobank data, defined by their age-of-onset profiles, and found that diseases with the same onset profile are genetically more similar, suggesting a common etiology. This similarity was not explained by disease categories, co-occurrences or disease cause-effect relationships. Two of the four disease clusters had an increased risk of occurrence from age 20 and 40 years respectively. They both showed an association with known aging-related genes, yet differed in functional enrichment and evolutionary profiles. Moreover, they both had age-related expression and methylation changes. We also tested mutation accumulation and antagonistic pleiotropy theories of aging and found support for both.

Transcriptomic profiling of long- and short-lived mutant mice implicates mitochondrial metabolism in ageing and shows signatures of normal ageing in progeroid mice.

Genetically modified mouse models of ageing are the living proof that lifespan and healthspan can be lengthened or shortened, and provide a powerful context in which to unravel the molecular mechanisms at work. In this study, we analysed and compared gene expression data from 10 long-lived and 8 short-lived mouse models of ageing. Transcriptome-wide correlation analysis revealed that mutations with equivalent effects on lifespan induce more similar transcriptomic changes, especially if they target the same pathway. Using functional enrichment analysis, we identified 58 gene sets with consistent changes in long- and short-lived mice, 55 of which were up-regulated in long-lived mice and down-regulated in short-lived mice. Half of these sets represented genes involved in energy and lipid metabolism, among which Ppargc1a, Mif, Aldh5a1 and Idh1 were frequently observed. Based on the gene sets with consistent changes, and also the whole transcriptome, the gene expression changes during normal ageing resembled the transcriptome of short-lived models, suggesting that accelerated ageing models reproduce partially the molecular changes of ageing. Finally, we identified new genetic interventions that may ameliorate ageing, by comparing the transcriptomes of 51 mouse mutants not previously associated with ageing to expression signatures of long- and short-lived mice and ageing-related changes.

Transposable Element Landscape in Drosophila Populations Selected for Longevity.

Transposable elements (TEs) inflict numerous negative effects on health and fitness as they replicate by integrating into new regions of the host genome. Even though organisms employ powerful mechanisms to demobilize TEs, transposons gradually lose repression during aging. The rising TE activity causes genomic instability and was implicated in age-dependent neurodegenerative diseases, inflammation, and the determination of lifespan. It is therefore conceivable that long-lived individuals have improved TE silencing mechanisms resulting in reduced TE expression relative to their shorter-lived counterparts and fewer genomic insertions. Here, we test this hypothesis by performing the first genome-wide analysis of TE insertions and expression in populations of Drosophila melanogaster selected for longevity through late-life reproduction for 50-170 generations from four independent studies. Contrary to our expectation, TE families were generally more abundant in long-lived populations compared with nonselected controls. Although simulations showed that this was not expected under neutrality, we found little evidence for selection driving TE abundance differences. Additional RNA-seq analysis revealed a tendency for reducing TE expression in selected populations, which might be more important for lifespan than regulating genomic insertions. We further find limited evidence of parallel selection on genes related to TE regulation and transposition. However, telomeric TEs were genomically and transcriptionally more abundant in long-lived flies, suggesting improved telomere maintenance as a promising TE-mediated mechanism for prolonging lifespan. Our results provide a novel viewpoint indicating that reproduction at old age increases the opportunity of TEs to be passed on to the next generation with little impact on longevity.

Highlights from the 16th International Society for Computational Biology Student Council Symposium 2020.

In this meeting overview, we summarise the scientific program and organisation of the 16th International Society for Computational Biology Student Council Symposium in 2020 (ISCB SCS2020). This symposium was the first virtual edition in an uninterrupted series of symposia that has been going on for 15 years, aiming to unite computational biology students and early career researchers across the globe.

Human population dynamics and Yersinia pestis in ancient northeast Asia.

We present genome-wide data from 40 individuals dating to c.16,900 to 550 years ago in northeast Asia. We describe hitherto unknown gene flow and admixture events in the region, revealing a complex population history. While populations east of Lake Baikal remained relatively stable from the Mesolithic to the Bronze Age, those from Yakutia and west of Lake Baikal witnessed major population transformations, from the Late Upper Paleolithic to the Neolithic, and during the Bronze Age, respectively. We further locate the Asian ancestors of Paleo-Inuits, using direct genetic evidence. Last, we report the most northeastern ancient occurrence of the plague-related bacterium, Yersinia pestis Our findings indicate the highly connected and dynamic nature of northeast Asia populations throughout the Holocene.

Temporal changes in the gene expression heterogeneity during brain development and aging.

Cells in largely non-mitotic tissues such as the brain are prone to stochastic (epi-)genetic alterations that may cause increased variability between cells and individuals over time. Although increased inter-individual heterogeneity in gene expression was previously reported, whether this process starts during development or if it is restricted to the aging period has not yet been studied. The regulatory dynamics and functional significance of putative aging-related heterogeneity are also unknown. Here we address these by a meta-analysis of 19 transcriptome datasets from three independent studies, covering diverse human brain regions. We observed a significant increase in inter-individual heterogeneity during aging (20 + years) compared to postnatal development (0 to 20 years). Increased heterogeneity during aging was consistent among different brain regions at the gene level and associated with lifespan regulation and neuronal functions. Overall, our results show that increased expression heterogeneity is a characteristic of aging human brain, and may influence aging-related changes in brain functions.

The widespread increase in inter-individual variability of gene expression in the human brain with age.

Aging is broadly defined as a time-dependent progressive decline in the functional and physiological integrity of organisms. Previous studies and evolutionary theories of aging suggest that aging is not a programmed process but reflects dynamic stochastic events. In this study, we test whether transcriptional noise shows an increase with age, which would be expected from stochastic theories. Using human brain transcriptome dataset, we analyzed the heterogeneity in the transcriptome for individual genes and functional pathways, employing different analysis methods and pre-processing steps. We show that unlike expression level changes, changes in heterogeneity are highly dependent on the methodology and the underlying assumptions. Although the particular set of genes that can be characterized as differentially variable is highly dependent on the methods, we observe a consistent increase in heterogeneity at every level, independent of the method. In particular, we demonstrate a weak but reproducible transcriptome-wide shift towards an increase in heterogeneity, with twice as many genes significantly increasing as opposed to decreasing their heterogeneity. Furthermore, this pattern of increasing heterogeneity is not specific but is associated with a wide range of pathways.

Identifying Potential Ageing-Modulating Drugs In Silico.

Increasing human life expectancy has posed increasing challenges for healthcare systems. As people age, they become more susceptible to chronic diseases, with an increasing burden of multimorbidity, and the associated polypharmacy. Accumulating evidence from work with laboratory animals has shown that ageing is a malleable process that can be ameliorated by genetic and environmental interventions. Drugs that modulate the ageing process may delay or even prevent the incidence of multiple diseases of ageing. To identify novel, anti-ageing drugs, several studies have developed computational drug-repurposing strategies. We review published studies showing the potential of current drugs to modulate ageing. Future studies should integrate current knowledge with multi-omics, health records, and drug safety data to predict drugs that can improve health in late life.

Molecular footprint of Medawar's mutation accumulation process in mammalian aging.

Medawar's mutation accumulation hypothesis explains aging by the declining force of natural selection with age: Slightly deleterious germline mutations expressed in old age can drift to fixation and thereby lead to aging-related phenotypes. Although widely cited, empirical evidence for this hypothesis has remained limited. Here, we test one of its predictions that genes relatively highly expressed in old adults should be under weaker purifying selection than genes relatively highly expressed in young adults. Combining 66 transcriptome datasets (including 16 tissues from five mammalian species) with sequence conservation estimates across mammals, here we report that the overall conservation level of expressed genes is lower at old age compared to young adulthood. This age-related decrease in transcriptome conservation (ADICT) is systematically observed in diverse mammalian tissues, including the brain, liver, lung, and artery, but not in others, most notably in the muscle and heart. Where observed, ADICT is driven partly by poorly conserved genes being up-regulated during aging. In general, the more often a gene is found up-regulated with age among tissues and species, the lower its evolutionary conservation. Poorly conserved and up-regulated genes have overlapping functional properties that include responses to age-associated tissue damage, such as apoptosis and inflammation. Meanwhile, these genes do not appear to be under positive selection. Hence, genes contributing to old age phenotypes are found to harbor an excess of slightly deleterious alleles, at least in certain tissues. This supports the notion that genetic drift shapes aging in multicellular organisms, consistent with Medawar's mutation accumulation hypothesis.

Global network of computational biology communities: ISCB's Regional Student Groups breaking barriers.

Regional Student Groups (RSGs) of the International Society for Computational Biology Student Council (ISCB-SC) have been instrumental to connect computational biologists globally and to create more awareness about bioinformatics education. This article highlights the initiatives carried out by the RSGs both nationally and internationally to strengthen the present and future of the bioinformatics community. Moreover, we discuss the future directions the organization will take and the challenges to advance further in the ISCB-SC main mission: "Nurture the new generation of computational biologists".

Gene expression-based drug repurposing to target aging.

Aging is the largest risk factor for a variety of noncommunicable diseases. Model organism studies have shown that genetic and chemical perturbations can extend both lifespan and healthspan. Aging is a complex process, with parallel and interacting mechanisms contributing to its aetiology, posing a challenge for the discovery of new pharmacological candidates to ameliorate its effects. In this study, instead of a target-centric approach, we adopt a systems level drug repurposing methodology to discover drugs that could combat aging in human brain. Using multiple gene expression data sets from brain tissue, taken from patients of different ages, we first identified the expression changes that characterize aging. Then, we compared these changes in gene expression with drug-perturbed expression profiles in the Connectivity Map. We thus identified 24 drugs with significantly associated changes. Some of these drugs may function as antiaging drugs by reversing the detrimental changes that occur during aging, others by mimicking the cellular defence mechanisms. The drugs that we identified included significant number of already identified prolongevity drugs, indicating that the method can discover de novo drugs that meliorate aging. The approach has the advantages that using data from human brain aging data, it focuses on processes relevant in human aging and that it is unbiased, making it possible to discover new targets for aging studies.

Gene expression reversal toward pre-adult levels in the aging human brain and age-related loss of cellular identity.

It was previously reported that mRNA expression levels in the prefrontal cortex at old age start to resemble pre-adult levels. Such expression reversals could imply loss of cellular identity in the aging brain, and provide a link between aging-related molecular changes and functional decline. Here we analyzed 19 brain transcriptome age-series datasets, comprising 17 diverse brain regions, to investigate the ubiquity and functional properties of expression reversal in the human brain. Across all 19 datasets, 25 genes were consistently up-regulated during postnatal development and down-regulated in aging, displaying an "up-down" pattern that was significant as determined by random permutations. In addition, 113 biological processes, including neuronal and synaptic functions, were consistently associated with genes showing an up-down tendency among all datasets. Genes up-regulated during in vitro neuronal differentiation also displayed a tendency for up-down reversal, although at levels comparable to other genes. We argue that reversals may not represent aging-related neuronal loss. Instead, expression reversals may be associated with aging-related accumulation of stochastic effects that lead to loss of functional and structural identity in neurons.

Characterising Complex Enzyme Reaction Data.

The relationship between enzyme-catalysed reactions and the Enzyme Commission (EC) number, the widely accepted classification scheme used to characterise enzyme activity, is complex and with the rapid increase in our knowledge of the reactions catalysed by enzymes needs revisiting. We present a manual and computational analysis to investigate this complexity and found that almost one-third of all known EC numbers are linked to more than one reaction in the secondary reaction databases (e.g., KEGG). Although this complexity is often resolved by defining generic, alternative and partial reactions, we have also found individual EC numbers with more than one reaction catalysing different types of bond changes. This analysis adds a new dimension to our understanding of enzyme function and might be useful for the accurate annotation of the function of enzymes and to study the changes in enzyme function during evolution.