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Bonnefous H, Teulière J, Lapointe FJ, Lopez P, Bapteste E. Most genetic roots of fungal and animal aging are hundreds of millions of years old according to phylostratigraphy analyses of aging networks. GeroScience 2024; 46:5037-5059. [PMID: 38862758 PMCID: PMC11335996 DOI: 10.1007/s11357-024-01234-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 05/30/2024] [Indexed: 06/13/2024] Open
Abstract
Few studies have systematically analyzed how old aging is. Gaining a more accurate knowledge about the natural history of aging could however have several payoffs. This knowledge could unveil lineages with dated genetic hardware, possibly maladapted to current environmental challenges, and also uncover "phylogenetic modules of aging," i.e., naturally evolved pathways associated with aging or longevity from a single ancestry, with translational interest for anti-aging therapies. Here, we approximated the natural history of the genetic hardware of aging for five model fungal and animal species. We propose a lower-bound estimate of the phylogenetic age of origination for their protein-encoding gene families and protein-protein interactions. Most aging-associated gene families are hundreds of million years old, older than the other gene families from these genomes. Moreover, we observed a form of punctuated evolution of the aging hardware in all species, as aging-associated families born at specific phylogenetic times accumulate preferentially in genomes. Most protein-protein interactions between aging genes are also old, and old aging-associated proteins showed a reduced potential to contribute to novel interactions associated with aging, suggesting that aging networks are at risk of losing in evolvability over long evolutionary periods. Finally, due to reshuffling events, aging networks presented a very limited phylogenetic structure that challenges the detection of "maladaptive" or "adaptative" phylogenetic modules of aging in present-day genomes.
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Affiliation(s)
- Hugo Bonnefous
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université Des Antilles, Paris, France
| | - Jérôme Teulière
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université Des Antilles, Paris, France
| | - François-Joseph Lapointe
- Département de Sciences Biologiques, Complexe Des Sciences, Université de Montréal, Montréal, QC, Canada
| | - Philippe Lopez
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université Des Antilles, Paris, France
| | - Eric Bapteste
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université Des Antilles, Paris, France.
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2
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Bornstein K, Gryan G, Chang ES, Marchler-Bauer A, Schneider VA. The NIH Comparative Genomics Resource: addressing the promises and challenges of comparative genomics on human health. BMC Genomics 2023; 24:575. [PMID: 37759191 PMCID: PMC10523801 DOI: 10.1186/s12864-023-09643-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Accepted: 08/31/2023] [Indexed: 09/29/2023] Open
Abstract
Comparative genomics is the comparison of genetic information within and across organisms to understand the evolution, structure, and function of genes, proteins, and non-coding regions (Sivashankari and Shanmughavel, Bioinformation 1:376-8, 2007). Advances in sequencing technology and assembly algorithms have resulted in the ability to sequence large genomes and provided a wealth of data that are being used in comparative genomic analyses. Comparative analysis can be leveraged to systematically explore and evaluate the biological relationships and evolution between species, aid in understanding the structure and function of genes, and gain a better understanding of disease and potential drug targets. As our knowledge of genetics expands, comparative genomics can help identify emerging model organisms among a broader span of the tree of life, positively impacting human health. This impact includes, but is not limited to, zoonotic disease research, therapeutics development, microbiome research, xenotransplantation, oncology, and toxicology. Despite advancements in comparative genomics, new challenges have arisen around the quantity, quality assurance, annotation, and interoperability of genomic data and metadata. New tools and approaches are required to meet these challenges and fulfill the needs of researchers. This paper focuses on how the National Institutes of Health (NIH) Comparative Genomics Resource (CGR) can address both the opportunities for comparative genomics to further impact human health and confront an increasingly complex set of challenges facing researchers.
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Affiliation(s)
| | - Gary Gryan
- The MITRE Corporation, 7525 Colshire Dr, McLean, VA, USA
| | - E Sally Chang
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Aron Marchler-Bauer
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Valerie A Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
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Bapteste E, Huneman P, Keller L, Teulière J, Lopez P, Teeling EC, Lindner AB, Baudisch A, Ludington WB, Franceschi C. Expanding evolutionary theories of ageing to better account for symbioses and interactions throughout the Web of Life. Ageing Res Rev 2023; 89:101982. [PMID: 37321383 PMCID: PMC10771319 DOI: 10.1016/j.arr.2023.101982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 05/26/2023] [Accepted: 06/11/2023] [Indexed: 06/17/2023]
Abstract
How, when, and why organisms age are fascinating issues that can only be fully addressed by adopting an evolutionary perspective. Consistently, the main evolutionary theories of ageing, namely the Mutation Accumulation theory, the Antagonistic Pleiotropy theory, and the Disposable Soma theory, have formulated stimulating hypotheses that structure current debates on both the proximal and ultimate causes of organismal ageing. However, all these theories leave a common area of biology relatively under-explored. The Mutation Accumulation theory and the Antagonistic Pleiotropy theory were developed under the traditional framework of population genetics, and therefore are logically centred on the ageing of individuals within a population. The Disposable Soma theory, based on principles of optimising physiology, mainly explains ageing within a species. Consequently, current leading evolutionary theories of ageing do not explicitly model the countless interspecific and ecological interactions, such as symbioses and host-microbiomes associations, increasingly recognized to shape organismal evolution across the Web of Life. Moreover, the development of network modelling supporting a deeper understanding on the molecular interactions associated with ageing within and between organisms is also bringing forward new questions regarding how and why molecular pathways associated with ageing evolved. Here, we take an evolutionary perspective to examine the effects of organismal interactions on ageing across different levels of biological organisation, and consider the impact of surrounding and nested systems on organismal ageing. We also apply this perspective to suggest open issues with potential to expand the standard evolutionary theories of ageing.
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Affiliation(s)
- Eric Bapteste
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, France.
| | - Philippe Huneman
- Institut d'Histoire et de Philosophie des Sciences et des Techniques (CNRS/ Université Paris I Sorbonne), Paris, France
| | - Laurent Keller
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
| | - Jérôme Teulière
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, France
| | - Philippe Lopez
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, France
| | - Emma C Teeling
- School of Biology and Environmental Science, University College Dublin, Ireland
| | - Ariel B Lindner
- Université de Paris, INSERM U1284, Center for Research and Interdisciplinarity (CRI), Paris, France
| | - Annette Baudisch
- Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, 5230 Odense M, Denmark
| | - William B Ludington
- Department of Embryology, Carnegie Institution for Science, Baltimore, MD 21218, USA; Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Claudio Franceschi
- Department of Medical and Surgical Sciences, Alma Mater Studiorum University of Bologna, 40138 Bologna, Italy; Department of Applied Mathematics and Laboratory of Systems Medicine of Aging, Lobachevsky University, Nizhny Novgorod 603950, Russia
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Treaster S, Deelen J, Daane JM, Murabito J, Karasik D, Harris MP. Convergent genomics of longevity in rockfishes highlights the genetics of human life span variation. SCIENCE ADVANCES 2023; 9:eadd2743. [PMID: 36630509 PMCID: PMC9833670 DOI: 10.1126/sciadv.add2743] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 12/09/2022] [Indexed: 05/16/2023]
Abstract
Longevity is a defining, heritable trait that varies dramatically between species. To resolve the genetic regulation of this trait, we have mined genomic variation in rockfishes, which range in longevity from 11 to over 205 years. Multiple shifts in rockfish longevity have occurred independently and in a short evolutionary time frame, thus empowering convergence analyses. Our analyses reveal a common network of genes under convergent evolution, encompassing established aging regulators such as insulin signaling, yet also identify flavonoid (aryl-hydrocarbon) metabolism as a pathway modulating longevity. The selective pressures on these pathways indicate the ancestral state of rockfishes was long lived and that the changes in short-lived lineages are adaptive. These pathways were also used to explore genome-wide association studies of human longevity, identifying the aryl-hydrocarbon metabolism pathway to be significantly associated with human survival to the 99th percentile. This evolutionary intersection defines and cross-validates a previously unappreciated genetic architecture that associates with the evolution of longevity across vertebrates.
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Affiliation(s)
- Stephen Treaster
- Department of Orthopaedic Surgery, Boston Children’s Hospital, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Joris Deelen
- Max Planck Institute for Biology of Ageing, Joseph-Stelzmann-Str. 9b, D-50931 Köln, Germany
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Jacob M. Daane
- Department of Biology and Biochemistry, University of Houston, Houston TX, USA
| | - Joanne Murabito
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - David Karasik
- Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
- Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, USA
| | - Matthew P. Harris
- Department of Orthopaedic Surgery, Boston Children’s Hospital, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
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Teulière J, Bernard C, Corel E, Lapointe FJ, Martens J, Lopez P, Bapteste E. Network analyses unveil ageing-associated pathways evolutionarily conserved from fungi to animals. GeroScience 2022; 45:1059-1080. [PMID: 36508078 PMCID: PMC9886728 DOI: 10.1007/s11357-022-00704-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 11/22/2022] [Indexed: 12/14/2022] Open
Abstract
The genetic roots of the diverse paces and shapes of ageing and of the large variations in longevity observed across the tree of life are poorly understood. Indeed, pathways associated with ageing/longevity are incompletely known, both in terms of their constitutive genes/proteins and of their molecular interactions. Moreover, there is limited overlap between the genes constituting these pathways across mammals. Yet, dedicated comparative analyses might still unravel evolutionarily conserved, important pathways associated with longevity or ageing. Here, we used an original strategy with a double evolutionary and systemic focus to analyse protein interactions associated with ageing or longevity during the evolution of five species of Opisthokonta. We ranked these proteins and interactions based on their evolutionary conservation and centrality in past and present protein-protein interaction (PPI) networks, providing a big systemic picture of the evolution of ageing and longevity pathways that identified which pathways emerged in which Opisthokonta lineages, were conserved, and/or central. We confirmed that longevity/ageing-associated proteins (LAPs), be they pro- or anti-longevity, are highly central in extant PPI, consistently with the antagonistic pleiotropy theory of ageing, and identified key antagonistic regulators of ageing/longevity, 52 of which with homologues in humans. While some highly central LAPs were evolutionarily conserved for over a billion years, we report a clear transition in the functionally important components of ageing/longevity within bilaterians. We also predicted 487 novel evolutionarily conserved LAPs in humans, 54% of which are more central than mTOR, and 138 of which are druggable, defining new potential targets for anti-ageing treatments in humans.
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Affiliation(s)
- Jérôme Teulière
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d’Histoire Naturelle, EPHE, Université Des Antilles, Paris, France
| | - Charles Bernard
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d’Histoire Naturelle, EPHE, Université Des Antilles, Paris, France
| | - Eduardo Corel
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d’Histoire Naturelle, EPHE, Université Des Antilles, Paris, France
| | - François-Joseph Lapointe
- grid.14848.310000 0001 2292 3357Département de Sciences Biologiques, Complexe Des Sciences, Université de Montréal, Montréal, QC Canada
| | - Johannes Martens
- Sciences, Normes, Démocratie (SND), Sorbonne Université, CNRS, 75005 Paris, France
| | - Philippe Lopez
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d’Histoire Naturelle, EPHE, Université Des Antilles, Paris, France
| | - Eric Bapteste
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université Des Antilles, Paris, France.
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Abstract
Aging has provided fruitful challenges for evolutionary theory, and evolutionary theory has deepened our understanding of aging. A great deal of genetic and molecular data now exists concerning mortality regulation and there is a growing body of knowledge concerning the life histories of diverse species. Assimilating all relevant data into a framework for the evolution of aging promises to significantly advance the field. We propose extensions of some key concepts to provide greater precision when applying these concepts to age-structured contexts. Secondary or byproduct effects of mutations are proposed as an important factor affecting survival patterns, including effects that may operate in small populations subject to genetic drift, widening the possibilities for mutation accumulation and pleiotropy. Molecular and genetic studies have indicated a diverse array of mechanisms that can modify aging and mortality rates, while transcriptome data indicate a high level of tissue and species specificity for genes affected by aging. The diversity of mechanisms and gene effects that can contribute to the pattern of aging in different organisms may mirror the complex evolutionary processes behind aging.
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Affiliation(s)
- Stewart Frankel
- Biology Department, University of Hartford, West Hartford, CT, United States
| | - Blanka Rogina
- Genetics and Genome Sciences, Institute for Systems Genomics, School of Medicine, University of Connecticut Health Center, Farmington, CT, United States
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Treaster S, Daane JM, Harris MP. Refining Convergent Rate Analysis with Topology in Mammalian Longevity and Marine Transitions. Mol Biol Evol 2021; 38:5190-5203. [PMID: 34324001 PMCID: PMC8557430 DOI: 10.1093/molbev/msab226] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The quest to map the genetic foundations of phenotypes has been empowered by the modern diversity, quality, and availability of genomic resources. Despite these expanding resources, the abundance of variation within lineages makes it challenging to associate genetic change to specific phenotypes, without an a priori means of isolating the changes from background genomic variation. Evolution provides this means through convergence-i.e., the shared variation that may result from replicate evolutionary experiments across independent trait occurrences. To leverage these opportunities, we developed TRACCER: Topologically Ranked Analysis of Convergence via Comparative Evolutionary Rates. Compared to current methods, this software empowers rate convergence analysis by factoring in topological relationships, because genetic variation between phylogenetically proximate trait changes is more likely to be facilitating the trait. Comparisons are performed not with singular branches, but with the complete paths to the most recent common ancestor for each pair of lineages. This ensures that comparisons represent a single context diverging over the same timeframe while obviating the problematic requirement of assigning ancestral states. We applied TRACCER to two case studies: mammalian transitions to marine environments, an unambiguous collection of traits which have independently evolved three times; and the evolution of mammalian longevity, a less delineated trait but with more instances to compare. By factoring in topology, TRACCER identifies highly significant, convergent genetic signals, with important incongruities and statistical resolution when compared to existing approaches. These improvements in sensitivity and specificity of convergence analysis generates refined targets for downstream validation and identification of genotype-phenotype relationships.
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Affiliation(s)
- Stephen Treaster
- Department of Orthopaedic Research, Boston Children's Hospital, Boston, MA, 02124, USA.,Department of Genetics, Harvard Medical School, Boston, MA, 02124, USA
| | - Jacob M Daane
- Department of Orthopaedic Research, Boston Children's Hospital, Boston, MA, 02124, USA.,Department of Genetics, Harvard Medical School, Boston, MA, 02124, USA.,Department of Marine and Environmental Sciences, Northeastern University Marine Science Center, Nahant, MA, 01908, USA
| | - Matthew P Harris
- Department of Orthopaedic Research, Boston Children's Hospital, Boston, MA, 02124, USA.,Department of Genetics, Harvard Medical School, Boston, MA, 02124, USA
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