CoChat
Sign Up
Cited by 95

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Pan-mammalian analysis of molecular constraints underlying extended lifespan

Kowalczyk, Amanda, Partha, Raghavendran, Clark, Nathan L, Chikina, Maria·2020·eLife
DOI 10.7554/elife.51089PMC PMC7012612
Open this paper in CoChat — free account

Abstract

Although lifespan in mammals varies over 100-fold, the precise evolutionary mechanisms underlying variation in longevity remain unknown. Species-specific genetic changes have been observed in long-lived species including the naked mole-rat, bats, and the bowhead whale, but these adaptations do not generalize to other mammals. We present a novel method to identify associations between rates of protein evolution and continuous phenotypes across the entire mammalian phylogeny. Unlike previous analyses that focused on individual species, we treat absolute and relative longevity as quantitative traits and demonstrate that these lifespan traits affect the evolutionary constraint on hundreds of genes. Specifically, we find that genes related to cell cycle, DNA repair, cell death, the IGF1 pathway, and immunity are under increased evolutionary constraint in large and long-lived mammals. For mammals exceptionally long-lived for their body size, we find increased constraint in inflammation, DNA repair, and NFKB-related pathways. Strikingly, these pathways have considerable overlap with those that have been previously reported to have potentially adaptive changes in single-species studies, and thus would be expected to show decreased constraint in our analysis. This unexpected finding of increased constraint in many longevity-associated pathways underscores the power of our quantitative approach to detect patterns that generalize across the mammalian phylogeny.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.7554/elife.51089

Cites

15 of 15 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • PhyloG2P studies based on continuous traits can provide a more detailed understanding of what aspect of the trait the genetic elements control.

    “PhyloG2P studies based on continuous traits can also provide a more detailed understanding of what aspect of the trait the genetic elements control (e.g. length, developmental timing, colour, etc) (Kowalczyk et al. 2020; Baker et al. 2021).”

    From From Trees to Traits: A Review of Advances in PhyloG2P Methods and Future Directions (2025) · cites this paper as Kowalczyk et al. 2020

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 43

  1. Blake, 2003, MGD: the mouse genome database, Nucleic Acids Research, 31, 193, 10.1093/nar/gkg047 · DOI
  2. Blanchette, 2004, Aligning multiple genomic sequences with the threaded blockset aligner, Genome Research, 14, 708, 10.1101/gr.1933104 · DOI · Paper page
  3. Chatsirisupachai, 2019, A human tissue-specific transcriptomic analysis reveals a complex relationship between aging, Cancer, and cellular senescence, Aging Cell, 18, 10.1111/acel.13041 · DOI
  4. Chikina, 2016, Hundreds of genes experienced convergent shifts in selective pressure in marine mammals, Molecular Biology and Evolution, 33, 2182, 10.1093/molbev/msw112 · DOI · Paper page
  5. Clark, 2013, Evolutionary rate covariation in meiotic proteins results from fluctuating evolutionary pressure in yeasts and mammals, Genetics, 193, 529, 10.1534/genetics.112.145979 · DOI
  6. Eppig, 2015, The mouse genome database (MGD): facilitating mouse as a model for human biology and disease, Nucleic Acids Research, 43, D726, 10.1093/nar/gku967 · DOI
  7. Foley, 2018, Growing old, yet staying young: the role of telomeres in bats' exceptional longevity, Science Advances, 4, 10.1126/sciadv.aao0926 · DOI
  8. Harmon, 2008, GEIGER: investigating evolutionary radiations, Bioinformatics, 24, 129, 10.1093/bioinformatics/btm538 · DOI
  9. Hiller, 2012, A "forward genomics" approach links genotype to phenotype using independent phenotypic losses among related species, Cell Reports, 2, 817, 10.1016/j.celrep.2012.08.032 · DOI · Paper page
  10. Howitz, 2003, Small molecule activators of sirtuins extend Saccharomyces cerevisiae lifespan, Nature, 425, 191, 10.1038/nature01960 · DOI · Paper page
  11. Janiak, 2018, Evolution of acidic mammalian chitinase genes (CHIA) Is related to body mass and insectivory in primates, Molecular Biology and Evolution, 35, 607, 10.1093/molbev/msx312 · DOI
  12. Jones, 2014, Diversity of ageing across the tree of life, Nature, 505, 169, 10.1038/nature12789 · DOI
  13. Keane, 2015, Insights into the evolution of longevity from the bowhead whale genome, Cell Reports, 10, 112, 10.1016/j.celrep.2014.12.008 · DOI · Paper page
  14. Kent, 2002, The human genome browser at UCSC, Genome Research, 12, 996, 10.1101/gr.229102 · DOI · Paper page
  15. Kimura, 1997, daf-2, an insulin receptor-like gene that regulates longevity and diapause in Caenorhabditis elegans, Science, 277, 942, 10.1126/science.277.5328.942 · DOI
  16. Kowalczyk, 2018, RERconverge: an R package for associating evolutionary rates with convergent traits, Bioinformatics, 35, 4815, 10.1093/bioinformatics/btz468 · DOI · Paper page
  17. Larsson, 2005, Role of insulin-like growth factor 1 receptor signalling in Cancer, British Journal of Cancer, 92, 2097, 10.1038/sj.bjc.6602627 · DOI
  18. Mao, 2012, Sirtuin 6 (SIRT6) rescues the decline of homologous recombination repair during replicative senescence, PNAS, 109, 11800, 10.1073/pnas.1200583109 · DOI · Paper page
  19. Medawar, 1952, An Unsolved Problem in Biology
  20. Meyer, 2018, Ancient convergent losses of paraoxonase 1 yield potential risks for modern marine mammals, Science, 361, 591, 10.1126/science.aap7714 · DOI
  21. Muntané, 2018, Biological processes modulating longevity across primates: a phylogenetic Genome-Phenome analysis, Molecular Biology and Evolution, 35, 1990, 10.1093/molbev/msy105 · DOI · Paper page
  22. Nowak, 1999, Walker’s Mammals of the World, 10.56021/9780801857898 · DOI · Paper page
  23. Oberdoerffer, 2008, SIRT1 redistribution on chromatin promotes genomic stability but alters gene expression during aging, Cell, 135, 907, 10.1016/j.cell.2008.10.025 · DOI · Paper page
  24. Partha, 2017, Subterranean mammals show convergent regression in ocular genes and enhancers, along with adaptation to tunneling, eLife, 6, 10.7554/eLife.25884 · DOI · Paper page
  25. Partha, 2018, Robust methods for detecting convergent shifts in evolutionary rates, 10.1101/457309 · DOI
  26. Peto, 2016, Epidemiology, multistage models, and short-term mutagenicity tests, International Journal of Epidemiology, 45, 621, 10.1093/ije/dyv199 · DOI · Paper page
  27. Prudent, 2016, Controlling for phylogenetic relatedness and evolutionary rates improves the discovery of associations between species' Phenotypic and genomic differences, Molecular Biology and Evolution, 33, 2135, 10.1093/molbev/msw098 · DOI · Paper page
  28. Revell, 2012, Phytools: an R package for phylogenetic comparative biology (and other things), Methods in Ecology and Evolution, 3, 217, 10.1111/j.2041-210X.2011.00169.x · DOI
  29. Rodríguez, 2017, Antagonistic pleiotropy and mutation accumulation influence human senescence and disease, Nature Ecology & Evolution, 1, 10.1038/s41559-016-0055 · DOI · Paper page
  30. Roscito, 2018, Phenotype loss is associated with widespread divergence of the gene regulatory landscape in evolution, Nature Communications, 9, 10.1038/s41467-018-07122-z · DOI
  31. Sackton, 2007, Dynamic evolution of the innate immune system in Drosophila, Nature Genetics, 39, 1461, 10.1038/ng.2007.60 · DOI
  32. Salminen, 2008, Activation of innate immunity system during aging: nf-kb signaling is the molecular culprit of inflamm-aging, Ageing Research Reviews, 7, 83, 10.1016/j.arr.2007.09.002 · DOI · Paper page
  33. Seim, 2013, Genome analysis reveals insights into physiology and longevity of the Brandt's bat Myotis brandtii, Nature Communications, 4, 10.1038/ncomms3212 · DOI
  34. Shi, 2012, Chromatin dynamics in DNA double-strand break repair, Biochimica Et Biophysica Acta (BBA) - Gene Regulatory Mechanisms, 1819, 811, 10.1016/j.bbagrm.2012.01.002 · DOI
  35. Shultz, 2019, Immune genes are hotspots of shared positive selection across birds and mammals, eLife, 8, 10.7554/eLife.41815 · DOI
  36. Storey, 2003, The positive false discovery rate: a bayesian interpretation and the q -value, The Annals of Statistics, 31, 2013, 10.1214/aos/1074290335 · DOI · Paper page
  37. Stout, 2013, Insulin/IGF-1-mediated longevity is marked by reduced protein metabolism, Molecular Systems Biology, 9, 10.1038/msb.2013.35 · DOI
  38. Sulak, 2016, TP53 copy number expansion is associated with the evolution of increased body size and an enhanced DNA damage response in elephants, eLife, 5, 10.7554/eLife.11994 · DOI
  39. Sutter, 2007, A single IGF1 allele is a major determinant of small size in dogs, Science, 316, 112, 10.1126/science.1137045 · DOI
  40. Tacutu, 2018, Human ageing genomic resources: new and updated databases, Nucleic Acids Research, 46, D1083, 10.1093/nar/gkx1042 · DOI · Paper page
  41. Williams, 1957, Pleiotropy, natural selection, and the evolution of senescence, Evolution, 11, 10.2307/2406060 · DOI · Paper page
  42. Yang, 2007, PAML 4: phylogenetic analysis by maximum likelihood, Molecular Biology and Evolution, 24, 1586, 10.1093/molbev/msm088 · DOI · Paper page
  43. Zhang, 2015, Determinants of the rate of protein sequence evolution, Nature Reviews Genetics, 16, 409, 10.1038/nrg3950 · DOI

Cited by

Sorted by citations

Metadata

Authors
Kowalczyk, A., Partha, R., Clark, N. L., & Chikina, M.
Affiliations
  • Joint Carnegie Mellon University-University of Pittsburgh PhD Program in Computational Biology, Pittsburgh, United States
  • Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, United States
ORCID
Venue
eLife
Publisher
eLife Sciences Publications, Ltd
Published
2020-02-11
Volume
9
ISSN
2050-084X
DOI
10.7554/elife.51089
PMC
PMC7012612
Cited by
95
References
15
Language
en
Licence
Funders
  • National Institutes of Health (R01HG009299, U54 HG008540)
  • Howard Hughes Medical Institute (T32 EB009403)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review