biological processes modulating longevity across primates

Biological Processes Modulating Longevity across PrimatesA Phylogenetic Genome-Phenome Analysis

Gerard Muntane12 Xavier Farre1 Juan Antonio Rodrıguez3 Cinta Pegueroles45 David A Hughes67

Jo~ao Pedro de Magalh~aes8 Toni Gabaldon459 and Arcadi Navarro1459

1Institute of Evolutionary Biology (UPF-CSIC) Universitat Pompeu Fabra Barcelona Catalonia Spain2Hospital Universitari Institut Pere Mata IISPV Universitat Rovira i Virgili Biomedical Network Research Centre on Mental Health(CIBERSAM) Reus Spain3CNAG-CRG Centre for Genomic Regulation (CRG) The Barcelona Institute of Science and Technology Barcelona Spain4Centre for Genomic Regulation (CRG) The Barcelona Institute of Science and Technology Barcelona Spain5Department of Experimental and Health Sciences Universitat Pompeu Fabra Barcelona Catalonia Spain6Population Health Sciences Bristol Medical School University of Bristol Bristol United Kingdom7MRC Integrative Epidemiology Unit University of Bristol Bristol United Kingdom8Integrative Genomics of Ageing Group Institute of Ageing and Chronic Disease University of Liverpool Liverpool United Kingdom9Institucio Catalana de Recerca i Estudis Avancats (ICREA) Barcelona Spain

Corresponding authors E-mails gerardmuntaneupfedu arcadinavarroupfedu

Associate editor Gregory Wray

Abstract

Aging is a complex process affecting different species and individuals in different ways Comparing genetic variationacross species with their aging phenotypes will help understanding the molecular basis of aging and longevityAlthough most studies on aging have so far focused on short-lived model organisms recent comparisons of geno-mic transcriptomic and metabolomic data across lineages with different lifespans are unveiling molecularsignatures associated with longevity Here we examine the relationship between genomic variation and maximumlifespan across primate species We used two different approaches First we searched for parallel amino-acidmutations that co-occur with increases in longevity across the primate linage Twenty-five such amino-acidvariants were identified several of which have been previously reported by studies with different experimentalsetups and in different model organisms The genes harboring these mutations are mainly enriched in functionalcategories such as wound healing blood coagulation and cardiovascular disorders We demonstrate that thesepathways are highly enriched for pleiotropic effects as predicted by the antagonistic pleiotropy theory of aging Asecond approach was focused on changes in rates of protein evolution across the primate phylogeny Using thephylogenetic generalized least squares we show that some genes exhibit strong correlations between their evolu-tionary rates and longevity-associated traits These include genes in the Sphingosine 1-phosphate pathway PI3Ksignaling and the Thrombinprotease-activated receptor pathway among other cardiovascular processesTogether these results shed light into human senescence patterns and underscore the power of comparativegenomics to identify pathways related to aging and longevity

Key words evolution longevity primates genotype-phenotype aging

IntroductionSenescence or biological aging refers to the general deterio-ration of physiological function of an organism leading to anincreased susceptibility to diseases and ultimately death Oneof the most intriguing and fundamental questions in biologyis why and how such a dazzling array of aging rates exists innature (Jones et al 2014) Just within metazoans aging ratesvary by as much as 10000-fold (Austad 2001) with for in-stance mammals differing gt100-fold in maximum lifespan(or MLS Foote et al 2013) Many lines of evidence supportthe conclusion that longevity is influenced by genetic varia-tion both between and within species (Christensen et al

2006) First estimates of the heritability of lifespan in humanpopulations are 025 (Herskind et al 1996 Hjelmborg et al2006) Second numerous gene mutations have been docu-mented to increase lifespan in a range of model organisms(Kenyon 2010 Barzilai et al 2012) and third different speciesof the same family or even genus occupying similar environ-ments can exhibit stark differences in their lifespans reflectingboth their unique ecology and genetics

Over the years numerous evolutionary aging theoriesand concepts have been postulated (see Trindade et al2013 for a review) although the two most established arethe mutation accumulation (MA) theory (Medawar 1952)

Article

The Author(s) 2018 Published by Oxford University Press on behalf of the Society for Molecular Biology and EvolutionThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(httpcreativecommonsorglicensesby-nc40) which permits non-commercial re-use distribution and reproduction in anymedium provided the original work is properly cited For commercial re-use please contact journalspermissionsoupcom Open Access1990 Mol Biol Evol 35(8)1990ndash2004 doi101093molbevmsy105 Advance Access publication May 21 2018

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and the antagonistic pleiotropy (AP) theory of senescence(Williams 1957) Both hypotheses predict the existence ofgenetic variants with adverse effects expressed later in life(hence modulating lifespan) with the AP theory adding anadaptive aspect since it poses that damaging mutationscould be favored by natural selection if they are advantageousearly in life

From an evolutionary perspective aging is a polygenic andhighly complex process whose expression evolves quite rap-idly with relatively close species displaying very different phe-notypes Of particular interest are current patterns of humanaging which have changed markedly since our divergencewith other primates Indeed primates are an interesting orderfrom the aging perspective since they are evolutionary closeto each other in terms of phylogenetic distances and havehomogeneously slow life histories relative to other mammalswhile displaying profound differences in lifespan Among pri-mates New World monkeys comprise some of both theshortest and longest-lived monkey species Prosimians de-velop the most rapidly and are the shortest lived and incontrast great apes have the slowest development and livethe longest among the primates (Finch and Austad 2012)

Contrary to average life expectancy which may changedepending on living conditions MLS is a stable characteristicof a species and evolves rapidly (Oeppen and Vaupel 2002 deMagalh~aes et al 2007 Foote et al 2013) For instance humansand macaques diverged only30 Ma yet over this time theirMLS has diverged as much as 3-fold (Colman et al 2014)Despite the remarkable evolutionary lability of MLS the exis-tence and nature of the molecular mechanisms involved insuch variation remains unclear

Leveraging primate variation to identify molecular changesthat contribute to increases in longevity among primate spe-cies may help shed light on the selection pressures thatshaped not only our distant past (Enard 2014) but also extantvariation contributing to human lifespans To identify suchchanges it is necessary to compare phenotypic diversity inaging patterns among primates to changes in DNA or proteinsequences that occurred independently on different lineagesof the primate phylogeny (OrsquoConnor and Mundy 2009 2013Lartillot and Poujol 2011 Boddy et al 2017) In fact parallelroutes of molecular evolution may be relatively commonamong protein-coding genes from different species (Scallyet al 2012) and comparative genomic approaches have al-ready been applied to investigate numerous traits such asvocal learning (Wirthlin et al 2014) echolocation (Parkeret al 2013) flight in bats (Zhang et al 2013) adaptation toaquatic life (Yim et al 2014) and evolution in horses (Orlandoet al 2013) A complete comparative approach of MLS needsto consider not only longevity but also other phenotypessuch as body size (Austad 2005 de Magalh~aes et al 2007)and life-history traits that correlated with MLS and may thusconfound the analysis and interpretation (Fushan et al 2015Ma and Gladyshev 2017) Surprisingly this approach hasrarely been applied to lifespan (Aledo et al 2011 Li and deMagalh~aes 2013 Doherty and de Magalh~aes 2016) although afew studies have addressed the mechanisms of plasticity forlifespan within species or established the contributions of

known longevity-related pathways (Bonafe et al 2003Holzenberger et al 2003 Kapahi et al 2004 Lopez-Otınet al 2013) Perhaps due to their limited focus many of thefindings of these works are difficult to reconcile and none ofthem seem to adequately explain all aspects of the agingprocess (Gladyshev 2013)

With such comparative phylogenetic strategy we wereable to identify molecular evolutionary correlates betweengenetic variation and MLS and other primate life-historytraits We deployed two approaches (fig 1) one based onthe detection of parallel mutations and the other one basedon the study of genendashphenotype coevolution using phyloge-netic generalized least squares (PGLS) The latter has provento be a powerful tool to detect genendashphenotype associationsin combination with the root-to-tip dNdS method(Montgomery et al 2011 Montgomery and Mundy 2012a2012b Luke et al 2014 Boddy et al 2017) In summary ourstudy differs from and extends previous comparative studiesin that we 1) consider several life-history variables and 2)perform analyses across the whole primate order Bothapproaches allowed us to identify mutations genes and path-ways that have putatively been fundamental to varying pat-terns of aging across primates

Results

Relationship between Maximum Life Span and OtherLife-History TraitsThe life-history traits under study were largely obtainedfrom the AnAge online database (de Magalh~aes andCosta 2009) They included MLS body mass female ageat sexual maturity gestation length and weaning timeLongevity quotients (LQ) were calculated from the ratioof MLS to the predicted MLS based on the allometric equa-tion for nonflying mammals (de Magalh~aes et al 2007)These traits showed strong correlation among each otherin primates (see supplementary fig 1 SupplementaryMaterial online) To test whether MLS covaries with otherlife-history traits linear regression on the primate pheno-type data was performed Univariate linear regressionshowed that MLS covaries with body mass (adjR2frac14053Plt 2e-16) female age at maturity (adjR2frac14057 Plt 2e-16) weaning time (adjR2frac14049 Plt 2e-16) and gestationlength (adjR2frac14032 Pfrac14 81e-12) Multiple linear regressionfollowed by a type I analysis of variance (ANOVA) showedthat whereas female maturity presents the most significantnominal association with primate longevity (Pfrac14 0002)body mass was the best predictor accounting for 60of the variance of MLS (Pfrac14 003) Age at female maturityaccounted for almost 7 of the remaining variance theremainder (30) being residual error (fig 2A)

Pagelrsquos k model was used to test for phylogenetic signals inprimate traits Consistent with previous findings phylogenyexplained a high proportion of the variance in primate MLS(kfrac14 087) as well as in the other life-history traits (femalematurityfrac14 09 weaning timefrac14 071 gestation lengthfrac14 093body massfrac14 1) The only trait that showed a notably smallerk was LQ which had a value of kfrac14 069 (table 1)

Biological Processes Modulating Longevity across Primates doi101093molbevmsy105 MBE

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Parallel MutationsTo take a simple approximation to the study of any amino-acid changes shared by the species that increase their lifespanwe dichotomized MLS Each primate species was classified ineither of two categories according to the mean value of theprimate family they belong to (see Materials and Methods)The speciesrsquo whose MLS is gt1 SD from the mean of their

family were classified within the Increased Lifespan groupwhereas the rest were categorized as Control The species inthe Increased Lifespan group which present the clearest in-crease in MLS since the ancestor of their family includedHomo sapiens Macaca mulatta and Macaca fascicularis(fig 2B) To confirm the validity of considering human asan Increased Lifespan species rather than discarding it due

FIG 1 Illustrated workflow of the two tests used in this study for measuring variation associated to MLS Parallel amino-acid (AA) changes wereinvestigated across all coding-regions for presence in the Increased Lifespan group of primate species compared with the rest as shown in theexample with a shared ldquoIrdquo (left panel) The second approach (right panel) was planned to test for coevolution between rates of protein evolutionand life-history traits (or in short genendashphenotype coevolution) First root-to-tip dNdS (x) ratios were calculated for each species for each geneUsing a phylogenetically controlled method we tested for a correlation between the log10-transformed rates of protein evolution (ie root-to-tipx x axis) and each life-history trait (eg MLS y axis) A significant linear relationship between gene and phenotype provides support forcoevolution as hypothetically illustrated in the figure

BMas

s

FMat

Ges

t

Wea

n

Erro

r

Type I ANOVA

Prop

ortio

n of

var

ianc

e ex

plai

ned

00

02

04

06

08

A

0 50 100 150

2040

6080

100

120

Species

MLS

CallitrichidaeCebidaeCercopithecidaeCheirogaleidaeDaubentoniidaeGalagonidaeHominidaeHylobatidaeIndridaeLemuridaeLoridaePitheciidaeTarsiidae

macFas5rheMac3

hg38

B

FIG 2 (A) Bar plot showing the variance in MLS explained by each life-history trait as studied in a multivariate model P valuelt 005 Pvaluelt 001 (B) Scatterplot showing variation in MLS (y axis) between primate species (x axis) Colors represent different primate families andspecies selected as Increased Lifespan in the parallel mutations analysis are displayed as bigger dots Dark gray and green lines show respectivelyHominidae and Cercopithecidae mean MLS (solid) and 61 SD values (dashed) UCSC version names were used for species labelingCorrespondence to the species names can be found in supplementary table 5 Supplementary Material online BMass body mass FMat timeto female maturity Gest gestation length Wean weaning time

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to culturally induced increase in lifespan the same criteria wasapplied using 90 years as the MLS record for human whichcould be more adequate for comparative purposes than 122the commonly used value corresponding to the longest docu-mented human lifespan (Lorenzini et al 2005) Even in thiscase humans are gt1 SD from the mean of their family andthus we could safely consider humans as an IncreasedLifespan species Other thresholds besides 1SD MLS increasefrom the family mean were also considered to classify primatespecies However the results were exactly the same with anythreshold between 06 and 14 SDs and poor informationwas obtained from more conservative or stringent cut-offs(supplementary fig 2 Supplementary Material online)Consistently discretizing LQ produced exactly the sameclassification

Out of the19000 genes surveyed 25 parallel amino-acidsubstitutions in 25 different genes were shared by all thespecies in the Increased Lifespan group while absent fromthe Control group (table 2 and supplementary fig 3Supplementary Material online) To ascertain whether thisnumber of parallel changes could be expected by chancewe performed a series of four conservative resampling teststhat produced distributions of parallel changes allowing us toassess the probability of our observation In other words weresampled as many species as within the Increased Lifespangroup three from the phylogeny using four different criteria(see Materials and Methods) In the four sets of permutationsour observation of 25 parallel changes was situated in theempirical percentiles 83 89 92 and 93 respectively Note thatmany of the sampled trios included more closely related spe-cies for which a high number of parallel changes or rathervariants that are identical by descent will naturally be ob-served The mean number of parallel amino-acid changesfound in the four resamplings was 716 258 86 and 57and the median numbers of parallel changes were 3 1 1and 0 respectively (supplementary fig 4 SupplementaryMaterial online) Thus we conservatively concluded thatour observation of 25 parallel changes in the threeIncreased Lifespan species and absent in the rest was notextreme in absolute terms However the observed value ofparallel changes exceeded the median number of observa-tions in the four random scenarios

Of course the fact that 25 parallel changes are withinrandom expectations does not exclude that the gene set isenriched with longevity-related genes Indeed the 25detected genes were significantly enriched in genes previously

related to aging as determined from 10000 bootstrappermutations of 25 genes from the genome (empirical Pvaluefrac14 6e-04) (supplementary fig 5 and table 1Supplementary Material online) Three genes ATG7 MNTand SUPV3L1 were categorized as aging-genes in modelorganisms from the GenAge database (Tacutu et al 2013)Furthermore we evaluated functional enrichment in the 25geneset using GO and KEGG annotations After false discov-ery rate (FDR) correction several biological processesappeared as particularly enriched (fig 3) including blood co-agulation and intrinsic pathway and fibrin clot formation(adjPfrac14 312e-02) negative regulation of hemostasis(adjPfrac14 357e-02) wound healing (adjPfrac14 357e-02) and reg-ulation of body fluids levels (adjPfrac14 357e-02) The KEGGpathway complement and coagulation cascades was alsoenriched (adjPfrac14 7e-04) plus we found enrichment in genesrelated to advanced-age diseases including blood coagulationdisorders (adjPfrac14 2e-04) coagulation protein disorders(adjPfrac14 16e-3) heart diseases (adjPfrac14 64e-03) cardiovasculardiseases and thrombosis (both adjPfrac14 7e-03) hemorrhagicdisorders (adjPfrac14 83e-03) arteriosclerosis adhesion and arte-rial occlusive diseases (adjPfrac14 00126) and coronary disease(adjPfrac14 00133) These results were further validated using theexpanded alignments generated in-house where new species(up-to 25) were included when available (fig 3)

Among the 25 nucleotide positions presenting parallelmutations 20 were fixed for a novel variant in humans(1kGP Database) whereas the remaining five were segregatingvariants (table 2) Out of these latter five variants only threehad a frequency gt1 in human populations (present ingenes BRD8 EFEMP2 and MYO16) and four of them weredefined as tolerated and benign by functional predictions ofthe SIFT and PolyPhen algorithms The mutation in the DSC2gene (pIle520Val) was predicted as highly deleterious andpathogenic by SIFT and PolyPhen respectively Another var-iant in the same amino-acid position (pIle520Thr) produces adilated cardiomyopathy in humans according to the ClinVardatabase In the ExAC Browser database (httpexacbroad-instituteorg) which contains exome data on gt60000 indi-viduals only one individual was found to bear this allele (afrequency of 824e-06) thus it would seem that having an ldquoIrdquoin this position is fixed or almost fixed in humans

The same amino-acid variants were evaluated in the 100-way alignment from UCSC (see Materials and Methods) inanother set of three broadly studied long-lived mammals thenaked mole-rat and two long-lived bats Out of the 25amino-acid positions only 16 were present in the data setamong which 12 were different from the background pri-mate state in at least one of these species and two of themshared the very same change in these long-lived mammalsPRL and STK31 (supplementary table 2 SupplementaryMaterial online)

GenendashPhenotype EvolutionTo assess the relationship between rates of protein evolutionand aging we calculated root-to-tip x values for each geneand species and evaluated their association with life-historytraits using PGLS For each gene all the available primate

Table 1 Lambda (k) Parameter Estimates for All Life-History Traits inPrimates

Life-History Trait k P (k 5 0)a

MLS 087 79e-24LQ 069 64e-11Adult body mass 1 29e-49Female maturity 090 25e-28Gestation length 093 63e-42Weaning time 071 82e-14

aSignificance of difference of the k model from noise (kfrac14 0 LRT)


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sequences were used (at least nfrac14 17) To correct for phylo-genetic history the median value for all the exome-wide root-to-tip xs for all species was included in the PGLS analyses as acovariate We found no significant association betweenexome-wide values and either MLS (Pfrac14 089) body mass(Pfrac14 016) female age at maturity (Pfrac14 038) weaning time(Pfrac14 038) or LQ (Pfrac14 07) in individual PGLS regressions (sup-plementary fig 6 Supplementary Material online) In contrastgestation length and median root-to-tip x values were nom-inally associated (Pfrac14 002)

In the PGLS analyses of the life-history traits only one geneexhibited marginally significant association to gestationlength IQCA1 (adjPfrac14 0049) whereas other genes showeda marginally nonsignificant association (FDRlt 01) to thestudied traits STK17B (adjPfrac14 0060) in MLS and CDC7(adjPfrac14 0065) PER3 (adjPfrac14 0095) and SPRR2G(adjPfrac14 0095) in body mass (fig 4A)

We further assessed for deviation from the null straightline in a QQ-plot of MLS using sets of genes related to se-nescence These genesets were obtained from a review paperon the hallmarks of aging (Lopez-Otın et al 2013 seeMaterials and Methods for details) together with the majorfunctional categories identified with our parallel mutationsstrategy (wound healing and blood coagulation) Most of thecategories were not deviating from the null expectation ex-cept Loss of Proteostasis which revealed ITPR1 (adjPfrac14 003)Moreover wound healing and blood coagulation pathwayspresented the largest deviations from the null distributionwith two genes that were clearly above expectations ITPR1

(adjPfrac14 001) and LBH (adjPfrac14 01) present in both pathways(fig 4B)

The fact that almost no gene reaches significance is prob-ably due to sample size and the drastic loss in statisticalpower induced by multiple-testing but again it does notexclude that the top associations are enriched with aging-related genes or pathways The top genes (nfrac14 26) with anominal P valuelt1e-04 from all assessed traits are partic-ularly enriched in aging genes (empirical Pfrac14 0005) from theGenAge database (supplementary table 3 SupplementaryMaterial online) This list of top genes was enriched in KEGGpathways such as cardiac muscle contraction (adjPfrac14 0015)and Alzheimer disease (adjPfrac14 002) myometrial relaxationand contraction pathways (adjPfrac14 0015) and categoriessuch as Sphingosine 1-phosphate pathway (adjPfrac14 002)IFN-gamma pathway (adjPfrac14 002) Class I PI3K signalingevents (adjPfrac14 002) and Thrombinprotease-activated re-ceptor (PAR) pathway (adjPfrac14 002) among many othersalso diseases such as ventricular outflow obstruction(adjPfrac14 0005) were particularly enriched

PGLS regressions were also performed for the 13 mitochon-drial genes using a set of 93 primate mitochondrial genomesfrom MitoMap Among all the evaluated life-history traitsonly MLS and body mass showed significant associationswith the root-to-tip x of mitochondrial genes Out of the13 mitochondrial genes ATP6 COX3 CYTB and ND1 werecorrelated to MLS and ATP6 and ND1 to body mass aftermitochondrial-FDR correction None of the genes associatedto MLS survived when correction for mitochondrial-wide

Table 2 List of the 25 Genes Found Mutated in the Increased Lifespan Group Together with a Description of Their Polymorphic State in Humansthe Reference and Alternative Alleles in Humans Their Frequency the Reported Change in 1 kG and the Amino-Acid Substitution in Primates

Gene 1kG ref alt Alternative Allele Frequency 1kG_Change Primates Change SIFT PolyPhen2

AKAP9 Not polymorphic I3885VATG7a Not polymorphic T120ABRD8 rs412051 T C AC54894 AF5097 pQ1198R Q1198R 1 T 00 BC1QTNF2a Not polymorphic T9AC9orf96STKLD1 Not polymorphic L297VDSC2a rs561310777 T C AC51 AF5000019 pI520V I520V 0 D 0654 PEFEMP2 rs601314 T C AC54480 AF5089 pI259V I259V 1 T 0001 BFCGBP Not polymorphic V499AFGA Not polymorphic V244AGP5a Not polymorphic Q68HHEMK1a rs192219149 C T AC52 AF5000039 pR98W R98Q 019 T 0001 BIQCK Not polymorphic D21NKIAA1614 Not polymorphic V29MKLKB1 Not polymorphic A29TMNTa Not polymorphic P392SMYO16 rs157024 A G AC5665 AF5013 pI1171M I1171M 00 BMYOF Not polymorphic L135PPLTPa Not polymorphic T435PPRLa Not polymorphic M103IRAD51AP1 Not polymorphic A161VRXFP4 Not polymorphic A167VSTK31a Not polymorphic C933YSUPV3L1a Not polymorphic M330TWDR87a Not polymorphic I36VZNF233a Not polymorphic Q556R

NOTEmdashWhen available SIFT and PolyPhen2 scores are also reported for each changeaDiscovered genes containing one gap in the control group


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root-to-tip xrsquos was applied in the model but ATP6 remainedassociated to body mass after correction (supplementary table4 Supplementary Material online)

Finally to assess the soundness of our PGLS strategy dif-ferent primate phylogenetic trees were tested resulting inconsistent P values (supplementary fig 7 SupplementaryMaterial online)

Overlap between Life-History TraitsNominally significant genes (Plt 005) showing associationbetween root-to-tip x and each of the life-history traits under

study (MLS female maturity gestation length weaning timeand body mass) were retrieved and investigated for overlapThese five life-history traits shared 11 genes which increasesup to 19 genes when body mass is excluded In both liststhe number of overlapping genes was significantly higherthan expected by chance under the assumption of trait in-dependence (empirical-Plt 22e-16 supplementary fig 8Supplementary Material online) The 19 overlapping genesin MLS weaning time gestation and female age at maturity(and body mass excluded) were GP9 ADORA1 CCNJ KCNQ5ZNF300 NKRF EMP1 RARS GDF15 NMUR1 RP1 GAPDHS

FIG 3 Heatmap of the enrichment analyses of genes disclosed in the Increased Lifespan group Analyses are for gene ontology (A) pathwaycommons (B) KEGG pathways (C) and diseases (D) The first columns show pathway enrichments revealed when gaps were not allowed in theparallel mutation analysis (17sp and 25sp) The second columns show the results when one missing specie was allowed in the control group(17spthorn gap 25 spthorn gap) Box diagrams roughly represent DNA Repair (dotted line) and Hemostasis (solid line) categories As shown in the topright legend green and yellow bars in top of the graphs show whether 17 or 25 primate species were used in the analyses Color scale in light yellow(nonsignificant adjP 005) orange (marginally significant 005lt adjPlt 001) and red (significant adjP 005)


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GRAMD4 AKAP7 ACOT13 ZNF408 HSPB6 GABRG1 andBTBD9 This gene list showed enrichment in heart disordersand p73 transcription factor network among other pathways(supplementary fig 9 Supplementary Material online)Among them GDF15 has been previously associated to agingin model organisms (GenAge database) and BTBD9 inhumans (LongevityMap database)

Pathway Enrichment of PleiotropiesAs recently shown by Rodrıguez et al (2017) some variationin our genomes follows the predictions of the AP theory ofsenescence with mutations providing selective advantageearly in life at cost of having an adverse effect in old ageUsing the list of pleiotropies provided by Rodrıguez et al(2017) we could confirm that aging pathways follow thisexpectation with 5 out of the 9 curated hallmarks of aging(Lopez-Otın et al 2013) showing a significant enrichment ofpleiotropic hits when compared with the genome-wide dis-tribution of pleiotropies This observation validates our use ofthese sets as aging-related gene-sets These categories werealtered intracellular communication mitochondrial dysfunc-tion cellular senescence genomic instability and telomere

attrition The rest were not significant after FDR correction(table 3) Wound healing and blood coagulation which arepathways identified here as having an evolutionary relation-ship to aging in primates were also evaluated for enrichmentin pleiotropies and both turned out to be strongly enriched(wound healing Pfrac14 26e-09 and blood coagulationPfrac14 233e-05) (table 3)

DiscussionBiological mechanisms related to aging rates include but arenot limited to the production of reactive oxygen species(ROS) control of oxidative damage telomere shortening var-ious signaling pathways that produce antagonisms betweendevelopment and aging and inflammation responses thatproduce antagonisms between disease prevention and tissuedamage (Ricklefs 2010 Lopez-Otın et al 2013) Other pro-cesses particularly developmental mechanisms that influencelife-history phenotypes might be brought into play by evo-lution including immune functions or inflammatory path-ways (Finch 2010 Franceschi et al 2017) How do thesemechanisms account for variations in lifespan in the evolu-tion of our species From an evolutionary standpoint it is

FIG 4 Phylogenetically controlled regression (PGLS) between log10 root-to-tip x for STK17B (A) and IQCA1 (B) and log10 MLS and log10 Gestationlength respectively across primate phylogeny The dotted red line represents the regression intercept of the linear model (nonphylogeneticallycorrected) UCSC version names were used for species labeling Correspondence to the species names can be found in supplementary table 5Supplementary Material online (C) QQ-plots illustrating the P values from each gene set of the root-to-tip x in MLS As depicted in the figureoutliers were above the null probability distribution corresponding to ITPR1 and LBH genes respectively


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surprising that despite strong evidence that increases in life-span have occurred in parallel in several independent primatespecies such changes have been largely ignored in previouslarge-scale genomic comparisons Here we leveraged on theconsiderable variation in lifespans across the primate lineageto identify mutations and patterns of genic evolution thatrelate to aging In particular we targeted mutations that haveoccurred parallel to increases of lifespan and correlations be-tween the rates of protein evolution and several life-historytraits (fig 1)

Mutations Parallel to Increased LifespanFirst we tested for convergent changes occurring in long-livedprimate species (to be precise in primate species presentingrelatively recent increases in lifespan) This is a reasonablehypothesis especially since convergence at the genetic levelseems to be more frequent than initially thought (Stern2013) We identified a set of 25 genes sharing convergentnonsynonymous mutations in three Increased Lifespan pri-mate species About 3 of the 25 genes have been previouslyrelated to longevity in model organisms as reported in theGenAge database ATG7 MNT and SUPV3L1 This is morethan what would be expected by chance (Pfrac14 6e-04) andhighlights the role of these genes in increasing aging via subtleamino-acid modifications ATG7 encodes an essential enzymefor autophagy which also functions as a modulator of p53 inthe regulation of survival during metabolic stress amongmany other roles (Lee et al 2012 Xiong 2015) Notably theinactivation of this gene leads to reduced lifespan in modelorganisms (Jia and Levine nd Juhasz and Neufeld 2008Eisenberg et al 2009 Mizushima and Levine 2010 Pyo et al2013) More specifically it results in loss of autophagy viadeletion of ATG7-impaired DNA repair by homologous re-combination through failed RAD51 recruitment (Liu et al2015) MNT is a tumor suppressor that has been also de-scribed to extend lifespan in Drosophila melanogaster andCaenorhabditis elegans (Demontis et al 2014) Finallymutants of the mitochondrial degradosome proteinSUPV3L1 have been described to increase lifespan in aSaccharomyces cerevisiae model (Caballero et al 2011)Although not directly associated to aging a few other genesfrom the list of 25 hold promise for further experimental

scrutiny particularly considering their known functions orrelation to aging phenotypes (supplementary table 1Supplementary Material online) One example is DSC2 forwhich a predisposing mutation (c631-2AgtG) implicated incardiopathy has been identified in one of the supercentenar-ians sequenced in a collection of the worldrsquos oldest people(Gierman et al 2014)

Although further functional data are necessary to demon-strate that these associations reflect causative relations withlifespan evolution our results suggest that biological mecha-nisms related to wound healing hemostasis blood coagula-tion clot formation and many cardiovascular pathways arecornerstones of lifespan changes in the primate lineage Inagreement with our results it has been largely documentedthat all phases of wound healing become delayed with age(Yanai et al 2015 Keyes et al 2016) and that imbalances inthe hemostatic system are a common feature of the agingprocess (Franchini 2006 Mari et al 2008) Additionally geneexpression signatures of blood coagulation are upregulatedwith age (de Magalhaes et al 2009) and interestingly cardiacfunctioning improves in dogs after just weeks of an antiagingtreatment with rapamycin (Urfer et al 2017) Moreover olderage has long been associated with altered inflammation andhemostasis regulation since cardiovascular-related pathwayshave prominent roles influencing human longevity (Pillinget al 2016) Thus specific changes to wound healing andcoagulation-related genes and pathways may underlie phe-notypic changes in aged individuals and trigger lifespan in-crease perhaps as a consequence of decreasing the risk ofsuffering cardiovascular diseases

It is of note that most of the genetic variants that appear inparallel with increases in primate lifespan are fixed in humanswhich highlights the importance of comparative genomicsapproaches since they yield results that are complementaryto those in within-species analysis that cannot access suchvariation Further studies using intraspecific variation acrossnonhuman primates are needed to address whether thesevariants are or not also fixed in them

Pleiotropies in the Aging PathwaysGenes affecting longevity might be crucial for organismic de-velopment implying that these genes are under selective

Table 3 Pleiotropies Found in Each Category

Hallmarks of Aging Genes SNPs n Pleios PleiosSNP P value SNPsGenes

Cellular senescence 51 44 29 065 lt22e-16 086Telomere attrition 117 43 26 060 194e-15 036Mitochondrial dysfunction 228 80 27 033 168e-08 035Genomic instability 483 96 27 028 109e-06 019Altered intracellular communication 624 354 65 018 468e-06 056Epigenetic alterations 528 172 34 019 000018 032StemCell exhaustion 105 75 13 017 00449 071Loss of proteostasis 811 210 26 012 02 025Deregulated nutrient sensing 185 58 8 013 025 031Wound healing 561 181 47 026 266e-09 032Blood coagulation 324 110 27 025 233e-05 034

NOTEmdashAsterisks represent significant categories after FDR correction


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pressures so that mutations are subject to complex trade-offsIn fact natural selection does not act on longevity per se butrather on survival and ultimately on reproductive successThis makes interpretations very difficult as the existence ofpleiotropic effects in genes involved in aging could lead to areduced capacity for their identification in the framework ofan evolutionary approach given that multiple functions canbe under the control of each gene In our analyses we exam-ined how genes previously described to be associated withaging were related to the pleiotropies described in Rodrıguezet al (2017) and we showed that 5 pathways out of 9 werehighly enriched in such pleiotropies Similarly wound healingand blood coagulation categories proposed by our evolution-ary analysis in primates were also enriched in pleiotropiceffects highlighting that these genes are involved in multiplepathways and exhibiting the importance that these categoriescould have in the evolution of senescence as predicted by theAP theory of aging In agreement with our results a recentstudy found that coronary artery disease loci are enriched inantagonistic-pleiotropic signals and suggests that natural se-lection may have maintained genetic variation contributingto cardiovascular disorders because of its beneficial effects inearly life (Byars et al 2017)

GenendashPhenotype CoevolutionPGLS treats both molecular and phenotypic data as contin-uous traits and can detect subtle variation between species aswell as associations between genes and phenotypes that areconsistent across a phylogeny Since most of the variation inrate of actual senescence within species is caused by stochas-tic variation and measurement error (Ricklefs 2010 Ma andGladyshev 2017) we also incorporated other life-history traitsinto the analyses Our PGLS study identified key genescoevolving with interspecific variation in longevity-associated traits IQCA1 (adjPfrac14 004) was revealed to be sig-nificantly associated to gestation length On the other handSTK17B (adjPfrac14 006) and CDC7 PER3 and SPRR2G were sig-nificantly associated to MLS and body mass (adjPlt01) re-spectively The 19 nominally significant genes (Plt 005)overlapping in the four life-history traits evaluated (MLS fe-male maturity weaning and gestation length) disclosed path-ways such as p73 transcription factor network andcardiovascular disorders Interestingly p73 has been previ-ously linked to senescence and aging (Rufini et al 2013)and the existence of cardiovascular phenotypes also foundin the coevolution approach suggests that the same processesmay have evolved along different routes to adapt to the longlifespans and slow development of primates Moreover thelist of top genes (Plt 1e-04) in all the studied phenotypes wasparticularly enriched in Sphingosine 1-phosphate pathwayIFN-gamma pathway Class I PI3K signaling events andThrombinprotease-activated receptor (PAR) pathway to-gether with other cardiovascular pathways Thrombin playsa critical role in hemostasis and coagulation whereas Class IPI3K activation finally leads to mTORC1 activation triggeringcellular growth (Dibble and Cantley 2015) FinallySphingosine-1-phosphate is primarily involved in supporting

growth and survival and it might contribute to aging by AP-like effects (Huang et al 2014)

Furthermore our analysis revealed associations betweenmitochondrial genes and MLS ATP6 COX3 CYTB andND1 Among them ATP6 has been previously associatedwith differences in metabolism and selection linked to ener-getics (da Fonseca et al 2008) and CYTB has been foundassociated to longevity in mammals using a linear modelanalysis (Feng and Zhou 2017) Because molecular evolutionrates correlate with generation times in mammals (Bromhamet al 1996) it is not surprising to find mitochondrial genesthat correlate with life-history traits in our study Even thoughsubsequent analyses suggested that this association is due tocovariation between generation time and longevity (Nabholzet al 2008) In favor of the latter when mean mitochondrial-wide x values were included as covariate in our model allsignals associated to longevity disappeared

Limitations of the Present StudyOur study did not examine genetic variation among individ-uals from the same species or over an individual lifespan butrather compared genetic variation among reference individ-uals of different species At the time of analysis only 17 fullprimate genomes were available although we could gatherup to 25 primate species for some of the genes The additionof more species to the analysis has the potential to contributeindependent variation in longevity thus increasing power Onthe other hand and since more distant species may differconsiderably in their developmental andor genetic mecha-nisms increasing the number of species may also result inadding more noise to the analysis At any rate despite therelatively small number of species in our analyses we still findseveral genes with a phylogenetic association with MLS andother life-history traits providing evidence for conserved mo-lecular mechanisms on the evolution of senescence

We have also identified several genes that coevolved withlife-history traits in primates However our PGLS approachcan only detect cases in which proteins and traits haveevolved consistently (that is when accelerated protein evo-lution has results in a systematic increment or decrement of atrait) so we cannot exclude neither the possibility that dif-ferent species-specific mechanisms might have evolved inparallel nor other more complex relationships between ratesof protein evolution and the traits under study All thesepossibilities remain to be assessed in future work

ConclusionsTo our knowledge this is the first systematic report providingdirect evidence of genendashphenotype evolution of aging-relatedtraits in primates Genes and biological processes reported inthis study could be added to the list of genes that increaselifespan when overexpressed or mutated (gerontogenes) andrepresent a valuable resource for examination of new candi-date interventions that mimic gene evolution associated withnatural changes in lifespan

Although our results may reflect local adaptive responsesof species to their environment we observed nonrandomassociation of gene evolution with pathways mainly related


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to wound healing coagulation and many cardiovascular pro-cesses This would make sense from a biological perspectivesince flexible and adjustable control of coagulation mecha-nisms is required for species that live longer As far as weknow for the first time we report pathways putatively in-volved in maximum lifespan and correlated life-history traitsThis can be explained in part by the fact that many studies inthe field have been using models such as yeast or C elegansAlthough these model organisms have proven very useful inmany aspects they are quite different from humans and lackmany of the molecular pathways that are fundamental inmore complex animals living under natural conditions

These findings provide direct insights into how nature re-versibly adjusts lifespan and other traits during adaptive ra-diation of primates and provide evidence that cardiovascularand hemostatic pathways evolve adaptively to allow forincreases in longevity

Materials and Methods

Phenotypic and Genomic DatabasesThe life-history traits evaluated in this study include MLSadult body mass female age at sexual maturity gestationlength and weaning time These variables were largelyobtained from the AnAge online database (de Magalh~aesand Costa 2009) Longevity quotients (LQ) were calculatedfrom the ratio of MLS to the predicted MLS based on theallometric equation for nonflying mammals (de Magalh~aeset al 2007) When information was not available in AnAge itwas complemented by collecting data from additional sour-ces such as the Animal Diversity Web (ADW) database(Myers et al 2013) accessed at httpanimaldiversityorgPrimate data from AnAge and ADW showed a strong corre-lation in life-history measures (supplementary fig 10Supplementary Material online) Correlation coefficientswere 086 for MLS 088 for gestation 099 for adult weightand 1 for birth mass All data used in the analyses can befound in supplementary table 5 Supplementary Materialonline

The consensus molecular chronogram tree for primateswas downloaded from the 10kTrees project version 3(Arnold et al 2010) at http10ktreesnunn-laborg The10kTrees data set is based on sequences of 11 mitochondrialand 6 autosomal genes sampled from GenBank 10KTreesphylogenies contain 301 species of primates out of which174 were present in our phenotype data set (fig 5) Thedatabase of life-history traits was adapted to the taxa fromthe phylogeny and the primate species tree was pruned tocontain the species used in each analysis

Human 20-way multiple alignments were downloaded for38851 coding sequences from the UCSC browser at httpsgenomeucscedu (accessed August 2016) These files in-cluded multiple alignments from 17 primate species plusMus musculus Tupaia belangeri and Canis lupus whichwere discarded from the analyses Of all transcripts onlythe longest one was kept for each gene Gene alignmentswith an overall number of gapsgt 50 and alignments whereat least 2 of the species had gt50 of the sequence in gaps

were discarded To avoid numerical problems with the logtransformation and unrealistic substitution rates the speciesfor which root-to-tip x had a value of 0 were discarded Afterfiltering a total of 16891 canonical genes were included in thestudy

Additionally protein multiple alignments of 179 primatespecies were downloaded from NCBIrsquos Organelle GenomeResources for the 13 mitochondrial genes For 93 out of the179 primate species data on life-history traits were availableand were included in the consensus 10kTrees tree The nu-cleotide alignment of the mitochondrial genes for the 93primate species was carried out with MAFFT v7271 (Katohand Standley 2013)

Multiple Alignments of New SpeciesTo enrich our set of primate alignments we used the follow-ing pipeline First we retrieved transcript sequences in FASTAformat from Aotus nancymaae Cebus capucinus imitatorCercocebus atys Colobus angolensis Macaca nemestrinaMandrillus leucophaeus Propithecus coquereli Rhinopithecusbieti from NCBI via ftp (accessed in March 2017) To findputative orthologues we ran BLASTN with an e-value cut-off of 1e-4 using the human sequences from the UCSC align-ments as a query Then we used an in-house python script totrim the untranslated regions from the retrieved sequencesusing the first and last nine nucleotides of the human sequen-ces and allowing a maximum of two mismatchesSubsequently we computed multiple alignments for eachgene using MAFFT v7271 (Katoh and Standley 2013) In afirst filtering step we calculated for each gene the averagepairwise percentage of identity using trimAl v14rev15(Capella-Gutierrez et al 2009) and an in-house script andwe removed those sequences havinglt60 of average se-quence identity Then we translated the nucleotidesequences into protein using an in-house script and wealigned the protein sequences using MAFFT v7271 To re-move incorrectly annotated sequences or those containingframe-shifts we used trimAl as described above to discardsequences withlt60 of average sequence identity at theprotein level Finally we used pal2nal v14 (Suyama et al2006) to back translate the final protein alignments andobtain the final nucleotide alignments After this process17663 canonical genes were retained and 1337 genes dis-carded due to poor similarity In the final set 8554 align-ments included 17 or more primate species (supplementarytable 6 Supplementary Material online)

Relation between Life History and Phylogeny inPrimatesCorrelation between life-history traits was assessed usingSpearmanrsquos correlation Nonphylogenetic regressions wereused to test whether maximum lifespan covaries with otherlife-history traits (log-transformed) We used Pagelrsquos k modelto test for phylogenetic signals in primate life-history traitsThis method estimates to which extent a correlation betweengiven traits reflects the shared evolutionary history of thespecies (Pagel 1999) Pagelrsquos k describes the proportion ofvariance that can be attributed to Brownian motion along


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a phylogeny (neutral drift) A value of k equal or close to 1suggests a character evolving stochastically whereas klt 1indicates departure from neutral drift Estimates of k for alllife-history traits were computed using the phylosig functionin the phytools package in R (Revell 2012)

Parallel Amino-Acid SubstitutionsTo discretize continuous traits such as MLS and LQ meanvalues of both traits were calculated for each of the 14 pri-mate families using all primate records (table 4) That allowedus to split the data set in two groups Species that fall gt1 SDfrom the mean of their family were considered as specieshaving Increased Lifespan The rest were grouped togetherin the Nonincreased Lifespan or Control group (fig 2B) Thenan in-house script was used to identify parallel amino-acidchanges across all coding regions Parallel mutations wereidentified as the same amino-acid change occurring in allthe species labeled as Increased Lifespan and in none of theother species (the Control group) One gap at each amino-acid position was permitted in the Control group

Parallel amino-acid substitutions were evaluated in the setof canonical genes across the 17 primate species phylogenyusing multiple protein-coding alignments from UCSC Newprimate species aligned in this study were used to further

confirm the results whenever possible given sequence avail-ability Finally when available sequences from other long-lived animals such as the naked-mole rat (Heterocephalusglaber) and two bats (Myotis davidii and Myotis lucifugus)which are part of the 100-way alignments from UCSC wereevaluated for the observed amino-acid variants

To assess whether the number of parallel changes foundwas higher than expected by chance we used four series ofconservative resampling tests Three species were (1) ran-domly selected from the primate tree and the number ofparallel changes evaluated for each combination and in orderto resemble as much as possible the Increased Lifespan set ofspecies three species were (2) randomly selected from thetree but limiting the sampling to 2 species of Cercopithecidae(Old World catarrhine monkeys) and an outgrup species (3)resampling was forced to contain 2 Cercopithecidae speciesand one Hominoidea and (4) resampling was performedcomparing humans to a combination of 2 Cercopithecidae(as shown in supplementary fig 11 Supplementary Materialonline)

We assessed human polymorphism levels for all the ge-nome positions corresponding to the list of identified parallelmutations To do so we used the 1000 Genomes Projectpanel (1kGP 1000 Genomes Project Consortium 2015) The

FIG 5 Circular tree created using all the primate species with longevity records from online databases (AnAge and Animal Diversity Web) In redthe 17 species from which genetic data were obtained from UCSC database are shown New primate species added in this study to enrich thediversity of primates are shown in orange (nfrac14 8) Species from which genetic data are not included in the study are shown in black External greenbars represent the MLS records obtained Lower values for MLS are shown in darker red higher values are shown in blue (nfrac14 174 species)


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discovered positions in the human hg19 build were deter-mined and the frequencies of the reference and the alterna-tive alleles were extracted from 1kGP for all humanpopulations using Annovar (Wang et al 2010) Functionalprediction of variants from SIFT and PolyPhen2 scores werealso obtained

Evolutionary Analyses GenendashPhenotype Coevolutionacross PrimatesEstimates of the dNdS during the evolution of each species asthe divergence from their last common ancestor termedldquoroot-to-tip dNdSrdquo were obtained for each gene using thefree ratio model from PAML 49 (Yang 2007) The root-to-tipdNdS (x) is more inclusive of the evolutionary history of alocus and it is a property of the species tip rather than theterminal branch Therefore it is more suitable for regressionsagainst phenotypic data from extant species (Montgomeryand Mundy 2013) Briefly for each gene and species root-to-tip dNs were summed up (the number of nonsynonymoussites of a given gene in the corresponding species) and root-to-tip dSs were summed up (the number of synonymoussites) Finally the ratio between the obtained dN and dSwas used as a measure of root-to-tip x for each speciesThe root-to-tip xs were then subjected to regression analysisin the PGLS framework As we were evaluating all the genessimultaneously (17000) and the corresponding BonferroniP value is 2e-06 which is overly stringent for this analysiswe instead adopted the 10 adjusted false discovery rate qvalue cutoff (Storey and Tibshirani 2003)

Association of gene and phenotypic changes were evalu-ated using the PGLS Brownian motion method from the Rlibrary nlme and P values for each gene root-to-tip x werekept Outliers can seriously affect the parameter estimates inany regression model thus when necessary species with stu-dentized residualsgt63 were removed and PGLS was fittedagain without the phylogenetic outliers (Jones and Purvis1997)

Finally associations between rates of protein evolution andlife-history traits should also take into account that such traitsare not independent from their phylogenetic history thus

genome-wide rates of protein evolution were also includedin the PGLS regressions as an independent variable (see nextsection) In all analyses life-history variables and root-to-tipxs were log10 transformed to make variances closer to lin-earize relationships between the variables and to make vari-ation scale-independent (ie related to proportional ratherthan absolute differences between observations)

In total 16891 nuclear genes underwent PGLS analyses weused in-house alignments for the 8554 multiple alignmentsthat contained more than 17 species For the rest the align-ments downloaded from UCSC were used to guarantee thatthe assessed gene alignments contained at least 17 primatespecies

The 13 mitochondrial genes were assessed for genendashphe-notype coevolution using the same PGLS regression pipelinedescribed earlier In that case evaluation of Pagelrsquos k was donesimultaneously to fitting PGLS using the method corPagelfrom R library nlme which calculates the phylogenetic signalin the sample and accounts for it This could be done in themitochondrial analyses because of the larger sample size ascompared with the whole-genome approach In the latter wedid not have enough power to use corPagel method andBrownian motion was chosen (supplementary fig 12Supplementary Material online)

Genome-Wide Rates of EvolutionInterspecific variation in effective population size could alterthe rate of neutral substitution and the efficacy of selection toremove or fix nonsynonymous substitutions This effect couldbias our phylogenetic regression analyses if effective popula-tion size covaries with the studied traits To address this weobtained estimates of genome-wide root-to-tip x by calcu-lating the median root-to-tip values for each species andadded them as covariates in the PGLS analyses The sameprocedure was applied to mitochondrial gene sequences toobtain an estimate of mitochondrial-wide x We then usedthese values in a PGLS regression to test for an associationwith the studied traits and the median genome rate ofevolution

Table 4 Mean MLS and LQ Computed Using All Records from the Primate Database

na MLS Mean MLS SD MLS Limits LQ Mean LQ SD LQ Limits

Callitrichidae 19 2049 419 163ndash246 166 031 13ndash19Cebidae 24 3649 922 272ndash457 219 053 16ndash27Cercopithecidae 66 3086 559 252ndash364 163 026 13ndash18Cheirogaleidae 6 1944 467 147ndash241 17 04 13ndash21Daubentoniidae 1 233 ndash ndash 146 ndash ndashGalagonidae 8 1762 337 142ndash209 148 014 13ndash16Hominidae 6 6822 2666 415ndash948 266 112 15ndash37Hylobatidae 10 4592 737 385ndash532 245 041 2ndash28Indridae 5 2575 608 196ndash318 146 034 11ndash18Lemuridae 12 3001 804 219ndash380 187 045 14ndash23Loridae 5 204 585 145ndash262 159 032 12ndash19Megaladapidae 2 ndash ndash ndash ndash ndash ndashPitheciidae 7 2852 718 213ndash357 19 046 14ndash23Tarsiidae 2 1615 021 159ndash163 159 002 15ndash16

aNumber of species included in each primate family


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Pleiotropies and Aging-Related GenesetsTo study genes that have been previously related to aging alist of curated human genes associated with aging in differentmodel systems was obtained from the GenAge data set (deMagalh~aes et al 2005) We used gene ontology (GO) anno-tation which describes how gene products behave in a cel-lular context to select GO categories encompassingmechanisms or functions corresponding to processes consid-ered hallmarks of aging in Lopez-Otın et al (2013) (supple-mentary table 7 Supplementary Material online) AdditionalGO categories such as wound healing (GO 0042060) andblood coagulation (GO 0007596) were also studied HumanGO gene sets were downloaded from AmiGO (Carbon et al2009) a tool for searching and browsing the Gene Ontologydatabase (amigogeneontologyorgamigo) To evaluatewhether these gene sets were enriched in pleiotropic signalswe retrieved cases of putative pleiotropies from the GWASCatalog (MacArthur et al 2017) by selecting cases in which agiven SNP or group of SNPs in LD have been associated withtwo or more pathologies by different GWAS studies using themethod described in Rodrıguez et al 2017 Binomial tests ineach of the aging categories (Lopez-Otın et al 2013) werecompared with genome-wide expectations (2559 disease-associated alleles and 266 pleiotropies see Rodrıguez et al2017)

Pathway EnrichmentPathway analyses were performed to explore possible biolog-ical mechanisms that may underlie the associations betweenthe identified genes and aging pathways We used The KyotoEncyclopedia of Genes and Genomes (KEGG) pathways GOontology Pathway commons and disease-associated genesfrom WebGestalt for our analyses (Wang et al 2013) Foreach pathway the hypergeometric test was used to detectthe overrepresentation of our set of genes among all genes inthe pathway Lastly FDR was controlled using the BenjaminindashHochberg procedure In all cases the complete set of protein-coding genes was used as the background

Supplementary MaterialSupplementary data are available at Molecular Biology andEvolution online

AcknowledgmentsThis work was supported by Ministerio de Ciencia eInnovacion Spain (BFU2012-38236 and BFU2015-68649-P(MINECOFEDER UE) to AN) by Direccio General deRecerca Generalitat de Catalunya (2014SGR1311 and2014SGR866 to AN and 2014BP-B00157 to GM) by theSpanish National Institute of Bioinfomatics of the Institutode Salud Carlos III (PT1300010026) by ldquoUnidad deExcelencia Marıa de Maezturdquo funded by the MINECO (refMDM-2014-0370) and by FEDER (Fondo Europeo deDesarrollo Regional)FSE (Fondo Social Europeo) We wouldlike to thank Greg Gibson for his helpful discussions and sug-gestions This research was performed at Institut BiologiaEvolutiva Universitat Pompeu Fabra Barcelona Spain

References1000 Genomes Project Consortium 2015 A global reference for human

genetic variation Nature 52668ndash74Aledo JC Li Y de Magalh~aes JP Ruız-Camacho M Perez-Claros JA 2011

Mitochondrially encoded methionine is inversely related to longev-ity in mammals Aging Cell 10(2)198ndash207

Arnold C Matthews LJ Nunn CL 2010 The 10kTrees website a newonline resource for primate phylogeny Evol Anthropol Issues NewsRev 19(3)114ndash118

Austad SN 2001 An experimental paradigm for the study of slowlyaging organisms Exp Gerontol 36599ndash605

Austad SN 2005 Diverse aging rates in metazoans targets for functionalgenomics Mech Ageing Dev Funct Genomics Ageing II 126(1)43ndash49

Barzilai N Guarente L Kirkwood TBL Partridge L Rando TA SlagboomPE 2012 The place of genetics in ageing research Nat Rev Genet13(8)589ndash594

Boddy AM Harrison PW Montgomery SH Caravas JA Raghanti MAPhillips KA Mundy NI Wildman DE 2017 Data from Evidence of aconserved molecular response to selection for increased brain size inprimates Genome Biol Evol 9(3)700ndash713

Bonafe M Barbieri M Marchegiani F Olivieri F Ragno E Giampieri CMugianesi E Centurelli M Franceschi C Paolisso G 2003Polymorphic variants of insulin-like growth factor I (IGF-I) receptorand phosphoinositide 3-kinase genes affect IGF-I plasma levels andhuman longevity cues for an evolutionarily conserved mechanismof life span control J Clin Endocrinol Metab 88(7)3299ndash3304

Bromham L Rambaut A Harvey PH 1996 Determinants of rate varia-tion in mammalian DNA sequence evolution J Mol Evol43(6)610ndash621

Byars SG Huang QQ Gray L-A Bakshi A Ripatti S Abraham G StearnsSC Inouye M 2017 Genetic loci associated with coronary arterydisease harbor evidence of selection and antagonistic pleiotropyPLoS Genet 13(6)e1006328

Caballero A Ugidos A Liu B euroOling D Kvint K Hao X Mignat C Nachin LMolin M Nystrom T 2011 Absence of mitochondrial translationcontrol proteins extends life span by activating sirtuin-dependentsilencing Mol Cell 42(3)390ndash400

Capella-Gutierrez S Silla-Martınez JM Gabaldon T 2009 trimAl a toolfor automated alignment trimming in large-scale phylogenetic anal-yses Bioinformatics 25(15)1972ndash1973

Carbon S Ireland A Mungall CJ Shu S Marshall B Lewis S Lomax JMungall C Hitz B Balakrishnan R et al 2009 AmiGO online accessto ontology and annotation data Bioinformatics 25(2)288ndash289

Christensen K Johnson TE Vaupel JW 2006 The quest for geneticdeterminants of human longevity challenges and insights Nat RevGenet 7(6)436ndash448

Colman RJ Beasley TM Kemnitz JW Johnson SC Weindruch RAnderson RM 2014 Caloric restriction reduces age-related andall-cause mortality in rhesus monkeys Nat Commun 53557

da Fonseca RR Johnson WE OrsquoBrien SJ Ramos MJ Antunes A 2008 Theadaptive evolution of the mammalian mitochondrial genome BMCGenomics 9119

de Magalh~aes JP Costa J 2009 A database of vertebrate longevityrecords and their relation to other life-history traits J Evol Biol22(8)1770ndash1774

de Magalh~aes JP Costa J Church GM 2007 An analysis of the relation-ship between metabolism developmental schedules and longevityusing phylogenetic independent contrasts J Gerontol A Biol Sci MedSci 62(2)149ndash160

de Magalh~aes JP Costa J Toussaint O 2005 HAGR the human ageinggenomic resources Nucleic Acids Res 33(Databaseissue)D537ndashD543

de Magalhaes JP Curado J Church GM 2009 Meta-analysis of age-related gene expression profiles identifies common signatures ofaging Bioinformatics 25(7)875ndash881

Demontis F Patel VK Swindell WR Perrimon N 2014 Intertissue controlof the nucleolus via a myokine-dependent longevity pathway CellRep 7(5)1481ndash1494


2002

Dow


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Dibble CC Cantley LC 2015 Regulation of mTORC1 by PI3K signalingTrends Cell Biol 25(9)545ndash555

Doherty A de Magalh~aes JP 2016 Has gene duplication impacted theevolution of Eutherian longevity Aging Cell 15(5)978ndash980

Eisenberg T Knauer H Schauer A Buttner S Ruckenstuhl C Carmona-Gutierrez D Ring J Schroeder S Magnes C Antonacci L et al 2009Induction of autophagy by spermidine promotes longevity Nat CellBiol 11(11)1305ndash1314

Enard W 2014 Comparative genomics of brain size evolution FrontHum Neurosci 8345

Feng P Zhou Q 2017 Absence of relationship between mitochondrialDNA evolutionary rate and longevity in mammals except for CYTB JMamm Evol doiorg101007s10914-017-9399-4

Finch CE 2010 Evolution of the human lifespan and diseases of agingroles of infection inflammation and nutrition Proc Natl Acad Sci U SA 107(suppl_1)1718ndash1724

Finch CE Austad SN 2012 Primate aging in the mammalian scheme thepuzzle of extreme variation in brain aging Age 34(5)1075ndash1091

Foote AD Kaschner K Schultze SE Garilao C Ho SYW Post K HighamTFG Stokowska C van der Es H Embling CB et al 2013 AncientDNA reveals that bowhead whale lineages survived Late Pleistoceneclimate change and habitat shifts Nat Commun 41677

Franceschi C Garagnani P Vitale G Capri M Salvioli S 2017Inflammaging and ldquoGarb-agingrdquo Trends Endocrinol Metab28(3)199ndash212

Franchini M 2006 Hemostasis and aging Crit Rev Oncol Hematol60(2)144ndash51

Fushan AA Turanov AA Lee S-G Kim EB Lobanov AV Yim SHBuffenstein R Lee S-R Chang K-T Rhee H et al 2015 Gene expres-sion defines natural changes in mammalian lifespan Aging Cell14(3)352ndash365

Gierman HJ Fortney K Roach JC Coles NS Li H Glusman G Markov GJSmith JD Hood L Coles LS Kim SK 2014 Whole-genome sequenc-ing of the worldrsquos oldest people PLoS One 9(11)e112430

Gladyshev VN 2013 The origin of aging imperfectness-driven non-ran-dom damage defines the aging process and control of lifespanTrends Genet 29(9)506ndash512

Herskind AM McGue M Holm NV Soslashrensen TI Harvald B Vaupel JW1996 The heritability of human longevity a population-based studyof 2872 Danish twin pairs born 1870-1900 Hum Genet97(3)319ndash323

Hjelmborg JB Iachine I Skytthe A Vaupel JW McGue M Koskenvuo MKaprio J Pedersen NL Christensen K 2006 Genetic influence onhuman lifespan and longevity Hum Genet 119(3)312ndash321

Holzenberger M Dupont J Ducos B Leneuve P Geloeuroen A Even PCCervera P Le Bouc Y 2003 IGF-1 receptor regulates lifespan andresistance to oxidative stress in mice Nature 421(6919)182ndash187

Huang X Withers BR Dickson RC 2014 Sphingolipids and lifespan reg-ulation Biochim Biophys Acta 1841(5)657ndash664

Jia K Levine B nd Autophagy is required for dietary restriction-mediated life span extension in C elegans Autophagy 3(6)597ndash599

Jones KE Purvis A 1997 An optimum body size for mammalsComparative evidence from bats Funct Ecol 11(6)751ndash756

Jones OR Scheuerlein A Salguero-Gomez R Camarda CG Schaible RCasper BB Dahlgren JP Ehrlen J Garcıa MB Menges ES 2014Diversity of ageing across the tree of life Nature 505(7482)169ndash173

Juhasz G Neufeld TP 2008 Drosophila Atg7 required for stress resis-tance longevity and neuronal homeostasis but not for metamor-phosis Autophagy 4(3)357ndash358

Kapahi P Zid BM Harper T Koslover D Sapin V Benzer S 2004Regulation of lifespan in Drosophila by modulation of genes in theTOR signaling pathway Curr Biol 14(10)885ndash890

Katoh K Standley DM 2013 MAFFT multiple sequence alignment soft-ware version 7 improvements in performance and usability Mol BiolEvol 30(4)772ndash780

Kenyon CJ 2010 The genetics of ageing Nature 467(7315)622ndash622Keyes BE Liu S Asare A Naik S Levorse J Polak L Lu CP Nikolova M

Pasolli HA Fuchs E Mesirov JP 2016 Impaired epidermal to

dendritic T cell signaling slows wound repair in aged skin Cell167(5)1323ndash1338e14

Lartillot N Poujol R 2011 A phylogenetic model for investigating cor-related evolution of substitution rates and continuous phenotypiccharacters Mol Biol Evol 28(1)729ndash744

Lee IH Kawai Y Fergusson MM Rovira II Bishop AJR Motoyama NCao L Finkel T 2012 Atg7 modulates p53 activity to regulate cellcycle and survival during metabolic stress Science 336(6078)225ndash228

Li Y de Magalh~aes JP 2013 Accelerated protein evolution analysisreveals genes and pathways associated with the evolution of mam-malian longevity Age 35(2)301ndash314

Liu EY Xu N OrsquoPrey J Lao LY Joshi S Long JS OrsquoPrey M Croft DRBeaumatin F Baudot AD 2015 Loss of autophagy causes a syntheticlethal deficiency in DNA repair Proc Natl Acad Sci U S A112(3)773ndash778

Lopez-Otın C Blasco MA Partridge L Serrano M Kroemer G 2013 Thehallmarks of aging Cell 153(6)1194ndash1217

Lorenzini A Tresini M Austad SN Cristofalo VJ 2005 Cellular replicativecapacity correlates primarily with species body mass not longevityMech Ageing Dev 126(10)1130ndash1133

Luke L Vicens A Tourmente M Roldan ERS 2014 Evolution of prot-amine genes and changes in sperm head phenotype in rodents BiolReprod 90(3)67

Ma S Gladyshev VN 2017 Molecular signatures of longevity insightsfrom cross-species comparative studies Semin Cell Dev Biol70190ndash203

MacArthur J Bowler E Cerezo M Gil L Hall P Hastings E Junkins HMcMahon A Milano A Morales J et al 2017 The new NHGRI-EBICatalog of published genome-wide association studies (GWASCatalog) Nucleic Acids Res 45(D1)D896ndashD901

Mari D Coppola R Provenzano R 2008 Hemostasis factors and agingExp Gerontol 43(2)66ndash73

Medawar P 1952 An unsolved problem of biology an inaugural lecturedelivered at University College London 6 December 1951 LondonHK Lewis and Co

Mizushima N Levine B 2010 Autophagy in mammalian developmentand differentiation Nat Cell Biol 12(9)823ndash830

Montgomery SH Capellini I Venditti C Barton RA Mundy NI 2011Adaptive evolution of four microcephaly genes and the evolu-tion of brain size in anthropoid primates Mol Biol Evol 28(1)625ndash638

Montgomery SH Mundy NI 2012a Evolution of ASPM is associatedwith both increases and decreases in brain size in primates Evolution66(3)927ndash932

Montgomery SH Mundy NI 2012b Positive selection on NIN a geneinvolved in neurogenesis and primate brain evolution Genes BrainBehav 11na na-na

Montgomery SH Mundy NI 2013 Microcephaly genes and the evolu-tion of sexual dimorphism in primate brain size J Evol Biol26(4)906ndash911

Myers PR Parr CS Jones T Hammond GS Dewey TA 2013 The animaldiversity web (online) Available from httpanimaldiversityorg

Nabholz B Glemin S Galtier N 2008 Strong variations of mitochondrialmutation rate across mammals ndash the longevity hypothesis Mol BiolEvol 25(1)120ndash130

OrsquoConnor TD Mundy NI 2009 Genotype-phenotype associations sub-stitution models to detect evolutionary associations between phe-notypic variables and genotypic evolutionary rate Bioinformatics25(12)i94ndash100

OrsquoConnor TD Mundy NI 2013 Evolutionary modeling of genotype-phenotype associations and application to primate coding andnon-coding mtDNA rate variation Evol Bioinform Online9EBOS11600ndash316

Oeppen J Vaupel JW 2002 Broken limits to life expectancy Science296(5570)1029ndash1031

Orlando L Ginolhac A Zhang G Froese D Albrechtsen A Stiller MSchubert M Cappellini E Petersen B Moltke I et al 2013


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Recalibrating Equus evolution using the genome sequence of anearly Middle Pleistocene horse Nature 499(7456)74ndash78

Pagel M 1999 Inferring the historical patterns of biological evolutionNature 401877ndash884

Parker J Tsagkogeorga G Cotton JA Liu Y Provero P Stupka E RossiterSJ 2013 Genome-wide signatures of convergent evolution in echo-locating mammals Nature 502(7470)228ndash231

Pilling LC Atkins JL Bowman K Jones SE Tyrrell J Beaumont RN RuthKS Tuke MA Yaghootkar H Wood AR et al 2016 Human longevityis influenced by many genetic variants evidence from 75000 UKBiobank participants Aging (Albany NY) 8(3)547ndash560

Pyo J-O Yoo S-M Ahn H-H Nah J Hong S-H Kam T-I Jung S Jung Y-K2013 Overexpression of Atg5 in mice activates autophagy andextends lifespan Nat Commun 4307ndash326

Revell LJ 2012 phytools an R package for phylogenetic comparativebiology (and other things) Methods Ecol Evol 3(2)217ndash223

Ricklefs RE 2010 Life-history connections to rates of aging in terrestrialvertebrates Proc Natl Acad Sci U S A 107(22)10314ndash10319

Rodrıguez JA Marigorta UM Hughes DA Spataro N Bosch E Navarro A2017 Antagonistic pleiotropy and mutation accumulation influencehuman senescence and disease Nat Ecol Evol 1(3)0055

Rufini A Tucci P Celardo I Melino G 2013 Senescence and aging thecritical roles of p53 Oncogene 32(43)5129ndash5143

Scally A Dutheil JY Hillier LDeana W Jordan GE Goodhead I Herrero JHobolth A Lappalainen T Mailund T Marques-Bonet T et al 2012Insights into hominid evolution from the gorilla genome sequenceNature 483(7388)169ndash175

Stern DL 2013 The genetic causes of convergent evolution Nat RevGenet 14(11)751ndash764

Storey JD Tibshirani R 2003 Statistical significance for genomewidestudies Proc Natl Acad Sci U S A 100(16)9440ndash9445

Suyama M Torrents D Bork P 2006 PAL2NAL robust conversion ofprotein sequence alignments into the corresponding codon align-ments Nucleic Acids Res 34(Web Server)W609

Tacutu R Craig T Budovsky A Wuttke D Lehmann G Taranukha DCosta J Fraifeld VE de Magalh~aes JP 2013 Human Ageing

Genomic Resources integrated databases and tools for the biol-ogy and genetics of ageing Nucleic Acids Res 41(Database issue)D1027ndashD1033

Trindade LS Aigaki T Peixoto AA Balduino A Manica da Cruz IBHeddle JG 2013 A novel classification system for evolutionary agingtheories Front Genet 425

Urfer SR Kaeberlein TL Mailheau S Bergman PJ Creevy KE PromislowDEL Kaeberlein M 2017 A randomized controlled trial to establisheffects of short-term rapamycin treatment in 24 middle-aged com-panion dogs GeroScience 39(2)117ndash127

Wang J Duncan D Shi Z Zhang B 2013 WEB-based GEne SeT AnaLysisToolkit (WebGestalt) update 2013 Nucleic Acids Res 41(Web Serverissue)W77ndashW83

Wang K Li M Hakonarson H 2010 ANNOVAR functional annotationof genetic variants from high-throughput sequencing data NucleicAcids Res 38(16)e164

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and the antagonistic pleiotropy (AP) theory of senescence(Williams 1957) Both hypotheses predict the existence ofgenetic variants with adverse effects expressed later in life(hence modulating lifespan) with the AP theory adding anadaptive aspect since it poses that damaging mutationscould be favored by natural selection if they are advantageousearly in life

From an evolutionary perspective aging is a polygenic andhighly complex process whose expression evolves quite rap-idly with relatively close species displaying very different phe-notypes Of particular interest are current patterns of humanaging which have changed markedly since our divergencewith other primates Indeed primates are an interesting orderfrom the aging perspective since they are evolutionary closeto each other in terms of phylogenetic distances and havehomogeneously slow life histories relative to other mammalswhile displaying profound differences in lifespan Among pri-mates New World monkeys comprise some of both theshortest and longest-lived monkey species Prosimians de-velop the most rapidly and are the shortest lived and incontrast great apes have the slowest development and livethe longest among the primates (Finch and Austad 2012)

Contrary to average life expectancy which may changedepending on living conditions MLS is a stable characteristicof a species and evolves rapidly (Oeppen and Vaupel 2002 deMagalh~aes et al 2007 Foote et al 2013) For instance humansand macaques diverged only30 Ma yet over this time theirMLS has diverged as much as 3-fold (Colman et al 2014)Despite the remarkable evolutionary lability of MLS the exis-tence and nature of the molecular mechanisms involved insuch variation remains unclear

Leveraging primate variation to identify molecular changesthat contribute to increases in longevity among primate spe-cies may help shed light on the selection pressures thatshaped not only our distant past (Enard 2014) but also extantvariation contributing to human lifespans To identify suchchanges it is necessary to compare phenotypic diversity inaging patterns among primates to changes in DNA or proteinsequences that occurred independently on different lineagesof the primate phylogeny (OrsquoConnor and Mundy 2009 2013Lartillot and Poujol 2011 Boddy et al 2017) In fact parallelroutes of molecular evolution may be relatively commonamong protein-coding genes from different species (Scallyet al 2012) and comparative genomic approaches have al-ready been applied to investigate numerous traits such asvocal learning (Wirthlin et al 2014) echolocation (Parkeret al 2013) flight in bats (Zhang et al 2013) adaptation toaquatic life (Yim et al 2014) and evolution in horses (Orlandoet al 2013) A complete comparative approach of MLS needsto consider not only longevity but also other phenotypessuch as body size (Austad 2005 de Magalh~aes et al 2007)and life-history traits that correlated with MLS and may thusconfound the analysis and interpretation (Fushan et al 2015Ma and Gladyshev 2017) Surprisingly this approach hasrarely been applied to lifespan (Aledo et al 2011 Li and deMagalh~aes 2013 Doherty and de Magalh~aes 2016) although afew studies have addressed the mechanisms of plasticity forlifespan within species or established the contributions of

known longevity-related pathways (Bonafe et al 2003Holzenberger et al 2003 Kapahi et al 2004 Lopez-Otınet al 2013) Perhaps due to their limited focus many of thefindings of these works are difficult to reconcile and none ofthem seem to adequately explain all aspects of the agingprocess (Gladyshev 2013)

With such comparative phylogenetic strategy we wereable to identify molecular evolutionary correlates betweengenetic variation and MLS and other primate life-historytraits We deployed two approaches (fig 1) one based onthe detection of parallel mutations and the other one basedon the study of genendashphenotype coevolution using phyloge-netic generalized least squares (PGLS) The latter has provento be a powerful tool to detect genendashphenotype associationsin combination with the root-to-tip dNdS method(Montgomery et al 2011 Montgomery and Mundy 2012a2012b Luke et al 2014 Boddy et al 2017) In summary ourstudy differs from and extends previous comparative studiesin that we 1) consider several life-history variables and 2)perform analyses across the whole primate order Bothapproaches allowed us to identify mutations genes and path-ways that have putatively been fundamental to varying pat-terns of aging across primates

Results

Relationship between Maximum Life Span and OtherLife-History TraitsThe life-history traits under study were largely obtainedfrom the AnAge online database (de Magalh~aes andCosta 2009) They included MLS body mass female ageat sexual maturity gestation length and weaning timeLongevity quotients (LQ) were calculated from the ratioof MLS to the predicted MLS based on the allometric equa-tion for nonflying mammals (de Magalh~aes et al 2007)These traits showed strong correlation among each otherin primates (see supplementary fig 1 SupplementaryMaterial online) To test whether MLS covaries with otherlife-history traits linear regression on the primate pheno-type data was performed Univariate linear regressionshowed that MLS covaries with body mass (adjR2frac14053Plt 2e-16) female age at maturity (adjR2frac14057 Plt 2e-16) weaning time (adjR2frac14049 Plt 2e-16) and gestationlength (adjR2frac14032 Pfrac14 81e-12) Multiple linear regressionfollowed by a type I analysis of variance (ANOVA) showedthat whereas female maturity presents the most significantnominal association with primate longevity (Pfrac14 0002)body mass was the best predictor accounting for 60of the variance of MLS (Pfrac14 003) Age at female maturityaccounted for almost 7 of the remaining variance theremainder (30) being residual error (fig 2A)

Pagelrsquos k model was used to test for phylogenetic signals inprimate traits Consistent with previous findings phylogenyexplained a high proportion of the variance in primate MLS(kfrac14 087) as well as in the other life-history traits (femalematurityfrac14 09 weaning timefrac14 071 gestation lengthfrac14 093body massfrac14 1) The only trait that showed a notably smallerk was LQ which had a value of kfrac14 069 (table 1)


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biological processes modulating longevity across primates

Documents