Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. mrvdfrcsigo uuecrlre elhbsdo h cp n ae frcvr sugnl needed. urgently is recovery of rates and scope the on gains. based genetic health the with reef and associated coral trade-offs future timeframes trait of and of forecasting success impacts Improved of and van incidences probabilities 2019; the the Oppen, interventions reduce determine genetic van designs, to of & breeding help experimentation Bay, from of Blackall, Quigley, gained optimisation knowledge 2019; Damjanovic, facilitate The Quigley, 2019; 2015). will & Gates, Oppen, Bourne, & van Putnam, Hung, Oliver, & Morgans, Oppen, Men´endez, Hoffmann, 2017; (Chakravarti, Peplow, manipulations Oppen, Chan, microbial & Academies Webster, 2017; and 2019). (National Oppen, species, Technical field between & Intervention include the hybridisation interventions Beltran, Program: evolution and and species, Assisted Adaptation early within importance. laboratory persistence high and the breeding the of the selective Restoration at in populations safeguard protect corals Reef tested also To of may 2019; being interventions tolerance bleaching. are These Medicine, heat adults coral and the in Sciences mass increase as of to as well recovery interventions as such and evolution 2019; stages resilience events al., assisted ecosystem life-history et reefs, acute for (Baums coral implications severe, processes of major of reproductive resilience with fundamental aftermath 2019), sea Loya, in the high & and changes by Shlesinger in temperatures to seawater 2019; driven leading warm al., mortality also Increasingly et coral 2018). are Hughes al., cover mass et coral to Hughes in 2017; due losses al., degradation et significant (Heron undergoing temperatures surface are globally reefs Coral reef Introduction of by modelling and affected feasibility are intervention genetic frequencies of allele assessments 31 for that the not at for demonstrates information but more here key futures. survival influenced presented breeding, for selective understanding traits of high mechanistic these generation were the one of heritability) crosses, heritability (narrow-sense of with number traits juveniles, limited fitness in 27.5 in bleaching of at variation and 43% total responses explained growth bleaching to genetics and contribution Underlying growth, responses). marker immune survival, Genetic and heat juvenile metabolism, in with formation, variation associated membrane PCoA (cell regions significantly stress 27.5 key alleles heat created at identified in to (SNPs) breeding reared diversity responses polymorphisms Intra-population nucleotide maintained offspring single juveniles. and with of and scans genome associated larvae cooler genome-wide coral a High-density hybrid from the and fitness. colonies and across purebred conspecific tolerance diversity cool with crossed and genetic corals reproductively warm greater how Reef of thus data Barrier significantly marker Great combinations and genomic the level produce and on genomic pedigree, to reef a phenotypic, warm reef combine at we a regulated Here from are sourced breeding. responses selective colonies through temperature from or how may naturally management unclear warming genetic is to Resilience-based adapt it may corals. but reef-building tolerance, in mortality heat of coral driver increase global principal the are waves heat Summer Abstract 2020 11, May 2 1 Quigley Kate coral of genetic breeding adaptive selective in through increase variation an reveals analysis SNP Genome-wide nvriyo ebun aut fScience of Faculty Melbourne of Science University Marine of Institute Australian 1 ieBay Line , 1 n aeen a Oppen van Madeleine and , ° 8 ,2 oi,icuiglc uaieyascae ihpoen novdin involved proteins with associated putatively loci including loci), 2,224 – (87 C 1 2 ° n 31 and C ° ewe h utlcsgenotypes. multilocus the between C ° eaiet 27.5 to relative C ° .Uigol a only Using C. Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. ils a pe,21) npriua,cagsi ybotcmuiycmoiincnatiue1.0- attribute can composition community symbiont in Coffroth, changes Baker, Quigley, particular, in can In Symbiodiniaceae) reviewed tolerance 2018). 2009; (family Takahashi, 1.5 symbionts heat Oppen, & dinoflagellate van Ralph, this of & Bhagooli, of abundance (Baird, Willis, Part tissues relative 2019). coral and inhabit Woesik, diversity that van the to & across attributed diversity limits Hodgson, et be genetic Donovan, increased thermal have (Ainsworth on Burkepile, corals their stress predicated (Sully, that heat to evidence capacity ˜0.5 temperatures is adaptive to by close There high tolerance response 2018). exist Bay, a heat in & Aglyamova, Corals their of phenotypes Treml, suggestive (Matz, 2017). of species 2013), range al., and al., wide populations et et butterfly understand a Kenkel Roitman Eltham’s to exhibit 2015; like 2017; adaptation but al., species and al., 2019) of Drury, selection et conservation of in the (Creech (reviewed effects respond to sheep the will applied of bighorn populations been how incorporation and has predict The trajectories to pressures. evolutionary adaptation selective and population of acclimatisation suite of a rates estimating to on rely will This n oetal ikteehrtblt siae tbt min n lvtdtmeaue oepanthe explain to temperatures Methods elevated and and traits. Materials and ambient quantitative changes both three frequency we at these allele Here estimates in underlying parents. variation heritability five genetic their these only to link from crosses potentially produced reproductive and crosses five of the (h number contribution in juvenilesgenomic limited measured a exposing traits of then those inspection link and upon reefs even cooler 2020)), Bay, from 31 sourced breeding to others like Selective posed with stress. symbionts heat tolerant reefs under warmer temperature evolve may to historically repro- corals bred from produced selectively corals from artificially collected of how 2008). samples elucidate to Alho, to sequencing & crosses Teplitsky, relatedness marker ductive Ovaskainen, genome-wide for Cano, high-density inputs (O’hara, variances apply and we selection as effects Here for genetic used potential additive data calculate the to marker heritable and used heritability measured the are finally, data, the provide phenotypic and of SNPs with combined proportion Specifically, when small the 2009). that a underlying models, al., only ultimately et explain markers may (Manolio identifies alleles variation approach single selection genetic although marker-assisted estimates, quantitative This heritability 2019). utilize al., that can et Bay, h programs (Holland (h and the & to heritability variation breeding Traylor-Knowles, linked broad-sense intrinsically trait Barshis, through and are SNPs narrow underlying Palumbi, practices and variants 2019; conservation values, common breeding al., genetic identifying principles, et to for Fuller respond applied valuable to 2015; particularly use be al., coral are mechanisms et et SNPs evolutionary Helyar (Dixon and 2014). 2011; ecological environment al., the effective, their et illuminating cost (Davey increasingly to relatively (SNPs) are and available and polymorphisms widely 2011) of single-nucleotide now al., of analysis genome is potential whole The sequencing and rates sequencing genome time. the whole including over understanding deep to and central and is populations Shallow populations adaptation. across artificially-bred and changes wild in frequency diversity populations genetic gene in describes their adaptation understand genetics enable to Evolutionary ultimately used frames. that be time phenotypes then evolutionary different can and of understand knowledge ecological emergence This particular to over regions. the at Therefore, genomic driving alleles specifically. polymorphic in in variation tolerance of influence the topology heat concerning broadly the not needed more and is may and loci The knowledge genes generally Multiple comprehensive target involved 2018). capacity, tolerance 2016). some genes adaptive Madin, although and al., stress corals 2017), & proteins et with Dyall, shock Baird, Jin & associated heat 2015; Baker, (Mizerek, including be Kenkel, Palumbi, examined, variability Bhagooli, & been bleaching (Louis, have (Bay immunity of sizes 2020) polygenic in Bay, effect 24% often varying & of to is Oppen, genes tolerance up van candidate heat explain Randall, of (Quigley, to architecture crosses found genomic cool-warm been and has warm-warm and to relative corals juvenile ° ficesdtlrnet dls(eklas&vnOpn 06 n 6 nrae oeac in tolerance increased 26x and 2006) Oppen, van & (Berkelmans adults to tolerance increased of C ° eg nrae uvvl rwhadbecigtlrne(uge,Rnal a pe,& Oppen, van Randall, (Quigley, tolerance bleaching and growth survival, increased (e.g. C 2 n dniytepttv astv ainssprtn h v aiist explain to families five the separating variants causative putative the identify and ) ° ntels eae hc ugsssbtnilcpct oaatt increasing to adapt to capacity substantial suggests which decade, last the in C 2 ie h rprinlt otepouto N uniyadeetsize effect and quantity SNP of product the to proportionality the given uudnu trenchii Durusdinium 2 infiatyipoe oa teswe ex- when fitness coral improved significantly 2 H , 2 Vsce,Hl,&Wa,2008). Wray, & Hill, (Visscher, ) Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. N erc eercluae nRfrps-lee aauigte‘AT akg’(rbr Unmack, PCoA (Gruber, Gower package’ with ‘DArTR genotypes the SNP larval using individual data from constructed post-filtered were for PCoAs R 2018). Georges, in & recalculated Berry, were metrics SNP statistics Multivariate the Analyses at Statistical alleles Equilibrium. Hardy-Weinberg of of repeatability out DART average loci proprietary for filtering both loci using filtering loci (‘filter.callrate’, quality included data high which only criteria, (‘filter.repavg’, of following locus dataset reduced the a and KDCompute produce software the to filtered with filtered was the and (SNPs) data against controlled polymorphisms sequence referenced nucleotide raw were single http://www.kddart.org/kdcompute.html). Technology, DArT restriction pipeline, SNPs Arrays call (Diversity The followed DArT algorithm contamination. to remove DArTsoft14 preparation the used and to library pipeline databases were of bacterial and generated part and Peng, viral fragments purification As (Jaccoud, against site DNA following filtered 2012). and enzymes 2012). al., Q-scores restriction on al., et based HpaII et (Kilian using and Kilian methods genotyped PstI 2001; and proprietary the HiSeq2500 Kilian, with Illumina & out the Feinstein, on carried (n sequenced were crosses were reactions population samples three ligation All representing 19). families CW: DArT-seq five 15, across proprietary WC: 68) 34, = WW: n = (total genotyped were larvae sequencing to Individual preparation, exposure experimental library of extraction, days DNA of 70 Sampling, after sequencing (percent quantified for bleaching were area), used dead) in previously or change (alive (percent protocol survival 27.5 growth SDS and Juvenile coloration), modified 2017). Bay, in a & change Willis, using (Quigley, extracted eggs were coral single samples tissue from DNA culture), juveniles per until spathulata in Acropora tanks time measurements further replicate trait one 3 and repeating = sampling and symbionts, Larval (n et and tank microscopy. corals Quigley 1x10 with juvenile between in contact confirmed adding each was for location, found by to allow infection each performed be to separately of flow was can strains the juveniles parameters symbiont establishment suspending environmental coral cultured symbiosis in collection, three and establishment the the symbiosis rearing, of Briefly, juvenile details 2020. Full and al., 2020). larval al., spawning, sire warm et permits, and dam Quigley cool in a with details one and (WC) with trenchii sire infected cool Durusdinium and were we dam juveniles warm Here Aposymbiotic a development). with (CW). (27.5 cross of stage one days larval WW3), the WW2, 70 recruits (WW1, both after produce at taken to sequenced 31 used were crosses and and familial measurements five settlement given larval those crosses juveniles on of familial focus time as distinct the to 30 at referred available from were larvae (hereafter northern in families far in outlined five three resulting from Only as colonies, 27.5 sperm designations). central 2017 and in November three eggs raised of separated in were the those spawning that spawning with coral of mixed night for the were (SeaSim) on colonies Briefly, Simulator 2020). Sea al., et National (Quigley the 18 to GBR; 13 central back (Backnumbers, GBR; brought GBR central northern the far in (Tijou, reef Reef species Barrier the Great of corals adult infection Gravid symbiont and settlement rearing, larval Spawning, ° n 31 and C ° ) hs rse nld he rdcdfo w aet ore rmtewr a otenreef northern far warm the from sourced parents two from produced three include crosses These C). ° ,adadtie seseto hspyilgcldt a efudi Qilye l,2020). al., et (Quigley in found be can data physiological this of assessment detailed a and C, avewr ape no10 tao fe ern t27.5 at rearing after ethanol 100% into sampled were larvae > > TM ihclue aeilotie rmteAM ybotClueFclt (further Facility Culture Symbiont AIMS the from obtained material cultured with 9) olpigdpiae eune ‘epmnmrh’,idvdaswt missing with individuals monomorphs’), (‘keep sequences duplicated collapsing 99%), 5) leigb io leeFeunis( Frequencies Allele Minor by filtering 25%), ° lrfitrd o-hog ewtr(e al o eireadprna colony parental and pedigree for 1 Table (see seawater flow-through ultrafiltered, C ehooya iest rasTcnlg Cner,Asrla.Dgsinand Digestion Australia). (Canberra, Technology Arrays Diversity at technology cooaspathulata Acropora cooadigitifera Acropora ° yboiimtridacnidorum Symbiodinium 04.”,143 10’44.0”S, 3 eoe(hnaoe l,21)adfrhrquality further and 2011) al., et (Shinzato genome ° eecletdfo n efi h a ot fthe of north far the in reef one from collected were 04.”,147 30’49.8”S, ° 65.”,pri 1/88.)adone and G16/38488.1) permit 56’54.6”E, < .2,cvrg ( coverage 0.02), ° 91.”,pri 1/53.)and G12/35236.1) permit 09’10.7”E, ° )adtejvnl tg (27.5 stage juvenile the and C) ° 25dy fe fertilization. after days ˜2.5 C , ldcpu goreaui Cladocopium < eddph,and depth), read 8 5 ml -1 foeof one of and , ° C Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. )uigteudryn hsooia aaad2 xedn h ie ffcsmdl sdi htstudy by: that 2020 in WW2, al., (WW1, inoculation used et for cross used models parental Quigley were and strains effects in Symbiodiniaceae CW) mixed Three performed WC, bleaching. the (WW, and that growth, origin extending survival, upon of on 2) CW) population builds WC, and of WW3, analysis influence data variance This the physiological phenotypic parameterized 2010). underlying that on al., the influence this et environmental using effect. by Hence, and (Wilson 1) heritability random 2004). genetic narrow-sense trait (Kruuk, a of calculates each effects contribution as that of random relative parameterized model the using mixed-effect is calculates individuals specialized juveniles analysis measured of individual between type relatedness between a parameterizing is relatedness 2010), model’ of (Hadfield, ‘animal ‘MCMCglmm’ coefficient package The the the using 2004) which (Kruuk, model’ in (h ‘animal estimates the pedigree heritability from Narrow-sense with calculated effect. variance combined 27.5 random a at were as trait input 2020) each pedigree for al., estimates et heritability 31 narrow-sense (Quigley calculate and growth to 1) and Table bleaching, (Supplementary information survival, on data Physiological heritability & diffe- (Fasano Narrow-sense of ‘Peacock.test’ package significance the statistical using multidimensional, assess distributions 1987). a two-dimensional Franceschini, to and continuous used families paired of the was between CW). from number rences test WC, frequencies statistical- and Two-Sample were genotype (WW, genotypes, Kolmogorov-Smirnov frequencies observed corals of genotype experimentally distribution-free parental HW number the for Expected to of sizes, samples populations. compared source population mated larval ly randomly total geographic single in parents, by from simulate population to of constructed pooled samples a generations number were larval in bioinformatically were frequencies profiles single as allele included from SNP of well Parameters profiles distribution proportions. as null SNP HW A families the follows 15). of 19, all evolving 34, sizes not = population is n three population, that each for in using 2011) larvae simulated (Chivers, of were (number frequencies script genotype R equilibrium custom (HW) Hardy-Weinberg a expected of distributions The distributions protein frequency only SNP for Modelling filtered were proteins Predicted blastx&PAGE annotations). (OIST on proteins BLAST instructions annotated searchable E-values to full a with blasted into for matches were re-formatted reference matches and Nucleotide see downloaded command. v.0.9, were “blastdbcmd” matches the using nucleotide database the All translated to identified, scripts. sequences were custom aligning cross and using family searching each by between sequences separation nucleotide was PCoA to the BIC to in contributing significantly drop SNPs largest the annotation which Polymorphism in Nucleotide 2010), Single al., et Jombart (BIC, (Gr Criteria admixture at was Information infer DAPC Bayesian 2008), to on Dunham, method & based alternative (Anderson analyses an STRUCTURE F as in relationships via used fraught close be differentiation of influence can measure the they Given that although 2019). analyses 2017). differentiation (Rajora, population Smouse, genetic positives suggests & false population differentiation Jost, with classic frequency Chao, allele to (Sherwin, high following similar which the ‘DArTR’ (Gr are including using x-values analyses explored, calculated of These were were (75%) thresholds metrics quartile within- Diversity loading third and 2015). Multiple the between- the outputs. of without value PCoA and Principal default Jom- from with of 2018; components Analysis constructed al., Discriminant variance 2010) using et Balloux, group inferred (Gruber & were ‘DArTR’ Devillard, individuals (Jombart, and related Components genetically ‘Adegenet’ packages of Clusters the 2008). using bart, distances Euclidean and ordination k 5. = ° .Rltdesbtenidvda ueie sbhp n aiygop)aecluae rmthe from calculated are groups) family and (sibships juveniles individual between Relatedness C. TYPE=BlastSearch&LINK < e4wr eand(https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM= retained were 1e-4 LOC=blasthome). 4 nade l,21) ec,“true Hence, 2010). al., et unwald ¨ nad avr vrat obr Collins, & Jombart Everhart, & Kamvar, unwald, ¨ cooadigitifera Acropora 2 eedrvdfo diiegenetic additive from derived were ) eoe(.OIST (v. genome k a calculated was ” st v1.1) in , ° C Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. itiuino oii h W rs a o infiatydffrn oprdt C( WC to ( compared size different same significantly the not of was populations cross ( WW3 WC the of ( in distribution ( the loci at CW to of loci compared and distribution distributions of respectively) Figure different 2.4e-4, abundance (Supplementary significantly and crosses lower exhibited interpopulational 5.5e-15 (e.g. WW2 the similarly as and diversity a frequencies WW1 demonstrated reduced intermediate purebred WW3 1). at average whereas individual loci WW2, on of and When abundance WW1 the greater crosses purebreds. of to attributed population purebred majority was frequencies) within population the intermediate loci than in analysed, of Kolmogorov- diversity were loci distributions; abundance genetic families of null greater greater distribution to a significantly average (compared with have The families crosses, 1. interpopulational test, the interpopulation or Two-Sample Smirnov in 0 to frequencies either compared intermediate at different at fixed significantly were was loci crosses of extent majority lesser The a to and profiles WW1, frequency WC, Allele WW3, CW. variances, between allele particularly especially within-group and and calcu- occurred, WW2, between-group probabilities families, with has in membership the admixture distributions Cluster across flat variance. that showed least varied demonstrating also the also 95% analysis shows genotypes The DAPC WW1 functions. from multilocus and discriminant lated greatest of two the first dispersion shows the the WW2 along where con- that CW further and demonstrate (DAPC) WW1 ellipses Components between confidence Principle clustering families of of divergent. pattern Analysis five Discriminant this more using firmed The were (WW1 structure space shared families each). population two (PCoA) between that of Analysis for other Families variation Analysis Components the 1A). 20 Principle the whereas (Figure in – WW2), of 4.1%) together with clustered 7 13.4; 43% CW roughly 25.8; = explained and 2A) (PC1-PC3: (Tijou variation (n families sire genetic same five families the the which five temperature from ambient in the genotypes at space, from multilocus collected multidimensional samples larvae larval in genotyped the separated from individually remained 68 SNPs quality across high 9,031 filtering, After differentiation Interpopulation maximum and 0.00598) = to (y equally the minimum Results estimate for the heritability values to each y-density a re-scaled visualize 57.42421) models, was to = across posterior 2006) (y levels each the (Lemon, Specifically, thinning package by interpretation. and ‘plottrix’ relatedness ease the iterations to x in in – attributed function differences x variance “rescale” et Given = model met. variance. (Wilson (x’ were the residual factor distribution autocorrelation dividing scaling and gamma and by additive distributions inverse calculated of posterior an was sum of heritability following normality mixing, posterior used, chain The was of Assumptions specification 2010). distribution. prior al., Gaussian flat a with non-informative models A survival the in parameterized were factors × (27.5 7500 of levels tridacnidorum thinning multiple at 150 and distribution), , iterations (categorical total regression of logistic burn-in binary 0.1% using factors, random as individual Information. Supplementary h the of in Models strains additional the and results only main for estimates spathulata heritability Acropora clarity, For juveniles. of = p ldcpu goreaui Cladocopium 10 6 .7.Alfmle iee infiatyfo xetd oeldH rqece hnmdle again modelled when frequencies HW modelled expected, from significantly differed families All 0.77). trtos hniglvlo ,0 n uni f1%o h oa trtos ie n random and Fixed iterations. total the of 10% of burn-in a and 1,500 of level thinning a iterations, 2 fjvnl uvvla ohtmeaue eernwt iea xdfco,pdge and pedigree factor, fixed a as time with run were temperatures both at survival juvenile of .Mdl fh of Models ). nteGR( GBR the on and , min = p uudnu trenchii Durusdinium /x 2 .e2 n .e2,Fgr ) hssget htteeitrouainhybrids interpopulation these that suggests This 2). Figure 1.3e-21, and 2.1e-26 max = p fjvnl lahn n rwha ohtmeaue eernuig1.5 using run were temperatures both at growth and bleaching juvenile of x – sensu WadW:10e4;C:22-6.Osre eeoyoiy(H heterozygosity Observed 2.2e-46). CW: 1.03e-45; WC: and WW min .tridacnidorum S. a ple otepseirdsrbtoso ahtatuigthe using trait each of distributions posterior the to applied was ) a pe,Plta iut ilr 01,i rsne nthe in presented is 2001), Miller, & Piquet, Palstra, Oppen, van = p .e1 n .e4 epciey Fgr ) ncnrs,the contrast, In 2). (Figure respectively) 6.7e-4, and 1.2e-11 31 , 5 ° C: Cladocopium ramn t31 at treatment .goreaui C. h uiieypicplsmin of symbiont principal punitively the , and ° C. .trenchii D. ° C: yboiimtridacnidorum Symbiodinium r3,0 (31 37,500 or ) = p × .e2 rCW or 8.7e-2) 10 6 iterations, ° C: = p o S. ), Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. eetv reigi n eei nevninsrtg htmyqikyices dpiegntcvrainin variation genetic adaptive increase quickly may that strategy on intervention genetic frequencies one intermediate is breeding with Selective act alleles can of selection occurrence natural increased which produces breeding Selective 31 and 27.5 at Discussion infected families five the from 1). Table juveniles Supplementary in varied differences 31 traits to and three little 27.5 the contributed at with families low rates across associated growth with variation in juveniles genotypic associated Heritable generally although estimates. were temperatures, heritability responses moderate both Bleaching at 1). Table with estimates al., Supplementary (h infected heritability corals 4, heritability et of narrow-sense (Figure Quigley survival Bayesian temperature in only calculate by that presented to demonstrate previously growth used were and were bleaching bleaching, data and raw 31 growth, from These survival, at sourced 2020. juvenile less coral for bleached symbiont, parental data Symbiodiniaceae and one Physiological the more, least with at grew infected with 27.5 better, if juveniles at significantly especially Specifically, survivorship survived crosses, symbiont 2020). and and GBR al., CW) bleaching northern et WC, growth, the WW3, Quigley to WW2, in (WW1, responses summary identity juvenile (full cross influenced family significantly CW), WC, type (WW, origin of Population re- immunity/stress, with and associated heritability functioning associated Narrow-sense were negatively cell PCoA2 were with transcription along and separation. (associated WC immunity their with proteins and with associated MAP CW, con- proteins multiple and Proteins and whereas WW1 radiation, separation. spectively) Alternatively, their WW2/WW3, UV 1A). with of (Figure to the associated 1 to separation responses negatively axis related the more PCoA positively were to along proteins broadly asso- tributing WC functioning were broadly and cell functioning are WW3 in cell which and differences and 3A), WW2/WW1/CW families stress, (Figure of and proteins Homeodomain-interacting separation immunity src proteins. transcription, and assigned with proteins hence ciated finger-containing and zinc SNPs significant two NFX1-type in for involved proteins, and cut-offs those 4,6-dehydratase-like defined including loadings dTDP-glucose proteins, PCoA related 2 detected. kinase were as of transcription well host and involved A functioning as Proteins cell proteins. families, transporter-like proteins. across bicarbonate NLRC3-like varied finger-containing sodium processes, production zinc other proteins, NFX1-type collagen and regulator-like spondin, with affinity lysosomal-trafficking RNF213-like, MAP/microtubule included and ligase NACHT, proteins metabolism, ubiquitin-protein protein, proteins and related E3 identified functioning Stress we cell protein, stress, temperatures, CEPU-1-like inset). and ambient immunity at 3 mainly crosses (Figure processes, of biological calcification separation of the range to a contributed be in involved that not SNPs could 87 the (30%) In SNPs 87 the of 2016)). Twenty-six Gates, quartile) quartile). (75% (99% SNPs inset, value 2,224 3 threshold from associ- the ranging stricter SNPs within cut-offs of annotations the number threshold assigned at The on SNPs depending temperature. 87 varied ambient families to under five reared these families with five ated the at with Entropy correlated Alpha were WW3. SNPs in 1). (Table lowest and high WW2 also WC, was analysis in which QTL highest WW2, the of was exception 1 the = with q purebreds, the to compared ( Diversity alpha and sensu Brhse l,21;Pn ta. 00 hnaoe l,21;Sgn unm nesn & Anderson, Putnam, Sogin, 2011; al., et Shinzato 2010; al., et Peng 2013; al., et (Barshis 0 D α and ° 2 Tbe2.Wt h te he yboiica aa h taxa, Symbiodiniaceae three other the With 2). (Table C D .digitifera A. α tq=0ad2 a ihs nteitrouaincoss(C CW) (WC, crosses interpopulation the in highest was 2) and 0 = q at eoe omnisei oa n ybot‘mc (Figure ‘omics symbiont and coral in issue common a genome, 6 .trenchii D. .goreaui C. . ° SplmnayFgr 1, Figure (Supplementary C .goreaui C. 2 siae o survival, for estimates ) ° oprdt other to compared C a togyaffected strongly was 2 siae across estimates xiie more exhibited ° n 31 and C ° C Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. eeiprati ieetaigtefiefmle rdcdi u td.Clae sipratfrthe for important is Collagen study. our in transport produced bicarbonate sodium families and as five Sogin production patterns, the 2013; collagen expression al., differentiating with protein et associated in and (Barshis proteins gene responses in important in immune their maintained were and Differences alter be metabolism, 2016). corals can lipids, al., stress, structural populations et heat their focal in to changes with response in associated In important reflected genes) the that process. tolerance suggests be breeding stress This may the at operating generation. next cellular and (i.e., the and generations diversity introgression within growth maintained functional F2 extensive responses, are immune but of in breeding with production during associated result re-arranged variants the may that although demonstrate GBR also warming, We even the this. to of confirm across interbreeding adaptation to reefs the needed for Therefore, different be potential would from generation. the F1 corals influence of accelerate resulting the of assumptions the suggests therefore this number given of However, architecture unsurprising small met. genetic perhaps not a of were the is sizes loss on population This breeding a infinite and of distributions. observe flow, gene HWE not frequencies no allele modelled did mating, resulting random to we the changed compared Importantly, significantly offspring breeding selective of offspring. interpopulation in that found diversity populations. we divergent Finally, reduced two of these WC crossing risk observed by in a higher diversity average highest been genetic on was have had and corals could evolvability, Tijou (H there shows of corals colonies Backnumbers measure variants. adult to natural of compared rare 2017), analysis heterozygosity a of preliminary al., as occurrence Finally, et informative increased WW2. (Sherwin an is and mutants had criteria, novel WW2 diversity Information introduce and Shannon genetic initially CW, parents, may WC, contributing that populations suggesting across and breeding The crosses given of CW). important ( number (WC, Diversity small crosses alpha 1975). a interpopulation (Hogenboom, and in incompatibility heterozygosity genome even like Observed that processes improves. populations to divergent support of due demonstrated breeding diversity results been the yet genetic van whether These not in unknown has & decrease was but it a 2011) Hoffmann example, al., cause For (Chan, et would corals. Weeks hybridization of 2019; rescue breeding al., inter-specific genetic selective et the and and Hazzouri in 2019; vigour intra- al., hybrid et of diversity, Flowers 2019; features quantitative genetic CW Oppen, single inconsistent in and regulatory, Increases but WC dominant, 2019). well-known parental the to Jarosz, the are linked in to & material been relative abundances (Jakobson of having performance/fitness genetic nucleotides greater abundance increased performance trait Hence, at to increased increased 2015). lead exists this may an Collins, with likely Hybridisation generation, & given crosses. operate WW (Jombart can important the selection where processes to are 1, relative for adaptive GBR. or but material selective the 0 common raw which either of overall at on the less regions an fixation are different suggesting are reach alleles crosses, nearly from frequencies loci intermediate WW corals intermediate most in HWE of that at loci under breeding follow of typically alleles expected selective distribution frequencies than from average allele abundances resulting on of diversity Distributions the greater to genetic at relative in were context. crosses increase marine frequencies CW wild intermediate al., and a at WC et in therefore in techniques (Dixon alleles may these larvae here that of learnt of found success Lessons tolerance We methods. the heat these underpinning using in mechanisms possible the increases are into significant 2020) over insights that al., breeding provide et shown Selective (Quigley has 2016). juveniles wild and corals Knibb, to 2015) & in compared Dove, generation diversity (O’Connor, genetic one combinations eroding only elevated breeding significantly In under pooling without growth 2016). after 2013) higher Galtier, populations Owens, 30% & & in Jerry, resulted (Ellegren (Stevenson, has R-strategist) crayfish breeding selective (e.g. of diversity generations genetic pCO few mariculture a of and oysters potentially only levels numerous, aquaculture like systems, of of species those high production range the important and including a Commercially corals, gametes, across traits. with low-quality attributes important used life-history commercially been similar share of has mussels number approach and Oppen, a van This improve & 2015). Hoffmann, to al., (Chan, species temperatures et surface Oppen sea 2 odtoscmae owl ouain Pre ta. 02 n 0 ihrgot nredclaw in growth higher 50% and 2012) al., et (Parker populations wild to compared conditions 0 D α erci estv otepeec frr lee,wihis which alleles, rare of presence the to sensitive is metric o .6 s .27 nulse aa,sgetn that suggesting data), unpublished 0.0217, vs. 0.065 = 7 0 D α and 2 D α tq=0ad2 a ihs nthe in highest was 2) and 0 = q at 1 H α , lokona the as known also Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. auh 08.W a hsi h xeto ditr n t soitdvrac costefiefmle,in families, five the across variance associated its & and Dorp, admixture Van of (Lawson, extent differently the individuals in and this populations saw We species, discontinuity 2018). of population Falush, members and affect admixture events of Admixture key level be the will methods. influences individuals intervention breeding between in for Selective differences processes tolerance important phenotypic thermal likely increasing to with growth, and SNPs selected and genotypes understanding the in responses to multilocus of differences stress identified breeding and the we Assigning that immunity revealing generally. approach, in the families, survival this bred to seen Using selectively changes these models. patterns targets of heritability populations Analysis separation genomic the classification. the in the to and contributing quantified detection links alleles processes difficult DAPC of biological situation SNPs underlying using a of the changes structure up key majority of setting population the majority 2005), mechanisms the given Martin, of of whereas challenging 2017), variety & Boyle, is (Cavallo a & differences coding (Nishizaki through are non-coding SNP effects are of to phenotypic studies function size association cause by Assigning effect to detected 2005). differences predicted and simplistically, Martin, are location and & regions effect, The (Cavallo phenotypic non-coding eventual corals? vs. its between determining coding differences to in important phenotypic are to difference lead SNP the variation genomic does families with environment.How bred combined aquarium selectively aquariums) the with (e.g. in associated selection hybrids variation artificial Functional versus 2008). of purebreds al., cases on et may strong Inter- selection (Hill which under mutations of period. purebreds, rare arise Supplementary effects rearing population may varying families, aquarium within distributions the the the to U-shaped of across during relative result used diversity heterozygotes the genetic colonies against (“U- be parental greater selection distributions displayed unique suggest frequency hybrids (5 also allele population derived may Dziedzic, of were 2015; but extremes al., cross 1), the Table et each at (Dixon in fixed described larvae alleles been the of rarely majority have The mechanisms of shaped” for 2017). goal underlying quantified Meyer, long-standing the been & a has but heritability, heritability Elder, traits, of narrow-sense of and mechanisms It Broad range and architecture. 2019). a origins genetic Jarosz, (27.5 molecular & underlying (Jakobson underlying conditions influences genetics ambient the breeding quantitative on under selective light reared how sheds to families also as five responses. knowledge the immune foundational protective from provides in larva role aposymbiotic important individual an Genotyping provide resistant proteins alpha in subunit these downregulated complex that 2012). similarly polypeptide-associated was Traylor-Knowles, suggesting nascent 2012) corals, & Rodriguez-Lanetty, of (Palmer & Expression corals detected, Hoegh-Guldberg, resistant spondin 2010). (Bellantuono, in al., and were protein downregulated et 2013), RNF213- and (Polato proteins here disease al., ligase related found to et was exposed ubiquitin-protein immunity protein (Hamada finger-containing E3 NACHT Additional zinc 1996), 2019), NFX1-type Interestingly, al., Brummendorf, Toll-like 2017). et through & al., responses (Iguchi (Spaltmann immune like et across innate protein of (Westphal significantly mounting CEPU-1-like varied mice the including regulator- also to in (lysosomal-trafficking linked 2017), detected activity been also al., also were receptor have et stress these to (Zhou and and response immunity proteins), modification in in like receptor involved suppression Toll-like proteins immune Other in acroporid families. acting in by implicated previously stress few been relatively heat combinations. has across genetic processes which distinct breeding foundational NLRC3-like, create even these Protein substantially that in to suggests crosses potential therefore between the has Differences biomineralization individuals Watanabe, and utilization. Yuyama, organization 2016; glucose cellular for Oppen, pentose like van critical non-oxidative & and 2011), the differences Willis, Takei, calcification the in Weynberg, coral & involvement through Wood-Charlson, varied for their potentially (Buerger, pivotal and pathway also detected are functioning phosphate proteins cellular transporters 4,6-dehydratase-like Basic bicarbonate dTDP-glucose 2015). whereas in al., functional 2008) et of al., organization (Zoccola spatial growth et the hence (Helman and multicellularity cells for of required units matrix, extracellular the of production sensu il odr,&Vsce,20)aelkl rvnb h ml ubro aet rmwhich from parents of number small the by driven likely are 2008) Visscher, & Goddard, Hill, 8 ° C) Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. neetnl,adtv eei ainewsol motn niflecn uvvla 31 at survival influencing in important only was with variance genetic additive Interestingly, ainsadpeoye soitdwt testlrnewe xoe ovrigtmeaue.These influence temperatures. significant having varying immigrants genetic recent to in of exposed influence differences the when significant demonstrating the tolerance studies on in with stress effects apparent line measurable with was in has are This associated breeding results offspring. selective phenotypes that resulting produced and suggest the study findings pilot variants of our this diversity in colonies, genotypes presented genomic adult specific are five crosses the link of of can number mixing small crosses the a familial only from among Although traits. differences fitness frequency a important allele under to potential methods of these identification use The to selection. important adaptive these be of with will models all associated it develop Conclusion additively and SNPs fully 2019) to incorporate the al., settings should all experimental et heritability not core of (Holland narrow-sense variety of that associated indicative although likely SNPs potentially captured common is and the been it 2019), heritability have Finally, al., High phenotypes pressures. et 2014). al., three selective (Kronenberg et common continual and (Yang be 2020), genes under al., of also traits wide expression et may disease-related Quigley with temperatures of genotypes, ambient (often range between with at variability a heritability even phenotypic across variability high Bimodal recorded within-population the been 2014). underlying have in high al., (mirrored by sizes et driven result sample of be (Yang generally large influence also distribution size can The effect underlying estimates eQTLs intervals) small 2017). the credibility effect of al., influence large loci et multiple single also whereas (Rudra by may heritability), driven distributions high heritability be unimodal with posterior as- can traits in the architecture estimates for of genomic heritability generally underlying shapes seen Bimodal the The (as breeding. concerning 2018). selective hypotheses Oppen, with van generating sociated & for Willis, informative Coffroth, are Baker, distributions Quigley, in 6.1 ( Table temperatures both at for temperatures to attributed growth and bleaching, on survival, in variation of level with high a linked (h intrinsically found heritability We are narrow-sense 2019). SNPs genetic 2008). al., al., et a et (Holland has (Visscher h size variation traits given trait these heritability phenotypic in narrow-sense change which adaptive to to for extent potential the the to and basis as information provide estimates Heritability Oppen, van individuals, & F1 Riginos, (Lukoschek, of Heritability flow architecture gene of genomic that level suggestive underlying underlying WW1, some the in 2016). undergoing between surprising, in especially likely shared also clusters, populations differences was was in between discrete even individuals ancestry populations produces of between of spread breeding discontinuity proportion reduced selective The the the simultaneously. by which clusters demonstrated in as three structure to clusters clustering two population hybrid single multiple to retained assigned bred not instead selectively were of families but number purebred between the covariance the interestingly, demonstrated recapitulated allelic although also of both not analysis produced, magnitude DAPC DAPC families is the labels, given Backnumbers2 and population space colony PCoA of multidimensional Furthermore, adult Irrespective in individuals. out that colonies. from separate suggest Tijou were families would five or origins the This Backnumbers whose that from 2018). other or sourced of al., to corals colony et related Tijou likelihood the (Lawson highly and the of founders Backnumbers statistically divergent ancestry other or shared the confirmed between few the AIC, limited that with be suggest conjunction may may Backnumbers2 in this be and Therefore, can differentiation. PCoA) this population Although and CW). (DAPC (especially techniques others two to the relative on admixture dependent little somewhat very exhibited families some which .tridacnidorum S. .goreaui C. .goreaui C. costetotmeaue etdhr seSplmnayIfrainfrfrhrdetails further for Information Supplementary (see here tested temperatures two the across u o t27.5 at not but .goreaui C. and .tridacnidorum S. .trenchii D. 2 hnpoe ttelvlo ouaincos hc aidi ueie infected juveniles in varied which cross, population of level the at pooled when ) k ossetwt h eeal vrl orrpromneo hs symbionts these of performance poorer overall generally the with consistent , tutr ftemdlue,bt atrswr xlrdidpnetyusing independently explored were patterns both used, model the of structure ° .Hne ti ieyta hr ssgicn eeto nsria thigh at survival on selection significant is there that likely is it Hence, C. 2 ). spootoa otepouto h ubro Nsadtereffect their and SNPs of number the of product the to proportional is ra ihrtmeaue ncrljvnls( juveniles coral in temperatures higher at or ) 9 cis and trans orglto ftetraits the of co-regulation ° .goreaui C. hninfected when C (see ) Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. pe,M .H 21) h oe fae aetg n niomn nbceiladaglendosymbiont algal van and & bacterial A., on environment A. management and Hoffmann, parentage conservation P., age, a Menendez, of as M., roles corals. Hybridization L. The Acropora (2019) Peplow, in (2019). H. communities Y., H. J. J. W. M. M. 0:e12652Chan, Oppen, Oppen Letters photosymbionts van Conservation in & adaptation A.A., tool. thermal Hoffmann Rapid (2017). W.Y., H. Chan J. M. Oppen, corals. & reef-building H., V. of Beltran, J., data. L. structure Chakravarti, and sequence protein to SNPs Disea- Mapping (2005). Band R. , Black C. A. coral Martin, CRISPR- the & (2016). A., with Cavallo, H. associated J. Cyanobacteria M. Oppen, in van prophages & potential L., se. B. and Willis, system D., defense K. corals: Weynberg, Cas change. of M., climate E. tolerance Wood-Charlson, thermal of P., the era Buerger, in an zooxanthellae in of reefs role coral The for (2006). Sciences hope’ H. of J. ‘nugget M. a Oppen, van in & stress R., thermal Berkelmans, to Resistance composition. (2012). symbiont M. in 279 Rodriguez-Lanetty, reef- changes & in without changes O., transcriptome corals Hoegh-Guldberg, by J., mediated A. ability A. Bellantuono, acclimation A. Rapid Shantz, (2015). western . R. the . . S. corals. in Palumbi, A., building populations S. & Kitchen, A., coral D., R. restored Bay, C. of Kenkel, potential G., A. adaptive (2013). Grottoli, the W., R. Atlantic. maximizing S. S. for Davies, Palumbi, C., Considerations & A. (2019). Baker, N., Traylor-Knowles, B., I. O., Baums, F. Seneca, America change. a, of climate T. to States Oliver, resilience United coral T., for host. J. the basis the of Ladner, Genomic role with J., the made bleaching: D. Coral inferences Barshis, (2009). on S. Takahashi, groups & Evolution J., & family P. Ecology Ralph, of in R., influence Bhagooli, H., The A. (2008). Baird, (2015). K. C. K. Smith, Dunham, Structure. . & . program . C., M., endosymbionts. E. Zakrzewski, ubiquitous Anderson, J.-B., as Raina, taxa bacterial G., rare Torda, identifies T., 9 microbiome Bridge, core L., coral Krause, The D., T. Fellowship Ainsworth, Laureate Council Research Australian the References and and photographs, science Hanaka support juvenile acknowledge Marine spawning, M.J.H.v.O. Marzonie, to like of and to coral would Magena We FL180100036 Institute with G16/38488.1 extractions. Threlfall, help Australian DNA permits larval their Siobhan the the in under help for from Skilton, collecting her Randall collected for Dylan Terrell in Carly were Alyx thank and help and Corals measurements, Speaks, to their reef. Justin like for and central also team Mera, the would GBRLegacy from We the colonies G12/35236.1. and coral Cantin collecting Neal for thank to spathulata like Acropora would authors The Acknowledgements shifts. frequency allele on 21 1) 2261–2274. (10), rnir nMicrobiology in Frontiers 13) 1100–1107. (1731), 8,1443–1450. (8), , clgclApplications Ecological 273 19) 3521.di 10.1098/rspb.2006.3567 doi: 2305–2312. (1599), eoeBooyadEvolution and Biology Genome oeua clg Resources Ecology Molecular ooisfo h a ot,adtecrlcleto em rmSai tAIMS at SeaSim from teams collection coral the and north, far the from colonies lblCag Biology Change Global , 24 , 110 1,1–0 o:10.1016/j.tree.2008.09.005 doi: 16–20. (1), , 7 4,18–32 o:10.1073/pnas.1210224110 doi: 1387–1392. (4), 2077. , , oeua Ecology Molecular 29 8,e17.di 10.1002/eap.1978 doi: e01978. (8), . , 7 , rceig fteRylSceyBBooia Sciences B-Biological Society Royal the of Proceedings 8 6,1602–1612. (6), , 10 rceig fteNtoa cdm fSine fthe of Sciences of Academy National the of Proceedings 6,1219–1229. (6), 28 1) 8034.di 10.1111/mec.15187 doi: 3830–3843. (16), rceig fteRylSceyB Biological B: Society Royal the of Proceedings h SEJournal ISME The Bioinformatics Trends , , Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. .G 20) xrclua arxpouto n acu abnt rcptto ycrlclsin cells coral by precipitation Falkowski, & carbonate Y., calcium M. and Gorbunov, V., production Starovoytov, matrix M., Extracellular LaVigne, M., vitro. R. (2008). Sherrell, G. F., P. Natale, Y., Fresquez, traits. Helman, fruit . palm . date . M., of Lebrun, mapping A., association Lemansour, 1–14. Genome-wide D., complex Copetti, (2019). The M., A. J. Flowers, Z. (2013). M., Gros-Balthazard, N. M., Satoh, K. Hazzouri, & J., D. Evolution Miller, coral and the T., Biology Kawashima, of C., repertoire receptor Shinzato, NOD-like E., Shoguchi, M., MCMCglmm the Hamada, models: mixed linear generalized multi-response for package. methods R (n.d.). MCMC E. (2010). D. S. J. Hadfield, Everhart, & N., of analysis Z. facilitate Kamvar, (DAPC) to J., package r N. An Grunwald, dartr: sequencing. (2018). genome A. representation Georges, reduced & 691–699. from F., (2019). generated O. L. Berry, P. data J., Andolfatto, SNP P. Unmack, . . B., . Gruber, L., Sarre, J., Shepherd, N., Cantin, coral 867754. L., the Morris, of L., genetics J. Population V. Aberlenc, Mocellin, L., . Z. . . Fuller, palms. A., date Perrakis, African North K., of Koutroumpa, Sciences origin Z., of the Mo, Academy and hybridization M., Cross-species Gros-Balthazard, M., (2019). F. K. Hazzouri, M., J. its Flowers, Society test. Kolmogorov–Smirnov Astronomical and the Royal of version the responses multidimensional of A diversity. Notices bleaching (1987). genetic A. Franceschini, in of & G., Determinants Fasano, variation (2016). Heritable N. Galtier, 422–433. & ( (2017). H., corals E. Ellegren, reef-building Meyer, in & basis http://biorxiv.org/content/early/2017/10/07/185595.abstract H., genomic Elder, functional K., Dziedzic, desert R. for Monello, models & resistance B., Holton, landscape S., using R. genotypes Crowhurst, selection-driven D., of J. Wehausen, sheep. spread L., bighorn the E. Simulating Landguth, (2017). W., C. J. Epps, G., T. Creech, https://gist.github.com/cjbayesian/468725f4bd7d6f3f027d#file-hw (2011). C. Chivers, io,G . ais .W,Alaoa .V ee,E,By .K,&Mt,M .(05.Ge- (2015). host V. the of M. importance Matz, evolutionary and & ecological The K., stress. corals: L. thermal reef-building to Bay, in response Resilience E., (2019). (2011). Meyer, C. L. Drury, latitudes. V, across M. G. tolerance Blaxter, Aglyamova, heat & W., coral http://science.sciencemag.org/content/348/6242/1460.abstract M., S. of J. determinants Davies, Catchen, nomic B., Q., G. J. Dixon, sequencing. Boone, next-generation D., using microbial P. genotyping of Etter, and contribution Genetics discovery A., The marker P. (2017). genetic Hohenlohe, H. Genome-wide J. W., M. J. Oppen, Davey, degradation. & reef S., coral N. mitigating Webster, to L., biotechnology L. Blackall, K., Damjanovic, rceig fteNtoa cdm fSciences of Academy National the of Proceedings . , 12 ora fSaitclSoftware Statistical of Journal 7,499. (7), LSONE PLOS , , 116 30 oeua Ecology Molecular 5,1651–1658. (5), 1,167–176. (1), , 12 cooamillepora Acropora 5,12.di 10.1371/journal.pone.0176960 doi: 1–26. (5), cooadigitifera Acropora , , 225 33 . 2,1–22. (2), 1,155–170. (1), irba Biotechnology Microbial oad eoi rdco fbleaching. of predictor genomic a Towards : 11 riel faveolata Orbicella , 105 iciiataayi fpicplcomponents principal of analysis Discriminant nldsnvldmi combinations. domain novel includes 1,54–58. (1), Science oeua clg Resources Ecology Molecular , aueRvesGenetics Reviews Nature 348 ). aueCommunications Nature , 4016.Rtivdfrom Retrieved 1460–1462. , 10 BioRxiv rceig fteNational the of Proceedings 5,1236–1243. (5), sim-r eree from Retrieved . aueReviews Nature Molecular BioRxiv , , Monthly , 17 18 10 (1), (3), (7), , Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. iin . ez,P,Htnr . aln,J,Xa . li,H,...Hpe,C 21) iest arrays Diversity (2012). C. Hopper, In . . platforms. . H., open Blois, on L., technology (2013). Xia, profiling genomics J., genome V. population Carling, generic M. E., a Matz, Huttner, technology: & P., coral Wenzl, E., hill mustard A., Bartels, the Kilian, of W., populations S. new between divergence Davies, a thermotolerance D., in components: astreoides) role Caillaud, host principal G., a of for Goodbody-Gringley, Evidence analysis D., Discriminant populations. C. structured (2010). Kenkel, genetically F. of analysis Balloux, the & for S., method Devillard, T., Jombart, (2015). C. markers. Collins, genetic & of T., analysis multivariate Jombart, the for package (2016). R H. J. a M. , adegenet: Oppen, van (2008). T. . Jombart, . . coral. S., reef-building A. Paley, a J., in http://advances.sciencemag.org/content/2/5/e1500842.abstract E. capacity Howells, Genotype- from antioxidant J.-B., Natural Raina, for in A., markers Heritability Lutz, Genetic for P., Complex Lundgren, technology of K., state Origins Y. Jin, Molecular solid a (2019). F. arrays: D. Diversity Relationships. Jarosz, to-Phenotype & (2001). M., A. C. Jakobson, Kilian, & genotyping. D., independent Feinstein, information K., sequence Peng, D., Jaccoud, multiple across maintained be oyster, diversity genetic rock 210–216. ( Can Sydney , (2019). (2016). coral of W. N. lines blue Knibb, Yasuda, selection & in M., mass . Dove, . species . W., O’Connor, Y., related V.-V., Hongo, In, closely J., R. across Toonen, divergence (2019). S., M. S. confirms R. I. coerulea Woods, genomics Knapp, H., . population . Z. . RADseq Forsman, A., Y., Dietzel, Yoshioka, J., A., T. corals. Chase, Iguchi, of K. R., dynamics S. S. Connolly, stock–recruitment Wilson, H., impairs A. . warming Baird, . . Global T., J. M., Kerry, Anthropocene. J. P., the T. Lough, in Hughes, T., (2019). corals J. of M. Kerry, 83. bleaching F., A. mass – S. of Dale, LP Heron, patterns 80 R., temporal S. . and Connolly, . Spatial . D., (2018). K. B., Anderson, O. P., Smeland, T. gaussian Hughes, univariate A., a A. with non- estimated Shadrin, phenotypes the C.-C., of model. discoverability Fan, for mixture and Polygenicity R., mechanisms heritability: Desikan, snp different O., Beyond Frei, two D., Holland, incongruity: genetic and additive Incompatibility mainly to Sciences point relationships. partner theory (1975). intimate and of G. functioning Data (2017). O. N. (2008). D. M. Assessment. Hogenboom, P. Obura, Scientifc Visscher, Global & traits. . . E., First complex . M. for A E., variance Goddard, Geiger, : G., J., W. Reefs Day, Hill, Coral D., Heritage K. Centre World Anderson, Heritage on F., World Change and Douvere, UNESCO opportunities Climate M., Carvalho, new of C. organisms: Eakin, Impacts . . . nonmodel F., T., of S. M. genetics Heron, Limborg, population R., for Ogden, SNPs I., of M. Application challenges. Taylor, D., (2011). Bekkevold, R. J., G. Hemmer-Hansen, J., S. Helyar, 24 1) 1403–1405. (11), ). , 188 M vltoayBiology Evolutionary BMC rmdffrn efenvironments. reef different from oeua clg Resources Ecology Molecular 19) 361–375. (1092), BioRxiv p.6–9.Springer. 67–89). (pp. 133132. , LSGenetics PLoS elSystems Cell . nlsn eoewd N aauigaeee ..0 2.0. adegenet using data SNP genome-wide Analysing , 19 , 11 , acsraglomerata Saccostrea 1,187. (1), , oeua Ecology Molecular 8 rceig fteRylSceyo odn eisB Biological B. Series London. of Society Royal the of Proceedings 4 123–136. , 5,363–379. (5), uli cd Research Acids Nucleic (2). 12 M Genetics BMC , Nature 22 ept oswti each? within loss despite cec Advances Science 1) 4335–4348. (16), o:10.1038/s41586-019-1081-y doi: . , 29 aapouto n nlssin analysis and production Data 4,e25–e25. (4), , 11 1,94. (1), , 2 Science 5,17 Retrieved 1–7. (5), Aquaculture . Bioinformatics , 359 Heliopora (Porites (6371), Paris, , 454 Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. uge,K,Wli,B,&By .(07.Hrtblt fthe of Heritability Proteomic Baums, (2017). coral L. . . reef-building Bay, corals. . (2010). the spawning & M., broadcast C. of A. B., horizontally-transmitting larvae Szmant, Willis, Chen, in J., K., C. stress & Quigley, Randall, thermal K., L., to M. responses Fang, DeSalvo, Location-specific J., faveolata C., Schnetzer, (2010). R., Lu, B. C. I. Voolstra, U., R., W. N. endosymbiosis. Polato, Adult cnidaria-dinoflagellate Chen, in (2012). L., H. membranes Wang, Portner, 10.1002/pmic.201000126 symbiosome & Y., of A., Wang, analysis D. oysters. S., Raftos, in L., Peng, acidification Borysko, ocean A., to W. response O’connor, 82–92. offspring M., P. influences resistance Ross, exposure coral reef M., of L. Mechanisms Parker, (2014). A. R. Bay, change. & climate N., Traylor-Knowles, future mechanisms. J., to immune D. in Barshis, coral R., approaches of Sciences S. Bayesian network Palumbi, Biological integrated B: (2008). an Society Towards single S. Royal (2012). J. the noncoding N. Traylor-Knowles, of Alho, Proceedings to & & V, function C., C. Teplitsky, assigning Palmer, O., Ovaskainen, unknown: M., the genetics. J. quantitative Mining Cano, evolutionary B., (2017). R. P. O’hara, A. Boyle, & polymorphisms. nucleotide S., S. use Nishizaki, for reefs probiotics coral (2019). Symbiodiniaceae of E. resilience Medicine, (2019). and and M. persistence Sciences K. of bleaching. Quigley, Academies & coral National G., of D. indicators Bourne, as recovery. Y., traits bleaching J. Species genetic in Hung, rapid (2018). A., for S. C. limits J. Morgans, and Madin, Potential & H., (2018). A. K. Reefs Baird, L. coral. Chakravarti, L., Bay, Reef T. & Barrier . Mizerek, . V, Great . G. a J., Aglyamova, in D. A., Hunter, warming A., to E. L. adaptation Treml, diseases. Hindorff, V, complex B., M. of D. Matz, heritability Goldstein, inform missing J., can the N. connectivity Finding Cox, of S., (2009). F. patterns A. Reef. Collins, Congruent Barrier A., Great (2016). T. the H. Manolio, on J. corals M. spawning Oppen, broadcast biomarkers van for expression & management Gene C., (2017). Riginos, D. V., limitations. S. Lukoschek, and Dyall, Promises Pharmacology & & C., corals: Toxicology A. C: scleractinian Baker, Part in R. D., C. of stress Kenkel, district heat R., STRUCTURE light of over-interpret red Bhagooli, to the D., in Y. not package Louis, how a on Plotrix: tutorial A (2006). J. (2018). model.’ Lemon, D. ‘animal Falush, the plots. & using bar L., ADMIXTURE populations Dorp, Sciences and Van Biological natural B: J., in London D. parameters of Lawson, genetic Society Royal Estimating the of (2004). Transactions re- B. Philosophical Temperature E. conditions. (2019). field L. A. under Kruuk, stages Hund, developmental key & of A., timing Walter, the 756700. and N., height , Kirchgessner, final P., affects M. wheat of Boer, sponse S., Yates, L., Kronenberg, 1–10. , . LSOne PLoS etrto Ecology Restoration , 5 Science 6,e11221. (6), rnsi Genetics in Trends aueCommunications Nature , ora fEouinr Biology Evolutionary of Journal 344 , 191 68) 895–898. (6186), ainlAaeisPress. Academies National . . 63–77. , , 33 1,34–45. (1), 13 cetfi Reports Scientific LSGenetics PLoS , , 279 9 eerhrve fitretost nraethe increase to interventions of review research A 1,3258. (1), 14) 4106–4114. (1745), Symbiodinium Nature oprtv iceityadPhysiology and Biochemistry Comparative R-News , 21 , oeua Ecology Molecular 14 , , 4,949–957. (4), 461 7 4,e1007220. (4), , lblCag Biology Change Global 8219. , 6 76) 747–753. (7265), 4,8–12. (4), omnt nvertically-and in community , Proteomics 359 14) 873–890. (1446), . , Montastraea 10 BioRxiv , 18 doi: . Coral (1), Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. ek,A . go .M,Yug .G,Faka,R,Mthl,N . ilr .A,...Hffan .A. A. perspective. Hoffmann, genetic a . . . environments: A., changing K. in Miller, translocations J., of N. risks Mitchell, R., and Applications Frankham, benefits Evolutionary G., miscon- the A. and Young, Assessing era—concepts M., genomics assisted (2011). C. the Sgro, through in R., resilience Heritability A. Weeks, reef (2008). R. coral N. Wray, Building & G., (2015). ceptions. W. Hill, R. M., P. Gates, Visscher, & H., Putnam, J., evolution. Oliver, Oppen, van coral–dinoflagellate of 10.1098/rspb.2001.1733 Patterns of doi: (2001). physiology J. 1759–1767. and D. availability Miller, local of & of selectivity. M.-T., analysis symbiont significance A. global Piquet, Acropora: P., A F. in Palstra, associations (2019). H., J. R. M. Woesik, Oppen, van van & G., Hodgson, decades. K., two 09238-2 past M. the Donovan, over E., bleaching coral D. Burkepile, S., Sully, is molecule, superfamily (2013). Corporation. L. immunoglobulin Development Owens, and novel & D., a Jerry, J., CEPU-1, Stevenson, cells. Purkinje (1996). cerebellar T. developing by Brummendorf, increases expressed of & signatures F., Metabolomic Spaltmann, (2016). coral, D. reef-building R. the Gates, from & acidification E., , persistence. P. ocean coral Anderson, and to M., temperature threat H. in (2011). silent Putnam, T. A M., Ikuta, E. synchrony: Sogin, spawning in . . Breakdown . (2019). M., change Y. Tanaka, environmental Science Loya, to K., & responses Hisata, coral T., of understand M., Shlesinger, spectrum to Hamada, the genome T., digitifera broadens Acropora Kawashima, theory the Information E., Using Shoguchi, (2017). E. C., P. Shinzato, Smouse, & evolution. L., and Jost, Eltham ecology A., molecular the Chao, of B., W. case Sherwin, the Harrisson, butterfly: endangered . . an . P., of Sunnucks, rescue J., genetic E. Roycroft, for report T., scope A T. the T. (2019). Nguyen, Assessing N. copper. R., Webster T. (2017). MJH Program. New, A. Oppen Adaptation G., K. van and M. Restoration Gardner, CJ, Reef M., Randall Buerger the Roitman, K, R, by Quigley Government Babcock L, Australian A, Bostrom-Einarsson the Negri M, to D, Rocker provided , Harrison LK P, Bay Cleves Program. P, reef Adaptation for and variation Restoraiton adaptive historical Reef of of spread active role (2019). The P. the O. (2019). Assessing H. Rajora, Bleaching J. (2020). M. K. (2018). Oppen, van L. juveniles. H. Bay, & coral K., J. & resilience. of L. tolerance M. H., Bay, M, heat J. Oppen, Kate the M. Quigley, van on Oppen, symbionts & van algal L., and J., regime B. C. temperature Randall, Willis, M, A., In K Endosymbionts. M. Quigley, Algal Coffroth, of Role C., the A. and Baker, Resistance M, K Quigley, ur,P,Si .J,Vsa,B,Rsel .H,Oel . oel .D,...Kcrs .(07.Model (2017). K. Kechris, . . . D., R. Dowell, A., Odell, H., data. P. sequencing Russell, high-throughput B., for Vestal, scores heritability J., based W. Shi, P., Rudra, 12 4,71. (4), , netCnevto n Diversity and Conservation Insect 365 aueRvesGenetics Reviews Nature clg n Evolution and Ecology rceig fteNtoa cdm fSciences of Academy National the of Proceedings 65) 0210.di 10.1126/science.aax0110 doi: 1002–1007. (6457), rceig fteRylSceyo odn eisB ilgclSciences Biological B: Series London, of Society Royal the of Proceedings ouainGnmc:Cnet,Apoce n Applications and Approaches Concepts, Genomics: Population , 4 6,7975 o:10.1111/j.1752-4571.2011.00192.x doi: 709–725. (6), rnsi clg Evolution & Ecology in Trends , Accepted , 9 4,255–266. (4), aueCommunications Nature , . 10 eca eetv reigProject Breeding Selective Redclaw 5,399–414. (5), ora fNeuroscience of Journal 14 oa Bleaching Coral , 112 M Bioinformatics BMC , 32 8,2307–2313. (8), , oilpr damicornis Pocillopora 10 1) 948–963. (12), p.1111.Springer. 111–151). (pp. 1,16.di 10.1038/s41467-019- doi: 1264. (1), , Symbiodinium 16 5,1770–1779. (5), ua nutisResearch Industries Rural . ilg Open Biology , 18 Springer. . 1,143. (1), tan n host– and strains . . Metabolomics , . 268 (1478), Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. uvvl000 00 .8 .3(.3-0.98) - (0.73 0.93 0.88) - (0.00 0.0007 Survival 2. Table 1 2 0 H the wrote interests. data, 1. financial Table the or competing analysed no declare work, authors lab The the Statement manuscript. performed Interest the reviewed of KMQ critically Conflict and research; reagents contributed the authors designed All manuscript; MvO LB, KMQ, X. and X accession contributions SRA Author NCBI through available R. is J. data Casey, Sequencing . NF- . calcification. . of cnidarian R., of Accessibility Suppression evolution C. Data the Voolstra, in (2017). step N., key B. Techer, a towards N., Huang, Reports point corals Caminiti-Segonds, Scientific in A., transporters . . Bicarbonate Bertucci, . P., (2015). stress. X., Ganot, heat Yu, under D., aculeus G., Zoccola, Acropora Chen, coral C., stony in Li, and protein Immunology C., symbiotic NLRC3-like Zhang, of by pathway Y., expression signal Wu, gene Z., differential Zhou, and Profiling analysis. eQTLs (HiCEP) profiling Genome-wide (2011). expression N.Y.) gene Y. (2014). York, coverage M. (New Takei, high Wang, a & using & corals T., Z., aposymbiotic Watanabe, Luo, individuals. L., H. I., unrelated D. Leach, Yuyama, Nussey, in J., traits Chen, . expression . . N., gene A., Jiang, for C. heritability Y., Walling, E., Liu, model. Postma, S., animal M., Yang, the M. to Morrissey, guide N., ecologist’s M. An Clements, Lysosomal D., (2010). Reale, (2017). J., K.-H. A. Lee, responses. Wilson, inflammatory . . receptor–mediated . Medicine toll-like O., Experimental to Holst, trafficking of M., membrane Journal Krautkramer, links G., Lyst Grassl, regulator J., trafficking Yu, W., Cheng, A., Westphal, H D D o α α α vrg bevdheterozygosity observed Average = ± ± ± D=Apawti-ouainEtoya 1 = q at Entropy within-population Alpha = SD D=Apawti-ouainDvriya 2 = q at Diversity within-population 0 Alpha = = q SD at Diversity within-population Alpha = SD ennro-es eiaiiy(h heritability narrow-sense Mean eoi iest metrics diversity Genomic 27.5 h , 2 67 (mean ° 31 C 322–330. , , , 5 13 9983. , W0241.30 0.244 CW 1.29 0.158 WW1 C0231.31 0.223 1.28 1.30 0.189 WC 0.219 WW3 WW2 ± rs H Cross 1,3–0 o:10.1007/s10126-010-9265-3 doi: 32–40. (1), 5 aeinCeiiiyItras h Intervals) Credibility Bayesian 95% o , 214 0 1,227–244. (1), Δ α 2 ± ± ± ± ± esrmnsfrcrljvnlsifce with infected juveniles coral for measurements ) ± .61.22 1.23 1.20 0.46 1.22 0.46 1.20 0.45 0.46 0.45 ΣΔ ora fAia Ecology Animal of Journal 15 2 Δ α ± ± ± ± ± ± .70.17 0.18 0.37 0.37 .60.16 0.18 0.17 0.36 0.36 0.34 M Genomics BMC 2 ΣΔ ° C (mean 1 Η ± α 5 aeinCeiiiyIntervals) Credibility Bayesian 95% ± ± ± ± ± ± 0.28 0.28 0.27 0.28 0.27 , 79 , ΣΔ 15 1,13–26. (1), 1,13. (1), aieBiotechnology Marine ih&Shellfish & Fish .goreaui. C. κ B Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. uerdadhbi rse W essW:21-6 Wvru W .e2)btntbtenhybrids between not but 1.3e-21) CW: versus WW crosses 2.1e-26, 0.34). WC: population CW: versus within versus (WW signficantly (WC crosses differed hybrid frequencies and allele WW: purebred WC: expected test, 34, for WW: versus Two-Sample = CW) (n Theoretical (Kolmogorov-Smirnov sizes (blue: 19). population three cool-warm CW: the yellow), for 15, simulated WC frequencies 27.5 allele (yellow: of at distributions warm-cool Hardy-Weinberg reared WW), variation larvae genotyped genetic (red: individually crosses greater warm-warm signficanlty of genome. creates consisting coral populations the across across breeding 2.Selective Figure membership clusters. the genetic of indicative assigned colors the with of larva, each genotyped into individually population an that crosses. represents for genetic bar probability five vertical to Each correspond 5. colors = Point CW). dataset. (blue: SNP cool-warm the WC), (yellow: and warm-cool Analysis WW3), nates WW2, genotyped WW1, crosses. individually (red: population 68 crosses for among analysis differential cluster Genetic 1. Figure 0.67) - (0.00 0.01 0.34) - (0.03 0.15 0.76) (0.00- 0.01 0.34) - (0.02 Growth 0.13 Bleaching h 2 (mean (B) ± iciiatAayi fPicplCmoet DP)o eei tutr across structure genetic of (DAPC) Components Principal of Analysis Discriminant 5 aeinCeiiiyItras h Intervals) Credibility Bayesian 95% itiuino leefeunisfrprbe n yrdosrn groups offspring hybrid and purebred for frequencies allele of Distribution ° .Baklnscrepn omdle hoeial expected theoretically modelled to correspond lines Black C. cooaspathulata Acropora = p 16 .e4,W:22-6adC:10-5 n between and 1.0e-45) CW: and 2.2e-46 WC: 1.0e-45, 2 (C) (mean igeNcetd oyopim(SNP) Polymorphism Nucleotide Single avepoue rmfiereproductive five from produced larvae ditr neec sn ACat DAPC using inference Admixture ± 5 aeinCeiiiyIntervals) Credibility Bayesian 95% (A) rnia Coordi- Principal k Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. costefierpoutv rse nPo- A n CA2() rprino rtisprfunctional per proteins. proteins of of categories functional Proportion the (B). proteins to PCoA-2 annotated correspond and different Colors (A) Significantly (inset). PCoA-1 variation). proteins in corals. of (PC1 of crosses category breeding loadings reproductive selective five PCoA of the to result across protein a as each proteins of functional contribution in Variation 3. Figure 17 A Relative (A) Posted on Authorea 11 May 2020 — CC-BY 4.0 — https://doi.org/10.22541/au.158921584.47783210 — This a preprint and has not been peer reviewed. Data may be preliminary. variation-through-selective-breeding-of-coral articles/449661-genome-wide-snp-analysis-reveals-an-increase-in-adaptive-genetic- Quigleyetal._SNPs_AGF2017_MErefs.docx file Hosted h mean to correspond 31 lines (red: Dashed stress heat and 4. Figure arwsnehrtblt (h heritability Narrow-sense ° )tmeauecniin njvnl oasifce with infected corals juvenile in conditions temperature C) 2 ftedistribution. the of 2 fsria,becigadgot ne min bu:27.5 (blue: ambient under growth and bleaching survival, of ) vial at available 18 https://authorea.com/users/320037/ ldcpu goreaui Cladocopium ° C) .