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The genetics and epigenetics of animal migration and orientation:birds, butterflies and beyondChristine Merlin1,* and Miriam Liedvogel2,*

ABSTRACTMigration is a complex behavioural adaptation for survival thathas evolved across the animal kingdom from invertebrates tomammals. In some taxa, closely related migratory species, or evenpopulations of the same species, exhibit different migratoryphenotypes, including timing and orientation of migration. In thesespecies, a significant proportion of the phenotypic variance inmigratory traits is genetic. In others, the migratory phenotype anddirection is triggered by seasonal changes in the environment,suggesting an epigenetic control of their migration. The genes andepigenetic changes underpinning migratory behaviour remain largelyunknown. The revolution in (epi)genomics and functional genomictools holds great promise to rapidly move the field of migrationgenetics forward. Here, we review our current understanding of thegenetic and epigenetic architecture of migratory traits, focusing ontwo emerging models: the European blackcap and the NorthAmerican monarch butterfly. We also outline a vision of howtechnical advances and integrative approaches could be employedto identify and functionally validate candidate genes and cis-regulatory elements on these and other migratory species acrossboth small and broad phylogenetic scales to significantly advance thefield of genetics of animal migration.

KEY WORDS: Seasonal adaptations, Migratory genes, Orientationgenes, Reverse genetics, Genomics, Clocks

IntroductionMigration is a common and critical behavioural adaptation forsurvival that has evolved in many animal taxa ranging frominvertebrates to mammals. Animal migrations greatly vary in thedistance travelled, from short trips as in the case of altitudinalmigration (i.e. from lower to higher altitudes and back) to trans-continental migrations. All are, however, characterised by a seasonalmovement to escape unfavourable environmental conditions andreach more-favourable sites during the inimical season, followingprecisely coordinated orientations and timing schedules. Toaccomplish such a remarkable navigational feat, migrants areequipped with a suite of adapted morphological, sensory,physiological and behavioural traits that are genetically encodedand turned on at the appropriate time of the year and/or under specificenvironmental conditions. Many studies have focused on elucidatingthe sensory cues and navigational strategies used for maintainingcourse orientation (Reppert et al., 2010; Reppert et al., 2016;

Mouritsen, 2018), which includes the use of celestial compass cues(Kramer, 1950, 1952; Sauer, 1957; Schmidt-Koenig, 1958;Wiltschko et al., 1987; Perez et al., 1997) and the Earth’s magneticfield (Wiltschko, 1968; Wiltschko and Wiltschko, 1972; Guerraet al., 2014). In contrast, the genetic architecture and molecularmechanisms that underlie the migratory phenotype, including flightdirection/orientation and timing of their migration, remain poorlyunderstood.

The explosion of technological advances in high-throughputsequencing (HTS) is starting to change this trend and holds greatpromise in applying non-biased approaches in the quest for de novodiscovery of ‘migratory’ genes. Draft genome sequences of afew migratory species, including the monarch butterfly Danausplexippus (Zhan et al., 2011), the Swainson’s thrush Catharusustulatus (Delmore et al., 2016), the willow warbler Phylloscopustrochilus (Lundberg et al., 2017), the stonechat Saxicola maurus(van Doren et al., 2017a), the rainbow trout Oncorhynchus mykiss(Berthelot et al., 2014) and the Chinook salmon Oncorhynchustshawytscha (Christensen et al., 2018) are now available, and manymore are on their way. This includes those of iconic migratory birdswith well-characterised behaviours and evolutionary historiessuch as the European blackcap Sylvia atricapilla (K. E. Delmoreand M.L., personal communication; Fig. 1). The use of whole-genome sequencing (WGS) or other HTS techniques, such asgenotyping by sequencing (GBS) or restriction site associatedDNA sequencing (RAD-seq) has enabled population genomicsstudies characterising migratory and non-migratory populations inthe monarch and avian species or populations with differentinherited migratory orientation (Zhan et al., 2014; Delmore et al.,2016). These studies revealed genomic regions with signaturesof selection that may contain candidate genes for migration,cis-regulatory elements (CREs) and chromosomal inversions (Zhanet al., 2014; Delmore et al., 2015, 2016). RNA-seq is anotherapproach that has been used to identify candidate migratory genesin the rainbow trout, the Swainson’s thrush and the Europeanblackbird Turdus merula by quantifying gene expressiondifferences in brains and/or blood of individuals exhibitingvariation in a migratory trait, such as migrants versus residents orpopulations of migrants varying in migratory orientation (Haleet al., 2016; Johnston et al., 2016; Franchini et al., 2017). Acomprehensive understanding of the genetic basis of migration will,however, only be achieved through the use of combinatorialgenomic and epigenomic (i.e. the study of modification in thegenetic material due to environmental factors) approaches and theultimate functional validation of candidate genomic regions throughin vivo genetic disruption and behavioural assays in any givenmigratory species.

Here, we provide an overview of two iconic and complementarysystems with well-characterised life history strategies andmigratory patterns that are poised to increase our understanding ofthe genetics and epigenetics of animal migration: the European

1Department of Biology and Center for Biological Clock Research, Texas A&MUniversity, College Station, TX 77843, USA. 2Max Planck Institute for EvolutionaryBiology, Max Planck Research Group (MPRG) Behavioural Genomics, 24306 Plon,Germany.

*Authors for correspondence (cmerlin@bio.tamu.edu; liedvogel@evolbio.mpg.de)

C.M., 0000-0003-2133-6972; M.L., 0000-0002-8372-8560

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© 2019. Published by The Company of Biologists Ltd | Journal of Experimental Biology (2019) 222, jeb191890. doi:10.1242/jeb.191890

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blackcap and the North American monarch butterfly. We alsooutline our vision of how technical advances and integrativeapproaches could be employed on these and other migratoryspecies across both small and broad evolutionary and phylogeneticscales to rapidly move the field of genetics of animal migrationforward.

Emerging model systems for the study of genetics andepigenetics of migration and navigationThe European blackcap Sylvia atricapillaPopulations of European blackcaps, which are common breedingbirds across Europe, exhibit a remarkably broad spectrum ofbehavioural variation in migratory status and orientation direction(Fig. 1A). Although selective breeding studies firmly established agenetic basis for migratory orientation decades ago (Helbig, 1991,1996; Berthold et al., 1992), the recent development of genomics isstarting to unlock the great potential of the extreme phenotypicvariation in blackcaps to study migration genetics at the molecularlevel. Phenotypic variation across populations ranges from residentsto short-, medium- and long-distance migrants (Berthold et al., 1990).In addition, migrants exhibit variation in migratory orientationstrategies and form so-called migratory divides, i.e. areas whereneighbouring populations breeding in close proximity have distinctmigratory routes and non-breeding grounds (Fig. 1B). Blackcaps aredistributed continuously across the central European migratorydivide, with breeding populations in Europe and overwinteringareas in southern Iberia and northern Africa. In autumn, populationsbreeding west of the divide migrate southwest (SW) around theMediterranean Sea, while populations east of the divide migratesoutheasterly (SE) (Fig. 1B). In addition, since the 1960s, a growingnumber of birds breeding in central Europe migrate northwest inautumn to overwinter in the British Isles (Berthold et al., 1992),possibly because of the milder wintering conditions and foodavailability in British gardens (Plummer et al., 2015).

A series of common garden experiments using blackcaps withdifferent migratory phenotypes provided clear evidence that migratorytraits like distance (Berthold and Querner, 1981) and direction(Helbig, 1991, 1996; Berthold et al., 1992) are genetically encodedand have the potential to drastically change within a few generationsunder strong artificial selection (Berthold, 1991). In theseexperiments, selection lines were first generated by mating SWmigrants with SW migrants and SE migrants with SE migrants forseveral generations in order to obtain populations that are fixed foreach migratory orientation (Fig. 1C). In cross-breeding experiments,SWmigrants were then mated with SEmigrants, and the progeny wasreared in isolation from their parents to exclude the possibility thatmigratory direction could be learned. The intermediate orientationtaken by hybrids unambiguously demonstrated the genetic inheritanceof this migratory trait (Helbig, 1991, 1996; Berthold et al., 1992).

Like most songbirds, blackcaps migrate at night and mostly bythemselves. Because parents often leave the breeding groundsearlier (Flack et al., 2018), young inexperienced birds on their firstmigratory journey have to find their way on their own. Despiteheading towards a completely unfamiliar destination, they reach itwith amazing precision. Behavioural experiments in the lab and inthe wild have shown that migratory birds use various compasses forcourse orientation. Like other night navigators, blackcaps rely on amagnetic compass calibrated by sunrise/sunset polarized light cuesand a star compass (Wiltschko and Merkel, 1966; Wiltschko andWiltschko, 1972; Wiltschko et al., 1987; Phillips and Moore, 1992;Cochran et al., 2004). Birds are also equipped with an inherited timeschedule and at least an initial migratory direction that are integratedinto a spatiotemporal strategy signalling of when to leave thebreeding grounds, and how far and in which direction to fly(Liedvogel et al., 2011).

The variability in migratory strategy that presumably reflectsdifferences in direction and strength of selection make blackcaps anexcellent model to study not only the genetic variation in migratorytraits, but also the effects of selection on this complex phenotype

A

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Fig. 1. Distribution map and migratory phenotypes of Europeanblackcaps. (A) Adult male with its characteristic black cap. (B) Map showingthe variability in migratory phenotypes with respect to distance (reflected by thelength of the arrows; partial migrants as dashed lines, resident island andcontinental populations as green circles) and direction during autumnmigration [south-west (SW) migrants red, south-east (SE) migrants blue, and arecently evolved population migrating north-west (NW) overwintering in theBritish Isles orange]. The approximate location of the central Europeanmigratory divide with neighbouring populations choosing distinctly differentmigratory orientation strategies is indicated (dashed blue line). (C) Cross-breeding experiments in blackcaps demonstrate the inherited nature ofmigratory direction during autumn. Offspring from selectively mated SW (red)or SE migrating parents (blue) follows the parental migratory direction, butoffspring from cross-bred parents (blue, framed red) exhibit an intermediatedirection. Circular plots depict directional preference of individuals (circles) andmean heading of the population (arrow). Modified from Helbig, 1991.

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(Fig. 1) (Liedvogel et al., 2011; Delmore and Liedvogel, 2016).The inability to estimate population structure using neutralmarkers across the genome (Helbig, 1994; Pérez-Tris et al., 2004;Mettler et al., 2013) suggests that migratory traits of neighbouringpopulations do not correlate with strong overall geneticdifferentiation. Migratory traits rather seem to be controlled eitherby selection processes on relatively few genomic regions and/ordifferences in gene expression. This hypothesis is supported by thefinding that few genes appear to be involved in determining theexpression of migratory traits (Helbig, 1996), and by the apparentstrong genetic correlation between different migratory traits forwhich variation in one trait is often dependent on variation inanother (Pulido et al., 1996; Pulido and Berthold, 1998). With ade novo assembly of the blackcap reference genome underway, andthe technological advances in HTS, characterizing the genetic basisof the variation in migratory phenotypes at the genome-wide levelwill now be feasible. Whole-genome re-sequencing of blackcapsexhibiting the full spectrum of migratory phenotypes is anticipatedto provide insights into the origins and maintenance of variation inthe migratory behaviour and the identification of genetic variantsunderlying focal traits in migratory behaviour, including thepropensity to migrate, orientation and distances travelled.

The North American monarch butterfly Danaus plexippusWith established genomic resources that include tools for germlineediting, the North American monarch butterfly is an equallycompelling model and arguably the best suited to define the geneticand epigenetic basis of insect long-distance migration. Monarchbutterflies from the eastern North American population undergoone of the most impressive annual long-distance migrationsaccomplished by any insects, have a rich and well-documentednatural history, and progress has been made in understanding theneurobiological basis of their migration (Urquhart, 1960; Reppertet al., 2016). Each autumn, coincident with decreasing day length (i.e.photoperiod), monarchs east of the Rocky Mountains depart fromtheir northern breeding sites, migrating south to reach theiroverwintering sites in Mexico, where they remain in a state ofreproductive quiescence (i.e. diapause) until the spring (Fig. 2A).Then, with increased temperatures and photoperiod, migrants becomereproductive, mate and re-migrate northward to the southern UnitedStates where females lay their progeny onto milkweed plants, theunique host on which larvae feed. Both autumn migrants and springre-migrants use a time-compensated sun compass as a primarycompass system to guide their course orientation (Perez et al., 1997;Mouritsen and Frost, 2002; Froy et al., 2003; Merlin et al., 2009) andmay also take advantage of their ability to orient to the magnetic fieldwhen the sun is not visible (Guerra et al., 2014). Unlike birds, the re-migrant adults do not make the return back to the breeding sites.Instead, the completion of the annual migratory cycle takes at leasttwo successive generations of reproductively competent spring andnon-oriented summer butterflies that follow the northwardprogression of milkweed availability (Fig. 2A). The butterflies thatemerge by late summer in the northern range of the breeding sites arethen re-programmed into autumn migrants. Just like younginexperienced birds, autumn migratory monarchs travel thousandsof kilometres on their virgin migratory journey and locate theiroverwintering grounds with astonishing precision, sometimes evenclustering on the same trees as their great-grandparents. However,unlike birds, migratory direction cannot just be an inherited trait, asautumn migrants not only share the genetic make-up of their non-migratory parents but also reverse flight orientation by 180 degrees inthe spring when they become remigrants.

The switch in migratory physiology and behaviour and thereversal in flight orientation that occur respectively in the autumn andspring in response to environmental changes suggest an epigeneticcontrol of the eastern North American monarch migration (Fig. 2A).While seasonal changes in autumn photoperiod and temperaturelikely control the migratory switch, the trigger that reverses flightorientation from south in autumn migrants to north in springremigrants has been identified as a prolonged exposure to lowtemperatures that mimic the coldness experienced by migrants attheir overwintering sites (Guerra and Reppert, 2013). The ability toexperimentally re-program the southward migratory orientation ofautumn migrants into a northward orientation in controlledlaboratory conditions provides a unique opportunity to define theepigenetic mechanisms underlying reorientation of the sun compassin the brain (Guerra and Reppert, 2013).

In fact, transient exposure of animals to environmental factorshas previously been shown to induce and maintain behavioural statesby changing the neuronal epigenetic landscape that regulatestranscription of genome-wide gene expression over long periods oftime (Bonasio, 2015; Yan et al., 2015). Reprogramming of generegulatory networks could involve the alteration of chromatinstructure via histone post-translational modifications, and/or theactivity of specific transcription factors that bind to CREs to activateor repress gene expression (Bonasio et al., 2010). In contrast to birds,DNAmethylation is unlikely to play a significant role in the monarchseasonal migratory behaviour, as this species appears to lackdetectable patterns of de novo DNA methylation (Zhan et al., 2011;Bewick et al., 2017). Temperature-dependent post-transcriptionalmechanisms involving regulation of gene expression bymicroRNAs,mRNA splicing or RNA editing are alternativemechanisms bywhichflight orientation could also be re-programmed, as temperature-dependent regulation of these mechanisms has previously beenreported in other organisms (Low et al., 2008; Garrett and Rosenthal,2012; Bizuayehu et al., 2015).

Despite being the focal population for studying the mechanismsthat drive monarch migration, the North American population isnot the only monarch population found around the globe. Otherpopulations are present in Oceania, Central America, South America,the Caribbean, Europe and North Africa (Fig. 2B). While theAustralian population also undergo a seasonal migration, although ofshorter distances than the North American population (Dingle et al.,1999), all the others are felt to be non-migratory (Dockx, 2007;Altizer and Davis, 2010; Zhan et al., 2014). These differences inmigratory behaviour between populations have also been leveraged toidentify putative genes involved in monarch migration (see below).

As illustrated with the blackcap and the monarch butterfly, thereare clear differences in the nature of the molecular basis (geneticand/or epigenetic) underlying migration between taxa that may beinherent to the biology of each species. The diversity of migratoryphenotypes across bird species, together with the existence ofpopulations with clearly defined and differing migratoryorientations within a single species, makes them uniquely suitedfor studying the genetic basis of migration. The seasonal plasticityof monarch butterflies trans-generational migratory behaviour, onthe other hand, offers opportunities to study the epigenetic basis ofmigration. With the ability to maintain colonies in the laboratoryyear-round, a fast generation time and its accessibility to in vivogenetic manipulation (Merlin et al., 2013; Markert et al., 2016;Zhang et al., 2017), the monarch is also uniquely suited to rapidlyassess the function of candidate migratory genes (Fig. 3B). Usingthese two species as focal examples, we highlight how integrating adiverse array of approaches used in behavioural ecology, sensory

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biology, evolutionary biology, genetics and molecular biology canbe leveraged to move the field of migration genetics forward.Ultimately, the discovery of generalizable mechanisms, or lackthereof, will, however, require the diversification of strategicallychosen migratory animal models across taxa.

Accurate phenotyping of migratory behaviour is keyRegardless of the species or population of interest, accurateknowledge of the migratory phenotype and the ability tocharacterize and quantify it is an essential prerequisite tocharacterize the underlying molecular machinery that modulatesthe variation in migratory behaviour. Capture–mark–recapturemethods and careful assessment of the individual’s morphologyand physiology associated with the migratory state (i.e. wing sizeand shape, fat stores) have provided useful information, with the

exception of the detailed behavioural strategies of individualmigrants.

Aided by the miniaturization of tracking devices, more advancedon-board tracking technologies can now inform both orientation andtiming characteristics of migratory routes taken by individuals overlong distances in their natural habitat. The most informative datacome from studies using global positioning system (GPS) satellitetransmitters (Perras and Nebel, 2012), where real-time recording ofthe signal by satellites enables the long-term monitoring ofmigratory movement around the globe without recapture of thetagged animal. Using this technology for real-time monitoring ofsmaller passerines such as the European blackcap is not yet possibledue to the relatively large size of transmitters. Current alternativetechnologies include archival tags that record light-intensity data(i.e. light-level geolocators) as well as radio-transmitters and

Photoperiod decreaseMigratory switch triggered

Overwintering coldness flips flight orientation

Autumn migration

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Fig. 2. Annual migratory cycle of North American monarch butterflies (Danaus plexippus) and world-wide distribution of monarch populations.(A) Monarch butterflies in flight (left). Photo credit: MonarchWatch. The southward migration of North American monarchs coincides with autumnal decreasingphotoperiod that is sensed by an endogenous seasonal timer (middle). Monarchs east of the Rocky Mountains (brown line) navigate over long distances(red arrows) to their overwintering sites in Mexico (orange dot) (Urquhart, 1960; Brower, 1995). Some migrants fly towards Florida where they mix with residentpopulations (dashed grey arrow) (Knight and Brower, 2009; Reppert et al., 2016). Monarchs west of the Rockies migrate southward in the autumn but overwinteralong the Californian coast (red arrows). In the spring, eastern monarchs in Mexico become reproductive, mate and fly northward to the southern United States(right; red arrows). Subsequent generations of spring and summer butterflies progress northward following the latitudinal emergence of their host plants torepopulate the northern summer breeding grounds (black arrows). Whether monarchs overwintering in Florida make the trip back north is not known (dashed greyarrow). Western monarchs also migrate northward in the spring (black arrows). The key roles that environmental changes (photoperiod and temperature) play inthe Eastern North American monarch migration suggest an epigenetic basis to the monarch migration. Modified from Reppert et al., 2016. (B) World-widegeographic distribution of monarch populations and their migratory/non-migratory status. Populations present on both the North American and the Australiancontinents exhibit seasonal migrations (Urquhart, 1960; Brower, 1995; Dingle et al., 1999) (circle with red border). Populations located in Central America, SouthAmerica, and the Caribbean, are felt to be non-migratory (Zhan et al., 2014), primarily based on wing morphology. Populations with similar genetic structures,determined by whole-genome re-sequencing (Zhan et al., 2014), are shown by similar colour inside the circles.

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telemetry systems (Stutchbury et al., 2009; Kishkinev et al., 2016;Taylor et al., 2017). In contrast, no comparable devices exist yetfor insects. Until the next revolution in miniaturization, whengeolocators or GPS devices weighing only a few tens of milligramscould be developed, entomological radars will likely remain themethod of choice to track flight paths and strategies of migratoryinsects in nature (Chapman et al., 2008, 2010, 2011; Bruderer,2016; Woodgate et al., 2016).Assessing migratory behaviour in laboratory conditions will be

equally important to ultimately test gene function in vivo. A numberof laboratory-based methods have been developed in birds andbutterflies for use as proxies of migratory status and orientation. Acommonly usedmethod in birds relies on recording the characteristicmigratory restlessness exhibited during the migratory season, even

when kept in cages in controlled conditions (Kramer, 1949, 1950).Quantified timing and directedness of this behaviour coincide withtiming and orientation of free-flying conspecifics (Gwinner, 1968,1986; Berthold, 1973, 1995). Behavioural cages for testing birdmigratory status and orientation, known as ‘Emlen funnel’ (Emlenand Emlen, 1966), are generally funnel-shape arenas. The walls arecovered with coated and scratch-sensitive paper such that restlessmigratory birds leave scratch marks on the inclined walls. Thesemarks can be quantified to measure activity levels and meanorientation bearings (Helbig, 1991; Wiltschko and Wiltschko, 1995;Mouritsen et al., 2009; Zapka et al., 2009). The precisemonitoring oftiming of migration, including onset, duration and intensity ofmigratory restlessness, can be achieved by fitting the cage withpassive infrared detectors that record activity profiles (Gwinner,

TF Pol

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1967). Related methodological approaches have been adapted toinsects, where the orientation of a tethered insect is tracked in a flightsimulator apparatus (Mouritsen and Frost, 2002). This cylindricalplastic barrel can be used outdoors under natural sky conditions toassess spontaneous migratory orientation of tethered insects that arefree to fly in any direction on the horizontal plane (Mouritsen andFrost, 2002; Froy et al., 2003; Dreyer et al., 2018). Similar circularplastic arenas have also been adapted to track orientation in aquaticanimals, including fish (Mouritsen et al., 2013a). Even thoughthese approaches do not fully recapitulate the natural behaviourexhibited by a migrating animal (van Doren et al., 2017b), they willbe valuable tools to ultimately test the function of migratory genesin vivo as genetically manipulated animals cannot be released intothe wild.

Migratory traits: hard-wired or environmentally regulated?Evidence suggests that migratory traits are genetically inherited and/or environmentally regulated in different taxa. The impressive seriesof common garden experiments with European blackcaps providedevidence for a genetic basis of migratory traits in birds (Fig. 1C)(Berthold et al., 1992; Helbig, 1991, 1996). Genetic inheritance ofboth timing and migratory direction was further supported byelegant displacement experiments in which both experiencedadults that already had successfully completed a migratoryjourney and naïve juvenile birds on their first journey weredisplaced from their original location (Perdeck, 1958; Thorupet al., 2007). Inexperienced juveniles followed an innate clock and

compass strategy (e.g. vector navigation), leaving at the right timeand flying the correct distance in the inherited migratory direction.In contrast, adult birds that had the opportunity to learn landmarkson their previous trip were able to compensate for the displacement,actively navigating to their original wintering area (Perdeck, 1958).

In contrast to blackcaps, genetic inheritance of migratory traits inNorth American monarchs has not been established using breedingexperiments, and the interpretation of displacement experimentsremains controversial (Mouritsen et al., 2013b; Oberhauser et al.,2013). Nevertheless, the multigenerational nature of the monarchmigratory cycle in the Eastern United States suggests that genesencoding migratory traits are encoded in the monarch genome, andthus heritable, but are turned on or off in response to seasonalenvironmental changes in the migratory generation.

Timing the seasonal migratory switch and departureAcross taxa, the onset of migratory behaviour and departure frombreeding grounds is tightly linked to the changing seasons. Toprecisely follow timing schedules, animals keep track of the seasonsusing an endogenous seasonal timer that measures photoperiodicchanges.

In birds, migratory timing appears to be controlled in concert withtiming of reproduction and moult by a circannual clock in both wildpopulations and caged birds (Gwinner, 2003; Visser et al., 2010).Correlative studies using a candidate gene approach identified theClock gene as a possible candidate for migratory timing (Petersonet al., 2013; Bazzi et al., 2015, 2016; Saino et al., 2017; Continaet al., 2018). The otherwise highly conserved Clock gene showslength variation at a poly-glutamine repeat, and shorter alleles havebeen associated with earlier arrival times at the breeding grounds inbarn swallows (Bazzi et al., 2015). In the same species, elevatedmethylation levels responsible for reduced transcription at theClocklocus have been shown to correlate with earlier spring migration andonset of breeding (Saino et al., 2017).

In monarchs, circadian clocks or clock genes in the brain havealso been proposed to take part in photoperiodic measurement(Reppert et al., 2016; Denlinger et al., 2017). They could not onlytrigger the photoperiodic programming of the migratory state in theautumn but also time the departure of migrants from their breedingrange. Although the role of circadian clocks in triggering themigratory switch remains to be explored, their importance formonarch migration is not unprecedented. Circadian clocks locatedin the antennae provide the necessary timing component thatallows autumn migrants and spring remigrants to maintain courseorientation by compensating for the daily changes of the position ofthe sun in the sky – the main compass cue used for navigation in thisspecies (Perez et al., 1997; Mouritsen and Frost, 2002; Froy et al.,2003; Merlin et al., 2009; Guerra et al., 2012). Brain clocks are,however, most likely involved in the induction of the migratorytraits and could impact migratory traits by regulating thetranscription of clock genes and clock-controlled genes in thistissue (Hardin and Panda, 2013). With the availability of severalclock gene knockouts in monarchs (Merlin et al., 2013; Markertet al., 2016; Zhang et al., 2017), functionally determining whethercircadian clocks or clock genes play a role in the migratory switchshould now be feasible, at least in this system.

Migration on the move in the genomic and epigenomic eraThe current revolution in HTS technologies and functional genomictools and their applicability in non-model organisms provide uniqueopportunities to comprehensively dissect the genetic and epigeneticbasis of migration (Fig. 3).

Fig. 3. Cutting-edge genomic approaches for identifying and functionallyvalidating candidate migratory genes and cis-regulatory elements.(A) Sequencing-based technologies for identifying gene expression, cis-regulatory elements (CREs) and the prediction of transcription factors (TFs)controlling gene expression. ATAC-seq and DNase-seq are used to identifynucleosome-depleted chromatin regions in which TFs bind DNA enhancersequences to activate or repress the transcription of the genes they control.The activity of enhancers can be determined using ChIP-seq of histone markssuch as H3K27me3 (associated with poised/inactive enhancers) andH3K27Ac (associated with active enhancers). ChIP-seq of RNA polymerase II(Pol II) can be used to measure actual transcription rates, and thetranscriptome can be explored using RNA-seq. The nature of the TF binding inenhancers can be predicted based on the motif sequences to which they leavefootprints using bioinformatics tools. ATAC-seq, assay for transposase-accessible chromatin with high throughput sequencing; ChIP, chromatinimmunoprecipitation; H3K27me3, trimethylation of lysine 27 on histone 3;H3K27Ac, acetylation of lysine 27 on histone 3. (B) The CRISPR/Cas9 systemas a tool for editing germline and post-mitotic cells. The CRISPR/Cas9 systemrelies on a Cas9 protein complexed to a guide RNA that is complementary to a20-bp target sequence harbouring a protospacer adjacent motif (PAM site;left). Upon binding to the targeted genomic sequence, the RNA-guided Cas9induces a DNA double-stranded break (DSB) that stimulates cellular DNArepair through either error-prone non-homologous end joining (NHEJ)-mediated repair or homology-directed repair. NHEJ-mediated repair canintroduce insertions/deletions (indels) that lead to frame shifts and subsequentgene disruptions through the introduction of an early stop codon. Genecorrection and/or addition can also be achieved through homology-directedrepair by co-injection of an exogenous DNA donor template. Germline editingis a technique classically used in insects, fish and mammals that can beachieved by the co-injection of a Cas9 mRNA or a Cas9 protein with a gRNAinto a ‘one-nucleus stage’ embryo (right). The injected embryo gives rise to amosaic founder, which once mated, can produce mutant progeny.Alternatively, CRISPR/Cas9-mediated editing can be achieved in adult post-mitotic cells through the delivery of viral vectors expressing Cas9 and thegRNA in the tissue or structure of interest. In both germline and post-mitoticediting, co-injection of a donor DNA template can stimulate gene correction orgene addition by knock-in (KI). Genetically manipulated organisms can thenbe subjected to assays such as flight orientation and migratory restlessness totest the function of targeted genes. AAV, adeno-associated virus; LV, lentivirus.

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The use of WGS has already enabled population genomicsstudies between migratory and non-migratory populations for theidentification of variation in the genome associated with variation inthe phenotype. In monarchs, for example, re-sequencing of morethan 100 individuals frommigratory and presumably non-migratorypopulations from around the globe (Fig. 2B) identified genomicregions of divergent natural selection comprising ∼500 candidategenes proposed to be associated with shifts in migratory behaviour(Zhan et al., 2014). The interpretation of such genome-wide scansfor a signature of selection is, however, often restricted to protein-encoding genes. Although variations within coding regions couldhave a fundamental impact on protein function, without functionalevidence, variations in non-coding regions such as in CREs shouldnot be excluded as they could affect differences in expression ofgenes located kilobases away. Quantification of differential geneexpression between migratory and non-migratory forms can beachieved using RNA-seq, as exemplified by a few studies in fish andinsects (Jones et al., 2008; Zhu et al., 2009; Hale et al., 2016).However, differential gene expression studies based on RNA-sequsually yield long lists of candidate genes and the prioritizationprocess for further functional studies (discussed below) is notalways straightforward. More-integrated approaches that considernot only loci under selection but also gene expression and itstranscriptional or post-transcriptional control within a single speciescould help in narrowing down the list to a smaller number ofpromising candidates.At the transcriptional level, gene expression is regulated by the

binding of transcription factors to specific DNA sequences in CREslocated in open chromatin regions, and by the recruitment of specificcofactors mediating histone post-transcriptional modifications(hPTMs) that regulate enhancer activity (Bonasio et al., 2010; Lelliet al., 2012) (Fig. 3A). The nature of the recruited cofactors, whichinclude chromatin-modifying enzymes (Bonasio et al., 2010),determines the type of hPTMs that ultimately either inactivate orstimulate transcriptional activity. Identifying CREs and correlatingtheir differential activity with the differential expression of the genesthey regulate in a given tissue between migrants and non-migrantswould be a powerful approach to pinpoint important candidatemigratory genes and genomic regulatory elements. Of note, genomicvariation associated to variation in migratory phenotypes inpopulation genomic studies could occur in these open chromatinregions. DNase-seq, a method that identifies genome-widenucleosome-free DNA regions that are hypersensitive to DNase Idigestion (Song and Crawford, 2010), has been used extensively toidentify gene regulatory elements in open chromatin regions. Thelarge amount of starting material it requires may, however, be animportant limitation on its application to migratory species. ATAC-seq (assay for transposase-accessible chromatin followed bysequencing), a technique relying on the integration of a mutatedhyperactive transposase into open chromatin regions emerged as anattractive alternative as it requires 1000-times less starting materialthan DNase-seq (Fig. 3A) (Buenrostro et al., 2013, 2015). Theactivity status of CREs can be determined using chromatinimmunoprecipitation (ChIP) of flanking histone marks followed byhigh-throughput sequencing (Fig. 3A). These are conserved acrossorganisms, and antibodies against marks associated with active andpoised/inactive promoters and enhancers (Creyghton et al., 2010;Shlyueva et al., 2014; Heinz et al., 2015) are commercially available.DNA methylation is another gene regulatory mechanism by

which behavioural and physiological plasticity can be regulated(Lyko et al., 2010; Foret et al., 2012; Herb et al., 2012; Pegoraroet al., 2016). Reprogramming of gene expression and gene

regulatory networks between different migratory phenotypescould occur through changes in DNA methylation patterns, whichcan be studied using bisulfite-sequencing methods, even for specieswithout a reference genome (Klughammer et al., 2015). Theexistence of such a mechanism may, however, be taxa-, lineage- orspecies-specific. While genome-wide patterns of DNA methylationoccur broadly in vertebrates, including birds (Li et al., 2011; Laineet al., 2016), DNA methylation does not appear to be ubiquitous ininsects (Bewick et al., 2017). Some species such as monarchs seemto lack detectable patterns of de novoDNAmethylation (Zhan et al.,2011; Bewick et al., 2017).

Post-transcriptional regulation of gene expression by microRNA(miRNA), RNA editing and alternative splicing should also beconsidered as potential mechanisms by which steady state mRNAlevels could be differentially regulated between migratoryphenotypes and/or seasons. So far, with the notable exception ofdifferential expression of miRNAs in migratory and non-migratoryforms of the monarch butterfly (Zhan et al., 2011), to ourknowledge, none of these mechanisms has been studied in anyother migratory species. The current array of HTS approaches offersunprecedented opportunities to exploit all these possibilities, andshould accelerate the identification of genes, epigenetic and post-transcriptional mechanisms underlying the migratory phenotype.

Ultimately, providing proofs of causality will be imperative.Genetically manipulating identified candidate genes and regulatoryregions in vivo to assess how genetic disruption affects the migratoryphysiology and behaviour will undoubtedly be challenging, butshould be facilitated by increasingly accessible functional genomictools. Classical approaches that use RNA interference (RNAi) toknock genes down are possible ways to test gene function, but couldhave limited applications, as the gene knockdown is oftenincomplete. Unlike RNAi, targeted genome editing allows thegeneration of complete gene knockouts and the creation ofmutations in CREs that would render them non-functional. Theuse of RNA-guided nucleases derived from clustered regularlyinterspaced short palindromic repeats (CRISPR)/Cas9 system isarguably one of the most exciting avenues of investigation for thestudy of migration genetics because of its simplicity andapplicability to virtually any species of interest. CRISPR/Cas9enables site-specific genetic modifications by inducing DNAdouble-stranded breaks (DSBs) at genomic locations of choice.DSBs repair by the cellular machinery stimulates the introduction ofsmall random insertions/deletions through non-homologous endjoining (NHEJ) repair, or the introduction of donor constructsthrough homology-directed repair (Fig. 3B) (Gaj et al., 2013; Kimand Kim, 2014).

Thus far, CRISPR/Cas9 has been successfully applied to generatefull knockouts and deletion mutants in the migratory monarchbutterfly (Markert et al., 2016; Zhang et al., 2017), therebyunlocking its potential for the functional characterization ofmigratory candidate genes and CREs. Germline genome editingin this species has been achieved with high efficiency by injection ofCas9 mRNA and a single guide (sg)RNA into fertilized embryoswithin the first nuclei divisions (Fig. 3B) (Merlin et al., 2013;Markert et al., 2016). Similar strategies are commonly used inmodel species such as the zebrafish and mouse, in which embryoscan be collected at an early development stage, and should thereforebe transferable to other migratory species such as fish andmammals.In birds, efficient germline transformation has proved to be morechallenging due to constraints associated with the structure of thezygote and the opacity of the oocyte (Dimitrov et al., 2016).However, the use of CRISPR/Cas9-mediated modification of

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primordial germ cells in vitro has been shown to overcome thislimitation in chickens (Dimitrov et al., 2016; Oishi et al., 2016;Woodcock et al., 2017), making it a possible approach for geneediting in migratory bird species. In the event that breeding coloniesin laboratory conditions preclude the implementation of similarapproaches, strategies for genome editing in post-mitotic cells usingvirus-mediated delivery of CRISPR/Cas9 into the appropriatetissue/organ, depending on the presumptive function of the gene ofinterest, are attractive alternatives (Fig. 3B). Expanding genetictools in migratory species for knocking genes out both in the wholeorganism and in a tissue-specific manner, as well as for knocking inreporters that can be used to probe circuit function, will be importantmilestones for the field. Combined with diagnostic physiologicaland behaviour assays, genetically engineered migratory organismswill ultimately facilitate a systematic dissection of the molecular andcellular mechanisms underlying animal migration and orientation.

Looking forward: exploiting the diversity of migratoryspecies within and across taxa for comparative studiesThe identity of genes underlyingmigratory orientation and how theycode for this remarkable behaviour remains largely unknown.Applying cutting-edge HTS technologies and powerful behaviouralapproaches in the European blackcap and the North Americanmonarch butterfly hold great promise to identify and functionallyvalidate migratory genes and molecular pathways. However,restricting genetic and molecular approaches to only a few speciescan limit our ability to differentiate the molecular pathways that arespecies- or taxa-specific from those widely generalizable acrosstaxa. Exploiting a larger number of strategically chosen migratoryspecies for comparative studies across evolutionary scales and taxawill be key, and will be facilitated by the increasing accessibility ofgenomics and molecular tools in non-model organisms.Among other migratory insect species, the nocturnal Australian

bogong moth Agrotis infusa is an ideal complement to the diurnalmonarch butterfly for molecular comparative studies. Each spring,migratory moths leave the breeding grounds in southern Queenslandand northwestern New South Wales and migrate south to reach theAustralian Alps, where they aggregate to aestivate (i.e. spendthe summer in a state of dormancy) in cool mountain caves. In theautumn, the same individuals migrate back to the breeding sites toreproduce, and die soon after, leaving their progeny to become thenew generation of southward migrants the following spring(Fig. 4A) (Heinze and Warrant, 2016; Warrant et al., 2016). Theopposite flight orientations taken by bogongs and monarchs eachautumn and spring in different hemispheres of the Earth, whereseasons are reversed, may suggest that similar environmental cues(i.e. photoperiod and/or temperature changes) recalibrate compassorientation. Leveraging this parallel using genomic comparativeapproaches may accelerate the identification of a set of conservedmolecules and pathways underlying migratory orientation in insects.All the genomic tools mentioned previously, including CRISPR/Cas9 that has been implemented in other moth species (Koutroumpaet al., 2016; Chen et al., 2018), should be easily transferable to thebogong.Although the spectrum of migratory orientation is exceptionally

diverse in blackcaps, other bird species also exhibit differences inmigratory timing and direction. Two subspecies of willow warblerform amigratory divide in central Scandinavia, andWGS combinedwith SNP-chip data identified two chromosomal regions showingstrong genetic differentiation between subspecies associated withdifferences in migratory behaviour (Lundberg et al., 2017). TheSwainson’s thrush is another compelling model forming amigratory

divide in western North America, and hybrids in this system havebeen shown to take intermediate migratory routes (Delmore andIrwin, 2014). Variation in one genomic region linked to variation inmigratory behaviour was identified, which included the Clock gene(Delmore et al., 2016). However, the overall lack of consistencybetween identified regions and genes linked to migratory traitsacross species may call for caution in assuming one common andsimple genetic basis of migratory traits (Delmore and Liedvogel,2016). Performing comparative analyses of gene expression and ofthe activity of CREs present in the regions under selection indifferent bird systems could help determine whether the molecularpathways responsible for flight orientation in birds are conservedor not.

Increasing the number of vertebrate taxa to include fish andmammals will be equally important to unravel molecularmechanisms underlying vertebrate migration and orientationbehaviour. Mass seasonal migrations are also performed belowthe ocean surface by many fish species. Indirect evidence for agenetic basis of migratory orientation comes from a study onAtlantic eels. American (Anguilla rostrata) and European (Anguillaanguilla) eels both start their migratory journeys in the SargassoSea, but their migration differs in distance and direction. Americaneels migrate towards the coast of North America while Europeaneels take a longer route to Europe. Icelandic eels, which have beencharacterised as possible hybrids (Albert et al., 2006), migrate usingan intermediate orientation. The Salmonidae are another well-suitedfamily to study the underlying genetics of fish migration and itsspatiotemporal characteristics because of the high variability inmigratory life history strategies within and among species (Dodsonet al., 2013). In these species, the high variability in migratoryphenotype is not mirrored in overall genetic differentiation(O’Malley and Banks, 2007). Variation within the Clock gene hashowever been shown to match a cline in spawning time in theChinook salmon O. tshawytscha (O’Malley and Banks, 2008;O’Malley et al., 2010). The genetics of adult migration timing havebeen further characterized through genome-wide associationmapping of migratory (steelhead) populations exhibiting twodistinct timing strategies in the wild (Hess et al., 2016). Thisstudy identified a 46 kb region overlapping an oestrogen receptorcofactor GREB1, a relevant candidate gene since upstreammigration happens during sexual maturation in steelhead andother salmonids (Choi et al., 2014). The same gene has recentlybeen shown to have a major effect on adult migration timing in bothO. mykiss and O. tshawytscha (Prince et al., 2017).

Research in O. mykiss, a species with both resident (rainbow trout)andmigratory (steelhead) phenotypes, also identified several genomicregions associated with adaptations during smoltification, the processfacilitating transition in preparation for seaward migration (Fig. 4B)(Nichols et al., 2008; Hecht et al., 2012; Hale et al., 2013). Epigeneticregulation of gene expression may contribute to controlling variationin migratory behaviour during the smoltification process, asdifferentially DNA methylated sites were found to distinguishmigratory from resident lines, including in regions associated withcircadian rhythm pathways (Baerwald et al., 2016). Correlatingdifferential DNA methylation to differential gene expression inmigratory versus resident forms ofO.mykiss could be used to identifypromising candidate genes underlying fish migration.

Bats living in temperate climate also embark on massive seasonalmigrations with navigational abilities that are no less impressivethan those of birds, insects and fish. Two examples of migratory batswith untapped potential for comparative genomics and molecularstudies are the lesser long-nosed bat Leptonycteris yerbabuenae,

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and the Mexican free-tailed bat Tadarida brasiliensis. These bats,which are found in the southwestern United States and northernMexico in the summer, migrate southward in the autumn to theirrespective overwintering sites in central or southernMexico. Matingoccurs in the early spring and pregnant females migrate north to givebirth in maternity roosts before returning in the autumn, along withtheir progeny, to central Mexico (Fig. 4C) (Cockrum, 1967;Wilkinson and Fleming, 1996). Variation in migratory tendency(migratory versus residents) has also been reported in T. brasiliensispopulations (Cockrum, 1967). Both the seasonal change inmigratory direction and the variation in migratory phenotypecould be exploited to uncover the molecular pathways underlyingbat migration and orientation. Initiatives to sequence the genome ofall bat species are underway (BAT 1K; http://www.bat1k.com).With blueprints in hand, applying cutting-edge genomic and

epigenomic tools in these species (from blood samples, wingpunches or even brain tissues in the case of the abundantT. brasiliensis) should take off.

Closing remarksThe cyclic, mostly seasonal, nature of many species migrations up inthe sky, on land and in the oceans has fascinated scientists and thepublic alike for decades. Its broad occurrence across the animalkingdom begs the question of whether common mechanisms ordifferent molecular toolkits underlie migratory strategies. Theinvolvement of genes associated with clock function in differenttaxa suggests that mechanisms timing the migration may use asimilar molecular pathway. In contrast, the key genomic regions andmolecular underpinnings responsible for variation in migratoryorientation remain largely unknown as the regions identified in

A

C

Australian bogong moth

500 km

Lesser long-nosed bat

Mexico

USA

Narrabri Adaminaby

500 km

Maternity roostsKnown routesSuspected routes

Spring

Autumn

B

1000 km

USA

Canada

Japan

North American steelhead

Rainbow trout

Fig. 4. Diversifying systems from different taxawill accelerate our understanding of the genetics and epigenetics of migration. (A) An Australian bogongmoth, Agrotis infusa, aestivating in a cool cave (top); photo credit: Ajay Narendra. Map shows the southward spring migration (orange arrow) and the northwardautumn remigration (grey arrow). Modified from Dreyer et al., 2018. (B) North American migratory steelhead (top) and resident rainbow (bottom) trout(Oncorhynchusmykiss) are the same species, although the appearance of both life-history patterns can differ as a function of the environment and food. Migratorysteelheads are an anadromous form of resident rainbow trout, migrating to sea and returning to their natal stream or river to spawn. The migratory pathwayof steelhead in their Pacific basins is depicted in red. Some steelhead populations continue to migrate inland after return. (C) Lesser long-nosed bats(Leptonycteris yerbabuenae) at the peak of the spring migration arriving in maternity roosts in the Sonoran desert; photo credit: Jens Rydell. Migratory cycleof L. yerbabuenae is shown on the right. These nectar-feeding bats, which are found in southern Arizona and northern Mexico in the summer, massively migratesouth in the autumn by presumably following Agave corridors to overwinter in central Mexico. In the spring, pregnant females migrate north along a corridor ofblooming columnar cacti on the western coast of Mexico and Baja California, where they give birth to their young in maternity caves.

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different species so far lack consistency and have not been validatedfunctionally. The answers are out there somewhere in the DNAsequences, and systematically implementing integrative approachesin a diverse array of species should accelerate the pace at which welearn where to look to unveil some of the molecular secrets behindmigratory behaviour.

AcknowledgementsWe thank Gernot Segelbacher, Krista Nichols, MonarchWatch, Ajay Narendra, JensRydell, and Melinda Baerwald for allowing use of their photos in Figs 1, 2 and 4;Andrew Clarke for generating the map in Fig. 4B; and Aldrin Lugena for commentson the manuscript.

Competing interestsThe authors declare no competing or financial interests.

Author contributionsC.M. and M.L. contributed equally to the writing of this manuscript.

FundingC.M. was supported by grants from the National Science Foundation (IOS-1456985and IOS-1754725) and the Esther A. and Joseph Klingenstein Fund; M.L. wassupported by the Max Planck Society (Max-Planck-Gesellschaft) through a MaxPlanck Research Group grant.

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