Genetic Control of Avian Migration: History
View Latest Version
Please note this is an old version of this entry, which may differ significantly from the current revision.
Subjects: Genetics & Heredity
Contributor:
Aakansha Sharma
,
Sayantan Sur
,
Vatsala Tripathi
,
Vinod Kumar

Twice-a-year, large-scale movement of billions of birds across latitudinal gradients is one of the most fascinating behavioral phenomena seen among animals. These seasonal voyages in autumn southwards and in spring northwards occur within a discrete time window and, as part of an overall annual itinerary, involve close interaction of the endogenous rhythm at several levels with prevailing photoperiod and temperature. The overall success of seasonal migrations thus depends on their close coupling with the other annual sub-cycles, namely those of the breeding, post-breeding recovery, molt and non-migratory periods. There are striking alterations in the daily behavior and physiology with the onset and end of the migratory period, as shown by the phase inversions in behavioral (a diurnal passerine bird becomes nocturnal and flies at night) and neural activities. Interestingly, there are also differences in the behavior, physiology and regulatory strategies between autumn and spring (vernal) migrations. Concurrent molecular changes occur in regulatory (brain) and metabolic (liver, flight muscle) tissues, as shown in the expression of genes particularly associated with 24 h timekeeping, fat accumulation and the overall metabolism.

  • bird
  • brain
  • gene expression
  • heritability
  • migration
  • seasonal

1. Introduction

Avian migration is a regular, seasonal, large-scale movement of a population between fixed breeding and wintering geographical locations [1]. Billions of birds undertake twice-a-year, migration journeys between breeding and wintering regions that, for many species, lie across the latitudinal gradient. These birds breeding in the northern hemisphere fly southwards in autumn to winter, and they begin their return flight northwards in spring to timely reach their homes (i.e., breeding ground). There are, however, species differences in the migratory distance and, perhaps because of the intraspecific competition, in the direction and location of winter grounds [2][3][4].
Three experimental approaches have been generally used to study the genetic control of migratory behavior in birds [5]. These approaches aim to examine if a migratory trait is genetically or environmentally determined, to predict the adaptability and evolution rate of a migratory trait using a quantitative genetic approach, and to identify specific genes or gene sets involved in controlling the expression of the migratory behavior. The first approach centers mainly around identifying the components of a migratory behavior having a genetic basis, and involves translocation, cross-fostering or cross-breeding experiments (for details, please see [6][7]). The second approach involves a number of quantitative genetic methods, e.g., the parent–offspring regression and full sibling correlations aimed at deciphering the adaptability and evolution of the migratory behavior trait [5]. The third and more recent approach focuses on the idea of the “migratory gene package” that controls migration-linked changes in the morphology, behavior and physiology [8].

2. Migration: A Heritable Seasonal Behavior

A successful migratory journey requires the occurrence of sequential changes at several levels with great precision. It is therefore important that a migratory trait has been genetically shaped and adapted to the external environment.

2.1. An Innate Migratory Template

Early in the 20th century, the experimental evidence came for an innate nature and inheritance of avian migratory behavior [9][10][11]. A more actual genetic basis of migration was published in the 1990s from a series of cross-breeding experiments of a non-migratory population (of Cape Verde Islands) with a migratory population (from southern Germany) of blackcaps (Sylvia atricapilla); ~40% of F1 hybrids were migratory [7][12]. Most interestingly, the migratory urge seemed genetically transmissible, and the urge could be further manipulated in magnitude by selective breeding experiments involving a partially migratory population [12]. All hybrids were migratory, suggesting that the migratory urge was determined by a multi-locus system having a reaction threshold in the face of environmental changes [7][12]. Further, common garden experiments on blackcaps have shown the genetic basis of both the distance [13] and direction of seasonal migrations [14].
There is also good evidence to show that a migrant can complete its migratory travel without guidance from experienced conspecifics, as concluded from a study on common cuckoos (Cuculus canorus). Satellite tracking of migrating cuckoos revealed that juveniles had initiated migratory travel later than the adults, and they traveled via a straighter and faster route to reach their African wintering grounds, perhaps as independently guided by their innate migration programs [15].

2.2. Heritable Migratory Activity Pattern

Both spatiotemporal migration program and migratory activity are heritable [7][12][16]. A study on parent–offspring regression and full sibling correlation as calculated from migratory activity of 280 southern German blackcaps from 69 families revealed that variability in the migratory behavior had come majorly from the genetic difference and with little, if any, contribution from the environment [17]. The pattern of migratory activity also in migratory garden warblers (Sylvia borin) was fairly insensitive to food availability or weather conditions, although a very long photoperiod could modify the amount of night activity [18][19][20]. Likewise, the migratory direction follows a dominant inheritance pattern, as shown by a genome-wide study on nearly identical two willow warbler (Phylloscopus trochilus) subspecies that have drastically different migratory routes. The subspecies P. t. trochilus migrates southwest from western European breeding to western African breeding grounds, while P. t. acredula migrates from southeast from northern and eastern Europe to eastern and southern Africa [21][22]. The single nucleotide polymorphisms (SNPs) of juveniles revealed that the hybrids of these two subspecies followed an intermediate route during the autumn migration [23]. Very recently, Sokolovskis et al. [24] discovered that the dominance to southwestern migratory direction in P. t. trochilus was associated with the trochilus allele at inversion polymorphisms on chromosomes 1 (InvP-Ch1), and to southeastern migratory direction in P. t. acredula was associated with migration associated repeat block (MARB-a); MARB-a seemed to have an epistatic suppressive effect on the InvP-Ch1 [24].

2.3. Heritable Arrival Dates

An important aspect of migration is the timing of arrival at the breeding site in order to have prior access to the prime breeding habitat and a better mate choice [25]. A decline in breeding success among late arrivals at breeding grounds has been documented for several migrant species [26][27][28][29][30][31]. Interestingly, this trait could also be heritable. Tarka et al. [32] studied the quantitative genetics of arrival dates at the breeding ground using data sets collected over 20 years (multigenerational pedigree) for both sexes of great reed warblers (Acrocephalus arundinaceus). There was 16.4% heritability for the arrival dates as well as directional selection for early arrivals in both sexes acting through the reproductive success [32].
Studies over the last three decades also suggest a correlation of rising mean spring temperature with the arrival date and hence the early start of reproduction [33]. Given the high heritability of the arrival dates [32], a strong response to climate change-induced selection (a micro-evolutionary change rather than the phenotypic response) can be expected [34]. Indeed, the results from Swedish data on spring arrival dates of migratory birds from the last 140 years suggest that an increased temperature possibly led to advanced spring arrival dates, and that the spring migration-linked phenologies have shown bigger changes in short-distance than those in the long-distance migrants [35].

3. Unraveling the Genetic Control of Migratory Behavior

3.1. Gene Polymorphism

A comparative study of gene polymorphism in an experimentally simulated (e.g., a reference experiment) or in naturally occurring (e.g., resident vs. migratory population) functional states can reveal the genetic basis of a trait, such as seasonal migration.
Using gene polymorphism as a molecular approach, few studies have documented the association of a single gene polymorphism with the migratory phenotype, while few others have failed to show such an association. For example, there was a significant correlation of Adcyap1 (adenylate cyclase activating polypeptide 1) gene polymorphism with the migratory restlessness in blackcaps; birds with longer Adcyap1 allele exhibited higher Zugunruhe [36]. A similar CLOCK (circadian locomotor output kaput) gene polymorphism was found associated with enroute stay (stopover) times (a longer CLOCK allele suggests delayed departure from Mediterranean island stopover sites) in trans-Saharan migratory common nightingales (Luscinia megarhynchos), European pied flycatchers (Ficedula hypoleuca), tree pipits (Anthus trivialis) and whinchats (Saxicola rubetra) [37][38]. At the same time, Peterson et al. [39] found no consistent association of Adcyap1 or CLOCK gene allele lengths with the migratory status in a study of 15 different populations across two subspecies of Junco ranging from sedentary to long-distance migrants. Notably, however, the long-distance migratory Juncos had longer CLOCK alleles on average and, similar to captive blackcaps, the Adcyap1 allele length showed a positive correlation with the migratory restlessness among individuals of one of the two Junco populations studied, indicating the association of Adcyap1 gene with migratory propensity within or between certain populations only [38]. The CLOCK gene polymorphism was also not associated with the migration phenotype in bar-tailed godwit (Limosa lapponica baueri) [40].
Similarly, a single nucleotide polymorphism of Vps13a (vacuolar protein sorting 13 homolog A) gene was found to be associated with migration directionality in two very closely genetically related Vermivora warbler species with similar breeding sites in North America and vastly different wintering sites in different geographical directions—golden-winged warbler (Vermivora chrysoptera) winters in Central America and blue-winged warbler (V. cyanoptera) winters in South America [41][42]. There was a reduced sequence variation in the Vps13a gene region among South America wintering warblers, indicating the likelihood of natural selection on this gene locus [43]. Likewise, a genome sequencing study of four different populations of peregrine falcons (Falco peregrinus) indicated the association of Adcy8 (adenylate cyclase 8) gene with population level differences in the migratory distance [44].
Notably, blackcaps have emerged as an experimental model system to study the genetics and epigenetics of migration [45]. To trace the evolutionary history of migration in blackcaps, for example, Delmore et al. [46] using high-throughput sequencing technologies sequenced the genome of 110 blackcaps from populations exhibiting differences in the autumn migration. Along with a revelation that the divergence began about 30,000 years ago, a small set of genes was found to code for differences in their migratory behavior. The genetic variations occurred in the regulatory region, not in gene sequence, suggesting the possibility for the occurrence of rapid changes in the migratory behavior [46]. A study on migratory American kestrels (Falco sparverius) further suggests this [47]. In kestrels that were captured during the autumn migration, the genetic variation in gene loci that modulate the internal biological clock (e.g., Top1, Phlpp1, Cpne4 and Peak1 genes) accounted for an intra-population existence of both early and late migratory chronotypes, supporting the argument that the variation in regulatory gene regions was responsible for the variation in migration phenotypes [47].

3.2. Gene Transcription

A migratory phenotype is expressed for a specific purpose and for a defined time period. Additionally, the two seasonal migrations (to-and-fro movement between breeding and wintering grounds) differ in several ways. For example, spring and autumn migrations differ in context: the spring travel is for the timely arrival at the breeding grounds (hence there is a stronger reproductive drive), whilst the autumn travel is essentially for escaping harsh winter conditions at breeding grounds and for finding adequate food resources for spending the winter season. This is reflected in the higher speed, longer nocturnal flights and shorter stopovers during spring than during the autumn migration [48][49][50]. Birds are also in different physiological states prior to the onset of the two migrations: they are sensitive to long-day photostimulation in spring and refractory to it in the autumn (Figure 1, [51]). Such differences in the phenotype are possibly the results of differential regulatory molecular strategies that can be deciphered by examining differences in the gene expression pattern between different seasonal states. However, studying the expression pattern using a candidate gene or global gene expression approach is challenging as it can vary significantly across the day and/or the year. It is, therefore, important that the samples for gene expression studies are collected at the same time of the day in different seasonal states. It is also desired to carry out gene expression assays using an appropriate tissue that answers a specific question (e.g., brain tissue for regulation, and liver and flight muscles for the metabolism), and to avoid cross-tissue comparisons.
Figure 1. Schematic illustration of annual life history of latitudinal obligate migratory buntings (Emberiza sp.). Panels (from left to right): Panel on the extreme left shows double plotted representative actograms of captive birds in non-migratory and migratory phenotypes. The white and gray shaded areas represent day and night time, respectively. Note that in non-migratory state, the birds remain active during the day (diurnal), while during migratory state, they become predominantly night active (nocturnal). The second panel lists change in body mass, fat deposition and hepatic neutral lipid accumulation as visualized by Oil Red O staining (magnification: ocular ×10, objective ×40) in different seasonal states. Note the lipid-laden liver cells during the spring migratory state. The next panel summarizes endocrine (hormonal) changes in different seasonal states. The extreme right panel shows a representative diagram of the hypothalamus showing Fos-like immunoreactive cells in the winter non-migratory and spring migratory states. Abbreviation: T4: thyroxine, T3: triiodothyronine, LH: Luteinizing hormone, DMH: dorsomedial hypothalamus, IH: inferior hypothalamic nucleus, IN: Infundibular nucleus, 3V: third ventricle. The figure has been drawn based on findings in several recent publications [52][53][54][55][56].

3.3. Global Gene Analyses

Migration is not a single component event; it is rather an outcome of several sequentially occurring component events, viz., the migratory urge, preparedness for the long journey, direction to fly, distance to cover and the mechanism to replenish energy during stopovers. Therefore, instead of a single or a set of genes, the genetic control for migration may involve an entire “migratory gene package”. The constituent genes of such a “gene package” must show differential expression possibly with varying degrees among its candidates during different stages of the migration. The study of such a proposition has become possible through recent technological advancements, such as the next-gen sequencing technique that allows for whole-genome or transcriptome sequencing.
Using the global gene approach, there have been attempts in the last ten years to identify the component genes of the “migratory gene package”. In a first study of the kind, using 454 pyrosequencing, Lundberg et al. [57] compared brain-derived transcriptomes of P. t. trochilus and P. t. acredula and found 55 highly differentiated SNPs between two subspecies clustering largely to two chromosome regions, possibly influenced by the divergent selection and adaptation to differential migratory strategies [57]. Similarly, Fudickar et al. [58] found 547 differentially expressed genes in peripheral tissues (blood and pectoral muscle) between migratory and sedentary populations of dark-eyed juncos (Junco hyemalis). There was an increased expression of genes associated with lipid transport and fatty acid catabolic processes in the muscle and with a ribosomal structure that indicated protein synthesis in the blood of the migratory J. h. hyemalis, as compared to those in the sedentary J. h. carolinensis [58].
Further studies focused on the differences in gene expressions in between seasonal states of the same species. Using microarrays, Boss et al. [59] reported substantial differences in the number of differentially expressed genes (DEGs, 13.8%), particularly enriching the calcium ion transport, neuronal firing and neuronal synapse formation pathways, in willow warblers’ brains between breeding and autumn migration periods [59]. Similarly, using RNASeq of the ventral hypothalamus region, Johnston et al. [60] reported a higher expression of genes involved in focal adhesion, proliferation and motility in migratory than in the non-migratory state in captive Swainson’s thrushes (Catharus ustulatus). On the other hand, Franchini et al. [61] reported only four differentially expressed genes linked with the hyperphagia, moulting and enhanced DNA replication in the blood transcriptome of partial migratory European blackbirds (Turdus merula).

This entry is adapted from the peer-reviewed paper 10.3390/genes14061191

References

  1. Lack, D. Bird migration and natural selection. Oikos 1968, 19, 1–9.
  2. Salomonsen, F. The evolutionary significance of bird migration. Dan. Biol. Medd. 1955, 22, 1–62.
  3. Alerstam, T. Bird Migration; Cambridge University Press: Cambridge, UK, 1991.
  4. Berthold, P. Control of Bird Migration; Chapman and Hall: London, UK, 1996.
  5. Pulido, F.; Berthold, P. Quantitative genetic analysis of migratory behavior. In Avian Migration; Berthold, P., Gwinner, E., Sonnenschein, E., Eds.; Springer: Berlin/Heidelberg, Germany, 2003; pp. 53–77.
  6. Harris, M.P. Abnormal migration and hybridization of Larus argentatus and L. fuscus after fostering experiments. Ibis 1969, 112, 488–498.
  7. Berthold, P.; Wiltschko, W.; Miltenberger, H.; Querner, U. Genetic transmission of migratory behavior into a nonmigratory bird population. Experientia 1990, 46, 107–108.
  8. Liedvogel, M.; Akesson, S.; Bensch, S. The genetics of migration on the move. Trends Ecol. Evol. 2011, 26, 561–569.
  9. Valikangas, I. Finnische Zugvogel aus englischen Vogeleiern. Vogelzug 1933, 4, 159–166.
  10. Nice, M.M. Zur Naturgeschichte des Singammers. J. Ornithol. 1934, 82, 1–96.
  11. Nice, M.M. Studies in the life history of the song sparrow. Vol I A population study of the song sparrow. Trans. Linn. Soc. N. Y. 1937, 4–6, 1–247.
  12. Berthold, P. Genetic control of migratory behavior in birds. Trends Ecol. Evol. 1991, 6, 254–257.
  13. Berthold, P.; Querner, U. Genetic basis of migratory behavior in European warblers. Science 1981, 212, 77–79.
  14. Berthold, P.; Helbig, A.J.; Mohr, G.; Querner, U. Rapid microevolution of migratory behaviour in a wild bird species. Nature 1992, 360, 668–670.
  15. Vega, M.L.; Willemoes, M.; Thomson, R.L.; Tolvanen, J.; Rutila, J.; Samaš, P.; Strandberg, R.; Grim, T.; Fossøy, F.; Stokke, B.G.; et al. First-time migration in juvenile common cuckoos documented by satellite tracking. PLoS ONE 2016, 11, e0168940.
  16. Berthold, P.; Helbig, A.J. The genetics of bird migration: Stimulus, timing, and direction. Ibis 1992, 134 (Suppl. S1), 35–40.
  17. Berthold, P.; Pulido, F. Heritability of migratory activity in a natural bird population. Proc. R. Soc. Lond. B 1994, 257, 311–315.
  18. Berthold, P. Endogenous component of annual cycles of migration and moult. In Acta XVIII Congressus Internationalis Ornithologici; Ilyichev, V.D., Gavrilov, V.M., Eds.; Nauka: Moscow, Ruassia, 1985; pp. 922–929.
  19. Gwinner, E. Circadian and circannual programmes in avian migration. J. Exp. Biol. 1996, 199, 39–48.
  20. Berthold, P.; Gwinner, E.; Klein, H.; Westrich, P. Beziehungen zwischen Zugunruhe und Zugablauf bei Garten und Monchsgrasmucke (Sylvia borin und S. atricapilla). Z. Tierpsychol. 1972, 30, 26–35.
  21. Hedenström, A. Migration routes and wintering areas of willow warblers Phylloscopus trochilus (L.) ringed in Fennoscandia. Ornis Fenn. 1987, 64, 137.
  22. Lerche-Jørgensen, M.; Willemoes, M.; Tøttrup, A.P.; Snell, K.R.; Thorup, K. No apparent gain from continuing migration for more than 3000 kilometres: Willow warblers breeding in Denmark winter across the entire northern Savannah as revealed by geolocators. Mov. Ecol. 2017, 5, 17.
  23. Zhao, T.; Ilieva, M.; Larson, K.; Lundberg, M.; Neto, J.M.; Sokolovskis, K.; Åkesson, S.; Bensch, S. Autumn migration direction of juvenile willow warblers (Phylloscopus t. trochilus and P. t. acredula) and their hybrids assessed by qPCR SNP genotyping. Mov. Ecol. 2020, 8, 22.
  24. Sokolovskis, K.; Lundberg, M.; Åkesson, S.; Willemoes, M.; Zhao, T.; Caballero-Lopez, V.; Bensch, S. Migration direction in a songbird explained by two loci. Nat. Comm. 2023, 14, 165.
  25. Morrison, C.A.; Alves, J.A.; Gunnarsson, T.G.; Porisson, B.; Gill, J.A. Why do earlier arriving migratory birds have better breeding success? Ecol. Evol. 2019, 9, 8856–8864.
  26. Aebischer, A.; Perrin, N.; Krieg, M.; Studer, J.; Meyer, D.R. The role of territory choice, mate choice and arrival date on breeding success in the Savi’s Warbler, Locustella luscinioides. J. Avian Biol. 1996, 27, 143–152.
  27. Currie, D.; Thompson, D.; Burke, T. Patterns of territory settlement and consequences for breeding success in the northern wheatear Oenanthe oenanthe. Ibis 2000, 142, 389–398.
  28. McKellar, A.E.; Marra, P.P.; Ratcliffe, L.M. Starting over: Experimental effects of breeding delay on reproductive success in early-arriving male American redstarts. J. Avian Biol. 2013, 44, 495–503.
  29. Norris, D.R.; Marra, P.P.; Kyser, T.K.; Sherry, T.W.; Ratcliffe, L.M. Tropical winter habitat limits reproductive success on the temperate breeding grounds in a migratory bird. Proc. Royal Soc. B Biol. Sci. 2004, 271, 59–64.
  30. Rockwell, S.M.; Bocetti, C.I.; Marra, P.P. Carry-over effects of winter climate on spring arrival date and reproductive success in an endangered migratory bird, Kirtland’s Warbler (Setophaga kirtlandii). Auk 2012, 129, 744–752.
  31. Velmala, W.; Helle, S.; Ahola, M.P.; Klaassen, M.; Lehikoinen, E.; Rainio, K.; Sirkia, P.M.; Laaksonen, T. Natural selection for earlier male arrival to breeding grounds through direct and indirect effects in a migratory songbird. Ecol. Evol. 2015, 5, 1205–1213.
  32. Tarka, M.; Hansson, B.; Hasselquist, D. Selection and evolutionary potential of spring arrival phenology in males and females of a migratory songbird. J. Evol. Biol. 2015, 28, 1024–1038.
  33. Bowers, E.K.; Grindstaff, J.L.; Soukup, S.S.; Drilling, N.E.; Eckerle, K.P.; Sakaluk, S.K.; Thompson, C.F. Spring temperatures influence selection on breeding date and the potential for phenological mismatch in a migratory bird. Ecology 2016, 97, 2880–2891.
  34. Visser, M.E.; Gienapp, P.; Husby, A.; Morrisey, M.; de la Hera, I.; Pulido, F.; Both, C. Effects of spring temperatures on the strength of selection on timing of reproduction in a long-distance migratory bird. PLoS Biol. 2015, 13, e1002120.
  35. Kullberg, C.; Fransson, T.; Hedlund, J.; Jonzén, N.; Langvall, O.; Nilsson, J.; Bolmgren, K. Change in spring arrival of migratory birds under an era of climate change, Swedish data from the last 140 years. Ambio 2015, 44 (Suppl. S1), S69–S77.
  36. Mueller, J.C.; Pulido, F.; Kempenaers, B. Identification of a gene associated with avian migratory behavior. Proc. R. Soc. B 2011, 278, 2848–2856.
  37. Bazzi, G.; Ambrosini, R.; Caprioli, M.; Costanzo, A.; Liechti, F.; Gatti, E.; Gianfranceschi, L.; Podofillini, S.; Romano, A.; Romano, M.; et al. Clock gene polymorphism and scheduling of migration: A geolocator study of the barn swallow Hirundo rustica. Sci. Rep. 2015, 5, 12443.
  38. Saino, N.; Bazzi, G.; Gatti, E.; Caprioli, M.; Cecere, J.G.; Possenti, C.D.; Galimberti, A.; Orioli, V.; Bani, L.; Rubolini, D.; et al. Polymorphism at the Clock gene predicts phenology of long-distance migration in birds. Mol. Ecol. 2015, 24, 1758–1773.
  39. Peterson, M.P.; Abolins-Abols, M.; Atwell, J.W.; Rice, R.J.; Milá, B.; Ketterson, E.D. Variation in candidate genes CLOCK and ADCYPA1 does not consistently predict differences in migratory behaviour in the songbird genus Junco. F1000 Res. 2013, 2, 115.
  40. Parody-Merino, Á.M.; Battley, P.F.; Conklin, J.R.; Fidler, A.E. No evidence for an association between Clock gene allelic variation and migration timing in a long-distance migratory shorebird (Limosa lapponica baueri). Oecologia 2019, 191, 843–859.
  41. Kramer, G.R.; Streby, H.M.; Peterson, S.M.; Lehman, J.A.; Buehler, D.A.; Wood, P.B.; McNeil, D.J.; Larkin, J.L.; Andersen, D.E. Nonbreeding isolation and population-specific migration patterns among three populations of Golden-winged Warblers. Condor Ornithol. Appl. 2017, 119, 108–121.
  42. Kramer, G.R.; Andersen, D.E.; Buehler, D.A.; Wood, P.B.; Peterson, S.M.; Lehman, J.A.; Aldinger, K.R.; Bulluck, L.P.; Harding, S.; Jones, J.A.; et al. Population trends in Vermivora warblers are linked to strong migratory connectivity. Proc. Natl. Acad. Sci. USA 2018, 115, E3192–E3200.
  43. Toews, D.P.L.; Taylor, S.A.; Streby, H.M.; Kramer, G.R.; Lovette, I.J. Selection on VPS13A linked to migration in a songbird. Proc. Nat. Acad. Sci. USA 2019, 116, 18272–18274.
  44. Gu, Z.; Pan, S.; Lin, Z.; Hu, L.; Dai, X.; Chang, J.; Xue, Y.; Su, H.; Long, J.; Sun, M.; et al. Climate-driven flyway changes and memory-based long-distance migration. Nature 2021, 591, 259–264.
  45. Merlin, C.; Liedvogel, M. The genetics and epigenetics of animal migration and orientation: Birds, butterflies and beyond. J. Exp. Biol. 2019, 222 (Suppl. S1), jeb191890.
  46. Delmore, K.; Illera, J.C.; Pérez-Tris, J.; Segelbacher, G.; Ramos, J.S.L.; Durieux, G.; Ishigohoka, J.; Liedvogel, M. The evolutionary history and genomics of European blackcap migration. eLife 2020, 9, e54462.
  47. Bossu, C.M.; Heath, J.A.; Kaltenecker, G.S.; Helm, B.; Ruegg, K.C. Clock linked genes underlie seasonal migratory timing in a diurnal raptor. Proc. R. Soc. B 2022, 289, 20212507.
  48. Newton, I. The Migration Ecology of Birds; Academic Press: London, UK, 2007.
  49. Tryjanowski, P.; Yosef, R. Differences between the spring and autumn migration of the red-backed shrike Lanius collurio: Record from the Eilat Stopover (Israel). Acta Ornithol. 2002, 37, 85–90.
  50. Nilsson, C.; Klaassen, R.H.G.; Alerstam, T. Differences in speed and duration of bird migration between spring and autumn. Am. Nat. 2013, 181, 837–845.
  51. Cornelius, J.M.; Boswell, T.; Eiermann, S.J.; Breuner, C.W.; Ramenofsky, M. Contribution of endocrinology to the migration life history of birds. Gen. Comp. Endocrinol. 2013, 190, 47–60.
  52. Sharma, A.; Singh, D.; Malik, S.; Gupta, N.J.; Rani, S.; Kumar, V. Difference in control between spring and autumn migration in birds: Insight from seasonal changes in hypothalamic gene expression in captive buntings. Proc. R. Soc. B 2018, 285, 1531.
  53. Sharma, A.; Kumar, V. Metabolic plasticity mediates differential responses to spring and autumn migrations: Evidence from gene expression patterns in migratory buntings. Exp. Physiol. 2019, 104, 1841–1857.
  54. Rastogi, A.; Kumari, Y.; Rani, S.; Kumar, V. Neural correlates of migration: Activation of hypothalamic clock(s) in and out of migratory state in the blackheaded bunting (Emberiza melanocephala). PLoS ONE 2013, 8, e70065.
  55. Jain, N.; Kumar, V. Changes in food intake, body weight, gonads and plasma concentrations of thyroxine, luteinizing hormone and testosterone in captive male buntings exposed to natural daylengths at 29° N. J. Biosci. 1995, 20, 417–426.
  56. Mishra, I.; Singh, D.; Kumar, V. Daily levels and rhythm in circulating corticosterone and insulin are altered with photostimulated seasonal states in night-migratory blackheaded buntings. Horm. Behav. 2018, 94, 114–123.
  57. Lundberg, M.; Boss, J.; Canbäck, B.; Liedvogel, M.; Larson, K.W.; Grahn, M.; Akesson, S.; Bensch, S.; Wright, A. Characterisation of a transcriptome to find sequence differences between two differentially migrating subspecies of the willow warbler Phylloscopus trochilus. BMC Genom. 2013, 14, 330.
  58. Fudickar, A.M.; Peterson, M.P.; Greives, T.J.; Atwell, J.W.; Bridge, E.S.; Ketterson, E.D. Differential gene expression in seasonal sympatry: Mechanisms involved in diverging life histories. Biol. Lett. 2016, 12, 20160069.
  59. Boss, J.; Liedvogel, M.; Lundberg, M.; Olsson, P.; Reischke, N.; Naurin, S.; Akesson, S.; Hasselquist, D.; Wright, A.; Grahn, M.; et al. Gene expression in the brain of a migratory songbird during breeding and migration. Mov. Ecol. 2016, 4, 4.
  60. Johnston, R.A.; Paxton, K.L.; Moore, F.R.; Wayne, R.K.; Smith, T.B. Seasonal gene expression in a migratory songbird. Mol. Ecol. 2016, 25, 5680–5691.
  61. Franchini, P.; Irisarri, I.; Fudickar, A.; Schmidt, A.; Meyer, A.; Wikelski, M.; Partecke, J. Animal tracking meets migration genomics: Transcriptomic analysis of a partially migratory bird species. Mol. Ecol. 2017, 26, 3204–3216.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
This entry is offline, you can click here to edit this entry!
ScholarVision Creations
Feedback