Selection and hybridization shaped the rapid spread of African honey bee ancestry in the Americas
Autoři:
Erin Calfee aff001; Marcelo Nicolás Agra aff002; María Alejandra Palacio aff002; Santiago R. Ramírez aff001; Graham Coop aff001; Marcelo Nicolás Agra aff003; María Alejandra Palacio aff003
Působiště autorů:
Center for Population Biology, University of California, Davis, California, United States of America
aff001; Department of Evolution and Ecology and Center for Population Biology, University of California, Davis
aff001; Department of Evolution and Ecology, University of California, Davis, California, United States of America
aff002; Instituto Nacional de Tecnología Agropecuaria (INTA), Balcarce, Argentina
aff002; Instituto Nacional de Tecnología Agropecuaria (INTA), Balcarce, Argentina
aff003; Facultad de Ciencias Agrarias, Universidad de Mar del Plata, Balcarce, Argentina
aff004
Vyšlo v časopise:
Selection and hybridization shaped the rapid spread of African honey bee ancestry in the Americas. PLoS Genet 16(10): e32767. doi:10.1371/journal.pgen.1009038
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1009038
Souhrn
Recent biological invasions offer ‘natural’ laboratories to understand the genetics and ecology of adaptation, hybridization, and range limits. One of the most impressive and well-documented biological invasions of the 20th century began in 1957 when Apis mellifera scutellata honey bees swarmed out of managed experimental colonies in Brazil. This newly-imported subspecies, native to southern and eastern Africa, both hybridized with and out-competed previously-introduced European honey bee subspecies. Populations of scutellata-European hybrid honey bees rapidly expanded and spread across much of the Americas in less than 50 years. We use broad geographic sampling and whole genome sequencing of over 300 bees to map the distribution of scutellata ancestry where the northern and southern invasions have presently stalled, forming replicated hybrid zones with European bee populations in California and Argentina. California is much farther from Brazil, yet these hybrid zones occur at very similar latitudes, consistent with the invasion having reached a climate barrier. At these range limits, we observe genome-wide clines for scutellata ancestry, and parallel clines for wing length that span hundreds of kilometers, supporting a smooth transition from climates favoring scutellata-European hybrid bees to climates where they cannot survive winter. We find no large effect loci maintaining exceptionally steep ancestry transitions. Instead, we find most individual loci have concordant ancestry clines across South America, with a build-up of somewhat steeper clines in regions of the genome with low recombination rates, consistent with many loci of small effect contributing to climate-associated fitness trade-offs. Additionally, we find no substantial reductions in genetic diversity associated with rapid expansions nor complete dropout of scutellata ancestry at any individual loci on either continent, which suggests that the competitive fitness advantage of scutellata ancestry at lower latitudes has a polygenic basis and that scutellata-European hybrid bees maintained large population sizes during their invasion. To test for parallel selection across continents, we develop a null model that accounts for drift in ancestry frequencies during the rapid expansion. We identify several peaks within a larger genomic region where selection has pushed scutellata ancestry to high frequency hundreds of kilometers past the present cline centers in both North and South America and that may underlie high-fitness traits driving the invasion.
Klíčová slova:
Bees – Europe – Genetic loci – Honey bees – Invertebrate genomics – Latitude – Single nucleotide polymorphisms – South America
Zdroje
1. Teeter KC, Payseur BA, Harris LW, Bakewell MA, Thibodeau LM, O’Brien JE, et al. Genome-wide patterns of gene flow across a house mouse hybrid zone. Genome Research. 2008;18(1):67–76. doi: 10.1101/gr.6757907 18025268
2. Tavares H, Whibley A, Field DL, Bradley D, Couchman M, Copsey L, et al. Selection and gene flow shape genomic islands that control floral guides. Proceedings of the National Academy of Sciences USA. 2018;5:201801832.
3. Powell DL, García-Olazábal M, Keegan M, Reilly P, Du K, Díaz-Loyo AP, et al. Natural hybridization reveals incompatible alleles that cause melanoma in swordtail fish. Science. 2020;368(6492):731–736. doi: 10.1126/science.aba5216 32409469
4. Hodgson JA, Pickrell JK, Pearson LN, Quillen EE, Prista A, Rocha J, et al. Natural selection for the Duffy-null allele in the recently admixed people of Madagascar. Proceedings Biological sciences. 2014;281:20140930. doi: 10.1098/rspb.2014.0930 24990677
5. Hufford MB, Lubinksy P, Pyhäjärvi T, Devengenzo MT, Ellstrand NC, Ross-Ibarra J. The genomic signature of crop-wild introgression in maize. PLoS Genetics. 2013;9(5):e1003477. doi: 10.1371/journal.pgen.1003477
6. Fitzpatrick BM, Johnson JR, Kump DK, Smith JJ, Voss SR, Shaffer HB. Rapid spread of invasive genes into a threatened native species. Proceedings of the National Academy of Sciences USA. 2010;107(8):3606–3610. doi: 10.1073/pnas.0911802107
7. Bay RA, Taylor EB, Schluter D. Parallel introgression and selection on introduced alleles in a native species. Molecular Ecology. 2019;28(11):2802–2813.
8. Cridland JM, Tsutsui ND, Ramírez SR. The complex demographic history and evolutionary origin of the western honey bee, Apis mellifera. Genome Biology and Evolution. 2017;9(2):457–472. doi: 10.1093/gbe/evx009
9. Moritz RFA, Härtel S, Neumann P. Global invasions of the western honeybee (Apis mellifera) and the consequences for biodiversity. Écoscience. 2016;12(3):289–301.
10. Crane E. The world history of beekeeping and honey hunting. New York, NY: Routledge; 1999.
11. Levine JM. Biological invasions. Current biology: CB. 2008;18(2):R57–60. doi: 10.1016/j.cub.2007.11.030
12. Winston ML. The biology and management of Africanized honey bees. Annual Review of Entomology. 1992;37:173–193. doi: 10.1146/annurev.en.37.010192.001133
13. Stort AC. Genetic Study of Aggressiveness of two Subspecies of Apis Mellifera in Brazil 1. Some Tests to Measure Aggressiveness. Journal of Apicultural Research. 1974;13(1):33–38. doi: 10.1080/00218839.1974.11099756
14. Collins AM, Rinderer TE, Harbo JR, Bolten AB. Colony Defense by Africanized and European Honey Bees. Science. 1982;218(4567):72–74. doi: 10.1126/science.218.4567.72
15. Hunt GJ, Guzman-Novoa E, Fondrk MK, Page RE. Quantitative trait loci for honey bee stinging behavior and body size. Genetics. 1998;148(3):1203–1213.
16. Winston ML. Killer bees. The Africanized honey bee in the Americas. Cambridge, MA: Harvard University Press; 1992.
17. Roell A, Whitehead H, Van Wyk J. Why the term Africanized bees is problematic in a racist society; 2020. Figshare. Available from: https://doi.org/10.6084/m9.figshare.12735452.v1.
18. Tsing AL. Empowering nature, or: some gleanings in bee culture. In: Yanagisako S, Delaney C, editors. Naturalizing Power. New York, NY: Routledge; 1995. p. 113–143.
19. Ksiazek P. Africanized honey bees; 2007. Press release, Zak Gallery.
20. Schumacher MJ, Egen NB. Significance of Africanized Bees for Public Health: A Review. Archives of Internal Medicine. 1995;155(19):2038–2043. doi: 10.1001/archinte.1995.00430190022003
21. Woyke J. Experiences with Apis mellifera adansonii in Brazil and in Poland. Apiacta. 1973;.
22. Villa JD, Koeniger N, Rinderer TE. Overwintering of Africanized, European, and hybrid honey bees in Germany. Environmental Entomology. 1991;20(1):39–43. doi: 10.1093/ee/20.1.39
23. Taylor OR Jr, Spivak M. Climatic limits of tropical African honeybees in the Americas. Bee World. 1984;65(1):38–47. doi: 10.1080/0005772X.1984.11098769
24. Harrison JF, Fewell JH, Anderson KE, Loper GM. Environmental physiology of the invasion of the Americas by Africanized honeybees. Integrative and Comparative Biology. 2006;46(6):1110–1122. doi: 10.1093/icb/icl046
25. Southwick EE, Roubik DW, Williams JM. Comparative energy balance in groups of Africanized and European honey bees: ecological implications. Comparative Biochemistry and Physiology. 1990;97(1):1–7. doi: 10.1016/0300-9629(90)90713-3
26. Sheppard WS, Rinderer TE, Mazzoli JA, Stelzer JA, Shimanuki H. Gene flow between African- and European-derived honey bee populations in Argentina. Nature. 1991;349(6312):782–784. doi: 10.1038/349782a0
27. Agra MN, Conte CA, Corva PM, Cladera JL, Lanzavecchia SB, Palacio MA. Molecular characterization of Apis mellifera colonies from Argentina: genotypic admixture associated with ecoclimatic regions and apicultural activities. Entomologia Experimentalis et Applicata. 2018;166(9):724–738. doi: 10.1111/eea.12719
28. Pinto MA, Rubink WL, Patton JC, Coulson RN, Johnston JS. Africanization in the United States: replacement of feral European honeybees (Apis mellifera L.) by an African hybrid swarm. Genetics. 2005;170(4):1653–1665. doi: 10.1534/genetics.104.035030
29. Loper GM, Fewell J, Smith DR, Sheppard WS, Schiff N. Changes in the genetics of a population of feral honey bees (Apis mellifera L.) in S. Arizona after the impact of tracheal mites (Acarapis woodi), Varroa mites (Varroa jacobsoni) and Africanization. In: Hoopingarner R, Connor L, editors. Apiculture for the 21st Century. Cheshire, CT: Wicwas; 1999. p. 47–51.
30. Kono Y, Kohn JR. Range and frequency of Africanized honey bees in California (USA). PLoS ONE. 2015;10(9):e0137407. doi: 10.1371/journal.pone.0137407
31. Lin W, McBroome J, Rehman M, Johnson BR. Africanized bees extend their distribution in California. PLoS ONE. 2018;13(1):e0190604. doi: 10.1371/journal.pone.0190604
32. Kadri SM, Harpur BA, Orsi RO, Zayed A. A variant reference data set for the Africanized honeybee, Apis mellifera. Scientific Data. 2016;3:160097. doi: 10.1038/sdata.2016.97
33. Wallberg A, Han F, Wellhagen G, Dahle B, Kawata M, Haddad N, et al. A worldwide survey of genome sequence variation provides insight into the evolutionary history of the honeybee Apis mellifera. Nature Genetics. 2014;46(10):1081–1088. doi: 10.1038/ng.3077 25151355
34. Cridland JM, Ramírez SR, Dean CA, Sciligo A, Tsutsui ND. Genome sequencing of museum specimens reveals rapid changes in the genetic composition of honey bees in California. Genome Biology and Evolution. 2018;10(2):458–472. doi: 10.1093/gbe/evy007
35. Whitfield CW, Behura SK, Berlocher SH, Clark AG, Johnston JS, Sheppard WS, et al. Thrice out of Africa: ancient and recent expansions of the honey bee, Apis mellifera. Science. 2006;314(5799):642–645. doi: 10.1126/science.1132772 17068261
36. Bozek K, Rangel J, Arora J, Tin M, Crotteau E, Loper G, et al. Parallel genomic evolution of parasite tolerance in wild honey bee populations. bioRxiv. 2018.
37. Nelson RM, Wallberg A, Simões ZLP, Lawson DJ, Webster MT. Genome-wide analysis of admixture and adaptation in the Africanized honeybee. Molecular Ecology. 2017;26:3603–3617.
38. Ruttner F. Honeybees of Tropical Africa. In: Biogeography and Taxonomy of Honeybees. Berlin: Springer; 1988. p. 199–227.
39. Schneider SS, DeGrandi-Hoffman G, Smith DR. The African honey bee: Factors contributing to a successful biological invasion. Annual Review Entomology. 2004;49(1):351–376. doi: 10.1146/annurev.ento.49.061802.123359
40. Danka RG, Rinderer TE, Hellmich RL, Collins AM. Comparative toxicities of four topically applied insecticides to Africanized and European honey bees (Hymenoptera: Apidae). Journal of Economic Entomology. 1986;79(1):18–21. doi: 10.1093/jee/79.1.18
41. Guzman-Novoa E, Vandame R, Arechavaleta ME. Susceptibility of European and Africanized honey bees (Apis mellifera L.) to Varroa jacobsoni Oud. in Mexico. Apidologie. 1999;30(2-3):173–182. doi: 10.1051/apido:19990207
42. Vandame R, Morand S, Colin ME, Belzunces LP. Parasitism in the social bee Apis mellifera: quantifying costs and benefits of behavioral resistance to Varroa destructor mites. Apidologie. 2002;33(5):433–445. doi: 10.1051/apido:2002025
43. Guerra J, Goncalves LS, De Jong D. Africanized honey bees (Apis mellifera L.) are more efficient at removing worker brood artificially infested with the parasitic mite Varroa jacobsoni Oudemans than are Italian bees or Italian/Africanized hybrids. Genetics and Molecular Biology. 2000;23(1):89–92. doi: 10.1590/S1415-47572000000100016
44. Moretto G, de Mello LJ. Varroa jacobsoni infestation of adult Africanized and Italian honey bees (Apis mellifera) in mixed colonies in Brazil. Genetics and Molecular Biology. 1999;22(3):321–323. doi: 10.1590/S1415-47571999000300006
45. Medina-Flores CA, Guzman-Novoa E, Hamiduzzaman MM, Aréchiga-Flores CF, López-Carlos MA. Africanized honey bees (Apis mellifera) have low infestation levels of the mite Varroa destructor in different ecological regions in Mexico. Genetics and Molecular Research. 2014;13(3):7282–7293. doi: 10.4238/2014.February.21.10
46. Daly HV, Balling SS. Identification of Africanized honeybees in the Western Hemisphere by discriminant analysis. Journal of the Kansas Entomological Society. 1978;.
47. Danka RG, Hellmich RL, Rinderer TE, Collins AM. Diet-selection ecology of tropically and temperately adapted honey-bees. Animal Behaviour. 1987;35(6):1858–1863. doi: 10.1016/S0003-3472(87)80078-7
48. Fewell JH, Bertram SM. Evidence for genetic variation in worker task performance by African and European honey bees. Behavioral Ecology and Sociobiology. 2002;52(4):318–325. doi: 10.1007/s00265-002-0501-3
49. Rivera-Marchand B, Oskay D, Giray T. Gentle Africanized bees on an oceanic island. Evolutionary applications. 2012;5(7):746–756. doi: 10.1111/j.1752-4571.2012.00252.x
50. Avalos A, Pan H, Li C, Acevedo-Gonzalez JP, Rendon G, Fields CJ, et al. A soft selective sweep during rapid evolution of gentle behaviour in an Africanized honeybee. Nature Communications. 2017;8(1):351. doi: 10.1038/s41467-017-01800-0
51. Winston ML, Otis GW, Taylor OR Jr. Absconding Behaviour of the Africanized Honeybee in South America. Journal of Apicultural Research. 1979;18(2):85–94. doi: 10.1080/00218839.1979.11099951
52. Skotte L, Korneliussen TS, Albrechtsen A. Estimating individual admixture proportions from next generation sequencing data. Genetics. 2013;195(3):693–702. doi: 10.1534/genetics.113.154138
53. Corbett-Detig R, Nielsen R. A Hidden Markov Model Approach for Simultaneously Estimating Local Ancestry and Admixture Time Using Next Generation Sequence Data in Samples of Arbitrary Ploidy. PLoS Genetics. 2017;13(1):e1006529. doi: 10.1371/journal.pgen.1006529
54. Kent RB. The introduction and diffusion of the African honeybee in South America. Yearbook of the Association of Pacific Coast Geographers. 1988;50(1):21–43. doi: 10.1353/pcg.1988.0009
55. USDA Agricultural Research Service. Spread of Africanized honey bees by year, by county; 2009. Available from: https://www.ars.usda.gov/ARSUserFiles/20220500/New%20Bee%20Map09%20compressed.jpg.
56. Becker R, Wilks A. Constructing a Geographical Database. AT&T Bell Laboratories Statistics Research Report. 1995;95.2.
57. R Core Team. R: A Language and Environment for Statistical Computing; 2019. Available from: https://www.R-project.org/.
58. Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, et al. Welcome to the tidyverse. Journal of Open Source Software. 2019;4(43):1686. doi: 10.21105/joss.01686
59. Abrahamovich AH, Atela O, De la Rúa P, Galián J. Assessment of the mitochondrial origin of honey bees from Argentina. Journal of Apicultural Research. 2015;46(3):191–194.
60. Simmons AD, Thomas CD. Changes in Dispersal during Species’ Range Expansions. American Naturalist. 2015;164(3):378–395.
61. Cwynar LC, MacDonald GM. Geographical Variation of Lodgepole Pine in Relation to Population History. American Naturalist. 1987;129(3):463–469. doi: 10.1086/284651
62. Phillips BL, Brown GP, Webb JK, Shine R. Invasion and the evolution of speed in toads. Nature. 2006;439(7078):803–803. doi: 10.1038/439803a
63. Hill JK, Thomas CD, Blakeley DS. Evolution of flight morphology in a butterfly that has recently expanded its geographic range. Oecologia. 1999;121(2):165–170. doi: 10.1007/s004420050918
64. Daly HV, Hoelmer K, Gambino P. Clinal geographic variation in feral honey bees in California, USA. Apidologie. 1991;22(6):591–609. doi: 10.1051/apido:19910603
65. Wang S, Rohwer S, Delmore K, Irwin DE. Cross-decades stability of an avian hybrid zone. Journal of Evolutionary Biology. 2019;32(11):1242–1251. doi: 10.1111/jeb.13524
66. Szymura JM, Barton NH. Genetic analysis of a hybrid zone between the fire-bellied toads, Bombina bombina and B. variegata, near Cracow in southern Poland. Evolution. 1986;40(6):1141. doi: 10.2307/2408943
67. Szymura JM, Barton NH. The genetic structure of the hybrid zone between the fire-bellied toads Bombina bombina and B. variegata: Comparisons between transects and between loci. Evolution. 1991;45(2):237. doi: 10.2307/2409660
68. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology. 2005;25(15):1965–1978. doi: 10.1002/joc.1276
69. Gompert Z, Mandeville EG, Buerkle CA. Analysis of Population Genomic Data from Hybrid Zones. Annual Review of Ecology, Evolution, and Systematics. 2017;48(1):207–229. doi: 10.1146/annurev-ecolsys-110316-022652
70. Barton NH. Multilocus Clines. Evolution. 1983;37(3):454. doi: 10.1111/j.1558-5646.1983.tb05563.x
71. Excoffier L, Foll M, Petit RJ. Genetic consequences of range expansions. Annual Review of Ecology, Evolution, and Systematics. 2009;40(1):481–501. doi: 10.1146/annurev.ecolsys.39.110707.173414
72. Hunt GJ, Amdam GV, Schlipalius D, Emore C, Sardesai N, Williams CE, et al. Behavioral genomics of honeybee foraging and nest defense. Die Naturwissenschaften. 2007;94(4):247–267. doi: 10.1007/s00114-006-0183-1 17171388
73. Tsuruda JM, Harris JW, Bourgeois L, Danka RG, Hunt GJ. High-resolution linkage analyses to identify genes that influence Varroa sensitive hygiene behavior in honey bees. PLoS ONE. 2012;7(11):e48276. doi: 10.1371/journal.pone.0048276
74. Oxley PR, Spivak M, Oldroyd BP. Six quantitative trait loci influence task thresholds for hygienic behaviour in honeybees (Apis mellifera). Molecular Ecology. 2010;19(7):1452–1461. doi: 10.1111/j.1365-294X.2010.04569.x
75. Spötter A, Gupta P, Nuernberg G, Reinsch N, Bienefeld K. Development of a 44K SNP assay focussing on the analysis of a varroa-specific defence behaviour in honey bees (Apis mellifera carnica). Molecular Ecology Resources. 2012;12(2):323–332. doi: 10.1111/j.1755-0998.2011.03106.x
76. Arechavaleta-Velasco ME, Alcala-Escamilla K, Robles-Rios C, Tsuruda JM, Hunt GJ. Fine-scale linkage mapping reveals a small set of candidate genes influencing honey bee grooming behavior in response to Varroa mites. PLoS ONE. 2012;7(11):e47269. doi: 10.1371/journal.pone.0047269
77. McDonnell CM, Alaux C, Parrinello H, Desvignes JP, Crauser D, Durbesson E, et al. Ecto- and endoparasite induce similar chemical and brain neurogenomic responses in the honey bee (Apis mellifera). BMC Ecology. 2013;13(1):1–15. doi: 10.1186/1472-6785-13-25
78. Surlis C, Carolan JC, Coffey M, Kavanagh K. Quantitative proteomics reveals divergent responses in Apis mellifera worker and drone pupae to parasitization by Varroa destructor. Journal of Insect Physiology. 2018;107:291–301. doi: 10.1016/j.jinsphys.2017.12.004
79. Buggs R. Empirical study of hybrid zone movement. Heredity. 2007;99(3):301–312. doi: 10.1038/sj.hdy.6800997
80. Taylor SA, Larson EL, Harrison RG. Hybrid zones: windows on climate change. Trends in Ecology & Evolution. 2015;30(7):398–406. doi: 10.1016/j.tree.2015.04.010
81. Good TP, Ellis JC, Annett CA, Pierotti R. Bounded hybrid superiority in an avian hybrid zone: effects of mate, diet, and habitat choice. Evolution. 2000;54(5):1774–1783. doi: 10.1111/j.0014-3820.2000.tb00721.x
82. De La Torre AR, Wang T, Jaquish B, Aitken SN. Adaptation and exogenous selection in a Picea glauca × Picea engelmannii hybrid zone: implications for forest management under climate change. New Phytologist. 2014;201(2):687–699. doi: 10.1111/nph.12540
83. Adrion JR, Hahn MW, Cooper BS. Revisiting classic clines in Drosophila melanogaster in the age of genomics. Trends in genetics: TIG. 2015;31(8):434–444. doi: 10.1016/j.tig.2015.05.006
84. Rinderer TE, Sylvester HA, Brown MA, Villa JD, Pesante D, Collins AM. Field and simplified techniques for identifying Africanized and European honey bees. Apidologie. 1986;17(1):13–48.
85. Currat M, Ruedi M, Petit RJ, Excoffier L. The hidden side of invasions: massive introgression by local genes. Evolution. 2008;62(8):1908–1920.
86. Barton N, Bengtsson BO. The barrier to genetic exchange between hybridising populations. Heredity. 1986;56:357–376.
87. Harpur BA, Kadri SM, Orsi RO, Whitfield CW, Zayed A. Defense response in Brazilian honey bees (Apis mellifera scutellata x spp.) is underpinned by complex patterns of admixture. Genome Biology and Evolution. 2020;. doi: 10.1093/gbe/evaa128 32597950
88. Goulson D, Nicholls E, Botías C, Rotheray EL. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science. 2015;347(6229):1255957–1255957. doi: 10.1126/science.1255957
89. Tange O. GNU Parallel 2018. Ole Tange; 2018. Available from: https://doi.org/10.5281/zenodo.1146014.
90. Rowan BA, Heavens D, Feuerborn TR, Tock AJ, Henderson IR, Weigel D. An ultra high-density Arabidopsis thaliana crossover map that refines the influences of structural variation and epigenetic features. Genetics. 2019;213(3):771–787. doi: 10.1534/genetics.119.302406
91. Harpur BA, Kent CF, Molodtsova D, Lebon JMD, Alqarni AS, Owayss AA, et al. Population genomics of the honey bee reveals strong signatures of positive selection on worker traits. Proceedings of the National Academy of Sciences USA. 2014;111(7):2614–2619. doi: 10.1073/pnas.1315506111
92. Wallberg A, Bunikis I, Pettersson OV, Mosbech MB, Childers AK, Evans JD, et al. A hybrid de novo genome assembly of the honeybee, Apis mellifera, with chromosome-length scaffolds. BMC Genomics. 2019;20(1):275. doi: 10.1186/s12864-019-5642-0 30961563
93. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature methods. 2012;9(4):357–359. doi: 10.1038/nmeth.1923
94. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics (Oxford, England). 2009;25(16):2078–2079. doi: 10.1093/bioinformatics/btp352
95. Korneliussen TS, Albrechtsen A, Nielsen R. ANGSD: Analysis of Next Generation Sequencing Data. BMC bioinformatics. 2014;15(1):356. doi: 10.1186/s12859-014-0356-4
96. Jones JC, Wallberg A, Christmas MJ, Kapheim KM, Webster MT, Singh N. Extreme differences in recombination rate between the genomes of a solitary and a social bee. Molecular Biology and Evolution. 2019;36(10):2277–2291. doi: 10.1093/molbev/msz130
97. Meisner J, Albrechtsen A. Inferring Population Structure and Admixture Proportions in Low-Depth NGS Data. Genetics. 2018;210(2):719–731. doi: 10.1534/genetics.118.301336
98. Thornton T, Tang H, Hoffmann TJ, Ochs-Balcom HM, Caan BJ, Risch N. Estimating Kinship in Admixed Populations. The American Journal of Human Genetics. 2012;91(1):122–138. doi: 10.1016/j.ajhg.2012.05.024
99. Long JC. The genetic structure of admixed populations. Genetics. 1991;127(2):417–428.
100. Venables WN, Ripley BD. Modern Applied Statistics with S. 4th ed. New York: Springer; 2002. Available from: http://www.stats.ox.ac.uk/pub/MASS4.
101. Hong Y. poibin: The Poisson Binomial Distribution; 2019. Available from: https://CRAN.R-project.org/package=poibin.
102. Hijmans RJ. geosphere: Spherical Trigonometry; 2019. Available from: https://CRAN.R-project.org/package=geosphere.
103. Bickel PJ, Boley N, Brown JB, Huang H, Zhang NR. Subsampling methods for genomic inference. The Annals of Applied Statistics. 2010;4(4):1660–1697. doi: 10.1214/10-AOAS363
104. Padfield D, Matheson G. nls.multstart: Robust Non-Linear Regression using AIC Scores; 2018. Available from: https://CRAN.R-project.org/package=nls.multstart.
105. Ruttner F. Morphometric Analysis and Classification. Berlin: Springer; 1988.
106. Grinde KE, Brown LA, Reiner AP, Thornton TA, Browning SR. Genome-wide significance thresholds for admixture mapping studies. American Journal of Human Genetics. 2019;104(3):454–465. doi: 10.1016/j.ajhg.2019.01.008
107. Siegmund D, Yakir B. The Statistics of Gene Mapping. Springer Science & Business Media; 2007.
108. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics (Oxford, England). 2010;26(6):841–842. doi: 10.1093/bioinformatics/btq033
109. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols. 2009;4(1):44–57. doi: 10.1038/nprot.2008.211
110. Benjamini Yoav, Hochberg Yosef. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. 1995;57(1):289–300.
111. Arechavaleta-Velasco ME, Hunt GJ, Emore C. Quantitative trait loci that influence the expression of guarding and stinging behaviors of individual honey bees. Behavior Genetics. 2003;33(3):357–364. doi: 10.1023/A:1023458827643
112. Solignac M, Mougel F, Vautrin D, Monnerot M, Cornuet JM. A third-generation microsatellite-based linkage map of the honey bee, Apis mellifera, and its comparison with the sequence-based physical map. Genome biology. 2007;8(4):R66. doi: 10.1186/gb-2007-8-4-r66
113. Harpur B. Hunt honey bee markers; 2020. Dryad. Available from: https://doi.org/10.5061/dryad.ns1rn8ppp.
114. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. Journal of molecular biology. 1990;215(3):403–410. doi: 10.1016/S0022-2836(05)80360-2
115. Bhatia G, Patterson N, Sankararaman S, Price AL. Estimating and interpreting FST: the impact of rare variants. Genome Research. 2013;23(9):1514–1521. doi: 10.1101/gr.154831.113
116. Honeybee Genome Sequencing Consortium. Insights into social insects from the genome of the honeybee Apis mellifera. Nature. 2006;444(7118):512–512. doi: 10.1038/nature05400
117. Miller CA, Hampton O, Coarfa C, Milosavljevic A. ReadDepth: A Parallel R Package for Detecting Copy Number Alterations from Short Sequencing Reads. PLoS ONE. 2011;6(1):e16327. doi: 10.1371/journal.pone.0016327
Článek vyšel v časopise
PLOS Genetics
2020 Číslo 10
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