How “simple” methodological decisions affect interpretation of population structure based on reduced representation library DNA sequencing: A case study using the lake whitefish

Autoři: Carly F. Graham aff001;  Douglas R. Boreham aff002;  Richard G. Manzon aff001;  Wendylee Stott aff003;  Joanna Y. Wilson aff004;  Christopher M. Somers aff001
Působiště autorů: Department of Biology, University of Regina, Regina, Saskatchewan, Canada aff001;  Medical Sciences, Northern Ontario School of Medicine, Greater Sudbury, Ontario, Canada aff002;  Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, USA aff003;  Department of Biology, McMaster University, Hamilton, Ontario, Canada aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0226608


Reduced representation (RRL) sequencing approaches (e.g., RADSeq, genotyping by sequencing) require decisions about how much to invest in genome coverage and sequencing depth, as well as choices of values for adjustable bioinformatics parameters. To empirically explore the importance of these “simple” methodological decisions, we generated two independent sequencing libraries for the same 142 individual lake whitefish (Coregonus clupeaformis) using a nextRAD RRL approach: (1) a larger number of loci at low sequencing depth based on a 9mer (library A); and (2) fewer loci at higher sequencing depth based on a 10mer (library B). The fish were selected from populations with different levels of expected genetic subdivision. Each library was analyzed using the STACKS pipeline followed by three types of population structure assessment (FST, DAPC and ADMIXTURE) with iterative increases in the stringency of sequencing depth and missing data requirements, as well as more specific a priori population maps. Library B was always able to resolve strong population differentiation in all three types of assessment regardless of the selected parameters, largely due to retention of more loci in analyses. In contrast, library A produced more variable results; increasing the minimum sequencing depth threshold (-m) resulted in a reduced number of retained loci, and therefore lost resolution at high -m values for FST and ADMIXTURE, but not DAPC. When detecting fine population differentiation, the population map influenced the number of loci and missing data, which generated artefacts in all downstream analyses tested. Similarly, when examining fine scale population subdivision, library B was robust to changing parameters but library A lost resolution depending on the parameter set. We used library B to examine actual subdivision in our study populations. All three types of analysis found complete subdivision among populations in Lake Huron, ON and Dore Lake, SK, Canada using 10,640 SNP loci. Weak population subdivision was detected in Lake Huron with fish from sites in the north-west, Search Bay, North Point and Hammond Bay, showing slight differentiation. Overall, we show that apparently simple decisions about library construction and bioinformatics parameters can have important impacts on the interpretation of population subdivision. Although potentially more costly on a per-locus basis, early investment in striking a balance between the number of loci and sequencing effort is well worth the reduced genomic coverage for population genetics studies. More conservative stringency settings on STACKS parameters lead to a final dataset that was more consistent and robust when examining both weak and strong population differentiation. Overall, we recommend that researchers approach “simple” methodological decisions with caution, especially when working on non-model species for the first time.

Klíčová slova:

Bioinformatics – DNA libraries – Genome sequencing – Genomic libraries – Genotyping – Islands – Lakes – Molecular genetics


1. Davey JW, Hohenlohe PA, Etter PA, Boone JQ, Catchen JM, Blaxter ML. Genome Wide Genetic Marker Discovery and Genotyping Using NGS. Nature. 2011;12:499–510.

2. Narum SR, Buerkle CA, Davey JW, Miller MR, Hohenlohe PA. Genotyping-by-sequencing in ecological and conservation genomics. Mol Ecol. 2013;22(11):2841–7. doi: 10.1111/mec.12350 23711105

3. Andrews KR, Good JM, Miller MR, Luikart G, Hohenlohe PA. Harnessing the power of RADseq for ecological and evolutionary genomics. Nat Rev Genet. 2016;17(2):81–92. doi: 10.1038/nrg.2015.28 26729255

4. Miller MR, Dunham JP, Amores A, Cresko WA, Johnson EA. Rapid and cost-effective polymorphism identification and genotyping using restriction site associated DNA (RAD) markers. Genome Res. 2007;17(2):240–8. doi: 10.1101/gr.5681207 17189378

5. Baird NA, Etter PD, Atwood TS, Currey MC, Shiver AL, Lewis ZA, et al. Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS One. 2008;3(10):e3376. doi: 10.1371/journal.pone.0003376 18852878

6. Peterson BK, Weber JN, Kay EH, Fisher HS, Hoekstra HE. Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLoS One. 2012;7(5):e37135. doi: 10.1371/journal.pone.0037135 22675423

7. Poland JA, Brown PJ, Sorrells ME, Jannink J-L. Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. PLoS One. 2012;7(2):e32253. doi: 10.1371/journal.pone.0032253 22389690

8. Wang S, Meyer E, McKay JK, Matz MV. 2b-RAD: a simple and flexible method for genome-wide genotyping. Nat Methods. 2012;9(8):808–10. doi: 10.1038/nmeth.2023 22609625

9. Graham CF, Glenn TC, McArthur AG, Boreham DR, Kieran T, Lance S, et al. Impacts of degraded DNA on restriction enzyme associated DNA sequencing (RADSeq). Mol Ecol Resour. 2015;15(6):1304–15. doi: 10.1111/1755-0998.12404 25783180

10. Ali OA O Rourke SM, Amish SJ, Meek MH, Luikart G, Jeffres C, et al. Rad capture (Rapture): Flexible and efficient sequence-based genotyping. Genetics. 2016;202(2):389–400. doi: 10.1534/genetics.115.183665 26715661

11. Hoffberg SL, Kieran TJ, Catchen JM, Devault A, Faircloth BC, Mauricio R, et al. RADcap: sequence capture of dual-digest RADseq libraries with identifiable duplicates and reduced missing data. Mol Ecol Resour. 2016;16(5):1264–78. doi: 10.1111/1755-0998.12566 27416967

12. Russello MA, Waterhouse MD, Etter PD, Johnson EA. From promise to practice: pairing non-invasive sampling with genomics in conservation. PeerJ. 2015;3:e1106. doi: 10.7717/peerj.1106 26244114

13. Larson WA, Seeb LW, Everett MV, Waples RK, Templin WD, Seeb JE. Genotyping by sequencing resolves shallow population structure to inform conservation of Chinook salmon (Oncorhynchus tshawytscha). Evol Appl. 2014;7(3):355–69. doi: 10.1111/eva.12128 24665338

14. Benestan L, Gosselin T, Perrier C, Sainte-Marie B, Rochette R, Bernatchez L. RAD genotyping reveals fine-scale genetic structuring and provides powerful population assignment in a widely distributed marine species, the American lobster (Homarus americanus). Mol Ecol. 2015;24(13):3299–315. doi: 10.1111/mec.13245 25977167

15. Cristofari R, Bertorelle G, Ancel A, Benazzo A, Le Maho Y, Ponganis PJ, et al. Full circumpolar migration ensures evolutionary unity in the Emperor penguin. Nat Commun. 2016;7:11842. doi: 10.1038/ncomms11842 27296726

16. Catchen J, Bassham S, Wilson T, Currey M, O’Brien C, Yeates Q, et al. The population structure and recent colonization history of Oregon threespine stickleback determined using restriction-site associated DNA-sequencing. Mol Ecol. 2013;22(11):2864–83. doi: 10.1111/mec.12330 23718143

17. Cammen KM, Schultz TF, Rosel PE, Wells RS, Read AJ. Genomewide investigation of adaptation to harmful algal blooms in common bottlenose dolphins (Tursiops truncatus). Mol Ecol. 2015;24(18):4697–710. doi: 10.1111/mec.13350 26290192

18. Flanagan SP, Rose E, Jones AG. Population genomics reveals multiple drivers of population differentiation in a sex-role-reversed pipefish. Mol Ecol. 2016;5043–72. doi: 10.1111/mec.13794 27485274

19. Gleason LU, Burton RS. Genomic evidence for ecological divergence against a background of population homogeneity in the marine snail Chlorostoma funebralis. Mol Ecol. 2016;25:3557–73. doi: 10.1111/mec.13703 27199218

20. Funk WC, Lovich RE, Hohenlohe PA, Hofman CA, Morrison SA, Sillett TS, et al. Adaptive divergence despite strong genetic drift: genomic analysis of the evolutionary mechanisms causing genetic differentiation in the island fox (Urocyon littoralis). Mol Ecol. 2016;25(10):2176–94. doi: 10.1111/mec.13605 26992010

21. Díaz-arce N, Arrizabalaga H, Murua H, Irigoien X, Rodríguez-ezpeleta N. Molecular Phylogenetics and Evolution RAD-seq derived genome-wide nuclear markers resolve the phylogeny of tunas. Mol Phylogenet Evol. 2016;102:202–7. doi: 10.1016/j.ympev.2016.06.002 27286653

22. Morgan TD, Graham CF, McArthur AG, Raphenya AR, Boreham DR, Manzon RG, et al. Genetic population structure of the round whitefish (Prosopium cylindraceum) in North America: multiple markers reveal glacial refugia and regional subdivision. Can J Fish Aquat Sci. 2017;75(6):836–49.

23. Buerkle AC, Gompert Z. Population genomics based on low coverage sequencing: how low should we go? Mol Ecol. 2013;22(11):3028–35. doi: 10.1111/mec.12105 23174005

24. Nielsen R, Paul JS, Albrechtsen A, Song YS. Genotype and SNP calling from next-generation sequencing data. Nature reviews. Genetics. 2011;12(6):443–51. doi: 10.1038/nrg2986 21587300

25. Ilut DC, Nydam ML, Hare MP. Defining Loci in Restriction-Based Reduced Representation Genomic Data from Nonmodel Species: Sources of Bias and Diagnostics for Optimal Clustering. BioMed Res Int. 2014;675158. doi: 10.1155/2014/675158 25057498

26. Mastretta-Yanes A, Arrigo N, Alvarez N, Jorgensen TH, Piñero D, Emerson BC. Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference. Mol Ecol Resour. 2015;10:28–41.

27. Sims D, Sudbery I, Ilott NE, Heger A, Ponting CP. Sequencing depth and coverage: key considerations in genomic analyses. Nat Rev Genet. 2014;15(2):121–32. doi: 10.1038/nrg3642 24434847

28. Song K, Li L, Zhang G. Coverage recommendation for genotyping analysis of highly heterologous species using next-generation sequencing technology. Sci Rep. 2016;6:35736. doi: 10.1038/srep35736 27760996

29. Rodriguez-Ezpeleta N, Bradbury IANR, Naki I, Alvarez P. Population structure of Atlantic mackerel inferred from RAD-seq-derived SNP markers: effects of sequence clustering parameters and hierarchical SNP selection. Mol Ecol Res. 2016;16(4):991–1001.

30. Catchen J, Hohenlohe PA, Bassham S, Amores A, Cresko WA. Stacks: an analysis tool set for population genomics. Mol Ecol. 2013;22(11):3124–40. doi: 10.1111/mec.12354 23701397

31. Lu F, Lipka AE, Glaubitz J, Elshire R, Cherney JH, Casler MD, et al. Switchgrass genomic diversity, ploidy, and evolution: novel insights from a network-based SNP discovery protocol. PLoS Genet. 2013;9(1):e1003215. doi: 10.1371/journal.pgen.1003215 23349638

32. Eaton DAR. PyRAD: Assembly of de novo RADseq loci for phylogenetic analyses. Bioinformatics. 2014;30(13):1844–9. doi: 10.1093/bioinformatics/btu121 24603985

33. Paris JR, Stevens JR, Catchen JM. Lost in parameter space: A road map for Stacks. Methods Ecol Evol. 2017;8(10):1360–73.

34. Rochette NC, Catchen JM. Deriving genotypes from RAD-seq short-read data using Stacks. Nat Protoc. 2017;12(12):2640–59. doi: 10.1038/nprot.2017.123 29189774

35. Crawford JE, Lazzaro BP. Assessing the accuracy and power of population genetic inference from low-pass next-generation sequencing data. Front Genet. 2012;3:1–13. doi: 10.3389/fgene.2012.00001

36. Fumagalli M. Assessing the Effect of Sequencing Depth and Sample Size in Population Genetics Inferences. PLoS One. 2013;8(11):e79667. doi: 10.1371/journal.pone.0079667 24260275

37. Fountain ED, Pauli JN, Reid BN, Palsboll PJ, Peery MZ. Finding the right coverage: the impact of coverage and sequence quality on single nucleotide polymorphism genotyping error rates. Mol Ecol Resour. 2016;16(4):966–78. doi: 10.1111/1755-0998.12519 26946083

38. Gaughran S, Quinzin M, Miller J, Garrick RC, Edwards DL, Russello MA, et al. Theory, practice and conservation in the age of genomics: the Galapagos tortoise as a case study. Evol Appl. 2017;11(7):1–28.

39. Eaton DAR, Spriggs EL, Park B, Donoghue MJ. Misconceptions on missing data in RAD-seq phylogenetics with a deep-scale example from flowering plants. Syst Biol. 2017;66(3):399–412. doi: 10.1093/sysbio/syw092 27798402

40. Davey JW, Cezard T, Fuentes-Utrilla P, Eland C, Gharbi K, Blaxter ML. Special features of RAD Sequencing data: implications for genotyping. Mol Ecol. 2013;22(11):3151–64. doi: 10.1111/mec.12084 23110438

41. Arnold B, Corbett-Detig RB, Hartl D, Bomblies K. RADseq underestimates diversity and introduces genealogical biases due to nonrandom haplotype sampling. Mol Ecol. 2013;22(11):3179–90. doi: 10.1111/mec.12276 23551379

42. Flanagan SP, Jones AG. Substantial differences in bias between single-digest and double-digest RAD-seq libraries: A case study. Mol Ecol Resour. 2018;18(2):264–80. doi: 10.1111/1755-0998.12734 29120082

43. Cariou M, Duret L, Charlat S. How and how much does RAD-seq bias genetic diversity estimates? BMC Evol Biol. 2016;16(1):1–8.

44. Gautier M, Gharbi K, Cezard T, Foucaud J, Kerdelhué C, Pudlo P, et al. The effect of RAD allele dropout on the estimation of genetic variation within and between populations. Mol Ecol. 2013;22(11):3165–78. doi: 10.1111/mec.12089 23110526

45. Cooke TF, Yee MC, Muzzio M, Sockell A, Bell R, Cornejo OE, et al. GBStools: A statistical method for estimating allelic dropout in reduced representation sequencing data. PLoS Genet. 2016;12(2):1–18.

46. Henning F, Lee HJ, Franchini P, Meyer A. Genetic mapping of horizontal stripes in Lake Victoria cichlid fishes: Benefits and pitfalls of using RAD markers for dense linkage mapping. Mol Ecol. 2014;23(21):5224–40. doi: 10.1111/mec.12860 25039588

47. Shafer ABA, Peart CR, Tusso S, Maayan I, Brelsford A, Wheat CW, et al. Bioinformatic processing of RAD-seq data dramatically impacts downstream population genetic inference. Methods Ecol Evol. 2016;1–11.

48. Chattopadhyay B, Garg KM, Ramakrishnan U. Effect of diversity and missing data on genetic assignment with RAD-Seq markers. BMC Res Notes. 2014;7:841. doi: 10.1186/1756-0500-7-841 25424532

49. O’Leary SJ, Puritz JB, Willis SC, Hollenbeck CM, Portnoy DS. These aren’t the loci you’e looking for: Principles of effective SNP filtering for molecular ecologists. Mol Ecol. 2018;27(16):3193–206.

50. Huang H, Lacey Knowles L. Unforeseen consequences of excluding missing data from next-generation sequences: Simulation study of rad sequences. Syst Biol. 2016;65(3):357–65. doi: 10.1093/sysbio/syu046 24996413

51. Wagner CE, Keller I, Wittwer S, Selz OM, Mwaiko S, Greuter L, et al. Genome-wide RAD sequence data provide unprecedented resolution of species boundaries and relationships in the Lake Victoria cichlid adaptive radiation. Mol Ecol. 2013;22(3):787–98. doi: 10.1111/mec.12023 23057853

52. Wessinger CA, Freeman CC, Mort ME, Rausher MD, Hileman LC. Multiplexed shotgun genotyping resolves species relationships within the North American genus Penstemon. Am J Bot. 2016;103(5):912–22. doi: 10.3732/ajb.1500519 27208359

53. Hodel RGJ, Chen S, Payton AC, McDaniel SF, Soltis P, Soltis DE. Adding loci improves phylogeographic resolution in red mangroves despite increased missing data: Comparing microsatellites and RAD-Seq and investigating loci filtering. Sci Rep. 2017;7(1):1–14. doi: 10.1038/s41598-016-0028-x

54. Tripp EA, Tsai YHE, Zhuang Y, Dexter KG. RADseq dataset with 90% missing data fully resolves recent radiation of Petalidium (Acanthaceae) in the ultra-arid deserts of Namibia. Ecol Evol. 2017;7(19):7920–36. doi: 10.1002/ece3.3274 29043045

55. Rogers SM, Bernatchez L. The genetic architecture of ecological speciation and the association with signatures of selection in natural lake whitefish (Coregonus sp. Salmonidae) species pairs. Mol Biol Evol. 2007;24(6):1423–38. doi: 10.1093/molbev/msm066 17404398

56. VanDeHey J a., Sloss BL, Peeters PJ, Sutton TM. Genetic structure of lake whitefish (Coregonus clupeaformis) in Lake Michigan. Can J Fish Aquat Sci. 2009;66(3):382–93.

57. Evans ML, Prïbel K, Peruzzi S, Bernatchez L. Parallelism in the oxygen transport system of the lake whitefish: The role of physiological divergence in ecological speciation. Mol Ecol. 2012;21(16):4038–50. doi: 10.1111/j.1365-294X.2012.05682.x 22724454

58. Renaut S, Nolte AW, Rogers SM, Derome N, Bernatchez L. SNP signatures of selection on standing genetic variation and their association with adaptive phenotypes along gradients of ecological speciation in lake whitefish species pairs (Coregonus spp.). Mol Ecol. 2011;20(3):545–59. doi: 10.1111/j.1365-294X.2010.04952.x 21143332

59. Gagnaire PA, Normandeau E, Pavey SA, Bernatchez L. Mapping phenotypic, expression and transmission ratio distortion QTL using RAD markers in the Lake Whitefish (Coregonus clupeaformis). Mol Ecol. 2013;22(11):3036–48. doi: 10.1111/mec.12127 23181719

60. Mee JA, Bernatchez L, Reist JD, Rogers SM, Taylor EB. Identifying designatable units for intraspecific conservation prioritization: A hierarchical approach applied to the lake whitefish species complex (Coregonus spp.). Evol Appl. 2015;8(5):423–41. doi: 10.1111/eva.12247 26029257

61. Dion-Cote A-M, Symonova R, Lamaze FC, Pelikanova S, Rab P, Bernatchez L. Standing chromosomal variation in Lake Whitefish species pairs: The role of historical contingency and relevance for speciation. Mol Ecol. 2017;26(1):178–92. doi: 10.1111/mec.13816 27545583

62. Nalepa TF, Mohr LC, Henderson B, Madenjian CP, Schneeberger PJ. Lake Whitefish and Diporeia spp. in the Great Lakes: An Overview. Proc a Work Dyn lake whitefish (Coregonus clupeaformis) amphipod Diporeia spp Gt Lakes. 2005;Technical Report 66.

63. Loftus BH, Hulsman PF. Predation of larval lake whitefish (Coregonus clupeaformis) and lake hering (C. artedii) by adult rainbow smelt (Osmerus mordax). Can J Fish Aquat Sci. 1986;43:812–8.

64. Harford W, Latremouille D, Crawford S. A Bayesian stock assessment of lake whitefish (Coregonus clupeaformis) in Lake Huron and evaluation of total allowable catch options for 2007 Saugeen Ojibway Nations commercial harvest. Chippewas of Nawash Unceded First Nation & Saugeen First Nation. 2007.

65. Ebener MP, Kinnunen RE, Schneeberger PJ, Mohr LC, Hoyle JA, Peeters P. Management of commercial fisheries for lake whitefish in the Laurentian Great Lakes of North America. Int Gov Fish Ecosyst Learn from Past, Find Solut Futur. 2008;99–143.

66. Eberts RL, Wissel B, Simpson GL, Crawford SS, Stott W, Hanner RH, et al. Isotopic Structure of Lake Whitefish in Lake Huron: Evidence for Regional and Local Populations Based on Resource Use. North Am J Fish Manag. 2017;37(1):133–48.

67. Thome C, Mitz C, Sreetharan S, Mitz C, Somers CM, Manzon RG, et al. Developmental effects of the industrial cooling water additives morpholine and sodium hypochlorite on lake whitefish (Coregonus clupeaformis). Environ Toxicol Chem. 2017;36(7):1955–65. doi: 10.1002/etc.3727 28036109

68. Stott W, Ebener MP, Mohr L, Schaeffer J, Roseman EF, Harford WJ, et al. Genetic structure of lake whitefi sh, Coregonus clupeaformis, populations in the northern main basin of Lake Huron. Adv Limnol. 2008;63(c):241–60.

69. Stott W, VanDeHey JA, Justin JA. Genetic diversity of lake whitefish in lakes Michigan and Huron; sampling, standardization, and research priorities. J Great Lakes Res. 2010;36(SUPPL. 1):59–65.

70. Stott W, Ebener MP, Mohr L, Hartman T, Johnson J, Roseman EF. Spatial and temporal genetic diversity of lake whitefish (Coregonus clupeaformis (Mitchill)) from Lake Huron and Lake Erie. Adv Limnol. 2013;64:205–22.

71. Graham CF, Eberts RL, Morgan TD, Boreham DR, Lance SL, Manzon RG, et al. Fine-Scale Ecological and Genetic Population Structure of Two Whitefish (Coregoninae) Species in the Vicinity of Industrial Thermal Emissions. PLoS One. 2016;11(1):e0146656. doi: 10.1371/journal.pone.0146656 26807722

72. Bolger AM, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20. doi: 10.1093/bioinformatics/btu170 24695404

73. Andrews S. FastQC: A quality control tool for high throughput sequence data [online]. Babraham Bioinformatics. 2010.

74. Catchen JM, Amores A, Hohenlohe P, Cresko W, Postlethwait JH. Stacks: building and genotyping Loci de novo from short-read sequences. G3 (Bethesda). 2011;1(3):171–82.

75. Gosselin T. grur: an R package tailored for RADseq data imputations. 2018.

76. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81(3):559–75. doi: 10.1086/519795 17701901

77. Weir BS, Cockerham CC. Estimating F-Statistics for the Analysis of Population Structure Evolution. 1984;38(6):1358–70. doi: 10.1111/j.1558-5646.1984.tb05657.x 28563791

78. Meirmans PG, van Tienderen PH. GENOTYPE and GENODIVE: two programs for the analysis of genetic diversity of asexual organisms. Mol Ecol Notes. 2004;4:792–4.

79. Jombart T, Devillard S, Balloux F. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet. 2010;11:94. doi: 10.1186/1471-2156-11-94 20950446

80. Alexander DH, Novembre J. Fast model-based estimation of ancestry in unrelated individuals. 2009;1655–64.

81. Zhou H, Alexander D, Lange K. A quasi-Newton acceleration for high-dimensional optimization algorithms. Stat Comput. 2011;21(2):261–73. doi: 10.1007/s11222-009-9166-3 21359052

82. Francis RM. Pophelper: an R package and web app to analyse and visualize population structure. Mol Ecol Resour. 2017;17(1):27–32. doi: 10.1111/1755-0998.12509 26850166

83. Puebla O, Bermingham E, McMillan WO. Genomic atolls of differentiation in coral reef fishes (Hypoplectrus spp., Serranidae). 2014;5291–303.

84. Lah L, Trense D, Benke H, Berggren P, Gunnlaugsson P, Lockyer C, et al. Spatially explicit analysis of genome-wide SNPs detects subtle population structure in a mobile marine mammal, the harbor porpoise. PLoS One. 2016;11(10):1–23.

85. Maroso F, Franch R, Dalla G, Arculeo M, Bargelloni L. Marine Genomics RAD SNP markers as a tool for conservation of dolphin fish Coryphaena hippurus in the Mediterranean Sea: Identification of subtle genetic structure and assessment of populations sex-ratios. Mar Genomics. 2016;28:57–62. doi: 10.1016/j.margen.2016.07.003 27450636

86. Xu P, Xu S, Wu X, Tao Y, Wang B, Wang S, et al. Population genomic analyses from low-coverage RAD-Seq data: a case study on the non-model cucurbit bottle gourd. Plant J. 2014;77(30):430–42.

87. Allendorf FW, Danzmann RG. Secondary tetrasomic segregation of MDH-B and preferential pairing of homeologues in rainbow trout. Genetics. 1997;145(4):1083–92. 9093860

88. Seeb JE, Pascal CE, Grau ED, Seeb LW, Templin WD, Harkins T, et al. Transcriptome sequencing and high-resolution melt analysis advance single nucleotide polymorphism discovery in duplicated salmonids. Mol Ecol Resour. 2011;11(2):335–48. doi: 10.1111/j.1755-0998.2010.02936.x 21429141

89. Amores A, Catchen J, Ferrara A, Fontenot Q, Postlethwait JH. Genome evolution and meiotic maps by massively parallel DNA sequencing: Spotted gar, an outgroup for the teleost genome duplication. Genetics. 2011;188(4):799–808. doi: 10.1534/genetics.111.127324 21828280

90. Hohenlohe PA, Day MD, Amish SJ, Miller MR, Kamps-Hughes N, Boyer MC, et al. Genomic patterns of introgression in rainbow and westslope cutthroat trout illuminated by overlapping paired-end RAD sequencing. Mol Ecol. 2013;22(11):3002–13. doi: 10.1111/mec.12239 23432212

91. Waples RS. Testing for Hardy-Weinberg Proportions: Have We Lost the Plot? J Hered. 2014;106(1):1–19. doi: 10.1093/jhered/esu062 25425676

92. Andrews KR, Luikart G. Recent novel approaches for population genomics data analysis. Mol Ecol. 2014;23(7):1661–7. doi: 10.1111/mec.12686 24495199

93. Alexander DH, Lange K. Enhancements to the ADMIXTURE algorithm for individual ancestry estimation. BMC Bioinformatics. 2011;12(1):246.

94. McPhail J, Lindsey C. Freshwater fishes of Northwestern Canada and Alaska. Bulletin 173. Fish Res Board Canada. 1970;

95. Pielou EC. After the ice age the return of life to glaciated North America. Chicago: University of Chicago Press; 1991.

96. Dawson A. Ice Age Earth. Routledge, London; 1992.

97. Ebener MP, Brenden TO, Wright GM, Jones ML, Faisal M. Spatial and temporal distributions of lake white fish spawning stocks in Northern lakes Michigan and Huron, 2003–2008. J Great Lakes Res. 2010;36:38–51.

98. Benestan L, Quinn BK, Maaroufi H, Laporte M, Clark FK, Greenwood SJ, et al. Seascape genomics provides evidence for thermal adaptation and current-mediated population structure in American lobster (Homarus americanus). Mol Ecol. 2016;25(20):5073–92. doi: 10.1111/mec.13811 27543860

99. Xuereb A, Daigle M, Eric LB, Curtis JMR, Bernatchez L. Asymmetric oceanographic processes mediate connectivity and population genetic structure, as revealed by RADseq, in a highly dispersive marine invertebrate (Parastichopus californicus). Mol Ecol. 2018;27(10):2347–64. doi: 10.1111/mec.14589 29654703

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