Fifteen years of quantitative trait loci studies in fish: challenges and future directions

Molecular Ecology

Volumn 26, Issue 6, 2017, Pages 1465-1476

  Ashton, David T ^a   Ritchie, Peter A ^b   Wellenreuther, Maren ^a,c  

^a THE NEW ZEALAND INSTITUTE FOR PLANT AND FOOD RESEARCH LIMITED   (New Zealand)

^b VICTORIA UNIVERSITY OF WELLINGTON   (New Zealand)

^c LUND UNIVERSITY   (Sweden)

Author keywords

association; fish; linkage mapping; phenomics; quantitative trait loci mapping; teleost

Indexed keywords

ANIMAL; CHROMOSOMAL MAPPING; FISH; GENETIC LINKAGE; GENETICS; GENOMICS; PHENOTYPE; QUANTITATIVE TRAIT LOCUS; TRENDS;

ANIMALS; CHROMOSOME MAPPING; FISHES; GENETIC LINKAGE; GENOMICS; PHENOTYPE; QUANTITATIVE TRAIT LOCI;

EID: 85011650433     PISSN: 09621083     EISSN: 1365294X     Source Type: Journal    
DOI: 10.1111/mec.13965     Document Type: Review

References (67)

1. Almuly R, Poleg-Danin Y, Gorshkov S et al. (2005) Characterization of the 5′ flanking region of the growth hormone gene of the marine teleost, gilthead sea bream Sparus aurata: analysis of a polymorphic microsatellite in the proximal promoter. Fisheries Science, 71, 479–490.
2. Arcade A, Labourdette A, Falque M et al. (2004) BioMercator: integrating genetic maps and QTL towards discovery of candidate genes. Bioinformatics, 20, 2324–2326.
3. Ayllon F, Kjaerner-Semb E, Furmanek T et al. (2015) The vgll3 locus controls age at maturity in wild and domesticated atlantic salmon (Salmo salar L.) males. PLOS Genetics, 11, 1–15.
4. Baerwald MR, Meek MH, Stephens MR et al. (2016) Migration-related phenotypic divergence is associated with epigenetic modifications in rainbow trout. Molecular Ecology, 25, 1785–1800.
5. Benfey PN, Mitchell-Olds T (2008) From genotype to phenotype: systems biology meets natural variation. Science (New York, N.Y.), 320, 495–497.
6. Bras Y, Dechamp N, Krieg F et al. (2011) Detection of QTL with effects on osmoregulation capacities in the rainbow trout (Oncorhynchus mykiss). BMC Genetics, 12, 1–14.
7. Clop A, Marcq F, Takeda H et al. (2006) A mutation creating a potential illegitimate microRNA target site in the myostatin gene affects muscularity in sheep. Nature Genetics, 38, 813–818.
8. Cohen-Zinder M, Seroussi E, Larkin DM et al. (2005) Identification of a missense mutation in the bovine ABCG2 gene with a major effect on the QTL on chromosome 6 affecting milk yield and composition in Holstein cattle. Genome research, 15, 936–944.
9. Cortijo S, Wardenaar R, Colomé-Tatché M et al. (2014) Mapping the epigenetic basis of complex traits. Science, 343, 1145.
10. Dekkers JCM (2012) Application of genomics tools to animal breeding. Current Genomics, 13, 207–212.
11. Desta ZA, Ortiz R (2014) Genomic selection: genome-wide prediction in plant improvement. Trends in Plant Science, 19, 592–601.
12. Eichler EE, Flint J, Gibson G et al. (2010) Missing heritability and strategies for finding the underlying causes of complex disease. Nature Reviews Genetics, 11, 446–450.
13. Ellegren H (2014) Genome sequencing and population genomics in non-model organisms. Trends in Ecology & Evolution, 29, 51–63.
14. Elshire RJ, Glaubitz JC, Sun Q et al. (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE, 6, e19379.
15. Fang Z, Polacco M, Chen S et al. (2003) cMap: the comparative genetic map viewer. Bioinformatics, 19, 416–417.
16. Gagnaire P-A, Normandeau E, Pavey SA, Bernatchez L (2013) Mapping phenotypic, expression and transmission ratio distortion QTL using RAD markers in the Lake Whitefish (Coregonus clupeaformis). Molecular Ecology, 22, 3036–3048.
17. Goddard ME, Hayes BJ (2007) Genomic selection. Journal of Animal Breeding and Genetics, 124, 323–330.
18. Goddard ME, Whitelaw E (2014) The use of epigenetic phenomena for the improvement of sheep and cattle. Frontiers in Genetics, 5, 1–6.
19. Gregory TR (2016). Animal genome size database. Retrieved February 2, 2016, from http://www.genomesize.com/index.php
20. Grigorenko EL (2005) The inherent complexities of gene-environment interactions. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 60, 53–64.
21. Hemmer-Hansen J, Therkildsen NO, Pujolar JM (2014) Population genomics of marine fishes: next-generation prospects and challenges. The Biological Bulletin, 227, 117–132.
22. Henderson CR (1984) Applications of Linear Models in Animal Breeding. University of Guelph, Guelph, Ontario.
23. Hilario E, Barron L, Deng CH et al. (2015) Random Tagging Genotyping by Sequencing (rtGBS), an unbiased approach to locate restriction enzyme sites across the target genome. PLoS ONE, 10, 1–15.
24. Hong EP, Park JW (2012) Sample size and statistical power calculation in genetic association studies. Genomics & Informatics, 10, 117–122.
25. Houle D, Mezey J, Galpern P, Carter A (2003) Automated measurement of Drosophila wings. BMC Evolutionary Biology, 3, 1–13.
26. Houle D, Govindaraju DR, Omholt S (2010) Phenomics: the next challenge. Nature Reviews. Genetics, 11, 855–866.
27. Hu Z, Xu S (2008) A simple method for calculating the statistical power for detecting a QTL located in a marker interval. Heredity, 101, 48–52.
28. Ioannidis JPA, Kavvoura FK (2006) Concordance of functional in vitro data and epidemiological associations in complex disease genetics. Genetics in Medicine, 8, 583–593.
29. Jin S, Zhang X, Jia Z et al. (2012) Genetic linkage mapping and genetic analysis of QTL related to eye cross and eye diameter in common carp (Cyprinus carpio L.) using microsatellites and SNPs. Aquaculture, 358, 176–182.
30. Kahraman A, Avramov A, Nashev LG et al. (2005) PhenomicDB: a multi-species genotype/phenotype database for comparative phenomics. Bioinformatics, 21, 418–420.
31. Kirschner J, Weber D, Neuschl C et al. (2012) Mapping of quantitative trait loci controlling lifespan in the short-lived fish Nothobranchius furzeri- a new vertebrate model for age research. Aging Cell, 11, 252–261.
32. Korte A, Vilhjalmsson BJ, Segura V et al. (2012) A mixed-model approach for genome-wide association studies of correlated traits in structured populations. Nature Genetics, 44, 1066–1071.
33. Lanaud C, Fouet O, Clément D et al. (2009) A meta–QTL analysis of disease resistance traits of Theobroma cacao L. Molecular Breeding, 24, 361–374.
34. Lehner B (2013) Genotype to phenotype: lessons from model organisms for human genetics. Nature Reviews Genetics, 14, 168–178.
35. Li Y, Tollefsbol TO (2011) DNA methylation detection: Bisulfite genomic sequencing analysis. Methods in Molecular Biology (Clifton, N.J.), 791, 11–21.
36. Mackay TFC (2001) The genetic architecture of quantitative traits. Annual Review of Genetics, 35, 303–339.
37. Mackay TFC, Stone EA, Ayroles JF (2009) The genetics of quantitative traits: challenges and prospects. Nature Reviews Genetics, 10, 565–577.
38. Manichaikul A, Dupuis J, Sen Ś, Broman KW (2006) Poor performance of bootstrap confidence intervals for the location of a quantitative trait locus. Genetics, 174, 481–489.
39. Massault C, Bovenhuis H, Haley C, de Koning D-J (2008) QTL mapping designs for aquaculture. Aquaculture, 285, 23–29.
40. McCarthy MI, Abecasis GR, Cardon LR et al. (2008) Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Reviews Genetics, 9, 356–369.
41. Meuwissen THE, Goddard ME (1996) The use of marker haplotypes in animal breeding schemes. Genetics Selection Evolution, 28, 161–176.
42. Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157, 1819.
43. Navarro A, Lee-Montero I, Santana D et al. (2016) IMAFISH_ML: a fully-automated image analysis software for assessing fish morphometric traits on gilthead seabream (Sparus aurata L.), meagre (Argyrosomus regius) and red porgy (Pagrus pagrus). Computers and Electronics in Agriculture, 121, 66–73.
44. Ott J, Kamatani Y, Lathrop M (2011) Family-based designs for genome-wide association studies. Nature Reviews, 12, 465–474.
45. R Core Team (2013) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
46. Rezende FM, Ferraz JBS, Eler JP et al. (2012) Study of using marker assisted selection on a beef cattle breeding program by model comparison. Livestock Science, 147, 40–48.
47. Risch N, Zhang H (1995) Extreme discordant sib pairs for mapping quantitative trait loci in humans. Science, 268, 1584.
48. Rockman MV (2012) The QTN program and the alleles that matter for evolution: all that's gold does not glitter. Evolution, 66, 1–17.
49. Rockman MV, Kruglyak L (2008) Breeding designs for recombinant inbred advanced intercross lines. Genetics, 179, 1069.
50. Samorè AB, Fontanesi L (2016) Genomic selection in pigs: state of the art and perspectives. Italian Journal of Animal Science, 15, 211–232.
51. Sarropoulou E, Nousdili D, Magoulas A, Kotoulas G (2008) Linking the genomes of nonmodel teleosts through comparative genomics. Marine Biotechnology, 10, 227–233.
52. Sauvage C, Vagner M, Derome N, Audet C, Bernatchez L (2012) Coding gene SNP mapping reveals QTL linked to growth and stress response in brook charr (Salvelinus fontinalis). G3-Genes Genomes. Genetics, 2, 707–720.
53. Savolainen O, Lascoux M, Merila J (2013) Ecological genomics of local adaptation. Nature Reviews Genetics, 14, 807–820.
54. Sham PC, Purcell SM (2014) Statistical power and significance testing in large-scale genetic studies. Nature Reviews Genetics, 15, 335–346.
55. Silva PF, McGurk C, Thompson KD, Jayasuriya NS, Bron JE (2015) Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis. Aquaculture, 442, 100–111.
56. Slate JON (2005) INVITED REVIEW: quantitative trait locus mapping in natural populations: progress, caveats and future directions. Molecular Ecology, 14, 363–379.
57. Slate J (2013) From beavis to beak color: a simulation study to examine how much QTL mapping can reveal about the genetic architecture of quantitative traits. Evolution, 67, 1251–1262.
58. Stranger BE, Stahl EA, Raj T (2011) Progress and promise of genome-wide association studies for human complex trait genetics. Genetics, 187, 367–383.
59. Sutherland BJG, Gosselin T, Normandeau E et al. (in press) Salmonid chromosome evolution as revealed by a novel method for comparing RADseq linkage maps. Genome Biology and Evolution, doi:10.1093/gbe/evw262
60. Tong J, Sun X (2015) Genetic and genomic analyses for economically important traits and their applications in molecular breeding of cultured fish. Science China Life Sciences, 58, 178–186.
61. Viazzi S, Van Hoestenberghe S, Goddeeris BM, Berckmans D (2015) Automatic mass estimation of Jade perch Scortum barcoo by computer vision. Aquacultural Engineering, 64, 42–48.
62. Visscher PM, Brown MA, McCarthy MI, Yang J (2012) Five years of GWAS discovery. The American Journal of Human Genetics, 90, 7–24.
63. Visscher PM, Thompson R, Haley CS (1996) Confidence intervals in QTL mapping by bootstrapping. Genetics, 143, 1013–1020.
64. Weight C, Parnham D, Waites R (2008) TECHNICAL ADVANCE: LeafAnalyser: a computational method for rapid and large-scale analyses of leaf shape variation. The Plant Journal, 53, 578–586.
65. Wellenreuther M, Hansson B (2016) Detecting polygenic evolution: problems, pitfalls, and promises. Trends in Genetics, 32, 155–164.
66. Zhang C, Hsieh TF (2013) Heritable epigenetic variation and its potential applications for crop improvement. Plant Breeding and Biotechnology, 1, 307–319.
67. Zhou X, Stephens M (2012) Genome-wide efficient mixed-model analysis for association studies. Nature Genetics, 44, 821–824.