Correction: A sibling method for identifying vQTLs (PLoS ONE (2018) 13:4 (e0194541) DOI: 10.1371/journal.pone.0194541);A sibling method for identifying vQTLs

PLoS ONE

Volumn 13, Issue 4, 2018, Pages

  Conley, Dalton ^a   Johnson, Rebecca ^a   Domingue, Ben ^b   Dawes, Christopher ^c   Boardman, Jason ^d   Siegal, Mark ^c  

^a PRINCETON UNIVERSITY   (United States)

^b STANFORD UNIVERSITY   (United States)

^c NEW YORK UNIVERSITY   (United States)

^d UNIVERSITY OF COLORADO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BODY HEIGHT; BODY MASS; CONFOUNDING VARIABLE; GAP JUNCTION; GENE CONTROL; GENE FREQUENCY; GENE ISOLATION; GENE REPLICATION; GENETIC CODE; GENETIC TRAIT; GENETIC VARIABILITY; GENOTYPE ENVIRONMENT INTERACTION; GENOTYPING TECHNIQUE; HUMAN; MOLECULAR DYNAMICS; QUANTITATIVE TRAIT LOCUS MAPPING; SIGNAL TRANSDUCTION; SINGLE NUCLEOTIDE POLYMORPHISM; BIOLOGICAL MODEL; CHROMOSOMAL MAPPING; COMPUTER SIMULATION; GENETICS; GENOTYPE; PHENOTYPE; PROCEDURES; QUANTITATIVE TRAIT LOCUS; SIBLING;

BODY HEIGHT; BODY MASS INDEX; CHROMOSOME MAPPING; COMPUTER SIMULATION; GENOTYPE; HUMANS; MODELS, GENETIC; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; QUANTITATIVE TRAIT LOCI; SIBLINGS;

EID: 85045036898     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0196881     Document Type: Erratum

References (85)

1. Dongen SV. Fluctuating asymmetry and developmental instability in evolutionary biology: past, present and future. Journal of Evolutionary Biology. 2006; 19(6):1727-1743. https://doi.org/10.1111/j.1420-9101.2006.01175.x PMID: 17040371
2. Levy SF, Siegal ML. The robustness continuum. Advances in Experimental Medicine and Biology. 2012; 751:431-452. https://doi.org/10.1007/978-1-4614-3567-9-20 PMID: 22821470
3. Geiler-Samerotte KA, Bauer CR, Li S, Ziv N, Gresham D, Siegal ML. The details in the distributions: why and how to study phenotypic variability. Current Opinion in Biotechnology. 2013; 24(4):752-759. https://doi.org/10.1016/j.copbio.2013.03.010 PMID: 23566377
4. Gibson G, Dworkin I. Uncovering cryptic genetic variation. Nature Reviews Genetics. 2004; 5(9): nrg1426. https://doi.org/10.1038/nrg1426
5. Masel J, Siegal ML. Robustness: mechanisms and consequences. Trends in Genetics. 2009; 25 (9):395-403. https://doi.org/10.1016/j.tig.2009.07.005 PMID: 19717203
6. Berger D, Bauerfeind SS, Blanckenhorn WU, Schäfer MA. High Temperatures Reveal Cryptic Genetic Variation in a Polymorphic Female Sperm Storage Organ. Evolution. 2011; 65(10):2830-2842. https://doi.org/10.1111/j.1558-5646.2011.01392.x PMID: 21967425
7. Gibson G. Decanalization and the origin of complex disease. Nature Reviews Genetics. 2009; 10(2): nrg2502. https://doi.org/10.1038/nrg2502
8. Gibson G, Reed LK. Cryptic genetic variation. Current Biology. 2008; 18(21):R989-R990. https://doi.org/10.1016/j.cub.2008.08.011 PMID: 19000804
9. Wagner A. Robustness and evolvability: a paradox resolved. Proceedings of the Royal Society of London B: Biological Sciences. 2008; 275(1630):91-100. https://doi.org/10.1098/rspb.2007.1137
10. Siegal ML, Leu JY. On the Nature and Evolutionary Impact of Phenotypic Robustness Mechanisms. Annual Review of Ecology, Evolution, and Systematics. 2014; 45:496-517. https://doi.org/10.1146/annurev-ecolsys-120213-091705 PMID: 26034410
11. Jarosz DF, Lindquist S. Hsp90 and Environmental Stress Transform the Adaptive Value of Natural Genetic Variation. Science. 2010; 330(6012):1820-1824. https://doi.org/10.1126/science.1195487 PMID: 21205668
12. Queitsch C, Sangster TA, Lindquist S. Hsp90 as a capacitor of phenotypic variation. Nature. 2002; 417 (6889):618-624. https://doi.org/10.1038/nature749 PMID: 12050657
13. Rutherford SL, Lindquist S. Hsp90 as a capacitor for morphological evolution. Nature. 1998; 396 (6709):24550. https://doi.org/10.1038/24550
14. Yeyati PL, Bancewicz RM, Maule J, Heyningen Vv. Hsp90 Selectively Modulates Phenotype in Vertebrate Development. PLOS Genetics. 2007; 3(3):e43. https://doi.org/10.1371/journal.pgen.0030043 PMID: 17397257
15. Hsieh YY, Hung PH, Leu JY. Hsp90 regulates nongenetic variation in response to environmental stress. Molecular Cell. 2013; 50(1):82-92. https://doi.org/10.1016/j.molcel.2013.01.026 PMID: 23434373
16. Sangster TA, Salathia N, Undurraga S, Milo R, Schellenberg K, Lindquist S, et al. HSP90 affects the expression of genetic variation and developmental stability in quantitative traits. Proceedings of the National Academy of Sciences. 2008; 105(8):2963-2968. https://doi.org/10.1073/pnas.0712200105
17. Siegal ML. Crouching variation revealed. Molecular Ecology. 2013; 22(5):1187-1189. https://doi.org/10.1111/mec.12195 PMID: 23437837
18. Bauer CR, Li S, Siegal ML. Essential gene disruptions reveal complex relationships between phenotypic robustness, pleiotropy, and fitness. Molecular Systems Biology. 2015; 11(1):773. https://doi.org/10.15252/msb.20145264 PMID: 25609648
19. Levy SF, Siegal ML. Network Hubs Buffer Environmental Variation in Saccharomyces cerevisiae. PLOS Biology. 2008; 6(11):e264. https://doi.org/10.1371/journal.pbio.0060264 PMID: 18986213
20. Richardson JB, Uppendahl LD, Traficante MK, Levy SF, Siegal ML. Histone Variant HTZ1 Shows Extensive Epistasis with, but Does Not Increase Robustness to, New Mutations. PLOS Genetics. 2013; 9(8):e1003733. https://doi.org/10.1371/journal.pgen.1003733 PMID: 23990806
21. Geiler-Samerotte KA, Zhu YO, Goulet BE, Hall DW, Siegal ML. Selection Transforms the Landscape of Genetic Variation Interacting with Hsp90. PLoS biology. 2016; 14(10):e2000465. https://doi.org/10.1371/journal.pbio.2000465 PMID: 27768682
22. Ansel J, Bottin H, Rodriguez-Beltran C, Damon C, Nagarajan M, Fehrmann S, et al. Cell-to-Cell Stochastic Variation in Gene Expression Is a Complex Genetic Trait. PLOS Genetics. 2008; 4(4): e1000049. https://doi.org/10.1371/journal.pgen.1000049 PMID: 18404214
23. Ayroles JF, Buchanan SM, O'Leary C, Skutt-Kakaria K, Grenier JK, Clark AG, et al. Behavioral idiosyncrasy reveals genetic control of phenotypic variability. Proceedings of the National Academy of Sciences. 2015; 112(21):6706-6711. https://doi.org/10.1073/pnas.1503830112
24. Fehrmann S, Bottin-Duplus H, Leonidou A, Mollereau E, Barthelaix A, Wei W, et al. Natural sequence variants of yeast environmental sensors confer cell-to-cell expression variability. Molecular Systems Biology. 2013; 9(1):695. https://doi.org/10.1038/msb.2013.53 PMID: 24104478
25. Fraser HB, Schadt EE. The Quantitative Genetics of Phenotypic Robustness. PLOS ONE. 2010; 5(1): e8635. https://doi.org/10.1371/journal.pone.0008635 PMID: 20072615
26. Hall MC, Dworkin I, Ungerer MC, Purugganan M. Genetics of microenvironmental canalization in Arabidopsis thaliana. Proceedings of the National Academy of Sciences. 2007; 104(34):13717-13722. https://doi.org/10.1073/pnas.0701936104
27. Hulse AM, Cai JJ. Genetic Variants Contribute to Gene Expression Variability in Humans. Genetics. 2013; 193(1):95-108. https://doi.org/10.1534/genetics.112.146779 PMID: 23150607
28. Janhunen M, Kause A, Vehviläinen H, Järvisalo O. Genetics of Microenvironmental Sensitivity of Body Weight in Rainbow Trout (Oncorhynchus mykiss) Selected for Improved Growth. PLOS ONE. 2012; 7 (6):e38766. https://doi.org/10.1371/journal.pone.0038766 PMID: 22701708
29. Jimenez-Gomez JM, Corwin JA, Joseph B, Maloof JN, Kliebenstein DJ. Genomic Analysis of QTLs and Genes Altering Natural Variation in Stochastic Noise. PLOS Genetics. 2011; 7(9):e1002295. https://doi.org/10.1371/journal.pgen.1002295 PMID: 21980300
30. Perry GML, Nehrke KW, Bushinsky DA, Reid R, Lewandowski KL, Hueber P, et al. Sex Modifies Genetic Effects on Residual Variance in Urinary Calcium Excretion in Rat (Rattus norvegicus). Genetics. 2012; 191(3):1003-1013. https://doi.org/10.1534/genetics.112.138909 PMID: 22554889
31. Rönnegård L, Valdar W. Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability. BMC Genetics. 2012; 13:63. https://doi.org/10.1186/1471-2156-13-63 PMID: 22827487
32. Shen X, Pettersson M, Ronnegard L, Carlborg O. Inheritance Beyond Plain Heritability: Variance-Controlling Genes in Arabidopsis thaliana. PLOS Genetics. 2012; 8(8):e1002839. https://doi.org/10.1371/journal.pgen.1002839 PMID: 22876191
33. Stinchcombe JR, Caicedo AL, Hopkins R, Mays C, Boyd EW, Purugganan MD, et al. Vernalization sensitivity in Arabidopsis thaliana (Brassicaceae): the effects of latitude and FLC variation. American Journal of Botany. 2005; 92(10):1701-1707. https://doi.org/10.3732/ajb.92.10.1701 PMID: 21646087
34. Takahashi KH, Okada Y, Teramura K. Genome-Wide Deficiency Mapping of the Regions Responsible for Temporal Canalization of the Developmental Processes of Drosophila melanogaster. Journal of Heredity. 2011; 102(4):448-457. https://doi.org/10.1093/jhered/esr026 PMID: 21525178
35. Takahashi KH, Okada Y, Teramura K. Deficiency Screening for Genomic Regions with Effects on Environmental Sensitivity of the Sensory Bristles of Drosophila Melanogaster. Evolution. 2012; 66(9):2878-2890. https://doi.org/10.1111/j.1558-5646.2012.01636.x PMID: 22946809
36. Tonsor SJ, Elnaccash TW, Scheiner SM. Developmental Instability Is Genetically Correlated with Phenotypic Plasticity, Constraining Heritability, and Fitness. Evolution. 2013; 67(10):2923-2935. PMID: 24094343
37. Chen B, Wagner A. Hsp90 is important for fecundity, longevity, and buffering of cryptic deleterious variation in wild fly populations. BMC Evolutionary Biology. 2012; 12:25. https://doi.org/10.1186/1471-2148-12-25 PMID: 22369091
38. Sgrò CM, Wegener B, Hoffmann AA. A naturally occurring variant of Hsp90 that is associated with decanalization. Proceedings of the Royal Society of London B: Biological Sciences. 2010; 277 (1690):2049-2057. https://doi.org/10.1098/rspb.2010.0008
39. Siegal ML, Masel J. Hsp90 depletion goes wild. BMC Biology. 2012; 10:14. https://doi.org/10.1186/1741-7007-10-14 PMID: 22369621
40. et al Y. FTO genotype is associated with phenotypic variability of body mass index. Nature. 2012; 490(7419):nature11401.
41. Paré G, Cook NR, Ridker PM, Chasman DI. On the Use of Variance per Genotype as a Tool to Identify Quantitative Trait Interaction Effects: A Report from the Women's Genome Health Study. PLoS Genetics. 2010; 6(6). https://doi.org/10.1371/journal.pgen.1000981 PMID: 20585554
42. Andreasen CH, Stender-Petersen KL, Mogensen MS, Torekov SS, Wegner L, Andersen G, et al. Low Physical Activity Accentuates the Effect of the FTO rs9939609 Polymorphism on Body Fat Accumulation. Diabetes. 2008; 57(1):95-101. https://doi.org/10.2337/db07-0910 PMID: 17942823
43. Cha SW, Choi SM, Kim KS, Park BL, Kim JR, Kim JY, et al. Replication of Genetic Effects of FTO Polymorphisms on BMI in a Korean Population. Obesity. 2008; 16(9):2187-2189. https://doi.org/10.1038/oby.2008.314 PMID: 18551112
44. Chang YC, Liu PH, Lee WJ, Chang TJ, Jiang YD, Li HY, et al. Common Variation in the Fat Mass and Obesity-Associated (FTO) Gene Confers Risk of Obesity and Modulates BMI in the Chinese Population. Diabetes. 2008; 57(8):2245-2252. https://doi.org/10.2337/db08-0377 PMID: 18487448
45. Dina C, Meyre D, Gallina S, Durand E, Körner A, Jacobson P, et al. Variation in FTO contributes to childhood obesity and severe adult obesity. Nature Genetics. 2007; 39(6):ng2048. https://doi.org/10.1038/ng2048
46. Hunt SC, Stone S, Xin Y, Scherer CA, Magness CL, Iadonato SP, et al. Association of the FTO Gene With BMI. Obesity. 2008; 16(4):902-904. https://doi.org/10.1038/oby.2007.126 PMID: 18239580
47. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM, et al. A Common Variant in the FTO Gene Is Associated with Body Mass Index and Predisposes to Childhood and Adult Obesity. Science. 2007; 316(5826):889-894. https://doi.org/10.1126/science.1141634 PMID: 17434869
48. Haworth CMA, Carnell S, Meaburn EL, Davis OSP, Plomin R, Wardle J. Increasing Heritability of BMI and Stronger Associations With the FTO Gene Over Childhood. Obesity. 2008; 16(12):2663-2668. https://doi.org/10.1038/oby.2008.434 PMID: 18846049
49. Scuteri A, Sanna S, Chen WM, Uda M, Albai G, Strait J, et al. Genome-Wide Association Scan Shows Genetic Variants in the FTO Gene Are Associated with Obesity-Related Traits. PLOS Genetics. 2007; 3(7):e115. https://doi.org/10.1371/journal.pgen.0030115 PMID: 17658951
50. Tönjes A, Zeggini E, Kovacs P, Böttcher Y, Schleinitz D, Dietrich K, et al. Association of FTO variants with BMI and fat mass in the self-contained population of Sorbs in Germany. European Journal of Human Genetics. 2009; 18(1):ejhg2009107.
51. Cao Y, Wei P, Bailey M, Kauwe JSK, Maxwell TJ, for the Alzheimer's Disease Neuroimaging Initiative. A Versatile Omnibus Test for Detecting Mean and Variance Heterogeneity. Genetic Epidemiology. 2014; 38(1):51-59. https://doi.org/10.1002/gepi.21778 PMID: 24482837
52. Struchalin MV, Dehghan A, Witteman JC, van Duijn C, Aulchenko YS. Variance heterogeneity analysis for detection of potentially interacting genetic loci: method and its limitations. BMC Genetics. 2010; 11:92. https://doi.org/10.1186/1471-2156-11-92 PMID: 20942902
53. Soave D, Corvol H, Panjwani N, Gong J, Li W, BoeÈlle PY, et al. A Joint Location-Scale Test Improves Power to Detect Associated SNPs, Gene Sets, and Pathways. The American Journal of Human Genetics. 2015; 97(1):125-138. https://doi.org/10.1016/j.ajhg.2015.05.015 PMID: 26140448
54. Aschard H, Zaitlen N, Tamimi RM, Lindström S, Kraft P. A non-parametric test to detect quantitative trait loci where the phenotypic distribution differs by genotypes. Genetic epidemiology. 2013; 37 (4):323-333. https://doi.org/10.1002/gepi.21716 PMID: 23512279
55. Hong C, Ning Y, Wei P, Cao Y, Chen Y. A semiparametric model for vQTL mapping. Biometrics. 2017; 73(2):571-581. https://doi.org/10.1111/biom.12612 PMID: 27861717
56. Wei WH, Bowes J, Plant D, Viatte S, Yarwood A, Massey J, et al. Major histocompatibility complex harbors widespread genotypic variability of non-additive risk of rheumatoid arthritis including epistasis. Scientific Reports. 2016; 6.
57. Caplin A. Genes, Addiction, and Economics;. Available from: https://bfi.uchicago.edu/events/biologicalbasis-preferences-and-behavior.
58. Cao Y, Maxwell TJ, Wei P. A Family-Based Joint Test for Mean and Variance Heterogeneity for Quantitative Traits. Annals of Human Genetics. 2015; 79(1):46-56. https://doi.org/10.1111/ahg.12089 PMID: 25393880
59. Rönnegård L, Valdar W. Detecting Major Genetic Loci Controlling Phenotypic Variability in Experimental Crosses. Genetics. 2011; 188(2):435-447. https://doi.org/10.1534/genetics.111.127068 PMID: 21467569
60. Hamer DH. Beware the chopsticks gene. Molecular psychiatry. 2000; 5(1):11-13. https://doi.org/10.1038/sj.mp.4000662 PMID: 10673763
61. Day RL, Laland KN, Odling-Smee FJ. Rethinking Adaptation: The Niche-Construction Perspective. Perspectives in Biology and Medicine. 2003; 46(1):80-95. https://doi.org/10.1353/pbm.2003.0003 PMID: 12582272
62. Laland KN, Brown GR. Niche construction, human behavior, and the adaptive-lag hypothesis. Evolutionary Anthropology: Issues, News, and Reviews. 2006; 15(3):95-104. https://doi.org/10.1002/evan. 20093
63. Laland KN, Odling-Smee FJ, Feldman MW. Evolutionary consequences of niche construction and their implications for ecology. Proceedings of the National Academy of Sciences. 1999; 96(18):10242-10247. https://doi.org/10.1073/pnas.96.18.10242
64. Odling-Smee FJ, Laland KN, Feldman MW. Niche Construction. The American Naturalist. 1996; 147 (4):641-648. https://doi.org/10.1086/285870
65. Odling-Smee FJ, Laland KN, Feldman MW. Niche Construction: The Neglected Process in Evolution. Princeton University Press; 2003.
66. Wang G, Yang E, Brinkmeyer-Langford CL, Cai JJ. Additive, Epistatic, and Environmental Effects Through the Lens of Expression Variability QTL in a Twin Cohort. Genetics. 2014; 196(2):413-425. https://doi.org/10.1534/genetics.113.157503 PMID: 24298061
67. Dieleman JL, Templin T. Random-Effects, Fixed-Effects and the within-between Specification for Clustered Data in Observational Health Studies: A Simulation Study. PLOS ONE. 2014; 9(10):e110257. https://doi.org/10.1371/journal.pone.0110257 PMID: 25343620
68. Ahmad S, Rukh G, Varga TV, Ali A, Kurbasic A, Shungin D, et al. Gene× physical activity interactions in obesity: combined analysis of 111, 421 individuals of European ancestry. PLoS genetics. 2013; 9(7): e1003607. https://doi.org/10.1371/journal.pgen.1003607 PMID: 23935507
69. Sun X, Elston R, Morris N, Zhu X. What Is the Significance of Difference in Phenotypic Variability across SNP Genotypes? The American Journal of Human Genetics. 2013; 93(2):390-397. https://doi.org/10.1016/j.ajhg.2013.06.017 PMID: 23910463
70. Consortium EGGE, et al. A genome-wide association meta-analysis identifies new childhood obesity loci. Nature genetics. 2012; 44(5):526-531. https://doi.org/10.1038/ng.2247
71. Dumitrascu B, Darnell G, Ayroles J, Engelhardt BE. A Bayesian test to identify variance effects. arXiv:151201616 [q-bio, stat]. 2015;.
72. Conley D, Rauscher E, Dawes C, Magnusson PK, Siegal ML. Heritability and the equal environments assumption: Evidence from multiple samples of misclassified twins. Behavior Genetics. 2013; 43 (5):415-426. https://doi.org/10.1007/s10519-013-9602-1 PMID: 23903437
73. Gelman A, Hill J. Data analysis using regression and multilevelhierarchical models. vol. 1. Cambridge University Press New York, NY, USA; 2007.
74. dbGaP | phs000007.v29.p10 | Framingham Cohort;. Available from: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study-id=phs000007.v29.p10.
75. Johnson AD, Handsaker RE, Pulit SL, Nizzari MM, O'Donnell CJ, Bakker D, et al. SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics. 2008; 24(24):2938-2939. https://doi.org/10.1093/bioinformatics/btn564 PMID: 18974171
76. Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 2010; 26(18):2336-2337. https://doi.org/10.1093/bioinformatics/btq419 PMID: 20634204
77. A map of human genome variation from population scale sequencing. Nature. 2010; 467(7319):1061-1073. https://doi.org/10.1038/nature09534 PMID: 20981092
78. Miller MB, Basu S, Cunningham J, Eskin E, Malone SM, Oetting WS, et al. The Minnesota Center for Twin and Family Research Genome-Wide Association Study. Twin research and human genetics: the official journal of the International Society for Twin Studies. 2012; 15(6):767-774. https://doi.org/10.1017/thg.2012.62
79. Iacono WG, McGue M. Minnesota Twin Family Study. Twin Research and Human Genetics. 2002; 5(5):482-487. https://doi.org/10.1375/136905202320906327
80. Liu JZ, Mcrae AF, Nyholt DR, Medland SE, Wray NR, Brown KM, et al. A Versatile Gene-Based Test for Genome-wide Association Studies. The American Journal of Human Genetics. 2010; 87(1):139-145. https://doi.org/10.1016/j.ajhg.2010.06.009 PMID: 20598278
81. Zhang K, Cui S, Chang S, Zhang L, Wang J. i-GSEA4GWAS: a web server for identification of pathways/gene sets associated with traits by applying an improved gene set enrichment analysis to genome-wide association study. Nucleic Acids Research. 2010; 38(suppl-2):W90-W95. https://doi.org/10.1093/nar/gkq324 PMID: 20435672
82. Lamparter D, Marbach D, Rueedi R, Kutalik Z, Bergmann S. Fast and rigorous computation of gene and pathway scores from SNP-based summary statistics. PLoS computational biology. 2016; 12(1): e1004714. https://doi.org/10.1371/journal.pcbi.1004714 PMID: 26808494
83. Champely S. pwr: Basic functions for power analysis. R package version 1.1. 1. The R Foundation. 2009;.
84. Imbens GW, Kolesá r M. Robust Standard Errors in Small Samples: Some Practical Advice. The Review of Economics and Statistics. 2015; 98(4):701-712. https://doi.org/10.1162/REST-a-00552
85. Cameron AC, Miller DL. A Practitioner's Guide to Cluster-Robust Inference. Journal of Human Resources. 2015; 50(2):317-372. https://doi.org/10.3368/jhr.50.2.317