1932

Abstract

The complexity of heredity has been appreciated for decades: Many traits are controlled not by a single genetic locus but instead by polymorphisms throughout the genome. The importance of complex traits in biology and medicine has motivated diverse approaches to understanding their detailed genetic bases. Here, we focus on recent systematic studies, many in budding yeast, which have revealed that large numbers of all kinds of molecular variation, from noncoding to synonymous variants, can make significant contributions to phenotype. Variants can affect different traits in opposing directions, and their contributions can be modified by both the environment and the epigenetic state of the cell. The integration of prospective (synthesizing and analyzing variants) and retrospective (examining standing variation) approaches promises to reveal how natural selection shapes quantitative traits. Only by comprehensively understanding nature's genetic tool kit can we predict how phenotypes arise from the complex ensembles of genetic variants in living organisms.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-genet-021920-102037
2020-11-23
2024-04-26
Loading full text...

Full text loading...

/deliver/fulltext/genet/54/1/annurev-genet-021920-102037.html?itemId=/content/journals/10.1146/annurev-genet-021920-102037&mimeType=html&fmt=ahah

Literature Cited

  1. 1. 
    Allis CD, Jenuwein T. 2016. The molecular hallmarks of epigenetic control. Nat. Rev. Genet. 17:8487–500
    [Google Scholar]
  2. 2. 
    Allison AC. 1954. Protection afforded by sickle-cell trait against subtertian malarial infection. Br. Med. J. 1:4857290–94
    [Google Scholar]
  3. 3. 
    Alonso-Blanco C, Andrade J, Becker C, Bemm F, Bergelson J et al. 2016. 1,135 genomes reveal the global pattern of polymorphism in Arabidopsis thaliana. . Cell 166:2481–91
    [Google Scholar]
  4. 4. 
    Alves JM, Carneiro M, Cheng JY, de Matos AL, Rahman MM et al. 2019. Parallel adaptation of rabbit populations to myxoma virus. Science 363:64331319–26
    [Google Scholar]
  5. 5. 
    Araya CL, Fowler DM, Chen W, Muniez I, Kelly JW, Fields S 2012. A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function. PNAS 109:4216858–63
    [Google Scholar]
  6. 6. 
    Barton NH, Etheridge AM, Véber A 2017. The infinitesimal model: definition, derivation, and implications. Theor. Popul. Biol. 118:50–73
    [Google Scholar]
  7. 7. 
    Baudin-Baillieu A, Legendre R, Kuchly C, Hatin I, Demais S et al. 2014. Genome-wide translational changes induced by the prion [PSI+]. Cell Rep 8:2439–48
    [Google Scholar]
  8. 8. 
    Beavis WD. 1994. The power and deceit of QTL experiments: lessons from comparative QTL studies. Proceedings of the Forty-Ninth Annual Corn and Sorghum Industry Research Conference252–68 Washington, DC: Am. Seed Trade Assoc.
    [Google Scholar]
  9. 9. 
    Benner C, Havulinna AS, Järvelin M-R, Salomaa V, Ripatti S, Pirinen M 2017. Prospects of fine-mapping trait-associated genomic regions by using summary statistics from genome-wide association studies. Am. J. Hum. Genet. 101:4539–51
    [Google Scholar]
  10. 10. 
    Bloom JS, Boocock J, Treusch S, Sadhu MJ, Day L et al. 2019. Rare variants contribute disproportionately to quantitative trait variation in yeast. eLife 8:e49212
    [Google Scholar]
  11. 11. 
    Bloom JS, Ehrenreich IM, Loo WT, Lite T-LV, Kruglyak L 2013. Finding the sources of missing heritability in a yeast cross. Nature 494:7436234–37
    [Google Scholar]
  12. 12. 
    Bloom JS, Kotenko I, Sadhu MJ, Treusch S, Albert FW, Kruglyak L 2015. Genetic interactions contribute less than additive effects to quantitative trait variation in yeast. Nat. Commun. 6:8712
    [Google Scholar]
  13. 13. 
    Boyle EA, Li YI, Pritchard JK 2017. An expanded view of complex traits: from polygenic to omnigenic. Cell 169:71177–86
    [Google Scholar]
  14. 14. 
    Breen MS, Kemena C, Vlasov PK, Notredame C, Kondrashov FA 2012. Epistasis as the primary factor in molecular evolution. Nature 490:7421535–38
    [Google Scholar]
  15. 15. 
    Brem RB, Yvert G, Clinton R, Kruglyak L 2002. Genetic dissection of transcriptional regulation in budding yeast. Science 296:5568752–55
    [Google Scholar]
  16. 16. 
    Breslow DK, Cameron DM, Collins SR, Schuldiner M, Stewart-Ornstein J et al. 2008. A comprehensive strategy enabling high-resolution functional analysis of the yeast genome. Nat. Methods 5:8711–18
    [Google Scholar]
  17. 17. 
    Brynedal B, Choi J, Raj T, Bjornson R, Stranger BE et al. 2017. Large-scale trans-eQTLs affect hundreds of transcripts and mediate patterns of transcriptional co-regulation. Am. J. Hum. Genet. 100:4581–91
    [Google Scholar]
  18. 18. 
    Buhr F, Jha S, Thommen M, Mittelstaet J, Kutz F et al. 2016. Synonymous codons direct cotranslational folding toward different protein conformations. Mol. Cell 61:3341–51
    [Google Scholar]
  19. 19. 
    Byers JS, Garcia DM, Jarosz DF 2017. Epigenetic regulation of genome integrity by a prion-based mechanism. bioRxiv 152512. https://doi.org/10.1101/152512
    [Crossref]
  20. 20. 
    Carter AJR, Nguyen AQ. 2011. Antagonistic pleiotropy as a widespread mechanism for the maintenance of polymorphic disease alleles. BMC Med. Genet. 12:160
    [Google Scholar]
  21. 21. 
    Cassidy JJ, Jha AR, Posadas DM, Giri R, Venken KJT et al. 2013. miR-9a minimizes the phenotypic impact of genomic diversity by buffering a transcription factor. Cell 155:71556–67
    [Google Scholar]
  22. 22. 
    Chakravarty AK, Smejkal T, Itakura AK, Garcia DM, Jarosz DF 2019. A non-amyloid prion particle that activates a heritable gene expression program. Mol. Cell 77:2251–65.e9
    [Google Scholar]
  23. 23. 
    Chang J, Zhou Y, Hu X, Lam L, Henry C et al. 2013. The molecular mechanism of a cis-regulatory adaptation in yeast. PLOS Genet 9:9e1003813
    [Google Scholar]
  24. 24. 
    Chen R, Mias GI, Li-Pook-Than J, Jiang L, Lam HYK et al. 2012. Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell 148:61293–1307
    [Google Scholar]
  25. 25. 
    Cheung VG, Spielman RS, Ewens KG, Weber TM, Morley M, Burdick JT 2005. Mapping determinants of human gene expression by regional and genome-wide association. Nature 437:70631365–69
    [Google Scholar]
  26. 26. 
    Chong JX, Buckingham KJ, Jhangiani SN, Boehm C, Sobreira N et al. 2015. The genetic basis of Mendelian phenotypes: discoveries, challenges, and opportunities. Am. J. Hum. Genet. 97:2199–215
    [Google Scholar]
  27. 27. 
    Cirulli ET, White S, Read RW, Elhanan G, Metcalf WJ et al. 2020. Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts. Nat. Commun. 11:542
    [Google Scholar]
  28. 28. 
    Civelek M, Lusis AJ. 2014. Systems genetics approaches to understand complex traits. Nat. Rev. Genet. 15:134–48
    [Google Scholar]
  29. 29. 
    Cooper DN, Krawczak M, Polychronakos C, Tyler-Smith C, Kehrer-Sawatzki H 2013. Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease. Hum. Genet. 132:101077–130
    [Google Scholar]
  30. 30. 
    Cortazzo P, Cerveñansky C, Marín M, Reiss C, Ehrlich R, Deana A 2002. Silent mutations affect in vivo protein folding in Escherichia coli. Biochem. Biophys. Res. Commun 293:1537–41
    [Google Scholar]
  31. 31. 
    Costanzo M, Baryshnikova A, Bellay J, Kim Y, Spear ED et al. 2010. The genetic landscape of a cell. Science 327:5964425–31
    [Google Scholar]
  32. 32. 
    Costanzo M, VanderSluis B, Koch EN, Baryshnikova A, Pons C et al. 2016. A global genetic interaction network maps a wiring diagram of cellular function. Science 353:6306aaf1420
    [Google Scholar]
  33. 33. 
    Cowen LE, Lindquist S. 2005. Hsp90 potentiates the rapid evolution of new traits: drug resistance in diverse fungi. Science 309:57442185–89
    [Google Scholar]
  34. 34. 
    Crow JF. 2010. On epistasis: why it is unimportant in polygenic directional selection. Philos. Trans. R. Soc. B 365:15441241–44
    [Google Scholar]
  35. 35. 
    Desai MM, Weissman D, Feldman MW 2007. Evolution can favor antagonistic epistasis. Genetics 177:21001–10
    [Google Scholar]
  36. 36. 
    Diss G, Lehner B. 2018. The genetic landscape of a physical interaction. eLife 7:e32472
    [Google Scholar]
  37. 37. 
    Dobzhansky TH 1936. Studies on hybrid sterility. II. Localization of sterility factors in Drosophila pseudoobscura hybrids. Genetics 21:2113–35
    [Google Scholar]
  38. 38. 
    Domingo J, Baeza-Centurion P, Lehner B 2019. The causes and consequences of genetic interactions (epistasis). Annu. Rev. Genom. Hum. Genet. 20:433–60
    [Google Scholar]
  39. 39. 
    Doudna JA. 2020. The promise and challenge of therapeutic genome editing. Nature 578:7794229–36
    [Google Scholar]
  40. 40. 
    Dowell RD, Ryan O, Jansen A, Cheung D, Agarwala S et al. 2010. Genotype to phenotype: a complex problem. Science 328:5977469
    [Google Scholar]
  41. 41. 
    Falconer DS, Mackay TFC. 1996. Introduction to Quantitative Genetics Harlow, UK: Pearson. , 4th. ed.
  42. 42. 
    Felson J. 2014. What can we learn from twin studies? A comprehensive evaluation of the equal environments assumption. Soc. Sci. Res. 43:184–99
    [Google Scholar]
  43. 43. 
    Fisher RA. 1919. XV.—The correlation between relatives on the supposition of Mendelian inheritance. Earth Environ. Sci. Trans. R. Soc. Edinburgh 52:2399–433
    [Google Scholar]
  44. 44. 
    Frazer KA, Murray SS, Schork NJ, Topol EJ 2009. Human genetic variation and its contribution to complex traits. Nat. Rev. Genet. 10:4241–51
    [Google Scholar]
  45. 45. 
    Frumkin I, Lajoie MJ, Gregg CJ, Hornung G, Church GM, Pilpel Y 2018. Codon usage of highly expressed genes affects proteome-wide translation efficiency. PNAS 115:21E4940–49
    [Google Scholar]
  46. 46. 
    Galton F. 1889. Natural Inheritance London: Macmillan
  47. 47. 
    Gamazon ER, Segrè AV, van de Bunt M, Wen X, Xi HS et al. 2018. Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation. Nat. Genet. 50:7956–67
    [Google Scholar]
  48. 48. 
    Gazal S, Loh P-R, Finucane HK, Ganna A, Schoech A et al. 2018. Functional architecture of low-frequency variants highlights strength of negative selection across coding and non-coding annotations. Nat. Genet. 50:111600–7
    [Google Scholar]
  49. 49. 
    Geiler-Samerotte KA, Sartori FMO, Siegal ML 2018. Decanalizing thinking on genetic canalization. Semin. Cell Dev. Biol. 88:54–66
    [Google Scholar]
  50. 50. 
    Geiler-Samerotte KA, Zhu YO, Goulet BE, Hall DW, Siegal ML 2016. Selection transforms the landscape of genetic variation interacting with Hsp90. PLOS Biol 14:10e2000465
    [Google Scholar]
  51. 51. 
    Génin E. 2019. Missing heritability of complex diseases: case solved. ? Hum. Genet. 139:103–13
    [Google Scholar]
  52. 52. 
    Giaever G, Chu AM, Ni L, Connelly C, Riles L et al. 2002. Functional profiling of the Saccharomyces cerevisiae genome. Nature 418:6896387–91
    [Google Scholar]
  53. 53. 
    Goodman DB, Church GM, Kosuri S 2013. Causes and effects of N-terminal codon bias in bacterial genes. Science 342:6157475–79
    [Google Scholar]
  54. 54. 
    Gray VE, Hause RJ, Luebeck J, Shendure J, Fowler DM 2018. Quantitative missense variant effect prediction using large-scale mutagenesis data. Cell Syst 6:1116–124.e3
    [Google Scholar]
  55. 55. 
    GTEx Consort 2017. Genetic effects on gene expression across human tissues. Nature 550:7675204–13 Erratum. 2018. Nature 553(7689):530
    [Google Scholar]
  56. 56. 
    Guerrero FD, Jamroz RC, Kammlah D, Kunz SE 1997. Toxicological and molecular characterization of pyrethroid-resistant horn flies, Haematobia irritans: identification of kdr and super-kdr point mutations. Insect Biochem. Mol. Biol. 27:8–9745–55
    [Google Scholar]
  57. 57. 
    Haldane JBS. 1922. Sex ratio and unisexual sterility in hybrid animals. J. Genet. 12:2101–9
    [Google Scholar]
  58. 58. 
    Halfmann R, Jarosz DF, Jones SK, Chang A, Lancaster AK, Lindquist S 2012. Prions are a common mechanism for phenotypic inheritance in wild yeasts. Nature 482:7385363–68
    [Google Scholar]
  59. 59. 
    Hansen TF. 2013. Why epistasis is important for selection and adaptation. Evolution 67:123501–11
    [Google Scholar]
  60. 60. 
    Harms MJ, Thornton JW. 2013. Evolutionary biochemistry: revealing the historical and physical causes of protein properties. Nat. Rev. Genet. 14:8559–71
    [Google Scholar]
  61. 61. 
    Hartman EC, Jakobson CM, Favor AH, Lobba MJ, Álvarez-Benedicto E et al. 2018. Quantitative characterization of all single amino acid variants of a viral capsid-based drug delivery vehicle. Nat. Commun. 9:11385
    [Google Scholar]
  62. 62. 
    Harvey ZH, Chen Y, Jarosz DF 2018. Protein-based inheritance: epigenetics beyond the chromosome. Mol. Cell 69:2195–202
    [Google Scholar]
  63. 63. 
    Harvey ZH, Chakravarty AK, Futia RA, Jarosz DF 2020. A prion epigenetic switch establishes an active chromatin state. Cell 180:5928–940.e14
    [Google Scholar]
  64. 64. 
    Hodgkin J. 2002. Seven types of pleiotropy. Int. J. Dev. Biol. 42:3501–5
    [Google Scholar]
  65. 65. 
    Hou F, Sun L, Zheng H, Skaug B, Jiang Q-X, Chen ZJ 2011. MAVS forms functional prion-like aggregates to activate and propagate antiviral innate immune response. Cell 146:3448–61
    [Google Scholar]
  66. 66. 
    Huang W, Mackay TFC. 2016. The genetic architecture of quantitative traits cannot be inferred from variance component analysis. PLOS Genet 12:11e1006421
    [Google Scholar]
  67. 67. 
    Hummel B, Hansen EC, Yoveva A, Aprile-Garcia F, Hussong R, Sawarkar R 2017. The evolutionary capacitor HSP90 buffers the regulatory effects of mammalian endogenous retroviruses. Nat. Struct. Mol. Biol. 24:3234–42
    [Google Scholar]
  68. 68. 
    Itakura AK, Chakravarty AK, Jakobson CM, Jarosz DF 2019. Widespread prion-based control of growth and differentiation strategies in Saccharomyces cerevisiae. Mol. Cell 7:2266–78.e6
    [Google Scholar]
  69. 69. 
    Itakura AK, Futia RA, Jarosz DF 2018. It pays to be in phase. Biochemistry 57:172520–29
    [Google Scholar]
  70. 70. 
    Jakobson CM, Jarosz DF. 2018. Organizing biochemistry in space and time using prion-like self-assembly. Curr. Opin. Syst. Biol. 8:16–24
    [Google Scholar]
  71. 71. 
    Jakobson CM, Jarosz DF. 2019. Molecular origins of complex heritability in natural genotype-to-phenotype relationships. Cell Syst 8:5363–79.e3
    [Google Scholar]
  72. 72. 
    Jakobson CM, She R, Jarosz DF 2019. Pervasive function and evidence for selection across standing genetic variation in S. cerevisiae. Nat. Commun 10:11222
    [Google Scholar]
  73. 73. 
    Jarosz DF, Lindquist S. 2010. Hsp90 and environmental stress transform the adaptive value of natural genetic variation. Science 330:60121820–24
    [Google Scholar]
  74. 74. 
    Jarvik J, Botstein D. 1975. Conditional-lethal mutations that suppress genetic defects in morphogenesis by altering structural proteins. PNAS 72:72738–42
    [Google Scholar]
  75. 75. 
    Jiang SH, Athanasopoulos V, Ellyard JI, Chuah A, Cappello J et al. 2019. Functional rare and low frequency variants in BLK and BANK1 contribute to human lupus. Nat. Commun. 10:2201
    [Google Scholar]
  76. 76. 
    Jones FC, Grabherr MG, Chan YF, Russell P, Mauceli E et al. 2012. The genomic basis of adaptive evolution in threespine sticklebacks. Nature 484:739255–61
    [Google Scholar]
  77. 77. 
    Joseph SB, Kirkpatrick M. 2008. Effects of the [PSI+] prion on rates of adaptation in yeast. J. Evol. Biol. 21:3773–80
    [Google Scholar]
  78. 78. 
    Julien P, Miñana B, Baeza-Centurion P, Valcárcel J, Lehner B 2016. The complete local genotype-phenotype landscape for the alternative splicing of a human exon. Nat. Commun. 7:11558
    [Google Scholar]
  79. 79. 
    Karasov T, Messer PW, Petrov DA 2010. Evidence that adaptation in Drosophila is not limited by mutation at single sites. PLOS Genet 6:6e1000924
    [Google Scholar]
  80. 80. 
    Karras GI, Yi S, Sahni N, Fischer M, Xie J et al. 2017. HSP90 shapes the consequences of human genetic variation. Cell 168:5856–866.e12
    [Google Scholar]
  81. 81. 
    Kimura M. 1967. On the evolutionary adjustment of spontaneous mutation rates. Genet. Res. 9:123–34
    [Google Scholar]
  82. 82. 
    Kinney JB, McCandlish DM. 2019. Massively parallel assays and quantitative sequence-function relationships. Annu. Rev. Genom. Hum. Genet. 20:99–127
    [Google Scholar]
  83. 83. 
    Kirschner M, Gerhart J. 1998. Evolvability. PNAS 95:158420–27
    [Google Scholar]
  84. 84. 
    Kita R, Venkataram S, Zhou Y, Fraser HB 2017. High-resolution mapping of cis-regulatory variation in budding yeast. PNAS 114:50E10736–44
    [Google Scholar]
  85. 85. 
    Klemm SL, Shipony Z, Greenleaf WJ 2019. Chromatin accessibility and the regulatory epigenome. Nat. Rev. Genet. 20:4207–20
    [Google Scholar]
  86. 86. 
    Klosin A, Oltsch F, Harmon T, Honigmann A, Jülicher F et al. 2020. Phase separation provides a mechanism to reduce noise in cells. Science 367:6476464–68
    [Google Scholar]
  87. 87. 
    Kobori S, Yokobayashi Y. 2016. High-throughput mutational analysis of a twister ribozyme. Angew. Chem. Int. Ed. Engl. 55:3510354–57
    [Google Scholar]
  88. 88. 
    Komar AA, Lesnik T, Reiss C 1999. Synonymous codon substitutions affect ribosome traffic and protein folding during in vitro translation. FEBS Lett 462:3387–91
    [Google Scholar]
  89. 89. 
    Kota SK, Feil R. 2010. Epigenetic transitions in germ cell development and meiosis. Dev. Cell 19:5675–86
    [Google Scholar]
  90. 90. 
    Kristofich J, Morgenthaler AB, Kinney WR, Ebmeier CC, Snyder DJ et al. 2018. Synonymous mutations make dramatic contributions to fitness when growth is limited by a weak-link enzyme. PLOS Genet 14:8e1007615
    [Google Scholar]
  91. 91. 
    Lachowiec J, Lemus T, Thomas JH, Murphy PJM, Nemhauser JL, Queitsch C 2013. The protein chaperone HSP90 can facilitate the divergence of gene duplicates. Genetics 193:41269–77
    [Google Scholar]
  92. 92. 
    Lander ES, Botstein D. 1989. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:1185–99 Erratum. 1994. Genetics 136(2):705
    [Google Scholar]
  93. 93. 
    Lattman EE, Rose GD. 1993. Protein folding—what's the question. ? PNAS 90:2439–41
    [Google Scholar]
  94. 94. 
    Lehner B. 2011. Molecular mechanisms of epistasis within and between genes. Trends Genet 27:8323–31
    [Google Scholar]
  95. 95. 
    Li J, Vázquez-García I, Persson K, González A, Yue J-X et al. 2019. Shared molecular targets confer resistance over short and long evolutionary timescales. Mol. Biol. Evol. 36:4691–708
    [Google Scholar]
  96. 96. 
    Li X, Dunn J, Salins D, Zhou G, Zhou W et al. 2017. Digital health: tracking physiomes and activity using wearable biosensors reveals useful health-related information. PLOS Biol 15:1e2001402
    [Google Scholar]
  97. 97. 
    Li Y, Petrov DA, Sherlock G 2019. Single nucleotide mapping of trait space reveals Pareto fronts that constrain adaptation. Nat. Ecol. Evol. 3:111539–51
    [Google Scholar]
  98. 98. 
    Liu X, Li YI, Pritchard JK 2019. Trans effects on gene expression can drive omnigenic inheritance. Cell 177:41022–34.e6
    [Google Scholar]
  99. 99. 
    Lutz S, Brion C, Kliebhan M, Albert FW 2019. DNA variants affecting the expression of numerous genes in trans have diverse mechanisms of action and evolutionary histories. PLOS Genet 15:11e1008375
    [Google Scholar]
  100. 100. 
    Lynch M, Walsh B. 1998. Genetics and Analysis of Quantitative Traits Sunderland, MA: Sinauer Assoc.
  101. 101. 
    Mackay TFC, Huang W. 2018. Charting the genotype-phenotype map: lessons from the Drosophila melanogaster Genetic Reference Panel. WIREs Dev. Biol. 7:e289
    [Google Scholar]
  102. 102. 
    Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA et al. 2009. Finding the missing heritability of complex diseases. Nature 461:7265747–53
    [Google Scholar]
  103. 103. 
    Marouli E, Graff M, Medina-Gomez C, Lo KS, Wood AR et al. 2017. Rare and low-frequency coding variants alter human adult height. Nature 542:7640186–90
    [Google Scholar]
  104. 104. 
    Masel J. 2006. Cryptic genetic variation is enriched for potential adaptations. Genetics 172:31985–91
    [Google Scholar]
  105. 105. 
    Masel J, Bergman A. 2003. The evolution of the evolvability properties of the yeast prion [PSI+]. Evolution 57:1498–512
    [Google Scholar]
  106. 106. 
    Maston GA, Evans SK, Green MR 2006. Transcriptional regulatory elements in the human genome. Annu. Rev. Genom. Hum. Genet. 7:29–59
    [Google Scholar]
  107. 107. 
    Mather K, Harrison BJ. 1949. The manifold effect of selection. Heredity 3:1–52
    [Google Scholar]
  108. 108. 
    McDonald ER III, de Weck A, Schlabach MR, Billy E, Mavrakis KJ et al. 2017. Project DRIVE: a compendium of cancer dependencies and synthetic lethal relationships uncovered by large-scale, deep RNAi screening. Cell 170:3577–92.e10
    [Google Scholar]
  109. 109. 
    McPherron AC, Lee S-J. 1997. Double muscling in cattle due to mutations in the myostatin gene. PNAS 94:2312457–61
    [Google Scholar]
  110. 110. 
    Melamed D, Young DL, Gamble CE, Miller CR, Fields S 2013. Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein. RNA 19:111537–51
    [Google Scholar]
  111. 111. 
    Messer PW, Ellner SP, Hairston NG 2016. Can population genetics adapt to rapid evolution. ? Trends Genet 32:7408–18
    [Google Scholar]
  112. 112. 
    Muller H. 1942. Isolating mechanisms, evolution, and temperature. Biol. Symp. 6:71–125
    [Google Scholar]
  113. 113. 
    Nica AC, Parts L, Glass D, Nisbet J, Barrett A et al. 2011. The architecture of gene regulatory variation across multiple human tissues: the MuTHER study. PLOS Genet 7:2e1002003
    [Google Scholar]
  114. 114. 
    O'Connor LJ, Schoech AP, Hormozdiari F, Gazal S, Patterson N, Price AL 2019. Extreme polygenicity of complex traits is explained by negative selection. Am. J. Hum. Genet. 105:3456–76
    [Google Scholar]
  115. 115. 
    Olson CA, Wu NC, Sun R 2014. A comprehensive biophysical description of pairwise epistasis throughout an entire protein domain. Curr. Biol. 24:222643–51
    [Google Scholar]
  116. 116. 
    Paaby AB, Rockman MV. 2013. The many faces of pleiotropy. Trends Genet 29:266–73
    [Google Scholar]
  117. 117. 
    Parker J, Tsagkogeorga G, Cotton JA, Liu Y, Provero P et al. 2013. Genome-wide signatures of convergent evolution in echolocating mammals. Nature 502:7470228–31
    [Google Scholar]
  118. 118. 
    Phillips PC. 2008. Epistasis—the essential role of gene interactions in the structure and evolution of genetic systems. Nat. Rev. Genet. 9:11855–67
    [Google Scholar]
  119. 119. 
    Poelwijk FJ, Socolich M, Ranganathan R 2019. Learning the pattern of epistasis linking genotype and phenotype in a protein. Nat. Commun. 10:14213
    [Google Scholar]
  120. 120. 
    Presnyak V, Alhusaini N, Chen Y-H, Martin S, Morris N et al. 2015. Codon optimality is a major determinant of mRNA stability. Cell 160:61111–24
    [Google Scholar]
  121. 121. 
    Pritchard JK, Pickrell JK, Coop G 2010. The genetics of human adaptation: hard sweeps, soft sweeps, and polygenic adaptation. Curr. Biol. 20:4R208–15
    [Google Scholar]
  122. 122. 
    Provine WB. 2001. The Origins of Theoretical Population Genetics Chicago: Univ. Chicago Press
  123. 123. 
    Puchta O, Cseke B, Czaja H, Tollervey D, Sanguinetti G, Kudla G 2016. Network of epistatic interactions within a yeast snoRNA. Science 352:6287840–44
    [Google Scholar]
  124. 124. 
    Purcell S. 2002. Variance components models for gene-environment interaction in twin analysis. Twin Res. Hum. Genet. 5:6554–71
    [Google Scholar]
  125. 125. 
    Queitsch C, Sangster TA, Lindquist S 2002. Hsp90 as a capacitor of phenotypic variation. Nature 417:6889618–24
    [Google Scholar]
  126. 126. 
    Rajon E, Masel J. 2011. Evolution of molecular error rates and the consequences for evolvability. PNAS 108:31082–87
    [Google Scholar]
  127. 127. 
    Rockman MV. 2012. The Qtn program and the alleles that matter for evolution: All that's gold does not glitter. Evolution 66:11–17
    [Google Scholar]
  128. 128. 
    Rohner N, Jarosz DF, Kowalko JE, Yoshizawa M, Jeffery WR et al. 2013. Cryptic variation in morphological evolution: HSP90 as a capacitor for loss of eyes in cavefish. Science 342:61641372–75
    [Google Scholar]
  129. 129. 
    Rollins NJ, Brock KP, Poelwijk FJ, Stiffler MA, Gauthier NP et al. 2019. Inferring protein 3D structure from deep mutation scans. Nat. Genet. 51:71170–76
    [Google Scholar]
  130. 130. 
    Rose MR. 1982. Antagonistic pleiotropy, dominance, and genetic variation. Heredity 48:163–78
    [Google Scholar]
  131. 131. 
    Roy KR, Smith JD, Vonesch SC, Lin G, Tu CS et al. 2018. Multiplexed precision genome editing with trackable genomic barcodes in yeast. Nat. Biotechnol. 36:6512–20
    [Google Scholar]
  132. 132. 
    Rudan M, Schneider D, Warnecke T, Krisko A 2015. RNA chaperones buffer deleterious mutations in E. coli. . eLife Sci 4:e04745
    [Google Scholar]
  133. 133. 
    Rudin C. 2019. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nat. Mach. Intell. 1:206–15
    [Google Scholar]
  134. 134. 
    Rutherford SL, Lindquist S. 1998. Hsp90 as a capacitor for morphological evolution. Nature 396:6709336–42
    [Google Scholar]
  135. 135. 
    Sadhu MJ, Bloom JS, Day L, Siegel JJ, Kosuri S, Kruglyak L 2018. Highly parallel genome variant engineering with CRISPR-Cas9. Nat. Genet. 50:4510–14
    [Google Scholar]
  136. 136. 
    Schaid DJ, Chen W, Larson NB 2018. From genome-wide associations to candidate causal variants by statistical fine-mapping. Nat. Rev. Genet. 19:491–504
    [Google Scholar]
  137. 137. 
    Schmiedel JM, Lehner B. 2019. Determining protein structures using deep mutagenesis. Nat. Genet. 51:71177–86
    [Google Scholar]
  138. 138. 
    Schopf FH, Biebl MM, Buchner J 2017. The HSP90 chaperone machinery. Nat. Rev. Mol. Cell Biol. 18:6345–60
    [Google Scholar]
  139. 139. 
    Segrè D, DeLuna A, Church GM, Kishony R 2005. Modular epistasis in yeast metabolism. Nat. Genet. 37:177–83
    [Google Scholar]
  140. 140. 
    Shah K, Cheng Y, Hahn B, Bridges R, Bradbury NA, Mueller DM 2015. Synonymous codon usage affects the expression of wild type and F508del CFTR. J. Mol. Biol. 427:6, Part B1464–79
    [Google Scholar]
  141. 141. 
    Sharon E, Chen S-AA, Khosla NM, Smith JD, Pritchard JK, Fraser HB 2018. Functional genetic variants revealed by massively parallel precise genome editing. Cell 175:2544–57.e16
    [Google Scholar]
  142. 142. 
    She R, Jarosz DF. 2018. Mapping causal variants with single-nucleotide resolution reveals biochemical drivers of phenotypic change. Cell 172:3478–490.e15
    [Google Scholar]
  143. 143. 
    Shin Y, Brangwynne CP. 2017. Liquid phase condensation in cell physiology and disease. Science 357:6357eaaf4382
    [Google Scholar]
  144. 144. 
    Shull GH. 1908. The composition of a field of maize. J. Hered. os-4:1296–301
    [Google Scholar]
  145. 145. 
    Solovieff N, Cotsapas C, Lee PH, Purcell SM, Smoller JW 2013. Pleiotropy in complex traits: challenges and strategies. Nat. Rev. Genet. 14:7483–95
    [Google Scholar]
  146. 146. 
    Stanley HM. 1889. Mr. Galton on natural inheritance. Nature 40:642–43
    [Google Scholar]
  147. 147. 
    Starr TN, Picton LK, Thornton JW 2017. Alternative evolutionary histories in the sequence space of an ancient protein. Nature 549:7672409–13
    [Google Scholar]
  148. 148. 
    Starr TN, Thornton JW. 2016. Epistasis in protein evolution. Protein Sci 25:71204–18
    [Google Scholar]
  149. 149. 
    Stearns Fenster 2013. Evidence for parallel adaptation to climate across the natural range of Arabidopsis thaliana. Ecol. Evol 3:72241–50
    [Google Scholar]
  150. 150. 
    Steinmetz LM, Sinha H, Richards DR, Spiegelman JI, Oefner PJ et al. 2002. Dissecting the architecture of a quantitative trait locus in yeast. Nature 416:6878326–30
    [Google Scholar]
  151. 151. 
    Taipale M, Jarosz DF, Lindquist S 2010. HSP90 at the hub of protein homeostasis: emerging mechanistic insights. Nat. Rev. Mol. Cell Biol. 11:7515–28
    [Google Scholar]
  152. 152. 
    Tam V, Patel N, Turcotte M, Bossé Y, Paré G, Meyre D 2019. Benefits and limitations of genome-wide association studies. Nat. Rev. Genet. 20:467–84
    [Google Scholar]
  153. 153. 
    Torkamani A, Wineinger NE, Topol EJ 2018. The personal and clinical utility of polygenic risk scores. Nat. Rev. Genet. 19:9581–90
    [Google Scholar]
  154. 154. 
    True HL, Lindquist SL. 2000. A yeast prion provides a mechanism for genetic variation and phenotypic diversity. Nature 407:6803477–83
    [Google Scholar]
  155. 155. 
    Tsherniak A, Vazquez F, Montgomery PG, Weir BA, Kryukov G et al. 2017. Defining a cancer dependency map. Cell 170:3564–576.e16
    [Google Scholar]
  156. 156. 
    Tuller T, Carmi A, Vestsigian K, Navon S, Dorfan Y et al. 2010. An evolutionarily conserved mechanism for controlling the efficiency of protein translation. Cell 141:2344–54
    [Google Scholar]
  157. 157. 
    Tyedmers J, Madariaga ML, Lindquist S 2008. Prion switching in response to environmental stress. PLOS Biol 6:11e294
    [Google Scholar]
  158. 158. 
    Uricchio LH. 2020. Evolutionary perspectives on polygenic selection, missing heritability, and GWAS. Hum. Genet. 139:5–21
    [Google Scholar]
  159. 159. 
    van de Haar J, Canisius S, Yu MK, Voest EE, Wessels LFA, Ideker T 2019. Identifying epistasis in cancer genomes: a delicate affair. Cell 177:61375–83
    [Google Scholar]
  160. 160. 
    van der Wijst MGP, Brugge H, de Vries DH, Deelen P, Swertz MA et al. 2018. Single-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs. Nat. Genet. 50:4493–97
    [Google Scholar]
  161. 161. 
    Venkataram S, Dunn B, Li Y, Agarwala A, Chang J et al. 2016. Development of a comprehensive genotype-to-fitness map of adaptation-driving mutations in yeast. Cell 166:61585–1596.e22
    [Google Scholar]
  162. 162. 
    Visscher PM, Goddard ME. 2019. From R.A. Fisher's 1918 paper to GWAS a century later. Genetics 211:41125–30
    [Google Scholar]
  163. 163. 
    Visscher PM, Wray NR, Zhang Q, Sklar P, McCarthy MI et al. 2017. 10 years of GWAS discovery: biology, function, and translation. Am. J. Hum. Genet. 101:15–22
    [Google Scholar]
  164. 164. 
    Vy HMT, Won Y-J, Kim Y 2017. Multiple modes of positive selection shaping the patterns of incomplete selective sweeps over African populations of Drosophila melanogaster. Mol. Biol. Evol 34:112792–807
    [Google Scholar]
  165. 165. 
    Waddington CH. 1942. Canalization of development and the inheritance of acquired characters. Nature 150:3811563–65
    [Google Scholar]
  166. 166. 
    Whitesell L, Mimnaugh EG, De Costa B, Myers CE, Neckers LM 1994. Inhibition of heat shock protein HSP90-pp60v-src heteroprotein complex formation by benzoquinone ansamycins: essential role for stress proteins in oncogenic transformation. PNAS 91:188324–28
    [Google Scholar]
  167. 167. 
    Williams GC. 1957. Pleiotropy, natural selection, and the evolution of senescence. Evolution 11:4398–411
    [Google Scholar]
  168. 168. 
    Williams PD, Day T. 2003. Antagonistic pleiotropy, mortality source interactions, and the evolutionary theory of senescence. Evolution 57:71478–88
    [Google Scholar]
  169. 169. 
    Williams PD, Pollock DD, Goldstein RA 2007. Functionality and the evolution of marginal stability in proteins: inferences from lattice simulations. Evol. Bioinform. Online 2:91–101
    [Google Scholar]
  170. 170. 
    Wu Y, Zheng Z, Visscher PM, Yang J 2017. Quantifying the mapping precision of genome-wide association studies using whole-genome sequencing data. Genome Biol 18:86
    [Google Scholar]
  171. 171. 
    Xie KT, Wang G, Thompson AC, Wucherpfennig JI, Reimchen TE et al. 2019. DNA fragility in the parallel evolution of pelvic reduction in stickleback fish. Science 363:642281–84
    [Google Scholar]
  172. 172. 
    Xu Y, Singer MA, Lindquist S 1999. Maturation of the tyrosine kinase c-src as a kinase and as a substrate depends on the molecular chaperone Hsp90. PNAS 96:1109–14
    [Google Scholar]
  173. 173. 
    Yalcin B, Fullerton J, Miller S, Keays DA, Brady S et al. 2004. Unexpected complexity in the haplotypes of commonly used inbred strains of laboratory mice. PNAS 101:269734–39
    [Google Scholar]
  174. 174. 
    Yao C, Joehanes R, Johnson AD, Huan T, Liu C et al. 2017. Dynamic role of trans regulation of gene expression in relation to complex traits. Am. J. Hum. Genet. 100:4571–80
    [Google Scholar]
  175. 175. 
    Yona AH, Alm EJ, Gore J 2018. Random sequences rapidly evolve into de novo promoters. Nat. Commun. 9:11530
    [Google Scholar]
  176. 176. 
    Young AI. 2019. Solving the missing heritability problem. PLOS Genet 15:6e1008222
    [Google Scholar]
  177. 177. 
    Yuan AH, Hochschild A. 2017. A bacterial global regulator forms a prion. Science 355:6321198–201
    [Google Scholar]
  178. 178. 
    Zabinsky RA, Mason GA, Queitsch C, Jarosz DF 2019. It's not magic - Hsp90 and its effects on genetic and epigenetic variation. Semin. Cell Dev. Biol. 88:21–35
    [Google Scholar]
  179. 179. 
    Zhen Y, Aardema ML, Medina EM, Schumer M, Andolfatto P 2012. Parallel molecular evolution in an herbivore community. Science 337:61021634–37
    [Google Scholar]
  180. 180. 
    Zuk O, Hechter E, Sunyaev SR, Lander ES 2012. The mystery of missing heritability: Genetic interactions create phantom heritability. PNAS 109:41193–98
    [Google Scholar]
  181. 181. 
    Zwart MP, Schenk MF, Hwang S, Koopmanschap B, de Lange N et al. 2018. Unraveling the causes of adaptive benefits of synonymous mutations in TEM-1 β-lactamase. Heredity 121:5406–21
    [Google Scholar]
/content/journals/10.1146/annurev-genet-021920-102037
Loading
/content/journals/10.1146/annurev-genet-021920-102037
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error