The Limits of Natural Selection in a Nonequilibrium World

Trends in Genetics

Volumn 32, Issue 4, 2016, Pages 201-210

  Brandvain, Yaniv ^a   Wright, Stephen I ^b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

DEMOGRAPHY; EFFECTIVE POPULATION SIZE; GENETIC ANALYSIS; GENETIC LOAD; GENETIC RECOMBINATION; GENOME; GENOMICS; HUMAN; MUTATION RATE; NATURAL POPULATION; NATURAL SELECTION; NONHUMAN; POPULATION SIZE; PRIORITY JOURNAL; REVIEW; WEIGHT; GENETIC SELECTION;

SELECTION, GENETIC;

EID: 84962622856     PISSN: 01689525     EISSN: 13624555     Source Type: Journal    
DOI: 10.1016/j.tig.2016.01.004     Document Type: Review

References (94)

1. Barton N., Partridge L. Limits to natural selection. Bioessays 2000, 22:1075-1084.
2. Eyre-Walker Y.C., Eyre-Walker A. The role of mutation rate variation and genetic diversity in the architecture of human disease. PLoS ONE 2014, 9:e90166.
3. Pritchard J.K. Are rare variants responsible for susceptibility to complex diseases?. Am. J. Hum. Genet. 2001, 69:124-137.
4. Lande R. Risk of population extinction from fixation of deleterious and reverse mutations. Genetica 1998, 102-103:21-27.
5. Lynch M., et al. Mutation accumulation and the extinction of small populations. Am. Nat. 1995, 146:489-518.
6. Lynch M., et al. The mutational meltdown in asexual populations. J. Hered. 1993, 84:339-344.
7. Goldberg E.E., et al. Species selection maintains self-incompatibility. Science 2010, 330:493-495.
8. Igic B., Busch J.W. Is self-fertilization an evolutionary dead end?. New Phytol. 2013, 198:386-397.
9. Takebayashi N., Morrell P.L. Is self-fertilization an evolutionary dead end? Revisiting an old hypothesis with genetic theories and a macroevolutionary approach. Am. J. Bot. 2001, 88:1143-1150.
10. Wright S.I., et al. Evolutionary consequences of self-fertilization in plants. Proc. Biol. Sci. 2013, 280:20130133.
11. Charlesworth B., Charlesworth D. The degeneration of Y chromosomes. Philos. Trans. R. Soc. Lond. B: Biol. Sci. 2000, 355:1563-1572.
12. Lynch M. The origins of eukaryotic gene structure. Mol. Biol. Evol. 2006, 23:450-468.
13. Lynch M. The Origins of Genome Architecture 2007, Sinauer Associates.
14. Lynch M., Conery J.S. The origins of genome complexity. Science 2003, 302:1401-1404.
15. Lynch M., et al. Mutation pressure and the evolution of organelle genomic architecture. Science 2006, 311:1727-1730.
16. Lu J., et al. The accumulation of deleterious mutations in rice genomes: a hypothesis on the cost of domestication. Trends Genet. 2006, 22:126-131.
17. Renaut S., Rieseberg L.H. The accumulation of deleterious mutations as a consequence of domestication and improvement in sunflowers and other Compositae crops. Mol. Biol. Evol. 2015, 32:2273-2283.
18. Marsden C.D., et al. Bottlenecks and selective sweeps during domestication have increased deleterious genetic variation in dogs. Proc. Natl. Acad. Sci. U.S.A. 2016, 113:152-157.
19. Schubert M., et al. Prehistoric genomes reveal the genetic foundation and cost of horse domestication. Proc. Natl. Acad. Sci. U.S.A. 2014, 111:E5661-E5669.
20. Laberge A.M., et al. Population history and its impact on medical genetics in Quebec. Clin. Genet. 2005, 68:287-301.
21. Polvi A., et al. The Finnish Disease Heritage Database (FinDis) update - a database for the genes mutated in the Finnish disease heritage brought to the next-generation sequencing era. Hum. Mutat. 2013, 34:1458-1466.
22. Casals F., et al. Whole-exome sequencing reveals a rapid change in the frequency of rare functional variants in a founding population of humans. PLoS Genet. 2013, 9:e1003845.
23. Lim E.T., et al. Distribution and medical impact of loss-of-function variants in the Finnish founder population. PLoS Genet. 2014, 10:e1004494.
24. Lohmueller K.E. The distribution of deleterious genetic variation in human populations. Curr. Opin. Genet. Dev. 2014, 29:139-146.
25. Lohmueller K.E., et al. Proportionally more deleterious genetic variation in European than in African populations. Nature 2008, 451:994-995.
26. Peischl S., et al. On the accumulation of deleterious mutations during range expansions. Mol. Ecol. 2013, 22:5972-5982.
27. Arunkumar R., et al. The evolution of selfing is accompanied by reduced efficacy of selection and purging of deleterious mutations. Genetics 2015, 199:817-829.
28. Brandvain Y., et al. Speciation and introgression between Mimulus nasutus and Mimulus guttatus. PLoS Genet. 2014, 10:e1004410.
29. Hollister J.D., et al. Recurrent loss of sex is associated with accumulation of deleterious mutations in Oenothera. Mol. Biol. Evol. 2015, 32:896-905.
30. Slotte T., et al. The Capsella rubella genome and the genomic consequences of rapid mating system evolution. Nat. Genet. 2013, 45:831-835.
31. Do R., et al. No evidence that selection has been less effective at removing deleterious mutations in Europeans than in Africans. Nat. Genet. 2015, 47:126-131.
32. Lohmueller K.E. The impact of population demography and selection on the genetic architecture of complex traits. PLoS Genet. 2014, 10:e1004379.
33. Simons Y.B., et al. The deleterious mutation load is insensitive to recent population history. Nat. Genet. 2014, 46:220-224.
34. Gordo I., Dionisio F. Nonequilibrium model for estimating parameters of deleterious mutations. Phys. Rev. E: Stat. Nonlin. Soft Matter Phys. 2005, 71:031907.
35. Pennings P.S., et al. Loss and recovery of genetic diversity in adapting populations of HIV. PLoS Genet. 2014, 10:e1004000.
36. Haldane J.B.S. The effect of variation on fitness. Am. Nat. 1937, 71:337-349.
37. Agrawal A.F., Whitlock M.C. Mutation load: the fitness of individuals in populations where deleterious alleles are abundant. Annu. Rev. Ecol. Evol. 2012, 43:115-135.
38. Li H., Durbin R. Inference of human population history from individual whole-genome sequences. Nature 2011, 475:493-496.
39. Rasmussen M.D., et al. Genome-wide inference of ancestral recombination graphs. PLoS Genet. 2014, 10:e1004342.
40. Schiffels S., Durbin R. Inferring human population size and separation history from multiple genome sequences. Nat. Genet. 2014, 46:919-925.
41. Sheehan S., et al. Estimating variable effective population sizes from multiple genomes: a sequentially Markov conditional sampling distribution approach. Genetics 2013, 194:647-662.
42. Conrad D.F., et al. Variation in genome-wide mutation rates within and between human families. Nat. Genet. 2011, 43:712-714.
43. Kong A., et al. Rate of de novo mutations and the importance of father's age to disease risk. Nature 2012, 488:471-475.
44. Gravel S. When is selection effective?. bioRxiv 2014, Published online October 30, 2014. 10.1101/010934.
45. Peischl S., Excoffier L. Expansion load: recessive mutations and the role of standing genetic variation. Mol. Ecol. 2015, 24:2084-2094.
46. Kirkpatrick M., Jarne P. The effects of a bottleneck on inbreeding depression and the genetic load. Am. Nat. 2000, 155:154-167.
47. Balick D.J., et al. Dominance of deleterious alleles controls the response to a population bottleneck. PLoS Genet. 2015, 11:e1005436.
48. Jensen J.D., Bachtrog D. Characterizing the influence of effective population size on the rate of adaptation: Gillespie's Darwin domain. Genome Biol. Evol. 2011, 3:687-701.
49. Song Y.S., Steinrucken M. A simple method for finding explicit analytic transition densities of diffusion processes with general diploid selection. Genetics 2012, 190:1117-1129.
50. Agrawal A.F., Whitlock M.C. Inferences about the distribution of dominance drawn from yeast gene knockout data. Genetics 2011, 187:553-566.
51. Henn B.M., et al. Estimating the mutation load in human genomes. Nat. Rev. Genet. 2015, 16:333-343.
52. Henn B.M., et al. Distance from sub-Saharan Africa predicts mutational load in diverse human genomes. Proc. Natl. Acad. Sci. U.S.A. 2016, 113:E440-E449.
53. Sousa V., et al. Impact of range expansions on current human genomic diversity. Curr. Opin. Genet. Dev. 2014, 29:22-30.
54. Fu W.Q., et al. Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature 2013, 493:216-220.
55. Tennessen J.A., et al. Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science 2012, 337:64-69.
56. Fu W., et al. Characteristics of neutral and deleterious protein-coding variation among individuals and populations. Am. J. Hum. Genet. 2014, 95:421-436.
57. Chun S., Fay J.C. Identification of deleterious mutations within three human genomes. Genome Res. 2009, 19:1553-1561.
58. Davydov E.V., et al. Identifying a high fraction of the human genome to be under selective constraint using GERP++. PLoS Comput. Biol. 2010, 6:e1001025.
59. Ng P.C., Henikoff S. SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003, 31:3812-3814.
60. Stone E.A., Sidow A. Physicochemical constraint violation by missense substitutions mediates impairment of protein function and disease severity. Genome Res. 2005, 15:978-986.
61. Glemin S., Galtier N. Genome evolution in outcrossing versus selfing versus asexual species. Methods Mol. Biol. 2012, 855:311-335.
62. Keightley P.D., Eyre-Walker A. Joint inference of the distribution of fitness effects of deleterious mutations and population demography based on nucleotide polymorphism frequencies. Genetics 2007, 177:2251-2261.
63. Boyko A.R., et al. Assessing the evolutionary impact of amino acid mutations in the human genome. PLoS Genet. 2008, 4:e1000083.
64. Messer P.W., Petrov D.A. Frequent adaptation and the McDonald-Kreitman test. Proc. Natl. Acad. Sci. U.S.A. 2013, 110:8615-8620.
65. Douglas G.M., et al. Hybrid origins and the earliest stages of diploidization in the highly successful recent polyploid Capsella bursa-pastoris. Proc. Natl. Acad. Sci. U.S.A. 2015, 112:2806-2811.
66. Harris K., Nielsen R. The genetic cost of Neanderthal introgression. bioRxiv 2015, Published online October 30, 2015. 10.1101/030387.
67. Juric I., et al. The strength of selection against Neanderthal introgression. bioRxiv 2015, Published online November 21, 2015. 10.1101/030148.
68. Akashi H., et al. Weak selection and protein evolution. Genetics 2012, 192:15-31.
69. Koenig D., et al. Comparative transcriptomics reveals patterns of selection in domesticated and wild tomato. Proc. Natl. Acad. Sci. U.S.A. 2013, 110:E2655-E2662.
70. Nabholz B., et al. Transcriptome population genomics reveals severe bottleneck and domestication cost in the African rice (Oryza glaberrima). Mol. Ecol. 2014, 23:2210-2227.
71. Cao J., et al. Whole-genome sequencing of multiple Arabidopsis thaliana populations. Nat. Genet. 2011, 43:956-963.
72. Elyashiv E., et al. Shifts in the intensity of purifying selection: an analysis of genome-wide polymorphism data from two closely related yeast species. Genome Res. 2010, 20:1558-1573.
73. Hill W.G., Robertson A. The effect of linkage on limits to artificial selection. Genet. Res. 1966, 8:269-294.
74. Hussin J.G., et al. Recombination affects accumulation of damaging and disease-associated mutations in human populations. Nat. Genet. 2015, 47:400-404.
75. Bullaughey K., et al. No effect of recombination on the efficacy of natural selection in primates. Genome Res. 2008, 18:544-554.
76. Gossmann T., et al. Highly variable recombinational landscape modulates efficacy of natural selection in birds. Genome Biol. Evol. 2014, 6:2061-2075.
77. Campos J.L., et al. The relation between recombination rate and patterns of molecular evolution and variation in Drosophila melanogaster. Mol. Biol. Evol. 2014, 31:1010-1028.
78. Burgarella C., et al. Molecular evolution of freshwater snails with contrasting mating systems. Mol. Biol. Evol. 2015, 32:2403-2416.
79. Brandvain Y., et al. Genomic identification of founding haplotypes reveals the history of the selfing species, Capsella rubella. PLoS Genet. 2013, 9:e1003754.
80. Qiu S., et al. Reduced efficacy of natural selection on codon usage bias in selfing Arabidopsis and Capsella species. Genome Biol. Evol. 2011, 3:868-880.
81. Pellino M., et al. Asexual genome evolution in the apomictic Ranunculus auricomus complex: examining the effects of hybridization and mutation accumulation. Mol. Ecol. 2013, 22:5908-5921.
82. Mank J.E., et al. Effective population size and the Faster-X effect: empirical results and their interpretation. Evolution 2010, 64:663-674.
83. Edmonds C.A., et al. Mutations arising in the wave front of an expanding population. Proc. Natl. Acad. Sci. U.S.A. 2004, 101:975-979.
84. Excoffier L., Ray N. Surfing during population expansions promotes genetic revolutions and structuration. Trends Ecol. Evol. 2008, 23:347-351.
85. Hallatschek O., Nelson D.R. Life at the front of an expanding population. Evolution 2010, 64:193-206.
86. Klopfstein S., et al. The fate of mutations surfing on the wave of a range expansion. Mol. Biol. Evol. 2006, 23:482-490.
87. Lehe R., et al. The rate of beneficial mutations surfing on the wave of a range expansion. PLoS Comput. Biol. 2012, 8:e1002447.
88. Moreau C., et al. Deep human genealogies reveal a selective advantage to be on an expanding wave front. Science 2011, 334:1148-1150.
89. Slatkin M., Excoffier L. Serial founder effects during range expansion: a spatial analog of genetic drift. Genetics 2012, 191:171-181.
90. Travis J.M.J., et al. Deleterious mutations can surf to high densities on the wave front of an expanding population. Mol. Biol. Evol. 2007, 24:2334-2343.
91. Eyre-Walker A., Keightley P.D. The distribution of fitness effects of new mutations. Nat. Rev. Genet. 2007, 8:610-618.
92. Eyre-Walker A., Keightley P.D. Estimating the rate of adaptive molecular evolution in the presence of slightly deleterious mutations and population size change. Mol. Biol. Evol. 2009, 26:2097-2108.
93. Eyre-Walker A., et al. The distribution of fitness effects of new deleterious amino acid mutations in humans. Genetics 2006, 173:891-900.
94. Kousathanas A., Keightley P.D. A comparison of models to infer the distribution of fitness effects of new mutations. Genetics 2013, 193:1197-1208.