Genotype to Phenotype Mapping and the Fitness Landscape of the E. coli lac Promoter

PLoS ONE

Volumn 8, Issue 5, 2013, Pages

  Otwinowski, Jakub ^a,b   Nemenman, Ilya ^a  

^a EMORY UNIVERSITY   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CYCLIC AMP BINDING PROTEIN; RNA POLYMERASE;

ARTICLE; BASE PAIRING; BINDING SITE; CONTROLLED STUDY; EPISTASIS; ESCHERICHIA COLI; GENE; GENE CONTROL; GENE EXPRESSION REGULATION; GENE FUNCTION; GENE IDENTIFICATION; GENE INTERACTION; GENE LOCUS; GENE MAPPING; GENETIC TRANSCRIPTION; GENOTYPE PHENOTYPE CORRELATION; HIGH THROUGHPUT SEQUENCING; LAC GENE; MATHEMATICAL MODEL; MUTATIONAL ANALYSIS; NONHUMAN; PROMOTER REGION; PROTEIN BINDING; REPORTER GENE; TRANSCRIPTION REGULATION; WILD TYPE; ALGORITHM; BIOLOGICAL MODEL; GENETIC ASSOCIATION; GENETICS; GENOTYPE; LACTOSE OPERON; REPRODUCTIVE FITNESS;

ALGORITHMS; EPISTASIS, GENETIC; ESCHERICHIA COLI; GENE EXPRESSION REGULATION, BACTERIAL; GENETIC ASSOCIATION STUDIES; GENETIC FITNESS; GENOTYPE; LAC OPERON; MODELS, GENETIC; PROMOTER REGIONS, GENETIC;

EID: 84877080561     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0061570     Document Type: Article

References (56)

1. Goldenfeld N, Woese C, (2011) Life is Physics: Evolution as a Collective Phenomenon Far From Equilibrium. Ann Rev Cond Mat Phys 2: 375-399.
2. Wright S, (1932) The roles of mutation, inbreeding, crossbreeding and selection in evolution. Proc 6th Int Congress Genetics 1: 356-365.
3. Szendro I, Schenk M, Franke J, Krug J, de Visser J, (2012) Quantitative analyses of empirical fitness landscapes. Arxiv preprint arXiv 12024378.
4. Chou H, Chiu H, Delaney N, Segrè D, Marx C, (2011) Diminishing returns epistasis among beneficial mutations decelerates adaptation. Science 332: 1190-1192.
5. Franke J, Klözer A, de Visser J, Krug J, (2011) Evolutionary accessibility of mutational pathways. PLoS Comp Biol 7: e1002134.
6. Khan AI, Dinh DM, Schneider D, Lenski RE, Cooper TF, (2011) Negative epistasis between beneficial mutations in an evolving bacterial population. Science 332: 1193-6.
7. Weinreich D, Delaney N, Depristo M, Hartl D, (2006) Darwinian evolution can follow only very few mutational paths to fitter proteins. Science 312: 111-114.
8. Hall DW, Agan M, Pope SC, (2010) Fitness epistasis among 6 biosynthetic loci in the budding yeast Saccharomyces cerevisiae. J Heredity 101: S75-84.
9. da Silva J, Coetzer M, Nedellec R, Pastore C, Mosier DE, (2010) Fitness epistasis and constraints on adaptation in a human immunodeficiency virus type 1 protein region. Genetics 185: 293-303.
10. Lunzer M, Miller SP, Felsheim R, Dean AM, (2005) The biochemical architecture of an ancient adaptive landscape. Science 310: 499-501.
11. Kingsolver JG, Hoekstra HE, Hoekstra JM, Berrigan D, Vignieri SN, et al. (2001) The strength of phenotypic selection in natural populations. American Naturalist 157: 245-61.
12. Shaw RG, Geyer CJ, (2010) Inferring fitness landscapes. Evolution 64: 2510-20.
13. Poelwijk FJ, Kiviet DJ, Weinreich DM, Tans SJ, (2007) Empirical fitness landscapes reveal accessible evolutionary paths. Nature 445: 383-6.
14. Segrè D, Deluna A, Church GM, Kishony R, (2005) Modular epistasis in yeast metabolism. Nature Genet 37: 77-83.
15. Costanzo M, Baryshnikova A, Bellay J, Kim Y, Spear ED, et al. (2010) The genetic landscape of a cell. Science 327: 425-31.
16. Moore JH, (2005) A global view of epistasis. Nature Genet 37: 13-4.
17. Phillips PC, (2008) Epistasis-the essential role of gene interactions in the structure and evolution of genetic systems. Nature Rev Genet 9: 855-67.
18. Stark C, Breitkreutz BJ, Chatr-Aryamontri A, Boucher L, Oughtred R, et al. (2011) The BioGRID Interaction Database: 2011 update. Nucl Acids Res 39: D698-704.
19. Baryshnikova A, Costanzo M, Kim Y, Ding H, Koh J, et al. (2010) Quantitative analysis of fitness and genetic interactions in yeast on a genome scale. Nature Methods 7: 1017-24.
20. Liu BH (1997) Statistical Genomics: Linkage, Mapping, and QTL Analysis. CRC Press.
21. Brem R, Kruglyak L, (2005) The landscape of genetic complexity across 5,700 gene expression traits in yeast. Proc Natl Acad Sci USA 102: 1572-1577.
22. Shendure J, Ji H, (2008) Next-generation DNA sequencing. Nature Biotech 26: 1135-1145.
23. Pitt JN, Ferré-D'Amaré AR, (2010) Rapid construction of empirical RNA fitness landscapes. Science 330: 376-9.
24. Mora T, Walczak AM, Bialek W, Callan CG, (2010) Maximum entropy models for antibody diversity. Proc Natl Acad Sci USA 107: 5405-10.
25. Hinkley T, Martins JA, Chappey C, Haddad M, Stawiski E, et al. (2011) A systems analysis of mutational effects in HIV-1 protease and reverse transcriptase. Nature Genet 43: 487-9.
26. Kouyos RD, Leventhal GE, Hinkley T, Haddad M, Whitcomb JM, et al. (2012) Exploring the Complexity of the HIV-1 Fitness Landscape. PLoS Genetics 8: e1002551.
27. Kinney JB, Murugan A, Callan CG, Cox EC, (2010) Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence. Proc Natl Acad Sci USA 107: 9158-9163.
28. Berg OG, von Hippel PH, (1988) Selection of DNA binding sites by regulatory proteins. II. The binding specificity of cyclic AMP receptor protein to recognition sites. J Mol Biol 200: 709-23.
29. Harley CB, Reynolds RP, (1987) Analysis of E. coli promoter sequences. Nucl Acids Res 15: 2343-2361.
30. Wall M, Markowitz D, Rosner J, Martin R, (2009) Model of transcriptional activation by MarA in Escherichia coli. PLoS Comput Biol 5: e1000614.
31. Garcia H, Sanchez A, Boedicker J, Osborne M, Gelles J, et al. (2012) Operator sequence alters gene expression independently of transcription factor occupancy in bacteria. Cell Rep 2: 150-161.
32. Kuhlman T, Zhang Z, Saier MH, Hwa T, (2007) Combinatorial transcriptional control of the lactose operon of Escherichia coli. Proc Natl Acad Sci USA 104: 6043-8.
33. Berg O, von Hippel P, (1987) Selection of dna binding sites by regulatory proteins. statistical-mechanical theory and application to operators and promoters. J Mol Biol 193: 723-750.
34. Djordjevic M, Sengupta AM, Shraiman BI, (2003) A biophysical approach to transcription factor binding site discovery. Genome Res 13: 2381-90.
35. Bauer AL, Hlavacek WS, Unkefer PJ, Mu F, (2010) Using Sequence-Specific Chemical and Structural Properties of DNA to Predict Transcription Factor Binding Sites. PLoS Comp Biol 6: 13.
36. Poelwijk FJ, Tanase-Nicola S, Kiviet DJ, Tans SJ, (2011) Reciprocal sign epistasis is a necessary condition for multi-peaked fitness landscapes. J Theor Biol 272: 141-4.
37. Dekel E, Alon U, (2005) Optimality and evolutionary tuning of the expression level of a protein. Nature 436: 588-592.
38. Perfeito L, Ghozzi S, Berg J, Schnetz K, Lässig M, (2011) Nonlinear fitness landscape of a molecular pathway. PLoS Genetics 7: 1-10.
39. Gerland U, Hwa T, (2002) On the selection and evolution of regulatory DNA motifs. J Mol Evol 55: 386-400.
40. Berg J, Willmann S, Lässig M, (2004) Adaptive evolution of transcription factor binding sites. BMC Evol Biol 4: 42.
41. Mustonen V, Lässig M, (2005) Evolutionary population genetics of promoters: predicting binding sites and functional phylogenies. Proc Natl Acad Sci USA 102: 15936-41.
42. Mustonen V, Kinney J, Callan CG, Lässig M, (2008) Energy-dependent fitness: a quantitative model for the evolution of yeast transcription factor binding sites. Proc Natl Acad Sci USA 105: 12376-81.
43. Goldenfeld N, Kadanoff L, (1999) Simple lessons from complexity. Science 284: 87-89.
44. Schneidman E, Berry M, Segev R, Bialek W, (2006) Weak pairwise correlations imply strongly correlated network states in a neural population. Nature 440: 1007-1012.
45. Tkacik G, Schneidman E, Berry M, Bialek W (2006) Ising models for networks of real neurons. ArXiv:q-bio/0611072arXiv.
46. Tang A, Jackson J, Hobbs J, Chen W, Smith JL, et al. (2008) A maximum entropy model applied to spatial and temporal correlations from cortical networks in vitro. J Neurosci 28: 505-518.
47. Cocco S, Leibler S, Monasson R, (2009) Neuronal couplings between retinal ganglion cells inferred by efficient inverse statistical physics methods. Proc Natl Acad Sci USA 106: 14058-14062.
48. Ohiorhenuan I, Mechler F, Purpura K, Schmid A, Hu Q, et al. (2010) Sparse coding and high-order correlations in fine-scale cortical networks. Nature 466: 617-621.
49. Margolin A, Nemenman I, Basso K, Wiggins C, Stolovitzky G, et al. (2006) ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinf 7: S7.
50. Wang K, Saito M, Bisikirska B, Alvarez WM, and Lim, et al. (2009) Genome-wide identification of post-translational modulators of transcription factor activity in human B cells. Nat Biotechnol 27: 829-839.
51. Margolin A, Wang K, Califano A, Nemenman I, (2010) Multivariate dependence and genetic networks inference. IET Syst Biol 4: 428-440.
52. Green WH (2003) Econometric Analysis. Prentice Hall.
53. Sharpee TO, Sugihara H, Kurgansky AV, Rebrik SP, Stryker MP, et al. (2006) Adaptive filtering enhances information transmission in visual cortex. Nature 439: 936-42.
54. MacKay DJC (2003) Information Theory, Inference, and Learning Algorithms. Cambridge University Press.
55. Tibshirani R, (1996) Regression shrinkage and selection via the lasso. J R Stat Soc Ser B 58: 267-288.
56. Friedman J, Hastie T, Tibshirani R (2010) Regularization Paths for Generalized Linear Models via Coordinate Descent. J Stat Software 33.