Adaptation to High Ethanol Reveals Complex Evolutionary Pathways
Organisms can evolve resistance to specific stress factors, which allows them to thrive in environments where non-adapted organisms fail to grow. However, the molecular mechanisms that underlie adaptation to complex stress factors that interfere with basic cellular processes are poorly understood. In this study, we reveal how yeast populations adapt to high ethanol concentrations, an ecologically and industrially relevant stress that is still poorly understood. We exposed six independent populations of genetically identical yeast cells to gradually increasing ethanol levels, and we monitored the changes in their DNA sequence over a two-year period. Together with novel computational analyses, we could identify the mutational dynamics and molecular mechanisms underlying increased ethanol resistance. Our results show how adaptation to high ethanol is complex and can be reached through different mutational pathways. Together, our study offers a detailed picture of how populations adapt to a complex continuous stress and identifies several mutations that increase ethanol resistance, which opens new routes to obtain superior biofuel yeast strains.
Vyšlo v časopise:
Adaptation to High Ethanol Reveals Complex Evolutionary Pathways. PLoS Genet 11(11): e32767. doi:10.1371/journal.pgen.1005635
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pgen.1005635
Souhrn
Organisms can evolve resistance to specific stress factors, which allows them to thrive in environments where non-adapted organisms fail to grow. However, the molecular mechanisms that underlie adaptation to complex stress factors that interfere with basic cellular processes are poorly understood. In this study, we reveal how yeast populations adapt to high ethanol concentrations, an ecologically and industrially relevant stress that is still poorly understood. We exposed six independent populations of genetically identical yeast cells to gradually increasing ethanol levels, and we monitored the changes in their DNA sequence over a two-year period. Together with novel computational analyses, we could identify the mutational dynamics and molecular mechanisms underlying increased ethanol resistance. Our results show how adaptation to high ethanol is complex and can be reached through different mutational pathways. Together, our study offers a detailed picture of how populations adapt to a complex continuous stress and identifies several mutations that increase ethanol resistance, which opens new routes to obtain superior biofuel yeast strains.
Zdroje
1. Steensels J, Verstrepen KJ (2014) Taming wild yeast: potential of conventional and nonconventional yeasts in industrial fermentations. Annu Rev Microbiol 68: 61–80. doi: 10.1146/annurev-micro-091213-113025 24773331
2. Snoek T, Picca Nicolino M, Van den Bremt S, Mertens S, Saels V, et al. (2015) Large-scale robot-assisted genome shuffling yields industrial Saccharomyces cerevisiae yeasts with increased ethanol tolerance. Biotechnology for biofuels in press.
3. Mukherjee V, Steensels J, Lievens B, Van de Voorde I, Verplaetse A, et al. (2014) Phenotypic evaluation of natural and industrial Saccharomyces yeasts for different traits desirable in industrial bioethanol production. Appl Microbiol Biotechnol 98: 9483–9498. doi: 10.1007/s00253-014-6090-z 25267160
4. Alexandre H, Ansanay-Galeote V, Dequin S, Blondin B (2001) Global gene expression during short-term ethanol stress in Saccharomyces cerevisiae. FEBS Lett 498: 98–103. 11389906
5. Fujita K, Matsuyama A, Kobayashi Y, Iwahashi H (2006) The genome-wide screening of yeast deletion mutants to identify the genes required for tolerance to ethanol and other alcohols. FEMS Yeast Res 6: 744–750. 16879425
6. Haft RJ, Keating DH, Schwaegler T, Schwalbach MS, Vinokur J, et al. (2014) Correcting direct effects of ethanol on translation and transcription machinery confers ethanol tolerance in bacteria. Proc Natl Acad Sci U S A 111: E2576–2585. doi: 10.1073/pnas.1401853111 24927582
7. Horinouchi T, Tamaoka K, Furusawa C, Ono N, Suzuki S, et al. (2010) Transcriptome analysis of parallel-evolved Escherichia coli strains under ethanol stress. BMC Genomics 11: 579. doi: 10.1186/1471-2164-11-579 20955615
8. Lewis JA, Broman AT, Will J, Gasch AP (2014) Genetic architecture of ethanol-responsive transcriptome variation in Saccharomyces cerevisiae strains. Genetics 198: 369–382. doi: 10.1534/genetics.114.167429 24970865
9. Lewis JA, Elkon IM, McGee MA, Higbee AJ, Gasch AP (2010) Exploiting natural variation in Saccharomyces cerevisiae to identify genes for increased ethanol resistance. Genetics 186: 1197–1205. doi: 10.1534/genetics.110.121871 20855568
10. van Voorst F, Houghton-Larsen J, Jonson L, Kielland-Brandt MC, Brandt A (2006) Genome-wide identification of genes required for growth of Saccharomyces cerevisiae under ethanol stress. Yeast 23: 351–359. 16598687
11. Ehrenreich IM, Torabi N, Jia Y, Kent J, Martis S, et al. (2010) Dissection of genetically complex traits with extremely large pools of yeast segregants. Nature 464: 1039–1042. doi: 10.1038/nature08923 20393561
12. Hu XH, Wang MH, Tan T, Li JR, Yang H, et al. (2007) Genetic dissection of ethanol tolerance in the budding yeast Saccharomyces cerevisiae. Genetics 175: 1479–1487. 17194785
13. Swinnen S, Schaerlaekens K, Pais T, Claesen J, Hubmann G, et al. (2012) Identification of novel causative genes determining the complex trait of high ethanol tolerance in yeast using pooled-segregant whole-genome sequence analysis. Genome Res 22: 975–984. doi: 10.1101/gr.131698.111 22399573
14. Wohlbach DJ, Rovinskiy N, Lewis JA, Sardi M, Schackwitz WS, et al. (2014) Comparative genomics of Saccharomyces cerevisiae natural isolates for bioenergy production. Genome Biol Evol 6: 2557–2566. 25364804
15. D'Amore T, Panchal CJ, Russell I, Stewart GG (1990) A study of ethanol tolerance in yeast. Crit Rev Biotechnol 9: 287–304. 2178780
16. Ding J, Huang X, Zhang L, Zhao N, Yang D, et al. (2009) Tolerance and stress response to ethanol in the yeast Saccharomyces cerevisiae. Appl Microbiol Biotechnol 85: 253–263. doi: 10.1007/s00253-009-2223-1 19756577
17. Ma M, Liu ZL (2010) Mechanisms of ethanol tolerance in Saccharomyces cerevisiae. Appl Microbiol Biotechnol 87: 829–845. doi: 10.1007/s00253-010-2594-3 20464391
18. Avrahami-Moyal L, Engelberg D, Wenger JW, Sherlock G, Braun S (2012) Turbidostat culture of Saccharomyces cerevisiae W303-1A under selective pressure elicited by ethanol selects for mutations in SSD1 and UTH1. FEMS Yeast Res 12: 521–533. doi: 10.1111/j.1567-1364.2012.00803.x 22443114
19. Brown SW, Oliver SG (1982) Isolation of ethanol-tolerant mutants of yeast by continuous selection. Eur J Appl Microbiol Biotechnol 16: 119–122.
20. Goodarzi H, Bennett BD, Amini S, Reaves ML, Hottes AK, et al. (2010) Regulatory and metabolic rewiring during laboratory evolution of ethanol tolerance in E. coli. Mol Syst Biol 6: 378. doi: 10.1038/msb.2010.33 20531407
21. Stanley D, Fraser S, Chambers PJ, Rogers P, Stanley GA (2010) Generation and characterisation of stable ethanol-tolerant mutants of Saccharomyces cerevisiae. J Ind Microbiol Biotechnol 37: 139–149. doi: 10.1007/s10295-009-0655-3 19902282
22. Cakar ZP, Seker UO, Tamerler C, Sonderegger M, Sauer U (2005) Evolutionary engineering of multiple-stress resistant Saccharomyces cerevisiae. FEMS Yeast Res 5: 569–578. 15780656
23. Barrick JE, Yu DS, Yoon SH, Jeong H, Oh TK, et al. (2009) Genome evolution and adaptation in a long-term experiment with Escherichia coli. Nature 461: 1243–1247. doi: 10.1038/nature08480 19838166
24. Gresham D, Desai MM, Tucker CM, Jenq HT, Pai DA, et al. (2008) The repertoire and dynamics of evolutionary adaptations to controlled nutrient-limited environments in yeast. PLoS Genet 4: e1000303. doi: 10.1371/journal.pgen.1000303 19079573
25. Hong J, Gresham D (2014) Molecular specificity, convergence and constraint shape adaptive evolution in nutrient-poor environments. PLoS Genet 10: e1004041. doi: 10.1371/journal.pgen.1004041 24415948
26. Oz T, Guvenek A, Yildiz S, Karaboga E, Tamer YT, et al. (2014) Strength of selection pressure is an important parameter contributing to the complexity of antibiotic resistance evolution. Mol Biol Evol 31: 2387–2401. doi: 10.1093/molbev/msu191 24962091
27. Toprak E, Veres A, Michel JB, Chait R, Hartl DL, et al. (2011) Evolutionary paths to antibiotic resistance under dynamically sustained drug selection. Nat Genet 44: 101–105. doi: 10.1038/ng.1034 22179135
28. Yona AH, Manor YS, Herbst RH, Romano GH, Mitchell A, et al. (2012) Chromosomal duplication is a transient evolutionary solution to stress. Proc Natl Acad Sci U S A 109: 21010–21015. doi: 10.1073/pnas.1211150109 23197825
29. Barrick JE, Lenski RE (2009) Genome-wide mutational diversity in an evolving population of Escherichia coli. Cold Spring Harb Symp Quant Biol 74: 119–129. doi: 10.1101/sqb.2009.74.018 19776167
30. Herron MD, Doebeli M (2013) Parallel evolutionary dynamics of adaptive diversification in Escherichia coli. PLoS Biol 11: e1001490. doi: 10.1371/journal.pbio.1001490 23431270
31. Kvitek DJ, Sherlock G (2013) Whole genome, whole population sequencing reveals that loss of signaling networks is the major adaptive strategy in a constant environment. PLoS Genet 9: e1003972. doi: 10.1371/journal.pgen.1003972 24278038
32. Lang GI, Rice DP, Hickman MJ, Sodergren E, Weinstock GM, et al. (2013) Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations. Nature 500: 571–574. doi: 10.1038/nature12344 23873039
33. Payen C, Di Rienzi SC, Ong GT, Pogachar JL, Sanchez JC, et al. (2014) The dynamics of diverse segmental amplifications in populations of Saccharomyces cerevisiae adapting to strong selection. G3 (Bethesda) 4: 399–409.
34. Gerrish PJ, Lenski RE (1998) The fate of competing beneficial mutations in an asexual population. Genetica 102–103: 127–144. 9720276
35. Kao KC, Sherlock G (2008) Molecular characterization of clonal interference during adaptive evolution in asexual populations of Saccharomyces cerevisiae. Nat Genet 40: 1499–1504. doi: 10.1038/ng.280 19029899
36. Gerstein AC, Chun HJ, Grant A, Otto SP (2006) Genomic convergence toward diploidy in Saccharomyces cerevisiae. PLoS Genet 2: e145. 17002497
37. Kellis M, Birren BW, Lander ES (2004) Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae. Nature 428: 617–624. 15004568
38. Wolfe KH, Shields DC (1997) Molecular evidence for an ancient duplication of the entire yeast genome. Nature 387: 708–713. 9192896
39. Fawcett JA, Maere S, Van de Peer Y (2009) Plants with double genomes might have had a better chance to survive the Cretaceous-Tertiary extinction event. Proc Natl Acad Sci U S A 106: 5737–5742. doi: 10.1073/pnas.0900906106 19325131
40. Selmecki AM, Maruvka YE, Richmond PA, Guillet M, Shoresh N, et al. (2015) Polyploidy can drive rapid adaptation in yeast. Nature 519: 349–352. doi: 10.1038/nature14187 25731168
41. Galitski T, Saldanha AJ, Styles CA, Lander ES, Fink GR (1999) Ploidy regulation of gene expression. Science 285: 251–254. 10398601
42. Ohno S (1970) Evolution by gene duplication. Berlin: Springer-Verlag.
43. Semon M, Wolfe KH (2007) Consequences of genome duplication. Curr Opin Genet Dev 17: 505–512. 18006297
44. Andalis AA, Storchova Z, Styles C, Galitski T, Pellman D, et al. (2004) Defects arising from whole-genome duplications in Saccharomyces cerevisiae. Genetics 167: 1109–1121. 15280227
45. Song K, Lu P, Tang K, Osborn TC (1995) Rapid genome change in synthetic polyploids of Brassica and its implications for polyploid evolution. Proc Natl Acad Sci U S A 92: 7719–7723. 7644483
46. Storchova Z, Breneman A, Cande J, Dunn J, Burbank K, et al. (2006) Genome-wide genetic analysis of polyploidy in yeast. Nature 443: 541–547. 17024086
47. Anderson JB, Sirjusingh C, Ricker N (2004) Haploidy, diploidy and evolution of antifungal drug resistance in Saccharomyces cerevisiae. Genetics 168: 1915–1923. 15371350
48. Gerstein AC, Cleathero LA, Mandegar MA, Otto SP (2011) Haploids adapt faster than diploids across a range of environments. J Evol Biol 24: 531–540. doi: 10.1111/j.1420-9101.2010.02188.x 21159002
49. Zeyl C, Vanderford T, Carter M (2003) An evolutionary advantage of haploidy in large yeast populations. Science 299: 555–558. 12543972
50. Lynch M, Sung W, Morris K, Coffey N, Landry CR, et al. (2008) A genome-wide view of the spectrum of spontaneous mutations in yeast. Proc Natl Acad Sci U S A 105: 9272–9277. doi: 10.1073/pnas.0803466105 18583475
51. Giraud A, Matic I, Tenaillon O, Clara A, Radman M, et al. (2001) Costs and benefits of high mutation rates: adaptive evolution of bacteria in the mouse gut. Science 291: 2606–2608. 11283373
52. McDonald MJ, Hsieh YY, Yu YH, Chang SL, Leu JY (2012) The evolution of low mutation rates in experimental mutator populations of Saccharomyces cerevisiae. Curr Biol 22: 1235–1240. doi: 10.1016/j.cub.2012.04.056 22727704
53. Pal C, Macia MD, Oliver A, Schachar I, Buckling A (2007) Coevolution with viruses drives the evolution of bacterial mutation rates. Nature 450: 1079–1081. 18059461
54. Sniegowski PD, Gerrish PJ, Lenski RE (1997) Evolution of high mutation rates in experimental populations of E. coli. Nature 387: 703–705. 9192894
55. Drotschmann K, Clark AB, Tran HT, Resnick MA, Gordenin DA, et al. (1999) Mutator phenotypes of yeast strains heterozygous for mutations in the MSH2 gene. Proc Natl Acad Sci U S A 96: 2970–2975. 10077621
56. Lang GI, Parsons L, Gammie AE (2013) Mutation rates, spectra, and genome-wide distribution of spontaneous mutations in mismatch repair deficient yeast. G3 (Bethesda) 3: 1453–1465.
57. Huang da W, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4: 44–57. doi: 10.1038/nprot.2008.211 19131956
58. De Maeyer D, Renkens J, Cloots L, De Raedt L, Marchal K (2013) PheNetic: network-based interpretation of unstructured gene lists in E. coli. Mol Biosyst 9: 1594–1603. doi: 10.1039/c3mb25551d 23591551
59. De Maeyer D, Weytjens B, Renkens J, De Raedt L, Marchal K (2015) PheNetic: network-based interpretation of molecular profiling data. Nucleic Acids Res.
60. Kubota S, Takeo I, Kume K, Kanai M, Shitamukai A, et al. (2004) Effect of ethanol on cell growth of budding yeast: genes that are important for cell growth in the presence of ethanol. Biosci Biotechnol Biochem 68: 968–972. 15118337
61. Gasch AP, Spellman PT, Kao CM, Carmel-Harel O, Eisen MB, et al. (2000) Genomic expression programs in the response of yeast cells to environmental changes. Mol Biol Cell 11: 4241–4257. 11102521
62. Lu C, Brauer MJ, Botstein D (2009) Slow growth induces heat-shock resistance in normal and respiratory-deficient yeast. Mol Biol Cell 20: 891–903. doi: 10.1091/mbc.E08-08-0852 19056679
63. Brauer MJ, Huttenhower C, Airoldi EM, Rosenstein R, Matese JC, et al. (2008) Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast. Mol Biol Cell 19: 352–367. 17959824
64. DeLuna A, Vetsigian K, Shoresh N, Hegreness M, Colon-Gonzalez M, et al. (2008) Exposing the fitness contribution of duplicated genes. Nat Genet 40: 676–681. doi: 10.1038/ng.123 18408719
65. Bonangelino CJ, Chavez EM, Bonifacino JS (2002) Genomic screen for vacuolar protein sorting genes in Saccharomyces cerevisiae. Mol Biol Cell 13: 2486–2501. 12134085
66. Duitama J, Sanchez-Rodriguez A, Goovaerts A, Pulido-Tamayo S, Hubmann G, et al. (2014) Improved linkage analysis of Quantitative Trait Loci using bulk segregants unveils a novel determinant of high ethanol tolerance in yeast. BMC Genomics 15: 207. doi: 10.1186/1471-2164-15-207 24640961
67. Teixeira MC, Raposo LR, Mira NP, Lourenco AB, Sa-Correia I (2009) Genome-wide identification of Saccharomyces cerevisiae genes required for maximal tolerance to ethanol. Appl Environ Microbiol 75: 5761–5772. doi: 10.1128/AEM.00845-09 19633105
68. Steensels J, Snoek T, Meersman E, Nicolino MP, Voordeckers K, et al. (2014) Improving industrial yeast strains: exploiting natural and artificial diversity. FEMS Microbiol Rev 38: 947–995. doi: 10.1111/1574-6976.12073 24724938
69. Dunham MJ, Badrane H, Ferea T, Adams J, Brown PO, et al. (2002) Characteristic genome rearrangements in experimental evolution of Saccharomyces cerevisiae. Proc Natl Acad Sci U S A 99: 16144–16149. 12446845
70. Rancati G, Pavelka N, Fleharty B, Noll A, Trimble R, et al. (2008) Aneuploidy underlies rapid adaptive evolution of yeast cells deprived of a conserved cytokinesis motor. Cell 135: 879–893. doi: 10.1016/j.cell.2008.09.039 19041751
71. Wildenberg GA, Murray AW (2014) Evolving a 24-hr oscillator in budding yeast. Elife 3.
72. Gerstein AC, Otto SP (2012) Cryptic fitness advantage: diploids invade haploid populations despite lacking any apparent advantage as measured by standard fitness assays. PLoS One 6: e26599.
73. Wu CY, Rolfe PA, Gifford DK, Fink GR (2010) Control of transcription by cell size. PLoS Biol 8: e1000523. doi: 10.1371/journal.pbio.1000523 21072241
74. Zorgo E, Chwialkowska K, Gjuvsland AB, Garre E, Sunnerhagen P, et al. (2013) Ancient evolutionary trade-offs between yeast ploidy states. PLoS Genet 9: e1003388. doi: 10.1371/journal.pgen.1003388 23555297
75. Pavelka N, Rancati G, Zhu J, Bradford WD, Saraf A, et al. (2010) Aneuploidy confers quantitative proteome changes and phenotypic variation in budding yeast. Nature 468: 321–325. doi: 10.1038/nature09529 20962780
76. Torres EM, Sokolsky T, Tucker CM, Chan LY, Boselli M, et al. (2007) Effects of aneuploidy on cellular physiology and cell division in haploid yeast. Science 317: 916–924. 17702937
77. Sunshine AB, Payen C, Ong GT, Liachko I, Tan KM, et al. (2015) The fitness consequences of aneuploidy are driven by condition-dependent gene effects. PLoS Biol 13: e1002155. doi: 10.1371/journal.pbio.1002155 26011532
78. Pavelka N, Rancati G, Li R (2010) Dr Jekyll and Mr Hyde: role of aneuploidy in cellular adaptation and cancer. Curr Opin Cell Biol 22: 809–815. doi: 10.1016/j.ceb.2010.06.003 20655187
79. Sheltzer JM, Amon A (2011) The aneuploidy paradox: costs and benefits of an incorrect karyotype. Trends Genet 27: 446–453. doi: 10.1016/j.tig.2011.07.003 21872963
80. Sheltzer JM, Blank HM, Pfau SJ, Tange Y, George BM, et al. (2011) Aneuploidy drives genomic instability in yeast. Science 333: 1026–1030. doi: 10.1126/science.1206412 21852501
81. Koschwanez JH, Foster KR, Murray AW (2011) Sucrose utilization in budding yeast as a model for the origin of undifferentiated multicellularity. PLoS Biol 9: e1001122. doi: 10.1371/journal.pbio.1001122 21857801
82. Wenger JW, Piotrowski J, Nagarajan S, Chiotti K, Sherlock G, et al. (2011) Hunger artists: yeast adapted to carbon limitation show trade-offs under carbon sufficiency. PLoS Genet 7: e1002202. doi: 10.1371/journal.pgen.1002202 21829391
83. Ihmels J, Bergmann S, Gerami-Nejad M, Yanai I, McClellan M, et al. (2005) Rewiring of the yeast transcriptional network through the evolution of motif usage. Science 309: 938–940. 16081737
84. Rozpedowska E, Hellborg L, Ishchuk OP, Orhan F, Galafassi S, et al. (2011) Parallel evolution of the make-accumulate-consume strategy in Saccharomyces and Dekkera yeasts. Nat Commun 2: 302. doi: 10.1038/ncomms1305 21556056
85. Thomson JM, Gaucher EA, Burgan MF, De Kee DW, Li T, et al. (2005) Resurrecting ancestral alcohol dehydrogenases from yeast. Nat Genet 37: 630–635. 15864308
86. Brachmann CB, Davies A, Cost GJ, Caputo E, Li J, et al. (1998) Designer deletion strains derived from Saccharomyces cerevisiae S288C: a useful set of strains and plasmids for PCR-mediated gene disruption and other applications. Yeast 14: 115–132. 9483801
87. Guldener U, Heck S, Fielder T, Beinhauer J, Hegemann JH (1996) A new efficient gene disruption cassette for repeated use in budding yeast. Nucleic Acids Res 24: 2519–2524. 8692690
88. Gueldener U, Heinisch J, Koehler GJ, Voss D, Hegemann JH (2002) A second set of loxP marker cassettes for Cre-mediated multiple gene knockouts in budding yeast. Nucleic Acids Res 30: e23. 11884642
89. Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25: 1754–1760. doi: 10.1093/bioinformatics/btp324 19451168
90. DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, et al. (2011) A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet 43: 491–498. doi: 10.1038/ng.806 21478889
91. Cingolani P, Platts A, Wang le L, Coon M, Nguyen T, et al. (2012) A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 6: 80–92.
92. Huang da W, Sherman BT, Lempicki RA (2009) Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 37: 1–13. doi: 10.1093/nar/gkn923 19033363
93. Kanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28: 27–30. 10592173
94. Jensen LJ, Kuhn M, Stark M, Chaffron S, Creevey C, et al. (2009) STRING 8—a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 37: D412–416. doi: 10.1093/nar/gkn760 18940858
95. Teixeira MC, Monteiro P, Jain P, Tenreiro S, Fernandes AR, et al. (2006) The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Nucleic Acids Res 34: D446–451. 16381908
96. Maere S, Heymans K, Kuiper M (2005) BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21: 3448–3449. 15972284
Štítky
Genetika Reprodukčná medicínaČlánok vyšiel v časopise
PLOS Genetics
2015 Číslo 11
- Je „freeze-all“ pro všechny? Odborníci na fertilitu diskutovali na virtuálním summitu
- Gynekologové a odborníci na reprodukční medicínu se sejdou na prvním virtuálním summitu
Najčítanejšie v tomto čísle
- UFBP1, a Key Component of the Ufm1 Conjugation System, Is Essential for Ufmylation-Mediated Regulation of Erythroid Development
- Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis
- Ernst Rüdin’s Unpublished 1922-1925 Study “Inheritance of Manic-Depressive Insanity”: Genetic Research Findings Subordinated to Eugenic Ideology
- Genetic Interactions Implicating Postreplicative Repair in Okazaki Fragment Processing