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Genetic Influences on Translation in Yeast


Individuals in a species differ from each other in many ways. For many traits, a fraction of this variation is genetic—it is caused by DNA sequence variants in the genome of each individual. Some of these variants influence traits by altering how much certain genes are expressed, i.e. how many mRNA and protein molecules are made in different individuals. Surprisingly, earlier work has found that the effects of genetic variants on mRNA and protein levels for the same genes appear to be very different. Many variants appeared to influence only mRNA (but not protein) levels, and vice versa. In this paper, we studied this question by using a technique called “ribosome profiling” to measure translation (the cellular process of reading mRNA molecules and synthesizing protein molecules) in two yeast strains. We found that the genetic differences between these two strains influence translation for hundreds of genes. Because most of these effects were small in magnitude, they explain at most a small fraction of the discrepancies between the effects of genetic variants on mRNA and protein levels.


Vyšlo v časopise: Genetic Influences on Translation in Yeast. PLoS Genet 10(10): e32767. doi:10.1371/journal.pgen.1004692
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1004692

Souhrn

Individuals in a species differ from each other in many ways. For many traits, a fraction of this variation is genetic—it is caused by DNA sequence variants in the genome of each individual. Some of these variants influence traits by altering how much certain genes are expressed, i.e. how many mRNA and protein molecules are made in different individuals. Surprisingly, earlier work has found that the effects of genetic variants on mRNA and protein levels for the same genes appear to be very different. Many variants appeared to influence only mRNA (but not protein) levels, and vice versa. In this paper, we studied this question by using a technique called “ribosome profiling” to measure translation (the cellular process of reading mRNA molecules and synthesizing protein molecules) in two yeast strains. We found that the genetic differences between these two strains influence translation for hundreds of genes. Because most of these effects were small in magnitude, they explain at most a small fraction of the discrepancies between the effects of genetic variants on mRNA and protein levels.


Zdroje

1. BremRB, YvertG, ClintonR, KruglyakL (2002) Genetic Dissection of Transcriptional Regulation in Budding Yeast. Science (New York, NY) 296: 752–755.

2. RockmanMV, KruglyakL (2006) Genetics of global gene expression. Nature Reviews Genetics 7: 862–872.

3. LappalainenT, SammethM, FriedländerMR, HoenPAC', MonlongJ, et al. (2013) Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501: 506–511.

4. FossEJ, FossEJ, RadulovicD, RadulovicD, ShafferSA, et al. (2007) Genetic basis of proteome variation in yeast. Nature Genetics 39: 1369–1375.

5. FossEJ, RadulovicD, ShafferSA, GoodlettDR, KruglyakL, et al. (2011) Genetic Variation Shapes Protein Networks Mainly through Non-transcriptional Mechanisms. PLoS Biology 9: e1001144 doi:10.1371/journal.pbio.1001144.s010

6. GhazalpourA, BennettB, PetyukVA, OrozcoL, HagopianR, et al. (2011) Comparative Analysis of Proteome and Transcriptome Variation in Mouse. PLoS Genetics 7: e1001393 doi:10.1371/journal.pgen.1001393.s015

7. DamervalC, MauriceA, JosseJM, de VienneD (1994) Quantitative trait loci underlying gene product variation: a novel perspective for analyzing regulation of genome expression. Genetics 137: 289–301.

8. AlbertFW, TreuschS, ShockleyAH, BloomJS, KruglyakL (2014) Genetics of single-cell protein abundance variation in large yeast populations. Nature 506: 494–497.

9. SkellyDA, SkellyDA, MerrihewGE, MerrihewGE, RiffleM, et al. (2013) Integrative phenomics reveals insight into the structure of phenotypic diversity in budding yeast. Genome Research 23: 1496–1504.

10. WuL, CandilleSI, ChoiY, XieD, JiangL, et al. (2013) Variation and genetic control of protein abundance in humans. Nature 499: 79–82.

11. SchwanhäusserB, BusseD, LiN, DittmarG, SchuchhardtJ, et al. (2011) Global quantification of mammalian gene expression control. Nature 473: 337–342.

12. LiJJ, BickelPJ, BigginMD (2014) System wide analyses have underestimated protein abundances and the importance of transcription in mammals. PeerJ 2: e270 doi:10.7717/peerj.270

13. IngoliaNT, GhaemmaghamiS, NewmanJRS, WeissmanJS (2009) Genome-Wide Analysis in Vivo of Translation with Nucleotide Resolution Using Ribosome Profiling. Science (New York, NY) 324: 218–223.

14. WittkoppPJ, HaerumBK, ClarkAG (2004) Evolutionary changes in cis and trans gene regulation. Nature 430: 85–88.

15. WittkoppPJ, HaerumBK, ClarkAG (2008) Regulatory changes underlying expression differences within and between Drosophila species. Nature Genetics 40: 346–350.

16. BloomJS, KhanZ, KruglyakL, SinghM, CaudyAA (2009) Measuring differential gene expression by short read sequencing: quantitative comparison to 2-channel gene expression microarrays. BMC Genomics 10: 221.

17. EmersonJJ, HsiehL-C, SungH-M, WangT-Y, HuangC-J, et al. (2010) Natural selection on cis and trans regulation in yeasts. Genome Research 20: 826–836.

18. PickrellJK, MarioniJC, PaiAA, DegnerJF, EngelhardtBE, et al. (2010) Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464: 768–772.

19. MontgomerySB, SammethM, Gutierrez-ArcelusM, LachRP, IngleC, et al. (2010) Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 464: 773–777.

20. SonenbergN, HinnebuschAG (2009) Regulation of Translation Initiation in Eukaryotes: Mechanisms and Biological Targets. Cell 136: 731–745.

21. KondrashovN, PusicA, StumpfCR, ShimizuK, HsiehAC, et al. (2011) Ribosome-Mediated Specificity in Hox mRNA Translation and Vertebrate Tissue Patterning. Cell 145: 383–397.

22. IngoliaNT, BrarGA, RouskinS, McGeachyAM, WeissmanJS (2012) The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosome-protected mRNA fragments. Nat Protoc 7: 1534–1550.

23. PreissT, Baron-BenhamouJ, AnsorgeW, HentzeMW (2003) Homodirectional changes in transcriptome composition and mRNA translation induced by rapamycin and heat shock. Nat Struct Biol 10: 1039–1047.

24. LacknerDH, SchmidtMW, WuS, WolfDA, BählerJ (2012) Regulation of transcriptome, translation, and proteome in response to environmental stress in fission yeast. Genome Biol 13: R25.

25. HalbeisenRE, GerberAP (2009) Stress-Dependent Coordination of Transcriptome and Translatome in Yeast. PLoS Biology 7: e1000105 doi:10.1371/journal.pbio.1000105

26. MacKayVL, LiX, FloryMR, TurcottE, LawGL, et al. (2004) Gene expression analyzed by high-resolution state array analysis and quantitative proteomics: response of yeast to mating pheromone. Mol Cell Proteomics 3: 478–489.

27. LacknerDH, BeilharzTH, MargueratS, MataJ, WattS, et al. (2007) A Network of Multiple Regulatory Layers Shapes Gene Expression in Fission Yeast. Molecular Cell 26: 145–155.

28. StoreyJD, TibshiraniR (2003) Statistical significance for genomewide studies. Proceedings of the National Academy of Sciences 100: 9440–9445.

29. SmithEN, KruglyakL (2008) Gene–Environment Interaction in Yeast Gene Expression. PLoS Biology 6: e83 doi:10.1371/journal.pbio.0060083.st004

30. SonesonC, DelorenziM (2013) A comparison of methods for differential expression analysis of RNA-seq data. BMC Bioinformatics 14: 91.

31. AndersS, HuberW (2010) Differential expression analysis for sequence count data. Genome Biol 11: R106.

32. RonaldJ, BremRB, WhittleJ, KruglyakL (2005) Local Regulatory Variation in Saccharomyces cerevisiae. PLoS Genetics 1: e25 doi:10.1371/journal.pgen.0010025

33. WartonDI, WrightIJ, FalsterDS, WestobyM (2006) Bivariate line-fitting methods for allometry. Biological Reviews 81: 259.

34. McManusCJ, MayGE, SpealmanP, ShteymanA (2014) Ribosome profiling reveals post-transcriptional buffering of divergent gene expression in yeast. Genome Research 24: 422–430.

35. ArtieriCG, FraserHB (2014) Evolution at two levels of gene expression in yeast. Genome Research 24: 411–421.

36. MacArthurDG, BalasubramanianS, FrankishA, HuangN, MorrisJ, et al. (2012) A Systematic Survey of Loss-of-Function Variants in Human Protein-Coding Genes. Science (New York, NY) 335: 823–828.

37. KellisM, PattersonN, EndrizziM, BirrenB, LanderES (2003) Sequencing and comparison of yeast species to identify genes and regulatory elements. Nature 423: 241–254.

38. GodardP, UrrestarazuA, VissersS, KontosK, BontempiG, et al. (2007) Effect of 21 Different Nitrogen Sources on Global Gene Expression in the Yeast Saccharomyces cerevisiae. Molecular and Cellular Biology 27: 3065–3086.

39. WilliamsI, RichardsonJ, StarkeyA, StansfieldI (2004) Genome-wide prediction of stop codon readthrough during translation in the yeast Saccharomyces cerevisiae. Nucleic Acids Research 32: 6605–6616.

40. PartsL, LiuYC, TekkedilM, SteinmetzLM, CaudyAA, et al. (2014) Heritability and genetic basis of protein level variation in an outbred population. Genome Research 24 doi:10.1101/gr.170506.113

41. WallaceEWJ, AiroldiEM, DrummondDA (2013) Estimating Selection on Synonymous Codon Usage from Noisy Experimental Data. Mol Biol Evol 30: 1438–1453.

42. MuzzeyD, SherlockG, WeissmanJS (2014) Extensive and coordinated control of allele-specific expression by both transcription and translation in Candida albicans. Genome Research 24: 963–973.

43. DahanO, GingoldH, PilpelY (2011) Regulatory mechanisms and networks couple the different phases of gene expression. Trends in Genetics 27: 316–322.

44. ZidBM, O'SheaEK (2014) Promoter sequences direct cytoplasmic localization and translation of mRNAs during starvation in yeast. Nature doi:10.1038/nature13578

45. Harel-SharvitL, EldadN, HaimovichG, BarkaiO, DuekL, et al. (2010) RNA Polymerase II Subunits Link Transcription and mRNA Decay to Translation. Cell 143: 552–563.

46. ParkerR (2012) RNA degradation in Saccharomyces cerevisae. Genetics 191: 671–702.

47. ShahP, DingY, NiemczykM, KudlaG, PlotkinJB (2013) Rate-limiting steps in yeast protein translation. Cell 153: 1589–1601.

48. KarolchikD, BaertschR, DiekhansM, FureyTS, HinrichsA, et al. (2003) The UCSC Genome Browser Database. Nucleic Acids Research 31: 51–54.

49. DermitzakisET (2012) Cellular genomics for complex traits. Nature Reviews Genetics doi:10.1038/nrg3115

50. GaffneyDJ (2013) Global Properties and Functional Complexity of Human Gene Regulatory Variation. PLoS Genetics 9: e1003501 doi:10.1371/journal.pgen.1003501

51. BloomJS, EhrenreichIM, LooWT, LiteT-LV, KruglyakL (2013) Finding the sources of missing heritability in a yeast cross. Nature 494: 234–237.

52. BrarGA, YassourM, FriedmanN, RegevA, IngoliaNT, et al. (2012) High-Resolution View of the Yeast Meiotic Program Revealed by Ribosome Profiling. Science (New York, NY) 335: 552–557.

53. LiH, DurbinR (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25: 1754–1760.

54. LiH, HandsakerB, WysokerA, FennellT, RuanJ, et al. (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25: 2078–2079.

55. SkellyDA, JohanssonM, MadeoyJ, WakefieldJ, AkeyJM (2011) A powerful and flexible statistical framework for testing hypotheses of allele-specific gene expression from RNA-seq data. Genome Research 21: 1728–1737.

56. BergstromA, SimpsonJT, SalinasF, BarreB, PartsL, et al. (2014) A high-definition view of functional genetic variation from natural yeast genomes. Mol Biol Evol

57. WartonDI, DuursmaRA, FalsterDS, TaskinenS (2011) smatr 3- an R package for estimation and inference about allometric lines. Methods in Ecology and Evolution 3: 257–259.

58. CoolonJD, McManusCJ, StevensonKR, GraveleyBR, WittkoppPJ (2014) Tempo and mode of regulatory evolution in Drosophila. Genome Research 24 doi:10.1101/gr.163014.113

59. DabneyA, StoreyJD (2004) Q-value estimation for false discovery rate control. Medicine 344: 539–548.

60. BenjaminiY, HochbergY (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B (Methodological) 289–300.

61. McLarenW, PritchardB, RiosD, ChenY, FlicekP, et al. (2010) Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics 26: 2069–2070.

62. Hahne F, Durinck S, Ivanek R, Mueller A, Lianoglou S, et al. (n.d.) Gviz: Plotting data and annotation information along genomic coordinates. R package version 1.7.4.

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Genetika Reprodukčná medicína

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PLOS Genetics


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