Causes and Consequences of Chromatin Variation between Inbred Mice

English version České info

Variation at regulatory elements, identified through hypersensitivity to digestion by DNase I, is believed to contribute to variation in complex traits, but the extent and consequences of this variation are poorly characterized. Analysis of terminally differentiated erythroblasts in eight inbred strains of mice identified reproducible variation at approximately 6% of DNase I hypersensitive sites (DHS). Only 30% of such variable DHS contain a sequence variant predictive of site variation. Nevertheless, sequence variants within variable DHS are more likely to be associated with complex traits than those in non-variant DHS, and variants associated with complex traits preferentially occur in variable DHS. Changes at a small proportion (less than 10%) of variable DHS are associated with changes in nearby transcriptional activity. Our results show that whilst DNA sequence variation is not the major determinant of variation in open chromatin, where such variants exist they are likely to be causal for complex traits.

Vyšlo v časopise: Causes and Consequences of Chromatin Variation between Inbred Mice. PLoS Genet 9(6): e32767. doi:10.1371/journal.pgen.1003570
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1003570

Souhrn

Zdroje

1. GrossDS, GarrardWT (1988) Nuclease hypersensitive sites in chromatin. Annu Rev Biochem 57 : 159–197.

2. BernsteinBE, BirneyE, DunhamI, GreenED, GunterC, et al. (2012) An integrated encyclopedia of DNA elements in the human genome. Nature 489 : 57–74.

3. ThurmanRE, RynesE, HumbertR, VierstraJ, MauranoMT, et al. (2012) The accessible chromatin landscape of the human genome. Nature 489 : 75–82.

4. NephS, StergachisAB, ReynoldsA, SandstromR, BorensteinE, et al. (2012) Circuitry and dynamics of human transcription factor regulatory networks. Cell 150 : 1274–1286.

5. McDaniellR, LeeBK, SongL, LiuZ, BoyleAP, et al. (2010) Heritable individual-specific and allele-specific chromatin signatures in humans. Science 328 : 235–239.

6. KasowskiM, GrubertF, HeffelfingerC, HariharanM, AsabereA, et al. (2010) Variation in transcription factor binding among humans. Science 328 : 232–235.

7. De GobbiM, ViprakasitV, HughesJR, FisherC, BuckleVJ, et al. (2006) A regulatory SNP causes a human genetic disease by creating a new transcriptional promoter. Science 312 : 1215–1217.

8. DegnerJF, PaiAA, Pique-RegiR, VeyrierasJB, GaffneyDJ, et al. (2012) DNase I sensitivity QTLs are a major determinant of human expression variation. Nature 482 : 390–394.

9. MauranoMT, HumbertR, RynesE, ThurmanRE, HaugenE, et al. (2012) Systematic localization of common disease-associated variation in regulatory DNA. Science 337 : 1190–1195.

10. KeaneTM, GoodstadtL, DanecekP, WhiteMA, WongK, et al. (2011) Mouse genomic variation and its effect on phenotypes and gene regulation. Nature 477 : 289–294.

11. YalcinB, WongK, AgamA, GoodsonM, KeaneTM, et al. (2011) Sequence-based characterization of structural variation in the mouse genome. Nature 477 : 326–329.

12. ValdarW, SolbergLC, GauguierD, BurnettS, KlenermanP, et al. (2006) Genome-wide genetic association of complex traits in heterogeneous stock mice. Nat Genet 38 : 879–887.

13. YalcinB, FlintJ, MottR (2005) Using progenitor strain information to identify quantitative trait nucleotides in outbred mice. Genetics 171 : 673–681.

14. FlintJ, ThomasK, MicklemG, RaynhamH, ClarkK, et al. (1997) The relationship between chromosome structure and function at a human telomeric region. Nature Genetics 15 : 252–257.

15. KowalczykMS, HughesJR, GarrickD, LynchMD, SharpeJA, et al. (2012) Intragenic enhancers act as alternative promoters. Mol Cell 45 : 447–458.

16. KarlinS, AltschulSF (1990) Methods for assessing the statistical significance of molecular sequence features by using general scoring methods. Proceedings of the National Academy of Sciences, USA 87 : 2264–2268.

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

18. HegmannJP, PossidenteB (1981) Estimating genetic correlations from inbred strains. Behav Genet 11 : 103–114.

19. SpivakJL, TorettiD, DickermanHW (1973) Effect of phenylhydrazine-induced hemolytic anemia on nuclear RNA polymerase activity of the mouse spleen. Blood 42 : 257–266.

20. HughesJR, ChengJF, VentressN, PrabhakarS, ClarkK, et al. (2005) Annotation of cis-regulatory elements by identification, subclassification, and functional assessment of multispecies conserved sequences. Proc Natl Acad Sci U S A 102 : 9830–9835.

21. McArthurM, GerumS, StamatoyannopoulosG (2001) Quantification of DNaseI-sensitivity by real-time PCR: quantitative analysis of DNaseI-hypersensitivity of the mouse beta-globin LCR. J Mol Biol 313 : 27–34.

22. LunterG, GoodsonM (2011) Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads. Genome Res 21 : 936–939.

23. DerrienT, EstelleJ, Marco SolaS, KnowlesDG, RaineriE, et al. (2012) Fast computation and applications of genome mappability. PLoS One 7: e30377.

24. BlanchetteM, KentWJ, RiemerC, ElnitskiL, SmitAF, et al. (2004) Aligning multiple genomic sequences with the threaded blockset aligner. Genome Res 14 : 708–715.

25. BaileyTL, BodenM, BuskeFA, FrithM, GrantCE, et al. (2009) MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res 37: W202–208.

26. R-Development-Core-Team (2004) A language and environment for statistical computing.; Computing RFfS, editor. Vienna: R Foundation for Statistical Computing.

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

28. TrapnellC, WilliamsBA, PerteaG, MortazaviA, KwanG, et al. (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28 : 511–515.