Genomics & Informatics

Korea Genome Organization (한국유전체학회)
권호 표지
DOI QR코드

DOI QR Code

Genetic Architecture of Transcription and Chromatin Regulation

  • Kim, Kwoneel (Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST)) ;
  • Bang, Hyoeun (Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST)) ;
  • Lee, Kibaick (Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST)) ;
  • Choi, Jung Kyoon (Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST))
  • Received : 2015.05.07
  • Accepted : 2015.06.11
  • Published : 2015.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

DNA microarray and next-generation sequencing provide data that can be used for the genetic analysis of multiple quantitative traits such as gene expression levels, transcription factor binding profiles, and epigenetic signatures. In particular, chromatin opening is tightly coupled with gene transcription. To understand how these two processes are genetically regulated and associated with each other, we examined the changes of chromatin accessibility and gene expression in response to genetic variation by means of quantitative trait loci mapping. Regulatory patterns commonly observed in yeast and human across different technical platforms and experimental designs suggest a higher genetic complexity of transcription regulation in contrast to a more robust genetic architecture of chromatin regulation.

Keywords

References

  1. Brem RB, Yvert G, Clinton R, Kruglyak L. Genetic dissection of transcriptional regulation in budding yeast. Science 2002;296:752-755. https://doi.org/10.1126/science.1069516
  2. Brem RB, Storey JD, Whittle J, Kruglyak L. Genetic interactions between polymorphisms that affect gene expression in yeast. Nature 2005;436:701-703. https://doi.org/10.1038/nature03865
  3. Cheung VG, Spielman RS, Ewens KG, Weber TM, Morley M, Burdick JT. Mapping determinants of human gene expression by regional and genome-wide association. Nature 2005;437:1365-1369. https://doi.org/10.1038/nature04244
  4. Morley M, Molony CM, Weber TM, Devlin JL, Ewens KG, Spielman RS, et al. Genetic analysis of genome-wide variation in human gene expression. Nature 2004;430:743-747. https://doi.org/10.1038/nature02797
  5. Pickrell JK, Marioni JC, Pai AA, Degner JF, Engelhardt BE, Nkadori E, et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 2010;464:768-772. https://doi.org/10.1038/nature08872
  6. Rockman MV, Kruglyak L. Genetics of global gene expression. Nat Rev Genet 2006;7:862-872. https://doi.org/10.1038/nrg1964
  7. Schadt EE, Monks SA, Drake TA, Lusis AJ, Che N, Colinayo V, et al. Genetics of gene expression surveyed in maize, mouse and man. Nature 2003;422:297-302. https://doi.org/10.1038/nature01434
  8. Degner JF, Pai AA, Pique-Regi R, Veyrieras JB, Gaffney DJ, Pickrell JK, et al. DNase I sensitivity QTLs are a major determinant of human expression variation. Nature 2012;482:390-394. https://doi.org/10.1038/nature10808
  9. Yvert G, Brem RB, Whittle J, Akey JM, Foss E, Smith EN, et al. Trans-acting regulatory variation in Saccharomyces cerevisiae and the role of transcription factors. Nat Genet 2003;35:57-64.
  10. Brem RB, Kruglyak L. The landscape of genetic complexity across 5,700 gene expression traits in yeast. Proc Natl Acad Sci U S A 2005;102:1572-1577. https://doi.org/10.1073/pnas.0408709102
  11. Choi JK, Kim YJ. Epigenetic regulation and the variability of gene expression. Nat Genet 2008;40:141-147. https://doi.org/10.1038/ng.2007.58
  12. Lee K, Kim SC, Jung I, Kim K, Seo J, Lee HS, et al. Genetic landscape of open chromatin in yeast. PLoS Genet 2013;9:e1003229. https://doi.org/10.1371/journal.pgen.1003229
  13. International HapMap Consortium, Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 2007;449:851-861. https://doi.org/10.1038/nature06258
  14. 1000 Genomes Project Consortium, Abecasis GR, Altshuler D, Auton A, Brooks LD, Durbin RM, et al. A map of human genome variation from population-scale sequencing. Nature 2010;467:1061-1073. https://doi.org/10.1038/nature09534
  15. Guan Y, Stephens M. Practical issues in imputation-based association mapping. PLoS Genet 2008;4:e1000279. https://doi.org/10.1371/journal.pgen.1000279
  16. Ng PC, Henikoff S. SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res 2003;31:3812-3814. https://doi.org/10.1093/nar/gkg509
  17. Boyle AP, Guinney J, Crawford GE, Furey TS. F-Seq: a feature density estimator for high-throughput sequence tags. Bioinformatics 2008;24:2537-2538. https://doi.org/10.1093/bioinformatics/btn480
  18. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 2010;26:841-842. https://doi.org/10.1093/bioinformatics/btq033
  19. Choi JK. Contrasting chromatin organization of CpG islands and exons in the human genome. Genome Biol 2010;11:R70. https://doi.org/10.1186/gb-2010-11-7-r70
  20. Choi JK, Bae JB, Lyu J, Kim TY, Kim YJ. Nucleosome deposition and DNA methylation at coding region boundaries. Genome Biol 2009;10:R89. https://doi.org/10.1186/gb-2009-10-9-r89
  21. Ernst J, Kheradpour P, Mikkelsen TS, Shoresh N, Ward LD, Epstein CB, et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 2011;473:43-49. https://doi.org/10.1038/nature09906
  22. Lee SI, Pe'er D, Dudley AM, Church GM, Koller D. Identifying regulatory mechanisms using individual variation reveals key role for chromatin modification. Proc Natl Acad Sci U S A 2006;103:14062-14067. https://doi.org/10.1073/pnas.0601852103
  23. Giresi PG, Kim J, McDaniell RM, Iyer VR, Lieb JD. FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements) isolates active regulatory elements from human chromatin. Genome Res 2007;17:877-885. https://doi.org/10.1101/gr.5533506