The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Pervasive transcription of the eukaryotic genome: functional indices and conceptual implications
Abstract
Genome-wide analyses of the eukaryotic transcriptome have revealed that the majority of the genome is transcribed, producing large numbers of non-protein-coding RNAs (ncRNAs). This surprising observation challenges many assumptions about the genetic programming of higher organisms and how information is stored and organized within the genome. Moreover, the rapid advances in genomics have given little opportunity for biologists to integrate these emerging findings into their intellectual and experimental frameworks. This problem has been compounded by the perception that genome-wide studies often generate more questions than answers, which in turn has led to confusion and controversy. In this article, we address common questions associated with the phenomenon of pervasive transcription and consider the indices that can be used to evaluate the function (or lack thereof) of the resulting ncRNAs. We suggest that many lines of evidence, including expression profiles, conservation signatures, chromatin modification patterns and examination of increasing numbers of individual cases, argue in favour of the widespread functionality of non-coding transcription. We also discuss how informatic and experimental approaches used to analyse protein-coding genes may not be applicable to ncRNAs and how the general perception that protein-coding genes form the main informational output of the genome has resulted in much of the misunderstanding surrounding pervasive transcription and its potential significance. Finally, we present the conceptual implications of the majority of the eukaryotic genome being functional and describe how appreciating this perspective will provide considerable opportunity to further understand the molecular basis of development and complex diseases.
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Cites
Chromatin modifications and their function
Kouzarides, T. (2007) · Cell · doi:10.1016/j.cell.2007.02.005 · Cited by 10,883
High-Resolution Profiling of Histone Methylations in the Human Genome
Barski, A., Cuddapah, S., Cui, K., Roh, T.-Y., Schones, D. E., Wang, Z., Wei, G., Chepelev, I., & Zhao, K. (2007) · Cell · doi:10.1016/j.cell.2007.05.009 · Cited by 6,845
Long non-coding RNAs: insights into functions
Mercer, T. R., Dinger, M. E., & Mattick, J. S. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2521 · Cited by 5,654
Self-citationThe ENCODE Project Consortium (2007) · Nature · doi:10.1038/nature05874 · Cited by 5,223
Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals
Guttman, M., Amit, I., Garber, M., French, C., Lin, M. F., Feldser, D., Huarte, M., Zuk, O., Carey, B. W., Cassady, J. P., et al. (2009) · Nature · doi:10.1038/nature07672 · Cited by 4,098
Khalil, A. M., Guttman, M., Huarte, M., Garber, M., Raj, A., Rivea Morales, D., Thomas, K., Presser, A., Bernstein, B. E., van Oudenaarden, A., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0904715106 · Cited by 2,872
A germline-specific class of small RNAs binds mammalian Piwi proteins
Girard, A., Sachidanandam, R., Hannon, G. J., & Carmell, M. A. (2006) · Nature · doi:10.1038/nature04917 · Cited by 1,762
Ultraconserved Elements in the Human Genome
Bejerano, G., Pheasant, M., Makunin, I., Stephen, S., Kent, W. J., Mattick, J. S., & Haussler, D. (2004) · Science · doi:10.1126/science.1098119 · Cited by 1,732
Self-citationClemson, C. M., Hutchinson, J. N., Sara, S. A., Ensminger, A. W., Fox, A. H., Chess, A., & Lawrence, J. B. (2009) · Molecular Cell · doi:10.1016/j.molcel.2009.01.026 · Cited by 1,445
Makeyev, E. V., Zhang, J., Carrasco, M. A., & Maniatis, T. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.07.015 · Cited by 1,395
Cited by
Kapusta, A., Kronenberg, Z., Lynch, V. J., Zhuo, X., Ramsay, L., Bourque, G., Yandell, M., & Feschotte, C. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003470 · Cited by 687
Genome-wide analysis of long noncoding RNA stability
Clark, M. B., Johnston, R. L., Inostroza-Ponta, M., Fox, A. H., Fortini, E., Moscato, P., Dinger, M. E., & Mattick, J. S. (2012) · Genome Research · doi:10.1101/gr.131037.111 · Cited by 593
Self-citationLong noncoding RNAs in cancer: mechanisms of action and technological advancements
Bartonicek, N., Maag, J. L. V., & Dinger, M. E. (2016) · Molecular Cancer · doi:10.1186/s12943-016-0530-6 · Cited by 459
Self-citationSNORD-host RNA Zfas1 is a regulator of mammary development and a potential marker for breast cancer
Askarian-Amiri, M. E., Crawford, J., French, J. D., Smart, C. E., Smith, M. A., Clark, M. B., Ru, K., Mercer, T. R., Thompson, E. R., Lakhani, S. R., et al. (2011) · RNA · doi:10.1261/rna.2528811 · Cited by 334
Self-citationEpigenetic control of variation and stochasticity in metabolic disease
Panzeri, I., & Pospisilik, J. A. (2018) · Molecular Metabolism · doi:10.1016/j.molmet.2018.05.010 · Cited by 50
Metadata
- Authors
- Dinger, M. E., Amaral, P. P., Mercer, T. R., & Mattick, J. S.
- Venue
- Briefings in Functional Genomics and Proteomics
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-09-21
- Volume
- 8
- Issue
- 6
- Pages
- 407-423
- ISSN
- 1473-9550 (ISSN-L)
- 1477-4062
- OpenAlex
- W2102649026
- Cited by
- 178
- References
- 16
- FWCI
- 3.79
- Type
- journal article
- Language
- en
- Open access
- closed
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