The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.
Recommendations for clinical interpretation of variants found in non-coding regions of the genome
Open accessAbstract
Background: The majority of clinical genetic testing focuses almost exclusively on regions of the genome that directly encode proteins. The important role of variants in non-coding regions in penetrant disease is, however, increasingly being demonstrated, and the use of whole genome sequencing in clinical diagnostic settings is rising across a large range of genetic disorders. Despite this, there is no existing guidance on how current guidelines designed primarily for variants in protein-coding regions should be adapted for variants identified in other genomic contexts. Methods: We convened a panel of nine clinical and research scientists with wide-ranging expertise in clinical variant interpretation, with specific experience in variants within non-coding regions. This panel discussed and refined an initial draft of the guidelines which were then extensively tested and reviewed by external groups. Results: We discuss considerations specifically for variants in non-coding regions of the genome. We outline how to define candidate regulatory elements, highlight examples of mechanisms through which non-coding region variants can lead to penetrant monogenic disease, and outline how existing guidelines can be adapted for the interpretation of these variants. Conclusions: These recommendations aim to increase the number and range of non-coding region variants that can be clinically interpreted, which, together with a compatible phenotype, can lead to new diagnoses and catalyse the discovery of novel disease mechanisms.
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Cites
Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., Grody, W. W., Hegde, M., Lyon, E., Spector, E., et al. (2015) · Genetics in Medicine · doi:10.1038/gim.2015.30 · Cited by 32,594
Self-citationThe Human Genome Browser at UCSC
Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M., & Haussler, A. D. (2002) · Genome Research · doi:10.1101/gr.229102 · Cited by 10,400
The mutational constraint spectrum quantified from variation in 141,456 humans
Karczewski, K. J., Francioli, L. C., Tiao, G., Cummings, B. B., Alföldi, J., Wang, Q., Collins, R. L., Laricchia, K. M., Ganna, A., Birnbaum, D. P., et al. (2020) · Nature · doi:10.1038/s41586-020-2308-7 · Cited by 9,434
Self-citationThe GTEx Consortium atlas of genetic regulatory effects across human tissues
The GTEx Consortium, Aguet, F., Anand, S., Ardlie, K. G., Gabriel, S., Getz, G. A., Graubert, A., Hadley, K., Handsaker, R. E., Huang, K. H., et al. (2020) · Science · doi:10.1126/science.aaz1776 · Cited by 5,547
ClinVar: improving access to variant interpretations and supporting evidence
Landrum, M. J., Lee, J. M., Benson, M., Brown, G. R., Chao, C., Chitipiralla, S., Gu, B., Hart, J., Hoffman, D., Jang, W., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1153 · Cited by 4,196 · cited 9×
“variants in ClinVar To identify non-coding region variants in ClinVar [31], all variants (n = 789,941) from the ClinVar GRCh38 VCF dated 01/31/2021 were annotated with respect to Matched Annotation from NCBI and EMBL-EBI (MANE) Select [32] v0.”
BackgroundMethodInfluentialPredicting splicing from primary sequence with deep learning
Jaganathan, K., Kyriazopoulou Panagiotopoulou, S., McRae, J. F., Darbandi, S. F., Knowles, D., Li, Y. I., Kosmicki, J. A., Arbelaez, J., Cui, W., Schwartz, G. B., et al. (2019) · Cell · doi:10.1016/j.cell.2018.12.015 · Cited by 2,853
Expanded encyclopaedias of DNA elements in the human and mouse genomes
The ENCODE Project Consortium, Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Ai, R., Aken, B., Akiyama, J. A., Jammal, O. A., et al. (2020) · Nature · doi:10.1038/s41586-020-2493-4 · Cited by 2,378
Disruptions of Topological Chromatin Domains Cause Pathogenic Rewiring of Gene-Enhancer Interactions
Lupiáñez, D. G., Kraft, K., Heinrich, V., Krawitz, P., Brancati, F., Klopocki, E., Horn, D., Kayserili, H., Opitz, J. M., Laxova, R., et al. (2015) · Cell · doi:10.1016/j.cell.2015.04.004 · Cited by 2,132
Chromatin accessibility and the regulatory epigenome
Klemm, S. L., Shipony, Z., & Greenleaf, W. J. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-018-0089-8 · Cited by 1,793
Riggs, E. R., Andersen, E. F., Cherry, A. M., Kantarci, S., Kearney, H., Patel, A., Raca, G., Ritter, D. I., South, S. T., Thorland, E. C., et al. (2020) · Genetics in Medicine · doi:10.1038/s41436-019-0686-8 · Cited by 1,768
Cited by
Schubach, M., Maass, T., Nazaretyan, L., Röner, S., & Kircher, M. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkad989 · Cited by 455
The performance of genome sequencing as a first-tier test for neurodevelopmental disorders
van der Sanden, B. P. G. H., Schobers, G., Corominas Galbany, J., Koolen, D. A., Sinnema, M., van Reeuwijk, J., Stumpel, C. T. R. M., Kleefstra, T., de Vries, B. B. A., Ruiterkamp-Versteeg, M., et al. (2023) · European Journal of Human Genetics · doi:10.1038/s41431-022-01185-9 · Cited by 97
The utility of ultra-deep RNA sequencing in Mendelian disorder diagnostics
Zhao, S., Sinson, J. C., Li, S., Rosenfeld, J. A., Zapata, G., Macakova, K., Pena, M., Maywald, B., Worley, K. C., Burrage, L. C., et al. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.09.013 · Cited by 5
Geysens, M., Souche, E., Baroni, M. C., Benoit, V., Beyltjens, T., Bossuyt, W., Bours, V., Crabbé, M., Croes, D., De Smet, M., et al. (2026) · Genome Medicine · doi:10.1186/s13073-026-01771-2
Metadata
- Authors
- Ellingford, J. M., Ahn, J. W., Bagnall, R. D., Baralle, D., Barton, S., Campbell, C., Downes, K., Ellard, S., Duff-Farrier, C., FitzPatrick, D. R., Greally, J. M., Ingles, J., Krishnan, N., Lord, J., Martin, H. C., Newman, W. G., O’Donnell-Luria, A., Ramsden, S. C., Rehm, H. L., Richardson, E., Singer-Berk, M., Taylor, J. C., Williams, M., Wood, J. C., Wright, C. F., Harrison, S. M., & Whiffin, N.
- Venue
- Genome Medicine
- Published
- 2022-07-19
- Volume
- 14
- Issue
- 1
- Pages
- 73-73
- ISSN
- 1756-994X (ISSN-L)
- OpenAlex
- W4285796131
- Cited by
- 259
- References
- 83
- FWCI
- 28.81
- Type
- journal article
- Language
- en
- Open access
- gold
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- Ellingford, J. M., Ahn, J. W., Bagnall, R. D., Baralle, D., Barton, S., Campbell, C., Downes, K., Ellard, S., Duff-Farrier, C., FitzPatrick, D. R., Greally, J. M., Ingles, J., Krishnan, N., Lord, J., Martin, H. C., Newman, W. G., O’Donnell-Luria, A., Ramsden, S. C., Rehm, H. L., . . . Whiffin, N. (2022). Recommendations for clinical interpretation of variants found in non-coding regions of the genome. Genome Medicine. https://doi.org/10.1186/s13073-022-01073-3
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