Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients
Abstract Clinical whole genome sequencing has enabled the discovery of potentially pathogenic noncoding variants in the genomes of rare disease patients with a prior history of negative genetic testing. However, interpreting the functional consequences of noncoding variants and distinguishing those...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-11589-8 |
| _version_ | 1828346896306929664 |
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| author | Jasmine A. McQuerry Merry Mclaird Samantha N. Hartin John C. Means Jeffrey Johnston Tomi Pastinen Scott T. Younger |
| author_facet | Jasmine A. McQuerry Merry Mclaird Samantha N. Hartin John C. Means Jeffrey Johnston Tomi Pastinen Scott T. Younger |
| author_sort | Jasmine A. McQuerry |
| collection | DOAJ |
| description | Abstract Clinical whole genome sequencing has enabled the discovery of potentially pathogenic noncoding variants in the genomes of rare disease patients with a prior history of negative genetic testing. However, interpreting the functional consequences of noncoding variants and distinguishing those that contribute to disease etiology remains a challenge. Here we address this challenge by experimentally profiling the functional consequences of rare noncoding variants detected in a cohort of undiagnosed rare disease patients at scale using a massively parallel reporter assay. We demonstrate that this approach successfully identifies rare noncoding variants that alter the regulatory capacity of genomic sequences. In addition, we describe an integrative analysis that utilizes genomic features alongside patient clinical data to further prioritize candidate variants with an increased likelihood of pathogenicity. This work represents an important step towards establishing a framework for the functional interpretation of clinically detected noncoding variants. |
| first_indexed | 2024-04-14T00:31:27Z |
| format | Article |
| id | doaj.art-db5cf431cf4e485abc023b16b1f5c44e |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-14T00:31:27Z |
| publishDate | 2022-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-db5cf431cf4e485abc023b16b1f5c44e2022-12-22T02:22:31ZengNature PortfolioScientific Reports2045-23222022-05-0112111110.1038/s41598-022-11589-8Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patientsJasmine A. McQuerry0Merry Mclaird1Samantha N. Hartin2John C. Means3Jeffrey Johnston4Tomi Pastinen5Scott T. Younger6Genomic Medicine Center, Children’s Mercy Kansas CityGenomic Medicine Center, Children’s Mercy Kansas CityGenomic Medicine Center, Children’s Mercy Kansas CityGenomic Medicine Center, Children’s Mercy Kansas CityGenomic Medicine Center, Children’s Mercy Kansas CityGenomic Medicine Center, Children’s Mercy Kansas CityGenomic Medicine Center, Children’s Mercy Kansas CityAbstract Clinical whole genome sequencing has enabled the discovery of potentially pathogenic noncoding variants in the genomes of rare disease patients with a prior history of negative genetic testing. However, interpreting the functional consequences of noncoding variants and distinguishing those that contribute to disease etiology remains a challenge. Here we address this challenge by experimentally profiling the functional consequences of rare noncoding variants detected in a cohort of undiagnosed rare disease patients at scale using a massively parallel reporter assay. We demonstrate that this approach successfully identifies rare noncoding variants that alter the regulatory capacity of genomic sequences. In addition, we describe an integrative analysis that utilizes genomic features alongside patient clinical data to further prioritize candidate variants with an increased likelihood of pathogenicity. This work represents an important step towards establishing a framework for the functional interpretation of clinically detected noncoding variants.https://doi.org/10.1038/s41598-022-11589-8 |
| spellingShingle | Jasmine A. McQuerry Merry Mclaird Samantha N. Hartin John C. Means Jeffrey Johnston Tomi Pastinen Scott T. Younger Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients Scientific Reports |
| title | Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients |
| title_full | Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients |
| title_fullStr | Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients |
| title_full_unstemmed | Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients |
| title_short | Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients |
| title_sort | massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients |
| url | https://doi.org/10.1038/s41598-022-11589-8 |
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