Systematic evaluation of the effect of polyadenylation signal variants on the expression of disease-associated genes
- 1State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, School of Life Sciences and Eye & ENT Hospital, Fudan University, Shanghai, 200438, China;
- 2Eye Institute, Eye & ENT Hospital, Shanghai Medical College, Fudan University, Shanghai, 200031, China;
- 3NHC Key Laboratory of Myopia (Fudan University), Key Laboratory of Myopia, Chinese Academy of Medical Sciences, and Shanghai Key Laboratory of Visual Impairment and Restoration (Fudan University), Shanghai, 200031, China;
- 4State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, School of Life Sciences and Huashan Hospital, Fudan University, Shanghai, 200438, China;
- 5Department of Pathology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China;
- 6MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, 200438, China;
- 7Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center of Genetics and Development, Shanghai Jiao Tong University, Shanghai, 200030, China;
- 8Singlera Genomics (Shanghai) Limited, Shanghai, 201318, China;
- 9Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai, 200438, China
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↵10 These authors contributed equally to this work.
Abstract
Single nucleotide variants (SNVs) within polyadenylation signals (PASs), a specific six-nucleotide sequence required for mRNA maturation, can impair RNA-level gene expression and cause human diseases. However, there is a lack of genome-wide investigation and systematic confirmation tools for identifying PAS variants. Here, we present a computational strategy to integrate the most reliable resources for discovering distinct genomic features of PAS variants and also develop a credible and convenient experimental tool to validate the effect of PAS variants on expression of disease-associated genes. This approach will greatly accelerate the deciphering of PAS variation-related human diseases.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at https://www.genome.org/cgi/doi/10.1101/gr.270256.120.
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Freely available online through the Genome Research Open Access option.
- Received August 15, 2020.
- Accepted March 2, 2021.
This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
