Science AdvancesBioinformaticsPeer-reviewed journal article
Incomplete annotation of disease-associated genes is limiting our understanding of Mendelian and complex neurogenetic disorders
David ZhangiD, Sebastian GuelfiiD, Sonia García-RuiziD, Beatrice CostaiD, Regina Hertfelder ReynoldsiD, Karishma D’SaiD, Wenfei LiuiD, Thomas CourtiniD, Amy PetersoniD, Andrew E. JaffeiD, John HardyiD, Juan Antonio BotíaiD, Leonardo Collado‐TorresiD, Mina RyteniD
Abstract
Although the increasing use of whole-exome and whole-genome sequencing have improved the yield of genetic testing for Mendelian disorders, an estimated 50% of patients still leave the clinic without a genetic diagnosis. This can be attributed in part to our lack of ability to accurately interpret the genetic variation detected through next-generation sequencing. Variant interpretation is fundamentally reliant on accurate and complete gene annotation, however numerous reports and discrepancies between gene annotation databases reveals that the knowledge of gene annotation remains far from comprehensive. Here, we detect and validate transcription in an annotation-agnostic manner across all 41 different GTEx tissues, then connect novel transcription to known genes, ultimately improving the annotation of 63% of the known OMIM-morbid genes. We find the majority of novel transcription to be tissue-specific in origin, with brain tissues being most susceptible to misannotation. Furthermore, we find that novel transcribed regions tend to be poorly conserved, but are significantly depleted for genetic variation within humans, suggesting they are functionally significant and potentially have human-specific functions. We present our findings through an online platform vizER, which enables individual genes to be visualised and queried for evidence of misannotation. We also release all tissue-specific transcriptomes in a BED format for ease of integration with whole-genome sequencing data. We anticipate that these resources will improve the diagnostic yield for a wide range of Mendelian disorders.
- organism: human
- assay: whole-exome sequencing
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 66
- FWCI
- 5.42
- Field percentile
- top 3%
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