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Rare variant association testing in the non-coding genome

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Abstract

The development of next-generation sequencing technologies has opened-up some new possibilities to explore the contribution of genetic variants to human diseases and in particular that of rare variants. Statistical methods have been developed to test for association with rare variants that require the definition of testing units and, in these testing units, the selection of qualifying variants to include in the test. In the coding regions of the genome, testing units are usually the different genes and qualifying variants are selected based on their functional effects on the encoded proteins. Extending these tests to the non-coding regions of the genome is challenging. Testing units are difficult to define as the non-coding genome organisation is still rather unknown. Qualifying variants are difficult to select as the functional impact of non-coding variants on gene expression is hard to predict. These difficulties could explain why very few investigators so far have analysed the non-coding parts of their whole genome sequencing data. These non-coding parts yet represent the vast majority of the genome and some studies suggest that they could play a major role in disease susceptibility. In this review, we discuss recent experimental and statistical developments to gain knowledge on the non-coding genome and how this knowledge could be used to include rare non-coding variants in association tests. We describe the few studies that have considered variants from the non-coding genome in association tests and how they managed to define testing units and select qualifying variants.

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  1. Génétique, Génomique Fonctionnelle Et Biotechnologies, Faculté de Médecine, Univ Brest, Inserm, Inserm UMR1078, Bâtiment E-IBRBS 2ieme étage, 22 avenue Camille Desmoulins, 29238, Brest Cedex 3, France

    Ozvan Bocher & Emmanuelle Génin

  2. CHU Brest, Brest, France

    Emmanuelle Génin

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Bocher, O., Génin, E. Rare variant association testing in the non-coding genome. Hum Genet 139, 1345–1362 (2020). https://doi.org/10.1007/s00439-020-02190-y

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