Privacy-preserving storage of sequenced genomic data

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Genomic data applications raise significant ethical and privacy concerns due to sensitive personal information.
• Processing and storing genomic data risks abuse by unauthorized individuals.
• Existing methods lack robust privacy-preserving solutions for raw genomic reads.

Purpose of the Study:

• To develop and present Varlock, a novel privacy-preserving method for secure storage of sequenced genomic data.
• To mask personal alleles within genomic reads while retaining valuable non-sensitive genetic properties.
• To enable secure sharing and on-demand restoration of specific genomic regions.

Main Methods:

• Utilized a public set of population allele frequencies to mask personal alleles in genomic reads.
• Masked each personal allele with a randomly selected population allele based on frequency.
• Stored masked alleles in an encrypted file, enabling secure sharing via public-key cryptography.
• Developed a reversible method for unmasking specific genomic regions on demand.

Main Results:

• Successfully masked personal variants, introducing new variants in the masked genome.
• Observed higher masking and introduction rates for alternative alleles with lower population frequencies.
• Principal Component Analysis (PCA) demonstrated that masked and personal VCFs are not trivially mappable.
• Confirmed the reversibility of the method, allowing selective unmasking of personal alleles.

Conclusions:

• Varlock effectively masks personal alleles in genomic reads, safeguarding sensitive genetic information.
• The method preserves crucial non-sensitive genomic properties essential for research.
• Varlock offers a reversible security layer for storing and sharing raw aligned genomic reads, facilitating controlled data access for patients, clinics, and researchers.