Mapping MAVE data for use in human genomics applications

Arbesfeld, JA; Da, EY; Stevenson, JS; Kuzma, K; Paul, A; Farris, T; Capodanno, BJ; Grindstaff, SB; Riehle, K; Saraiva-Agostinho, N; Safer, JF; Casper, J; Haeussler, M; Milosavljevic, A; Foreman, J; Firth, HV; Hunt, SE; Iqbal, S; Cline, MS; Rubin, AF; Wagner, AH

Author(s): Arbesfeld, JA; Da, EY; Stevenson, JS; Kuzma, K; Paul, A; Farris, T; Capodanno, BJ; Grindstaff, SB; Riehle, K; Saraiva-Agostinho, N; Safer, JF; Casper, J; Haeussler, M; Milosavljevic, A; Foreman, J; Firth, HV; Hunt, SE; Iqbal, S; Cline, MS; Rubin, AF; Wagner, AH;
Details: Publication Year 2025-06-25,Volume 26,Issue #1,Page 179
Journal Title: Genome Biology
Abstract: BACKGROUND: Experimental data from functional assays have a critical role in interpreting the impact of genetic variants. Assay data must be unambiguously mapped to a reference genome to make it accessible, but it is often reported relative to assay-specific sequences, complicating downstream use and integration of variant data across resources. To make multiplexed assays of variant effect (MAVE) data more broadly available to the research and clinical communities, the Atlas of Variant Effects Alliance mapped MAVE data from the MaveDB community database to human reference sequences, creating an extensive set of machine-readable homology mappings that are incorporated into widely used human genomics applications. RESULTS: Here, we map approximately 9.0 million individual protein and nucleotide variants in MaveDB to the human genome, describing the examined variants with respect to human reference sequences while preserving the data provenance of the original MAVE sequences. We then disseminate the results to major genomic resources including the Genomics 2 Proteins Portal, UCSC Genome Browser, Ensembl Variant Effect Predictor, and DECIPHER platform. Within these applications, MAVE variants can now be visualized and integrated with other relevant clinical and biological data, making additional knowledge available when performing variant interpretation and conducting other research activities. CONCLUSIONS: Mapping MAVE variants to human reference sequences and sharing the mapped dataset with several key human genomics applications enables a new and diverse set of applications for MAVE data. This study provides increased access to functional data that can assist in clinical variant interpretation pipelines and enable biomedical research and discovery.
Publisher: BMC
Keywords: Humans; *Genomics/methods; *Genome, Human; Databases, Genetic; *Genetic Variation; *Chromosome Mapping/methods; Deep mutational scanning; Functional assay; Genomic medicine; Genomics; Global Alliance for Genomics and Health; Massively parallel reporter assays; Multiplexed assays of variant effect; Variation representation specification
Research Division(s): Bioinformatics and Computational Biology
PubMed ID: 40563119
Publisher's Version: https://doi.org/10.1186/s13059-025-03647-x
Open Access at Publisher's Site: https://doi.org/10.1186/s13059-025-03647-x
Terms of Use/Rights Notice: Refer to copyright notice on published article.

Creation Date: 2025-07-28 08:47:51

Last Modified: 2025-07-28 08:48:02