MACSNVdb
MACSNVdb catalogs approximately 74.51 million high-quality, non-redundant single nucleotide variants (SNVs) identified from sequencing data of 20 individual macaques across six species groups to enable analysis of interspecies genetic divergence in macaques for biomedical and evolutionary studies.
Key Features:
- Dataset composition: Approximately 74.51 million SNVs derived from sequencing data of 20 individuals spanning six Macaca species groups: M. mulatta (rhesus), M. fascicularis, M. sinica, M. arctoides, M. silenus, and M. sylvanus.
- High-quality, non-redundant SNVs: Variants are curated to be high-quality and non-redundant, as identified from sequencing data.
- Interspecies comparison support: Enables comparative analyses of genetic differences across multiple macaque species groups to study divergence.
- Functional annotations: Integrates SNV annotations and gene functional annotations, including non-synonymous SNVs that may impact protein structure or function, particularly within orthologs of human disease and drug-target genes.
Scientific Applications:
- Biomedical research: Investigating molecular mechanisms underlying species-specific disease responses and assessing variation in orthologs of human disease and drug-target genes.
- Population genetics and evolutionary biology: Studying population structure, interspecies genetic divergence, and conservation-relevant genetic variation among macaques.
Methodology:
SNVs were identified from sequencing data of 20 individual macaques across six species groups and curated to yield ~74.51 million high-quality, non-redundant variants, which were annotated with SNV and gene functional information including nonsynonymous variants.
Topics
Details
- Tool Type:
- web application
- Added:
- 1/18/2021
- Last Updated:
- 2/19/2021
Operations
Publications
Du L, Guo T, Liu Q, Li J, Zhang X, Xing J, Yue B, Li J, Fan Z. MACSNVdb: a high-quality SNV database for interspecies genetic divergence investigation among macaques. Database. 2020;2020. doi:10.1093/database/baaa027. PMID:32367112. PMCID:PMC7198316.