GGVD
GGVD provides a curated compendium of goat genomic variation from ancient and modern samples to support analyses of evolution, selection, introgression, and molecular-marker discovery.
Key Features:
- Extensive genomic dataset: Integrates whole-genome sequencing data from 208 modern domestic goats, 24 bezoars, 46 wild ibexes, and 82 ancient goat samples, comprising approximately 41.44 million single nucleotide polymorphisms (SNPs), around 5.14 million insertions and deletions (indels), 6,193 selected loci, and 112 introgression regions.
- Genomic variation visualizations: Provides frequency maps, selective-sweep displays via tables, Manhattan plots and line charts, and SNP genotype heatmaps for pattern inspection.
- Ancient haplotype representation: Displays ancient genome data as haplotypes across early, middle, and late periods to track variants associated with selection and introgression.
- Integrated bioinformatics tools: Incorporates the UCSC Genome Browser, BLAT, BLAST, LiftOver, and pcadapt for sequence feature exploration and comparative analyses.
Scientific Applications:
- Population genetics studies: Enables analysis of population structure, evolutionary history, and adaptive processes across diverse goat populations.
- Molecular marker design: Supports identification and design of molecular markers for trait-associated loci and downstream genotyping.
- Breeding programs: Informs selection decisions and management of genetic diversity in breeding and conservation programs.
Methodology:
Compiled and analyzed whole-genome sequencing data from ancient and modern goat samples and integrated UCSC Genome Browser, BLAT, BLAST, LiftOver, and pcadapt for data analysis and exploration.
Topics
Details
- Tool Type:
- web application
- Added:
- 9/20/2021
- Last Updated:
- 9/20/2021
Operations
Data Inputs & Outputs
Database search
Inputs
Outputs
Publications
Fu W, Wang R, Yu J, Hu D, Cai Y, Shao J, Jiang Y. GGVD: A goat genome variation database for tracking the dynamic evolutionary process of selective signatures and ancient introgressions. Journal of Genetics and Genomics. 2021;48(3):248-256. doi:10.1016/j.jgg.2021.03.003. PMID:33965348.
PMID: 33965348
Funding: - National Natural Science Foundation of China: 31822052