Release 52
(Dec 27, 2023)
This Goat Quantitative Trait Locus (QTL) Database (Goat QTLdb) contains goat QTL and association data curated from published data. The database is designed to facilitate the process for users to compare, confirm, and locate the most plausible location for genes responsible for quantitative traits important to goat production. We have been striving our best to curate all available data, and adding tools to the QTLdb for users to accomplish many data meta-analysis and comparison tasks.

The current release of the Goat QTLdb contains 1,201 QTLs/associations from 17 publications. Those QTLs / associations represent 26 different base traits and 52 trait variants. (see data summary for more recent updates). The released data have also been submitted to the NCBI Gene, Ensembl, and UCSC databases, where the QTL information can be retrieved and analyzed using the respective tools on these sites. New tools and functions are continually added. Please see the release history or FAQ for new updates.

 

Information in the Goat QTLdb can be accessed in the following ways:

1. Search and Analysis: Tools for search by chromosomes, traits, breeds, publications, candidate genes, etc. and tools for data analysis primed with search.
2. Traits view:
3. Maps view:
4. Downloads:
5. Data Summary: Database statistics by chromosomes, traits, trait types, journals, publication years, etc.

QTL on
- Gbrowse
- Jbrowse
Frequently
Asked
Questions
Video
Tutorials
New Data
- Curation
- Batch load
Data
Downloads
REFERENCES:
Zhi-Liang Hu, Carissa A. Park, and James M. Reecy (2022). Bringing the Animal QTLdb and CorrDB into the future: meeting new challenges and providing updated services. Nucleic Acids Research, Volume 50, Issue D1, Pages D956–D961. DOI: 10.1093/nar/gkab1116

Zhi-Liang Hu, Carissa A. Park, and James M. Reecy (2019). Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB. Nucleic Acids Research, Volume 47, Issue D1, 8 January 2019, Pages D701–D710. DOI: 10.1093/nar/gky1084

Zhi-Liang Hu, Carissa A. Park, and James M. Reecy (2018). Development of Animal QTLdb and CorrDB: Resynthesizing Big Data to Improve Meta-analysis of Genetic and Genomic Information. The 11th World Congress on Genetics Applied to Livestock Production (WCGALP). New Zealand, February 11-16, 2018.

Zhi-Liang Hu, Carissa A. Park and James M. Reecy (2016). Developmental progress and current status of the Animal QTLdb. Nucleic Acids Research, 44 (D1): D827-D833. DOI: 10.1093/nar/gkv1233

Zhi-Liang Hu, Carissa A. Park, Xiao-Lin Wu and James M. Reecy (2013). Animal QTLdb: an improved database tool for livestock animal QTL/association data dissemination in the post-genome era. Nucleic Acids Research, 41 (D1): D871-D879; DOI: 10.1093/nar/gks1150

Zhi-Liang Hu, Carissa A. Park, Eric R. Fritz and James M. Reecy (2010). QTLdb: A Comprehensive Database Tool Building Bridges between Genotypes and Phenotypes. Invited Lecture with full paper published electronically on The 9th World Congress on Genetics Applied to Livestock Production (WCGALP). Leipzig, Germany August 1-6, 2010.

Zhi-Liang Hu and James M. Reecy (2007). Animal QTLdb: beyond a repository - A Public Platform for QTL Comparisons and Integration with Diverse Types of Structural Genomic Information. Mammalian Genome, Volume 18(1), 1-4 (2007). DOI: 10.1007/s00335-006-0105-8

Zhi-Liang Hu, Eric Ryan Fritz and James M. Reecy (2007). AnimalQTLdb: a livestock QTL database tool set for positional QTL information mining and beyond. Nucleic Acids Research, 2007, 35 (Database issue):D604-D609.

 

© 2003-2024: USA · USDA · NRPSP8 · Program to Accelerate Animal Genomics Applications. Contact: Bioinformatics Team