Ag Data Commons Maintenance - Thursday 08/18/2022
The Ag Data Commons will be undergoing technical maintenance on Thursday, August 18, 2022. Avoid adding or editing datasets during this period to prevent losing information. We apologize for the inconvenience. This notice will be removed once the issue is resolved.
Veterinary Pest Genomics Center Overview
The Veterinary Pest Genomics Center (VPGC) is an initiative within the US Department of Agriculture's Agricultural Research Service (ARS). The vision for this initiative is to leverage big data solutions to evaluate risk from, and develop mitigations for invasive and other economically important veterinary pests. The introduction of invasive veterinary pests is accelerated by global change, including anomalies related to climate variability. An important aspect of this effort is to foster an innovation ecosystem involving the network of laboratories directly linked to ARS National Program 104 (Veterinary, Medical, and Urban Entomology), and related locations, in a way that allows ARS to leverage its scientific talent and other research assets.
VPGC's mission is to:
- Utilize key biological resources, next generation sequencing technology, and state-of-the-art bioinformatics approaches to sequence and annotate the genomes, transcriptomes, proteomes and metagenomes of important and emerging arthropod pests of veterinary importance
- Develop and use molecular tools for population genomics studies of veterinary pests in their indigenous and invasive ranges to understand the role of different evolutionary forces in shaping phenotypic variation of high-consequence to agriculture
- Apply biogeographic, spatial, and temporal analyses to quantify and predict economically important or potential veterinary pest distributional changes, and integrate these analyses with genetic studies of rapid evolution and adaptation of pests to new or changing environments
- Conduct feasibility studies to evaluate advanced computing hardware and software systems for their ability to store and analyze large data sets on veterinary pests, and the capacity to integrate results from longitudinal