We've updated our Privacy Policy to make it clearer how we use your personal data. We use cookies to provide you with a better experience. You can read our Cookie Policy here.

Advertisement

USDA Purchases Fluidigm Solution for Development and Validation Testing of Cattle SNP Panels

Listen with
Speechify
0:00
Register for free to listen to this article
Thank you. Listen to this article using the player above.

Want to listen to this article for FREE?

Complete the form below to unlock access to ALL audio articles.

Read time: Less than a minute
Fluidigm Corporation has announced that the U.S. Department of Agriculture’s Agricultural Research Service (ARS) has purchased a Fluidigm microfluidic-based EP1™ System to help develop and validate focused 96- and 384-SNP (single-nucleotide polymorphism) panels for testing America’s dairy and beef cattle. To ensure healthy cows and top quality product.

ARS scientists are collaborating with members of the U.S. biotechnology industry to develop high-throughput SNP panels that can genetically indicate cattle growth rates, disease resistance, milk productivity, health and longevity.

“ARS purchased a Fluidigm EP1 System to perform focused SNP validation and testing of cattle samples. The flexibility of our system allows them to quickly reconfigure their SNP panels for each experiment and our low cost per data point will allow the industry to adopt Fluidigm’s technology broadly. Our hope is that genetic understanding and testing of these cattle can help consumers and producers of cattle in the U.S., and around the world, increase the output of their herds and help meet the global demand for high-quality cattle,” said Gajus Worthington, president and chief executive officer of Fluidigm. “Increasing our genetic understanding of plants and animals and applying that knowledge to improve the world’s food supply is one of the most important developments of the 21st century.”

The ARS project is led by animal geneticist Curtis P. Van Tassell. Under his leadership, ARS scientists are integrating newly identified molecular markers with existing data sources to determine how to raise the predictive accuracy of evaluated traits in cattle, thus increasing the rate of productivity improvement.