# Russian honey bee genotype identification through enhanced marker panel set

## TL;DR

Scientists developed a new, efficient method to identify the genetic makeup of Russian honey bees using advanced technology and machine learning.

## Contribution

A novel genotyping assay combining existing and new genetic markers with microfluidic and machine learning techniques is introduced.

## Key findings

- The new genotyping assay improves upon the original genetic stock identification method for Russian honey bees.
- The assay uses a microfluidic platform and machine learning for high-throughput accuracy.
- This approach supports better breeding decisions to enhance bee health and productivity.

## Abstract

Russian honey bees (RHB) are a breeding population developed by USDA-ARS as an effort to provide Varroa-resistant honey bees to beekeepers. The selection strategy for this breeding population was the first in honey bees to incorporate genetic stock identification (GSI). The original GSI approach has been in use for over a decade, and though effective, novel technologies and analytical approaches recently developed provide an opportunity for improvement. Here we outline a novel genotyping assay that capitalizes on the markers used in the GSI as well as new loci recently identified in a whole genome pooled study of commercial honey bee stocks. Our approach utilizes a microfluidic platform and machine learning analyses to arrive at an accurate, high throughput assay. This novel approach provides an improved tool that can be readily incorporated into breeding decisions towards healthier more productive bees.