# Accurate determination of breed origin of alleles in a simulated smallholder crossbred dairy cattle population

## TL;DR

This paper introduces a new algorithm that accurately determines the breed origin of alleles in crossbred dairy cattle, which can help improve breeding programs in low- and middle-income countries.

## Contribution

A novel algorithm for breed origin assignment of alleles in crossbred cattle without requiring pedigree information is developed and tested.

## Key findings

- The algorithm correctly assigned breed origin to 95.76% of alleles on average across all scenarios.
- The consensus-based assignment achieved a mean accuracy of 1.00, indicating very high reliability.
- Threshold levels significantly affect assignment yield and accuracy, with less stringent thresholds increasing yield but decreasing accuracy.

## Abstract

Accurate assignment of breed origin of alleles (BOA) at a heterozygote locus may help to introduce a resilient or adaptive haplotype in crossbreeding. In this study, we developed and tested a method to assign breed of origin for individual alleles in crossbred dairy cattle. After generations of mating within and between local breeds as well as the importation of exotic bulls, five rounds of selected crossbred cows were simulated to mimic a dairy breeding program in the low- and middle-income countries (LMICs). In each round of selection, the alleles of those crossbred animals were phased and assigned to their breed of origin (being either local or exotic).

Across all core lengths and modes of phasing (with offset—move 50% of the core length forward or no-offset), the average percentage of alleles correctly assigned a breed origin was 95.76%, with only 1.39% incorrectly assigned and 2.85% missing or unassigned. On consensus, the average percentage of alleles correctly assigned a breed origin was 93.21%, with only 0.46% incorrectly assigned and 6.33% missing or unassigned. This high proportion of alleles correctly assigned a breed origin resulted in a high core-based mean accuracy of 0.99 and a very high consensus-based (most frequently observed assignment across all the scenarios) mean accuracy of 1.00. The algorithm’s assignment yield and accuracy were affected by the choice of threshold levels for the best match of assignments. The threshold level had the opposite effect on assignment yield and assignment accuracy. A less stringent threshold generated higher assignment yields and lower assignment accuracy.

We developed an algorithm that accurately assigns a breed origin to alleles of crossbred animals designed to represent breeding programs in the LMICs. The developed algorithm is straightforward in its application and does not require prior knowledge of pedigree, which makes it more relevant and applicable in LMICs breeding programs.

The online version contains supplementary material available at 10.1186/s12711-025-00985-z.