Genetic selection is pivotal in determining which animals are chosen to reproduce, how many offspring they produce and their duration in the breeding population. The main objective is to increase the prevalence of desirable genes aligned with specific breeding goals as rapidly as possible. 

Breeders aim to select animals with optimal genetic traits and exclude those with less favorable genes, striving to enhance the genetic quality of future generations. As superior genes are consistently chosen, their frequency rises within the population, steering the entire group towards desired genetic traits.

Tools and techniques

Through time, various tools have been employed to identify Angus cattle with superior genetic traits. 

Performance testing to gather phenotypic data has become a standard practice among seedstock producers to enhance genetic quality. Within-herd ratios use the data to rank individual progeny within a contemporary group, accounting for age, sex and dam age differences. 

This approach has helped eliminate some known factors influencing performance traits, allowing for more accurate selection of progeny with superior genetic traits within a herd.

Expected progeny differences (EPDs) enabled comparisons across different groups, herds and environments — a development accelerated by the early adoption of artificial insemination (AI) by the Angus breed. In 2010, the American Angus Association pioneered the combination of phenotypes and genomic data in EPDs, which has evolved significantly over the last decade. Today, more than 1.8 million genotypes are used in the World Angus Evaluation for the prediction of calving ease, growth, foot score, scrotal and carcass traits.

Initially, the advent of genomics raised hopes of pinpointing specific genes linked to individual traits eliminating the need for more phenotype collection. However, ongoing research has confirmed the importance of continued phenotypic data capture to maintain accurate genetic evaluations. 

Today, genotypes are used to create more precise relationships among animals in Angus pedigrees, termed genomic relationships, which more accurately track gene overlap compared to traditional pedigree relationships. Figure 1 depicts the differences between the expected average relationships within a traditional pedigree versus the estimated genomic relationships within a pedigree that is using genotypic information. 

More precise relationships are not only formed among the individuals linked to the three-generation pedigree, but also for those collateral relatives like full and half siblings, aunts and uncles. These relationships inform which chunks of DNA are passed from parent to offspring. Then by linking genomic relationships back to actual phenotypes and performance data, the evaluation system can make earlier and more accurate predictions of genetic merit. 

Embracing innovations

Despite the advancements in genetic evaluation tools, their adoption often takes time. When EPDs were introduced, within-herd ratios were the primary selection tool. Since ratios offered limited value in cross-herd comparisons, EPDs were initially used alongside them. In the early days of genomic testing, genomic scores ranked individual animals within the tested population, which were then used in genetic evaluations to enhance EPDs.

Currently, genomic scores are obsolete for genetic prediction of registered animals with known pedigrees. The value of genomic testing now lies in the increased accuracy from calculating precise relationships among animals in the Angus pedigree, including both direct and collateral relatives. 

While genomic scores correlate with EPDs, they do not directly influence EPD calculations (see Figure 2). Instead, EPDs remain the primary tool for evaluating registered animals and incorporating comprehensive information, including pedigrees, phenotypic data and progeny records.

Consistent progress 

From individual weights to within-herd ratios to EPDs enhanced with genomics, various tools have emerged to identify animals with the best genetic traits. Using these tools in breeding and selection decisions helps breeders steer populations towards favorable economic traits. 

Realistic expectations are essential when utilizing these tools to improve mating decisions, acknowledging that the system generally predicts an animal’s genetic potential effectively. 

Consistent use of these tools and updating phenotypic information will enhance prediction accuracy, ensuring steady genetic progress over time. Combining these advanced tools with practical management decisions will yield maximum returns for breeders.