meta Accurate Pedigrees: The Lifeline of Genetic Evaluations | The Bullvine

Accurate Pedigrees: The Lifeline of Genetic Evaluations 

Learn how errors in pedigrees affect the genetic evaluations. Do these errors distort breeding values and validation statistics? Discover more.

Accurate pedigrees are crucial for genetic evaluations, forming the backbone for understanding relatedness among individuals and guiding breeding decisions. They are vital for estimating breeding values, identifying superior genes, and enhancing livestock quality. 

However, pedigree errors, like misidentified parents or incorrect lineage records, are surprisingly common. These seemingly minor inaccuracies can have significant consequences, distorting the robustness of genetic models and leading to potentially detrimental breeding recommendations. 

These errors act as random exchanges, making individuals seem more or less related than they are. 

The single-step model, a promising solution, directly integrates genomic data into genetic evaluations. This method surpasses traditional models by providing greater accuracy through the combination of pedigree and genomic information, offering a comprehensive view of genetic potential. 

Using the single-step model, we examine how pedigree errors affect genetic evaluations. We’ll focus on the correlation between actual breeding values (TBV) and estimated breeding values (EBV) and the implications of these errors for validation studies with forward prediction. Understanding and addressing these errors is vital for robust genetic assessments. 

Pedigree Errors: An Often Overlooked but Critically Significant Issue 

Though often neglected, pedigree errors are critically significant as they misrepresent an animal’s genetic ancestry, leading to erroneous assumptions regarding genetic relationships. These errors can manifest in various ways, from incorrect parent recording to data entry mistakes. 

Familiar sources of pedigree errors include: 

  • Misidentification of parents: Errors during breeding or registration processes can lead to incorrect sire or dam recordings.
  • Recording mistakes: Clerical errors during data entry can misassign parents or offspring.
  • Multiple sires: The presence of numerous potential sires without genetic testing can cause uncertainties in pedigree records.
  • Errors in artificial insemination records: Mistakes in recording insemination details can significantly skew pedigree accuracy.

Previous research indicates that pedigree errors undermine genetic evaluations and impact breeding decisions. Traditional methods like the Animal Model or Parental Best Linear Unbiased Prediction (PBLUP), which often exclude genomic data, are particularly susceptible. These errors bias breeding values and hinder selection accuracy, making animals appear better or worse than they indeed are, thus distorting genetic evaluations and selection indices

Studies have shown that even a 5% error rate can reduce the accuracy of estimated breeding values (EBVs) by about 10%. Minor errors can also inflate early predictions in forward prediction models, creating a false sense of genetic progress

Traditionally, research focused on pedigree-based genetic evaluations, highlighting the detrimental effects of pedigree errors. This underscores the importance of the current investigation, which integrates genomic data to mitigate the negative impacts seen in traditional models. Looking ahead, future research should be inspired to refine methods that can detect and rectify pedigree errors, paving the way for more accurate genetic assessments.

Enhancing Breeding Precision Through Genomic Integration: An In-Depth Analysis 

This study, published in the Journal of Dairy Science, examined the impact of pedigree errors on genetic evaluations that incorporate both traditional and genomic information. These errors can significantly affect the accuracy of these evaluations, which are vital for breeding decisions. By understanding the influence of incorrect pedigree information, we can enhance precision, allowing farmers to make more informed breeding choices and ultimately improve their herds. 

This study analyzed the pedigrees and genetic data of 361,980 Fleckvieh cattle, with detailed genetic information on 25,950. This dataset provided a robust foundation to examine how errors in records might influence our findings. 

We simulated actual breeding values (TBV) and phenotypes by integrating genetic and environmental factors, with an assumed heritability of 25%. This approach ensured that our simulated data closely resembled real-life scenarios. 

Next, we examined the effect of pedigree errors on genetic evaluations using conventional (non-genomic) and single-step (genomic) models. We compared results using the correct pedigree against scenarios with 5%, 10%, and 20% incorrect records created by randomly reassigning sires to non-genotyped cows to replicate common recording mistakes.

Pedigree Errors: The Unseen Threat to Genetic Evaluation Integrity and Breeding Decisions

Our study reveals the practical implications of pedigree errors on genetic evaluations of cattle, particularly the link between True Breeding Values (TBV) and Estimated Breeding Values (EBV). As errors increase, this link weakens, impacting the reliability of genetic evaluations. This finding underscores the importance of accurate pedigree records in making informed breeding decisions. 

Along with this weak link came less variation in the predictions. This means pedigree errors made bulls look more similar in genetic quality than they are. This is much more obvious in bulls that have sired many calves, where such errors make it challenging to tell which bulls are the best. This blending effect in bulls with many offspring suggests that the system can’t differentiate well between high and low-quality bulls, potentially messing up your selection decisions. 

On the flip side, pedigree errors were not as damaging for young bulls that haven’t sired any calves yet. This happens because genetic evaluations for these young ones rely more on their DNA data than their offspring’s performance. This helps to buffer against the mistakes in their pedigree records. 

Moreover, in scenarios where future performance predictions are made, the errors in bulls with progeny tended to blow up early predictions. This makes early decisions potentially misleading and off-track. Thus, correcting pedigree errors is critical to keep genetic evaluations trustworthy and accurate, ensuring early predictions and overall breeding strategies stay on point.

Mitigating Pedigree Errors: Safeguarding the Future of Genetic Evaluations 

Understanding how pedigree errors impact genetic evaluations is crucial for dairy farmers. These errors, stemming from incorrect family tree data, lead to inaccurate breeding values (EBV) and poor selection decisions. 

As pedigree errors rise, the standard deviation of EBVs diminishes, making related animals, especially progeny-tested bulls, appear more alike than they are. This issue is less severe for younger animals but significantly affects bulls with many offspring. 

Reduced variation from pedigree errors causes overly optimistic early predictions, disrupting breeding programs. Inaccurate pedigrees weaken genetic evaluations, compromising effective selection. Ensuring accurate pedigrees through verification and genomic corrections is vital for precise EBV predictions, enhancing breeding programs, and strengthening your dairy herd.

The Bottom Line

When errors infiltrate cattle pedigrees, they severely disrupt genetic evaluations. A high frequency of mistakes weakens the correlation between a bull’s actual breeding value (TBV) and the estimated breeding value (EBV), reducing prediction reliability and consistency. This issue is particularly pronounced in progeny-tested bulls, where incorrect sire assignments inflate perceived similarities among bulls, skewing early predictions and undermining validation statistics. 

Maintaining precise pedigrees is fundamental for robust genetic evaluations. Accurate lineage information ensures the integrity of family relationships and sustains reliable breeding decisions. Implementing stringent checks, improving record-keeping, and leveraging advanced DNA testing are essential to minimize pedigree errors. DNA parentage tests significantly reduce the risk of misrecording sire-dam pairs. 

Future research should focus on refining methods to detect and rectify pedigree errors, assessing their impact across breeds, and seamlessly integrating genetic data into evaluation models. This approach will enhance the accuracy of genetic evaluations, ultimately fostering more reliable and efficient breeding programs.

Key Takeaways:

  • Pedigree errors, including misidentified parents and incorrect lineage records, undermine the assumptions about relatedness in genetic evaluation models.
  • The integration of genomic data using a single-step model enhances the precision of genetic evaluations, despite the presence of pedigree errors.
  • Incorrect pedigrees lead to lower correlations between true breeding values (TBV) and estimated breeding values (EBV), particularly affecting progeny-tested bulls.
  • Pedigree errors result in less variation among predictions, making genetically distinct animals appear more similar.
  • In forward prediction validation scenarios, pedigree errors can cause an apparent inflation in the accuracy of early predictions for young animals.
  • Implementation of stringent checks and advanced DNA testing can minimize pedigree errors, ensuring more robust genetic evaluations.
  • Future research should focus on developing better methods for detecting and correcting pedigree errors to further enhance the accuracy and reliability of genetic evaluation models.

Summary: Accurate pedigrees are crucial for genetic evaluations, guiding breeding decisions and estimating breeding values. However, pedigree errors, such as misidentified parents or incorrect lineage records, can distort the robustness of genetic models and lead to detrimental breeding recommendations. A single-step model that integrates genomic data into genetic evaluations provides greater accuracy by examining the correlation between actual breeding values (TBV) and estimated breeding values (EBV). Traditional methods like the Animal Model or Parental Best Linear Unbiased Prediction (PBLUP) are particularly susceptible to these errors. Studies have shown that even a 5% error rate can reduce the accuracy of estimated breeding values (EBVs) by about 10%. Maintaining precise pedigrees is essential for robust genetic evaluations, and implementing stringent checks, improving record-keeping, and leveraging advanced DNA testing are essential to minimize pedigree errors. Future research should focus on refining methods to detect and rectify pedigree errors, assessing their impact across breeds, and seamlessly integrating genetic data into evaluation models to enhance genetic evaluation accuracy and foster more reliable and efficient breeding programs.

(T13, D1)
Send this to a friend