Association of Phenotypic Markers of Heat Tolerance with Australian Genomic Estimated Breeding Values and Dairy Cattle Selection Indices
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Data Collection
2.2. Genotyping
2.3. Prediction of GEBVs for HT
2.4. Prediction of Australian GEBVs for Other Traits and Selection Indices
- Quality assurance of the genotype-evaluating call rate and genetrain scores for each marker in a batch, lack of variation in the X-chromosome for males, duplicates in a batch indicating sampling issues, and duplicate genotypes for different animals across batches, indicating monozygotic twins or clones (which may cause dependencies in the analysis), Hardy Weinberg equilibrium and genotype inconsistencies given the pedigree.
- Imputation of missing genotypes or genotypes failing to meet the minimum genetrain score.
- Estimation of Direct Genetic Values (DGVs) using BLUP (SNP BLUP) described as RR-BLUP [35], based on an assumption that SNP effects are random and the DGV for bull i called gi is defined as follows:
- iv.
- Blending was based on Harris and Johnson’s [36] estimation of genomic breeding values (GEBVs).
2.5. Statistical Analysis
3. Results
3.1. Variation in Physiological and Production Performance by Relative Thermotolerance
3.2. Variation in Genomic Estimated Breeding Values (GEBVs) by Relative Thermotolerance
3.3. Variation in GEBVs of Selection Indices by Age Group
3.4. Association of GEBVs of Economic Traits
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Parameter | Description | Remarks |
---|---|---|
Balanced Performance Index (BPI) | The Balanced Performance Index (BPI) is an economic index that balances the economic contribution of production, health and fertility, type, workability, and feed efficiency. The updated BPI applies greater emphasis to health by adding in survival and mastitis resistance. | The BPI identifies bulls and cows that combine traits that are important to profit. Farmers can track this in their genetic progress report and make appropriate and timely breeding decisions. |
Health Weighted Index (HWI) | The Health Weighted Index (HWI) allows farmers to fast-track traits such as fertility, mastitis resistance, and feed saved (efficiency). | The HWI puts the greatest emphasis on health and fertility, with production secondary. |
Type Weighted Index (TWI) | The Type Weighted Index (TWI) allowed farmers to fine-tune type traits to make a good herd even better. | Currently, the TWI has been replaced by good bulls guide tables. |
Australian Selection Index (ASI) | The ASI is a production-based index that ranks animals (bulls or females) on their ability to produce daughters with the most profitable combination of protein, fat, and milk production. Traits are weighted according to the way Australian dairy farmers are paid for their milk (fat + protein − volume). The ASI is expressed in dollars. An ASI of 200 means this animal is AUD200 per year more profitable from production than average. | The ASI is included in all three indices (the BPI, HWI, and sustainability indices) with the highest waiting on the sustainability index. For example, if an animal has an ASI of 200, then that is the contribution to production. If that same animal has a BPI of 300, then BPI 300 = ASI 200 + 100 from non-production. |
Feed Saved (FS) ABV | The feed saved ABV allows one to breed cows with reduced maintenance requirements for the same amount of milk produced. It is expressed in kilograms of dry matter of feed saved per cow per year more or less than the average of zero. A positive number represents feed saved; a negative number represents extra feed consumed. In genotyped Holsteins, feed saved ABV utilises maintenance feed requirements predicted from type traits and Residual Feed Intake (RFI). Reliability is a measure of confidence in an ABV. The reliability of an animal’s breeding values improves with age as more information becomes available; for example, genomics, daughters’ performance records, and herd test results. | To improve feed efficiency in your herd, select animals with a feed saved ABV greater than zero. Feed saved is a moderately heritable trait (20–30%), which means that selection for feed saved will make a difference. An updated model for the feed saved ABV was implemented in November 2020, resulting in improved reliability (42–45%). For Holstein bulls, this represented an 11% improvement in reliability. |
Heat Tolerance (HT) ABV | HT ABV allows farmers to identify animals with a greater ability to tolerate hot, humid conditions with less impact on milk production. It is expressed as a percentage, with a base of 100. An animal with an ABV of 105 is 5% more tolerant to hot, humid conditions than the average, and its drop in production will be 5% less than the average. On the other hand, an ABV of 95 means the animal is 5% less tolerant to hot, humid conditions than the average and its drop in production under heat stress is 5% more than the average. | To improve heat tolerance in your herd, select animals with a heat tolerance ABV of greater than 100. Allow for the lower reliability (36–38%) of the heat tolerance ABV by using a team of bulls. Reliability for HT ABV is expected to increase as more records become available. |
Parameter | Group 1 (Thermo-Susceptible) | Group 2 (Thermotolerant) |
---|---|---|
Respiration rate (breadths min−1) # | 91.8 ± 34.7 (303) * | 90.1 ± 32.1 (313) |
Panting score λ | 2.0 ± 0.8 (307) | 1.9 ± 0.8 (317) |
Daily milk production (kg/d) | 21.3 ± 5.6 b (341) | 30.0 ± 6.9 a (340) |
Fat % | 4.4 ± 0.9 a (340) | 3.9 ± 0.6 b (313) |
Protein % | 3.2 ± 0.3 a (340) | 3.0 ± 0.2 b (340) |
Concentrate intake (kg/d) | 5.3 ± 1.8 b (322) | 6.2 ± 1.6 a (320) |
Rumination time (mins) | 399.4 ± 108 b (320) | 445.9 ± 108.5 a (320) |
Residual feed (kg/d) | 1.1 ± 0.2 a (322) | 0.7 ± 0.8 b (322) |
Thermo-Susceptible Group (n = 19) | Thermotolerant Group (n = 20) | Herd Average | |
---|---|---|---|
n (sample size) | 19 * | 20 | 39.0 |
BPI | 75.7 ± 19.2 | 63.2 ± 16.5 | 69.3 |
ASI | 32.0 ± 12.5 | 19.0 ± 11.9 | 25.3 |
HWI | 65.6 ± 15.3 | 58.4 ± 13.3 | 61.9 |
TWI | 37.8 ± 21.5 | 29.5 ± 14.3 | 33.5 |
Milk | 86.7 ± 68.7 | −14.1 ± 91.2 | 35.0 |
Milk protein | 4.4 ± 1.8 | 2.4 ± 1.6 | 3.3 |
Milk fat | 6.1 ± 1.6 | 0.25 ± 2.6 | 3.1 |
HT | 102.4 ± 0.95 | 104.1 ± 0.93 | 103.2 |
Feed saved | 20.8 ± 12.0 | 31.5 ± 14.3 | 26.28 |
Fertility | 106.0 ± 1.05 | 105.8 ± 1.38 | 105.9 |
Age Category | ||||
---|---|---|---|---|
<5 Years | 5–7 Years | >7 Years | Total/Overall | |
n | 15 | 11 | 13 | 39 |
BPI | 106.1 a ± 21.3 | 62.6 ab ± 17.6 | 32.4 b ± 20.1 | 69.26 |
ASI | 53.9 a ± 15.6 | 18.5 ab ± 12.8 | −1.9 b ± 10.4 | 25.33 |
HWI | 86.9 ± 16.8 | 59.1 ± 13.1 | 35.5 ± 18.1 | 61.9 |
TWI | 83.4 a ± 17.9 | 17.3 ab ± 20.1 | −10.2 b ± 19.5 | 33.54 |
Milk | 207.1 a ± 79.0 | −175.3 b ± 131.1 | 14.4 ab ± 68.7 | 35.0 |
Milk protein | 9.0 a ± 1.7 | −0.18 b ± 2.0 | −0.23 b ± 1.5 | 3.33 |
Milk fat | 7.0 ± 3.0 | 1.2 ± 2.8 | 0.2 ± 2.2 | 3.10 |
HT | 100.9 ± 1.2 | 103.9 ± 1.0 | 105.4 ± 0.80 | 103.2 |
Feed saved | −0.3 ± 15.04 | 51.7 ± 19.7 | 35.2 ± 11.0 | 26.28 |
Fertility | 104.7 ± 1.43 | 106.91 ± 0.80 | 106.4 ± 1.91 | 105.9 |
BPI # | ASI | HWI | TWI | Milk | Protein | Fat | FS | Fertility | |
---|---|---|---|---|---|---|---|---|---|
ASI | 0.80 ** | ||||||||
HWI | 0.97 ** | 0.64 ** | |||||||
TWI | 0.95 ** | 0.77 ** | 0.92 ** | ||||||
Milk | 0.11 | −0.05 | −0.13 | −0.02 | |||||
Protein | 0.52 ** | 0.70 ** | 0.40 ** | 0.58 ** | 0.64 ** | ||||
Fat | 0.61 ** | 0.80 ** | 0.46 ** | 0.56 ** | −0.02 | 0.46 ** | |||
FS | −0.30 | −0.41 ** | −0.13 | −0.32 * | −0.29 | −0.45 ** | 0.48 ** | ||
Fertility | 0.51 ** | 0.02 | 0.62 ** | 0.30 | −0.28 | 0.18 | 0.04 | 0.03 | |
HT | −0.43 ** | −0.70 ** | −0.28 | −0.45 ** | −0.33 * | −0.74 ** | −0.59 ** | 0.45 ** | 0.25 |
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Osei-Amponsah, R.; Dunshea, F.R.; Leury, B.J.; Abhijith, A.; Chauhan, S.S. Association of Phenotypic Markers of Heat Tolerance with Australian Genomic Estimated Breeding Values and Dairy Cattle Selection Indices. Animals 2023, 13, 2259. https://doi.org/10.3390/ani13142259
Osei-Amponsah R, Dunshea FR, Leury BJ, Abhijith A, Chauhan SS. Association of Phenotypic Markers of Heat Tolerance with Australian Genomic Estimated Breeding Values and Dairy Cattle Selection Indices. Animals. 2023; 13(14):2259. https://doi.org/10.3390/ani13142259
Chicago/Turabian StyleOsei-Amponsah, Richard, Frank R. Dunshea, Brian J. Leury, Archana Abhijith, and Surinder S. Chauhan. 2023. "Association of Phenotypic Markers of Heat Tolerance with Australian Genomic Estimated Breeding Values and Dairy Cattle Selection Indices" Animals 13, no. 14: 2259. https://doi.org/10.3390/ani13142259