Kristen Parker Gaddis - Academia.edu (original) (raw)
Papers by Kristen Parker Gaddis
Supplemental Web Files for paper submitted to the Journal of Dairy Science<br>
Interbull Bulletin, Oct 5, 2021
Frontiers in Genetics
Genetic selection has been an effective strategy to improve calving traits including stillbirth i... more Genetic selection has been an effective strategy to improve calving traits including stillbirth in dairy cattle. The primary objectives of the present study were to characterize stillbirth data and determine the feasibility of implementing routine genetic evaluations of stillbirth in five non-Holstein dairy breeds, namely Ayrshire, Guernsey, Milking Shorthorn, Brown Swiss, and Jersey. An updated sire-maternal grandsire threshold model was used to estimate genetic parameters and genetic values for stillbirth. Stillbirth data with the birth years of dams from 1995 to 2018 were extracted from the United States national calving ease database maintained by the Council on Dairy Cattle Breeding. The extracted stillbirth records varied drastically among the five dairy breeds. There were approximately 486K stillbirth records for Jersey and more than 80K stillbirth records for Brown Swiss. The direct and maternal heritability estimates of stillbirth were 6.0% (4.5–7.6%) and 4.7% (3.3–6.1%) in...
Interbull Bulletin, Oct 5, 2021
Additional file 3. List of variants into genes with highest posterior probability of causality mo... more Additional file 3. List of variants into genes with highest posterior probability of causality mostly associated with displaced abomasum (DSAB), ketosis (KETO), mastitis (MAST), metritis (METR), retained placenta (RETP) and cow livability.
Additional file 1. Boxplot with PTA reliability for hypocalcemia (CALC), displaced abomasum (DSAB... more Additional file 1. Boxplot with PTA reliability for hypocalcemia (CALC), displaced abomasum (DSAB), ketosis (KETO), mastitis (MAST), metritis (METR), retained placenta (RETP) and cow livability.
Additional file 2. Manhattan plots using the PTA as phenotype for hypocalcemia (CALC), displaced ... more Additional file 2. Manhattan plots using the PTA as phenotype for hypocalcemia (CALC), displaced abomasum (DSAB), ketosis (KETO), mastitis (MAST), metritis (METR), retained placenta (RETP) and cow livability. The genome-wide threshold (red line) corresponds to the Bonferroni correction for a nominal P-value = 0.05.
Animal Health Research Reviews, 2020
Bovine respiratory disease (BRD) is of considerable economic importance to the dairy industry, sp... more Bovine respiratory disease (BRD) is of considerable economic importance to the dairy industry, specifically among young animals. Several studies have demonstrated that BRD has a significant genetic component, with heritabilities ranging from 0.04 up to 0.22, which could be utilized to select more resistant animals. Taking advantage of available genomic data will allow more accurate genetic predictions to be made earlier in an animal's life. The availability of genomic data does not negate the necessity of quality phenotypes, in this case, records of BRD incidence. Evidence has shown that genetic selection is possible through the use of producer-recorded health information. The national dairy cooperator database currently has minimal records on respiratory problems. There is an existing pipeline for these data to flow from events recorded by producers on the farm to the national database used for genetic evaluation. Additional data could also be collected through the expansion of...
Interbull Bulletin, 2019
In 2013, the Council on Dairy Cattle Breeding (CDCB) started calculating and releasing U.S. genet... more In 2013, the Council on Dairy Cattle Breeding (CDCB) started calculating and releasing U.S. genetic and genomic evaluations, which historically had been totally managed by USDA. The role of USDA in the U.S. dairy genetics industry is still extremely important because USDA’s Animal Genomic and Improvement Laboratory conducts most of the research for developing the cutting-edge methodologies applied by CDCB. This presentation reviews the latest enhancements to U.S. evaluations during 2018 and 2019, all of them result of the interaction between public service and private U.S. industry. In April 2018, CDCB introduced six new health traits for Holsteins; these traits were included in lifetime net merit in August 2018. Early first calving, another new trait, was introduced in April 2019. In April 2018, CDCB also extended genomic evaluation to an all-breed system, which had been used for traditional evaluations since 2007. This, together with further methodology developments to determine a...
The objectives of this research were to develop and implement genetic and genomic evaluations for... more The objectives of this research were to develop and implement genetic and genomic evaluations for resistance to six common health events reported in U.S. dairy herds. Events included hypocalcemia (milk fever), displaced abomasum, ketosis, mastitis, metritis, and retained placenta. Dairy Records Management Systems (Raleigh, NC) provided producer-recorded data for these six health events. After applying standardization and editing constraints to the data, there were 3.1 million records from 1.7 million Holsteins. Variance components were estimated for each trait using univariate linear animal models. Heritability estimates on the observed scale were 0.6%, 1.1%, 1.2%, 3.1%, 1.4%, and 1.0% for hypocalcemia, displaced abomasum, ketosis, mastitis, metritis, and retained placenta, respectively. Traditional predicted transmitting abilities (PTA) were calculated for 63.1 million Holsteins through pedigree relationships using a linear animal model including effects of year-season, age-parity,...
Animal Genomics and Improvement Laboratory, ARS, USDA, Bldg 005, BARC-West, 10300 Baltimore Avenu... more Animal Genomics and Improvement Laboratory, ARS, USDA, Bldg 005, BARC-West, 10300 Baltimore Avenue, Beltsville, MD 20705 Council on Dairy Cattle Breeding, 4201 Northview Drive, Bowie, MD 20716, USA 3 Department of Animal Science, College of Agriculture and Life Sciences, North Carolina State University, Campus Box 7621, Raleigh, NC 27695 Dairy Records Management Systems, 313 Chapanoke Road, Suite 100, Raleigh, NC 27603
JDS Communications, 2021
Genetic evaluation on residual feed intake (RFI) often takes 2 stages. Combining these 2 modeling... more Genetic evaluation on residual feed intake (RFI) often takes 2 stages. Combining these 2 modeling stages leads to one-step linear regression, eliminating the need to estimate the residuals as the RFI phenotypes specifically. However, fitting phenotypes as regressor variables in a standard linear regression is criticized because phenotypes are subject to measurement errors. Multiple-trait models have been proposed, which give the genetic values of RFI through a follow-up partial regression procedure. By rearranging the linear regression equation, we came across an alternative, causal RFI interpretation by phenotype recursiveness between DMI and energy sinks. In this technical note, we propose a Bayesian recursive structural equation model (RSEM) for directly evaluating RFI, extending its analytical capacity to multiple-trait analysis. Highlights • The model postulates RFI as resulting from phenotypic recursive effects from energy sinks to DMI. • It predicts RFI genetic values and estimates genetic parameters simultaneously. • A simplified algorithm is proposed to sample model parameters via Marko chain Monte Carlo. • The model extends naturally to deal with heterozygous relationships between DMI and energy sinks. • Modeling simultaneous effects between energy sinks and DMI is possible, subject to model identifiability.
BackgroundHealth traits are of significant economic importance to the dairy industry due to their... more BackgroundHealth traits are of significant economic importance to the dairy industry due to their effects on milk production and associated treatment costs. Genome-wide association studies (GWAS) provide a means to identify associated genomic variants and thus reveal insights into the genetic architecture of complex traits and diseases. The objective of this study is to investigate the genetic basis of seven health traits in dairy cattle and to identify potential candidate genes associated with cattle health using GWAS, fine mapping, and analyses of multitissue transcriptome data.ResultsWe studied cow livability and six direct disease traits, mastitis, ketosis, hypocalcemia, displaced abomasum, metritis, and retained placenta, using de-regressed breeding values and more than three million imputed DNA sequence variants. After data edits and filtering on reliability, phenotypes for 11,880 to 24,699 Holstein bulls were included in the analyses of the seven traits. GWAS was performed us...
Genetics Selection Evolution, 2015
Background: Genetic selection has been successful in achieving increased production in dairy catt... more Background: Genetic selection has been successful in achieving increased production in dairy cattle; however, corresponding declines in fitness traits have been documented. Selection for fitness traits is more difficult, since they have low heritabilities and are influenced by various non-genetic factors. The objective of this paper was to investigate the predictive ability of two-stage and single-step genomic selection methods applied to health data collected from on-farm computer systems in the U.S. Methods: Implementation of single-trait and two-trait sire models was investigated using BayesA and single-step methods for mastitis and somatic cell score. Variance components were estimated. The complete dataset was divided into training and validation sets to perform model comparison. Estimated sire breeding values were used to estimate the number of daughters expected to develop mastitis. Predictive ability of each model was assessed by the sum of χ 2 values that compared predicted and observed numbers of daughters with mastitis and the proportion of wrong predictions. Results: According to the model applied, estimated heritabilities of liability to mastitis ranged from 0.05 (SD = 0.02) to 0.11 (SD = 0.03) and estimated heritabilities of somatic cell score ranged from 0.08 (SD = 0.01) to 0.18 (SD = 0.03). Posterior mean of genetic correlation between mastitis and somatic cell score was equal to 0.63 (SD = 0.17). The single-step method had the best predictive ability. Conversely, the smallest number of wrong predictions was obtained with the univariate BayesA model. The best model fit was found for single-step and pedigree-based models. Bivariate single-step analysis had a better predictive ability than bivariate BayesA; however, the latter led to the smallest number of wrong predictions. Conclusions: Genomic data improved our ability to predict animal breeding values. Performance of genomic selection methods depends on a multitude of factors. Heritability of traits and reliability of genotyped individuals has a large impact on the performance of genomic evaluation methods. Given the current characteristics of producer-recorded health data, single-step methods have several advantages compared to two-step methods.
PloS one, 2015
Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profita... more Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profitability and animal welfare. The objective of this study was to perform a genome-wide association study (GWAS) for CM in first-lactation Holstein. Producer-recorded mastitis event information for 103,585 first-lactation cows were used, together with genotype information on 1,361 bulls from the Illumina BovineSNP50 BeadChip. Single-step genomic-BLUP methodology was used to incorporate genomic data into a threshold-liability model. Association analysis confirmed that CM follows a highly polygenic mode of inheritance. However, 10-adjacent-SNP windows showed that regions on chromosomes 2, 14 and 20 have impacts on genetic variation for CM. Some of the genes located on chromosome 14 (LY6K, LY6D, LYNX1, LYPD2, SLURP1, PSCA) are part of the lymphocyte-antigen-6 complex (LY6) known for its neutrophil regulation function linked to the major histocompatibility complex. Other genes on chromosome 2 we...
In the United States, most dairy farmers who use on-farm dairy management systems voluntarily rec... more In the United States, most dairy farmers who use on-farm dairy management systems voluntarily record health incidences to facilitate effective cattle management. However, there is no national effort to organize or regulate the recording of health data such as enforcing standard or consistent definitions of health conditions. But when the data have been aggregated into experimental databases, several researchers have been able to compute lactation incidence rates, heritabilities and reliabilities at levels that are relatively comparable with other studies. PCDART from DRMS is one of three primary on-farm software systems that service dairy farmers and provide typical methods for data recording such as flexible health definitions, unlimited number of events and assistance with consistent within farm recording. There are 3250 herds (845K cows) that are managed by producers using PCDART and also enrolled on DHIA. Herds are representative of U.S. herd sizes and breeds. Of these herds, 44% deliver health incidences for off-farm backup at DRMS. Another 45% of herds also record health incidences at a lower rate, but these herds do not routinely deliver data files for off-farm backup at DRMS. Data recording histories for 'backup' herds were assessed for calving years 2009 through 2011 for entry of 34 recognized mature cow conditions of varying value to the dairy industry. Lactation incidence rates were similar to those found in earlier studies under more controlled environments. Additionally, the rates of entry of health events for large 'non-backup' herds were comparable to those of large 'backup' herds. 'Backup' herds recorded a mean of 123 events per 100 cows per year and 65% of herds recorded a minimum of 10 usable events per 100 cows per year. Larger herds (number of cows>500) recorded useful data at almost twice the rate of smaller herds. The most prevalent conditions were mastitis, lameness, metritis, cystic ovaries, other reproductive problems, retained placenta, Johne's and ketosis. There is sufficient potential in both volume and quality of U.S. health data to contribute to computation of meaningful genetic measures for selection using conditions of concern to producers.
With an emphasis on increasing profit through increased dairy cow production, a negative relation... more With an emphasis on increasing profit through increased dairy cow production, a negative relationship with fitness traits such as health has become apparent. Decreased cow health impacts herd profitability because it increases rates of involuntary culling and decreases milk revenues. Improvement of health traits through genetic selection is an appealing tool; however, there is no mandated recording system for health data in the US. Producer-recorded health information provides a wealth of information for improvement of dairy cow health, thus improving the profitability of a farm, yet several challenges remain. The broad definition of 'direct health' does not truly reflect the heterogeneity and complexity of these traits. While there is a virtually endless pool of phenotypes potentially considered for selection, it is paramount to identify a few key parameters for which a consistent and demonstrable improvement can be achieved. We have demonstrated how farmers' recorded events represent a credible source of information with reported incidences matching most of the epidemiological evidence in literature, with calculated incidence rates ranging from 1.37% for respiratory problems to 12.32% for mastitis. Furthermore, we have demonstrated that relationships among common health events constructed from on-farm data provide supporting evidence of plausible interconnection between diseases and overall data quality. The results of our analyses provide evidence for the feasibility of on-farm recorded health base breeding programs. Nevertheless, there is an intrinsic heterogeneity of players, and a complex infrastructure in the collection and flow of information connected to health traits, and among the reasons for the slow implementation of health selection programs, data privacy concerns are at the top of the list in the US.
There is growing interest from dairy producers in traits related to health and fitness of cattle,... more There is growing interest from dairy producers in traits related to health and fitness of cattle, which often have low heritabilities but high economic values. Traits with low heritability can be improved by genetic selection, but large numbers of daughter records are required to produce predicted transmitting abilities with high reliability. Producer-recorded health event data collected from on-farm computer systems were used to estimate variance components and compute traditional predicted transmitting abilities (PTA) for several health traits (digestive problems, displaced abomasum, ketosis, lameness, mastitis, metritis, reproductive problems, and retained placenta) using single-trait threshold sire models. Heritabilities ranged from 0.01 for lameness to 0.30 for displaced abomasum using only first lactation data. Results were similar when only first lactation or first through fifth parity data were used. Multiple trait models also were used to estimate genetic correlations among those traits, which ranged from-0.29 (ketosis, lameness) to +0.81 (displaced abomasum, ketosis). Only three traits (displaced abomasum, mastitis, metritis) had 300 or more bulls with traditional reliabilities of at least 0.50. A multiple-trait sire threshold model was used to compute genomic PTA for 2,649 genotyped bulls. The increase in reliability from including the genomic data ranged from 0.38 (displaced abomasum) to 0.48 (lameness). These results suggest that enough data may exist in on-farm computer systems to enable the routine calculation of genetic and genomic evaluations for the most common health disorders in US Holstein cattle.
Supplemental Web Files for paper submitted to the Journal of Dairy Science<br>
Interbull Bulletin, Oct 5, 2021
Frontiers in Genetics
Genetic selection has been an effective strategy to improve calving traits including stillbirth i... more Genetic selection has been an effective strategy to improve calving traits including stillbirth in dairy cattle. The primary objectives of the present study were to characterize stillbirth data and determine the feasibility of implementing routine genetic evaluations of stillbirth in five non-Holstein dairy breeds, namely Ayrshire, Guernsey, Milking Shorthorn, Brown Swiss, and Jersey. An updated sire-maternal grandsire threshold model was used to estimate genetic parameters and genetic values for stillbirth. Stillbirth data with the birth years of dams from 1995 to 2018 were extracted from the United States national calving ease database maintained by the Council on Dairy Cattle Breeding. The extracted stillbirth records varied drastically among the five dairy breeds. There were approximately 486K stillbirth records for Jersey and more than 80K stillbirth records for Brown Swiss. The direct and maternal heritability estimates of stillbirth were 6.0% (4.5–7.6%) and 4.7% (3.3–6.1%) in...
Interbull Bulletin, Oct 5, 2021
Additional file 3. List of variants into genes with highest posterior probability of causality mo... more Additional file 3. List of variants into genes with highest posterior probability of causality mostly associated with displaced abomasum (DSAB), ketosis (KETO), mastitis (MAST), metritis (METR), retained placenta (RETP) and cow livability.
Additional file 1. Boxplot with PTA reliability for hypocalcemia (CALC), displaced abomasum (DSAB... more Additional file 1. Boxplot with PTA reliability for hypocalcemia (CALC), displaced abomasum (DSAB), ketosis (KETO), mastitis (MAST), metritis (METR), retained placenta (RETP) and cow livability.
Additional file 2. Manhattan plots using the PTA as phenotype for hypocalcemia (CALC), displaced ... more Additional file 2. Manhattan plots using the PTA as phenotype for hypocalcemia (CALC), displaced abomasum (DSAB), ketosis (KETO), mastitis (MAST), metritis (METR), retained placenta (RETP) and cow livability. The genome-wide threshold (red line) corresponds to the Bonferroni correction for a nominal P-value = 0.05.
Animal Health Research Reviews, 2020
Bovine respiratory disease (BRD) is of considerable economic importance to the dairy industry, sp... more Bovine respiratory disease (BRD) is of considerable economic importance to the dairy industry, specifically among young animals. Several studies have demonstrated that BRD has a significant genetic component, with heritabilities ranging from 0.04 up to 0.22, which could be utilized to select more resistant animals. Taking advantage of available genomic data will allow more accurate genetic predictions to be made earlier in an animal's life. The availability of genomic data does not negate the necessity of quality phenotypes, in this case, records of BRD incidence. Evidence has shown that genetic selection is possible through the use of producer-recorded health information. The national dairy cooperator database currently has minimal records on respiratory problems. There is an existing pipeline for these data to flow from events recorded by producers on the farm to the national database used for genetic evaluation. Additional data could also be collected through the expansion of...
Interbull Bulletin, 2019
In 2013, the Council on Dairy Cattle Breeding (CDCB) started calculating and releasing U.S. genet... more In 2013, the Council on Dairy Cattle Breeding (CDCB) started calculating and releasing U.S. genetic and genomic evaluations, which historically had been totally managed by USDA. The role of USDA in the U.S. dairy genetics industry is still extremely important because USDA’s Animal Genomic and Improvement Laboratory conducts most of the research for developing the cutting-edge methodologies applied by CDCB. This presentation reviews the latest enhancements to U.S. evaluations during 2018 and 2019, all of them result of the interaction between public service and private U.S. industry. In April 2018, CDCB introduced six new health traits for Holsteins; these traits were included in lifetime net merit in August 2018. Early first calving, another new trait, was introduced in April 2019. In April 2018, CDCB also extended genomic evaluation to an all-breed system, which had been used for traditional evaluations since 2007. This, together with further methodology developments to determine a...
The objectives of this research were to develop and implement genetic and genomic evaluations for... more The objectives of this research were to develop and implement genetic and genomic evaluations for resistance to six common health events reported in U.S. dairy herds. Events included hypocalcemia (milk fever), displaced abomasum, ketosis, mastitis, metritis, and retained placenta. Dairy Records Management Systems (Raleigh, NC) provided producer-recorded data for these six health events. After applying standardization and editing constraints to the data, there were 3.1 million records from 1.7 million Holsteins. Variance components were estimated for each trait using univariate linear animal models. Heritability estimates on the observed scale were 0.6%, 1.1%, 1.2%, 3.1%, 1.4%, and 1.0% for hypocalcemia, displaced abomasum, ketosis, mastitis, metritis, and retained placenta, respectively. Traditional predicted transmitting abilities (PTA) were calculated for 63.1 million Holsteins through pedigree relationships using a linear animal model including effects of year-season, age-parity,...
Animal Genomics and Improvement Laboratory, ARS, USDA, Bldg 005, BARC-West, 10300 Baltimore Avenu... more Animal Genomics and Improvement Laboratory, ARS, USDA, Bldg 005, BARC-West, 10300 Baltimore Avenue, Beltsville, MD 20705 Council on Dairy Cattle Breeding, 4201 Northview Drive, Bowie, MD 20716, USA 3 Department of Animal Science, College of Agriculture and Life Sciences, North Carolina State University, Campus Box 7621, Raleigh, NC 27695 Dairy Records Management Systems, 313 Chapanoke Road, Suite 100, Raleigh, NC 27603
JDS Communications, 2021
Genetic evaluation on residual feed intake (RFI) often takes 2 stages. Combining these 2 modeling... more Genetic evaluation on residual feed intake (RFI) often takes 2 stages. Combining these 2 modeling stages leads to one-step linear regression, eliminating the need to estimate the residuals as the RFI phenotypes specifically. However, fitting phenotypes as regressor variables in a standard linear regression is criticized because phenotypes are subject to measurement errors. Multiple-trait models have been proposed, which give the genetic values of RFI through a follow-up partial regression procedure. By rearranging the linear regression equation, we came across an alternative, causal RFI interpretation by phenotype recursiveness between DMI and energy sinks. In this technical note, we propose a Bayesian recursive structural equation model (RSEM) for directly evaluating RFI, extending its analytical capacity to multiple-trait analysis. Highlights • The model postulates RFI as resulting from phenotypic recursive effects from energy sinks to DMI. • It predicts RFI genetic values and estimates genetic parameters simultaneously. • A simplified algorithm is proposed to sample model parameters via Marko chain Monte Carlo. • The model extends naturally to deal with heterozygous relationships between DMI and energy sinks. • Modeling simultaneous effects between energy sinks and DMI is possible, subject to model identifiability.
BackgroundHealth traits are of significant economic importance to the dairy industry due to their... more BackgroundHealth traits are of significant economic importance to the dairy industry due to their effects on milk production and associated treatment costs. Genome-wide association studies (GWAS) provide a means to identify associated genomic variants and thus reveal insights into the genetic architecture of complex traits and diseases. The objective of this study is to investigate the genetic basis of seven health traits in dairy cattle and to identify potential candidate genes associated with cattle health using GWAS, fine mapping, and analyses of multitissue transcriptome data.ResultsWe studied cow livability and six direct disease traits, mastitis, ketosis, hypocalcemia, displaced abomasum, metritis, and retained placenta, using de-regressed breeding values and more than three million imputed DNA sequence variants. After data edits and filtering on reliability, phenotypes for 11,880 to 24,699 Holstein bulls were included in the analyses of the seven traits. GWAS was performed us...
Genetics Selection Evolution, 2015
Background: Genetic selection has been successful in achieving increased production in dairy catt... more Background: Genetic selection has been successful in achieving increased production in dairy cattle; however, corresponding declines in fitness traits have been documented. Selection for fitness traits is more difficult, since they have low heritabilities and are influenced by various non-genetic factors. The objective of this paper was to investigate the predictive ability of two-stage and single-step genomic selection methods applied to health data collected from on-farm computer systems in the U.S. Methods: Implementation of single-trait and two-trait sire models was investigated using BayesA and single-step methods for mastitis and somatic cell score. Variance components were estimated. The complete dataset was divided into training and validation sets to perform model comparison. Estimated sire breeding values were used to estimate the number of daughters expected to develop mastitis. Predictive ability of each model was assessed by the sum of χ 2 values that compared predicted and observed numbers of daughters with mastitis and the proportion of wrong predictions. Results: According to the model applied, estimated heritabilities of liability to mastitis ranged from 0.05 (SD = 0.02) to 0.11 (SD = 0.03) and estimated heritabilities of somatic cell score ranged from 0.08 (SD = 0.01) to 0.18 (SD = 0.03). Posterior mean of genetic correlation between mastitis and somatic cell score was equal to 0.63 (SD = 0.17). The single-step method had the best predictive ability. Conversely, the smallest number of wrong predictions was obtained with the univariate BayesA model. The best model fit was found for single-step and pedigree-based models. Bivariate single-step analysis had a better predictive ability than bivariate BayesA; however, the latter led to the smallest number of wrong predictions. Conclusions: Genomic data improved our ability to predict animal breeding values. Performance of genomic selection methods depends on a multitude of factors. Heritability of traits and reliability of genotyped individuals has a large impact on the performance of genomic evaluation methods. Given the current characteristics of producer-recorded health data, single-step methods have several advantages compared to two-step methods.
PloS one, 2015
Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profita... more Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profitability and animal welfare. The objective of this study was to perform a genome-wide association study (GWAS) for CM in first-lactation Holstein. Producer-recorded mastitis event information for 103,585 first-lactation cows were used, together with genotype information on 1,361 bulls from the Illumina BovineSNP50 BeadChip. Single-step genomic-BLUP methodology was used to incorporate genomic data into a threshold-liability model. Association analysis confirmed that CM follows a highly polygenic mode of inheritance. However, 10-adjacent-SNP windows showed that regions on chromosomes 2, 14 and 20 have impacts on genetic variation for CM. Some of the genes located on chromosome 14 (LY6K, LY6D, LYNX1, LYPD2, SLURP1, PSCA) are part of the lymphocyte-antigen-6 complex (LY6) known for its neutrophil regulation function linked to the major histocompatibility complex. Other genes on chromosome 2 we...
In the United States, most dairy farmers who use on-farm dairy management systems voluntarily rec... more In the United States, most dairy farmers who use on-farm dairy management systems voluntarily record health incidences to facilitate effective cattle management. However, there is no national effort to organize or regulate the recording of health data such as enforcing standard or consistent definitions of health conditions. But when the data have been aggregated into experimental databases, several researchers have been able to compute lactation incidence rates, heritabilities and reliabilities at levels that are relatively comparable with other studies. PCDART from DRMS is one of three primary on-farm software systems that service dairy farmers and provide typical methods for data recording such as flexible health definitions, unlimited number of events and assistance with consistent within farm recording. There are 3250 herds (845K cows) that are managed by producers using PCDART and also enrolled on DHIA. Herds are representative of U.S. herd sizes and breeds. Of these herds, 44% deliver health incidences for off-farm backup at DRMS. Another 45% of herds also record health incidences at a lower rate, but these herds do not routinely deliver data files for off-farm backup at DRMS. Data recording histories for 'backup' herds were assessed for calving years 2009 through 2011 for entry of 34 recognized mature cow conditions of varying value to the dairy industry. Lactation incidence rates were similar to those found in earlier studies under more controlled environments. Additionally, the rates of entry of health events for large 'non-backup' herds were comparable to those of large 'backup' herds. 'Backup' herds recorded a mean of 123 events per 100 cows per year and 65% of herds recorded a minimum of 10 usable events per 100 cows per year. Larger herds (number of cows>500) recorded useful data at almost twice the rate of smaller herds. The most prevalent conditions were mastitis, lameness, metritis, cystic ovaries, other reproductive problems, retained placenta, Johne's and ketosis. There is sufficient potential in both volume and quality of U.S. health data to contribute to computation of meaningful genetic measures for selection using conditions of concern to producers.
With an emphasis on increasing profit through increased dairy cow production, a negative relation... more With an emphasis on increasing profit through increased dairy cow production, a negative relationship with fitness traits such as health has become apparent. Decreased cow health impacts herd profitability because it increases rates of involuntary culling and decreases milk revenues. Improvement of health traits through genetic selection is an appealing tool; however, there is no mandated recording system for health data in the US. Producer-recorded health information provides a wealth of information for improvement of dairy cow health, thus improving the profitability of a farm, yet several challenges remain. The broad definition of 'direct health' does not truly reflect the heterogeneity and complexity of these traits. While there is a virtually endless pool of phenotypes potentially considered for selection, it is paramount to identify a few key parameters for which a consistent and demonstrable improvement can be achieved. We have demonstrated how farmers' recorded events represent a credible source of information with reported incidences matching most of the epidemiological evidence in literature, with calculated incidence rates ranging from 1.37% for respiratory problems to 12.32% for mastitis. Furthermore, we have demonstrated that relationships among common health events constructed from on-farm data provide supporting evidence of plausible interconnection between diseases and overall data quality. The results of our analyses provide evidence for the feasibility of on-farm recorded health base breeding programs. Nevertheless, there is an intrinsic heterogeneity of players, and a complex infrastructure in the collection and flow of information connected to health traits, and among the reasons for the slow implementation of health selection programs, data privacy concerns are at the top of the list in the US.
There is growing interest from dairy producers in traits related to health and fitness of cattle,... more There is growing interest from dairy producers in traits related to health and fitness of cattle, which often have low heritabilities but high economic values. Traits with low heritability can be improved by genetic selection, but large numbers of daughter records are required to produce predicted transmitting abilities with high reliability. Producer-recorded health event data collected from on-farm computer systems were used to estimate variance components and compute traditional predicted transmitting abilities (PTA) for several health traits (digestive problems, displaced abomasum, ketosis, lameness, mastitis, metritis, reproductive problems, and retained placenta) using single-trait threshold sire models. Heritabilities ranged from 0.01 for lameness to 0.30 for displaced abomasum using only first lactation data. Results were similar when only first lactation or first through fifth parity data were used. Multiple trait models also were used to estimate genetic correlations among those traits, which ranged from-0.29 (ketosis, lameness) to +0.81 (displaced abomasum, ketosis). Only three traits (displaced abomasum, mastitis, metritis) had 300 or more bulls with traditional reliabilities of at least 0.50. A multiple-trait sire threshold model was used to compute genomic PTA for 2,649 genotyped bulls. The increase in reliability from including the genomic data ranged from 0.38 (displaced abomasum) to 0.48 (lameness). These results suggest that enough data may exist in on-farm computer systems to enable the routine calculation of genetic and genomic evaluations for the most common health disorders in US Holstein cattle.