Development of genomic evaluation for methane efficiency in Canadian Holsteins.

Reducing methane (CH) emissions from agriculture, among other sectors, is a key step to reducing global warming. There are many strategies to reduce CH emissions in ruminant animals, including genetic selection, which yields cumulative and permanent genetic gains over generations. A single-step genomic evaluation for methane efficiency (MEF) was officially implemented in April 2023 for the Canadian Holstein breed, aiming to reduce CH emissions without affecting production levels.

Phenotypic and genomic modeling of lactation curves: A longitudinal perspective.

Lactation curves, which describe the production pattern of milk-related traits over time, provide insightful information about individual cow health, resilience, and milk production efficiency. Key functional traits can be derived through lactation curve modeling, such as lactation peak and persistency. Furthermore, novel traits such as resilience indicators can be derived based on the variability of the deviations of observed milk yield from the expected lactation curve fitted for each animal.

Estimation of genetic parameters for feed efficiency traits using random regression models in dairy cattle.

Feed efficiency has become an increasingly important research topic in recent years. As feed costs rise and the environmental impacts of agriculture become more apparent, improving the efficiency with which dairy cows convert feed to milk is increasingly important. However, feed intake is expensive to measure accurately on large populations, making the inclusion of this trait in breeding programs difficult.

Symposium review: Multiple-trait single-step genomic evaluation for hoof health.

Hoof lesions represent an important issue in modern dairy herds, with reported prevalence in different countries ranging from 40 to 70%. This high prevalence of hoof lesions has both economic and social consequences, resulting in increased labor expenses and decreasing animal production, longevity, reproduction, health, and welfare. Therefore, a key goal of dairy herds is to reduce the incidence of hoof lesions, which can be achieved both by improving management practices and through genetic selection.

Estimation of genetic parameters for mid-infrared-predicted lactoferrin and milk fat globule size in Holstein cattle.

Lactoferrin (LF) and milk fat globule (MFG) are 2 biologically active components of milk with great economical and nutritional value in the dairy industry. The objectives of this study were to estimate (1) the heritability of mid-infrared (MIR)-predicted LF and MFG size (MFGS) and (2) the genetic correlations between predicted LF and MFGS with milk, fat, and protein yields, fat and protein percentages, and somatic cell score in first-parity Canadian Holstein cattle. A total of 109,029 test-day records from 22,432 cows and 1,572 farms for MIR-predicted LF and 109,212 test-day records from 22,424 cows and 1,559 farms for MIR-predicted MFGS were used in the analyses.

Single-step genome-wide association for longitudinal traits of Canadian Ayrshire, Holstein, and Jersey dairy cattle.

Estimating single nucleotide polymorphism (SNP) effects over time is essential to identify and validate candidate genes (or quantitative trait loci) associated with time-dependent variation of economically important traits and to better understand the underlying mechanisms of lactation biology. Therefore, in this study, we aimed to estimate time-dependent effects of SNP and identifying candidate genes associated with milk (MY), fat (FY), and protein (PY) yields, and somatic cell score (SCS) in the first 3 lactations of Canadian Ayrshire, Holstein, and Jersey breeds, as well as suggest their potential pattern of phenotypic effect over time. Random regression coefficients for the additive direct genetic effect were estimated for each animal using single-step genomic BLUP, based on 2 random regression models: one considering MY, FY, and PY in the first 3 lactations and the other considering SCS in the first 3 lactations.

Genome-wide association for milk production traits and somatic cell score in different lactation stages of Ayrshire, Holstein, and Jersey dairy cattle.

We performed genome-wide association analyses for milk, fat, and protein yields and somatic cell score based on lactation stages in the first 3 parities of Canadian Ayrshire, Holstein, and Jersey cattle. The genome-wide association analyses were performed considering 3 different lactation stages for each trait and parity: from 5 to 95, from 96 to 215, and from 216 to 305 d in milk. Effects of single nucleotide polymorphisms (SNP) for each lactation stage, trait, parity, and breed were estimated by back-solving the direct breeding values estimated using the genomic best linear unbiased predictor and single-trait random regression test-day models containing only the fixed population average curve and the random genomic curves.

Invited review: Advances and applications of random regression models: From quantitative genetics to genomics.

An important goal in animal breeding is to improve longitudinal traits; that is, traits recorded multiple times during an individual's lifetime or physiological cycle. Longitudinal traits were first genetically evaluated based on accumulated phenotypic expression, phenotypic expression at specific time points, or repeatability models. Until now, the genetic evaluation of longitudinal traits has mainly focused on using random regression models (RRM).

Impact of including information from bulls and their daughters in the training population of multiple-step genomic evaluations in dairy cattle: A simulation study.

The objective of this study was to investigate the impact of accounting for parent average (PA) and genotyped daughters' average (GDA) on the estimation of deregressed estimated breeding values (dEBVs) used as pseudo-phenotypes in multiple-step genomic evaluations. Genomic estimated breeding values (GEBVs) were predicted, in eight different simulated scenarios, using dEBVs calculated based on four methods. These methods included PA and GDA in the dEBV (VR) or only GDA (VRpa) and excluded both PA and GDA from the dEBV with either all information or only information from PA and GDA (JA and NEW, respectively).

Application of single-step genomic evaluation using multiple-trait random regression test-day models in dairy cattle.

Test-day traits are important for genetic evaluation in dairy cattle and are better modeled by multiple-trait random regression models (RRM). The reliability and bias of genomic estimated breeding values (GEBV) predicted using multiple-trait RRM via single-step genomic best linear unbiased prediction (ssGBLUP) were investigated in the 3 major dairy cattle breeds in Canada (i.e.

Genomic prediction of lactation curves for milk, fat, protein, and somatic cell score in Holstein cattle.

Application of random regression models (RRM) in a 2-step genomic prediction might be a feasible way to select young animals based on the complete pattern of the lactation curve. In this context, the prediction reliability and bias of genomic estimated breeding value (GEBV) for milk, fat, and protein yields and somatic cell score over days in milk (DIM) using a 2-step genomic approach were investigated. In addition, the effect of including cows in the training and validation populations was investigated.

Age-Focused Design - A Pedagogical Approach Integrating Empathy and Embodiment.

Architects seldom design for themselves, yet in the course of studying architecture one is rarely presented with the opportunity to design for a real client. The abstract nature of this education model leads to a focus that typically prioritizes formal or technical design exploration and de-emphasizes the role of the user. While Universal Design centers human bodies within design practice, the broad and often vague ambition of universality is difficult for students to engage within an academic context.

Comparing deregression methods for genomic prediction of test-day traits in dairy cattle.

We aimed to investigate the performance of three deregression methods (VanRaden, VR; Wiggans, WG; and Garrick, GR) of cows' and bulls' breeding values to be used as pseudophenotypes in the genomic evaluation of test-day dairy production traits. Three scenarios were considered within each deregression method: (i) including only animals with reliability of estimated breeding value (REL ) higher than the average of parent reliability (REL ) in the training and validation populations; (ii) including only animals with REL higher than 0.50 in the training and REL higher than REL in the validation population; and (iii) including only animals with REL higher than 0.

Genetic correlations of mid-infrared-predicted milk fatty acid groups with milk production traits.

The objective of this research was to estimate the genetic correlations between milk mid-infrared-predicted fatty acid groups and production traits in first-parity Canadian Holsteins. Contents of short-chain, medium-chain, long-chain, saturated, and unsaturated fatty acid groupings in milk samples can be predicted using mid-infrared spectral data for cows enrolled in milk recording programs. Predicted fatty acid group contents were obtained for 49,127 test-day milk samples from 10,029 first-parity Holstein cows in 810 herds.

Genetic analysis of groups of mid-infrared predicted fatty acids in milk.

The objective of this study was to investigate genetic variability of mid-infrared predicted fatty acid groups in Canadian Holstein cattle. Genetic parameters were estimated for 5 groups of fatty acids: short-chain (4 to 10 carbons), medium-chain (11 to 16 carbons), long-chain (17 to 22 carbons), saturated, and unsaturated fatty acids. The data set included 49,127 test-day records from 10,029 first-lactation Holstein cows in 810 herds.

Short communication: Recursive model approach to traits defined as ratios: Genetic parameters and breeding values.

A novel method for analysis of ratio traits (Y/Y) is proposed. Utilizing a recursive modeling approach, a proxy for Y/Y can be postulated as Y - λ × Y (i.e.

Multiple-trait estimates of genetic parameters for metabolic disease traits, fertility disorders, and their predictors in Canadian Holsteins.

Producer-recorded health data for metabolic disease traits and fertility disorders on 35,575 Canadian Holstein cows were jointly analyzed with selected indicator traits. Metabolic diseases included clinical ketosis (KET) and displaced abomasum (DA); fertility disorders were metritis (MET) and retained placenta (RP); and disease indicators were fat-to-protein ratio, milk β-hydroxybutyrate, and body condition score (BCS) in the first lactation. Traits in first and later (up to fifth) lactations were treated as correlated in the multiple-trait (13 traits in total) animal linear model.

Genetic analysis of milk β-hydroxybutyrate and its association with fat-to-protein ratio, body condition score, clinical ketosis, and displaced abomasum in early first lactation of Canadian Holsteins.

The aim of this study was to estimate genetic parameters for milk β-hydroxybutyrate (BHBA) in early first lactation of Canadian Holstein cows and to examine its genetic association with indicators of energy balance (fat-to-protein ratio and body condition score) and metabolic diseases (clinical ketosis and displaced abomasum). Data for milk BHBA recorded between 5 and 100 d in milk was obtained from Valacta (Sainte-Anne-de-Bellevue, Québec, Canada), the Canadian Dairy Herd Improvement organization responsible for Québec and Atlantic provinces. Test-day milk samples were analyzed by mid-infrared spectrometry using previously developed calibration equations for milk BHBA.

Genetic relationships of clinical mastitis, cystic ovaries, and lameness with milk yield and somatic cell score in first-lactation Canadian Holsteins.

The objective of this study was to investigate the genetic relationships of the 3 most frequently reported dairy cattle diseases (clinical mastitis, cystic ovaries, and lameness) with test-day milk yield and somatic cell score (SCS) in first-lactation Canadian Holstein cows using random regression models. Health data recorded by producers were available from the National Dairy Cattle Health System in Canada. Disease traits were defined as binary traits (0=healthy, 1=affected) based on whether or not the cow had at least one disease case recorded within 305 d after calving.

Estimates of genetic parameters for stayability to consecutive calvings of Canadian Simmentals by random regression models.

Stayability to consecutive calvings was selected as a measure of cow longevity in the Canadian Simmental population. Calving performance data on 188,579 cows and culling information from the Total Herd Reporting System were used to determine whether a cow stayed in a herd for her second and later (up to the eighth) calvings, given that she had calved as 2 yr old. Binary records (n = 1,164,319) were analyzed with animal linear and threshold models including fixed effects of year of birth by season of birth by parity number and age of cow at first calving by parity number and random effects of contemporary group (CG) defined as herd of birth within year by season, animal additive genetic effect, and a cow permanent environmental (PE) effect.

Genetic associations of ketosis and displaced abomasum with milk production traits in early first lactation of Canadian Holsteins.

The aim of this study was to investigate the genetic associations of ketosis and displaced abomasum with milk production traits in early first lactation of Canadian Holsteins. Health data recorded by producers were available from the national dairy cattle health system in Canada. Test-day records of milk, fat, and protein yields were obtained from the routine milk recoding scheme.

Development of a genetic evaluation for body condition score for Canadian Holsteins.

Valacta (Sainte-Anne-de-Bellevue, Québec, Canada) is the Canadian Dairy Herd Improvement organization responsible for milk recording in Québec and Atlantic provinces. Up to 14 first-lactation body condition score (BCS) records were collected per cow (average of 2.5 records per cow), allowing the trait to be described by a random regression animal model so that animals could be ranked by the shape of their BCS curve.

Relationship between body condition score and health traits in first-lactation Canadian Holsteins.

The objective of this research was to estimate daily genetic correlations between longitudinal body condition score (BCS) and health traits by using a random regression animal model in first-lactation Holsteins. The use of indicator traits may increase the rate of genetic progress for functional traits relative to direct selection for functional traits. Indicator traits of interest are those that are easier to record, can be measured early in life, and are strongly genetically correlated with the functional trait of interest.

Genetic parameters for producer-recorded health data in Canadian Holstein cattle.

Health traits are of paramount importance for economic dairy production. Improvement in liability to diseases has been made with better management practices, but genetic aspects of health traits have received less attention. Dairy producers in Canada have been recording eight health traits (mastitis (MAST), lameness (LAME), cystic ovarian disease (COD), left displaced abomasum (LDA), ketosis (KET), metritis (MET), milk fever (MF) and retained placenta (RP)) since April 2007.

Test-day somatic cell score, fat-to-protein ratio and milk yield as indicator traits for sub-clinical mastitis in dairy cattle.

Test-day (TD) records of milk, fat-to-protein ratio (F:P) and somatic cell score (SCS) of first-lactation Canadian Holstein cows were analysed by a three-trait finite mixture random regression model, with the purpose of revealing hidden structures in the data owing to putative, sub-clinical mastitis. Different distributions of the data were allowed in 30 intervals of days in milk (DIM), covering the lactation from 5 to 305 days. Bayesian analysis with Gibbs sampling was used for model inferences.