Genetic analysis of feed efficiency and novel feeding behavior traits measured in group-housed broilers using electronic feeders

This study aimed to estimate genetic parameters for feeding behavior (FB) traits and to assess their genetic relationship with performance traits in group-housed broilers. In total, 99,472,151 visits were recorded for 95,711 birds between 2017 and 2022 using electronic feeders. The visits were first clustered into 2,667,617 daily observations for ten FB traits: daily feed intake (DFI), daily number of visits (NVIS), time spent at the feeders (TSF), number of visited feeders (NVF), visiting activity interval (VAI), feeding rate (FR), daily number of meals (NMEAL), average intake per meal (INTMEAL), number of visits per meal (VISMEAL) and interval between meals (MEALIVL). All FB traits were then considered as the average per bird across the feeding test period. Three growth traits (body weight at the start - SBW and at the end of the feeding test - FBW, and weight gain over the test period - BWG), and 2 feed efficiency (FE) traits (Feed Conversion Rate - FCR and Residual Feed Intake - RFI) were also recorded. The (co)variance components were estimated using multitrait animal mixed models. For growth and FE, the heritability (h2) estimates were moderate, ranging from 0.20 ± 0.01 (BWG) to 0.32 ± 0.02 (RFI). Overall, the h2 estimates for FB traits were higher than for productive traits, ranging from 0.31 ± 0.01 (DFI) to 0.56 ± 0.02 (TSF). DFI presented high genetic correlations (0.53-0.86) with all performance traits. Conversely, the remaining FB traits presented null to moderate genetic correlations with these traits, ranging from -0.38 to 0.42 for growth traits and between -0.14 and 0.25 for FE traits. Genetic selection for favorable feeding behavior is expected to exhibit a fast genetic response. The results suggest that it is possible to consider different feeding strategies without compromising the genetic progress of FE. Conversely, breeding strategies prioritizing a higher bird activity might result in lighter broiler lines in the long term, given the negative genetic correlations between visit-related traits (NV, NVF, and NMEAL) and growth traits (SBW and FBW).

Risk Factor Analysis and Genetic Parameter Estimation for Pre-Weaning Mortality Traits in Boer, Spanish, and Crossbred Goat Kids

The objectives of this study were to evaluate fixed risk factors associated with PWM and to estimate genetic parameters for PWM. A total of 927 birth records from a mixed population of purebred and crossbred Boer and Spanish goats born between 2016 and 2023 at the International Goat Research Center (IGRC) were used for this study. Four binary traits were studied: D0-3 (death within 3 days after birth), D4-60 (death between 4 and 60 days), D61-90 (death between 61 and 90 days), and D0-90 (death within 90 days). Logistic regression models were used to evaluate the risk factors associated with PWM traits. Bayesian threshold models and Gibbs sampling were used to estimate the genetic parameters. Birth weight, season, litter size, sex, dam age, breed, and heterosis were found to be significantly associated with at least one of the PWM traits. Heritability estimates were 0.263, 0.124, 0.080, and 0.207, for D0-3, D4-60, D61-90, and D0-90, respectively. The genetic correlations between the studied traits ranged from 0.892 (D0-3 and D0-90) to 0.999 (D0-3 and D61-90). These results suggest that PWM in goats is influenced by both non-genetic and genetic factors and can be reduced by management, genetic selection, and crossbreeding approaches.

Genetic aspects of immunoglobulins and cyclophilin A in milk as potential indicators of mastitis resistance in Holstein cows

Mastitis is one of the most frequent and costly diseases affecting dairy cattle. Natural antibodies (immunoglobulins) and cyclophilin A (CyPA), the most abundant member of the family of peptidyl prolyl cis/trans isomerases, in milk may serve as indicators of mastitis resistance in dairy cattle. However, genetic information for CyPA is not available, and knowledge on the genetic and nongenetic relationships between these immune-related traits and somatic cell score (SCS) and milk yield in dairy cattle is sparse. Therefore, we aimed to comprehensively evaluate whether immune-related traits consisting of 5 Ig classes (IgG, IgG1, IgG2, IgA, and IgM) and CyPA in the test-day milk of Holstein cows can be used as genetic indicators of mastitis resistance by evaluating the genetic and nongenetic relationships with SCS in milk. The nongenetic factors affecting immune-related traits and the effects of these traits on SCS were evaluated. Furthermore, the genetic parameters of immune-related traits according to health status and genetic relationships under different SCS environments were estimated. All immune-related traits were significantly associated with SCS and directly proportional. Additionally, evaluation using a classification tree revealed that IgA, IgG2, and IgG were associated with SCS levels. Genetic factor analyses indicated that heritability estimates were low for CyPA (0.08) but moderate for IgG (0.37), IgA (0.44), and IgM (0.44), with positive genetic correlations among Ig (0.25-0.96). We also evaluated the differences in milk yield and SCS of cows between the low and high groups according to their sires' estimated breeding value for immune-related traits. In the high group, IgA had a significantly lower SCS in milk at 7 to 30 d compared with that in the low group. Furthermore, the Ig in milk had high positive genetic correlations between healthy and infected conditions (0.82-0.99), suggesting that Ig in milk under healthy conditions could interact with those under infected conditions, owing to the genetic ability based on the level of Ig in milk. Thus, Ig in milk are potential indicators for the genetic selection of mastitis resistance. However, because only the relationship between immune-related traits and SCS was investigated in this study, further study on the relationship between clinical mastitis and Ig in milk is needed before Ig can be used as an indicator of mastitis resistance.

Evaluation of Genetic Parameters and Comparison of Stress Tolerance Traits in Different Strains of Litopenaeus vannamei

Litopenaeus vannamei stands out globally in aquaculture for its fast growth, broad salt tolerance, disease resistance, and high protein levels. Selective breeding requires the precise estimation of the variance components and genetic parameters for important traits. This study formed lineages from 20 full sibling families of L. vannamei, with progenitors from Thailand and the USA. We then assessed the genetic resilience traits of juvenile shrimp from these families to high ammonia-N, high pH, and low salinity by performing a 96 h acute toxicity test. Mortality rates for the families under 96 h exposure to high ammonia-N, high pH, and low salinity were 19.52-92.22%, 23.33-92.22%, and 19.33-80.00%, respectively, showing significant variance in stress tolerance among families (p < 0.05). Survival heritability estimates, using threshold male and female models, were 0.44 ± 0.12 in high ammonia-N, 0.41 ± 0.12 in high pH, and 0.27 ± 0.08 in low salinity, respectively. Genetic correlations between growth and stress resistance traits varied from 0.0137 ± 0.2406 to 0.8327 ± 0.0781, and phenotypic correlations ranged from 0.0019 ± 0.0590 to 0.6959 ± 0.0107, indicating a low-to-high positive correlation significant at (p < 0.05). It was found that the survival rate of families No. 2 and No. 9 was higher under high ammonia-N and high pH stresses, while the survival rate of family No. 10 was higher under low salinity stress after comparing two selection criteria, the breeding values and phenotypic values. Thus, these three families are identified as potential breeding program candidates. Through the creation of a genetic parameter estimation model, the genetic variances across mating combinations for stress resistance traits were obtained and families with heightened stress resistance were identified, laying the groundwork for enhanced genetic selection of L. vannamei.

Optimizing selection strategy for enhancing reproduction efficiency in Indian crossbred goats using milk productivity as a selection criterion

The present study was aimed at optimizing the selection strategy for enhancing reproductive efficiency and milk productivity of Alpine × Beetal crossbred goats. The data set included 2949 milk trait records across parities and 1389 milk records from first parity and corresponding reproductive traits. The traits included for analysis were 150-day milk yield (150DMY), days in milk (DIM), peak yield (PY) and total milk yield (TMY). The litter size (LS) and litter weight (LW) were used for specifically formulating selection plan using indirect selection. The least squares mean for lactation traits during the first parity were 150DMY: 195.32 ± 2.09 kg, DIM: 236.42 ± 3.04 days, PY: 1.82 ± 0.02 kg, TMY: 269.62 ± 4.52 kg. Notably, Alpine × Beetal goats demonstrated genetic superiority pan India for milk productivity as compared to other native goat breeds. The least squares mean for 150DMY across all parities was 236 ± 3.13 kg. An animal model employing average information restricted maximum likelihood was used for (co)variance component estimation to get the genetic parameters. The analysis revealed total heritability estimates for 150DMY, DIM, PY and TMY as 0.18 ± 0.06, 0.04 ± 0.04, 0.12 ± 0.06 and 0.08 ± 0.05, respectively. Repeatability estimates for 150DMY, DIM, and TMY were 0.28 ± 0.04, 0.21 ± 0.03 and 0.37 ± 0.03, respectively. Bivariate analysis of 150DMY with reproductive traits revealed heritability for LS and LW as 0.05 ± 0.01 and 0.10 ± 0.01, respectively using Gibbs sampling. Strong and positive genetic correlations of 150DMY with other production and reproduction traits was observed, such as DIM (0.72), PY (0.98), TMY (0.88), LS (0.57) and LW (0.33). Moderate heritability and repeatability estimate of 150DMY, along with its positive correlation with production and reproductive traits suggested it as a suitable selection criterion for early selection and overall genetic progress of lactation traits. The genetic trend analysis showed an overall improvement in all these traits, with observed gain of 98.4 g per year for 150DMY, 0.04 days per year for DIM, 0.5 g per year for PY and 220.5 g per year for TMY. We observed that selecting based on 150DMY would lead to a favourable indirect improvement for LW as 79 g and LS 0.04 units per generation. We, therefore, recommend employing 150DMY as the single trait selection criteria to enhance both milk productivity and reproductive potential of Alpine × Beetal goats.

Estimation of genetic parameters for visceral diseases of fattening Japanese Black cattle in Shimane Prefecture, Japan

In this study, the genetic parameters of major visceral diseases were estimated using the postmortem inspection records of 9057 fattening Japanese Black cattle in Shimane Prefecture, Japan, and the genetic correlation between visceral diseases and carcass traits was analyzed. There were six visceral diseases with a prevalence of 5% or higher, namely, pleurisy, pneumonia, bovine abdominal fat necrosis (BFN), rumenitis, hemorrhagic hepatitis, and perihepatitis. Variance components were estimated using the Gibbs sampling method, and the heritability of the visceral disease ranged from 0.07 to 0.49 for perihepatitis and BFN, respectively. Significant negative genetic correlations were identified between pleurisy and rib thickness (-0.32), BFN and carcass weight (-0.29), and BFN and rib eye area (-0.22). No significant genetic correlation was observed among the visceral diseases. The least squares analysis of variance suggested that some visceral diseases decrease the value of carcass traits. In particular, carcass weight and rib eye area in individuals with BFN were 11.7 kg and 1.87 cm2 lower than those of healthy cattle, respectively. Thus, it was inferred that genetic factors were involved in the visceral diseases of fattening Japanese Black cattle in Shimane Prefecture.

Genetic Parameter and Hyper-Parameter Estimation Underlie Nitrogen Use Efficiency in Bread Wheat

Estimation and prediction play a key role in breeding programs. Currently, phenotyping of complex traits such as nitrogen use efficiency (NUE) in wheat is still expensive, requires high-throughput technologies and is very time consuming compared to genotyping. Therefore, researchers are trying to predict phenotypes based on marker information. Genetic parameters such as population structure, genomic relationship matrix, marker density and sample size are major factors that increase the performance and accuracy of a model. However, they play an important role in adjusting the statistically significant false discovery rate (FDR) threshold in estimation. In parallel, there are many genetic hyper-parameters that are hidden and not represented in the given genomic selection (GS) model but have significant effects on the results, such as panel size, number of markers, minor allele frequency, number of call rates for each marker, number of cross validations and batch size in the training set of the genomic file. The main challenge is to ensure the reliability and accuracy of predicted breeding values (BVs) as results. Our study has confirmed the results of bias-variance tradeoff and adaptive prediction error for the ensemble-learning-based model STACK, which has the highest performance when estimating genetic parameters and hyper-parameters in a given GS model compared to other models.

Research Note: Genetic parameters for egg production and clutch-related traits in indigenous Beijing-You chickens

Egg products from indigenous chickens have growing market shares as consumers are pursuing differentiation in egg consumption. The genetic improvement in egg production performance of those breeds is crucial for increasing the economic profit. This study aimed to estimate genetic parameters for egg production and clutch-related traits in indigenous Beijing-You chickens for understanding the genetic architecture and exploring proper biological traits for selection. Data on traits including age at first egg (AFE), egg number (EN), average clutch length (ACL), maximum clutch length (MCL), number of clutches (NC) and pauses (NP), and average pause length (APL) were collected from 4 generations of purebred Beijing-You chickens based on the 43-wk and 66-wk of individual egg production record. The heritabilities, genetic and phenotypic correlations were analyzed by the DMU software with the restricted maximum likelihood method in a multivariate animal model. The results showed that the AFE of Beijing-You chickens was 174.45 d of age, and its heritability was as high as 0.62. The heritability was 0.26 for EN43 and 0.18 for EN66. The clutch traits including ACL, MCL, NC, and NP were moderate to high heritable (h2 = 0.15-0.39), but APL was very low heritable (h2 = 0.05). Genetic correlations were high between AFE and EN (rG(AFE, EN43) = -0.79, rG(AFE, EN66) = -0.39), whereas low between AFE and ACL (rG(AFE, ACL43) = -0.08, rG(AFE, ACL66) = 0.01) and MCL (rG(AFE, MCL) = -0.07). EN had higher correlations with ACL (rG(EN43, ACL43) = 0.59, rG(EN66, ACL66) = 0.40) than that with MCL (rG(EN43, MCL43) = 0.56, rG(EN66, MCL66) = 0.32). The heritability for ACL43 (h2 = 0.38) was higher than that for MCL43 (h2 = 0.33). ACL43 had a positive correlation with EN66 (rG(ACL43, EN66) = 0.62). These results indicated that the egg production of whole laying period could be improved by early selection for AFE and ACL at the same time in Beijing-You chickens.

Single-step genome-wide association for selected milk fatty acids in Dual-Purpose Belgian Blue cows

The aim of this study was to estimate genetic parameters and identify genomic regions associated with selected individual and groups of milk fatty acids (FA) predicted by milk mid-infrared spectrometry in Dual-Purpose Belgian Blue cows. The used data were 69,349 test-day records of milk yield, fat percentage, and protein percentage along with selected individual and groups FA of milk (g/dL milk) collected from 2007 to 2020 on 7,392 first-parity (40,903 test-day records), and 5,185 second-parity (28,446 test-day records) cows distributed in 104 herds in the Walloon Region of Belgium. Data of 28,466 SNPs, located on 29 Bos taurus autosomes (BTA), of 1,699 animals (639 males and 1,060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by each 25-SNP sliding window (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Average daily heritability estimated for the included milk FA traits ranged from 0.01 (C4:0) to 0.48 (C12:0) and 0.01 (C4:0) to 0.42 (C12:0) in the first and second parities, respectively. Genetic correlations found between milk yield and the studied individual milk FA, except for C18:0, C18:1 trans, C18:1 cis-9, were positive. The results showed that fat percentage and protein percentage were positively genetically correlated with all studied individual milk FA. Genome-wide association analyses identified 11 genomic regions distributed over 8 chromosomes [BTA1, BTA4, BTA10, BTA14 (4 regions), BTA19, BTA22, BTA24, and BTA26] associated with the studied FA traits, though those found on BTA14 partly overlapped. The genomic regions identified differed between parities and lactation stages. Although these differences in genomic regions detected may be due to the power of quantitative trait locus detection, it also suggests that candidate genes underlie the phenotypic expression of the studied traits may vary between parities and lactation stages. These findings increase our understanding about the genetic background of milk FA and can be used for the future implementation of genomic evaluation to improve milk FA profile in Dual-Purpose Belgian Blue cows.

Estimation of heritability for milk urea and genetic correlations with milk production traits in 3 Danish dairy breeds

The aim of this study was to estimate genetic parameters for milk urea (MU) content in 3 main Danish dairy breeds. As a part of the Danish milk recording system, milk samples from cows on commercial farms were analyzed for MU concentration (mmol/L) and the percentages of fat and protein. There were 323,800 Danish Holstein, 70,634 Danish Jersey, and 27,870 Danish Red cows sampled with a total of 1,436,580, 368,251, and 133,922 test-day records per breed, respectively, included in the data set. Heritabilities for MU were low to moderate (0.22, 0.18, and 0.24 for the Holstein, Jersey, and Red breeds, respectively). The genetic correlation was close to zero between MU and milk yield in Jersey and Red, and -0.14 for Holstein. The genetic correlations between MU and fat and protein percentages, respectively, were positive for all 3 dairy breeds. Herd-test-day explained 51%, 54%, and 49% of the variation in MU in Holstein, Jersey, and Red, respectively. This indicates that MU levels in milk can be reduced by farm management. The current study shows that there are possibilities to influence MU by genetic selection as well as by farm management.

Identifying Genetic Architecture of Carcass and Meat Quality Traits in a Ningxiang Indigenous Pig Population

Ningxiang pig is a breed renowned for its exceptional meat quality, but it possesses suboptimal carcass traits. To elucidate the genetic architecture of meat quality and carcass traits in Ningxiang pigs, we assessed heritability and executed a genome-wide association study (GWAS) concerning carcass length, backfat thickness, meat color parameters (L.LD, a.LD, b.LD), and pH at two postmortem intervals (45 min and 24 h) within a Ningxiang pig population. Heritability estimates ranged from moderate to high (0.30~0.80) for carcass traits and from low to high (0.11~0.48) for meat quality traits. We identified 21 significant SNPs, the majority of which were situated within previously documented QTL regions. Furthermore, the GRM4 gene emerged as a pleiotropic gene that correlated with carcass length and backfat thickness. The ADGRF1, FKBP5, and PRIM2 genes were associated with carcass length, while the NIPBL gene was linked to backfat thickness. These genes hold the potential for use in selective breeding programs targeting carcass traits in Ningxiang pigs.

Genomic-based genetic parameters for resilience across lactations in North American Holstein cattle based on variability in daily milk yield records

Considering the increasing challenges imposed by climate change and the need to improve animal welfare, breeding more resilient animals capable of better coping with environmental disturbances is of paramount importance. In dairy cattle, resilience can be evaluated by measuring the longitudinal occurrences of abnormal daily milk yield throughout lactation. Aiming to estimate genetic parameters for dairy cattle resilience, we collected 5,643,193 daily milk yield records on automatic milking systems (milking robots) and milking parlors across 21,350 lactations 1 to 3 of 11,787 North American Holstein cows. All cows were genotyped with 62,029 SNPs. After determining the best fitting models for each of the 3 lactations, daily milk yield residuals were used to derive 4 resilience indicators: weighted occurrence frequency of yield perturbations (wfPert), accumulated milk losses of yield perturbations (dPert), and log-transformed variance (LnVar) and lag-1 autocorrelation (r_auto) of daily yield residuals. The indicator LnVar presented the highest heritability estimates (±standard error), ranging from 0.13 ± 0.01 in lactation 1 to 0.15 ± 0.02 in lactation 2; the other 3 indicators had relatively lower heritabilities across the 3 lactations (0.01-0.06). Based on bivariate analyses of each resilience indicator across lactations, stronger genetic correlations were observed between lactations 2 and 3 (0.88-0.96) than between lactations 1 and 2 or 3 (0.34-0.88) for dPert, LnVar, and r_auto. For the pairwise comparisons of different resilience indicators within each lactation, dPert had the strongest genetic correlations with wfPert (0.64) and r_auto (0.53) in lactation 1, whereas the correlations in lactations 2 and 3 were more variable and showed relatively high standard errors. The genetic correlation results indicated that different resilience indicators across lactations might capture additional biological mechanisms and should be considered as different traits in genetic evaluations. We also observed favorable genetic correlations of these resilience indicators with longevity and Net Merit index, but further biological validation of these resilience indicators is needed. In conclusion, this study provided genetic parameter estimates for different resilience indicators derived from daily milk yields across the first 3 lactations in Holstein cattle, which will be useful when potentially incorporating these traits in dairy cattle breeding schemes.

Genetic parameters of sole lesion recovery in Holstein cows

Sole hemorrhage and sole ulcers, referred to as sole lesions, are important causes of lameness in dairy cattle. The objective of this study was to estimate the genetic parameters of a novel trait reflecting how well cows recovered from sole lesions and the genetic correlation of this trait with overall susceptibility to sole lesions. A cohort of Holstein dairy cows was prospectively enrolled on 4 farms and assessed at 4 timepoints: before calving, immediately after calving, in early lactation, and in late lactation. At each timepoint, sole lesions were recorded at the claw level by veterinary surgeons and used to define 2 binary traits: (1) susceptibility to sole lesions-whether animals were affected with sole lesions at least once during the study or were unaffected at every assessment, and (2) sole lesion recovery-whether sole lesions healed between early and late lactation. Animals were genotyped and pedigree details extracted from the national database. Analyses were conducted with BLUPF90 software in a single-step framework; genetic parameters were estimated from animal threshold models using Gibbs sampling. The genetic correlation between both traits was approximated as the correlation between genomic estimated breeding values, adjusting for their reliabilities. A total of 2,025 animals were used to estimate the genetic parameters of sole lesion susceptibility; 44% of animals recorded a sole lesion at least once during the study period. The heritability of sole lesion susceptibility, on the liability scale, was 0.25 (95% highest density interval = 0.16-0.34). A total of 498 animals were used to estimate the genetic parameters of sole lesion recovery; 71% of animals had recovered between the early and late lactation assessments. The heritability of sole lesion recovery, on the liability scale, was 0.27 (95% highest density interval = 0.02-0.52). The approximate genetic correlation between each trait was -0.11 (95% confidence interval = -0.20 to -0.02). Our results indicate that recovery from sole lesions is heritable. If this finding is corroborated in further studies, it may be possible to use selective breeding to reduce the frequency of chronically lame cows. As sole lesion recovery appears to be weakly genetically related to sole lesion susceptibility, successful genetic improvement of sole lesion recovery would benefit from selection on this trait directly.

A meta-analysis of the genetic contribution to greenhouse gas emission in sheep

The objective of this study was to use a random-effects model of meta-analysis to merge various heritability estimates of different gas emission traits (methane yield [METY], methane production [METP], carbon dioxide production [CO₂ ], the sum of carbon dioxide and methane production [METP + CO₂ ], METP METP + CO 2 ratio, and oxygen consumption [O₂ ]) and their genetic association with growth and partial efficiency traits in sheep. A total of 53 genetic correlations and 47 heritability estimates from 13 scientific articles were used in the meta-analysis. The included papers were published between 2010 and 2022. To measure heterogeneity, Chi-square (Q) test was performed, and the I² statistic was determined. The average heritability estimates for the studied traits were low to moderate and ranged from 0.137 (for METY) to 0.250 (for METP + CO₂ ). The heterogeneity test of heritability estimates indicated that heritability estimates for METY, O₂ consumption, and METP METP + CO 2 had low Q values and non-significant heterogeneity (p > 0.10). However, the average heritability estimates for other traits experienced significant heterogeneities (p < 0.10). The genetic correlation estimate between METP with O₂ was -0.597 (p < 0.05), but its genetic correlations with other gas traits ranged from 0.593 (with METP + CO₂ ) to 0.653 (CO₂ ; p < 0.05). Also, mean estimates of genetic correlation between METP with live weight (LW), feed intake (FI), and residual feed intake (RFI) were 0.719, 0.598, and 0.408, respectively. The genetic correlations of CO₂ with performance traits varied from 0.641 (with RFI) to 0.833 (with FI; p < 0.05). This meta-analysis showed gas emission traits in sheep are under low-to-moderate genetic control. The average genetic parameter estimates obtained in this study could be considered in the genetic selection programmes for sheep, especially when there is no access to accurate phenotypic records or genetic parameter estimates for gas emission traits.

Direct-Maternal Genetic Parameters for Litter Size and Body Weight of Piglets of a New Black Breed for the Taiwan Black Hog Market

The objective of this study was to estimate the genetic parameters of litter size and piglet weight from farrowing to weaning in KHAPS Black sows. The genetic parameters investigated were the direct (h²_d), maternal (h²_m), realized (h²_r), and total (h²_T) heritability, as well as correlations (r_d, r_m, and r_dm) within and between traits. The analyses were performed using single- and three-trait animal models with and without maternal genetic effects. In the three-trait model with maternal genetic effect, all estimates of h²_d and h²_m were significantly different from zero except the h²_d of mean birth weight. Positive values of r_d and r_m between traits were observed as expected in the range of 0.322-1.000. Negative values of r_dm were found within and between traits and were less associated with mean piglet weight traits than litter size traits. Estimates of h²_T were consistently larger than those of h²_r in both the single- and three-trait model analyses. In addition, the three-trait model can take into account the association between the traits, so the estimates are more accurate with smaller SEs. In conclusion, maternal genetic effects were not negligible in this study, and thus, a multiple-trait animal model with maternal genetic effects and full pedigree is recommended to assist future pig breeding decisions in this new breed.

Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows

This study aimed to estimate genetic parameters and identify genomic region(s) associated with selected cheese-making properties (CMP) in Dual-Purpose Belgian Blue (DPBB) cows. Edited data were 46,301 test-day records of milk yield, fat percentage, protein percentage, casein percentage, milk calcium content (CC), coagulation time (CT), curd firmness after 30 min from rennet addition (a30), and milk titratable acidity (MTA) collected from 2014 to 2020 on 4,077 first-parity (26,027 test-day records), and 3,258 second-parity DPBB cows (20,274 test-day records) distributed in 124 herds in the Walloon Region of Belgium. Data of 28,266 SNP, located on 29 Bos taurus autosomes (BTA) of 1,699 animals were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 25 consecutive SNPs (with an average size of ∼2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Heritability estimates for the included CMP ranged from 0.19 (CC) to 0.50 (MTA), and 0.24 (CC) to 0.41 (MTA) in the first and second parity, respectively. The genetic correlation estimated between CT and a30 varied from -0.61 to -0.41 and from -0.55 to -0.38 in the first and second lactations, respectively. Negative genetic correlations were found between CT and milk yield and composition, while those estimated between curd firmness and milk composition were positive. Genome-wide association analyses results identified 4 genomic regions (BTA1, BTA3, BTA7, and BTA11) associated with the considered CMP. The identified genomic regions showed contrasting results between parities and among the different stages of each parity. It suggests that different sets of candidate genes underlie the phenotypic expression of the considered CMP between parities and lactation stages of each parity. The findings of this study can be used for future implementation and use of genomic evaluation to improve the cheese-making traits in DPBB cows.

Genetic analysis of fetal loss in Holstein cattle

Pregnancy loss is recognized as one of the major factors contributing to poor reproductive performance in dairy cattle. Here, we performed a comprehensive genetic analysis of fetal loss, defined as a pregnancy loss that occurs after detection of a viable embryo around 42 d of gestation. The objectives of this study were to reveal (1) whether fetal loss is heritable and, hence, whether it will respond to selection, and (2) to what extent current fertility traits, such as daughter pregnancy rate, are associated with fetal loss. Data consisted of 59,308 confirmed pregnancy or fetal loss records distributed across nulliparous heifers and primiparous and multiparous cows. We defined fetal loss as a binary trait (yes vs. no) or as an ordinal trait (pregnancy maintenance, early fetal loss ≤150 d of gestation, and late fetal loss >150 d of gestation), and we assessed both linear and threshold models. Heritability estimates for fetal loss ranged from 1 to 18%, depending upon parity, trait definition, and statistical model used. Heritability estimates were greater for lactating cows than for nonlactating nulliparous heifers. Threshold models were able to capture more additive genetic variance and, thus, yielded higher heritability estimates than linear models. Notably, fetal loss traits were highly genetically correlated with each other but only weakly correlated with current fertility traits included in the national genetic evaluation. Overall, our study provides evidence that fetal loss is heritable enough to make genetic selection for reducing fetal loss and improving pregnancy maintenance feasible. In addition, our results suggest that fetal loss is largely independent from current traits used to select for cow fertility, and thus current breeding efforts have unfortunately little effect on reducing the incidence of fetal loss.

Genetic parameters for dairy calf and replacement heifer wellness traits and their association with cow longevity and health indicators in Holstein cattle

High mortality and involuntary culling rates cause great economic losses to the worldwide dairy cattle industry. However, there is low emphasis on wellness traits in replacement animals (dairy calves and replacement heifers) during their development stages in modern dairy cattle breeding programs. Therefore, the main objectives of this study were to estimate genetic parameters of wellness traits in replacement cattle (replacement wellness traits) and obtain their genetic correlations with 12 cow health and longevity traits in the Chinese Holstein population. Seven replacement wellness traits were analyzed, including birth weight, survival from 3 to 60 d (Sur1), survival from 61 to 365 d (Sur2), survival from 366 d to the first calving (Sur3), calf diarrhea, calf pneumonia, and calf serum total protein (STP). Single and bivariate animal models were employed to estimate (co)variance components using the data from 189,980 Holstein cattle. The genetic correlations between replacement wellness traits and cow longevity, health traits were calculated by employing bivariate models, including 6 longevity traits and 6 health traits (clinical mastitis, metritis, ketosis, displaced abomasum, milk fever, and hoof health or hoof disease). The estimated heritabilities (± SE) were 0.335 (± 0.008), 0.088 (± 0.005), 0.166 (± 0.006), 0.102 (±0 .006), 0.048 (± 0.003), 0.063 (± 0.004), and 0.170 (± 0.019) for birth weight, Sur1, Sur2, Sur3, pneumonia, diarrhea, and STP, respectively. The majority of the genetic correlations among the 7 replacement wellness traits were negligible. The genetic correlations among Sur1, Sur2, and Sur3 ranged from 0.112 (Sur1 and Sur3) to 0.445 (Sur1 and Sur2) when fitting a linear model (estimates in the observed scale), and from 0.560 (Sur1 and Sur3) to 0.773 (Sur1 and Sur2) when fitting a threshold model (estimates in the liability scale). The genetic correlations between replacement wellness and cow longevity were low (absolute value lower than 0.30), but some of them were significantly different from zero. Compared with other replacement wellness traits, Sur3 and STP had relatively high genetic correlations with cow longevity. Replacement wellness traits are heritable and can be improved through direct genetic and genomic selection. The results from the current study will contribute for better balancing dairy cattle breeding goals to genetically improve dairy cattle wellness in the period from birth to first calving.

Genome-wide association for milk urea concentration in Dual-Purpose Belgian Blue cows

The objectives of this study were to estimate genetic parameters and identify genomic regions associated with milk urea concentration (MU) in Dual-Purpose Belgian Blue (DPBB) cows. The data were 29,693 test-day records of milk yield (MY), fat yield (FY), protein yield (PY), fat percentage (FP), protein percentage (PP) and MU collected between 2014 and 2020 on 2498 first parity cows (16,935 test-day records) and 1939 second-parity cows (12,758 test-day records) from 49 herds in the Walloon Region of Belgium. Data of 28,266 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA), on 1699 animals (639 males and 1060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method using a single chain of 100,000 iterations after a burn-in period of 20,000. SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by windows of 25 consecutive SNPs (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. The mean (SD) of MU was 22.89 (10.07) and 22.35 (10.07) mg/dl for first and second parity, respectively. The mean (SD) heritability estimates for daily MU were 0.18 (0.01) and 0.22 (0.02), for first and second parity, respectively. The mean (SD) genetic correlations between daily MU and MY, FY, PY, FP and PP were -0.05 (0.09), -0.07 (0.11), -0.03 (0.13), -0.05 (0.08) and -0.03 (0.11) for first parity, respectively. The corresponding values estimated for second parity were 0.02 (0.10), -0.02 (0.09), 0.02 (0.08), -0.08 (0.06) and -0.05 (0.05). The genome-wide association analyses identified three genomic regions (BTA2, BTA3 and BTA13) associated with MU. The identified regions showed contrasting results between parities and among different stages within each parity. This suggests that different groups of candidate genes underlie the phenotypic expression of MU between parities and among different lactation stages within a parity. The results of this study can be used for future implementation and use of genomic evaluation to reduce MU in DPBB cows.

Role of CSN2, CSN3, and BLG genes and the polygenic background in the cattle milk protein profile

To devise better selection strategies in dairy cattle breeding programs, a deeper knowledge of the role of the major genes encoding for milk protein fractions is required. The aim of the present study was to assess the effect of the CSN2, CSN3, and BLG genotypes on individual protein fractions (α_S1-CN, α_S2-CN, β-CN, κ-CN, β-LG, α-LA) expressed qualitatively as percentages of total nitrogen content (% N), quantitatively as contents in milk (g/L), and as daily production levels (g/d). Individual milk samples were collected from 1,264 Brown Swiss cows reared in 85 commercial herds in Trento Province (northeast Italy). A total of 989 cows were successfully genotyped using the Illumina Bovine SNP50 v.2 BeadChip (Illumina Inc.), and a genomic relationship matrix was constructed using the 37,519 SNP markers obtained. Milk protein fractions were quantified and the β-CN, κ-CN, and β-LG genetic variants were identified by reversed-phase HPLC (RP-HPLC). All protein fractions were analyzed through a Bayesian multitrait animal model implemented via Gibbs sampling. The effects of days in milk, parity order, and the CSN2, CSN3, and BLG genotypes were assigned flat priors in this model, whereas the effects of herd and animal additive genetic were assigned Gaussian prior distributions, and inverse Wishart distributions were assumed for the respective co-variance matrices. Marginal posterior distributions of the parameters of interest were compared before and after the inclusion of the effects of the 3 major genes in the model. The results showed that a high portion of the genetic variance was controlled by the major genes. This was particularly apparent in the qualitative protein profile, which was found to have a higher heritability than the protein fraction contents in milk and their daily yields. When the genes were included individually in the model, CSN2 was the major gene controlling all the casein fractions except for κ-CN, which was controlled directly by the CSN3 gene. The BLG gene had the most influence on the 2 whey proteins. The genetic correlations showed the major genes had only a small effect on the relationships between the protein fractions, but through comparison of the correlation coefficients of the proteins expressed in different ways they revealed potential mechanisms of regulation and competitive synthesis in the mammary gland. The estimates for the effects of the CSN2 and CSN3 genes on protein profiles showed overexpression of protein synthesis in the presence of the B allele in the genotype. Conversely, the β-LG B variant was associated with a lower concentration of β-LG compared with the β-LG A variant, independently of how the protein fractions were expressed, and it was followed by downregulation (or upregulation in the case of the β-LG B) of all other protein fractions. These results should be borne in mind when seeking to design more efficient selection programs aimed at improving milk quality for the efficiency of dairy industry and the effect of dairy products on human health.

Genetic relationships of feed efficiency and growth traits with carcass traits in Japanese Shorthorn cattle

In this study, we examined genetic parameters for feed efficiency, growth, and carcass traits in Japanese Shorthorn cattle, based on 714 performance tests and 15,790 field carcass records. Feed efficiency traits, including residual feed intake (RFI) and residual body weight gain (RG), were calculated. Single-trait and two-trait animal models were used to estimate heritability and genetic correlations. Heritability estimates for feed efficiency traits were found to be low to moderate (ranging from 0.03 to 0.36); notably, heritability was moderate for RG and low for RFI. Estimates for genetic correlations between feed efficiency traits and average daily gain (DG) were favorably moderate to high (absolute values of 0.43-0.85), and those with daily feed intake were low (absolute values of 0.00-0.32). We also estimated a high genetic correlation between RG and DG. The backfat thickness (BF) of bull calves showed favorable or no genetic correlation estimates with feed efficiency and growth traits, whereas RG and BF showed favorable or no genetic correlation estimates with carcass traits. Our findings indicate that genetic improvements in both feed utilization ability and carcass traits could be achieved by utilizing RG and BF in Japanese Shorthorn cattle.

Longitudinal genetic analysis of semen production traits in Holstein bulls according to a random regression animal models on age

Here we used random regression animal models (RRAMs) to investigate genetic change over age in the semen volume (VOL) and sperm concentration (CON) of Holstein bulls. We used 35,294 collection records from 1284 Holstein bulls and their 4166 pedigree records. The models included year and month of collection, collection place, collection method, and number of collections attempted for each day and month of age (second-order regressions) as fixed effects; technician as a random effect; and additive genetic and permanent environment as random regressions (first-order regressions). We examined two RRAMs with homogeneous and heterogeneous residual variances (RRAM1 and RRAM2, respectively). By using RRAM1, heritability for VOL and CON increased from 0.08 to 0.61 and 0.18 to 0.57, respectively, between 10 and 126 months of age. By using RRAM2, heritability for VOL increased from 0.11 to 0.28 between 10 and 24 months of age for young bulls and increased from 0.08 to 0.48 between 25 and 126 months of age for mature bulls; heritability for CON ranged from 0.18 to 0.19 for young bulls and increased from 0.10 to 0.48 for mature bulls. Posterior genetic correlations between young ages and older ages were strongly positive for VOLs but weak for CONs.

Genetic Effect and Growth Curve Parameter Estimation under Heat Stress in Slow-Growing Thai Native Chickens

Heat stress is becoming a major problem because it limits growth in poultry production, especially in tropical areas. The development of genetic lines of Thai native chickens (TNC) which can tolerate the tropical climate with the least compromise on growth performance is therefore necessary. This research aims to analyze the appropriate growth curve function and to estimate the effect of heat stress on the genetic absolute growth rate (AGR) in TNC and Thai synthetic chickens (TSC). The data comprised 35,355 records for body weight from hatching to slaughtering weight of 7241 TNC and 10,220 records of 2022 TSC. The best-fitting growth curve was investigated from three nonlinear regression models (von Bertalanffy, Gompertz, and logistic) and used to analyze the individual AGR. In addition, a repeatability test-day model on the temperature-humidity index (THI) function was used to estimate the genetic parameters for heat stress. The Gompertz function produced the lowest mean squared error (MSE) and Akaike information criterion (AIC) and highest the pseudo-coefficient of determination (Pseudo-R²) in both chicken breeds. The growth rates in TSC were higher than TNC; the growth rates of males were greater than females, but the age at inflection point in females was lower than in males in both chicken breeds. The THI threshold started at 76. The heritability of the AGR was 0.23 and 0.18 in TNC and TSC, respectively. The additive variance and permanent environmental variance of the heat stress effect increased sharply after the THI of 76. The growth rate decreased more severely in TSC than TNC. In conclusion, the Gompertz function can be applied with the THI to evaluate genetic performance for heat tolerance and increase growth performance in slow-growing chicken.

Genomic loci and genetic parameters for uterine diseases in first-parity Holstein cows and associations with milk production and fertility

Based on the clinical stage (e.g., vaginal discharge) and bacterial species, several forms of uterine diseases (UD) exist and can be classified as different traits [i.e., different stages of endometritis (EM) and metritis (MET)], which may differ in their genetic background and causal physiological mechanisms. Consequently, the present study aimed to study (1) the effect of UD on 305-d lactation and fertility, (2) the estimation of heritabilities for UD traits using pedigree- and SNP-based relationships, and (3) genome-wide associations to detect significant SNP markers and to infer candidate genes for UD traits. The data set contained herd manager and veterinarian recorded UD traits of 14,810 first-lactating genotyped Holstein cows from 63 large-scale contract herds. Binary defined UD traits (healthy or diseased) according to the clinical stage were endometritis catarrhalis (EM I), endometritis mucopurulenta (EM II), endometritis purulenta (EM III), pyometra (EM IV), endometritis (EM_SOD; superordinate diagnosis = no specific clinical stage defined), and MET. The binary defined trait UDall included all EM and MET diagnoses. The prevalence of UDall was 26.7%. The effect of UD on 305-d lactation and fertility was estimated via linear and generalized linear mixed models. We applied linear single-trait animal models and threshold models to estimate pedigree- and SNP-based heritabilities for UD traits, and bivariate linear models for genetic correlation estimations between UDall with 305-d lactation and fertility traits. A diagnosis for UDall had significant unfavorable effects on the female fertility traits calving interval, interval from calving to first service, days open, and nonreturn rate after 90 d, but was unrelated to 305-d lactation records for production traits milk yield, protein yield, and fat yield. Heritabilities for UDall and EM stages were close to zero, displaying maximal values of 0.05 for pedigree and 0.07 for SNP-based relationship matrices. For MET, pedigree- and SNP-based heritabilities were <0.001 and 0.07, respectively. Genetic correlations ranged from 0.20 to 0.31 between UDall with 305-d milk, protein, and fat yield, and from 0.17 to 0.40 with fertility traits. The GWAS revealed 5 SNP on bovine chromosomes (BTA) 1, 8, 10, 23 for UDall, 5 SNP on BTA 26 for EM I, 1 SNP on BTA 19 for EM II, 4 SNP on BTA 2, 18, 20, 25 for EM III, and 4 SNP on BTA 4, 16, 20 for EM IV above the significance threshold. For EM_SOD, we identified 15 significantly associated SNP on 4 chromosomes, and 4 significant SNP on BTA 3, 20, 22, 28 for MET. Marker associations for UD traits were annotated to 24 potential candidate genes using the ENSEMBL database. Six of these genes were previously reported to be involved in uterine defense mechanisms or in endometritis. Further detected genes contribute to immune response mechanisms during bacterial infections. Different SNP significantly influenced different UD stages, explaining the inter-individual variations in clinical severity of uterine infections.

Genetic parameters and weighted single-step genome-wide association study for supernumerary teats in Holstein cattle

Supernumerary teats (SNT) are a common epidermal abnormality of udders in mammals. The SNT negatively affect machine milking ability, udder health, and animal welfare and sometimes act as reservoirs for undesirable bacteria, resulting in economic losses on calves and lactating cows due to the cost of SNT removal surgery, early culling, and low milk yield. This study aimed to analyze the incidence and genetic parameter of SNT and detect SNT-related genes in Chinese Holstein cattle. In this study, the incidence of SNT was recorded in 4,670 Chinese Holstein cattle (born between 2008 and 2017) from 2 farms, including 734 genotyped cows with 114,485 SNPs. The SNT had a total frequency of 9.8% and estimated heritability of 0.22 (SE = 0.07), which were obtained using a threshold model in the studied Chinese Holstein population. Furthermore, we calculated approximate genetic correlations between SNT and the following indicator traits: 12 milk production, 28 body conformation, 5 fertility and reproduction, 5 health, and 9 longevity. Generally, the estimated correlations, such as 305-d milk yield for third parity (-0.55; SE = 0.02) and age at first calving in heifer (0.19; SE = 0.03), were low to moderate. A single-step GWAS was implemented, and 10 genes associated with SNT located in BTA4 were identified. The region (112.70-112.90 Mb) on BTA4 showed the highest genetic variance for SNT. The quantitative trait loci on BTA4 was mapped into the RARRES2 gene, which was previously shown to affect adipogenesis and hormone secretion. The WIF1 gene, which was located in BTA5, was also considered as a candidate gene for SNT. Overall, these findings provide useful information for breeders who are interested in reducing SNT.

Genetic analysis of semen characteristic traits in Norwegian Red bulls at the artificial insemination center

Compared with cow fertility, genetic analyses of bull fertility are limited and based on relatively few animals. The aim of the present study was to estimate genetic parameters for semen characteristics of Norwegian Red bulls at the artificial insemination (AI) center (Geno AI station, Stange, Norway) and to estimate genetic correlations between some of these traits and andrology traits measured at the performance test station. The data from the AI center consisted of records from 137,919 semen collections from 3,145 bulls with information on semen weight, sperm concentration, motility before and after cryopreservation, motility change during cryopreservation, and number of accepted straws made. Data from the performance test station included 12,522 observations from 3,219 bulls on semen volume, concentration, and motility (%) when fresh and after storing for 24 and 48 h. Genetic parameters were estimated using linear animal repeatability models that included fixed effects of year-month of observation, age of bull, interaction between semen collection number, and interval between collections for all traits and type of diluter for postcryopreservation traits. The random effects included test-day, permanent environmental, and additive genetic effects of the bull. Based on records from the AI center, we found that semen weight, sperm concentration, and number of straws were moderately heritable (0.18-0.20), whereas motility had a lower heritability (0.02-0.08). Heritability of motility (%) was higher after cryopreservation than before. Genetic correlations among the semen characteristics ranged from unfavorable (-0.35) to favorable (0.93), with standard errors ranging from 0.02 to 0.22. Among the most precise genetic correlation estimates, number of straws made from a batch correlated favorably with semen weight (0.62 ± 0.06) and sperm concentration (0.44 ± 0.08), whereas sperm concentration was negatively correlated with weight (-0.33 ± 0.09). The genetic correlation between motility (%) before and after cryopreservation was 0.64 ± 0.14, and motility change during cryopreservation had a strong favorable genetic correlation with motility after cryopreservation (-0.93 ± 0.02). The estimated genetic correlation (standard error) between the traits volume, concentration, and motility when fresh measured at the performance test station and their respective corresponding traits at the AI center were 0.83 (0.05), 0.78 (0.09), and 0.49 (0.31). The final product at the AI center (number of accepted straws) correlated genetically favorably with all semen characteristic traits recorded at the performance test station (ranging from 0.51 to 0.67). Our results show that the andrology testing done at the performance test station is a resource to identify the genetically best bulls for AI production.

Genetic Aspects of Somatic Cell Count in Holstein Dairy Cows in Iran

Simple Summary

Holstein Friesian is the dominant breed of modern dairy cattle in Iran, therefore the development of a genetic evaluation system for economically important traits for this population is needed. Genetic parameters for SCS and its genetic correlations with production traits were estimated in Iranian Holstein cows. The moderate heritability for SCS and its low negative genetic correlations with yield traits indicate that genetic selection for decreasing SCS would have a relatively medium genetic progress with no necessarily antagonistic effects on lactation performance. The estimates found in this study can be considered as the first step to include SCS in the national genetic evaluations in Iranian Holsteins using a multiple-trait, multiple-lactation random regression model.

Abstract

The aim of this study was to estimate the genetic parameters of somatic cell count (SCC) and its relationship with production traits in the first three parities in Iranian Holstein dairy cows. Data were 1,891,559 test-day records of SCC, milk yield, and milk compositions on 276,217 lactations on 147,278 cows distributed in 134 herds. The number of test-day records in the first, second and third parities were 995,788 (on 147,278 cows), 593,848 (on 85,153 cows), and 301,923 (on 43,786 cows), respectively. Test-day SCCs were transformed to somatic cell scores (SCS). A random regression test-day animal model through four-trait three-lactation was used to estimate variance components for test-day records of SCS and lactation traits were included. Gibbs sampling was used to obtain marginal posterior distributions for the various parameters using a single chain of 200,000 iterates in which the first 50,000 iterates of each chain were regarded as a burn-in period. The mean heritability estimates for SCS (0.15 to 0.18) were lower than those for milk yield (0.36 to 0.38), fat yield (0.30 to 0.31), protein yield (0.31 to 0.32), fat percentage (0.21 to 0.25), and protein percentage (0.21 to 0.22). Low negative genetic correlations ranging from −0.05 to −0.30 were found between SCS and yield traits (milk, fat, and protein yields). The genetic correlation found between SCS and fat percentage was close to zero, however, a low positive genetic correlation ranging from 0.12 to 0.17 was found between SCS and protein percentage. Based on the results, it can be concluded that genetic selection for decreasing SCS would also increase lactation yield. The estimates found in this study can be used to perform breeding value estimations for national genetic evaluations in Iranian Holsteins using a multiple-trait, multiple-lactation random regression model.

Genetic Analysis of Persistency for Milk Fat Yield in Iranian Buffaloes (Bubalus bubalis)

This study aimed to estimate heritabilities and genetic trends for different persistency measures for milk fat yield and their genetic correlations with 270-day milk yield in Iranian buffaloes. The records of test-day milk fat yield belonging to the first three lactations of buffaloes within 523 herds consisting of 43,818 records were got from the Animal Breeding Center and Promotion of Animal Products of Iran from 1996 to 2012. To fit the lactation curves based on a random regression test-day model, different orders of Legendre polynomial (LP) functions were selected. Three persistency measures were altered according to the specific condition of the lactation curve in buffaloes: (1) The average of estimated breeding values (EBVs) for test day fat yield from day 226 to day 270 as a deviation from the average of EBVs from day 44 to day 62 (PM₁), (2) A summation of contribution for each day from day 53 to day 247 as a deviation from day 248 (PM₂), and (3) The difference between EBVs for day 257 and day 80 (PM₃). The estimates of heritability for PM₁, PM₂, and PM₃ ranged from 0.20 to 0.48, from 0.36 to 0.47, and from 0.19 to 0.35 over the first three lactations, respectively. The estimate of genetic trends for different persistency measures of milk fat yield was not significant over the lactations (P > 0.05). Genetic correlation estimates between various measures of persistency were generally high over the first three lactations. Also, genetic correlations estimates between persistency measures and 270-day milk yield were mostly low and varied from 0.00 to 0.24 (between PM₁ and 270-day milk yield), from −0.19 to 0.13 (between PM₂ and 270-day milk yield), and from −0.02 to 0.00 (between PM₁ and 270-day milk yield) over the first three lactations, respectively. Persistency measures that showed low genetic correlations with milk fat yield were considered the most suitable measures in selection schemes. Besides, medium to high heritability estimates for different persistency measures for milk fat yield indicated that relevant genetic variations detected for these characters could be regarded in outlining later genetic improvement programs of Iranian buffaloes.

Estimation of the genetic parameters of traits relevant to feed efficiency: result from broiler lines divergent for high or low abdominal fat content

Feed consumption represents a major cost in poultry production and improving feed efficiency is one of the important goals in breeding strategies. The present study aimed to analyze the relationship between feed efficiency and relevant traits and find the proper selection method for improving feed efficiency by using the Northeast Agricultural University High and Low Fat broiler lines that were divergently selected for abdominal fat content. A total of 899 birds were used to measure the feed intake (FI), abdominal fat weight (AFW), and body weight traits. The abdominal fat percentage (AFP), feed conversion ratio (FCR), and the residual feed intake (RFI) were calculated for each individual broiler. The differences in the AFW, AFP, and in traits relevant to feed efficiency, such as FCR and RFI, between the fat line and the lean line were analyzed, and the genetic parameters were estimated for AFW, AFP, and feed efficiency relevant traits. The results showed that AFW, AFP, body weight gain (BWG), FI, FCR, and RFI were significantly higher in the fat line compared with the lean line. The heritability of FI, BWG, FCR, RFI, AFW, and AFP were 0.45, 0.28, 0.36, 0.38, 0.33, and 0.30, respectively. Both FCR and RFI showed high positive genetic correlations with FI, AFW, and AFP and relatively low, negative genetic correlations with BWG. The RFI showed much higher positive genetic correlation with the abdominal fat traits than FCR. In addition, the FCR showed negative genetic correlation with body weight of 4 wk (BW4) and 7 wk (BW7), whereas RFI showed positive genetic correlation with BW4 and BW7. The results showed that both RFI and FCR could be used for improving feed efficiency. When selecting against RFI, the AFP could be significantly reduced, and by selecting against FCR, the body weight could be improved simultaneously.

Genetic and nongenetic profiling of milk β-hydroxybutyrate and acetone and their associations with ketosis in Holstein cows

Ketosis is a metabolic disorder of increasing importance in high-yielding dairy cows, but accurate population-wide binary health trait recording is difficult to implement. Against this background, proper Gaussian indicator traits, which can be routinely measured in milk, are needed. Consequently, we focused on the ketone bodies acetone and β-hydroxybutyrate (BHB), measured via Fourier-transform infrared spectroscopy (FTIR) in milk. In the present study, 62,568 Holstein cows from large-scale German co-operator herds were phenotyped for clinical ketosis (KET) according to a veterinarian diagnosis key. A sub-sample of 16,861 cows additionally had first test-day observations for FTIR acetone and BHB. Associations between FTIR acetone and BHB with KET and with test-day traits were studied phenotypically and quantitative genetically. Furthermore, we estimated SNP marker effects for acetone and BHB (application of genome-wide association studies) based on 40,828 SNP markers from 4,384 genotyped cows, and studied potential candidate genes influencing body fat mobilization. Generalized linear mixed models were applied to infer the influence of binary KET on Gaussian-distributed acetone and BHB (definition of an identity link function), and vice versa, such as the influence of acetone and BHB on KET (definition of a logit link function). Additionally, linear models were applied to study associations between BHB, acetone and test-day traits (milk yield, fat percentage, protein percentage, fat-to-protein ratio and somatic cell score) from the first test-day after calving. An increasing KET incidence was statistically significant associated with increasing FTIR acetone and BHB milk concentrations. Acetone and BHB concentrations were positively associated with fat percentage, fat-to-protein ratio and somatic cell score. Bivariate linear animal models were applied to estimate genetic (co)variance components for KET, acetone, BHB and test-day traits within parities 1 to 3, and considering all parities simultaneously in repeatability models. Pedigree-based heritabilities were quite small (i.e., in the range from 0.01 in parity 3 to 0.07 in parity 1 for acetone, and from 0.03-0.04 for BHB). Heritabilites from repeatability models were 0.05 for acetone, and 0.03 for BHB. Genetic correlations between acetone and BHB were moderate to large within parities and considering all parities simultaneously (0.69-0.98). Genetic correlations between acetone and BHB with KET from different parities ranged from 0.71 to 0.99. Genetic correlations between acetone across parities, and between BHB across parities, ranged from 0.55 to 0.66. Genetic correlations between KET, acetone, and BHB with fat-to-protein ratio and with fat percentage were large and positive, but negative with milk yield. In genome-wide association studies, we identified SNP on BTA 4, 10, 11, and 29 significantly influencing acetone, and on BTA 1 and 16 significantly influencing BHB. The identified potential candidate genes NRXN3, ACOXL, BCL2L11, HIBADH, KCNJ1, and PRG4 are involved in lipid and glucose metabolism pathways.

Short communication: Genetic aspects of milk urea nitrogen and new indicators of nitrogen efficiency in dairy cows

Milk urea nitrogen (MUN), a trait routinely measured in the national milk recording system, is a useful indicator of nitrogen utilization efficiency of dairy cows, and selection for MUN and MUN-derived traits could be a valid strategy to produce better animals with regard to efficiency of nitrogen utilization. Therefore, the aim of the present study was to explore the genetic aspects of MUN and new potential indicators of nitrogen efficiency, namely ratios of protein to MUN, casein to MUN, and whey protein to MUN, in the Italian Brown Swiss population. A total of 153,175 test-day records of 10,827 cows in 500 herds were used for genetic analysis. Variance components and heritability of the investigated traits were estimated using single-trait repeatability animal models, whereas genetic and phenotypic correlations between the traits were estimated through bivariate repeatability animal models, including fixed effects of herd-test-date, stage of lactation, parity, calving year, and calving season, and the random effects of additive genetic animal, cow permanent environment, and the residual. Heritability estimates for MUN (0.20 ± 0.01) and the 3 new indicators of nitrogen utilization efficiency (0.15 ± 0.01 for protein-to-MUN and casein-to-MUN ratios, and 0.12 ± 0.01 for ratio of whey protein to MUN) suggested that additive genetic variation exists for these traits, and thus there is potential to select for greater organic nitrogen and lower inorganic nitrogen in milk. Genetic association between MUN and the 3 ratios was high (-0.87 ± 0.01) but not unity, suggesting that ratios could provide some further information beyond that provided by MUN with regard to efficiency of nitrogen utilization. Genetic trend of the investigated traits by year of birth of Brown Swiss sires showed how the selection applied in the last 30 yr has led to an increase of both quantity and quality of milk, and a decrease of somatic cell score and MUN. The inclusion of MUN in breeding programs could speed up the process of increasing organic nitrogen such as protein, which is useful for cheese-making, and reducing inorganic nitrogen (MUN) in milk.

Genetic parameters for noncoagulating milk, milk coagulation properties, and detailed milk composition in Swedish Red Dairy Cattle

The rennet-induced coagulation ability of milk is important in cheese production. For Swedish Red Dairy Cattle (RDC), this ability is reduced because of a high prevalence of noncoagulating (NC) milk. In this study, we simultaneously combined genetic parameters for NC milk, milk coagulation properties, milk composition, physical traits, and milk protein composition. Our aim was to estimate heritability and genetic and phenotypic correlations for NC milk and 24 traits (milk coagulation properties, milk composition, physical traits, and milk protein composition). Phenotypes and ∼7,000 SNP genotypes were available for all 600 Swedish RDC. The genotypes were imputed from ∼7,000 SNP to 50,000 SNP. Variance components and genetic parameters were estimated with an animal model. In Swedish RDC, a moderate heritability estimate of 0.28 was found for NC milk. For the other 24 traits, heritability estimates ranged from 0.12 to 0.77 (standard errors from 0.08 to 0.18). A total of 300 phenotypic and genetic correlations were estimated. For phenotypic and genetic correlations, 172 and 95 were significant, respectively. In general, most traits showing significant genetic correlations also showed significant phenotypic correlations. In this study, phenotypic and genetic correlations with NC milk suggest that many correlations between traits exist, making it difficult to predict the real consequences on the composition of milk, if selective breeding is applied on NC milk. We speculate that some of these consequences may lead to changes in the composition of milk, most likely affecting its physical and organoleptic properties. However, our results suggest that κ-casein could be used as an indicator trait to predict the occurrence of NC milk at the herd level.

Genetic parameters of direct methane using noninvasive methods and proxies of methane

Records of methane emissions from 1,501 cows on 14 commercial farms in 4 regions of Spain were collected from May 2018 to June 2019. Methane concentrations (MeC) were measured using a nondispersive infrared methane detector installed within the feed bin of the automatic milking system during 14- to 21-d periods. Rumination time (RT; min/d) was collected using collars with a tag that registered time (minutes) spent eating and ruminating. The means of MeC and methane production (MeP) were 1,254.28 ppm and 182.49 g/d, respectively; mean RT was 473.38 min/d. Variance components for MeC, MeP, and RT were estimated with REML using pedigree and genomic information in a single-step model. Heritabilities for MeC and MeP were 0.11 and 0.12, respectively. Rumination time showed a slightly larger heritability estimate (0.17). The genetic correlation between MeP and MeC was high (>0.95), suggesting that selection on either trait would lead to a positive correlated response on the other. Negative correlations were estimated between RT and MeC (-0.24 ± 0.38) and MeP (-0.43 ± 0.35). Methane concentration and MeP had slightly positive correlations with milk yield (0.17 ± 0.39 and 0.21 ± 0.36), protein percentage (0.08 ± 0.32 and 0.30 ± 0.45), protein yield (0.22 ± 0.41 and 0.31 ± 0.35), fat percentage (0.02 ± 0.40 and 0.27 ± 0.36), and fat yield (0.27 ± 0.28 and 0.29 ± 0.28) from bivariate analyses. Rumination time had positive correlations with milk yield (0.41 ± 0.75) and protein yield (0.26 ± 0.57) and negative correlations with fat yield (-0.45 ± 0.32), protein percentage (-0.15 ± 0.38), and fat percentage (-0.40 ± 0.47). A positive approximated genetic correlation was estimated between fertility and MeC (0.10 ± 0.05) and MeP (0.18 ± 0.05), resulting in slightly higher CH₄ production when selecting for better fertility [days open estimated breeding values (EBV) are expressed with mean 100 and SD 10, inversely related to days from calving to conception; that is, greater days open EBV implies better fertility]. Positive correlations were also estimated for stature with MeC and MeP (0.30 ± 0.04 and 0.43 ± 0.04, respectively). Other type traits (chest width, udder depth, angularity, and capacity) were positively correlated with methane traits, possibly because of higher milk yield and higher feed intake from these animals. Rumination time showed positive EBV correlations with production traits and type traits, and negative correlations with somatic cell count and body condition score. Based on the genetic correlations and heritabilities estimated in this study, methane is measurable and heritable, and estimates of genetic correlations suggest no strong opposition to current breeding objectives in Spanish Holsteins.

Genetic correlations between body weight, daily weight gain, and semen characteristic traits in young Norwegian Red bulls

The aim of this study was to estimate genetic parameters for body weight (BW) at 150 d (Bw_150d), and 330 d (Bw_330d) of age and average daily weight gain (Dwg), and to estimate genetic correlations between these traits and semen characteristic traits: volume; concentration (Conc); motility in fresh, 24-h, and 48-h samples (Mot0h, Mot24h, Mot48h); and sperm defects. Data were collected at the performance test station of young Norwegian Red bulls from 2002 to 2012, before selection of bulls for artificial insemination. The weight and growth data consisted of observations for 3,209 bulls, and andrology information was available for up to 2,034 of these bulls. Genetic parameters were estimated using linear animal models. Models for BW and growth traits included the group and year the bull left the station and the pen they occupied during weighing (group-year-pen) and parity of their dam as fixed effects. Models for andrology traits had group-year, age in months (11 to 15), and the interaction between ejaculate number and days since previous collection included as fixed effects. Estimated heritability was 0.14 for Bw_150d, 0.26 for Bw_330d, and 0.34 for Dwg; the estimated genetic correlations among these traits were all favorable. Both BW traits correlated favorably with all the semen characteristic traits (0.20 to 0.76), whereas Dwg was favorably correlated with volume, Mot24h, Mot48h, and sperm defects, and unfavorably correlated with Conc (-0.25) and Mot0h (-0.53). Our results indicate that the genetic correlations between weight and growth traits and semen characteristics depend on the age of the bulls. Although most genetic correlations were favorable, selection for higher daily weight gain between 150 and 330 d might explain the slight negative genetic trends observed for semen characteristics in young Norwegian Red bulls.

Genetic parameters for clutch and broodiness traits in turkeys (Meleagris Gallopavo) and their relationship with body weight and egg production

The objective of this study was to estimate phenotypic and genetic parameters for clutch and broodiness (BR) traits in turkeys and their relationship with body weight and egg production. Data on dam line hens was available and included: body weight at 18 wk of age (BW18), body weight at lighting (BWL, 29 to 33 wk), age at first egg (AFE), egg number (EN), rate of lay (RL), clutch length (CL), maximum clutch length (MCL), pause length (PL), maximum PL (MPL) and BR. BR was defined as the average number of consecutive pause days between clutches that was higher than the average PL per hen. Heritability estimates for BW18 and BWL were 0.50 and 0.53, respectively. The heritability for egg production, clutch, and pause traits varied from low (MPL = 0.15; BR = 0.15) to moderate (AFE = 0.22; EN = 0.28; RL = 0.29; CL = 0.21; MCL = 0.27; PL = 0.25). Genetic correlations were negative between body weight traits and EN (r_{g (BW18, EN)} = −0.27; r_{g(BWL, EN)} = −0.33) and CL (r_{g(BW18, CL)} = −0.40; r_{g(BWL, CL)} = −0.33). BR was negatively genetically correlated with EN (r_{g(BR, EN)} = −0.85) and CL (r_{g(BR, CL)} = −0.30), and positively genetically correlated with PL (r_{g(BR, PL)} = 0.93) and AFE (r_{g(BR, AFE)} = 0.21). EN had a positive (0.73) and a negative (−0.84) genetic correlation with CL and PL, respectively. Overall, the results of this study confirmed the negative (unfavorable) correlations between egg production and body weight. Despite unfavorable genetic and phenotypic correlations between egg production traits and those relating to BR, the inclusion of BR in a selection program through incorporation of clutch length traits and pause length traits is feasible. Integration of either clutch length traits or pause length traits in a selection index is likely to increase egg number while decreasing broodiness.

Symposium review: Development, implementation, and perspectives of health evaluations in the United States

The rate at which new traits are being developed is increasing, leading to an expanding number of evaluations provided to dairy producers, especially for functional traits. This review will discuss the development and implementation of genetic evaluations for direct health traits in the United States, as well as potential future developments. Beginning in April 2018, routine official genomic evaluations for 6 direct health traits in Holsteins were made available to US producers from the Council on Dairy Cattle Breeding (Bowie, MD). Traits include resistance to milk fever, displaced abomasum, ketosis, clinical mastitis, metritis, and retained placenta. These health traits were included in net merit indices beginning in August 2018, with a total weight of approximately 2%. Previously, improvement of cow health was primarily made through changes to management practices or genetic selection on indicator traits, such as somatic cell score, productive life, or livability. Widespread genomic testing now allows for accelerated improvement of traits with low heritabilities such as health; however, phenotypes remain essential to the success of genomic evaluations. Establishment and maintenance of data pipelines is a critical component of health trait evaluations, as well as appropriate data quality control standards. Data standardization is a necessary process when multiple data sources are involved. Model refinement continues, including implementation of variance adjustments beginning with the April 2019 evaluation. Mastitis evaluations are submitted to Interbull along with somatic cell score for international validation and evaluation of udder health. Additional areas of research include evaluation of other breeds for direct health traits, use of multiple-trait models, and evaluations for additional functional traits such as calf health and feed efficiency. Future developments will require new and continued cooperation among numerous industry stakeholders. There is more information available than ever before with which to make better selection decisions; however, this also makes it increasingly important to provide accurate and unbiased information.

Selection response and genetic parameter estimation of feeding behavior traits in Pekin ducks

Body weight-related traits and feeding behavior traits are important in poultry breeding and production. To investigate the heritability of feeding behavior and their genetic correlation with body weight-related traits in Pekin ducks, 5,594 Pekin ducks were selected. The information about body weight-related traits and feeding behavior from 3 to 6 wk of age were recorded by automatic electronic feeders. The heritability estimates for body weight, residual feed intake, and feeding behavior traits are relatively high (ranging from 0.29 to 0.65). We observed that total feed intake, meal feed intake, body weight at the age of 3 wk, and daily body weight gain had strong positive genetic correlations with body weight at the age of 6 wk. Moreover, body weight at the age of 3 wk also showed a positive genetic correlation with the feed conversion ratio (0.33). Total feeding time, daily feed intake, and feeding rate had significant positive phenotypic correlations with feed efficiency. However, the average interval between meals, the number of daily visits, and the number of meals all had a low genetic or phenotypic relationship with body weight and feed efficiency. In conclusion, our study revealed that body weight, residual feed intake, and feeding behavior traits were all highly heritable traits, and the selection for certain feeding behaviors could improve feed efficiency in Pekin ducks. This study is the first report about genetic parameter estimates about feeding behaviors in ducks based on large datasets and provides solid data for genetic study in ducks.

Community-based sheep breeding programs generated substantial genetic gains and socioeconomic benefits

Community-based breeding programs (CBBPs) for small ruminants have been suggested as alternatives to centralised, government-controlled breeding schemes which have been implemented in many developing countries. An innovative methodological framework on how to design, implement and sustain CBBPs was tested in three sites in Ethiopia: Bonga, Horro and Menz. In these CBBPs, the main selection trait identified through participatory approaches was 6-month weight in all three sites. In Horro and Bonga, where resources such as feed and water permitted larger litter sizes, twinning rate was included. Ten-year (2009 to 2018) performance data from the breeding programs were analysed using Average Information Restricted Maximum Likelihood method (AI-REML). Additionally, the socioeconomic impact of CBBPs was assessed. Results indicated that 6-month weight increased over the years in all breeds. In Bonga, the average increase was 0.21 ± 0.018 kg/year, followed by 0.18 ± 0.007 and 0.11 ± 0.003 kg/year in Horro and Menz, respectively. This was quite substantial in an on-farm situation. The birth weight of lambs did not improve over the years in Bonga and Horro sheep but significant increases occurred in Menz. Considering that there was no direct selection on birth weight in the community flock, the increased weights observed in Menz could be due to correlated responses, but this was not the case in Bonga and Horro. The genetic trend for prolificacy over the years in both Bonga and Horro flocks was positive and significant (P < 0.01). This increase in litter size, combined with the increased 6-month body weight, increased income by 20% and farm-level meat consumption from slaughter of one sheep per year to three. The results show that CBBPs are technically feasible, result in measurable genetic gains in performance traits and impact the livelihoods of farmers.

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. Four separate 5-trait random regression test-day models were used. The models included days in milk, herd test date, and a polynomial regression on DIM nested in age-season of calving classes as fixed effects, random polynomial regressions on DIM nested in herd-year of calving, animal additive genetic and permanent environment classes, and a residual effect. Regression curves were modeled using orthogonal Legendre polynomials of order 4 for the fixed age-season of calving effect and of order 5 for the random effects. Moderate overall heritability estimates of 0.34 and 0.46 were estimated for the MIR-predicted LF and MIR-predicted MFGS, respectively. These heritability estimates were similar to the ones estimated for the direct measure of MFGS in a previous study. The genetic correlations between predicted MFGS and fat percentage (0.53) and between predicted LF and protein percentage (0.41) were both moderate and positive. Predicted LF and somatic cell score showed a weaker correlation (0.06) compared with other studies. The moderate genetic correlation between MIR-predicted MFGS and fat percentage and between MIR-predicted LF and protein percentage suggests that MIR predictions of MFGS and LF are not simply a function of the amount of fat and protein percentage, respectively, in the milk (i.e., the prediction equations are not simply predicting fat or protein percentages). Thus, these MIR-predicted values may provide additional information for selecting for fine milk components in Holstein cattle.

Correlation and genetic analysis of seed shell thickness and yield factors in Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn.)

In order to solve the difficult problem of the outer shell covering in the processing of Tartary buckwheat, we conducted a genetic analysis in segregating F₂ and F₃ populations derived from a hybrid between 'Yunqiao No. 1' and 'Rice buckwheat', and the F₃ population was used to analyze the phenotypic and genetic correlation among the traits. The results showed that the variety with a value of trait for seed shell thickness over 0.20 mm is a hard-shelled type (The thick shell type = seed shell rate > 20%), and that with a value of trait for seed shell thickness below 0.15 mm is a easily-shelled type (The thin shell type = seed shell rate < 20%), while that with a value of trait for seed shell thickness ranging from 0.15 mm to 0.20 mm is a hard-shelled type or easily-shelled type. In addition, alleles for traits of number of seed per plant and total seed weight per plant have larger dominance variance relative to their additive variance, indicating that genes controlling these traits have larger dominant effects, it is not suitable for the selection of single plant in offspring plants at the early stage of development, because these traits do not show up then. The alleles for traits of 1000 kernel weight and seed shell thickness have larger additive variance relative to their dominant variance, indicating that genes governing these traits have greater additive effects, with which the single plant can be selected in the progeny at the early stage of development. Although, the value of seed shell thickness has been shown to correlated positively with that of 1000 kernel weight, almost all the seeds of easily-shelled type are those with thin shell. However, ideal single plants with easily-shelled trait are those with intermediate phenotypes of seed shell thickness and 1000 kernel weight, by which the traits of large number of seeds per plant and total seed weight per plant could be selected. In the progeny population of this study, there were excellent single plants with high-yield and easily-shelled traits, of which the value of seed shell thickness was 0.17 mm (0.15 mm to 0.20 mm), the value of 1000 kernel weight was 14 g, the value of number of seeds per plant was 1137 and value of total seed weight per plant was 15.9 g. The results showed that taking the hybrid combinations of easily-shelled trait with the trait of seed shell thickness was the most effective selection indexes to breed the high-yield buckwheat varieties with the trait of easy shelling.

Genetic analyses of novel temperament and milkability traits in Norwegian Red cattle based on data from automatic milking systems

The number of dairy cows milked in automatic milking systems (AMS) is steadily increasing in Norway. Capacity and efficiency of AMS are highly dependent on the individual cow's milking efficiency, such as milking speed and occupation time in the milking robot. Cows meet new challenges in herds utilizing AMS. Consequently, new or revised traits may be needed for genetic evaluation of dairy cattle. The AMS records relevant information on an individual cow basis. The aims of this study were to estimate genetic parameters of new automatically recorded milkability and temperament traits. Data from 77 commercial herds with Norwegian Red dairy cattle were analyzed by mixed linear animal models. The final data set contained 1,012,912 daily records from 4,883 cows in first to ninth lactation. For variance component estimation, univariate and bivariate models were used. Daily records of box time (BT), average flow rate (FR), kilograms of milk per minute of box time (MEF), handling time (HT), log-transformed HT, milking frequency, and milking interval were analyzed with repeatability models. Among these traits, FR, BT, and MEF showed the highest heritabilities of 0.48, 0.27, and 0.22, respectively, whereas heritability of log-transformed HT, HT, milking frequency, and milking interval was low (0.02-0.07). Unsuccessful milkings expressed as rejected milkings, incomplete milkings (IM), milkings with kick-offs (KO), and teat not found also showed low heritabilities (0.002-0.06). Due to low frequency, KO, rejected milkings, IM, and teat not found were also analyzed as proportions per lactation, which resulted in slightly higher heritability estimates. Genetic correlations were favorable and intermediate to strong between BT, HT, MEF, and FR with absolute values above 0.50. Intermediate and favorable correlations were found for IM and KO with BT, HT, MEF, and FR. Cow milkability in AMS can be improved by selection for reduced number of unsuccessful milkings, faster FR, increased MEF, and shorter BT and HT. Our results confirm that automatically recorded data on milkability and temperament can be valuable sources of information for routine genetic evaluations and that milking efficiency in AMS can be genetically improved.

Genetic parameters for mastitis incidence and its indicators based on somatic cell score for Holsteins in Hokkaido, Japan

The objectives of this study were to estimate the heritability of mastitis incidence and genetic correlations between the mastitis and the somatic cell score (SCS) statistics, and to compare the practicability between different models. We used test-day records with the mastitis incidence and SCS collected from Holstein cows calving from 1988 to 2015 in Hokkaido, Japan. As indicators of mastitis, the average SCS (avSCS), the standard deviation of SCS (sdSCS), and the maximum SCS (maxSCS) were calculated using test-day records up to the first 305 days in milk within a lactation. We compared a four-trait repeatability animal model (MTRP) with a four-trait multiple-lactation animal model (MTML). The heritability for mastitis was equal to or lower than 0.05 in all the models. Genetic correlations between lactations with MTML within the same trait were positive and close to 1. With MTRP, the estimated genetic correlations of the mastitis incidence with avSCS, sdSCS, and maxSCS were 0.66, 0.79, and 0.82, respectively. A joint evaluation with SCS statistics is expected to give an extra reliability for mastitis because of high and positive genetic correlations among the traits.

Reliability of breeding values for feed intake and feed efficiency traits in dairy cattle: When dry matter intake recordings are sparse under different scenarios

Currently, routine recordings of dry matter intake (DMI) in commercial herds are practically nonexistent. Recording DMI from commercial herds is a prerequisite for the inclusion of feed efficiency (FE) traits in dairy cattle breeding goals. To develop future on-farm phenotyping strategies, recording strategies that are low cost and less demanding logistically and that give relatively accurate estimates of the animal's genetic merit are therefore needed. The objectives of this study were (1) to estimate genetic parameters for daily DMI and FE traits and use the estimated parameters to simulate daily DMI phenotypes under different DMI recording scenarios (SCN) and (2) to use the simulated data to estimate for different scenarios the associated reliability of estimated breeding value and accuracies of genomic prediction for varying sizes of reference populations. Five on-farm daily DMI recording scenarios were simulated: once weekly (SCN1), once monthly (SCN2), every 2 mo (SCN3), every 3 mo (SCN4), and every 4 mo (SCN5). To estimate reliability of estimated breeding values, DMI and FE observations and true breeding values were simulated based on variance components estimated for daily observations of Nordic Red cows. To emulate realistic on-farm recording, 5 data set replicates, each with 36,037 DMI and FE records, were simulated for real pedigree and data structure of 789 Holstein cows. Observations for the 5 DMI recording scenarios were generated by discarding data in a step-wise manner from the full simulated data per the scenario's definitions. For each of these scenarios, reliabilities were calculated as correlation between the true and estimated breeding values. Variance components and genetic parameters were estimated for daily DMI, residual feed intake (RFI), and energy conversion efficiency (ECE) fitting the random regression model. Data for variance components were from 227 primiparous Nordic Red dairy cows covering 8 to 280 d in milk. Lactation-wise heritability for DMI, RFI, and ECE was 0.33, 0.12, and 0.32, respectively, and daily heritability estimates during lactation ranged from 0.18 to 0.45, 0.08 to 0.32, and 0.08 to 0.45 for DMI, RFI, and ECE, respectively. Genetic correlations for DMI between different stages of lactation ranged from -0.50 to 0.99. The comparison of different on-farm DMI recording scenarios indicated that adopting a less-frequent recording scenario (SCN3) gave a similar level of accuracy as SCN1 when 17 more daughters are recorded per sire over the 46 needed for SCN1. Such a strategy is less demanding logistically and is low cost because fewer observations need to be collected per animal. The accuracy of genomic predictions associated with the 5 recording scenarios indicated that setting up a relatively larger reference population and adopting a less-frequent DMI sampling scenario (e.g., SCN3) is promising. When the same reference population size was considered, the genomic prediction accuracy of SCN3 was only 5.0 to 7.0 percentage points lower than that for the most expensive DMI recording strategy (SCN1). We concluded that DMI recording strategies that are sparse in terms of records per cow but with slightly more cows recorded per sire are advantageous both in genomic selection and in traditional progeny testing schemes when accuracy, logistics, and cost implications are considered.

A genome-wide association study for susceptibility and infectivity of Holstein Friesian dairy cattle to digital dermatitis

Selection and breeding can be used to fight transmission of infectious diseases in livestock. The prevalence in a population depends on the susceptibility and infectivity of the animals. Knowledge on the genetic background of those traits would facilitate efficient selection for lower disease prevalence. We investigated the genetic background of host susceptibility and infectivity for digital dermatitis (DD), an endemic infectious claw disease in dairy cattle, with a genome-wide association study (GWAS), using either a simple linear mixed model or a generalized linear mixed model based on epidemiological theory. In total, 1,513 Holstein-Friesian cows of 12 Dutch dairy farms were scored for DD infection status and class (M0 to M4.1) every 2 wk for 11 times; 1,401 of these cows were genotyped with a 75k SNP chip. We performed a GWAS with a linear mixed model on 10 host disease status traits, and with a generalized linear mixed model with a complementary log-log link function (GLMM) on the probability that a cow would get infected between 2 scorings. With the GLMM, we fitted SNP effects for host susceptibility and host infectivity, while taking the variation in exposure of the susceptible cow to infectious herd mates into account. With the linear model we detected 4 suggestive SNP (false discovery rate < 0.20), 2 for the fraction of observations a cow had an active lesion on chromosomes 1 and 14, one for the fraction of observations a cow had an M2 lesion on at least one claw on chromosome 1 (the same SNP as for the fraction of observations with an active lesion), and one for the fraction of observations a cow had an M4.1 lesion on at least one claw on chromosome 10. Heritability estimates ranged from 0.09 to 0.37. With the GLMM we did not detect significant nor suggestive SNP. The SNP effects on disease status analyzed with the linear model had a correlation coefficient of only 0.70 with SNP effects on susceptibility of the GLMM, indicating that both models capture partly different effects. Because the GLMM better accounts for the epidemiological mechanisms determining individual disease status and for the distribution of the y-variable, results of the GLMM may be more reliable, despite the absence of suggestive associations. We expect that with an extended GLMM that better accounts for the full genetic variation in infectivity via the environment, the accuracy of SNP effects may increase.

Genomic analysis of perinatal sucking reflex in German Brown Swiss calves

A healthy sucking reflex is essential for newborn calves to ensure sufficient colostrum intake in the first few hours postpartum. In recent decades, European Brown Swiss breeders have repeatedly reported that some calves lack the ability to consume colostrum directly after birth due to an absent sucking reflex. In this study, we collected the phenotypes of more than 5,500 German Brown Swiss calves and performed variance component estimation with sire threshold models using Markov chain Monte Carlo algorithms. The 50K (777K) genotypes of nearly 2,000 (200) calves were collected, and an imputation was performed for all 50K genotypes up to 777K. Genome-wide association studies (GWAS) for the trait sucking reflex were conducted for all 777K genotypes. Depending on the trait coding, a low heritability was estimated to range from 0.08 to 0.11. The GWAS results identified 34 trait-associated SNP on 6 different chromosomes. Post-GWAS analyses showed significant overrepresentation of Gene Ontologies for central nervous development and several regulative processes. Functional annotation clustering and pathway analysis revealed relations to lipid metabolism, immune and endocrine systems, and signal transduction. The results of this study suggest that breeding for an improved sucking reflex is possible but requires large data sets for the estimation of reliable breeding values (either large progeny testing groups or a large reference genome in a genomic selection program).

Phenotypic relationships, genetic parameters, genome-wide associations, and identification of potential candidate genes for ketosis and fat-to-protein ratio in German Holstein cows

Energy demand for milk production in early lactation exceeds energy intake, especially in high-yielding Holstein cows. Energy deficiency causes increasing susceptibility to metabolic disorders. In addition to several blood parameters, the fat-to-protein ratio (FPR) is suggested as an indicator for ketosis, because a FPR >1.5 refers to high lipolysis. The aim of this study was to analyze phenotypic, quantitative genetic, and genomic associations between FPR and ketosis. In this regard, 8,912 first-lactation Holstein cows were phenotyped for ketosis according to a veterinarian diagnosis key. Ketosis was diagnosed if the cow showed an abnormal carbohydrate metabolism with increased content of ketone bodies in the blood or urine. At least one entry for ketosis in the first 6 wk after calving implied a score = 1 (diseased); otherwise, a score = 0 (healthy) was assigned. The FPR from the first test-day was defined as a Gaussian distributed trait (FPRgauss), and also as a binary response trait (FPRbin), considering a threshold of FPR = 1.5. After imputation and quality controls, 45,613 SNP markers from the 8,912 genotyped cows were used for genomic studies. Phenotypically, an increasing ketosis incidence was associated with significantly higher FPR, and vice versa. Hence, from a practical trait recording perspective, first test-day FPR is suggested as an indicator for ketosis. The ketosis heritability was slightly larger when modeling the pedigree-based relationship matrix (pedigree-based: 0.17; SNP-based: 0.11). For FPRbin, heritabilities were larger when modeling the genomic relationship matrix (pedigree-based: 0.09; SNP-based: 0.15). For FPRgauss, heritabilities were almost identical for both pedigree and genomic relationship matrices (pedigree-based: 0.14; SNP-based: 0.15). Genetic correlations between ketosis with FPRbin and FPRgauss using either pedigree- or genomic-based relationship matrices were in a moderate range from 0.39 to 0.71. Applying genome-wide association studies, we identified the specific SNP rs109896020 (BTA 5, position: 115,456,438 bp) significantly contributing to ketosis. The identified potential candidate gene PARVB in close chromosomal distance is associated with nonalcoholic fatty liver disease in humans. The most important SNP contributing to FPRbin was located within the DGAT1 gene. Different SNP significantly contributed to ketosis and FPRbin, indicating different mechanisms for both traits genomically.

Genetic parameter estimates for body conformation traits using composite index, principal component, and factor analysis

Information about genetic parameters is population specific and it is crucial for designing animal breeding programs and predicting response to selection. This study was carried out to estimate the genetic parameters for 23 body conformation traits of 45,517 Chinese Holstein reared in Eastern China from 1995 to 2017 with the Bayesian inference method using a linear animal mixed model. The methods to integrate these traits included (1) using the composite index from the Dairy Association of China and (2) applying principal component analysis and factor analysis to explore the relationship between the conformation traits. Estimates of heritability using the composite index were low (0.04; feet and legs) to moderate (0.23; body capacity). Strong genetic correlations were observed between the individual body conformation traits. Both principal components (1 to 7; eigenvalues ≥ 1) and latent factors (1 to 7; eigenvalues ≥ 1) explained 60.37% of total variability. Principal component 1 and factor 1 accounted for the traits that are usually associated with milk production. Moderate to low heritability were estimated through multi-trait analysis for principal components (from 0.07 to 0.21) and latent factors (from 0.07 to 0.23). Genetic correlations among the 2 multivariate techniques are typically lower compared with the one existing among the measured traits. Results from these analyses suggest the possibility of using both principal component analysis and factor analysis in morphological evaluation, simplifying the information given by the body conformation traits into new variables that could be useful for the genetic improvement of the Chinese Holstein population. This information could also be used to avoid analyzing large number of correlated traits, thereby improving precision and reducing computation burdens to analyze large and complex data.

Detailed genetic analysis of feeding behaviour in Romane lambs and links with residual feed intake

Breeding strategies based on feed efficiency are now implemented in most animal species using residual feed intake (RFI) criteria. Although relevant, the correlated responses of feeding behaviour traits resulting from such selection on RFI are poorly documented. We report the estimated feeding behaviour at three time levels (visit, meal and day) and genetic parameters between the feeding behaviour traits and their links with RFI and its components. Feed intake, feeding duration at three time levels (per visit, meal and day), feeding rate, number of visits and time-between-visits were estimated for 951 Romane lambs fed via automatic concentrate feeders. Heritability estimates of feeding behaviour traits ranged from 0.19 to 0.54 with higher estimates for the day level than the visit level. Daily feed intake was not genetically linked to feed intake at the visit level, whereas feeding duration between visit and day levels was moderately correlated (R_g  = +0.41 ± 0.12). RFI was not significantly correlated with feeding rate, but was positively linked to feed intake and feeding duration at the day level (+0.73 ± 0.09 and +0.41 ± 0.13, respectively) and negatively at the visit level (-0.33 ± 0.14 and -0.22 ± 0.17, respectively). Selecting animals with lower RFI values might modify their feeding behaviour by increasing feed intake and feeding duration at the visit level but decrease the number of visits per day (+0.51 ± 0.14).

Estimation of genetic parameters and season effects for semen traits in three pig breeds of South China

The economic profitability of a boar station largely depends on semen quantity and quality traits. However, genetic analysis of semen traits has not yet been done in the boar population in China. In this study, we aimed to estimate genetic parameters for semen traits and the influence of seasons on these traits by using data of Duroc, Landrace and Yorkshire boars in South China. The following four semen traits were analysed: semen volume (ml; VOL), sperm concentration (10⁶ /ml; DEN), sperm motility (MOT) and percentage of abnormal sperm (ABN). Genetic parameters and season effects were estimated simultaneously for each breed by using a multiple-trait (4 × 4) repeatability animal model. The four traits had a moderate heritability with average estimates of 0.23, 0.28, 0.26 and 0.17 across the three breeds, respectively. The estimates of genetic correlations among four traits differed in the three breeds. In particular, in Yorkshire, the four traits were nearly genetically independent. The season of collecting semen had a significant impact on these four semen traits except ABN in Duroc (Bonferroni adjusted p < 0.05/6). The moderate heritabilities indicate the possibility of effective selection of boars for semen traits. Different genetic correlations for the three breeds suggest that the selection strategy for the four traits should be investigated separately for each breed. Some necessary actions should be taken to reduce the influence of seasons on semen traits.

Parent-of-origin effects on carcass traits in Japanese Black cattle

Variances caused by the differential expression of paternally and maternally imprinted genes controlling carcass traits in Japanese Black cattle were estimated in this study. Data on marbling score (BMS), carcass weight, rib thickness, rib-eye area (REA) and subcutaneous fat thickness (SFT) were collected from a total of 13,115 feedlot steers and heifers in a commercial population. A sire-maternal grandsire model was used to analyse the data, and then, imprinting parameters were derived by replacing the genetic effect of the dam with the effect of the maternal grandsire in the imprinting model to calculate the genetic parameter estimates. The proportions of the total genetic variance attributable to imprinted genes ranged from 8.7% (SFT) to 35.2% (BMS). The remarkably large imprinting variance of BMS was mainly contributed by maternally expressed inheritance because the maternal contribution of the trait was much larger than that of the paternal trait. The parent-of-origin effect originating from maternal gene expression was also observed for REA. The results suggested the existence of genomic imprinting effects on the traits of the Japanese Black cattle. Hence, the parent-of-origin effect should be considered for the genetic evaluation of Japanese Black cattle in breeding programmes.