Genomic evaluation for breeding and genetic management in Cordia africana, a multipurpose tropical tree species.

BACKGROUND: Planting tested forest reproductive material is crucial to ensure the increased resilience of intensively managed productive stands for timber and wood product markets under climate change scenarios. Single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) analysis is a cost-effective option for using genomic tools to enhance the accuracy of predicted breeding values and genetic parameter estimation in forest tree species. Here, we tested the efficiency of ssGBLUP in a tropical multipurpose tree species, Cordia africana, by partial population genotyping. A total of 8070 trees from three breeding seedling orchards (BSOs) were phenotyped for height. We genotyped 6.1% of the phenotyped individuals with 4373 single nucleotide polymorphisms. The results of ssGBLUP were compared with pedigree-based best linear unbiased prediction (ABLUP) and genomic best linear unbiased prediction (GBLUP), based on genetic parameters, theoretical accuracy of breeding values, selection candidate ranking, genetic gain, and predictive accuracy and prediction bias. RESULTS: Genotyping a subset of the study population provided insights into the level of relatedness in BSOs, allowing better genetic management. Due to the inbreeding detected within the genotyped provenances, we estimated genetic parameters both with and without accounting for inbreeding. The ssGBLUP model showed improved performance in terms of additive genetic variance and theoretical breeding value accuracy. Similarly, ssGBLUP showed improved predictive accuracy and lower bias than the pedigree-based relationship matrix (ABLUP). CONCLUSIONS: This study of C. africana, a species in decline due to deforestation and selective logging, revealed inbreeding depression. The provenance exhibiting the highest level of inbreeding had the poorest overall performance. The use of different relationship matrices and accounting for inbreeding did not substantially affect the ranking of candidate individuals. This is the first study of this approach in a tropical multipurpose tree species, and the analysed BSOs represent the primary effort to breed C. africana.

Genetic parameter changes and age-age correlations in Pinus koraiensis growth over 40-year progeny testing.

BACKGROUND: Early selection in tree breeding could be achieved by addressing the longevity of tree improvement activities. Genetic parameter changes and age-age correlations are essential for determining the optimal timing of early selection. Practical tracking of genetic parameters of Pinus koraiensis, a major timber species with economic and ecological value, has become feasible as its progeny testing has entered the mid-term age in Korea. However, research on the age-age correlation of P. koraiensis as progeny trials approach rotation age is limited. This study aimed to investigate genetic parameter trends and age-age correlations in P. koraiensis progeny. P. koraiensis progeny were assessed at two sites using a linear mixed-effects model with two-dimensional spatial autoregressive structure. Height, diameter, and volume growth were measured in 11 assessments over 40 years. RESULTS: Genetic parameters, such as height and diameter, showed different patterns of change. The heritability ranged for the three growth traits in 0.083-0.710, 0.288-0.781, and 0.299-0.755 across the sites and age. Height heritability and its coefficient of variance decreased, whereas the diameter and volume estimates remained relatively constant. Correlations with Age 40 for phenotypic, genetic, and rank of breeding values ranged between 0.16 and 0.92, 0.594 and 0.988, and 0.412 and 0.965, respectively. These correlations generally increased as the age approached Age 40, with particularly high levels observed at Age 26 and Age 30. CONCLUSION: The observed genetic trends in P. koraiensis progeny testing offer valuable insights for early and precise selection. Notably, selecting superior genotypes at Ages 26-30 is supported by discernible genetic gains and robust correlations. Future research should integrate unbalanced data for selecting mother trees or families and conduct a comprehensive economic analysis of early selection to validate its practical benefits.

Genetic parameters, GWAS and selection perspective on gestation length in 16 French cattle breeds.

In this paper, we present a comprehensive study of gestation length (GL) in 16 cattle breeds by using large genotype and animal record databases. Data included over 20 million gestations since 2000 and genotypes from one million calves. The study addressed the GL variability within and between breeds, estimation of its direct and maternal heritability coefficients, association with fitness and several economic traits, and QTL detection. The breed average GL varied from 279.7 to 294.4 d, in Holstein and Blonde d'Aquitaine breeds, respectively. Standard deviations per breed were similar and ranged from 5.2 to 5.8 d. Direct heritability (i.e., for GL defined as a trait of the calf) was moderate to high (h2 = 0.40 to 0.67), whereas the maternal heritability was low (0.04 to 0.06). Extreme breeding values for GL were strongly associated with a higher mortality during the first 2 d of life and were associated with milk production of dams for dairy breeds and precocity of females. Finally, several QTL were detected affecting GL with cumulated effects up to a few days, and at least 2 QTL were found to be shared between different breeds. Our study highlights the risks that would be associated with selection toward a reduced gestation length. Further genomic studies are needed to identify the causal variants, and their association with juvenile mortality and other economic traits.

Effect of transgenerational environmental condition on genetics parameters of Italian Brown Swiss.

The aim of this study was to infer the effects of heat stress (HS) of dams during late gestation on direct and maternal genetic parameters for traits related to milk production and milk quality parameters (90,558 records) in Italian Brown Swiss cattle (12,072 cows in 617 herds). Daily average temperature-humidity indices (THI) during the last 56 d of pregnancy were calculated, using the climate data from the nearest public weather station for each herd. Heat load effects were considered as the average across the entire periods considering a thermoneutrality condition for data below the THI 60. For parameter estimation a random regression model using the second-order Legendre polynomial regression coefficient for THI considering both animal and maternal effect for heat load. Direct heritability increased sharply from THI 60 to 65, then decreased gradually up to THI ∼72, and sharply thereafter. Maternal heritability showed a different trend, with values close to 0 up until to THI 65 and slightly increasing toward extreme THI values. The study suggests a lower threshold of THI 60 for the onset of HS. Higher heritability values indicate greater selective efficiency in the THI range of 65 to 70, even if a higher standard deviation value have been detected. The effects of high THI during intrauterine life varied among traits with different heritability levels. Genetic correlations for milk, fat, and protein content at 60 THI with increasing value of environmental variable, remained constant (∼0.90) until THI >75, where they slightly decreased (∼0.85). Fat and protein yields, as well as milk and energy-corrected milk, showed correlations dropping to 0.80 around THI 67 to 68 and stabilizing between 0.75 and 0.85 at extreme THI values. Maternal component correlations dropped close to zero, with negative values for protein content at THI 65 to 70. Antagonism between direct and maternal components was stronger for intermediate THI values but less divergent for extremes. Genotype by environment interaction was observed, indicating the selection of resilient animals would be theoretically possible. In the future, the application of climate variables in selection schemes first should take into account the dimensions of the genetic correlations to be able to decide between the simple inclusion of the environmental effect in the statistical models, rather than a real parallel genetic evaluation.

Investigating the potential for genetic selection of dairy calf disease traits using management data.

Genetic selection could be a tool to help improve the health and welfare of calves; however, to date, there is limited research on the genetics of calfhood diseases. This study aimed to understand the current impact of calf diseases, by investigating incidence rates, estimating genetic parameters, and providing industry recommendations to improve calf disease recording practices on farms. Available calf disease data composed of 69,695 Holstein calf disease records for respiratory problems (RESP) and diarrhea (DIAR), from 62,361 calves collected on 1,617 Canadian dairy herds from 2006 to 2021. Single- and multiple-trait analysis using both a threshold and linear animal model for each trait were evaluated. Furthermore, each trait was analyzed using 2 scenarios with respect to minimum disease incidence threshold criterion (herd-year incidence of at least 1% and 5%) to highlight the effect of different filtering thresholds on selection potential. Observed scale heritability estimates for RESP and DIAR ranged from 0.02 to 0.07 across analyses, while estimated genetic correlations between the traits ranged from 0.50 to 0.62. Sires were compared based on their estimated breeding value and their diseased daughter incidence rates. On average, calves born to the bottom 10% of sires were 1.8 times more likely to develop RESP and 1.9 times to develop DIAR compared with daughters born to the top 10% of sires. Results from the current study are promising for the inclusion of both DIAR and RESP in Canadian genetic evaluations. However, for effective genetic evaluation, standardized approaches on data collection and industry outreach to highlight the importance of collecting and uploading this information to herd management software is required. In particular, it is important that the herd management software is accessible to the national milk recording system to allow for use in national genetic evaluation.

Genetic evaluations and genome-wide association studies for specific digital dermatitis diagnoses in dairy cows considering genotype × housing system interactions.

The present study aimed to use detailed phenotyping for the claw disorder digital dermatitis (DD) considering specific DD stages in 2 housing systems (conventional cubicle barns [CON] and compost-bedded pack barns [CBPB]) to infer possible genotype × housing system interactions. The DD stages included 2,980 observations for the 3 traits DD-sick, DD-acute, and DD-chronic from 1,311 Holstein-Friesian and 399 Fleckvieh-Simmental cows. Selection of the 5 CBPB and 5 CON herds was based on a specific protocol to achieve a high level of herd similarity with regard to climate, feeding, milking system, and location, but with pronounced housing-system differences. Five other farms had a "mixed system" with 2 subherds, one representing CBPB and the other one CON. The CBPB system was represented by 899 cows (1,530 observations), and 811 cows (1,450 observations) represented the CON system. The average disease prevalence was 20.47% for DD-sick, 13.88% for DD-acute, and 5.34% for DD-chronic, with a higher prevalence in CON than in CBPB. After quality control of 50K genotypes, 38,495 SNPs from 926 cows remained for the ongoing genomic analyses. Genetic parameters for DD-sick, DD-acute, and DD-chronic were estimated by applying single-step approaches for single-trait repeatability animal models considering the whole dataset, and separately for the CON and CBPB subsets. Genetic correlations between same DD traits from different housing systems, and between DD-sick, DD-chronic, and DD-acute, were estimated via bivariate animal models. Heritabilities based on the whole dataset were 0.16 for DD-sick, 0.14 for DD-acute, and 0.11 for DD-chronic. A slight increase of heritabilities and genetic variances was observed in CON compared with the "well-being" CBPB system, indicating a stronger genetic differentiation of diseases in a more challenging environment. Genetic correlations between same DD traits recorded in CON or CBPB were close to 0.80, disproving obvious genotype × housing system interactions. Genetic correlations among DD-sick, DD-acute and DD-chronic ranged from 0.58 to 0.81. SNP main effects and SNP × housing system interaction effects were estimated simultaneously via GWAS, considering only the phenotypes from genotyped cows. Ongoing annotations of potential candidate genes focused on chromosomal segments 100 kb upstream and downstream from the significantly associated candidate SNP. GWAS for main effects indicated heterogeneous Manhattan plots especially for DD-acute and DD-chronic, indicating particularities in disease pathogenesis. Nevertheless, a few shared annotated potential candidate genes, that is, METTL25, AFF3, PRKG1, and TENM4 for DD-sick and DD-acute, were identified. These genes have direct or indirect effects on disease resistance or immunology. For the SNP × housing system interaction, the annotated genes ASXL1 and NOL4L on BTA 13 were relevant for DD-sick and DD-acute. Overall, the very similar genetic parameters for the same traits in different environments and negligible genotype × housing system interactions indicate only minor effects on genetic evaluations for DD due to housing-system particularities.

Estimation of maternal and additive effect on reproduction and productive traits in Hardhenu cattle.

The study aimed to assess performance traits in Hardhenu cattle by analysing data from 445 animals born to 59 sires and 227 dams. The investigation focused on estimating (co)variance components and genetic parameters for reproduction and production traits in dairy cattle. Results from least-squares analysis indicated a significant effect (p < .01) of the period of calving (POC) on key production traits, including first lactation milk yield (FLMY), 300-day milk yield (FLMY300), first peak yield (FPY) and total lactation milk yield (TLMY) in studied population. The least squares means for these traits were reported as follows: FLMY (2665.68 ± 45.66 kg), FLMY300 (2425.52 ± 34.41 kg), FLL (312.95 ± 3.83 days), FPY (11.52 ± 0.15 kg) and TLMY (9282.44 ± 167.03 kg) in Hardhenu cattle. In the studied population, only additive genetic variability was found to be present and there was absence of any significant maternal effect with respect to targeted traits in the resource population. Direct heritability estimates (h2) for FLMY, FLMY300, FLL, FPY, TLMY and other traits ranged from 0.03 to 0.41 in Hardhenu cattle. These findings offer valuable insights into the genetic factors influencing performance traits, contributing to the enhancement of breeding and management practices in Hardhenu cattle.

A systematic review with meta-analysis of heritability estimates for temperament-related traits in beef and dairy cattle populations.

Temperament (docility) is a key breeding goal in the cattle industry due to its direct relationship with animal welfare, cattle handler's safety and animal productivity. Over the past six decades, numerous studies have reported heritability estimates for temperament-related traits in cattle populations ranging from low to high values. Therefore, the primary objective of this study was to perform a comprehensive systematic review with meta-analysis to obtain weighted estimates of heritability for temperament-related traits in worldwide cattle populations. After data editing and quality control, 106 studies were included in the systematic review, of which 29.2% and 70.8% reported estimates of heritability for temperament-related traits in dairy and beef cattle populations, respectively. Meta-analyses were performed for 95 heritability estimates using a random model approach. The weighted heritability estimates were as follow: (a) flight score at weaning = 0.23 (95% CI: 0.15-0.32); (b) flight speed at weaning = 0.30 (95% CI: 0.26-0.33); (c) joint analysis of flight speed and flight score at weaning = 0.27 (95% CI: 0.22-0.31); (d) flight speed at yearling = 0.26 (95% CI: 0.21-0.30); (e) joint analysis of flight speed at weaning and yearling = 0.27 (95% CI: 0.24-0.30); (f) movement score = 0.12 (95% CI: 0.08-0.15); (g) crush score at weaning = 0.21 (95% CI: 0.17-0.25); (h) pen score at weaning = 0.27 (95% CI: 0.19-0.34); (i) pen score at yearling = 0.20 (95% CI: 0.17-0.23); (j) joint analysis of pen score at weaning and yearling = 0.22 (95% CI: 0.18-0.26); (k) cow's aggressiveness at calving = 0.10 (95% CI: 0.01-0.19); (l) general temperament = 0.13 (95% CI: 0.06-0.19); (m) milking temperament = 0.16 (95% CI: 0.11-0.21); and (n) joint analysis of general and milking temperament = 0.14 (95% CI: 0.11-0.18). The heterogeneity index ranged from 0% to 77%, and the Q-test was significant (p < 0.05) for four single-trait meta-analyses. In conclusion, temperament is moderately heritable in beef cattle populations, and flight speed at weaning had the highest weighted heritability estimate. Moreover, between-study heterogeneity was low or moderate in beef cattle traits, suggesting reasonable standardization across studies. On the other hand, low-weighted heritability and high between-study heterogeneity were estimated for temperament-related traits in dairy cattle, suggesting that more studies are needed to better understand the genetic inheritance of temperament in dairy cattle populations.

Genomic background of biotypes related to growth, carcass and meat quality traits in Duroc pigs based on principal component analysis.

As the swine industry continues to explore pork quality traits alongside growth, feed efficiency and carcass leanness traits, it becomes imperative to understand their underlying genetic relationships. Due to this increase in the number of desirable traits, animal breeders must also consider methods to efficiently perform direct genetic changes for each trait and evaluate alternative selection indexes with different sets of phenotypic measurements. Principal component analysis (PCA) and genome-wide association studies (GWAS) can be combined to understand the genetic architecture and biological mechanisms by defining biological types (biotypes) that relate these valuable traits. Therefore, the main objectives of this study were to: (1) estimate genomic-based genetic parameters; (2) define animal biotypes utilizing PCA; and (3) utilize GWAS to link the biotypes to candidate genes and quantitative trait loci (QTL). The phenotypic dataset included 2583 phenotypic records from female Duroc pigs from a terminal sire line. The pedigree file contained 193,764 animals and the genotype file included 21,309 animals with 35,651 single nucleotide polymorphisms (SNPs). Eight principal components (PCs), accounting for a total of 99.7% of the population variation, were defined for three growth, eight conventional carcass, 10 pork quality and 18 novel carcass traits. The eight biotypes defined from the PCs were found to be related to growth rate, maturity, meat quality and body structure, which were then related to candidate genes. Of the 175 candidate genes found, six of them [LDHA (SSC1), PIK3C3 (SSC6), PRKAG3 (SSC15), VRTN (SSC7), DLST (SSC7) and PAPPA (SSC1)] related to four PCs were found to be associated with previously defined QTL, linking the biotypes with biological processes involved with muscle growth, fat deposition, glycogen levels and skeletal development. Further functional analyses helped to make connections between biotypes, relating them through common KEGG pathways and gene ontology (GO) terms. These findings contribute to a better understanding of the genetic relationships between growth, carcass and meat quality traits in Duroc pigs, enabling breeders to better understand the biological mechanisms underlying the phenotypic expression of these traits.

Genomic analysis of genotype-environment interaction in age at first calving of Murrah buffaloes.

Age at first calving (AFC) is a measure of sexual maturity associated with the start of productive life of dairy animals. Additionally, a lower AFC reduces the generation interval and early culling of females. However, AFC has low heritability, making it a trait highly influenced by environmental factors. In this scenario, one way to improve the reproductive performance of buffalo cows is to select robust animals according to estimated breeding value (EBV) using models that include genotype-environment interaction (GEI) with the application of reaction norm models (RNMs). This can be achieved by understanding the genomic basis related to GEI of AFC. Thus, in this study, we aimed to predict EBV considering GEI via the RNM and identify candidate genes related to this component in dairy buffaloes through genome-wide association studies (GWAS). We used 1795 AFC records from three Murrah buffalo herds and formed environmental gradients (EGs) from contemporary group solutions obtained from genetic analysis of 270-day cumulative milk yield. Heritability estimates ranged from 0.15 to 0.39 along the EG. GWAS of the RNM slope parameter identified important genomic regions. The genomic window that explained the highest percentage of genetic variance of the slope (0.67%) was located on BBU1. After functional analysis, five candidate genes were detected, involved in two biological processes. The results suggested the existence of a GEI for AFC in Murrah buffaloes, with reclassification of animals when different environmental conditions were considered. The inclusion of genomic information increased the accuracy of breeding values for the intercept and slope of the reaction norm. GWAS analysis suggested that important genes associated with the AFC reaction norm slope were possibly also involved in biological processes related to lipid metabolism and immunity.

Transgenerational effects of the maternal gestational environment on the post-natal performance of beef cattle: A reaction norm approach.

In tropical beef cattle production systems, animals are commonly raised on pastures, exposing them to potential stressors. The end of gestation typically overlaps with a dry period characterized by limited food availability. Late gestation is pivotal for fetal development, making it an ideal scenario for inter- and transgenerational effects of the maternal gestational environment. Intergenerational effects occur due to exposure during gestation, impacting the development of the embryo and its future germline. Transgenerational effects, however, extend beyond direct exposure to the subsequent generations. The objective of the present study was to verify these effects on the post-natal performance of zebu beef cattle. We extended the use of a reaction norm model to identify genetic variation in the animals' responses to transgenerational effects. The inter- and transgenerational effects were predominantly positive (-0.09% to 19.74%) for growth and reproductive traits, indicating improved animal performance on the phenotypic scale in more favourable maternal gestational environments. Additionally, these effects were more pronounced in the reproductive performance of females. On average, the ratio of direct additive genetic variances of the slope and intercept of the reaction norm ranged from 1.23% to 3.60% for direct and from 10.17% to 11.42% for maternal effects. Despite its relatively modest magnitude, this variation proved sufficient to prompt modifications in parameter estimates. The average percentage variation of direct heritability estimates ranged from 19.3% for scrotal circumference to 33.2% for yearling weight across the environmental descriptors evaluated. Genetic correlations between distant environments for the studied traits were generally high for direct effects and far from unity for maternal effects. Changes in EBV rankings of sires across different gestational environments were also observed. Due to the multifaceted nature of inter- and transgenerational effects of the maternal gestational environment on various traits of beef cattle raised under tropical pasture conditions, they should not be overlooked by producers and breeders. There were differences in the specific response of beef cattle to variations in the quality of the maternal gestational environment, which can be partially explained by transgenerational epigenetic inheritance. Adopting a reaction norm model to capture a portion of the additive variance induced by inter- or transgenerational effects could be an alternative for future research and animal genetic evaluations.

Genetic analysis of body weight and growth curve parameters in Muzaffarnagari sheep of India.

The objective of this study was to estimate genetic effects on parameters of the Brody and Richards growth curves using body weight records from birth to 12 months of age on 2287 Muzaffarnagari lamb for a period of 29 years (1976-2004). Estimated growth curve parameters were analysed using six univariate animal models, and genetic correlations among and between the parameters of each function and between parameters of the functions and observed birth and yearling weights were estimated using bivariate analyses. Significant environmental factors including birth year, sex, season, birth status and dam parity were included as fixed effects in all models. Likelihood ratio tests indicated that maternal genetic effects were significant only for birth weight (BW) and degree of maturity at birth (u0) for the Brody and Richards functions. For these traits, direct heritabilities were similar (0.21, 0.19 and 0.17, respectively), but the estimated maternal heritability for BW (0.18) was twice that of u0 for both functions. Heritabilites for yearling weight and asymptotic final body weights for the Brody and Richards functions were 0.28, 0.17 and 0.21, respectively. The remaining growth curve parameters were lowly heritable, ranging from zero for the predicted degree of maturity at the age of maximum growth rate for the Richards function to 0.08 for the maturing rate parameter of the Brody function. Genetic correlations between corresponding parameters for different growth functions exceeded 0.88. Our results showed that the Brody and Richards functions had similar genetic architecture, but the Richards function had no apparent advantages over the more easily interpreted Brody function. Failure to identify maternal genetic effects on maturing rate parameters suggested that both functions failed to identify potentially important maternal genetic effects. Therefore, there is no usefulness of estimated growth curve parameters in selection compared to the simple multi-trait genetic evaluations of individual body weights.

Early life jumping traits: Are they good proxies for success in show jumping competitions in Belgian warmblood horses?

The main goal of the Belgian Warmblood horse studbook (BWP) is to breed successful competition horses, with emphasis on show jumping. However, competition results are only available later in life and competition traits are lowly heritable. Hence, the use of phenotypes that record performance-related traits at an early life stage could help increase genetic progress. In this study, we evaluated the potential of eleven linear scored early life jumping traits assessed during jumping in freedom (2-5 years old) or under the saddle (4-6 years old) as proxies for later success in show jumping competitions. To this end, we estimated their heritabilities and genetic correlations with the competition trait, adjusted fence height, by using 2170 free jumping records, 1588 jumping under saddle records, 674,527 show jumping competition records and almost 81,000 informative horses in the pedigree. As participation of young horses in these contests is on a voluntary basis, a pre-selection most probably exists. To verify this hypothesis, we investigated the association between participation to young horse contests and participation to show jumping competitions later on (called here start status phenotype). We also estimated heritabilities for "start status in free jumping contest", "start status in jumping under saddle contest" and "start status in free jumping or jumping under saddle contest" by fitting threshold models. Furthermore, we calculated genetic correlations between these traits and adjusted fence height and calculated the correlations between EBVs for start status in young horse contests and EBVs for success in competitions. Estimated heritabilities of early life jumping traits ranged between 0.05 and 0.30. Their genetic correlations with adjusted fence height were moderate to high (rg = 0.37-0.63). Relatively more horses that participated in young horse contests competed later on compared to horses that did not participate in young horse contests (p-value < 0.001). They were also significantly more successful in show jumping competitions. Furthermore, start status in young horse contests was moderately heritable in BWP horses (h2 = 0.56-0.65) and moderately to highly correlated with later success in competitions (rg = 0.30-0.77). Hence, we showed that ELJ traits are good proxies for later success in competitions and that a pre-selection of horses occurs in young horse contests. It is suggested to stimulate participation to young horse contests to achieve a more representative sample of the population. Early life jumping traits can therefore optimize the genetic progress for show jumping performance.

Genetic parameters for milk yield and reproductive traits in Honduran Holstein cattle.

The aim of this study was to estimate the (co)variance components and genetic parameters for milk yield adjusted to 305d (MY305), calving-to-conception interval (CCI), number of services per conception (NSC) and calving interval (CI) of Honduran Holstein cows, by fitting a bivariate animal model using Maximum Restricted Likelihood procedures. Model included the fixed effects of calving number, the contemporary calving group (farm-season-year of calving and the cow age as covariate). The estimated means and standard deviations for MY, CCI, NSC and CI were, 5098.60 ± 1564.32 kg, 168.27 ± 104.71 days, 2.46 ± 1.69 services, and 448.73 ± 109.16 days, respectively; and their estimated heritabilities were 0.21 ± 0.05, 0.03 ± 0.028, 0.02 ± 0.024 and 0.06 ± 0.04, respectively. The genetic correlations between MY305 and CCI, NSC and CI were positive and antagonist, with values of 0.64 ± 0.52, 0.99 ± 0.56, and 0.32 ± 0.24 respectively. Even though moderate to low heritability was estimated for MY305, systematic selection for milk yield, with a reduction in reproductive efficiency, if considered as the only selection criterion is important to be considered. By including reproductive traits and considering permanent environment effects into the breeding program, might yield a slow, but constant and permanent improvement over time.

Genetic association between fat-to-protein ratio and traits of economic interest in early lactation Holstein cows in Brazil.

The aims of this study were to estimate the genetic parameters for fat-to-protein ratio (F:P) within the first 90 days of lactation and to examine their genetic associations with daily milk yield (MY), somatic cell score (SCS), and calving interval between the first and second calving (IFSC) and between the second and third calving (ISTC) during the first three lactations of Holstein cows. We utilized 200,626 production-related data officially recorded from 77,436 cows milked two or three times a day from 2012 to 2022, sourced from the Holstein Cattle Breeders Association of Paraná State, Brazil. The (co)variance components were estimated using animal models, adopting the restricted maximum likelihood (REML) method with single-trait analysis (for heritability and repeatability) and two-trait analysis (for genetic and phenotypic correlations), per lactation. Regardless of lactation number, heritability estimates were relatively low, ranging from 0.08 ± 0.005 to 0.10 ± 0.003 for F:P; 0.08 ± 0.01 to 0.18 ± 0.005 for MY; 0.04 ± 0.01 to 0.07 ± 0.004 for SCS; and 0.03 ± 0.01 for both IFSC and ISTC. Repeatability estimates within the same lactation were low for F:P (ranging from 0.17 ± 0.002 to 0.19 ± 0.03), high for MY (between 0.50 ± 0.003 and 0.53 ± 0.002), and moderate to high for SCS (between 0.39 ± 0.003 and 0.44 ± 0.004). Genetic correlations between F:P and MY ranged from -0.26 ± 0.03 to -0.15 ± 0.02; F:P and SCS, from -0.06 ± 0.03 to -0.03 ± 0.08; F:P and IFSC, 0.31 ± 0.01; F:P and ISTC, 0.20 ± 0.01; MY and IFSC, 0.24 ± 0.05; and MY and ISTC, 0.13 ± 0.08. The fat-to-protein ratio during early lactation showed low genetic variability, regardless of lactation number. Furthermore, it was genetically correlated with MY, IFSC, and ISTC, although there is an antagonistic and unfavorable correlation between traits that can limit genetic progress.

Genetic evaluation for survival traits in Japanese quail line selected for fast growth rate.

The main objectives of this study were to estimate genetic parameters for the survival, longevity and evaluate risk factors for the occurrence of mortality in a Japanese quail line selected for high growth rate during the period from hatch to 21 days of age (GR1-21) for eight generations and its control. Total number of 1095, 2289 and 16,506 for sires, dams and progeny, respectively, was used to estimate genetic parameters, a separate hatch of 687 chicks was used to examine the risk factors of quails in the selected (SL, 438) and control (CL, 249) lines. The proportion of censored quails until 42 days of age was 82.20 and 87.14 for SL and CL, respectively. The CL showed higher longevity than SL (38.42 vs. 36.86 days). In the two tested lines, mortality% significantly declined when body weight at death increased, however, the CL had a higher reduction of mortality% than the SL (50 vs. 42%). Survival and longevity had low heritability values, low genetic and phenotypic correlations between survival and longevity with GR1-21 and ranging from 0.025 to 0.208. The survival tended to be less correlated with GR1-21 and body weight at marketing age than the longevity.

Synchronization of breeding and its impact on genetic parameters and evaluation of female fertility traits.

Achieving an acceptable level of fertility in herds is difficult for many dairy producers because identifying cows in estrus has become challenging owing to poor estrus expression, increased herd size, and lack of time and skilled labor for estrus detection. As a result, synchronization of estrus is often used to manage reproduction. The aims of this study were (1) to identify artificial inseminations (AI) that were performed following synchronization and (2) to assess the effect of synchronization on genetic parameters and evaluation of fertility traits. This study used breeding data collected between 1995 and 2021 from over 4,600 Australian dairy herds that had at least 30 matings per year. Because breeding methods were not reported, the recording pattern of breeding dates showing a large proportion of the total AI being recorded on a single date of the year served as an indicator of synchronization. First, the proportion of AI recorded on each day of the year was calculated for each herd-year. Subsequently, synchronization was defined when a herd with, for instance, only 30 matings in a year, had at least 0.20 or more AI on the same day. As the number of breedings in a herd-year increased, the threshold for classifying AI was continuously reduced from 0.20 to as low as 0.03 under the assumption that mating of many cows on a single date becomes increasingly difficult without synchronization. From the current data, we deduced that 0.11 of all AI were possibly performed following synchronization (i.e., timed AI, TAI). The proportion of AI classified as TAI increased over time and with herd size. Although the deviation from equal numbers of mating on 7 d of the week was not used for classifying AI, 0.44 of AI being categorized as TAI were performed on just 2 d of the week. When data classified as TAI were used for estimating genetic parameters and breeding values, the interval between calving and first service (CFS) was found to be the most affected trait. The phenotypic and additive genetic variance and heritability, as well as variability and reliability of estimated breeding values of bulls and cows for CFS were lower for TAI than for AI performed following detected estrus (i.e., estrus-detected AI, EAI). For calving interval, first service nonreturn rate (FNRR), and successful calving rate to first service, genetic correlations between the same trait measured in TAI and EAI were close to 1, in contrast to 0.55 for CFS. The lower genetic variances and heritabilities for FNRR and calving interval in TAI than in EAI suggests that synchronization reduces the genetic variability of fertility. In conclusion, TAI makes CFS an ineffective measure of fertility. One approach to minimize this effect on genetic evaluations is to identify TAI (using the method described for example) and then set the CFS of these cows as missing records when running multitrait genetic evaluations of fertility traits that include CFS. In the long term, the most practical and accurate way to reduce the effect of synchronization on genetic evaluations is to record TAI along with mating data.

Predicting milk protein fractions using infrared spectroscopy and a gradient boosting machine for breeding purposes in Holstein cattle.

In recent years, increasing attention has been focused on the genetic evaluation of protein fractions in cow milk with the aim of improving milk quality and technological characteristics. In this context, advances in high-throughput phenotyping by Fourier transform infrared (FTIR) spectroscopy offer the opportunity for large-scale, efficient measurement of novel traits that can be exploited in breeding programs as indicator traits. We took milk samples from 2,558 Holstein cows belonging to 38 herds in northern Italy, operating under different production systems. Fourier transform infrared spectra were collected on the same day as milk sampling and stored for subsequent analysis. Two sets of data (i.e., phenotypes and FTIR spectra) collected in 2 different years (2013 and 2019-2020) were compiled. The following traits were assessed using HPLC: true protein, major casein fractions [αS1-casein (CN), αS2-CN, ß-CN, κ-CN, and glycosylated-κ-CN], and major whey proteins (ß-lactoglobulin and α-lactalbumin), all of which were measured both in grams per liter (g/L) and proportion of total nitrogen (% N). The FTIR predictions were calculated using the gradient boosting machine technique and tested by 3 different cross-validation (CRV) methods. We used the following CRV scenarios: (1) random 10-fold, which randomly split the whole into 10-folds of equal size (9-folds for training and 1-fold for validation); (2) herd/date-out CRV, which assigned 80% of herd/date as the training set with independence of 20% of herd/date assigned as the validation set; (3) forward/backward CRV, which split the data set in training and validation set according with the year of milk sampling (FTIR and gold standard data assessed in 2013 or 2019-2020) using the "old" and "new" databases for training and validation, and vice-versa with independence among them; (4) the CRV for genetic parameters (CRV-gen), where animals without pedigree as assigned as a fixed training population and animals with pedigree information was split in 5-folds, in which 1-fold was assigned to the fixed training population, and 4-folds were assigned to the validation set (independent from the training set). The results (i.e., measures and predictions) of CRV-gen were used to infer the genetic parameters for gold standard laboratory measurements (i.e., proteins assessed with HPLC) and FTIR-based predictions considering the CRV-gen scenario from a bi-trait animal model using single-step genomic BLUP. We found that the prediction accuracies of the gradient boosting machine equations differed according to the way in which the proteins were expressed, achieving higher accuracy when expressed in g/L than when expressed as % N in all CRV scenarios. Concerning the reproducibility of the equations over the different years, the results showed no relevant differences in predictive ability between using "old" data as the training set and "new" data as the validation set and vice-versa. Comparing the additive genetic variance estimates for milk protein fractions between the FTIR predicted and HPLC measures, we found reductions of -19.7% for milk protein fractions expressed in g/L, and -21.19% expressed as % N. Although we found reductions in the heritability estimates, they were small, with values ranging from -1.9 to -7.25% for g/L, and -1.6 to -7.9% for % N. The posterior distributions of the additive genetic correlations (ra) between the FTIR predictions and the laboratory measurements were generally high (>0.8), even when the milk protein fractions were expressed as % N. Our results show the potential of using FTIR predictions in breeding programs as indicator traits for the selection of animals to enhance milk protein fraction contents. We expect acceptable responses to selection due to the high genetic correlations between HPLC measurements and FTIR predictions.

Genetic evaluations for endangered dual-purpose German Black Pied cattle using 50K SNPs, a breed-specific 200K chip, and whole-genome sequencing.

Genetic evaluations of local cattle breeds are hampered due to small reference groups or biased due to the utilization of SNP effects estimated in other large populations. Against this background, there is a lack of studies addressing the possible advantage of whole-genome sequences (WGS) or consideration of specific variants from WGS data in genomic predictions for local breeds with small population size. Consequently, the aim of this study was to compare genetic parameters and accuracies of genomic estimated breeding values (GEBV) for 305-d production traits, fat-to protein ratio (FPR), and somatic cell score (SCS) at the first test date after calving and confirmation traits of the endangered German Black Pied cattle (DSN) breed using 4 different marker panels: (1) the commercial 50K Illumina BovineSNP50 BeadChip, (2) a customized 200K chip designed for DSN (DSN200K) which considers the most important variants for DSN from WGS, (3) randomly generated 200K chips based on WGS data, and (4) a WGS panel. The same number of animals was considered for all marker panel analyses (i.e., 1,811 genotyped or sequenced cows for conformation traits, 2,383 cows for lactation production traits, and 2,420 cows for FPR and SCS). Mixed models for the estimation of genetic parameters directly included the respective genomic relationship matrix from the different marker panels plus the trait-specific fixed effects. For the calculation of GEBV accuracies, we applied repeated random subsampling validation. In the process of separate cross-validations per trait, we created a validation set including 20% of cows with masked phenotypes, and a training set comprising 80% of the cows. The cows were selected randomly in a procedure with 10 replicates considering replacements in the different scenarios. The accuracy was defined as the correlation between the direct GEBV and the phenotypes with subtracted corresponding fixed effects for the cows in the validation set. For FPR and SCS, as well as for lactation production traits, heritabilities were largest based on WGS data, but the increase compared with the 50K or DSN200K applications was quite small in the range from 0.01 to 0.03. Also, for most of the conformation traits, heritabilities were largest based on WGS and DSN200K data, but the increase was in the range of the corresponding standard error. Accordingly, GEBV accuracies for most of the studied traits were highest based on WGS data or when utilizing the DSN200K chip, but the accuracy differences across the marker panels were quite small and nonsignificant. In conclusion, WGS data and the DSN200K chip only contributed to minor improvements in genomic predictions, still justifying the use of the commercial 50K chip. Nevertheless, WGS and the 200KDSN chip harbor breed-specific variants, which are valuable for studying causal genetic mechanisms in the endangered DSN population.

Genetic relationships between weight loss in early lactation and daily milk production throughout lactation in Holstein cows.

After calving, high-yielding dairy cows mobilize body reserves for energy, sometimes to the detriment of health and fertility. This study aimed to estimate the genetic correlation between body weight loss until nadir and daily milk production (MY24) in first- (L1) and second-lactation (L2) Holstein cows. The data set included 859,020 MY24 records and 570,651 daily raw body weight (BWr) phenotypes from 3,989 L1 cows, and 665,361 MY24 records and 449,449 BWr phenotypes from 3,060 L2 cows, recorded on 36 French commercial farms equipped with milking robots that included an automatic weighing platform. To avoid any bias due to change in digestive content, BWr was adjusted for variations in feed intake, estimated from milk production and BWr. Adjusted body weight was denoted BW. The genetic parameters of BW and MY24 in L1 and L2 cows were estimated using a 4-trait random regression model. In this model, the random effects were fitted by second-order Legendre polynomials on a weekly basis from wk 1 to 44. Nadir of BW was found to be earlier than reported in the literature, at 29 d in milk, and BW loss from calving to nadir was also lower than generally assumed, close to 29 kg. To estimate genetic correlations between body weight loss and production, we defined BWL5 as the loss of weight between wk 1 and 5 after calving. Genetic correlations between BWL5 and MY24 ranged from -0.26 to 0.05 in L1 and from -0.11 to 0.10 in L2, according to days in milk. These moderate to low values suggest that it may be possible to select for milk production without increasing early body mobilization.