Journal of Animal Breeding and Genetics最新文献

The economic benefits of genetic improvement were estimated based on genetic trends observed for economically important traits in stud herds participating in Argentina's genetic evaluation scheme. The analysis included Horned Merino, Polled Merino, Dohne Merino, Corriedale and Polwarth sheep born between 2014 and 2023. This benefit was calculated as the difference between the additional income generated by the increased value of meat and wool in multiplier and commercial herds, and the costs associated with genetic improvement at the stud tier and additional cost of improved rams at multiplier and commercial tiers. The benefits of 10 years of genetic improvement and their residual effect for another 10 years were computed, updating the annual results with a discount rate of 5%. The benefit obtained in the five breeds reached USD 4.95 million considering only breeding program costs at the stud tier. Including additional ram buying costs, the benefit reached USD 3.75 million, the difference being captured by the ram selling tiers. At the breed level (ignoring ram buying costs) the return to investment (ROI) amounted to 33.6. At multiplier and commercial herd tiers (including ram buying costs) the income to cost ratios were 5.5 and 4.0, respectively. The Corriedale breed was responsible for 39% of the total benefit. Altogether, genetic improvement in the stud tier reached 1.47 million lambs annually or about 54% of the five wool sheep populations of the country. Thus, conventional genetic improvement efforts of economically important traits of wool sheep breeds proved to have been highly profitable.

In autochthonous livestock breeds with small populations, such as the Rubia Galega from Galicia (Spain), mating between relatives is common and can lead to inbreeding depression. Genomic inbreeding coefficients were estimated for 4984 animals using ~63,000 SNPs to assess inbreeding depression in four key traits: age at first calving (AFC) with 3503 records, calving interval (CI) with 3315 records, birth weight (BW) with 4878 records and weight at 210 days (W210) with 3285 records. Runs of homozygosity were sorted by length ([1,2], (2,4], (4,8], (8,16], > 16 Mb), and the corresponding inbreeding coefficients (F_ROH>1, F_ROH>2, F_ROH>4, F_ROH>8, F_ROH>16) were calculated using the consecutiveRUNs R package. A Genomic BLUP (GBLUP) was conducted for each F_ROH estimate using the BLUPF90+ programs. The results revealed significant inbreeding depression for AFC and CI, whereas W210 and BW exhibited similar inbreeding trends, but the effects of inbreeding on these traits were not statistically significant. To further explore the genetic basis of inbreeding depression, SNPs located within ROHs were tested, though a t-test, for their association with phenotypic traits. Genes located in significant regions (-log(p-value) > 3 from t-test) were annotated using Ensembl BioMart within a ± 0.5 Mb window. Recent inbreeding (ROH > 8 Mb) showed significant negative effects on reproductive traits, and key genomic regions-particularly on chromosome 2 involving MSTN, NAB1, and COL5A2-were linked to increased AFC and reduced BW and W210; ROH-based inbreeding estimates proved effective in detecting inbreeding depression in this native breed. Overall, ROH-based analyses revealed genomic regions and candidate genes, notably MSTN, contributing to inbreeding depression and key production traits in Rubia Galega cattle.

Climate change has intensified the need to reduce greenhouse gas emissions, particularly methane (CH₄) from enteric fermentation. Genetic selection has emerged as a promising mitigation strategy; however, studies on Bos taurus indicus , especially Nellore cattle, remain limited. This study aimed to estimate heritabilities and genetic correlations for CH₄ emission traits and their relationships with feeding behaviour, feed efficiency, and performance, as well as to evaluate the direct and correlated responses to selection for lower CH₄ emissions. Data were from 2418 Nellore cattle evaluated in feed efficiency trials. Traits included dry matter intake (DMI), feeding time per day (FTd), feed events per day (FEd), and feeding rate (FR), residual feed intake (RFI), average daily gain (ADG), and mid-test body weight (MBW). Methane emissions were measured in 1153 animals using the SF₆ tracer technique, providing daily CH₄ emission (g/day), CH₄ per unit of DMI (CH₄DMI, g/day), and residual CH₄ (CH₄res). Variance components were estimated using the single-step genomic BLUP (ssGBLUP) method through Bayesian inference. Heritability estimates were moderate for CH₄ (0.25), CH₄DMI (0.14), CH₄res (0.14), and performance traits such as DMI (0.35), ADG (0.36), and MBW (0.40). Higher estimates were observed for feeding behaviour traits FTd (0.49) and FR (0.42). Genetic correlations between CH₄ and production traits were high, particularly with DMI (0.79), ADG (0.90), and MBW (0.91), indicating that selection for reduced CH₄ emissions may affect growth. Direct selection for CH₄ led to a modest annual reduction in emissions but also a correlated decline in MBW. These results demonstrate that while CH₄ emissions are heritable, their strong genetic association with productivity traits indicates that isolated selection for reduced emissions may lead to undesirable outcomes in feed intake and performance. Therefore, strategies aiming to reduce CH₄ emissions should consider the genetic relationships with growth and efficiency traits to avoid compromising animal productivity.

The objective was to evaluate the genetic relationship between the surface temperature of regions of interest, measured using infrared images of young horses and functional longevity in jumping. This relationship was assessed by comparing the temperatures measured in the offspring of two groups of sires, one favourable and one unfavourable, to longevity. The study used a specific data collection protocol on a sample of 921 young progeny, before they began competing, of 141 extreme stallions, comprising 61 favourable and 80 unfavourable sires. These stallions had been selected based on estimated breeding values for functional longevity derived from official competition data of 202,320 horses. Infrared imaging provided 49 temperature variables, including average and maximum values for regions of interest such as temperature differences from the body for eyes, hocks, fetlocks, feet, carpi and back. It also included differentials between these regions, asymmetry between right and left sides and variability within each area. Heritability was estimated using a mixed model with fixed effects, of age, sex, coat colour, weight and visit, along with random genetic effects (considering a pedigree of 8002 horses). The effect of temperature on the group of sires was assessed using multivariate partial least squares logistic regression, adjusting temperature for fixed effects. Results indicated high heritability for the temperature of regions of interest: body (0.53 ± 0.14), carpi (0.55 ± 0.19), fetlocks (0.47 ± 0.12), feet (0.46 ± 0.12 and 0.38 ± 0.12). Lower heritability was observed for differences between regions (around 0.20) and even lower for asymmetry and variability. Lower average and maximum eye temperatures, lateral asymmetry in hind feet temperature and temperature variability in the back were associated with a higher probability of belonging to the favourable group of sires for functional longevity. Infrared imaging may be a tool for identifying easily measurable selection criteria associated with longevity. Given the limited number of horses, the limited number of significant variables associated with the group of sires and the specificity of the protocol, verification and validation studies are necessary before its use.

The identification of quantitative trait locus (QTL) or genes responsible for key agronomic traits has significantly enhanced genetic improvement through marker-assisted selection (MAS). However, the impacts of MAS on genetic parameters and subsequent selection processes have not been thoroughly characterised. Here, through genome-wide selective sweep analysis, we identified a diverse set of genes involved in oocyte meiosis, including PPP3CA, AR, PPP1CB, SPDYA, MAD1L1, and BMPR1B. The genome-wide association study (GWAS) further identified three genes UNC5C, BMPR1B, and PDLIM5 as being associated with lambing rate in Hu sheep. From these analyses, the FecB loci emerged as a potential molecular marker for lambing rate. with an increase of 0.5 lambs per G allele. The heritability of the lambing rate was estimated to be 0.19 (±0.02). Moreover, based on 10-fold cross-validation, the accuracy of genomic selection (GS) was found to be 0.30. Simulated MAS resulted in a reduction of the additive genetic variance components, with estimated heritability dropping to 0.14 (±0.02) and GS accuracy decreasing to 0.18-representing a decline of 26.42% and 34.81%, respectively. To address the reduced GS accuracy, we performed GWAS on the reference set to identify weighted single nucleotide polymorphisms (SNPs). This method has the potential to increase accuracy by 13.8%. Our study found that MAS has a negative impact on GS. To address this issue, we integrated prior information on SNPs from GWAS, which exhibit pleiotropic genetic architecture. This integration enables us to utilise genetic markers for complex traits more effectively, thereby improving the accuracy and efficiency of GS.

The ability of ruminants to mobilise and restore body reserves (BR) over time, referred to as BR dynamics, is currently considered an interesting biological component to be included in breeding programs targeting enhanced BR resilience. However, genetic studies of proxies for BR levels and BRD remain scarce, particularly in small ruminants. The aim of this study was to estimate the genetic parameters for key plasma biomarker concentrations in sheep at critical physiological stages (PhySt i.e., mating; mid-pregnancy, before-lambing, after-lambing, and weaning), and their changes over time. Non-esterified fatty acids (NEFA), β-hydroxybutyrate (BHB), triiodothyronine (T3) and insulin (INS) were monitored at those PhySt in successive production cycles. A total of 659 productive Romane ewes were phenotyped for one (n = 252, multiparous) or two (n = 407, primiparous and multiparous) cycles. BR mobilisation was observed from the second half of pregnancy and during suckling while BR accretion was more evident from weaning until the next mid-pregnancy. Considering biomarkers concentrations as repeated measurements through the whole production cycle, heritability estimates were 0.07, 0.09, 0.15, and 0.10 for NEFA, BHB, T3, and INS, respectively. Heritability estimates for plasma biomarkers at key PhySt ranged from 0.08 to 0.16 for NEFA, 0.07 to 0.12 for BHB, 0.09 to 0.18 for T3, and 0.04 to 0.15 for INS. Heritability estimates for biomarker changes over time ranged from 0.01 to 0.23. Genetic correlation estimates between different PhySt were positive for each plasma biomarker and ranged from 0.19 to 0.87 for NEFA, from 0.50 to 0.89 for BHB, from 0.54 to 0.95 for T3 and from 0.34 to 0.90 for INS. Most genetic correlation estimates between biomarkers at a given PhySt were generally low to moderate (r_g = -0.52 to 0.59), with few showing strong negative or positive values beyond 0.60 in magnitude. Considering changes over time, correlations were similarly low to moderate ( $r_g$  = -0.59 to 0.53), with only a few estimates reaching high values ( $r_g$  = -0.60 to -0.97 and 0.67 to 0.97). This study demonstrates that blood biomarkers related to energy BR have genetic variation, indicating their potential for implementation in sheep breeding programs aimed at improving BR use and build-up.

Enhancing female longevity through regular calvings improves herd replacement rates and reduces the costs associated with replacing low reproductive efficiency animals. Stayability (STAY), defined as a cow's ability to remain productive in the herd, is a categorical trait that challenges traditional genetic evaluation due to its non-normal distribution. This study aimed to estimate genomic predictions for different STAY definitions-based on the number of calvings at specific ages in Nellore females-and to compare the predictive ability of linear and threshold models using the linear regression (LR) method. Phenotypic and genotypic data from 187 herds provided by the Nellore Brazil breeding program (ANCP, Ribeirão Preto, Brazil) were used. Four STAY definitions (STAY48-2, STAY48-3, STAY54-2, STAY54-3, STAY72-3) were evaluated. Genomic estimated breeding values (GEBV) were obtained using univariate linear and threshold models implemented in the BLUPF90 software family. Variance components were transformed from liability to observed scale. Heritability estimates ranged from 0.16 to 0.22 on the liability scale and 0.07 to 0.09 on the observed scale. Threshold models showed superior predictive ability compared to linear models, with higher accuracies (0.531 to 0.698 vs. 0.451 to 0.532), lower bias (-0.0004 to 0.008 vs. 0.027 to 0.096) and dispersion values closer to the ideal (0.932 to 1.000 vs. 0.811 to 0.848). Among the definitions, STAY48 with at least two or three calvings demonstrated the most consistent performance, representing a promising criterion for genetic evaluation in Nellore cattle.

This study evaluated the influence of variance component (VC) estimates, obtained from different models and two relationship matrices, pedigree-based (BLUP) and genomic information-based (ssGBLUP), on genomic predictions of carcass traits in Montana composite cattle. Phenotypic records from 14,422 animals were analysed for ribeye area, rump fat thickness, backfat thickness and marbling, along with pedigree information from 193,129 animals and genomic data from 3911 animals genotyped with 49,457 SNPs. Variance components and heritability estimates were calculated using restricted maximum likelihood under single-trait linear models. Across five models (M1-M5), fixed effects included contemporary group, embryo transfer, age at ultrasound and cow age at calving, while random effects included direct genetic effect and residual. From model M2 onwards, biological type, heterosis and both combined and specific recombination effects were also considered. The Akaike information criterion (AIC) was used to identify the best-fitting model. Different VC estimates were applied in ssGBLUP predictions to evaluate predictive ability based on accuracy, bias and dispersion. Variance component and heritability estimates were similar between methods, although ssGBLUP yielded higher direct additive genetic variances and heritabilities. More parameterised models using ssGBLUP provided a better fit according to AIC. However, less parameterised models showed superior predictive ability, regardless of whether VCs were estimated by BLUP or ssGBLUP. When comparing predictive ability across sources, pedigree-based VC estimates resulted in more accurate predictions. Thus, the choice of model complexity should be guided by the analysis objective and the available data structure.

This study aimed to estimate the variance components, heritabilities and genetic correlations between four new different categories of stayability (STAY48-2, STAY48-3, STAY54-2, STAY54-3) with weight at 240 days of age (W240), weight at 450 days of age (W450), scrotal circumference at 365 days of age (SC365), age at puberty in males (APM), traditional stayability (STAY72), probability of precocious calving at 30 months of age (PPC30), ribeye area (REA), rump fat thickness (RFT), residual feed intake (RFI), dry-matter intake (DMI), residual live weight gain (RG) and frame score (FRAME). Records from 80,958 females born between 2000 and 2019, exposed to mating starting at 10 months of age, raised on pasture from 508 farms in the central-west, southeast, northeast and northern regions of Brazil that participate in the National Association of Breeders and Researchers (ANCP), were analysed. The (co)variance components were estimated by Bayesian inference in a two-trait animal model. The posterior means of heritability estimates for STAY48-2, STAY48-3, STAY54-2 and STAY54-3 were moderate to low, 0.20, 0.20, 0.22 and 0.22 respectively. The traits related to different categories of stayability showed low genetic correlations with male reproductive traits (-0.22 to 0.19), feed efficiency (-0.03 to 0.13), carcass (0.11 to 0.18) and body composition (-0.09 to -0.6), moderate with growth (0.04 to 0.29) and high with sexual precocity (0.88 to 0.93) and fertility (0.65 to 0.73). The heritability estimates of the different categories of stayability indicate genetic improvement for longevity in early challenged females. The genetic correlations with sexual precocity showed that its use as selection criteria is recommended for production systems of younger females challenged in the reproductive season rather than traditional stayability to increase the probability of stayability in the herd.

This study aimed to estimate (co)variance components and genetic parameters for accumulated profitability (AFP) and profit per kilogram of liveweight gain (PFT), and their relationships with weight at 450 days of age (W450), scrotal circumference at 365 days of age (SC365), age at first calving (AFC), probability of precocious calving at 30 months of age (PPC30), age at puberty in males (APM), stayability (STAY), accumulated cow productivity (ACP), rib eye area (REA), rump fat thickness (RFT), residual feed intake (RFI), dry-matter intake (DMI), residual live weight gain (RG), and frame score (FRAME). Data of profitability from 3614 Nelore (Bos indicus) animals were used. The (co)variance components and genetic parameters were estimated using Bayesian inference in a multi-trait animal model. The heritability estimates for AFP and PFT were 0.18 and 0.02, respectively. AFP and PFT exhibited moderate to high genetic correlations with growth traits (0.64 to 0.65), carcass (0.43 to 0.44), feed efficiency (0.72 to 0.88), and frame (0.44 to 0.77), except for the correlation with RFT (-0.10 to -0.68), RFI (-0.23 to 0.28), and between PFT and DMI (0.26). Low to high genetic correlations (-0.47 to 0.76) with female reproductive traits and low correlations (-0.03 to -0.21) with male reproductive traits were observed for both traits. These results provide important information for improving economic performance by including complementary AFP and PFT tools in the selection criteria. Such traits can be strategic tools for producers when identifying animals with greater genetic potential for profitability, supporting decision-making in genetic planning and herd management.