Category Archives: Journal of Animal Breeding and Genetics

Validating genomic prediction for nitrogen efficiency index and its composition traits of Holstein cows in early lactation

Posted on 10 October 2023 by

Abstract

Nitrogen (N) use efficiency (NUE) is an economically important trait for dairy cows. Recently, we proposed a new N efficiency index (NEI), that simultaneously considers both NUE and N pollution. This study aimed to validate the genomic prediction for NEI and its composition traits and investigate the relationship between SNP effects estimated directly from NEI and indirectly from its composition traits. The NEI composition included genomic estimated breeding value of N intake (NINT), milk true protein N (MTPN) and milk urea N yield. The edited data were 132,899 records on 52,064 cows distributed in 773 herds. The pedigree contained 122,368 animals. Genotypic data of 566,294 SNP was available for 4514 individuals. A total of 4413 cows (including 181 genotyped) and 56 bulls (including 32 genotyped) were selected as the validation populations. The linear regression method was used to validate the genomic prediction of NEI and its composition traits using best linear unbiased prediction (BLUP) and single-step genomic BLUP (ssGBLUP). The mean theoretical accuracies of validation populations obtained from ssGBLUP were higher than those obtained from BLUP for both NEI and its composition traits, ranging from 0.57 (MTPN) to 0.72 (NINT). The highest mean prediction accuracies for NEI and its composition traits were observed for the genotyped cows estimated under ssGBLUP, ranging from 0.48 (MTPN) to 0.66 (NINT). Furthermore, the SNP effects estimated from NEI composition traits, multiplied by the relative weight were the same as those estimated directly from NEI. This study preliminary showed that genomic prediction can be used for NEI, however, we acknowledge the need for further validation of this result in a larger dataset. Moreover, the SNP effects of NEI can be indirectly calculated using the SNP effects estimated from its composition traits. This study provided a basis for adding genomic information to establish NEI as part of future routine genomic evaluation programs.

Ascertaining the genetic background of the Celtic‐Iberian pig strain: A signatures of selection approach

Posted on 9 October 2023 by

Abstract

Celtic-Iberian pig breeds were majority in Spain and Portugal until the first half of the 20th century. In the 1990s, they were nearly extinct as a result of the introduction of foreign improved pig breeds. Despite its historical importance, the genetic background of the Celtic-Iberian pig strain is poorly documented. In this study, we have identified genomic regions that might contain signatures of selection peculiar of the Celtic-Iberian genetic lineage. A total of 153 DNA samples of Celtic-Iberian pigs (Spanish Gochu Asturcelta and Portuguese Bísara breeds), Iberian pigs (Spanish Iberian and Portuguese Alentejano breeds), Cinta Senese pig, Korean local pig and Cosmopolitan pig (Hampshire, Landrace and Large White individuals) were analysed. A pairwise-comparison approach was applied: the Gochu Asturcelta and the Bísara samples as test populations and the five other pig populations as reference populations. Three different statistics (XP-EHH, F _ST and ΔDAF) were computed on each comparison. Strict criteria were used to identify selection sweeps in order to reduce the noise brought on by the Gochu Asturcelta and Bísara breeds' severe population bottlenecks. Within test population, SNPs used to construct potential candidate genomic areas under selection were only considered if they were identified in four of ten two-by-two pairwise comparisons and in at least two of three statistics. Genomic regions under selection constructed within test population were subsequently overlapped to construct candidate regions under selection putatively unique to the Celtic-Iberian pig strain. These genomic regions were finally used for enrichment analyses. A total of 39 candidate regions, mainly located on SSC5 and SSC9 and covering 3130.5 kb, were identified and could be considered representative of the ancient genomic background of the Celtic-Iberian strain. Enrichment analysis allowed to identify a total of seven candidate genes (NOL12, LGALS1, PDXP, SH3BP1, GGA1, WIF1, and LYPD6). Other studies reported that the WIF1 gene is associated with ear size, one of the characteristic traits of the Celtic-Iberian pig strain. The function of the other candidate genes could be related to reproduction, adaptation and immunity traits, indirectly fitting with the rusticity of a non-improved pig strain traditionally exploited under semi-extensive conditions.

Genetic associations between stayability to consecutive calvings and traits of economic interest in taurine and zebu breeds

Posted on 3 October 2023 by

Abstract

Stayability (STAY) is a way to evaluate the productive longevity of females. Measuring the STAY at each cow calving allows earlier indicators of longevity to be obtained. Our objective with this study was to verify the association between STAY and consecutive calvings and traits potentially used as selection criteria in beef cattle, such as age at first calving (AFC), days to calving (DC), weaning weight (WW), and yearling weight (YW). Data from the Nelore, Angus/Brangus, and Hereford/Braford breeds were used. The estimation of variance components and subsequent prediction of breeding values were performed for all traits. The estimated breeding values (EBV) were used to analyse the association between STAY and the other traits. The Pearson's correlation estimated between the EBV for the intercept coefficient for STAY to consecutive calvings and those of AFC, DC, WW (direct and maternal effects), and YW was favourable and of low magnitude (<0.25) depending on the breed studied. The influence of the genetic merit of AFC on the chance of selection for STAY was favourable and relevant regardless of the intensity of selection and breed. DC and WW (maternal effect) traits were favourably influenced by the chance of selection for STAY, irrespective of breed. The WW (direct effect) did not affect the chance of selection for STAY for the Nelore and Hereford/Braford breeds and negatively influenced, but to a small extent, the Angus/Brangus breed. For YW, an increase in genetic merit affected the chances of selection for STAY, depending on the breed and selection intensity evaluated. The influence of the genetic merit for AFC, DC, and WW (maternal effect) on the chance of selection for STAY to consecutive calvings was favourable and relevant regardless of the selection intensity scenario evaluated. The WW (direct effect) did not influence the chance of selection for STAY. For the scenario with high selection intensity, the selection for YW favourably influenced the chance of selection for STAY in Angus/Brangus and Hereford/Braford breeds but not in Nelore.

Including genomic information in the genetic evaluation of production and reproduction traits in South African Merino sheep

Posted on 3 October 2023 by

Abstract

Genomic selection (GS) has become common in sheep breeding programmes in Australia, New Zealand, France and Ireland but requires validation in South Africa (SA). This study aimed to compare the predictive ability, bias and dispersion of pedigree BLUP (ABLUP) and single-step genomic BLUP (ssGBLUP) for production and reproduction traits in South African Merinos. Animals in this study originated from five research and five commercial Merino flocks and included between 54,072 and 79,100 production records for weaning weight (WW), yearling weight (YW), fibre diameter (FD), clean fleece weight (CFW) and staple length (SL). For reproduction traits, the dataset included 58,744 repeated records from 17,268 ewes for the number of lambs born (NLB), number of lambs weaned (NLW) and the total weight weaned (TWW). The single-step relationship matrix, H, was calculated using PreGS90 software combining 2811 animals with medium density (~50 K) genotypes and the pedigree of 88,600 animals. Assessment was based on single-trait analysis using ASREML V4.2 software. The accuracy of prediction was evaluated according to the ‘LR-method’ by a cross-validation design. Validation candidates were assigned according to Scenario I: born after a certain time point; and Scenario II: born in a particular flock. In Scenario I, the genotyping rate for the reference population between 2006 and the 2013 cut-off point approached 7% of animals with phenotypes and 20% of their sires. For reproduction traits, about 20% of ewes born between 2006 and 2011 cut-off were genotyped, along with 15% of their sires. Genotyping rates in the validation set of Scenario I were 3.7% (production) and 11.4% (reproduction) for candidates and 35% of their sires. Sires were allowed to have progeny in both the reference and validation set. In Scenario I, ssGBLUP increased the accuracy of prediction for all traits except NLB, ranging between +8% (0.62–0.67) for FD and +44% (0.36–0.52) for WW. This showed a promising gain in accuracy despite a modestly sized reference population. In the ‘across flock validation’ (Scenario II), overall accuracy was lower, but with greater differences between ABLUP and ssGBLUP ranging between +17% (0.12–0.14) for TWW and +117% (0.18–0.39) for WW. There was little indication of severe bias, but some traits were prone to over dispersion and the use of genomic information did not improve this. These results were the first to validate the benefit of genomic information in South African Merinos. However, because production traits are moderately heritable and easy to measure at an early age, future research should be aimed at best exploiting GS methods towards genetic prediction of sex-limited and/or lowly heritable traits such as NLW. GS methods should be combined with dedicated efforts to increase genetic links between sectors and improved phenotyping by commercial flocks.

Genetic parameters for health traits and their association with fertility and milk production in Chinese Holsteins

Posted on 25 September 2023 by

Abstract

Herd health is one of the key problems influencing the efficiency of the dairy industry. Genetic selection, with a focus on animal health, is important for herd improvement. This study aimed to estimate genetic parameters for health traits and their correlations with fertility and milk production traits in dairy cattle. Based on records from 58,549 lactating cows calved between 2015 and 2021, a total of 24 health traits (six composite health traits and 18 independent health traits), four fertility traits and five milk production traits were analysed. First, linear and threshold animal models were used to estimate the variance components and heritabilities of the health traits. Second, a bivariate linear animal model was used to estimate genetic correlations among all 24 health traits. Finally, a bivariate linear animal model based on records from the first lactation was used to estimate the correlations between health traits and fertility or milk production traits. The results showed that all health traits had low heritabilities, ranging from 0.002 (0.001) to 0.048 (0.004) in the linear model and from <0.001 (0.021) to 0.226 (0.035) in the threshold model. Genetic correlations between health traits across categories were generally low, whereas the relatively high genetic correlations were found between health traits within the same category. In this study, only a few significant and moderate genetic correlations were observed between health traits and fertility or milk production traits. Clinical mastitis showed relatively moderate correlations with fertility traits, ranging from 0.277 (0.113) (interval from first to last insemination) to 0.401 (0.104) (calving interval). Moreover, there were moderate genetic correlations between hoof health and milk production traits. The results from the current study will support balanced dairy breeding to genetically improve disease resistance in dairy cows.

Conditioning on the causal network prevents indirect response to selection

Posted on 19 September 2023 by

Abstract

Multiple trait animal models (MTM) allow to estimate the breeding values (BV) of several traits simultaneously while accounting for genetic and environmental correlations among them. However, relationships among traits may not be reciprocal but rather causal in nature. In these cases, and given a causal network, structural equations models (SEM) arise as a more appropriate methodology. Although MTM and SEM have been shown to be parametrically equivalent, the estimated breeding value (EBV) obtained from either one or the other should be interpreted differently. In this study, we investigated the impact of using these estimates on the response to selection for a causal network comprising five different traits through a stochastic simulation experiment. Three different selection targets were assayed, involving traits located upstream, midstream and downstream this causal network. We first considered the case in which traits were causally related but not genetically correlated. The current results support our hypothesis that MTM will absorb causal relationships as genetic correlations and, consequently, change the response to selection achieved as compared with SEM. We found no differences on the response to selection when the target trait was located at the top of the causal network, but noticeable differences were detected on upstream traits when selection pressure was placed on midstream or downstream traits. We also assayed a scenario in which causal effects and genetic correlations act simultaneously and found that selection based on BVs estimated using SEM diminished the indirect response in traits upstream the causal network.

Genetic parameters for carcass and meat quality traits in Jinhua, Duroc, and their crossbred pigs

Posted on 5 September 2023 by nKei Terada, nToshiyuki Ohtani, nShinichiro Ogawa, nHiroyuki Hirookan

Abstract

Jinhua pigs have excellent meat quality and intramuscular fat content (IMF). Crossbreeding of Jinhua with Duroc pigs with high productivity was conducted to develop a new composite breed that possesses the beneficial characteristics of both breeds. The objective of this study was to estimate the crossbreeding parameters (additive breed, dominance, and epistatic loss effects) using the Kinghorn model and genetic parameters (heritability and genetic correlation) for carcass and meat quality traits by analysing the phenotypic data of Jinhua, Duroc, and their crossbred pigs. Backfat thickness at the thinnest point above the 9th to 13th thoracic vertebrae (BF), longissimus muscle area between the 4th and 5th thoracic vertebrae (LMA), meat shear force value (SFV), and IMF were measured. The additive breed effects were significant for all traits: 1.59 cm, −8.30 cm², −6.38 lb/cm², and 1.76% for BF, LMA, SFV, and IMF, respectively. The dominance effect was significant for LMA (7.41 cm²) and IMF (−2.46%), whereas the epistatic loss effect was significant for only LMA (−15.18 cm²). The estimated heritability values were high, ranging from 0.58 for IMF to 0.76 for LMA. A negative but non-significant genetic correlation of −0.11 was estimated between BF and IMF; however, previous studies have reported that the genetic correlation between these traits is moderately positive in modern western pigs. Our results imply that, with the estimation of crossbreeding and genetic parameters, genetic improvement could be implemented to produce a new composite breed with good meat quality and productivity, to meet Japanese market requirements, by crossbreeding Jinhua and Duroc pigs.

Assessing the predictability of racing performance of Thoroughbreds using mixed‐effects model

Posted on 28 August 2023 by nDaiki Oda, nAkio Onogin

Abstract

The inheritance of racing performance in Thoroughbreds is of interest to breeders and geneticists. Therefore, the genetic parameters of racing performance have been investigated in various populations of Thoroughbreds. However, the predictability of the racing performance of a racehorse has not been assessed well. In this study, we built mixed-effects models for Japanese Thoroughbreds and assessed their predictability of racing performance. We used the average velocity as an index of racing performance and treated each category of racecourse and distance as different traits. Model selection using the deviance information criterion showed that explanatory variables, such as race, age and jockey effects are important for racing performance. Using the selected models, the phenotypic values of horses born after 2009, adjusted using the entire dataset, were predicted with the breeding values estimated from a partial dataset until 2010. The correlation coefficients ranged from 0.000 to 0.235 (average of 0.084 ± 0.066) and were higher for longer distances. When predicting the graded race winners born after 2009 from the partial dataset until 2010, the area under the curve values ranged from 0.516 to 0.776 (average of 0.613 ± 0.073) and were also higher for longer distances. Although these results indicate the predictability of racing performance, further efforts, including exploring more suitable racing performance indices and refining statistical modelling, are required for improvement.

Bayesian estimates of genetic effects on calf survival in Hardhenu (Bos taurus × Bos indicus) cattle

Posted on 23 August 2023 by

Abstract

The aim of the present study is to carry out a risk analysis and Bayesian estimates of genetic effects on calf survival in Hardhenu cattle using data records of 2593 calves born to 102 sires and 790 dams over 25 years. The Bayesian analysis using Gibbs sampling was employed towards threshold animal models to estimate direct and maternal effects on animal survival of studied population. The results showed that mortality from birth to 3 months of age (S1), birth to 6 months of age (S2) and birth to 12 months of age (S3) was 10.22, 12.88 and 14.65%, respectively. It was revealed from the results of logistic regression analysis that the male animals had greater risk (1.41–1.61 times) of mortality during S1, S2 and S3 as compared to female animals. However, calves born during rainy season had higher risk (1.36 to 1.44 times) of mortality than calves born during winter season. Among died animals, the simultaneous infection of respiratory and digestive diseases had leading contribution (26.84%–30.19%) to deaths while alone of them contributed to 18%–20% only. On evaluation of six threshold animal models, model 1 was found to be most appropriate model and the Bayesian estimates (95% highest posterior density confidence intervals) of direct additive heritability for S1, S2 and S3 under model 1 were 0.15 ± 0.07 (0.04–0.23), 0.23 ± 0.12, (0.02–0.44) and 0.26 ± 0.06 (0.08–0.41), respectively. It was concluded that the inclusion of survival traits in existing selection criteria may be helpful to increase calf survival and ultimately economic gain in the dairy herd.

Breeding objectives for Central Highland goats using participatory and bio‐economic modelling approaches

Posted on 22 August 2023 by

Abstract

The breeding objectives of Central Highland goats rearing under a low-input production system were defined through a participatory proportional piling method and bio-economic model. Additionally, the economic values and relative economic value of the breeding objective traits were derived. A participatory proportional piling method was used to estimate the relative weights of farmers attached to a list of goat traits identified, and the relative weights were statistically evaluated using a generalized multinomial logit model analysis. A bio-economic model was used to compute the economic values of the identified traits. The most important traits for selection of does according to farmer's preference were body size, coat colour, post-weaning growth rate and weaning rate with a relative weight (odds ratio) of 1.58, 1.38, 1.37 and 1.13, respectively. Goats with dark red followed by light red coat colour were the most preferred (p < 0.001) by goat keepers compared with white-coloured goats. Farmers were more likely (p < 0.001) to allocate higher scores for does-bearing twins than for single and triplet-bearing does. Using the bio-economic model (economic value and relative economic value), post-weaning growth rate, weaning rate, and six-month weight (body size) were identified as the most important traits and if the mean of these traits is changed by one genetic standard deviation, the change in profit will range from 2.06 to 3.03 $ doe⁻¹ year⁻¹. Therefore, the most important traits for the selection of Central Highland goats according to the economic-based method were post-weaning weight gain, weaning rate and body size (six-month weight). Besides, coat colour was the second preferred trait by goat keepers next to body size. Thus, this aesthetical trait should be included in the designed breeding programme besides economically important quantitative traits. The combination of the participatory proportional piling method and bio-economic model would give better insights to explore the trait preferences of farmers and enhance profitability. The economic values of traits estimated in this study can be used for the construction of selection indices for Central Highland goats.