Direct Genetic Effects Research Articles

The Law of Nature and Nurture and Its Impact on Education

The debate between nature and nurture is a long-standing and highly deliberated concept in fields ranging from psychology to education. This research therefore sought to determine the effects of nature and nurture on academic performance, learning approaches, behaviours, and educational expectations among students within the context of Ogun State, Nigeria. The study adopted a quantitative research design where data was collected from 240 students and 60 teachers from three local government areas using structured questionnaires. Descriptive statistics, correlation analyses, and independent sample t-tests were used to analyze data. In this context, both direct genetic effects and indirect environmental influences on the investigated educational outcomes were identified. However, the level of using environmental factors including socioeconomic status, family, teaching approaches and resources was higher with significantly more frequency. The correlation analyses and t-tests also corroborated these findings, suggesting a connection between environment and academic performance, learning styles, behavioural patterns and educational achievements. The study adds to the current body of knowledge on the nature-nurture debate within the context of the education system in Nigeria. The findings underscore the role of socioeconomic status in children’s achievement and readiness to learn, emphasizing the need for equal opportunities in education and support for their aspirations. In the same respect, the study emphasizes the importance of a bio-psychosocial model that considers both genetic predeterminations and environmental conditions to explain educational processes and performance.

Estimation of the genetic parameters of sheep growth traits based on machine vision acquisition

In the realm of animal phenotyping, manual measurements are frequently utilised. While machine-generated data show potential for enhancing high-throughput breeding, additional research and validation are imperative before incorporating them into genetic evaluation processes. This research presents a method for managing meat sheep and collecting data, utilising the Sheep Data Recorder system for data input and the Sheep Body Size Collector system for image capture. The study aimed to investigate the genetic parameter changes of growth traits in Ujumqin sheep by comparing machine-generated measurements with manual measurements. The dataset consisted of 552 data points from the offspring of 75 breeding rams and 399 breeding ewes. Six distinct random regression models were assessed to pinpoint the most suitable model for estimating genetic parameters linked to growth traits. These models were distinguished based on the inclusion or exclusion of maternal genetic effects, maternal permanent environmental effects, and covariance between maternal and direct genetic effects. Fixed factors such as individual age, individual sex, and ewe age were taken into account in the analysis. The genetic parameters for the yearling growth traits of Ujumqin sheep were calculated using ASReml software. The Akaike information criterion, the Bayesian information criterion, and fivefold cross-validation were employed to identify the optimal model. Research findings indicate that the most accurate models for manually measured data revealed heritability estimates of 0.12 ± 0.15 for BW, 0.05 ± 0.07 for body slanting length, 0.03 ± 0.07 for withers height, 0.15 ± 0.12 for hip height, 0.11 ± 0.11 for chest depth, 0.13 ± 0.13 for shoulder width, and 0.53 ± 0.15 for chest circumference. The optimal models for machine-predicted data showed heritability estimates of 0.1 ± 0.09 for body slanting length, 0.14 ± 0.12 for withers height, 0.55 ± 0.15 for hip height, 0.34 ± 0.15 for chest depth, 0.26 ± 0.15 for shoulder width, and 0.47 ± 0.16 for chest circumference. In manually measured data, genetic correlations ranged from 0.35 to 0.99, while phenotypic correlations ranged from 0.07 to 0.90. In machine data, genetic correlations ranged from −0.05 to 0.99, while phenotypic correlations ranged from 0.03 to 0.84. The results suggest that machine-based estimations may lead to an overestimation of heritability, but this discrepancy does not impact the selection of breeding models.

Early growth performance in the Murciano-Granadina goats: insights from genetic and phenotypic analyses

Abstract This study investigates the genetic and phenotypic aspects of early growth performance in the Murciano-Granadina goat breed, using data collected between 2016 and 2022 from a private dairy farm in Ghale-Ganj city, located in the southern area of Kerman province, Iran. Pedigree and data information were collected on several early body weight traits, including birth weight (BW), weaning weight (WW), average daily gain (ADG), Kleiber ratio (KR) and growth efficiency from birth to weaning (GE). Nine univariate animal models included direct additive genetic effects and different combinations of maternal effects were compared by using Akaike information criterion (AIC). Among the tested models, the best genetic analysis model for BW, included direct additive, maternal additive, maternal permanent and maternal temporary environmental effects. The best model for ADG, KR and GE included direct additive, maternal permanent and litter effects. For WW, the best model was determined to be one that included direct additive and maternal additive genetic effects. The estimated direct heritabilities were low values of 0.04, 0.07, 0.08, 0.05 and 0.07 for BW, ADG, KR, GE and WW, respectively. The estimates of genetic correlations among the studied traits were positive and low to high in magnitude which ranged from 0.11 for BW-KR to 0.91 for BW-GE. The phenotypic correlations ranged from 0.03 for KR-WW to 0.87 for ADG-KR. The positive correlations observed among the studied growth traits of the Murciano-Granadina goat breed indicate no negative genetic or phenotypic changes associated with selection for these traits.

78 Estimates of genetic parameters for weight, wool, and carcass traits of Rambouillet sheep

Abstract The Rambouillet sheep breed is the foundation to most western range sheep in the U.S. Through the National Sheep Improvement Program (NSIP), Rambouillet breeders seek to improve economically relevant traits. However, the parameters used in the NSIP genetic evaluation were last estimated two decades ago. Our aim was to re-estimate genetic parameters for body weight (BW), carcass, and wool traits. Data were provided by NSIP, which included BW at birth (BWT; n = 28,817), weaning [WWT; n = 5,633; age: 68 (SD 16) day], early post-weaning [PWTE; n = 23,303; 128 (SD 22) d], late post-weaning [PWTL; n = 7,689; 201 (SD 45) d] and as yearlings [YWT; n = 5,830; 375 (SD 33) d]. Yearling ultrasound scans of 12th rib backfat depth (YCF; n = 2,447) and eye muscle depth (YEMD; n = 2,457) were also available. Yearling wool traits were fiber curvature (YFC; n = 6,009), fiber diameter (YFD; n = 9,880), fiber diameter coefficient of variation (YFDCV; n = 8,803), greasy fleece weight (YGFW; n = 11,859) and staple length (YSL; n = 11,270). The pedigree consisted of 36,297 individuals. Animals with phenotypic records were progeny of 333 sires and 1,727 dams. A succession of univariate animal models was fitted. The most comprehensive model included direct and maternal additive genetic effects, their genetic covariance, and maternal permanent environmental and residual effects. Phenotypes were pre-adjusted for birth-rearing type category and, as covariates, dam age and age at recording. Contemporary group—a concatenation of flock, year, season, management group, sex, and, excluding BWT, recording date—was the only fixed effect fitted in the model. Model selection was based on the log-likelihood ratio test, and Akaike and Bayesian information criteria. The data structure, namely dams and their daughters and granddaughters contributing data, allowed reliable testing of the maternal effect terms. The direct-maternal genetic covariance did not explain variation for any trait (P > 0.18). The most parsimonious model for BW traits included direct and maternal additive genetic, and maternal permanent environmental, effects. For carcass and wool traits, only direct additive genetic effects were included in the final model. Such was unsurprising, as maternal effects often diminish as animals age. For the final models fitted (Table 1), direct heritabilities (± SE) for body weights ranged from 0.14 ± 0.01 (BWT) to 0.38 ± 0.04 (PWTL); the maternal heritabilities ranged from 0.04 ± 0.02 (PWTL; YWT) to 0.13 ± 0.01 (BWT). For carcass traits, direct heritabilities were 0.13 ± 0.04 (YCF) and 0.31 ± 0.05 (YEMD). For wool traits, they ranged from 0.37 ± 0.02 (YSL) to 0.58 ± 0.02 (YFD). These re-estimated parameter values are consistent with those used by NSIP, with the exception of PWTL (greater) and YSL (lower). With genomic data accumulating in Rambouillet, further refinements in parameter estimation are planned.

Genetic parameters, genetic trends and correlated responses of growth traits considering maternal ability in Nelore cattle.

The growth of Nelore cattle was analysed considering the following performance parameters; the effect of the calving order of cows on the phenotypic expression of birth weight (BW), average daily gain from birth to weaning (BWG), and weaning weight (WW), the estimated genetic parameters for the traits, including the covariance components between direct and maternal genetic effects. Genetic trends and correlated responses were also obtained for the studied traits. The calving order of cows, as well as other fixed effects used to obtain the adjusted phenotypic means, were statistically significant (p < 0.001) for studied traits. Direct heritability was estimated at 0.24 ± 0.01 (BW), 0.15 ± 0.01 (BWG), and 0.18 ± 0.01 (WW), while maternal heritability was 0.06 ± 0.01 (BW), 0.12 ± 0.01 (BWG), and 0.11 ± 0.01 (WW). The correlations between direct and maternal effects within the same trait were negligible. Moderate to higher direct genetic correlations (ranging from 0.54 ± 0.04 to 0.98 ± 0.01) and maternal genetic correlations (ranging from 0.34 ± 0.09 to 0.99 ± 0.002) were estimated between the studied traits. Unlike direct genetic effects, there was no significant change in maternal genetic effects over time (p > 0.05). These results indicated the need for revising selection indexes for enhancing maternal ability. Correlated responses were generally lower compared to direct responses, except for BWG. The selection for BWG, considering the maternal genetic effect, would be more efficient to improve maternal ability of the cows for pre-weaning growth in relation to selection for WW. Our results found that direct genetic merit improves pre-weaning weight and this trait can be incorporated into the breeding goal as reflected in the WW.

Genetic parameters for mesenteric torsion in a pig maternal line

Mesenteric torsion (MT) is a condition characterized by the twisting of intestinal loops, leading to a disruption in blood flow and abdominal distension. Several factors can predispose animals to this condition, which primarily affects healthy, fast-growing pigs and often results in fatal outcomes. Given the absence of studies on the genetic factors associated with this condition, our research aimed to estimate the heritability coefficient for MT and explore the genetic correlations between MT and performance traits in pigs. Our dataset comprised of 43,384 records of pigs from a maternal line from a nucleus farm. These pigs were born between 2010 and 2022 and had recorded information regarding MT status (0 for healthy and 1 for affected animals), weaning weight (WW), as well as pedigree, genotypes, and genomic estimated breeding values (GEBVs) for the following traits: MT status, days to reach 110 kg (D110), feed conversion adjusted to 110 kg (FC110), and backfat thickness adjusted to 110 kg (BT110). In our statistical model, the effects of contemporary group (CG: sex, year, and week of weaning) and the linear covariate WW were considered fixed effects, while the direct additive genetic effect was accounted as random. On average, pigs affected by MT had an age of 104.35 ± 37.75 days, and the condition had an overall herd frequency of 2.46 %. Mesenteric torsion occurred more frequently in female pigs raised in collective pens compared to non-castrated males raised in individual pens. Heritability estimates for MT, using both pedigree (0.13 ± 0.02) and genomic (0.12 ± 0.02) data, were of low magnitude. This suggests that while there is genetic variability associated with MT, a significant portion of this variation is due to environmental variance. The correlation between MT and BT110 GEBVs was of low magnitude (0.05). In contrast, the correlations between GEBVs for MT and both D110 and FC110 were moderate in magnitude (0.22 for both traits). This implies that pigs taking longer to reach 110 kg and those with poorer feed conversion are more likely to develop MT. There is genetic variability for mesenteric torsion in pigs. Selection aimed at improving feed conversion and reducing the age at which pigs reach 110 kg could lead to a decrease in the occurrence of MT within pig populations.

Interpreting population- and family-based genome-wide association studies in the presence of confounding.

A central aim of genome-wide association studies (GWASs) is to estimate direct genetic effects: the causal effects on an individual's phenotype of the alleles that they carry. However, estimates of direct effects can be subject to genetic and environmental confounding and can also absorb the "indirect" genetic effects of relatives' genotypes. Recently, an important development in controlling for these confounds has been the use of within-family GWASs, which, because of the randomness of mendelian segregation within pedigrees, are often interpreted as producing unbiased estimates of direct effects. Here, we present a general theoretical analysis of the influence of confounding in standard population-based and within-family GWASs. We show that, contrary to common interpretation, family-based estimates of direct effects can be biased by genetic confounding. In humans, such biases will often be small per-locus, but can be compounded when effect-size estimates are used in polygenic scores (PGSs). We illustrate the influence of genetic confounding on population- and family-based estimates of direct effects using models of assortative mating, population stratification, and stabilizing selection on GWAS traits. We further show how family-based estimates of indirect genetic effects, based on comparisons of parentally transmitted and untransmitted alleles, can suffer substantial genetic confounding. We conclude that, while family-based studies have placed GWAS estimation on a more rigorous footing, they carry subtle issues of interpretation that arise from confounding.

A Polygenic Score Predicts Caries Experience in Elderly Swedish Adults

Caries is a partially heritable disease, raising the possibility that a polygenic score (PS, a summary of an individual’s genetic propensity for disease) might be a useful tool for risk assessment. To date, PS for some diseases have shown clinical utility, although no PS for caries has been evaluated. The objective of the study was to test whether a PS for caries is associated with disease experience or increment in a cohort of Swedish adults. A genome-wide PS for caries was trained using the results of a published genome-wide association meta-analysis and constructed in an independent cohort of 15,460 Swedish adults. Electronic dental records from the Swedish Quality Registry for Caries and Periodontitis (SKaPa) were used to compute the decayed, missing, and filled tooth surfaces (DMFS) index and the number of remaining teeth. The performance of the PS was evaluated by testing the association between the PS and DMFS at a single dental examination, as well as between the PS and the rate of change in DMFS. Participants in the highest and lowest deciles of PS had a mean DMFS of 63.5 and 46.3, respectively. A regression analysis confirmed this association where a 1 standard deviation increase in PS was associated with approximately 4-unit higher DMFS (P < 2 × 10−16). Participants with the highest decile of PS also had greater change in DMFS during follow-up. Results were robust to sensitivity analysis, which adjusted for age, age squared, sex, and the first 20 genetic principal components. Mediation analysis suggested that tooth loss was a strong mediating factor in the association between PS and DMFS but also supported a direct genetic effect on caries. In this cohort, there are clinically meaningful differences in DMFS between participants with high and low PS for caries. The results highlight the potential role of genomic data in improving caries risk assessment.

Genetic parameter estimates indicate the possibility of genetic gain by selecting for reproductive traits of females from a commercial tilapia population (Oreochromis niloticus)

This study aimed to verify the possibility of obtaining genetic gain by selecting breeders based on genetic parameter estimates for reproductive performance traits of female tilapia (Oreochromis sp.) from a commercial population. The study was conducted using a database containing information on reproductive traits collected from 2009 to 2021. During the breeding period, the animals were stocked in tanks in a 1:3 male: female ratio. Eggs were collected from the mouth of the females every five days, and the collected eggs were measured in 100 mL beakers to estimate the egg volume. To estimate the variance components and genetic parameters (heritability, correlation, and repeatability), a mixed animal model was used with the fixed effects of the production cycle and breeding tanks, in addition to the additive direct genetic and permanent environmental random effects. The heritability values were 0.26 ± 0.14, 0.18 ± 0.10, 0.15 ± 0.09, and 0.13 ± 0.08 for total egg volume, average egg volume, spawning frequency, and average spawning interval, respectively, with repeatability above 0.43 for all analyzed variables, demonstrating the ability of the evaluated breeds to maintain the same production level during the different cycles. The genetic correlations among the variables were high, with a correlation of −0.99 between the total egg volume and the average spawning interval. Thus, selecting for total egg volume, which had the highest heritability, would result in animals that produce a large volume of eggs and have short spawning intervals.

Indirect genetic effects should make group size more evolvable than expected.

Group size is an important trait for many ecological and evolutionary processes. However, it is not a trait possessed by individuals but by social groups, and as many genomes contribute to group size understanding its genetic underpinnings and so predicting its evolution is a conceptual challenge. Here I suggest how group size can be modelled as a joint phenotype of multiple individuals, and so how models for evolution accounting for indirect genetic effects are essential for understanding the genetic variance of group size. This approach makes it clear that (a) group size should have a larger genetic variance than initially expected as indirect genetic effects always contribute exactly as much as direct genetic effects and (b) the response to selection of group size should be faster than expected based on direct genetic variance alone as the correlation between direct and indirect effects is always at the maximum positive limit of 1. Group size should therefore show relatively rapid evolved increases and decreases, the consequences of which and evidence for I discuss.

Evaluation of models for estimation of genetic parameters for post-weaning body measurements and their association with yearling weight in Nellore sheep.

The objective of this study was to obtain (co) variance components and genetic parameter estimates for post-weaning body measurements such as body length (BL), height at withers (HW), and chest girth (HG) recorded at six (SBL, SHW, and SHG), nine (NBL, NHW, and NHG) and twelve (YBL, YHW, and YHG) months of age along with yearling weight (YW) in Nellore sheep maintained at livestock research station, Palamaner, Andhra Pradesh, India and also the association among body measurements with YW was studied. Data on 2,076 Nellore sheep (descended from 75 sires and 522 dams) recorded between 2007 and 2016 (10 years) were utilized in the study. Lambing year, sex of lamb, season of lambing and parity of dam were included in the model as fixed effects and ewe weight was kept as a covariate. Analyses were conducted with six animal models with different combinations of direct and maternal genetic effects using restricted maximum likelihood procedure. Best model for each trait was determined based on Akaike's information criterion. Moderate estimates of direct heritability were obtained for the studied traits viz., BL (0.02 to 0.24), HW (0.31 to 0.49), and CG (0.08 to 0.35) and their corresponding maternal heritability estimates were in the range of 0.00 to 0.07 (BL), 0.13 to 0.17 (HW), and 0.07 to 0.13 (CG), respectively. Positive direct genetic and phenotypic correlations among the traits and they ranged from 0.07 (YBL-YW) to 0.99 (SBL-SHG, SHG-YW, and NBL-YBL) and 0.01 (SBL-YBL) to 0.99 (NBL-NHG), respectively. Further, the genetic correlations among all the body measurements and YW were positive and ranged from 0.07 (YW and YBL) to 0.99 (YW and SHG). There was a strong association of chest girth at six months with YW. Further, it is indicated that moderate improvement of post-weaning body measurements in Nellore sheep would be possible through selection.

Interpreting polygenic score effects in sibling analysis.

Researchers often claim that sibling analysis can be used to separate causal genetic effects from the assortment of biases that contaminate most downstream genetic studies (e.g. polygenic score predictors). Indeed, typical results from sibling analysis show large (>50%) attenuations in the associations between polygenic scores and phenotypes compared to non-sibling analysis, consistent with researchers' expectations about bias reduction. This paper explores these expectations by using family (quad) data and simulations that include indirect genetic effect processes and evaluates the ability of sibling analysis to uncover direct genetic effects of polygenic scores. We find that sibling analysis, in general, fail to uncover direct genetic effects; indeed, these models have both upward and downward biases that are difficult to sign in typical data. When genetic nurture effects exist, sibling analysis creates "measurement error" that attenuates associations between polygenic scores and phenotypes. As the correlation between direct and indirect effect changes, this bias can increase or decrease. Our findings suggest that interpreting results from sibling analysis aimed at uncovering direct genetic effects should be treated with caution.

Genetic Parameters for Limousine Interbeef Genetic Evaluation of Calving Traits.

The aim of this study was to estimate across-country genetic correlations for calving traits (birth weight, calving ease) in the Limousine breed. Correlations were estimated for eight populations (Czech Republic, joint population of Denmark, Finland, and Sweden, France, Great Britain, Ireland, Slovenia, Switzerland, and Estonia). An animal model on raw performance accounting for across-country interactions (AMACI) was used. (Co)variance components were estimated for pairwise combinations of countries. Fixed and random effects were defined by each country according to its national genetic evaluation system. The average across-country genetic correlation for the direct genetic effect was 0.85 for birth weight (0.69-0.96) and 0.75 for calving ease (0.62-0.94). The average correlation for the maternal genetic effect was 0.57 for birth weight and 0.61 for calving ease. After the estimation of genetic parameters, the weighted bending procedure was used to compute the full Interbeef genetic correlation matrix. After bending, direct genetic correlations ranged from 0.62 to 0.84 (with an average of 0.73) for birth weight and from 0.58 to 0.82 (with an average of 0.68) for calving ease.

Sex-specific genetic parameter estimates of body weight in Mazandaran indigenous chickens.

Body weight is an economically important trait in poultry that shows sexual dimorphism (SD). In the present study, variation in SD in Mazandaran native chickens was investigated in terms of the (Co) variance components and genetic parameters of body weight between males and females. Studied traits were body weights at hatch (BW1), 8 weeks (BW8) and 12 weeks of age (BW12). Also, for weight at sexual maturity (WSM) covariance components were only estimated in females. Cross-sex direct and maternal correlations were also estimated for studied traits except for WSM. For this purpose, a deep 21-generation pedigree and body weight data (57,576 BW1, 72,925 BW8, 62,727 BW12 and, 42,496 WSM) were used. Evaluation of SD of body weight was performed using six bivariate animal models with and without considering the genetic and permanent maternal environmental effects under the restricted maximum likelihood method in WOMBAT software. Model with direct additive genetic effects and maternal genetic effects without covariance between them was identified as the best model for BW1 and BW8. The Model including direct additive genetic effects and permanent maternal environmental effects was the best model for BW12 and WSM. Direct heritability (h2 ) estimates for BW1, BW8 and, BW12 were, respectively, 0.05 ± 0.013, 0.17 ± 0.02 and, 0.25 ± 0.03 in males and, 0.05 ± 0.012, 0.15 ± 0.01 and 0.21 ± 0.01 in females. Also, the direct heritability of WSM based on univariate analysis in females was estimated to be 0.40 ± 0.01. Maternal heritability ( ) varied from 0.39 ± 0.01 (BW1) to 0.04 ± 0.009 (BW8) in males, and 0.36 ± 0.10 (BW1) to 0.04 ± 0.006 (BW8) in females. The correlation between direct genetic effects between males and females for BW1 was not significantly different from one. The direct genetic correlation between the two sexes for BW8 and BW12 was significantly different from 1 concluding that these traits are dimorphic in terms of direct genetic effects and therefore independent selection in both sexes is possible.

Estimation of genetic parameters for growth traits and kleiber ratio in dorper sheep breed

The study aimed to estimate genetic and phenotypic parameters for growth traits and Kleiber ratio in Dorper sheep breed. Data used in this study were collected over 12 years (2012–2023) at Debre Birhan Agricultural Research Center sheep research station in Ethiopia. Studied traits were body weights at birth (WT0), weaning (WT3), six month (WT6), and yearling (WT12) age; average daily gains from birth to weaning (ADG0-3), from weaning to six months (ADG3-6), from six months to yearling (ADG6-12); and Kleiber ratios from birth to weaning (KR1) and from weaning to six months (KR2). The (co)variance components were estimated with different animal models using Average Information Restricted Maximum Likelihood (AI-REML) procedure. The best-fitted model for each trait was determined using likelihood ratio tests. Phenotypic performance for WT3, WT6, WT12, ADG0-3 and ADG3-6 showed a decline trend at a rate of 0.216 kg, 0.794 kg, 0.671 kg, 2.601 g and 4.865 g over years respectively. However, WT3, WT6, WT12, ADG0-3 showed a positive genetic improvement trend at a rate of 0.029 kg, 0.043 kg, 0.049 kg and 0.257 g over years respectively. Year of birth had a significant effect (P < 0.001) on all studied traits. Model including direct genetic as well as permanent environmental effect (Model 2) was chosen as the most appropriate model for WT0. Model which included only direct genetic effect (Model 1) was the best-fit model for all other studied traits. Direct heritability estimates based on suitable models were 0.07 ± 0.06, 0.11 ± 0.06, 0.09 ± 0.07, 0.11 ± 0.09 0.11 ± 0.06, 0.00 ± 0.04, 0.15 ± 0.07 and 0.00 ± 0.04 for WT0, WT3, WT6, WT12, ADG0-3, ADG3-6, KR1 and KR2 respectively. The variance ratio for the permanent environmental effect was 0.13 ± 0.04 for WT0. Genetic correlations among the traits ranged from negative (−0.39) for WT0-KR1 to high (0.99) for WT3-ADG0-3 and phenotypic correlations ranged from negative (−0.31) for WT0-KR1 to high (0.98) for WT3-ADG0-3. The low direct heritability estimates for the studied traits indicated that genetic improvement by direct selection might be difficult. Further investigation for the unexpected declined trend of phenotypic performance over years need to be required.

Delineating maternal influence in regulation of variance in major economic traits of White Leghorns: Bayesian insights.

Proper variance partitioning and estimation of genetic parameters at appropriate time interval is crucial for understanding the dynamics of trait variance and genetic correlations and for deciding the future breeding strategy of the population. This study was conducted on the same premise to estimate genetic parameters of major economic traits in a White Leghorn strain IWH using Bayesian approach and to identify the role of maternal effects in the regulation of trait variance. Three different models incorporating the direct additive effect (Model 1), direct additive and maternal genetic effect (Model 2) and direct additive, maternal genetic and maternal permanent environmental effects (Model 3) were tried to estimate the genetic parameters for body weight traits (birth weight, body weight at 16, 20, 40 and 52 weeks), Age at sexual maturity (ASM), egg production traits (egg production up to 24, 28, 40, 52, 64 and 72 weeks) and egg weight traits (egg weight at 28, 40 and 52 weeks). Model 2 and Model 3 with maternal effects were found to be the best having the highest accuracy for almost all the traits. The direct additive genetic heritability was moderate for ASM, moderate to high for body weight traits and egg weight traits and low to moderate for egg production traits. Though the maternal heritability (h2mat) and permanent environmental effect (c2mpe) was low (<0.1) for most of the traits, they formed an important component of trait variance. Traits like egg weight at 28 weeks (0.14±0.06) and egg production at 72 weeks (0.13±0.07) reported comparatively higher values for c2mpe and h2mat respectively. Additive genetic correlation was high and positive between body weight traits, between egg weight traits, between consecutive egg production traits and between body weight and egg weight traits. However, a negative genetic correlation existed between egg production and egg weight traits, egg production and body weight traits, ASM and early egg production traits. Overall, a moderate positive genetic correlation was estimated between ASM and body weight traits and ASM and egg weight traits. Based on our findings, we can deduce that maternal effects constitute an important source of variation for all the major economic traits in White Leghorn and should be necessarily considered in genetic evaluation programs.

Host and rumen microbiome contributions to feed efficiency traits in Holstein cows

It is now widely accepted that dairy cow performance is influenced by both the host genome and rumen microbiome composition. The contributions of the genome and the microbiome to the phenotypes of interest are quantified by heritability (h2) and microbiability (m2), respectively. However, if the genome and microbiome are included in the model, then the h2 reflects only the contribution of the direct genetic effects quantified as direct heritability (hd2), and the holobiont effect reflects the joint action of the genome and the microbiome, quantified as the holobiability (ho2). The objectives of this study were to estimate h2, hd2,m2, and ho2 for dry matter intake, milk energy, and residual feed intake; and to evaluate the predictive ability of different models, including genome, microbiome, and their interaction. Data consisted of feed efficiency records, SNP genotype data, and 16S rRNA rumen microbial abundances from 448 mid-lactation Holstein cows from 2 research farms. Three kernel models were fit to each trait: one with only the genomic effect (model G), one with the genomic and microbiome effects (model GM), and one with the genomic, microbiome, and interaction effects (model GMO). The model GMO, or holobiont model, showed the best goodness-of-fit. The hd2 estimates were always 10% to 15% lower than h2 estimates for all traits, suggesting a mediated genetic effect through the rumen microbiome, and m2 estimates were moderate for all traits, and up to 26% for milk energy. The ho2 was greater than the sum of hd2 and m2, suggesting that the genome-by-microbiome interaction had a sizable effect on feed efficiency. Kernel models fitting the rumen microbiome (i.e., models GM and GMO) showed larger predictive correlations and smaller prediction bias than the model G. These findings reveal a moderate contribution of the rumen microbiome to feed efficiency traits in lactating Holstein cows and strongly suggest that the rumen microbiome mediates part of the host genetic effect.

Genetic correlations of direct and indirect genetic components of social dominance with fitness and morphology traits in cattle

BackgroundWithin the same species, individuals show marked variation in their social dominance. Studies on a handful of populations have indicated heritable genetic variation for this trait, which is determined by both the genetic background of the individual (direct genetic effect) and of its opponent (indirect genetic effect). However, the evolutionary consequences of selection for this trait are largely speculative, as it is not a usual target of selection in livestock populations. Moreover, studying social dominance presents the challenge of working with a phenotype with a mean value that cannot change in the population, as for every winner of an agonistic interaction there will necessarily be a loser. Thus, to investigate what could be the evolutionary response to selection for social dominance, it is necessary to focus on traits that might be correlated with it. This study investigated the genetic correlations of social dominance, both direct and indirect, with several morphology and fitness traits. We used a dataset of agonistic contests involving cattle (Bos taurus): during these contests, pairs of cows compete in ritualized interactions to assess social dominance. The outcomes of 37,996 dominance interactions performed by 8789 cows over 20 years were combined with individual data for fertility, mammary health, milk yield and morphology and analysed using bivariate animal models including indirect genetic effects.ResultsWe found that winning agonistic interactions has a positive genetic correlation with more developed frontal muscle mass, lower fertility, and poorer udder health. We also discovered that the trends of changes in the estimated breeding values of social dominance, udder health and more developed muscle mass were consistent with selection for social dominance in the population.ConclusionsWe present evidence that social dominance is genetically correlated with fitness traits, as well as empirical evidence of the possible evolutionary trade-offs between these traits. We show that it is feasible to estimate genetic correlations involving dyadic social traits.

Influence of birth weight on later life cardiovascular structure, function and disease: unpacking influences from direct genetic effects versus intrauterine programming

Abstract Aims The cardinal risk factors for cardiovascular disease in adulthood are well-recognised. In addition to these, observational studies have suggested that intrauterine and early developmental factors might play a role. However, observational associations are liable to influence by residual confounding and bias. Additionally, observational and genetic studies to date have not been able to isolate the fetal versus maternal influences. Purpose We aim to explore the causal relevance of birth weight on cardiovascular disease and cardiac structure and function using Mendelian randomization (MR), and specifically investigate the role of fetal genetic effects (reflecting the direct causal influence of birth weight) versus maternal genetic effects (reflecting the influence of the intrauterine environment). Methods Uncorrelated (r2&amp;lt;0.001), genome-wide significant (p&amp;lt;5x10-8) SNPs were extracted from genome-wide association study summary statistics for gestational age-adjusted birth weight overall, and after isolating the indirect maternal versus direct fetal genetic effects. Inverse-variance weighted Mendelian randomisation (MR) was utilised for primary analyses on outcomes of atrial fibrillation, coronary artery disease, heart failure, ischaemic stroke, and 15 measures of cardiac structure and function indexed to body surface area. Multivariable MR was utilised to explore potential mediation of effects observed on cardiovascular outcomes by cardiometabolic risk factors. P-values were FDR-adjusted to account for multiple testing. Results Higher genetically-predicted birth weight was associated with higher risk of atrial fibrillation (OR 1.26 [1.15-1.39], p&amp;lt;0.001), but lower risk of coronary artery disease (OR 0/78 [0.71-0.86] p&amp;lt;0.001). These associations were driven predominantly by direct fetal genetic effects. For the association with atrial fibrillation, there was no evidence of mediation through body mass index or height. For the association with coronary artery disease, there was at least partial mediation through systolic blood pressure (Figure 1). Higher genetically-predicted birth weight was associated with a greater chamber volumes, but lower ejection fraction (Figure 2), driven by direct fetal genetic effects. Conclusion The results of this study suggest that lower birthweight is associated with higher risk of coronary artery disease, partly mediated by a higher systolic blood pressure. Conversely, a greater birth weight was associated with higher risk of atrial fibrillation, and this was not mediated by body mass index or height. Higher birth weight was also associated with greater chamber volumes and lower ejection fraction. The associations were in all cases predominantly driven by direct fetal effects, suggesting a causal relevance of birth weight itself, and not of the intrauterine environment, on later life cardiovascular disease.Figure 1Figure 2

133 Genetic Parameter Estimation for Dry Matter Required in Angus Cattle

Abstract Dry matter intake (DMI) is critical to determine feed efficiency in cattle. However, this trait is expensive and difficult to measure on an individual basis. An alternative to overcome such limitations is to approximate DMI by using mathematical models to estimate the dry matter required (DMR) for animals originally fed in groups. High genetic correlations (e.g., rg&amp;gt;0.95) have been informed between DMI and DMR. Thus, DMR has been proposed as an indicator trait for DMI in genetic evaluations. Few reports exist about genetic parameters associated to DMR and, when available, estimates have been obtained with datasets of limited size (~1,500 animals with phenotypes). Additionally, previous reports have focused on older animals during the finishing phase, such that mathematical models employed to derive DMR have not explicitly accounted for the presence of weaner calves on the data. Therefore, the objective was to estimate genetic parameters for DMR using a moderately large dataset that included weaning and yearling Angus bulls. A total of 8,121 records of estimated DMR were available for analyses. From these records, 6,324 belonged to weaned males whose phenotype was obtained using an equation proposed by NRC to predict DMR for calves. The 1,797 remaining records pertained to yearling bulls for which a different NRC equation was employed. First, a single-trait animal model was implemented to estimate genetic parameters for DMR, with contemporary group (defined as year of test and pen within the testing facility), test length and age of the animal when entering to the test (linear covariate) being included as fixed effects, while animal was considered a random effect. Afterwards, a bivariate model that included weaning weight (WW) as a correlated trait was implemented. In this model, the same effects were included for DMR but for WW, fixed effects included sex, weaning contemporary group and age of dam (BIF classes), while direct genetic, maternal genetic, and maternal permanent environmental effects were considered as random. For both models, a reduced pedigree was used to estimate variance components by tracing back 5 generations from animals having phenotypes. A total of 12,212 and 56,023 animals were included in the univariate analysis and the bivariate analysis, respectively. Heritability (h2) estimates (± SE) for DMR were 0.43 (± 0.04) and 0.49 (± 0.03) under univariate and bivariate model, respectively. Genetic correlation between DMR and WW was 0.69 (± 0.03), with a h2 estimate of 0.29 (± 0.01) for WW. Heritability estimates for DMR obtained with both models resembled those of DMR reported in literature. Results suggested that substantial additive genetic variation exists for DMR and, consequently, indirect genetic progress for DMI can be attained if selecting for DMR. Further studies are required to validate DMR as an indicator trait for DMI in larger Angus populations.