Maternal Genetic Effects Research Articles

Bayesian Evaluation of Growth Rates and Kleiber's Ratios in Harnali Sheep: Dissecting Maternal and Additive Genetic Contributions.

Understanding the genetic basis of growth and metabolic traits in sheep is crucial for improving production efficiency and sustainability. The current study aimed to estimate the genetic influences, both direct and maternal, on growth rate and Kleiber's ratio traits in Harnali sheep using pedigree data under Bayesian inference. The data pertained to 2404 animals spanned over 24 years (1998-2021). Fixed factors such as birth period, lamb sex and dam's weight at lambing were considered. The traits studied included average daily gains (ADGs) categorised into ADG1 (birth to weaning age), ADG2 (weaning to 6 months of age) and ADG3 (6-12 months of age), as well as corresponding Kleiber's ratios (KR1, KR2 and KR3). Six single-trait animal models were employed to estimate covariance components and heritabilities, integrating direct additive and maternal effects alongside significant fixed factors using THRGIBBS1F90 and POSTGIBBSF90 programmes. Direct heritability estimates were obtained for ADG1 (0.11 ± 0.05), ADG2 (0.06 ± 0.03), ADG3 (0.03 ± 0.03), KR1 (0.07 ± 0.03), KR2 (0.06 ± 0.03) and KR3 (0.05 ± 0.03). Maternal genetic effects have contributed significant particularly to pre-weaning traits. The study identified an antagonistic relationship between direct additive and maternal genetic effects. Positive genetic and phenotypic correlations emphasised the intricate relationship between growth and metabolic efficiency in Harnali sheep. The current study offers critical insights into the genetic basis of growth and metabolic traits in Harnali sheep, ultimately contributing to more efficient and sustainable sheep production systems.

Effects of the Prenatal Maternal Health Status on Calf Disease Prevalences and Respective Genetic Parameter Estimates in German Holstein Cattle.

The aim of the present study was to infer phenotypic responses and genetic parameters of the F1 calf diseases diarrhoea (DIAR) and pneumonia (PNEU) in dependency of the prenatal maternal health status (PMHS) of the dam and of the herd-calving year. The PMHS considered diagnoses for the cow disease mastitis (MAST) and claw disorders (CD) during gestation of F0 dams. Furthermore, 305-d milk production traits of F1 offspring from either healthy or diseased dam groups were compared. The study comprised 20,045 female calves (F1 = generation 1) and their corresponding dams (F0 = parental generation 0), kept in 41 large-scale herds. All F1 calves were from their dams' 2nd parity, implying that all dam (maternal) diseases were recorded during the first lactation and dry period of the dams. The F1 calves were phenotyped for DIAR up to 30 days post-partum, and for PNEU up to 180 days of age. At least one entry for the respective disease implied a score = 1 = sick, otherwise, a score = 0 = healthy, was assigned. Production records of the 10,129 F1 cows comprised 305-d records in first lactation for milk yield (MY), protein yield (PY) and fat yield (FY). Linear and generalised linear mixed models were applied to infer phenotypic responses of F1 traits in dependency of the PMHS for CD and MAST. A diagnosis for MAST or CD in F0 cows during gestation was significantly (p ≤ 0.05) associated with an increased prevalence for DIAR and PNEU, with pairwise differences of least-squares-means between calves from healthy and diseased cow groups up to 3.61%. The effects of PMHS on 305-d production traits in offspring were non-significant (p > 0.05). In bivariate genetic analyses, DIAR and PNEU were defined as different traits according to the PMHS, i.e., DIAR-MASThealthy and DIAR-MASTdiseased, DIAR-CDhealthy and DIAR-CDdiseased, PNEU-MASThealthy and PNEU-MASTdiseased, and PNEU-CDhealthy and PNEU-CDdiseased. The direct heritabilities for DIAR and PNEU were quite similar in the healthy and respective diseased dam group. Slightly larger direct heritabilities in the diseased dam groups were due to increased genetic variances. Maternal heritabilities were quite stable and smaller than the direct heritabilities. In random regression models, genetic parameters for DIAR and PNEU were estimated along the continuous herd-calving-year prevalence scale, considering a prevalence for MAST and CD (based on the 20,045 dam records plus 16,193 herd contemporary records) in the range from 0% to 30%. Direct heritabilities for PNEU were quite stable along the herd-calving-year gradient for MAST and CD. For DIAR, we observed stronger estimate fluctuations, especially increasing direct heritabilities in dependency of the herd-calving-year prevalence for MAST from 0.13 (at a MAST prevalence of 0%) to 0.30 (at a MAST prevalence of 30%). Consequently, obvious genotype x herd-calving-year PMHS interactions were observed for DIAR on the prenatal MAST scale, with a minimal correlation of 0.48 between direct genetic effects at 0% MAST prevalence and at 30% MAST prevalence. The correlations between direct genetic and maternal genetic effects were antagonistic at all herd-calving-year prevalence levels, displaying strongest fluctuations for "DIAR-MAST." The genotype x herd-calving-year PMHS interactions for DIAR suggest consideration of specific sires according to the herd health status for CD and for MAST.

Estimates of genetic parameters and genetic trends for growth traits in Menz sheep under community-based breeding programs

The main objectives of this study were to estimate genetic and phenotypic parameters for growth traits in Menz sheep under community-based breeding programs (CBBPs). Data used in the study were collected from five Menz CBBPs villages during 15-year period (2009–2023). Studied growth traits were birth weight (BW), weaning weight (WW), six-month weight (6 MW), yearling weight (YW), Average daily gain from birth to weaning (ADG1), average daily gain from weaning to six months (ADG2) and average daily gain from six months to yearling (ADG3). Fixed effects were estimated using the GLM procedure of SAS 9.4. Genetic parameters were estimated fitting different univariate animal models using Average Information Restricted Maximum Likelihood (AI-REML) procedure with WOMBAT software. The most appropriate model for each trait was determined applying likelihood ratio tests. Model including only direct additive genetic effect was the most appropriate model for BW, YW, ADG2 and ADG3, whereas model including direct additive and maternal additive genetic effect without taking into account covariance between them was the most appropriate for WW, 6 MW and ADG1. Based on the most appropriate models, direct heritability of BW, WW, 6 MW, YW, ADG1, ADG2 and ADG3 were 0.29 ± 0.01, 0.45 ± 0.01, 0.46 ± 0.02, 0.42 ± 0.02, 0.44 ± 0.01, 0.75 ± 0.02 and 0.21 ± 0.02, respectively. The estimated maternal heritability were 0.04 ± 0.01, 0.02 ± 0.01 and 0.02 ± 0.01 for WW, 6 MW and ADG1, respectively. Additive coefficient of variance were ranged from 9.53 % for BW to 33.02 % for ADG2. Moderate to higher estimates of direct heritability and additive coefficient of variation (CVA) in the current study indicates higher potential for genetic improvement of studied traits through direct selection. The genetic trend for the Menz sheep's six-month weight in Molale CBBPs village reveals a promising annual growth rate of 0.20 kg. Optimizing the ongoing breeding program into specializing-sire producer groups and applying intensive selection on the sub-nucleus flock could improve the efficiency of the breeding program. Genetic correlations among the studied traits were ranged from −0.50 for ADG-ADG2 to 0.98 for WW-ADG1. Genetic correlation between 6 MW and other studied traits was positive and moderate in magnitude. To achieve optimum genetic gain, the implemented selection criteria for Menz sheep (6 MW) should be continued.

Influence of additive and maternal effects on growth traits in Deccani sheep through Bayesian inference

The aim of this study was to estimate genetic parameters for growth traits in Deccani sheep using Bayesian inference. A dataset comprising pedigree information and growth trait records from 2590 Deccani animals, born to 127 sires and 836 dams between 2011 and 2020, was analyzed. The growth traits considered included birth weight (BWT), weaning weight (WWT), and weights at six (SWT), nine (NWT), and twelve (YWT) months of age. Genetic evaluation employed six univariate animal models incorporating direct and maternal effects, implemented through THRGIBBS1F90 and POSTGIBBSF90 programs. Fixed factors adjusted in the analysis included year of birth, sex of lamb, season of lambing, and dam’s age and weight at lambing. Bayesian estimates of direct heritability, under the best model, revealed values of 0.14±0.05, 0.13±0.01, 0.20±0.04, 0.15±0.06, and 0.18±0.05 for BWT, WWT, SWT, NWT, and YWT traits, respectively. Corresponding maternal heritability estimates were 0.07±0.02, 0.08±0.01, 0.02±0.01, 0.10±0.02, and 0.17±0.06. Negative genetic correlations between additive and maternal genetic effects ranged from -0.14 to 0.07, while maternal permanent environmental influences were negligible. Positive and moderate to high genetic correlations among growth traits suggest potential relationships between them. These findings suggested selection based on WWT because it measured early in life, and has high correlation with other body weight especially SWT trait.

Evaluating animal models comprising additive genetic and maternal effects on growth traits in German Angora rabbit

This investigation was carried out to estimate the genetic parameters for German Angora rabbits using most appropriate animal model comprising additive and maternal effects. The pedigree information and data on growth traits were collected from 5221 rabbits, which descended from 699 does and 294 bucks over a period of 21 yr (2001–2021) kept at Northern Temperate Regional Station, Garsa, Kullu (Himachal Pradesh), India. The average daily gain (ADG) and Kleiber ratio (KR) were calculated at different age intervals. Analyses were carried out by restricted maximum likelihood procedure fitting six animal models with various combinations of direct and maternal effects. The best model was evaluated on the basis of a likelihood ratio test. Analysis revealed that the model including both direct and maternal genetic effects along with permanent effect of the dam was most suitable for all traits except for body weight (BW) at 6th wk of age, ADG from 6th to 12th wk of age and KR associated to ADG from 12th to 18th wk of age. The direct heritability estimates from the best model were ranged from, 0.34±0.05 to 0.49±0.05 for BW; 0.19±0.04, to 0.46±0.06 for ADG and 0.21±0.04 to 0.41±0.05 for KR, respectively. Direct heritability estimates were overestimated when maternal effects were ignored. Maternal effects on BW declined from 0.49±0.04 at weaning to 0.06±0.03 at 12th wk of age and 0.09±0.04 at 18th wk of age. Correlations between direct and maternal effects ranged from −0.44±0.15 to−0.52±0.14 for body weights, indicating biological antagonism between these effects. Genetic correlations among various growth traits were positive and high, indicating scope for correlated response in later expressed traits. Analysis revealed that maternal additive influences were only important until weaning, whereas permanent environmental maternal influences were present in all growth traits considered in this study. The moderate estimates of heritability for growth traits and Kleiber ratio of rabbit in this study indicate that rates of genetic progress may be possible for these traits by selection under the standard management system.

Estimating genetic parameters and trends in growth curve traits of Zandi sheep using the SAEM algorithm.

The objectives of this study were to evaluate the influence of environmental effects on growth curve traits of Zandi lambs and estimate their genetic parameters with the best-fit animal model. For this purpose, live body weight (BW) records (n = 10,607) of 2,519 individuals (which were progeny of 278 rams and 1,485 ewes) were used to estimate genetic effects on growth curve traits from birth to yearling age of Zandi lambs. Using the Stochastic Approximation Expectation Maximization (SAEM) algorithm the growth curve parameters of five different mixed functions (i.e., Brody, Richards, Von Bertalanffy, Gompertz and Logistic) were obtained, then for the most appropriate model the genetic parameters were estimated using a Bayesian approach fitted multivariate animal model and ignoring or including maternal genetic effect. Except Richards model, all other mixed functions used here closely fitted actual BW records (R2 > 0.96). However, the Logistic function provided the best fit in every type. So, studied growth curve traits were estimated asymptotic weight which considered as mature weight (a), rate parameter (b), rate of maturing (k), and age (Ai)/weight (Wi) at the point of inflection. Of the fixed effects studied (i.e., gender, birth type, dam age, season and year of birth), the only non-significant relationship was the effect dam age on b and Ai. Based on the best-fitted model, posterior means of heritability estimates for a, b, k, Wi and Ai were 0.142 ± 0.036, 0.094 ± 0.029, 0.143 ± 0.063, 0.149 ± 0.039 and 0.029 ± 0.013, respectively. Posterior means of genetic correlations between mentioned traits ranged from -0.018 ± 0.069 (b-k) to 0.959 ± 0.029 (a-b), whereas the phenotypic correlation varied from -0.047 ± 0.014 (b-k) to 0.836 ± 0.007 (a-b). It was concluded that the model including only direct additive effect was sufficient to explain the variation in all investigated growth traits of Zandi lambs, selection for these traits results in slow genetic gain (due to the lack of sufficient genetic variation), but it would not be difficult to improve their mature weight and rate of maturing jointly. The results indicate that although the rate of genetic change for mature weight has been small (0.008 ± 0.003 kgyear-1; P < 0.05) but in the favorable direction for this breed.

Modeling embryo survival: Genetic and environmental influences on eye-up rate in a north American Atlantic salmon selective breeding program

Selective breeding programs improve target traits but can also unintentionally change genetically correlated traits in the selected strain. The U.S. Department of Agriculture–Agricultural Research Service National Cold Water Marine Aquaculture Center (NCWMAC) in Franklin, Maine maintains a North American Atlantic salmon selective breeding program focused on improving commercially important traits (e.g., carcass weight). However, the program has experienced a significant decline in the percent of eyed embryos over its 14 years of operation, leading to concerns that reproductive performance was being unintentionally changed by selection for the target traits. The aims of this study were to 1) model eye up success as a potentially heritable trait utilizing the recorded pedigree and 2) assess the relationship between eye-up rate and environmental conditions experienced by the broodstock. Over 14 years of data encompassing 1537 full-sib families produced by 1537 dams and 885 sires was analyzed. Counts of eyed embryos and carcass weight were analyzed with a linear multi-trait trait model that included maternal genetic effects and a spawn year effect to determine the strength of genetic and environmental influences on the eyed embryo rate. To investigate the environmental influences in more detail, we assessed the correlation between water quality parameters in the broodstock rearing system observed over the same 14-year time period and the estimated spawn year effects. There was small heritability of the direct genetic effect (0.059 ± 0.009) and the maternal genetic effect (0.039 ± 0.013). Comparatively, the proportion of phenotypic variance explained by the maternal environmental effect was moderate (0.165 ± 0.012). The genetic correlations between carcass weight and eye up rate were very small and had a large amount of uncertainty. The correlation between the direct genetic effects on eye-up and carcass weight was −0.0528 ± 0.1469 while the correlation between the maternal genetic effect on eye-up and the direct genetic effect on carcass weight was 0.2030 ± 0.1791. The correlation between maternal common environmental effects on the two traits was also low at 0.0676 ± −0.0804. The effect of spawn year was statistically significant (p < 0.01), and the values were negatively correlated with mean un-ionized ammonia (mg/L, −0.56, p = 0.04,), nitrate concentrations (mg/L r = −0.65, p = 0.01) and temperature (°C, r = −0.61, p = 0.02) experienced by the broodstock prior to spawning. Overall, the results suggest that the decrease in eyed embryos over time was not caused by inadvertent selection but instead due to increases in water temperature and/or nitrogenous waste concentrations in the broodstock rearing system. Further investigation of the mechanisms behind these apparent environmentally induced declines and potential mitigation measures to prevent decreases in eye-up rates are needed.

Estimation of Genetic Parameters of Early Growth Traits in Dumeng Sheep.

This study aimed to estimate the genetic and non-genetic factors that affect the nine early growth traits of Dumeng sheep, as well as to estimate the variance components and genetic parameters associated with these traits. A dataset containing detailed information on 17,896 preweaning trait records of 4474 lambs was collected. In addition, 5015 postweaning trait records of 1003 lambs were documented. The effects of recipient dam age, sex, year, season, and herd on the early growth traits were assessed using the general linear model procedure of the statistical analysis system, revealing different levels of significance across different traits. To determine the most suitable model for estimating the genetic parameters, the likelihood ratio (LR) test was employed, fitting six animal models that either excluded or included maternal genetic and maternal permanent environmental effects within the average information restricted maximum likelihood (AIREML) framework using WOMBAT software (Version: 23/11/23). The model incorporating direct additive genetic effects, maternal genetic effects, and maternal permanent environment effects as random effects (model 6) provided the best fit for birth weight (BW) estimation. In contrast, the model combining direct additive genetic effects and maternal permanent environment effects as random effects (model 2) demonstrated a superior fit for estimating the genetic parameters of weaning weight (WW), average daily gain weight from birth to weaning (ADG1), and Kleiber ratio from birth to weaning (KR1). With regard to the genetic parameters of body weight at 6 months of age (6MW), average daily gain weight from weaning to 6 months (ADG2), average daily gain weight from birth to 6 months (ADG3), Kleiber ratio from weaning to 6 months (KR2), and Kleiber ratio from birth to 6 months (KR3), model 1, which incorporates only direct additive genetic effects, was identified as the optimal choice. With the optimal model, the heritability estimates ranged from 0.010 ± 0.033 for 6MW to 0.1837 ± 0.096 for KR3. The bivariate analysis method was employed to estimate the correlation between various traits using the most suitable model. The absolute values of genetic correlation coefficients among the traits spanned a range from 0.1460 to 0.9998, highlighting both weak and strong relationships among the studied traits. Specifically, the estimated genetic correlations between WW and ADG1, ADG3, KR1, and KR3 were 0.9859, 0.9953, 0.9911, and 0.9951, respectively, while the corresponding phenotypic correlations were 0.9752, 0.7836, 0.8262, and 0.5767. These findings identified that WW could serve as an effective selection criterion for enhancing early growth traits.

ASReml-based estimation of early genetic parameters in hybrid mutton sheep populations

The aim of this study was to analyze the effects of non-genetic factors on the estimation of genetic parameters of early growth traits in hybrid mutton sheep using ASReml software, in order to provide theoretical basis for screening the optimal hybriding combinations and accelerating the breeding process of new breeds of specialized housed-feeding mutton sheep. We selected the wellgrown hybrid Southhu (Southdown × Hu sheep) and Dorhu (Dorset × Hu sheep) sheep as the research objects, constructed weight correction formulae for SH and DH sheep at 60 and 180 days; and used ASReml software to investigate the effects of non-genetic factors on the estimation of genetic parameters of early growth traits in hybrid sheep. The results showed that the birth month and birth type were found significant for all traits (p < 0.001); the heritability of maternal effects ranged from 0.0709 to 0.1859. It was found that both SH and DH sheep emerged the potential for rapid early growth and development, early growth traits are significantly affected by maternal genetic effects, thereby the maternal effect should be taken into consideration for the purpose of improving accuracy in parameter estimations and therefore increasing the success of breeding programs.

Reviewing the definition of mortality in broiler chickens and its implications in genomic evaluations.

Mortality is an economically important trait usually handled as a discrete outcome from hatch time until selection in most broiler breeder programs. However, in other species, it has been shown that not only does the genetic component change over time, but also there are maternal genetic effects to be considered when mortality is recorded early in life. This study aimed to investigate alternative trait definitions of mortality with varying models and effects. Three years' worth of data were provided by Cobb-Vantress, Inc. and included 2 mortality traits. The first trait was binary, whether the bird died or not (OM), and the second trait was a categorical weekly mortality trait. After data cleaning, 6wk of data for the 2 given mortality traits were used to develop 5 additional trait definitions. The definitions were broiler mortality (BM), early and late mortality (EM & LM), and 2 traits with repeated records as cumulative or binary (CM and RM, respectively). Variance components were estimated using linear and threshold models to investigate whether either model had a benefit. Genomic breeding values were predicted using the BLUP90 software suite, and linear regression validation (LR) was used to compare trait definitions and models. Heritability estimates ranged from 0.01 (0.00) to 0.16 (0.01) under linear and 0.04 (0.01) to 0.21 (0.01) under threshold models, indicating genetic variability within the population across these trait definitions. The genetic correlation between EM and LM ranged from 0.48 to 0.81 across the different lines, indicating they have divergent genetic backgrounds and should be considered different traits. The LR accuracies showed that EM and LM used together in a 2-trait model have comparable accuracies to that of OM while giving a more precise picture of mortality. When including the maternal effect, the direct heritability considerably decreased for EM, indicating that the maternal effect plays an important role in early mortality. Therefore, a suitable approach would be a model with EM and LM while considering the maternal effect for EM. Single nucleotide polymorphism effects were estimated, and no individual SNP explained more than 1% of the additive genetic variance. Additionally, the SNP with the largest effect size and variance were inconsistent across trait definitions. Chicken mortality can be defined in different ways, and reviewing these definitions and models may benefit poultry breeding programs.

Genetic parameter estimates for growth traits in Texel sheep of Brazil

The present study aimed to estimate the genetic parameters for direct and maternal influences on birth weight (BW), weaning weight (WW) and postweaning weight (PW) of Texel sheep, raised in an extensive system from Brazil. Data file used in this study consisted of 834 body weight records of 834 Texel lambs (376 males and 458 females) born from 2020 to 2021, offspring of 475 ewes and 45 rams. Multivariate animal model was conducted to estimate the variance components, heritability and genetic correlations using the restricted maximum likelihood method in ASReml-R software, while the effects of fixed factors were analyzed by the general linear model procedure of statistical analysis system. Five different animal models, with or without maternal genetic effect, maternal permanent environment effect and covariance between additive genetic and maternal genetic effects, were fitted on the growth traits data of the Texel sheep population. AIC and BIC test results were used to evaluate the best fit models for growth traits. The effect of lamb's sex was significant on BW, WW and PW while birth type and year of lambing effects were on all traits (P < 0.05). Model 4, incorporating direct additive genetic, maternal additive genetic and maternal permanent environmental effects showed the minimum AIC estimate for all growth traits. The direct additive genetic heritability for BW, WW and PW were 0.11 ± 0.03, 0.37 ± 0.05 and 0.31 ± 0.08, respectively and maternal heritability for these traits were 0.00 ± 0.00, 0.04 ± 0.02 and 0.00 ± 0.00, respectively. The total heritability estimates for BW, WW and PW were 0.11 ± 0.03, 0.39 ± 0.05 and 0.31 ± 0.08, respectively. The estimates of the direct additive genetic correlation between BW-WW, BW-PW and WW-PW were 0.68 ± 0.12, 0.66 ± 0.12 and 0.78 ± 0.07, respectively. The maternal permanent environmental correlation between BW-WW, BW-PW and WW-PW were 0.38 ± 0.27, 0.29 ± 0.20 and 0.74 ± 0.16, respectively. Phenotypic correlation ranged from 0.43 ± 0.03 to 0.75 ± 0.02. It is concluded that due to the existence of genetic variation for BB, WW and PW and strong genetic correlation among them, genetic progress for these traits is possible by selection in Texel sheep from Brazil.

Genetic analysis of efficiency-related traits in Boer x Central Highland goats.

This study aimed to identify important non-genetic factors and estimate genetic parameters for efficiency-related traits in Boer x Central Highland goats. The genetic parameters were estimated using the Average Information Restricted Maximum Likelihood algorithm using the WOMBAT program fitting animal model. The least-squares means for growth efficiency from birth to 3 months (GE1), 3-6 months (GE2), 6-12 months (GE3), relative growth rate from birth to 3 months (RGR1), 3-6 months (RGR2) and 6-12 month (RGR3) were 294.0 ± 5.06, 36.6 ± 1.20, 44.9 ± 1.81, 1.46 ± 0.01, 0.32 ± 0.01 and 0.19 ± 0.01, respectively. Birth type, blood level, sex of the kid, and year of kidding had a sizable effect on efficiency-related traits. About 18, 3.0, 23, 20, and 12% of the phenotypic variation in GE2, GE3, RGR1, RGR2, and RGR3 was explained by the direct additive genetic effect. Except for RGR3, all investigated traits were under the influence of maternal genetic effect, and maternal heritability ranged from 0.09 to 0.17. The total heritability estimate depicts that slow genetic progress would be expected from selection. Nevertheless, even with this level of heritability, selection for efficiency-related traits would improve the efficiency of chevon production as these traits are economically important traits. Nearly six-months of age was when farmers sold Boer crossbred goats. Therefore, improving the growth efficiency till the marketing age (GE2) in such a scenario could increase the production efficiency.

Folate Metabolism and Risk of Childhood Acute Lymphoblastic Leukemia: A Genetic Pathway Analysis from the Childhood Cancer and Leukemia International Consortium.

Prenatal folate supplementation has been consistently associated with a reduced risk of childhood acute lymphoblastic leukemia (ALL). Previous germline genetic studies examining the one carbon (folate) metabolism pathway were limited in sample size, scope, and population diversity and led to inconclusive results. We evaluated whether ∼2,900 single-nucleotide polymorphisms (SNP) within 46 candidate genes involved in the folate metabolism pathway influence the risk of childhood ALL, using genome-wide data from nine case-control studies in the Childhood Cancer and Leukemia International Consortium (n = 9,058 cases including 4,510 children of European ancestry, 3,018 Latinx, and 1,406 Asians, and 92,364 controls). Each study followed a standardized protocol for quality control and imputation of genome-wide data and summary statistics were meta-analyzed for all children combined and by major ancestry group using METAL software. None of the selected SNPs reached statistical significance, overall and for major ancestry groups (using adjusted Bonferroni P-value of 5 × 10-6 and less-stringent P-value of 3.5 × 10-5 accounting for the number of "independent" SNPs). None of the 10 top (nonsignificant) SNPs and corresponding genes overlapped across ancestry groups. This large meta-analysis of original data does not reveal associations between many common genetic variants in the folate metabolism pathway and childhood ALL in various ancestry groups. Genetic variants in the folate pathway alone do not appear to substantially influence childhood acute lymphoblastic leukemia risk. Other mechanisms such as gene-folate interaction, DNA methylation, or maternal genetic effects may explain the observed associations with self-reported prenatal folate intake.

Weighted single-step genome-wide association study for direct and maternal genetic effects associated with birth and weaning weights in sheep

Body weight is an important economic trait for sheep meat production, and its genetic improvement is considered one of the main goals in the sheep breeding program. Identifying genomic regions that are associated with growth-related traits accelerates the process of animal breeding through marker-assisted selection, which leads to increased response to selection. In this study, we conducted a weighted single-step genome-wide association study (WssGWAS) to identify potential candidate genes for direct and maternal genetic effects associated with birth weight (BW) and weaning weight (WW) in Baluchi sheep. The data used in this research included 13,408 birth and 13,170 weaning records collected at Abbas-Abad Baluchi Sheep Breeding Station, Mashhad-Iran. Genotypic data of 94 lambs genotyped by Illumina 50K SNP BeadChip for 54,241 markers were used. The proportion of variance explained by genomic windows was calculated by summing the variance of SNPs within 1 megabase (Mb). The top 10 window genomic regions explaining the highest percentages of additive and maternal genetic variances were selected as candidate window genomic regions associated with body weights. Our findings showed that for BW, the top-ranked genomic regions (1 Mb windows) explained 4.30 and 4.92% of the direct additive and maternal genetic variances, respectively. The direct additive genetic variance explained by the genomic window regions varied from 0.31 on chromosome 1 to 0.59 on chromosome 8. The highest (0.84%) and lowest (0.32%) maternal genetic variances were explained by genomic windows on chromosome 10 and 17, respectively. For WW, the top 10 genomic regions explained 6.38 and 5.76% of the direct additive and maternal genetic variances, respectively. The highest and lowest contribution of direct additive genetic variances were 1.37% and 0.42%, respectively, both explained by genomic regions on chromosome 2. For maternal effects on WW, the highest (1.38%) and lowest (0.41%) genetic variances were explained by genomic windows on chromosome 2. Further investigation of these regions identified several possible candidate genes associated with body weight. Gene ontology analysis using the DAVID database identified several functional terms, such as translation repressor activity, nucleic acid binding, dehydroascorbic acid transporter activity, growth factor activity and SH2 domain binding.

Estimates of Maternal Effect and (co)Variance Components for BodyWeight at Different Ages by Animal Model in Chokla Sheep

Background: For this study, information was gathered on 6785 Chokla sheep at the Central Sheep and Wool Research Institute in Bikaner, Rajasthan, India and documented between 1974 and 2020. Methods: (Co)variance components and genetic parameters of weight at birth (BW), weaning (WW), 6, 9 and 12 months of age (6W,9W and YW, respectively) of Chokla sheep, were estimated by average algorithm restricted maximum likelihood (AIREML), fitting six different animal models with various combinations of direct and maternal effects. Result: The direct heritability estimates increased from birth to twelve months of age and values for all the body weight traits except birth weight (0.170) were moderate (0.30-0.50). The maternal influence diminished as age increases and maternal genetic effect (m2) was found to be important and sizeable at weaning stage (0.181). Maternal permanent environmental variance was found to influence the early body weight traits. Negative and high estimate of covariance between direct and maternal effects, resulted in highly inflated values of additive heritability. In this condition, it is more useful to use the total heritability (h2t) for evaluation of the response for selection based on phenotypic values to prevent the use of biased estimates of additive heritability. Genetic and phenotypic correlations among body weights at different ages were positive and ranged from medium to high.

Maternal genetic effects throughout the life of the dam in Pirenaica beef cattle. a random regression model approach

In beef cattle, dams play a crucial role in shaping the pre- and postnatal environment for the growth of their offspring. Acknowledging the substantial impact of maternal influence on the early development of calves, researchers utilize maternal animal models. These models take into account both maternal genetic and permanent environmental effects, operating under the assumption that these influences remain constant throughout the productive life of the cow. Nevertheless, it cannot be ruled out that these genetic and environmental effects may evolve throughout the lifespan of the cows. Therefore, this study aims to describe the changes in genetic and environmental maternal effects over the productive lifespan of cows. To accomplish this goal, we utilized random regression models, incorporating the age of the dam effect, maternal genetic effects, and environmental permanent effects using Legendre orthogonal polynomials. Additionally, the analytical model incorporated a covariate to adjust for the calf’s age at recording, a two-level sex effect, a random herd-year-season effect, and an additive direct genetic effect associated linked to the calf. The dataset comprised information from dams aged between 2 and 16 years, resulting in a final database that comprised weight records of 58 332 calves from 21 673 dams. The average weight at 90 days was 135.0 ± 39.3 kg, and the mean age of the dam at calving was 7.03 ± 3.41 years. We evaluated models incorporating 2, 3, 4, 5, and 6 orthogonal polynomials alongside the standard maternal animal model. Afterward, we selected the model with five orthogonal polynomials based on the Akaike Information Criteria. The Restricted Maximum Likelihood estimates within this model indicated a direct heritability of around 0.50, and a maternal heritability ranging between 0.15 and 0.25, exhibiting a consistent increase between 4, 5 to 13 years. The genetic correlation estimates between direct and maternal genetic effects remained stable at approximately −0.55 across the lifespan of the cows. Furthermore, maternal genetic correlations between different ages of the dam decreased to around 0.7 for more distant age points. The maternal permanent correlations were notably lower, occasionally even reaching negative values, suggesting variability in environmental influence on maternal effects over the productive lifespan of the cow. Finally, the model enables the prediction of breeding values for the maternal genetic effects of the cow across its lifespan, providing opportunities for innovative selection strategies on the maternal side.

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.

Evaluating possible maternal effect lethality and genetic background effects in Naa10 knockout mice.

Amino-terminal (Nt-) acetylation (NTA) is a common protein modification, affecting approximately 80% of all human proteins. The human essential X-linked gene, NAA10, encodes for the enzyme NAA10, which is the catalytic subunit in the N-terminal acetyltransferase A (NatA) complex. There is extensive genetic variation in humans with missense, splice-site, and C-terminal frameshift variants in NAA10. In mice, Naa10 is not an essential gene, as there exists a paralogous gene, Naa12, that substantially rescues Naa10 knockout mice from embryonic lethality, whereas double knockouts (Naa10-/Y Naa12-/-) are embryonic lethal. However, the phenotypic variability in the mice is nonetheless quite extensive, including piebaldism, skeletal defects, small size, hydrocephaly, hydronephrosis, and neonatal lethality. Here we replicate these phenotypes with new genetic alleles in mice, but we demonstrate their modulation by genetic background and environmental effects. We cannot replicate a prior report of "maternal effect lethality" for heterozygous Naa10-/X female mice, but we do observe a small amount of embryonic lethality in the Naa10-/y male mice on the inbred genetic background in this different animal facility.

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 &amp;gt; 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.