Estimates Of Genetic Correlations Research Articles

Assessing the effects of piglet behavior, diet supplementation, and lesion score breeding values of sires on behavior pattern in weaned pigs

The aim of the present study was to study effects of feeding in terms of a herbal diet supplement (HD; basal diet plus a supplement with chicory herbs), of early piglet backtest scores and of relative breeding values for skin lesions (RBV-LS) on behavior pattern of weaned pigs during the post-weaning period. In this regard, we implemented a balanced research design, allowing a semi-randomized allocation of pigs in groups with a very similar number of observations for all sub-cells of diet x backtest score x RBV-LS class combinations. With regard to backtest scores, piglets were classified as high-resisting (HR), low-resisting (LR) or intermediate-resisting (IR). RBV-LS were estimated for the sires based on skin lesions from 993 offspring. The sires were categorized into 2 groups with RBV-LS > 100 (favorable genetic value indicating only a few or no lesions) or RBV-LS ≤ 100 (indicating a large number or severe lesions). Video images were analyzed one day after weaning and 5 weeks later, and considered 300 min per monitoring date for the 8 different possible behavior traits resting time (REST), body contact (BCON), initiating fights (IFIGHT), fighting (FIGHT), refusing of fights (RFIGHT), ear or tail biting (BITE), explorative behavior (EXPLORE) and remaining activities (RACT). Finally, 104 pigs with complete observations over the total video monitoring time at both recording dates, and with complete observations for the explanatory variables sire RBV-LS, backtest score and feeding group, were considered for ongoing association studies. The 104 pigs were crosses from matings of Piétrain boars with German Landrace or German Edelschwein sows. The 104 pigs were offspring of 9 different boars (sire lines). Effects of feeding, backtest score and RBV-LS class on video behaviors were inferred via mixed model analyses, implying 8 different runs for the 8 video behavior traits. Least squares means (lsmeans) significantly (P < 0.05) differed between HD and the control feeding group (CON) for FIGHT and BITE, with longer durations of aggressive behavior for CON pigs. Vice versa, lsmeans for REST indicating calm behavior were larger for the HD group. Pigs classified as HR piglets were more aggressive than the LR and IR contemporaries, with significantly higher lsmeans for FIGHT, BITE and EXPLORE. The pigs allocated to the sire RBV-LS > 100 group had significantly (P < 0.05) longer durations for REST and RFIGHT. Vice versa, pigs allocated to the sire RBV-LS ≤ 100 groups spent more with aggressive behavior in terms of BITE and FIGHT. Consequently, boar RBV-LS were favorably correlated with REST, IFIGHT and RACT. In conclusion, the early piglet backtest scores as well as breeding values from a victim perspective (lesion scores) can be used as indicator traits for selection against aggressiveness. Nevertheless, results from the present study are first indications and breeding value correlations are approximations in this regard, which should be validated in ongoing studies based on larger datasets via real genetic correlation estimates between actor and victim traits, and considering social interactions and interactions between all fixed effects simultaneously.

Milk coagulation properties are moderately heritable in dairy cows: a meta-analysis using the random-effects model.

This study aimed to conduct a meta-analysis using the random-effects model to merge published genetic parameter estimates for milk coagulation properties (MCP: comprising rennet coagulation time (RCT), curd-firming time (k20), curd firmness 30 min after rennet addition (a30), titrable acidity (TA) and milk acidity or pH) in dairy cows. Overall, 80 heritability estimates and 157 genetic correlations from 23 papers published between 1999 and 2020 were used. The heritability estimates for RCT, a30, k20, TA, and pH were 0.273, 0.303, 0.278, 0.189 and 0.276, respectively. The genetic correlation estimates between RCT-a30, RCT-pH, and RCT-TA were 0.842, 0.549 and -0.565, respectively. Genetic correlation estimates between RCT and production traits were generally low and ranged from -0.142 (between RCT and casein content) to 0.094 (between RCT and somatic cell score). Moderate and significant genetic correlations were observed between a30-pH (-0.396) and a30-TA (0.662). Also, the genetic correlation estimates between a30 and production traits were low to moderate and varied from -0.165 (between a30 and milk yield) to 0.481 (between a30 and casein content). Genetic correlation estimates between pH and production traits were low and varied from -0.190 (between pH and milk protein percentage) to 0.254 (between pH and somatic cell score). The results of this meta-analysis indicated the existence of additive genetic variation for MCP that could be used in genetic selection programs for dairy cows. Because of the moderate heritability of MCP and small genetic correlations with production traits, it could be possible to improve MCP with negligible correlated effects on production traits.

Estimation of genetic parameters for milking temperament in Holstein-Gyr cows

IntroductionDairy cattle with poor temperament can cause several inconveniences during milking, leading to labor difficulties, increasing the risk of accidents with animals and workers, and compromising milk yield and quality. This study aimed to estimate variance components and genetic parameters for milking temperament and its genetic correlations with milk yield in crossbred Holstein-Gyr cattle.MethodsData were collected at three commercial farms, resulting in 5,904 records from 1,212 primiparous and multiparous lactating cows. Milking temperament (MT), measured as the milking temperament of each cow, was assessed during pre-milking udder preparation (RP) and when fitting the milking cluster (RF) by ascribing scores from 1 (cow stands quietly) to 8 (the cow is very agitated, with vigorous movements and frequent kicking). The number of steps and kicks were also recorded during pre-milking udder preparation (SRPand KRP, respectively) and when fitting the milking cluster (SRFand KRF, respectively). Milk yield (MY) was obtained from each farm database. In two of them, MY was recorded during the monthly milk control (that could or could not coincide with the date when the milking temperament assessments were carried out) and in the remaining farm, MY was recorded on the same day that the milking temperament assessments were made. Genetic parameters were estimated using the THRGibbs1f90 program applying a threshold model, which included 89 contemporary groups as fixed effects, animal age at the assessment day and the number of days in milking as covariates, and direct additive genetic and residual effects as random effects.Results and discussionsThe heritability estimates were MT= 0.14 ± 0.03 (for both, MRPand MRF), MY= 0.11 ± 0.08, SRP= 0.05 ± 0.03, KRP= 0.14 ± 0.05, SRF= 0.10 ± 0.05, and KRF= 0.32 ± 0.16. The repeatability estimates were 0.38 ± 0.05, 0.42 ± 0.02, and 0.84 ± 0.006 for MTRP, MTRF, and MY, respectively; and 0.38 ± 0.02, 0.30 ± 0.07, 0.52 ± 0.02, and 0.46 ± 0.15 for SRP, KRP, SRF, and KRF, respectively. The estimates of most genetic correlation coefficients between MTRP-MTRFwere all strong and positive (MTRR-MTRF= 0.63 ± 0.10, MTRP-SRP= 0.65 ± 0.12, MTRP-KRP= 0.56 ± 0.16, MTRF-SRF= 0.77 ± 0.06, and MTRF-KRF= 0.56 ± 0.34) except for MY (MTRP-MY= 0.26 ± 0.26 and MTRF-MY= 0.21 ± 0.23). Despite the low magnitude of MT heritability, it can be included as a selection trait in the breeding program of Holsteins-Gyr cattle, although its genetic progress will be seen only in the long term. Due to the low accuracy of the genetic correlation estimates between MT and MY and the high range of the 95% posterior density interval, it cannot be affirmed by this study that the selection of a milking temperament trait will infer on milk yield. More data is therefore needed per cow and more cows need to be observed and measured to increase the reliability of the estimation of these correlations to be able to accurately interpret the results.

Genetic Parameter Estimates for Teat and Mammary Traits in Commercial Sows.

The objective was to evaluate the genetics of sow teat and mammary traits at farrowing and at weaning. Data were recorded on 3099 Landrace × Large White F1 sows. Underline traits included the total teat number (TT), the functional teat number (FT), the non-functional teat number (NFT), the damaged teat number (DT), and the number of functional mammary glands (FMG). Variance components were estimated using AIREMLF90. Means for TT, FT, and NFT at farrowing were 14.93, 13.90, and 1.03, respectively. Heritability estimates for TT, FT, and NFT ranged from 0.18 to 0.37, 0.16 to 0.28, and 0.14 to 0.18, respectively. Estimates of heritability for DT and FMG at weaning were 0.03 and 0.06, respectively. Estimated genetic correlations between FT with TT and NFT were 0.68 to 0.78 and -0.19 to -0.57, respectively. Genetic correlation estimates between TT, FT, and NFT with the number weaned were 0.25, 0.50, and -0.38, respectively. An increase of one TT and FT enhanced (p < 0.05) the number weaned by 0.14 to 0.16 and 0.18 to 0.27 piglets, respectively. The results suggest that genetically increasing the number of functional teats on a sow at farrowing would improve the number of piglets at weaning.

Estimation of genetic correlations and genomic prediction accuracy for reproductive and carcass traits in Hanwoo cows

Estimation of genetic correlations and genomic prediction accuracy for reproductive and carcass traits in Hanwoo cows

Production environment is determinant in the genetic relationship between growth traits of Nile tilapia through a reaction norm model

Genotype by environment interaction (G × E) has been a matter of interest for breeders and fish producers around the world, mainly because the selection performed in one environment may not have the desired response in other environments. Most studies conducted on G × E in aquaculture species have used a single trait approach; however, breeding programs have selected for multiple traits simultaneously. Thus, it was of interest in this study to use a multiple trait reaction norm model to analyze the genetic relationship between growth traits of Nile tilapia in the presence of G × E in a (sub)tropical environment. A multiple trait reaction norm model was applied to data from 12,192 animals evaluated for body weight (BW), trunk length (TL) and head percentage (HP). The adopted environmental descriptor was the solution of contemporary groups for BW. The ratio between slope and additive genetic intercept of the reaction norms ranged from 0.59 to 0.70, which demonstrated the presence of G × E for BW, TL, and HP. The mean of the heritability estimates showed variation of up to 300% along the environmental descriptor. Thus, the selection responses for BW, TL, and HP should be different depending on the production environment. The genetic correlations within each trait across different levels of the environmental descriptor were high and positive between closer environments and reached values close to or below zero between distant environments (−0.34, −0.31, and 0.07 for BW, TL, and HP, respectively). Therefore, the best individuals in one environment will not necessarily be the same in a different environment. Given genetic correlation estimates greater than 0.85 between BW and TL across the environmental descriptor, selection for increased BW or TL will lead to a favorable reciprocal correlated response regardless of the environment. The genetic correlations between BW and HP and between TL and HP across environmental descriptor reached negative values of −0.63 and − 0.77 in better environments, respectively. Thus, selection to increase BW or TL contributes to a more expressive reduction in HP in favorable production environments compared to more restrictive ones.

Estimation of Genetic Parameters for Weights at Different Ages in Anatolian Buffalo Calves

Background: The determination of the breeding potential and direction of the population in terms of traits of interest depends on the genetic variation. Therefore, it is essential to know the genetic parameters of economic traits to improve yields in animal breeding. The objective of this study was to investigate the heritability, genetic and phenotypic correlations among growth traits in Anatolian buffaloes of ìstanbul province. Methods: A total records of 7649 birth weights, 4623 sixth-month weights and 3133 yearling weights belonging to buffalo calves born between 2012 and 2021 were used. Genetic and phenotypic parameters were estimated from univariate and bivariate animal model using restricted maximum likelihood (REML) procedure in Wombat software. Village, year, season, sex and age of dam were considered as fixed effects and animal additive genetic effect was taken as random effect. Result: The heritability estimates for birth, sixth-month and yearling weights were 0.14±0.03; 0.22±0.05; 0.39±0.07 respectively. Genetic and phenotypic correlations among growth traits were generally significant and positive and ranged from 0.28±0.02 to 0.97±0.02. As a consequence, the moderate to high estimates of heritability, genetic and phenotypic correlations on growth traits showed that there were some opportunities for genetic improvement in buffaloes of ìstanbul. These genetic parameters should be considered in selection programs.

A meta-analysis of genetic parameter estimates for growth traits in fat-tailed sheep

This study aimed at using a random-effects model of meta-analysis to compile the estimates of direct heritability, maternal heritability, the ratio of the permanent environmental variance to phenotypic variance, the correlation between direct and maternal genetic effects for growth traits (body weights, average daily gains, and Kleiber ratios), and also genetic correlations among these traits in fat-tailed sheep. A total of 458 direct heritability estimates, 260 maternal heritability estimates, 217 estimates of the ratio of the permanent environmental variance to phenotypic variance, 144 estimates of the correlation between direct and maternal genetic effects, and 349 genetic correlations from articles which were published between 1978 and 2021 were used in the meta-analysis. Chi-square (Q) test was performed to measure heterogeneity and the I2 statistic was determined. The average direct heritability estimates for the studied traits were low to moderate and ranged from 0.108 (for Kleiber ratio from three to six-months of age (KR3–6)) to 0.258 (for Kleiber ratio from birth to six-months of age (KR0–6)). The average maternal heritability estimates for growth traits were low and varied from 0.056 (for KR3–6) to 0.142 (for birth weight (BW)). The average correlation estimates between direct and maternal genetic effects for growth traits were negative and varied from −0.826 (for KR3–6) to −0.039 (for three-months weight (3 MW)). The genetic correlation estimates between BW and other traits were low to moderate and ranged from 0.089 (between BW-KR0–3) to 0.472 (between BW-3 MW). Also, the genetic correlation estimate between 3 MW and average daily gain from three to six-months of age (ADG3–6) was low (0.187) and not significant, but genetic correlation estimates between 3 MW and other traits were moderate to high and varied from 0.637 to 0.853 (P < 0.05). The meta-analysis showed that growth traits in fat-tailed sheep were under low to moderate genetic control. The average genetic parameter estimates obtained in this study could be utilized in the genetic selection plans for fat-tailed sheep, especially when there is limited access to accurate phenotypic records or genetic parameter estimates for the studied traits.

Genetic evaluation of growth rate and efficiency-related traits in Dorper × local crossbred sheep population.

The present study was carried out to estimate genetic and phenotypic parameters for growth rate and efficiency-related traits in Dorper crossbred sheep population. Data on body weight collected from 2012 to 2021 at Debre Birhan Agricultural Research Center, Amhara Regional State, Ethiopia, were used to estimate phenotypic and genetic parameters for daily gain from birth to weaning (DG0-3), daily gain from weaning to 6 months (DG3-6), and daily gain from 6 months to yearling (DG6-12) and corresponding Kleiber ratios (KR0-3, KR3-6, KR6-12), efficiency of growth (GE0-3, GE3-6, GE6-12), and relative growth rate (RG0-3, RG3-6, RG6-12). Genetic parameters were estimated by restricted maximum likelihood (REML) procedure fitting six different univariate animal models and the most appropriate model for each trait was determined by log-likelihood ratio test. Multivariate analysis was carried out to estimate correlations between traits. Year and season of birth had a significant effect (p<0.001) in all studied traits. Direct heritability estimates for DG0-3, DG3-6, DG6-12, KR0-3, KR3-6, KR6-12, GE0-3, GE3-6, GE6-12, GR0-3, GR3-6, and GR6-12 were 0.45±0.15, 0.04±0.06, 0.15±0.11, 0.30±0.08, 0.13±0.11, 0.14±0.12, 0.34±0.15, 0.39±0.17, 0.31±0.14, 0.25±0.08, 0.23±0.13, and 0.23±0.13 respectively. Genetic correlation estimates between DG3-6 and other traits were positive and high in magnitude to their respective growth phase (0.95, 0.86, and 0.91 for KR3-6, GE3-6, and GR3-6 respectively). As the Dorper crossbred sheep are reaches market weight at about 6 months of age, focusing on improving traits measured during weaning to 6 months of age is more feasible. Selection based on DG3-6 is recommended to improve efficiency-related traits.

Genetic divergence and correlation estimates for quantitative traits in Salix

Genetic divergence and correlation estimates for quantitative traits in Salix

Similarity and diversity of genetic architecture for complex traits between East Asian and European populations

BackgroundGenome-wide association studies have detected a large number of single-nucleotide polymorphisms (SNPs) associated with complex traits in diverse ancestral groups. However, the trans-ethnic similarity and diversity of genetic architecture is not well understood currently.ResultsBy leveraging summary statistics of 37 traits from East Asian (Nmax=254,373) or European (Nmax=693,529) populations, we first evaluated the trans-ethnic genetic correlation (ρg) and found substantial evidence of shared genetic overlap underlying these traits between the two populations, with {widehat{rho }}_{g} ranging from 0.53 (se = 0.11) for adult-onset asthma to 0.98 (se = 0.17) for hemoglobin A1c. However, 88.9% of the genetic correlation estimates were significantly less than one, indicating potential heterogeneity in genetic effect across populations. We next identified common associated SNPs using the conjunction conditional false discovery rate method and observed 21.7% of trait-associated SNPs can be identified simultaneously in both populations. Among these shared associated SNPs, 20.8% showed heterogeneous influence on traits between the two ancestral populations. Moreover, we demonstrated that population-common associated SNPs often exhibited more consistent linkage disequilibrium and allele frequency pattern across ancestral groups compared to population-specific or null ones. We also revealed population-specific associated SNPs were much likely to undergo natural selection compared to population-common associated SNPs.ConclusionsOur study provides an in-depth understanding of similarity and diversity regarding genetic architecture for complex traits across diverse populations, and can assist in trans-ethnic association analysis, genetic risk prediction, and causal variant fine mapping.

Biases in quantitative genetic parameters estimations caused by self-fertilization in the Caribbean pectinid Argopecten nucleus (Mollusca: Bivalvia)

Inbreeding can cause an important bias in the estimates of quantitative genetic parameters, which in turn can affect the estimated potential for a selection response in species that are simultaneous hermaphrodite with partial self-fertilization. In the present study, the biases caused by self-fertilization on heritability (h2) estimates for productive traits were assessed at different ages in the tropical hermaphrodite pectinid Argopecten nucleus. Self-fertilization rates were estimated in both oocytes and adults, as the percentage of zygotes formed from unfertilized oocytes and by paternity analysis using microsatellite genetic markers, respectively. Fifty sexually mature individuals were individually spawned and genotyped using microsatellite markers. The sperm of one individual used as a male was used to fertilize the oocytes of 4 other individuals, generating 10 half-sibling families (HS) and 40 full-siblings families (FS). At the age of 3.5 months, the total weight, and the length, height, and width of the shell of 60 animals per FS family were individually measured. At the age of 9 months, the same measurements were repeated in the same individuals, which were then euthanized to weigh the soft tissues. In addition, the fecundity was estimated in each individual (number of oocytes produced), and a paternity analysis was performed. No significant differences were found in the average inbreeding rates estimated in oocytes and adults. However, no significant correlation was observed in the estimates of family self-fertilization rates when using both methods. The individuals derived from crossbreeding showed higher average values for productive traits than those produced by selfing, although interactions between the genotype and the depth of culture were observed in both groups. The h2 estimates using statistical models that consider self-fertilization in adults (models II and III) were lower than those observed when self-fertilization rates were estimated in oocytes, or not included in the model. However, the genetic correlations between the traits were similar using both methods for estimating self-fertilization rates. The present results suggest that self-fertilization results in inbreeding depression and induces an overestimation of the h2 for productive traits, but it does not affect estimates of genetic correlations or genotype by environment interactions.

Indirect genetic effects increase heritability estimates for male and female extra-pair reproduction.

The question of why females engage in extra-pair behaviours is long-standing in evolutionary biology. One suggestion is that these behaviours are maintained through pleiotropic effects on male extra-pair behaviors (genes controlling extra-pair reproduction are shared between sexes, but only beneficial to one sex, in this case, males). However, for this to evolve extra-pair reproduction must be both heritable and positively genetically correlated between sexes. Previous studies have suggested low heritability with no evidence for between-sex genetic correlations in extra-pair reproduction. However, these have not considered indirect genetic effects (derived from the behaviour of others, IGEs) from the social partner, the influence of the social partner's genotype on the phenotype of an individual, despite the potential of IGEs to uncover hidden heritable variation. Using data from a closed house sparrow population with a genetic pedigree spanning two decades, we tested the influence of social partner IGEs on heritable variation and genetic correlation estimates of extra-pair reproduction. We found that the inclusion of IGEs resulted in larger heritable genetic variance for both male and female extra-pair heritability. While IGEs did not change between-sex genetic correlations, we found they reduced uncertainty in those estimates. Future studies should consider the effect of IGEs on the mechanisms of sex specific extra-pair reproduction.

Genetic parameters and multi-trait genomic prediction for hemoparasites infection levels in cattle

Babesiosis and anaplasmosis are tick-borne diseases that substantially affect the economic outcomes of livestock production in tropical countries. This study aimed to evaluate the genetics of resistance to infection caused by these parasites through the estimation of heritabilities and genetic correlations of infection levels among Babesia bigemina (BigIL), B. bovis (BovIL), and Anaplasma marginale (AmIL), and tick counts (TC). The predictive ability of single and multi-trait genomic prediction models was evaluated through various combinations of these traits. To our knowledge, this is the first genomic study to examine BigIL and AmIL. Infection levels of BigIL (n = 1,882), BovIL (n = 1,858), and AmIL (n = 1,523) were estimated from blood samples using real-time PCR. TC phenotypes (n = 5,867) were obtained by counting the number of parasites larger than 4.5 mm from the right-hand side of each animal. Genotypic data were available for 3,977 animals which were then imputed up to ∼777,000 SNP and, after quality control, 502,398 SNP remained for downstream analyses. Variance components for BigIL and AmIL and the genetic correlations between traits were estimated using a Bayesian approach. The single-step best linear unbiased prediction was used to estimate genomic breeding values (GBV). The heritability estimates for BigIL and AmIL were low at 0.094 and 0.090, respectively, suggesting high environmental influence levels for both traits. The genetic correlations between tick count and infection levels for BigIL (0.239), BovIL (0.160), and AmIL (-0.019) were low, as well as the correlation between AmIL and BovIL (0.043). The genetic correlations between BigIL and BovIL (0.524) and BigIL and AmIL (0.793) were high, which contributed to improved GBV accuracies when these traits were combined in multi-trait models in comparison to single-trait models. These results suggested that multi-trait genomic prediction models of infection levels for tick-borne diseases are preferable to single-trait models. Additionally, our results indicated that the TC data and the GBV based on them are not useful for predicting infection levels of BigIL, BovIL, and AmIL.

Fine-mapping of retinal vascular complexity loci identifies Notch regulation as a shared mechanism with myocardial infarction outcomes

There is increasing evidence that the complexity of the retinal vasculature measured as fractal dimension, Df, might offer earlier insights into the progression of coronary artery disease (CAD) before traditional biomarkers can be detected. This association could be partly explained by a common genetic basis; however, the genetic component of Df is poorly understood. We present a genome-wide association study (GWAS) of 38,000 individuals with white British ancestry from the UK Biobank aimed to comprehensively study the genetic component of Df and analyse its relationship with CAD. We replicated 5 Df loci and found 4 additional loci with suggestive significance (P < 1e−05) to contribute to Df variation, which previously were reported in retinal tortuosity and complexity, hypertension, and CAD studies. Significant negative genetic correlation estimates support the inverse relationship between Df and CAD, and between Df and myocardial infarction (MI), one of CAD’s fatal outcomes. Fine-mapping of Df loci revealed Notch signalling regulatory variants supporting a shared mechanism with MI outcomes. We developed a predictive model for MI incident cases, recorded over a 10-year period following clinical and ophthalmic evaluation, combining clinical information, Df, and a CAD polygenic risk score. Internal cross-validation demonstrated a considerable improvement in the area under the curve (AUC) of our predictive model (AUC = 0.770 ± 0.001) when comparing with an established risk model, SCORE, (AUC = 0.741 ± 0.002) and extensions thereof leveraging the PRS (AUC = 0.728 ± 0.001). This evidences that Df provides risk information beyond demographic, lifestyle, and genetic risk factors. Our findings shed new light on the genetic basis of Df, unveiling a common control with MI, and highlighting the benefits of its application in individualised MI risk prediction.

Reliable Genetic Correlation Estimation via Multiple Sample Splitting and Smoothing

In this paper, we aim to investigate the problem of estimating the genetic correlation between two traits. Instead of making assumptions about the distribution of effect sizes of the genetic factors, we propose the use of a high-dimensional linear model to relate a trait to genetic factors. To estimate the genetic correlation, we develop a generic strategy that combines the use of sparse penalization methods and multiple sample splitting approaches. The final estimate is determined by taking the median of the calculations, resulting in a smoothed and reliable estimate. Through simulations, we demonstrate that our proposed approach is reliable and accurate in comparison to naive plug-in methods. To further illustrate the advantages of our method, we apply it to a real-world example of a bacterial GWAS dataset, specifically to estimate the genetic correlation between antibiotic resistant traits in Streptococus pneumoniae. This application not only validates the effectiveness of our method but also highlights its potential in real-world applications.

Identification of the genetic basis of sow pelvic organ prolapse.

Introduction: Pelvic organ prolapse (POP) is one contributor to recent increases in sow mortality that have been observed in some populations and environments, leading to financial losses and welfare concerns. Methods: With inconsistent previous reports, the objective here was to investigate the role of genetics on susceptibility to POP, using data on 30,429 purebred sows, of which 14,186 were genotyped (25K), collected from 2012 to 2022 in two US multiplier farms with a high POP incidence of 7.1% among culled and dead sows and ranging from 2% to 4% of all sows present by parity. Given the low incidence of POP for parities 1 and >6, only data from parities 2 to 6 were retained for analyses. Genetic analyses were conducted both across parities, using cull data (culled for POP versus another reason), and by parity, using farrowing data. (culled for POP versus culled for another reason or not culled). Results and Discussion: Estimates of heritability from univariate logit models on the underlying scale were 0.35 0.02 for the across-parity analysis and ranged from 0.41 0.03 in parity 2 to 0.15 0.07 in parity 6 for the by-parity analyses. Estimates of genetic correlations of POP between parities based on bivariate linear models indicated a similar genetic basis of POP across parities but less similar with increasing distance between parities. Genome wide association analyses revealed six 1Mb windows that explained more than 1% of the genetic variance in the across-parity data. Most regions were confirmed in several by-parity analyses. Functional analyses of the identified genomic regions showed a potential role of several genes on chromosomes 1, 3, 7, 10, 12, and 14 in susceptibility to POP, including the Estrogen Receptor gene. Gene set enrichment analyses showed that genomic regions that explained more variation for POP were enriched for several terms from custom transcriptome and gene ontology libraries. Conclusion: The influence of genetics on susceptibility to POP in this population and environment was confirmed and several candidate genes and biological processes were identified that can be targeted to better understand and mitigate the incidence of POP.

Genetic Variability and Correlation Estimates for Morpho-Physiological Characteristics in Half Sib Progenies of Toona ciliate

Genetic Variability and Correlation Estimates for Morpho-Physiological Characteristics in Half Sib Progenies of Toona ciliate

Genetic and Phenotypic Correlations between Characteristics in Local Guinea Fowl in Ghana

This study aimed at estimating genetic and phenotypic correlations among traits in local Guinea fowl in Ghana. Animal farm of Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development Mampong-Ashanti campus was where the study took place, from 2015 to 2018. Data for the experiment was obtained from keets made up of 300 males and 300 females. Parents of the keets consisted of 110 dams and 22 sires. Arithmetic method and Pearson’s product moment correlation were used for the estimates. In male Guinea fowl, the values of genetic correlations among growth characteristics ranged from -0.63 to 0.93. Between growth and other characteristics, estimates of genetic correlation ranged from 0.29 to 0.97, -0.67 to 0.43, -0.62 and 0.94 respectively. Values of phenotypic correlations among growth parameters were between -0.32 and 0.49. Range of figures of phenotypic correlations recorded between growth characteristics and survival, docility, and dressing percentage were between -0.28 and 0.28, -0.46 and 0.18, and -0.41 and 0.36 correspondently. In female Guinea fowl on the other hand, range of genetic correlations among growth traits was between -0.80 and 0.95. Range of figures of genetic correlation between growth traits and survival, docility, dressing percentage and reproductive characteristics of were from -0.47 to 0.9, -0.52 to 0.58, -0.58 to 0.82 and -0.59 to 0.9 respectively. The values of phenotypic correlations among growth characteristics fell between -0.39 and 0.46. Phenotypic correlations recorded between growth traits and survival, docility, dressing percentage and reproductive characteristics were from -0.26 to 0.47, -0.47 to 0.19, -0.35 to0.47 and -0.33 to 0.47 respectively. Values of genetic correlations higher than one (1) among some traits in male Guinea fowl were recorded. To conclude, discoveries of this study are in general agreement of what pertains to Guinea fowl and other farm livestock species.

Estimation of genetic variability, correlation and path analysis in elite rice genotypes (Oryza sativa L.)

A trial was carried out to explore the variability and correlation among thirty five rice (Oryza sativa L.) germplasm for fifteen characters, during kharif 2017-18 at Bihar Agricultural University, Sabour, (Bihar). Analysis of variance revealed significant differences among all the genotypes and for all fifteen characters, which reflects that considerable amount of variability, were present in the genotypes. Two genotypes LPD104-B-B-1-8-2-1-1and RP5124-11-6-2 were identified as the superior genotypes for yield. The highest magnitude of genotypic coefficient of variation was recorded for length breadth ratio of rice grain, however highest phenotypic coefficients of variation were recorded for grain yield per plant followed by kernel length. High heritability coupled with high genetic advance as per cent mean was observed for kernel length and length breadth ratio. In this experiment grain yield per plant had positive and significant association with biological yield per plant, days to 50 per cent flowering, days to maturity, while remaining characters had non-significant association with yield. Path coefficient analysis revealed that the biological yield per plant, harvest index and kernel length had high positive direct effects on grain yield per plant indicating true relationship of these characters with grain yield. Therefore, these traits could be considered in rice improvement programme.