Restricted Maximum Likelihood Method Research Articles

Genetic parameters and genome-wide association analyses for lifetime productivity in Chinese Holstein cattle

Lifetime productivity is a trait of great importance to dairy cattle populations as it combines information from production and longevity variables. Therefore, we investigated the genetic background of lifetime productivity in high-producing dairy cattle by integrating genomics and transcriptomics data sets. A total of 3,365,612 test-day milk yield records from 134,029 Chinese Holstein cows were used to define 6 lifetime productivity traits, including lifetime milk yield covering full lifespan and 5 cumulative milk yield traits covering partial lifespan. Genetic parameters were estimated based on univariate and bivariate linear animal models and the Restricted Maximum Likelihood (REML) method. Genome-wide association studies (GWAS) and weighted gene co-expression network analyses (WGCNA) were performed to identify candidate genes associated with lifetime productivity based on genomic data from 3,424 cows and peripheral blood RNA-seq data from 23 cows, respectively. Lifetime milk yield averaged 24,800.8 ± 14,396.6 kg (mean ± SD) across an average of 2.4 parities in Chinese Holstein population. The heritability estimates for lifetime productivity traits ranged from 0.05 (±0.01 for SE) to 0.10 (±0.02 for SE). The estimate of genetic correlation between lifetime milk yield and productive life is 0.88 (±0.3 for SE) while the genetic correlation with 305d milk yield in the first lactation was 0.49 (±0.08 for SE). Absolute values for most genetic correlation estimates between lifetime productivity and type traits were lower than 0.30. Moderate genetic correlations were found between udder related traits and lifetime productivity, such as with udder depth (0.33), rear udder attachment height (0.33), and udder system (0.34). Some single nucleotide polymorphisms and gene co-expression modules significantly associated with lifetime milk yield were identified based on GWAS and WGCNA analyses, respectively. Functional enrichment analyses of the candidate genes identified revealed important pathways related to immune system, longevity, energy utilization and metabolism, and FoxO signaling. The genes NTMT1, FNBP1, and S1PR1 were considered to be the most important candidate genes influencing lifetime productivity in Holstein cows. Overall, our findings indicate that lifetime productivity is heritable in Chinese Holstein cattle and important candidate genes were identified by integrating genomic and transcriptomic data sets.

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.

Association between perivascular spaces burden and future stroke risk in ischemic stroke and transient ischemic attack: A systematic review and meta-analysis.

This meta-analysis aimed to explore the association of perivascular spaces (PVS) burden with the risks of future stroke events and mortality in patients with ischemic stroke and transient ischemic attack (TIA). We systematically searched PubMed, Embase and Cochrane database from inception to 31 December 2023. We included eligible studies that reported adjusted estimated effects for future intracranial hemorrhage (ICH), ischemic stroke and mortality with baseline PVS burden in patients with ischemic stroke and TIA. Data were pooled using an inverse-variance method for fixed effect (FE) model and a restricted maximum likelihood (REML) method for random effects (RE) model. Thirteen observational studies (5 prospective, 8 retrospective) were included, comprising 20256 patients. Compared to 0 - 10 PVS at basal ganglia (BG), a higher burden (&gt;10) of BG-PVS was significantly associated with an increased risk of future intracranial hemorrhage (adjusted hazards ratio [aHR] 2.79, 95% confidence interval [CI] 1.16 - 6.73, RE model; aHR 2.14, 95%CI 1.34 - 3.41, FE model; I2 = 64%, n = 17084 from four studies) followed-up for at least one year. There was no significant association between &gt;10 BG-PVS and intracranial hemorrhage within 7 days after reperfusion therapy (adjusted odds ratio [aOR] 1.69, 95%CI 0.74 - 3.88, RE model; aOR 1.43, 95%CI 0.89 - 2.88, FE model; I2 = 67%, n = 1176 from four studies). We did not detect a significant association of recurrent ischemic stroke, mortality or disability with BG-PVS burden. Neither &gt;10 PVS at centrum semiovale (CSO-PVS) nor increasing CSO-PVS burden was significantly associated with the risk of future intracerebral hemorrhage or ischemic stroke recurrence. Current evidence suggests that a higher BG-PVS burden may be associated with an increased risk of future intracranial hemorrhage in patients with ischemic stroke and TIA. PROSPERO registration number: CRD42021232713 Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021232713.

Intravascular imaging-guided percutaneous coronary intervention for heavily calcified coronary lesions: a systematic review and meta-analysis.

Although multiple randomized clinical trials (RCTs) have shown that intravascular imaging (IVI)-guided percutaneous coronary intervention (PCI) is associated with improved clinical outcomes compared with angiography-guided PCI, its benefits specifically in calcified coronary lesions is unclear due to the small number of patients included in individual trials. We performed a meta-analysis of RCTs to investigate benefits of IVI-guided PCI compared with angiography-guided PCI in heavily calcified coronary lesions. The primary endpoint was major adverse cardiac events (MACE), a composite of cardiac death, target-vessel or target-lesion myocardial infarction, and target-vessel or target lesion revascularization. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated by using a random-effects meta-analysis based on the restricted maximum likelihood method. A search PubMed, EMBASE, and Cochrane Library from their inception to January 2024 identified 4 trials that randomized 1319 patients with angiographically moderate or severe or severe coronary calcification to IVI-guided (n = 702) vs. angiography-guided PCI (n = 617). IVI-guided PCI resulted in a significantly lower odds of MACE (OR 0.57, 95% CI 0.40-0.80) compared with angiography-guided PCI at a weighted median follow-up duration of 27.3 months. There was no evidence of heterogeneity among the studies (I2 = 0.0%), and included trials were judged to be low risk of bias. Compared with angiography-guided PCI, IVI-guided PCI was associated with a significantly lower MACE in angiographically heavily calcified coronary lesions.

Prevalence and Risk of Schizophrenia and Bipolar Disorder in Patients with Type 1 Diabetes Mellitus: A Systematic Review and Meta-analysis

Purpose: Schizophrenia and bipolar disorder are understood to have neuroinflammatory/neuro-immunological basis in their etiopathogenesis. There are few studies synthesizing the association of schizophrenia and bipolar disorder in type 1 diabetes mellitus (T1DM), a common immunological disorder. Data Collection and Analysis: We performed meta-analyses of studies assessing the prevalence and risk of schizophrenia and related disorders and bipolar disorder in individuals with T1DM. Fifteen studies consisting of a total sample of 9,768,028 (T1DM: 435,553; non-T1DM controls: 9,332,475) were included. Random-effects meta-analyses using the restricted maximum likelihood method for pooling logit transformed prevalence values and the Mantel–Haenszel test for pooling risk ratios were used. I2 statistic and the rank correlation test for Funnel plots’ asymmetry were used to assess heterogeneity and publication bias, respectively. Results: Pooled (transformed-back-transformed) prevalence for schizophrenia and related psychotic disorders was 0.37% (95%CI: 0.19–0.73), and for bipolar disorder it was 0.39% (95%CI: 0.05–2.99) (together: 0.38% (95%CI: 0.2–0.71)] in T1DM. The prevalence models showed significant heterogeneity but were statistically significant, had low publication bias, and survived sensitivity analysis. The pooled risk ratio for schizophrenia and related disorders together with bipolar disorder was 1.80 (95%CI: 0.64–5.03), and for schizophrenia and related disorders alone it was 1.19 (95%CI: 0.46–3.11), indicating higher rates of these disorders in T1DM. The pooled risk ratios were not statistically significant and did not survive sensitivity analysis. Trial sequential analysis suggested the need for more studies to confirm increased risk. Conclusion: With available studies, we could not provide convincing evidence for the hypothesis that the prevalence and risk of schizophrenia and related disorders and bipolar disorder are significantly greater in individuals with T1DM.

Resistance to natural tick infestation varies with age and coat and hair traits in a tropically adapted beef cattle breed

Rhipicephalus (Boophilus) microplus causes considerable livestock production losses. Knowledge of the traits that influence tick resistance contributes to the development of breeding strategies designed to improve herd productivity. Within this context, this study evaluated the resistance of Caracu, a tropically adapted cattle breed, to R. microplus. Tick count, hair length, coat thickness, and coat color were evaluated in 202 naturally tick-infested females (cows and heifers) over a period of 18 months. Blood samples were collected from all animals during the winter season for hematological analysis. Data were analyzed using Pearson correlations, generalized linear models, and principal component analysis. Correlation coefficients of tick count with coat color, coat thickness, and hair length were estimated within each season. Hematological parameters were only included in the winter season analysis and were analyzed by the restricted maximum likelihood method using log-transformed data. No differences in blood parameters were observed between animals with and without ticks. However, tick count was negatively correlated with erythrocytes (−0.29) and hematocrit (−0.24) and positively correlated with mean corpuscular hemoglobin (0.21) and mean corpuscular hemoglobin concentration (0.25). These findings suggest that higher tick counts lead to a decrease in erythrocytes but also to an increase in the amount of hemoglobin per erythrocyte, which could reduce the damage caused by low erythrocyte levels due to tick hematophagy, delaying or preventing anemia. Although tick infestation on pasture was demonstrated by the infestation of all staff members during herd management, none of the animals exhibited high tick counts, providing evidence of resistance of Caracu animals to R. microplus. Tick infestation was influenced by age class (cows > heifers), season (spring and summer > fall and winter), coat thickness (>1.5 mm > <1.5 mm), and hair length (>6 mm > <6 mm). Three components were extracted by principal component analysis, which accounted for 69.46% of data variance. The findings of this study will contribute to the development of efficient strategies aimed at reducing economic losses due to tick infestation and could be applied in animal breeding to select for tick resistance traits, reducing chemical control strategies and consequently improving sustainable livestock production.

Small Sample Methods in Multilevel Analysis

Bayesian methods have been said to solve small sample problems in frequentist methods by reflecting prior knowledge in the prior distribution. However, there are dangers in strongly reflecting prior knowledge or situations where much prior knowledge cannot be used. In order to address the issue, in this article, we considered to apply two Bayesian methods, one with weakly informative prior for random effect parameters (BayesW) and another with non-informative prior (BayesN) and compared their performance of parameter recovery with restricted maximum likelihood (REML) method, a frequentist-based estimation method commonly used in multilevel analysis. Specifically, we conducted two simulation studies using a two-level linear multilevel model and compared the performance of the BayesW, the BayesN, and the REML in various conditions that include scenarios of small sample data with a combination of small sample size both at level-1 and level-2. The results showed that the REML performed better than the BayesW, which showed overall better performance than the BayesN, in terms of convergence, bias, and coverage in some small sample scenarios. Therefore, based on the results of the present study, it is recommended to use the REML when adapting the two-level linear multilevel model and analyzing real-world data with small samples.

Reliability generalization meta-analysis of orthorexia nervosa using the ORTO-11/12/15/R scale in all populations and language versions

BackgroundThe ORTO scale was developed in 2004 as a self-report questionnaire to assess symptoms of orthorexia nervosa (ON). ON is an unhealthy preoccupation with eating healthy food. The scale aims to measure obsessive attitudes and behaviors related to the selection, purchase, preparation, and consumption of pure, healthy food. Since its development, the ORTO-15 has been adapted into several shorter versions. The objective was to conduct a reliability generalization meta-analysis of the ORTO scale and its variant versions in all populations and languages.MethodsA systematic literature search was conducted to identify studies reporting the internal consistency of ORTO. Random-effect models were used to evaluate summary statistics of reliability coefficients, weighting the coefficients by the inverse variance using the restricted maximum likelihood method. The heterogeneity among the reliability coefficients was evaluated and assessed using numerous statistical metrics. The tau (τ), tau2 (τ2), I2, H2, R2, df, and the Q-statistic are among those obtained. Meta-regression analyses were used to examine moderators such as age and sex.ResultsTwenty-one studies (k = 21) involving 11,167 participants (n = 11,167) were analyzed. The overall effect estimate on internal consistency was 0.59 (95% CI 0.49–0.68), with a minimum reliability coefficient of 0.23 and a maximum reliability coefficient of 0.83. The heterogeneity statistics were found to have an I2 of 99.31%, which suggested high heterogeneity owing to a decrease in the confidence interval (95% CI) and an increase in variability. Sensitivity analysis revealed that a few studies strongly influenced the overall estimate. Egger’s test suggested possible publication bias. Neither age nor sex significantly moderated reliability via meta-regression.ConclusionsThe ORTO scale has a relatively low pooled reliability coefficient. Alternative ON assessment tools with enhanced psychometric properties are needed. Clinicians should not base diagnoses or treatment decisions on ORTO alone. Comprehensive psychiatric assessment is essential for accurate ON evaluation.

Do statistical heterogeneity methods impact the results of meta- analyses? A meta epidemiological study.

Orthodontic systematic reviews (SRs) use different methods to pool the individual studies in a meta-analysis when indicated. However, the number of studies included in orthodontic meta-analyses is relatively small. This study aimed to evaluate the direction of estimate changes of orthodontic meta-analyses (MAs) using different between-study variance methods considering the level of heterogeneity when few trials were pooled. Search and study selection: Systematic reviews (SRs) published over the last three years, from the 1st of January 2020 to the 31st of December 2022, in six main orthodontic journals with at least one MA pooling five or lesser primary studies were identified. Data collection and analysis: Data were extracted from each eligible MA, which was replicated in a random effect model using DerSimonian and Laird (DL), Paule-Mandel (PM), Restricted maximum-likelihood (REML), Hartung Knapp and Sidik Jonkman (HKSJ) methods. The results were reported using median and interquartile range (IQR) for continuous data and frequencies for categorical data and analyzed using non-parametric tests. The Boruta algorithm was used to assess the significant predictors for the significant change in the confidence interval between the different methods compared to the DL method, which was only feasible using the HKSJ method. 146 MAs were included, most applying the random effect model (n = 111; 76%) and pooling continuous data using mean difference (n = 121; 83%). The median number of studies was three (range 2, 4), and the overall statistical heterogeneity (I2 ranged from 0 to 99% with a median of 68%). Close to 60% of the significant findings became non-significant when HKSJ was applied compared to the DL method and when the heterogeneity was present I2>0%. On the other hand, 30.43% of the non-significant meta-analyses using the DL method became significant when HKSJ was used when the heterogeneity was absent I2 = 0%. Orthodontic MAs with few studies can produce different results based on the between-study variance method and the statistical heterogeneity level. Compared to DL, HKSJ method is overconservative when I2 is greater than 0% and may result in false positive findings when the heterogeneity is absent.

Genetic association between fat-to-protein ratio and traits of economic interest in early lactation Holstein cows in Brazil.

The aims of this study were to estimate the genetic parameters for fat-to-protein ratio (F:P) within the first 90days of lactation and to examine their genetic associations with daily milk yield (MY), somatic cell score (SCS), and calving interval between the first and second calving (IFSC) and between the second and third calving (ISTC) during the first three lactations of Holstein cows. We utilized 200,626 production-related data officially recorded from 77,436 cows milked two or three times a day from 2012 to 2022, sourced from the Holstein Cattle Breeders Association of Paraná State, Brazil. The (co)variance components were estimated using animal models, adopting the restricted maximum likelihood (REML) method with single-trait analysis (for heritability and repeatability) and two-trait analysis (for genetic and phenotypic correlations), per lactation. Regardless of lactation number, heritability estimates were relatively low, ranging from 0.08 ± 0.005 to 0.10 ± 0.003 for F:P; 0.08 ± 0.01 to 0.18 ± 0.005 for MY; 0.04 ± 0.01 to 0.07 ± 0.004 for SCS; and 0.03 ± 0.01 for both IFSC and ISTC. Repeatability estimates within the same lactation were low for F:P (ranging from 0.17 ± 0.002 to 0.19 ± 0.03), high for MY (between 0.50 ± 0.003 and 0.53 ± 0.002), and moderate to high for SCS (between 0.39 ± 0.003 and 0.44 ± 0.004). Genetic correlations between F:P and MY ranged from -0.26 ± 0.03 to -0.15 ± 0.02; F:P and SCS, from -0.06 ± 0.03 to -0.03 ± 0.08; F:P and IFSC, 0.31 ± 0.01; F:P and ISTC, 0.20 ± 0.01; MY and IFSC, 0.24 ± 0.05; and MY and ISTC, 0.13 ± 0.08. The fat-to-protein ratio during early lactation showed low genetic variability, regardless of lactation number. Furthermore, it was genetically correlated with MY, IFSC, and ISTC, although there is an antagonistic and unfavorable correlation between traits that can limit genetic progress.

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.

Decompressive Craniectomy versus Craniotomy for Acute Subdural Hematoma: Updated meta-analysis of real-world clinical outcome after RESCUE-ASDH trial.

The RESCUE-ASDH trial found that disability and quality-of-life outcomes were similar between craniotomy and decompressive craniectomy for traumatic acute subdural hematoma, contrasting previous literature. This meta-analysis aims to validate the applicability of RESCUE-ASDH results using real-world data in acute subdural hematoma patients. We searched Chocrane, Embase, and MEDLINE for relevant articles reporting clinical outcomes of craniotomy and decompressive craniectomy. Meta-analysis utilized R software with the restricted maximum likelihood method for random-effects meta-analyses, presenting odds ratios and 95% confidence intervals with Hartung-Knapp-Sidik-Jonkman adjustment for heterogeneity. Besides RESCUE-ASDH, 5 retrospective studies were included, spanning 2006-2016. A total of 961 patients with traumatic ASDH were included in this study (Craniotomy = 467; Decompressive craniotomy = 494). The pooled analysis of retrospective studies showed no significant difference in poor clinical outcomes between the two groups (OR 0.59, 95% CI, 0.32 to 1.10). These findings align with the RESCUE-ASDH trial (OR 0.84, 95% CI, 0.58 to 1.23). Mortality rate was significant higher in patients undergoing craniectomy in pooled result of retrospective studies (OR 0.59, 95% CI, 0.32 to 1.10). In RESCUE-ASDH trial, reoperation rate was higher in the craniotomy group, but the pooled result of retrospective did not show significant difference between the craniotomy and craniectomy group. This real-world evidence confirms the RESCUE-ASDH trial results. Both craniotomy and decompressive craniectomy yielded similar disability and quality-of-life outcomes for traumatic acute subdural hematoma patients. Level 2, Systematic and meta-analysis.

Restricted estimators of repeated measurements model for unbalanced data

The model of one-way repeated measurements for imbalanced data, as the number of explanations are not the same at some levels, is the subject of this research. We used two methods to estimate the model parameters: the restricted maximum likelihood method and maximum likelihood approach, and we considered some of their characteristics. The Experiment’s practical research goal is to determine how the experimental elements and their interactions affect date palm productivity. The Experiment included the factor of irrigation method with three treatments: drip irrigation, basin irrigation, and the regular tidal method, while the irrigation interval factor included three treatments: 3, 6 and 9 days.

Assessing Water Quality Spatial Heterogeneity from Multiple Pollution Sources in the Boung Cheung Ek Wetland, Phnom Penh, Cambodia

Phnom Penh, the capital of Cambodia, as with many other world megacities, is exposed to multiple major ecological and environmental hazards. Without a proper wastewater treatment facility, it is difficult for local residents to obtain a health-compliant water supply. In this study, a hybrid aggregation method using principal component analysis (PCA) and weighted means was used to calculate a water quality index (WQI) to map the water quality of the entire Boeung Cheung Ek (BCE) wetland region. We used Universal Kriging to map eight water quality parameters: DO, pH, TDS, F, Cl, NO3−, PO43−, and NH4+. The restricted maximum likelihood method was used for model fitting. Data were collected from groundwater and surface water for different rainfall seasons between March 2017 and February 2018. The principal component analysis (PCA) used to compute a water quality index (WQI) is based on the resulting dimensions of the highest variation among all water quality parameters. The results show that the northern part of the study area has a worse water quality than the southern region, which is caused by the discharge of municipal wastewater directly into the BCE wetland area. The results for different rainfall seasons also show that groundwater has a relatively better quality than surface water. The results of this analysis can serve as a supplementary study to support sustainable development goals because they might confirm the need for a wastewater treatment facility being under construction at the time of writing this article with funding from the Japan International Cooperation Agency (JICA).

Unraveling phenotypic variance in metabolic syndrome through multi-omics.

Complex multi-omics effects drive the clustering of cardiometabolic risk factors, underscoring the imperative to comprehend how individual and combined omics shape phenotypic variation. Our study partitions phenotypic variance in metabolic syndrome (MetS), blood glucose (GLU), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and blood pressure through genome, transcriptome, metabolome, and exposome (i.e., lifestyle exposome) analyses. Our analysis included a cohort of 62,822 unrelated individuals with white British ancestry, sourced from the UK biobank. We employed linear mixed models to partition phenotypic variance using the restricted maximum likelihood (REML) method, implemented in MTG2 (v2.22). We initiated the analysis by individually modeling omics, followed by subsequent integration of pairwise omics in a joint model that also accounted for the covariance and interaction between omics layers. Finally, we estimated the correlations of various omics effects between the phenotypes using bivariate REML. Significant proportions of the MetS variance were attributed to distinct data sources: genome (9.47%), transcriptome (4.24%), metabolome (14.34%), and exposome (3.77%). The phenotypic variances explained by the genome, transcriptome, metabolome, and exposome ranged from 3.28% for GLU to 25.35% for HDL-C, 0% for GLU to 19.34% for HDL-C, 4.29% for systolic blood pressure (SBP) to 35.75% for TG, and 0.89% for GLU to 10.17% for HDL-C, respectively. Significant correlations were found between genomic and transcriptomic effects for TG and HDL-C. Furthermore, significant interaction effects between omics data were detected for both MetS and its components. Interestingly, significant correlation of omics effect between the phenotypes was found. This study underscores omics' roles, interaction effects, and random-effects covariance in unveiling phenotypic variation in multi-omics domains.

Modeling the Yield of Glycine max (L.) Merrill Using Mixture Process Variable Model within an Optimal Split-Plot Design

A mixture design has become famous in statistical modeling in a mixture process variable experiment owing to its usefulness in modeling the blending surface that predicts the response of any mixture empirical. The mixture blends included manure from cows, chickens, goats, and sheep while the process variable was seeding rate of Glycine max seeds and the pH of the soil. The effect of variety of the seed used was established through variation of seeds per acre with uniform application of organic and inorganic fertilizer. This study's main aim was to determine the best desirable split-plot design for performing the Glycine max experiment with the settings mixture-process variables. The split-plot design (SPD) was used to solve the problem of restricted randomization. It constituted a simplex centroid design (SCD) of four design points of mixture components and factorial design with a central composite design (CCD) of the process variable. We formulated a new Scheffe model and the proposed design for SPD for the combined second-order mixture process variable model with CCD. We used the restricted maximum likelihood method to approximate values for parameter models within the SPD. We also found the effect of mixture component at vertices of components of the mixture plus with interaction effect between mixture and process variable to have the highest impact on the growth and pod development of Glycine max. The optimum total yield of Glycine max for variety R184 and Blyvoor used in Bushel per acre was 180.53 and 219. 217, respectively on the Whole Plot with a pH of soil being 5.4. The mean response maximum optimum yield for the total number of pods per plant and seeds per pod of Glycine max were found to be 32.30 and 2.331, respectively. We recommend using SPDs in experiments involving mixture settings formulations to measure the interaction effects of both the mixture components and the processing conditions like a pH of the soil and seeding rate.

A REML method for the evidence-splitting model in network meta-analysis.

Checking for possible inconsistency between direct and indirect evidence is an important task in network meta-analysis. Recently, an evidence-splitting (ES) model has been proposed, that allows separating direct and indirect evidence in a network and hence assessing inconsistency. A salient feature of this model is that the variance for heterogeneity appears in both the mean and the variance structure. Thus, full maximum likelihood (ML) has been proposed for estimating the parameters of this model. Maximum likelihood is known to yield biased variance component estimates in linear mixed models, and this problem is expected to also affect the ES model. The purpose of the present paper, therefore, is to propose a method based on residual (or restricted) maximum likelihood (REML). Our simulation shows that this new method is quite competitive to methods based on full ML in terms of bias and mean squared error. In addition, some limitations of the ES model are discussed. While this model splits direct and indirect evidence, it is not a plausible model for the cause of inconsistency.

Glme: An R package for mixed effects model inference by the generalized approach

This article documents the use of the glme package, which performs generalized inferences based on exact distributions and exact probability statements, provided by such papers as Weerahandi and Yu (2020) under the widely used Compound Symmetric Covariance structure. The underlying model and comparative results of the simulation study for the model with the counterparts are the maximum likelihood method and restricted maximum likelihood method, and illustrative examples; desired future research is also provided.

Elucidation of the genetic determination of clutch traits in Chinese local chickens of the Laiwu Black breed

BackgroundEgg laying rate (LR) is associated with a clutch, which is defined as consecutive days of oviposition. The clutch trait can be used as a selection indicator to improve egg production in poultry breeding. However, little is known about the genetic basis of clutch traits. In this study, our aim was to estimate genetic parameters and identify quantitative trait single nucleotide polymorphisms for clutch traits in 399 purebred Laiwu Black chickens (a native Chinese breed) using a genome-wide association study (GWAS).MethodsIn this work, after estimating the genetic parameters of age at first egg, body weight at first egg, LR, longest clutch until 52 week of age, first week when the longest clutch starts, last week when the longest clutch ends, number of clutches, and longest number of days without egg-laying until 52 week of age, we identified single nucleotide polymorphisms (SNPs) and potential candidate genes associated with clutch traits in Laiwu Black chickens. The restricted maximum likelihood method was used to estimate genetic parameters of clutch pattern in 399 Laiwu Black hens, using the GCTA software.ResultsThe results showed that SNP-based heritability estimates of clutch traits ranged from 0.06 to 0.59. Genotyping data were obtained from whole genome re-sequencing data. After quality control, a total of 10,810,544 SNPs remained to be analyzed. The GWAS revealed that 421 significant SNPs responsible for clutch traits were scattered on chicken chromosomes 1–14, 17–19, 21–25, 28 and Z. Among the annotated genes, NELL2, SMYD9, SPTLC2, SMYD3 and PLCL1 were the most promising candidates for clutch traits in Laiwu Black chickens.ConclusionThe findings of this research provide critical insight into the genetic basis of clutch traits. These results contribute to the identification of candidate genes and variants. Genes and SNPs potentially provide new avenues for further research and would help to establish a framework for new methods of genomic prediction, and increase the accuracy of estimated genetic merit for egg production and clutch traits.

Genetic relationships between reproductive and production traits in Jersey crossbred cattle

The study aimed to estimate the genetic parameters of different reproductive traits namely age at first calving (AFC), calving interval (CI), days open (DO) and number of service per conception (NSPC) and their associations with productive traits including 305-day milk yield (305DMY), total lactation milk yield (TLMY) and lactation length (LL) of Jersey crossbred cattle maintained at Kalyani, Nadia, West Bengal, India. Genetic parameters of reproductive traits and their correlations with productive traits were estimated by Restricted Maximum Likelihood method and Bayesian approach. Using both analytical approaches, the estimates of heritability for AFC, CI, DO and NSPC ranged from 0.12 −0.15, 0.05–0.08, 0.08–0.09 and 0.04–0.06, respectively. Low proportion of variances associated with permanent environmental effect of animals (c2 effect) were detected for CI (0.08–0.10), DO (0.09–0.11) and NSPC (0.05–0.06) in both the methods. Repeatability measures for all the reproductive traits considered in this study were low to moderate in nature, which ranged from 0.09 to 0.17. Genetic correlations between different reproductive traits were positive and low (0.05) to high (0.98) in magnitude except AFC-NSPC. Low and negative genetic correlations of AFC with 305DMY and TLMY were favourable and indicated animals with high milk yield had early age of maturity. Positive genetic correlations between CI, DO and NSPC with all production traits implied the antagonism relationships among these traits, therefore in any breeding program for improvement of production traits via selection, the reproductive traits should be taken into account as well.