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Objective: This study aimed to identify the optimal single nucleotide polymorphism (SNP) panel density for accurate imputation in the Korean native chicken (KNC) and Yeonsan Ogye (YO) populations. The primary focus was on evaluating how the reference population size and SNP density influence imputation performance and accuracy.Methods: Data were collected from five purebred lines of KNC and the YO population, comprising a total of 256 KNC and 199 YO chickens. Imputed genotype ratio and accuracy were evaluated across various scenarios using SNP densities of 2.5K, 5K, 10K, and 50K in both populations. Additionally, for the YO dataset, reference population sizes of 50, 100, and 150 were analyzed to assess their impact on imputation outcomes.Results: Higher SNP densities notably improved imputation performance. Specifically, when SNP panel density reached 10K or greater, the ratio of imputed SNPs exceeded 70% and the accuracy increased substantially, regardless of the reference population size. However, imputation efficiency decreased markedly when either the reference or test population size was around 50 individuals.Conclusion: A test SNP density of at least 10K was determined to be essential for accurate genotype imputation. Additionally, imputation efficiency was observed to decline when either the reference or test population included around 50 individuals. These findings provide important data that can guide the genetic improvement of indigenous livestock populations.

Background Size of reference population is a crucial factor affecting the accuracy of prediction of the genomic estimated breeding value (GEBV). There are few studies in beef cattle that have compared accuracies achieved using real data to that achieved with simulated data and deterministic predictions. Thus, extent to which traits of interest affect accuracy of genomic prediction in Japanese Black cattle remains obscure. This study aimed to explore the size of reference population for expected accuracy of genomic prediction for simulated and carcass traits in Japanese Black cattle using a large amount of samples. Results A simulation analysis showed that heritability and size of reference population substantially impacted the accuracy of GEBV, whereas the number of quantitative trait loci did not. The estimated numbers of independent chromosome segments ( M e ) and the related weighting factor ( w ) derived from simulation results and a maximum likelihood (ML) approach were 1900–3900 and 1, respectively. The expected accuracy for trait with heritability of 0.1–0.5 fitted well with empirical values when the reference population comprised > 5000 animals. The heritability for carcass traits was estimated to be 0.29–0.41 and the accuracy of GEBVs was relatively consistent with simulation results. When the reference population comprised 7000–11,000 animals, the accuracy of GEBV for carcass traits can range 0.73–0.79, which is comparable to estimated breeding value obtained in the progeny test. Conclusion Our simulation analysis demonstrated that the expected accuracy of GEBV for a polygenic trait with low-to-moderate heritability could be practical in Japanese Black cattle population. For carcass traits, a total of 7000–11,000 animals can be a sufficient size of reference population for genomic prediction.

Objective: A genomic region associated with a particular phenotype is called quantitative trait loci (QTL). To detect the optimal F2 population size associated with QTLs in native chicken, we performed a simulation study on F2 population derived from crosses between two different breeds.Methods: A total of 15 males and 150 females were randomly selected from the last generation of each F1 population which was composed of different breed to create two different F2 populations. The progenies produced from these selected individuals were simulated for six more generations. Their marker genotypes were simulated with a density of 50K at three different heritability levels for the traits such as 0.1, 0.3, and 0.5. Our study compared 100, 500, 1,000 reference population (RP) groups to each other with three different heritability levels. And a total of 35 QTLs were used, and their locations were randomly created.Results: With a RP size of 100, no QTL was detected to satisfy Bonferroni value at three different heritability levels. In a RP size of 500, two QTLs were detected when the heritability was 0.5. With a RP size of 1,000, 0.1 heritability was detected only one QTL, and 0.5 heritability detected five QTLs. To sum up, RP size and heritability play a key role in detecting QTLs in a QTL study. The larger RP size and greater heritability value, the higher the probability of detection of QTLs.Conclusion: Our study suggests that the use of a large RP and heritability can improve QTL detection in an F2 chicken population.

Inner Mongolia Cashmere Goats (IMCGs) are famous for its cashmere quality and it's a unique genetic resource in China. Therefore, it is necessary to use genomic selection to improve the accuracy of selection for fleece traits in Inner Mongolia cashmere goats. The aim of this study was to determine the effect of methods (GBLUP, BayesA, BayesB, Bayesian LASSO, Bayesian Ridge Region) and the reference population size on accuracy of genomic selection in IMCGs. This study fully utilizes the pedigree and phenotype records of fleece traits in 2255 individuals, genotype of 50794 SNPs after quality control, and environmental data to perform genomic selection of fleece traits. Then GBLUP and Bayes series methods (BayesA, BayesB, Bayesian LASSO, Bayesian Ridge Region) were used to perform estimates of genetic parameter and genomic breeding value. And the accuracy of genomic estimated breeding value (GEBV) is evaluated using the five-fold cross validation method. And the analysis of variance and multiple comparison methods were used to determine the best method for genomic selection in fleece traits of IMCGs. Further the different reference population sizes (500, 1000, 1500, and 2000) was set. Then the best method was applied to estimate genome breeding values, and evaluate the impact of reference population sizes on the accuracy of genome selection for fleece traits in IMCGs. It was found that the genomic prediction accuracy for each fleece trait in IMCGs by GBLUP method is highest, and it is significantly higher than that obtained by Bayesian method. The accuracy of breeding value estimation is 58.52% -68.49%. Also, it was found that the size of the reference population has a significant impact on the accuracy of genome prediction of fleece traits. When the reference population size is 2000, the accuracy of genomic prediction for each fleece trait is significantly higher than other levels, with accuracy of 55.47% -67.87%. This provides a theoretical basis for design a reasonable genome selection plan for Inner Mongolia cashmere goats in the later stag.

The present study aimed to elucidate the population structure and genetic diversity along with the estimation of genealogical parameters in Vrindavani cattle using pedigree data. The study was based on pedigree data on 12,718 animals, spread across multiple generations during a 52-year period (between 1971 and 2023). The pedigree data was used to estimate different population genealogical parameters including the generation interval; pedigree completeness; rate and level of inbreeding; effective population size; and parameters characterizing the probabilities of gene origin. The ENDOG program was used for estimation of different parameters while using population after 2010 as reference cohort. The results revealed the maximum number of generations (MG) to be 13, while the numbers of completed (CG) and equivalent generations (EqG) were 3.23 and 1.95, respectively. The mean generation interval for the population was 6.9 years. The average inbreeding coefficient of animals in the whole and reference population was 1.11 and 3.44%, respectively; with 0.68% rate of inbreeding per generation. The average additive relationship among all the animals and those in the reference population was 1.16 and 5.49%, respectively. The average effective population sizes for the maximum, equivalent, and complete generations were 115.56, 56.42, and 46.02, respectively. The effective population size on the basis of regression and log-regression on birth date was 77.40 and 71.24, respectively. The probabilities of gene origin were estimated by the effective number of founders (fe) and ancestors (fa), which was 115 and 78, respectively. The fe/fa ratio in the reference population was 1.20, indicating that occasional bottlenecks may have occurred in the population. The analysis revealed a loss of 5.3% of total heterozygosity as compared to base population, though significant variability exists in the latest generations. The results revealed that considerable genetic variability exists within the population that may be exploited through appropriate breed improvement programs targeting various economic traits.

In a collaboration between the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) and the Canadian Health Measures Survey (CHMS), we determined reference value distributions using an a priori approach and created a comprehensive database of age- and sex-stratified reference intervals for clinically relevant hematologic parameters in a large household population of children and adults. The CHMS collected data and blood samples from 11 999 respondents aged 3-79 years. Hematology markers were measured with either the Beckman Coulter HmX or Siemens Sysmex CA-500 Series analyzers. After applying exclusion criteria and removing outliers, we determined statistically relevant age and sex partitions and calculated reference intervals, including 90% CIs, according to CSLI C28-A3 guidelines. Hematology marker values showed dynamic changes from childhood into adulthood as well as between sexes, necessitating distinct partitions throughout life. Most age partitions were necessary during childhood, reflecting the hematologic changes that occur during growth and development. Hemoglobin, red blood cell count, hematocrit, and indices (mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration) increased with age, but females had lower hemoglobin and hematocrit starting at puberty. Platelet count gradually decreased with age and required multiple sex partitions during adolescence and adulthood. White blood cell count remained relatively constant over life, whereas fibrinogen increased slightly, requiring distinct age and sex partitions. The robust dataset generated in this study has allowed observation of dynamic biological profiles of several hematology markers and the establishment of comprehensive age- and sex-specific reference intervals that may contribute to accurate monitoring of pediatric, adult, and geriatric patients.

Background The allele frequency spectrum (AFS) consists of counts of the number of single nucleotide polymorphism (SNP) loci with derived variants present at each given frequency in a sample. Multiple approaches have recently been developed for parameter estimation and calculation of model likelihoods based on the joint AFS from two or more populations. We conducted a simulation study of one of these approaches, implemented in the Python module δaδi, to compare parameter estimation and model selection accuracy given different sample sizes under one- and two-population models. Results Our simulations included a variety of demographic models and two parameterizations that differed in the timing of events (divergence or size change). Using a number of SNPs reasonably obtained through next-generation sequencing approaches (10,000 - 50,000), accurate parameter estimates and model selection were possible for models with more ancient demographic events, even given relatively small numbers of sampled individuals. However, for recent events, larger numbers of individuals were required to achieve accuracy and precision in parameter estimates similar to that seen for models with older divergence or population size changes. We quantify i) the uncertainty in model selection, using tools from information theory, and ii) the accuracy and precision of parameter estimates, using the root mean squared error, as a function of the timing of demographic events, sample sizes used in the analysis, and complexity of the simulated models. Conclusions Here, we illustrate the utility of the genome-wide AFS for estimating demographic history and provide recommendations to guide sampling in population genomics studies that seek to draw inference from the AFS. Our results indicate that larger samples of individuals (and thus larger AFS) provide greater power for model selection and parameter estimation for more recent demographic events.

Abstract Context Reliable reference values for thyroid ultrasound measurements are essential to effectively guide individual diagnostics and direct population-level health care measures, such as iodine fortification programs. However, the latest reference values for total thyroid volume (Tvol) provided by the World Health Organization (WHO) in 2004 only apply to the 6- to 12-year-old age group and are limited to countries with a long history of iodine sufficiency, which does not reflect the situation in most European countries, including Germany. Objective This study aims to derive up-to-date thyroid volume ultrasound reference values in German children and adolescents. Methods Data from the baseline assessment of a nationwide study in German children and adolescents (KiGGS) conducted between 2003 and 2006 were used to determine sex-specific reference values for Tvol in thyroid-healthy participants aged 6 to 17 years by age and body surface area according to the lambda-mu-sigma method. Results Data from 5559 participants were available for reference chart construction (2509 girls [45.1%]). On average, the 97th percentile is 33.4% and 28.5% higher than the corresponding WHO reference values for boys and girls, respectively. These findings are consistent with most other studies in German and European children and adolescents at a similar time of investigation. Notably, the sample used for this study was iodine-sufficient according to WHO criteria. Conclusion The reference values provided by the WHO are overly conservative for this population and could potentially apply to other European countries with a similar history of iodine supply.

The identification of somatic growth, through reference curves, can be used to create strategies and public policies to reduce public health problems such as malnutrition and obesity and to identify underweight, overweight and obesity. The purpose of this systematic review was to identify studies providing reference growth curves for weight status in children and adolescents. A systematic search was conducted in eight databases and in gray literature (Google scholar). To assess the risk of bias/methodological quality of studies, the National Institutes of Health (NIH) Quality Assessment Tool for Observational Cohort and Cross-sectional Studies (NHLBI) was used. Overall, 86 studies that met the inclusion criteria were included. Through the values   of reference growth curves for the identification of underweight, overweight and obesity, it was possible to verify that there is great variability among percentiles for the identification of underweight, overweight and obesity. The most prevalent percentiles for underweight were P3 and P5; for overweight, the most prevalent was P85 and the most prevalent percentiles for obesity were P95 and P97. The most prevalent anthropometric indicators were Body Mass Index (BMI), Waist Circumference (WC), Body Mass (BM) for age and height for age. Conclusion: Such data can demonstrate that the optimal growth must be reached, through the standard growth curves, but that the reference curves demonstrate a cut of the population growth, raising possible variables that can influence the optimal growth, such as an increase in the practice of physical activities and an awareness of proper nutrition.