Genetic parameter estimates for body conformation traits using composite index, principal component, and factor analysis

Bayesian fine-mapping and Mendelian randomization leveraging expression quantitative trait loci reveal novel candidate causal genes for body conformation traits in cattle

Cattle body size measurements constitute the conformation traits that facilitate their production, fertility, and longevity status. Prioritizing functional variants and causal genes of conformation traits is essential for understanding their genetic basis. In this study, we conducted single-trait and multitrait GWAS for 20 body conformation traits using imputed sequence data in 7,674 Chinese Holstein individuals and identified 27 QTL regions. Leveraging these QTL regions, we performed multitrait Bayesian fine-mapping to identify 30 independent credible sets of putative causal variants. Incorporating GWAS and cis-acting expression QTL data, Mendelian randomization was used to infer 153 putative causal gene-trait relationships. The previously reported genes, such as CCND2, TMTC2, and NRG3, were confirmed in our study. Of note, several novel candidate causal genes were also identified, such as C1R, RIMS1, SERPINB8, NETO2, TTYH3, TTC3, ANAPC4, and PSMD13. Our results provide new insights into the regulatory mechanisms of body conformation traits in cattle.

Multi-trait phenotypic modeling through factor analysis and bayesian network learning to develop latent reproductive, body conformational, and carcass-associated traits in admixed beef heifers

Despite high-throughput and large-scale phenotyping becoming easier, interpretation of such data in cattle production remains challenging due to the complex and highly correlated nature of many traits. Underlying biological traits (UBT) of economic importance are defined by a subset of easy-to-measure traits, leading to challenges in making appropriate selection decisions on them. Research on UBT in beef cattle is limited. In this study, the phenotypic data of admixed beef heifers (n = 336) for reproductive, body conformation, and carcass-related traits (traits, t = 35) were used to identify latent variables from factor analysis (FA) that can be characterized as UBT. Given sample size constraints for carcass (n = 161) and other body size-related traits (n = 336), two models were explored. In Model 1, all individual traits were considered (n = 161), while in Model 2, the dataset was split into body size (n = 336) and carcass (n = 161) traits to maximize available heifers per dataset. A combination of FA and Bayesian network (BN) learning was adopted to develop UBT and infer BN structure for subsequent analyses. All heifers (n = 336) were genotyped using GeneSeek Genomic Profiler 150K for Beef Cattle. Following quality checks, 117,373 autosomal SNP markers were retained and used for genomic estimated breeding values (gEBV) in BN learning steps. Using exploratory and confirmatory FA, Body Size (BS) and Body Composition (BC) were identified as UBT for Model 1, explaining 14 phenotypic traits (t = 14). For Model 2, BS, Ovary Size, and Yield Grade (YG) were identified as UBT, explaining 12 phenotypic traits (t = 12). When using gEBV, the causal network structure inferred showed BS contributed to BC in Model 1 and to Ovary Size in Model 2. Therefore, a structure equation-based approach should be used in subsequent modeling for these traits. From Model 2, YG should be modeled univariately. This study is the first to identify UBT in growing admixed heifers using body size, conformation, and carcass traits. We also identified that BC and YG did not explain intra-muscular fat and body density, indicating these two traits should also be modeled univariately.

Simultaneous monitoring of two comprehensive quality evaluation indexes of frozen-thawed beef meatballs using hyperspectral imaging and multi-task convolutional neural network

The quality of beef meatballs during repeated freeze-thaw (F-T) cycles was assessed by multiple indicators. This study introduced a novel quality evaluation method using hyperspectral imaging (HSI) and multi-task learning. Seventeen quality indicators were analyzed to assess the impact of F-T cycles. Subsequently, a comprehensive quality index (CQI) and a comprehensive weight index (CWI) were constructed from 11 key indicators via factor analysis. By integrating HSI data from 150 samples with multi-task convolutional neural network (MT-CNN), the feasibility of simultaneous monitoring of CQI and CWI of the beef meatballs was explored. The results demonstrated that MT-CNN achieved superior predictions for CQI (RMSEp = 1.24, R2 = 0.94) and CWI (RMSEp = 20.436, R2 = 0.94) compared to traditional machine learning and single-task CNN approaches. Furthermore, the deterioration trends of beef meatballs during multiple F-T cycles were effectively visualized. Thus, the integration of HSI and MT-CNN enabled efficient prediction of comprehensive evaluation indexes for beef meatballs, contributing to their quality control.

Genome-Wide Association Study as an Efficacious Approach to Discover Candidate Genes Associated with Body Linear Type Traits in Dairy Cattle

Body shape traits are very important and play a crucial role in the economic development of dairy farming. By improving the accuracy of selection for body size traits, we can enhance economic returns across the dairy industry and on farms, contributing to the future profitability of the dairy sector. Registered body conformation traits are reliable and cost-effective tools for use in national cattle breeding selection programs. These traits are significantly related to the production, longevity, mobility, health, fertility, and environmental adaptation of dairy cows. Therefore, they can be considered indirect indicators of economically important traits in dairy cows. Utilizing efficacious genetic methods, such as genome-wide association studies (GWASs), allows for a deeper understanding of the genetic architecture of complex traits through the identification and application of genetic markers. In the current review, we summarize information on candidate genes and genomic regions associated with body conformation traits in dairy cattle worldwide. The manuscript also reviews the importance of body conformation, the relationship between body conformation traits and other traits, heritability, influencing factors, and the genetics of body conformation traits. The information on candidate genes related to body conformation traits provided in this review may be helpful in selecting potential genetic markers for the genetic improvement of body conformation traits in dairy cattle.

A new comprehensive quantitative index for the assessment of essential amino acid quality in beef using Vis-NIR hyperspectral imaging combined with LSTM

The quality of beef is usually predicted by measuring a single index rather than a comprehensive index. To precisely determine the essential amino acid (EAA) contents in 360 beef samples, the feasibility of optimized spectral detection techniques based on the comprehensive EAA index (CEI) and comprehensive weight index (CWI) constructed by factor analysis was explored. Two-dimensional correlation spectroscopy (2D-COS) was used to analyse the mechanisms of spectral peak shifts in complex disturbance systems with CEI and CWI contents, and 15 sensitive feature variables were extracted to establish a quantitative analysis model of a long short-term memory network (LSTM). The results indicated that 2D-COS had good predictive performance in both CEI-LSTM (R2P of 0.9095 and RPD of 2.76) and CWI-LSTM (R2P of 0.8449 and RPD of 2.45), which reduced data information by 88%. This indicates that utilizing 2D-COS can eliminate collinearity and redundant information among variables while achieving data dimensionality reduction and simplification of calibration models. Furthermore, a spatial distribution map of the comprehensive EAA content was generated by combining the optimal prediction model. This study demonstrated that the comprehensive index method furnishes a new approach to rapidly evaluate EAA content.

Evaluation of accuracies of genomic predictions for body conformation traits in Korean Holstein

OBJECTIVE

This study aimed to assess the genetic parameters and accuracy of genomic predictions for twenty-four linear body conformation traits and overall conformation scores in Korean Holstein dairy cows.

METHODS

A dataset of 2,206 Korean Holsteins was collected, and genotyping was performed using the Illumina Bovine 50K single nucleotide polymorphism (SNP) chip. The traits investigated included body traits (stature, height at front end, chest width, body depth, angularity, body condition score, and locomotion), rump traits (rump angle, rump width, and loin strength), feet and leg traits (rear leg set, rear leg rear view, foot angle, heel depth, and bone quality), udder traits (udder depth, udder texture, udder support, fore udder attachment, front teat placement, front teat length, rear udder height, rear udder width, and rear teat placement), and overall conformation score. Accuracy of genomic predictions was assessed using the single-trait animal model genomic best linear unbiased prediction method implemented in the ASReml-SA v4.2 software.

RESULTS

Heritability estimates ranged from 0.10 to 0.50 for body traits, 0.21 to 0.35 for rump traits, 0.13 to 0.29 for feet and leg traits, and 0.05 to 0.46 for udder traits. Rump traits exhibited the highest average heritability (0.29), while feet and leg traits had the lowest estimates (0.21). Accuracy of genomic predictions varied among the twenty-four linear body conformation traits, ranging from 0.26 to 0.49. The heritability and prediction accuracy of genomic estimated breeding value (GEBV) for the overall conformation score were 0.45 and 0.46, respectively. The GEBVs for body conformation traits in Korean Holstein cows had low accuracy, falling below the 50% threshold.

CONCLUSION

The limited response to selection for body conformation traits in Korean Holsteins may be attributed to both the low heritability of these traits and the lower accuracy estimates for GEBVs. Further research is needed to enhance the accuracy of GEBVs and improve the selection response for these traits.

Genetic Parameters of Semen Traits and Their Correlations with Conformation Traits in Chinese Holstein Bulls

The elite bull plays an extremely important role in the genetic progression of the dairy cow population. The previous results indicated the potential positive relationship of large scrotal circumference (SC) with improved semen volume, concentration, and motility. In order to improve bull's semen quantity and quality by selection, it is necessary to estimate the genetic parameters of semen traits and their correlations with other conformation traits such as SC that could be used for an indirect selection. In this study, the genetic parameters of seven semen traits (n = 66,260) and nine conformation traits (n = 3,642) of Holstein bulls (n = 453) were estimated by using the bivariate repeatability animal model with the average information-restricted maximum likelihood (AI-REML) approach. The results showed that the estimated heritabilities of semen traits ranged from 0.06 (total number of motile sperm, TNMS) to 0.37 (percentage of abnormal sperm, PAS) and conformation traits ranged from 0.23 (pin width, PW) to 0.69 (hip height, HH). The highest genetic correlations were found between semen volume per ejaculation (SVPE), semen concentration per ejaculation (SCPE), total number of sperm (TNS), and TNMS traits that were 0.97, 0.98, 1.00, and 0.99, respectively. Phenotypic correlations between SC and SVPE, SCPE, TNS, and TNMS were 0.35, 0.35, 0.48, and 0.42, respectively. In summary, the moderate or high heritability of semen traits indicates that genetic improvement of semen quality by selection is feasible, where SC could be a useful trait for indirect selection or as correlated information to improve semen quantity and production in the practical bull breeding programs.

Estimation of genetic parameters for fertility traits in Chinese Holstein of south China

Introduction: Chinese Holstein in South China suffer heat stress for a long period, which leads to evolutionary differences from Chinese Holstein in North China. The aim of this study was to estimate the genetic parameters of fertility traits for Chinese Holstein in South China. Methods: A total of 167,840 Chinese Holstein heifers and cows from Guangming Animal Husbandry Co., LTD farms were used in this study. The fertility traits analyzed were calving interval (CI), days open (DO), age of first service (AFS), age of first calving (AFC), calving to first insemination (CTFS), first insemination to conception (FSTC), gestation length (GL), non-return rate to 56 days (NRR), and number of services (NS). Results: The descriptive statistics revealed that the same trait in heifers performed better than in cows, which was consistent with the other studies. The heritabilities of fertility traits in this study ranged from close to 0 (for NS of cows) to 0.2474 (for AFC of heifers). The genetic correlation of NRR between heifers and cows was 0.9993, which indicates that the NRR for heifers and cows could be treated as one trait in this population. Conclusion: The heritabilities of fertility traits in Chinese Holstein in south China were quite different from the heritabilities of fertility traits in North China. NRR56, NS, AFC, and CI were suggested to be included into the selection index to improve fertility performance of Chinsese Holstein of south China. The results of this study could provide genetic parameters for the animal breeding program of Chinese Holstein in the south of China.

Factor Analysis of Genetic Parameters for Body Conformation Traits in Dual-Purpose Simmental Cattle

Simple Summary

Body conformation traits are closely related to economically important characteristics and should be considered in cattle breeding programs. A variety of body conformation traits recorded by classifiers can complicate the analysis process. Factor analysis can reduce the number of variables by combining two or more variables into a single factor, which has biological significance. The results of this study could be used by breeders to define conformation indexes and implement genetic assessments for conformation traits in dual-purpose breeds.

Abstract

In this study, we estimated the genetic parameters for 6 composite traits and 27 body conformation traits of 1016 dual-purpose Simmental cattle reared in northwestern China from 2010 to 2019 using a linear animal mixed model. To integrate these traits, a variety of methods were used as follows: (1) genetic parameters estimates for composite and individual body conformation traits based on the pedigree relationship matrix (A) and combined genomic-pedigree relationship matrix (H); (2) factor analysis to explore the relationships among body conformation traits; and (3) genetic parameters of factor scores estimated using A and H, and the correlations of EBVs of the factor scores and EBVs of the composite traits. Heritability estimates of the composite traits using A and H were low to medium (0.07–0.47). The 24 common latent factors explained 96.13% of the total variance. Among factors with eigenvalues ≥ 1, F1 was mainly related to body frame, muscularity, and rump; F2 was related to feet and legs; F3, F4, F5, and F6 were related to teat placement, teat size, udder size, and udder conformation; and F7 was related to body frame. Single-trait analysis of factor scores yielded heritability estimates that were low to moderate (0.008–0.43 based on A and 0.04–0.43 based on H). Spearman and Pearson correlations, derived from the best linear unbiased prediction analysis of composite traits and factor scores, showed a similar pattern. Thus, incorporating factor analysis into the morphological evaluation to simplify the assessment of body conformation traits may improve the genetics of dual-purpose Simmental cattle.

A new quantitative index for the assessment of tomato quality using Vis-NIR hyperspectral imaging

The quality of tomatoes is usually predicted by measuring a single index, rather than a comprehensive index. To find a comprehensive index, visible and near infrared (Vis-NIR) hyperspectral imaging was used for capturing the images of three varieties of tomatoes, and twelve quality indexes were measured as the reference standards. The changing trends and correlations of different indexes were analyzed, and comprehensive quality index (CQI) was proposed through factor analysis. The characteristic wavelengths were selected by successive projection algorithm (SPA) based on the hyperspectral data, which was used to establish three regression models for CQI prediction. The result indicated that MLR achieved good performance withR_V² = 0.87, RMSEV = 1.33 and RPD = 2.58. After that, spatial distribution map was generated to visualize the CQI in tomato fruit. This study indicated that the comprehensive quality of tomatoes can be predicted non-destructively based on hyperspectral imaging and chemometrics, determining the optimal harvesting period.

Effects of the Use of Different Temperature and Calcium Chloride Treatments during Storage on the Quality of Fresh-Cut “Xuebai” Cauliflowers

This study revealed the effect of the use of different temperature and calcium chloride (CaCl₂) treatments on the storage quality of fresh-cut “Xuebai” cauliflowers. Fresh-cut “Xuebai” cauliflowers were soaked with 2% CaCl₂ solution at different temperatures. The change in the firmness, color, and ascorbic acid (ASA), total glucosinolates (TGLS), polygalacturonase (PG), and lipoxygenase (LOX) content of fresh-cut “Xuebai” cauliflowers during the cold storage period was assessed. In addition, the sensory quality was also evaluated. The results show that the combined treatments with CaCl₂ at different temperatures could effectively maintain the storage quality of fresh-cut “Xuebai” cauliflowers. Then, a method based on factor analysis with comprehensive quality evaluation was proposed. A factor analysis with a principal component analysis (PCA) was conducted on nine indicators of cauliflowers. Two principal components were extracted with a cumulative contribution rate of 97.513%. The results demonstrated that the treatment with the best fresh-keeping effect of cauliflowers in storage was the combination treatment at 40 °C with 2% CaCl₂ solution, while the optimal storage period was 15 days.

Genome-Wide Association Study Candidate Genes on Mammary System-Related Teat-Shape Conformation Traits in Chinese Holstein Cattle

In the dairy industry, mammary system traits are economically important for dairy animals, and it is important to explain their fundamental genetic architecture in Holstein cattle. Good and stable mammary system-related teat traits are essential for producer profitability in animal fitness and in the safety of dairy production. In this study, we conducted a genome-wide association study on three traits—anterior teat position (ATP), posterior teat position (PTP), and front teat length (FTL)—in which the FarmCPU method was used for association analyses. Phenotypic data were collected from 1000 Chinese Holstein cattle, and the GeneSeek Genomic Profiler Bovine 100K single-nucleotide polymorphisms (SNP) chip was used for cattle genotyping data. After the quality control process, 984 individual cattle and 84,406 SNPs remained for GWAS work analysis. Nine SNPs were detected significantly associated with mammary-system-related teat traits after a Bonferroni correction (p < 5.92 × 10⁻⁷), and genes within a region of 200 kb upstream or downstream of these SNPs were performed bioinformatics analysis. A total of 36 gene ontology (GO) terms and 3 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched (p < 0.05), and these terms and pathways are mainly related to metabolic processes, immune response, and cellular and amino acid catabolic processes. Eleven genes including MMS22L, E2F8, CSRP3, CDH11, PEX26, HAL, TAMM41, HIVEP3, SBF2, MYO16 and STXBP6 were selected as candidate genes that might play roles in the teat traits of cows. These results identify SNPs and candidate genes that give helpful biological information for the genetic architecture of these teat traits, thus contributing to the dairy production, health, and genetic selection of Chinese Holstein cattle.

Escalating health risk of thallium and arsenic from farmland contamination fueled by cement-making activities: A hidden but significant source

Soil-to-vegetable migration of toxic metal(loid)s is a pivotal pathway of human exposure to chemical intoxication. Thallium (Tl) and arsenic (As) are highly toxic metal(loid)s but their co-occurrence in soils and vegetables remain poorly understood. Herein, the present study focuses on potential health risk arising from co-occurrence of TlAs in various common vegetables cultivated in different farmlands around an industrial area featured by cement production activities. The results reveal obvious co-contamination of Tl (2.28 ± 1.39 mg/kg) and As (102.0 ± 66.7 mg/kg) in soils. Fine particles bearing sulfide and other minerals associated with Tl and As are detected in fly ash from cement plant, which can be migrated by wind over a long distance with hidden but inevitable pollution. Bioaccumulation Factor (BCF) and Enrichment Factor (EF) show that taro and corn preferentially accumulate Tl especially in underground parts. Hazard Quotient (HQ) indicates that consumption of these vegetables may result in chronic poisoning and/or even carcinogenic risk. The study highlights that the pathway and high risk of co-contamination of TlAs in the nearby farmlands posed by cement-making activities should be highly concerned.

Polarimetric data-based model for tissue recognition

We highlight the potential of a predictive optical model method for tissue recognition, based on the statistical analysis of different polarimetric indicators that retrieve complete polarimetric information (selective absorption, retardance and depolarization) of samples. The study is conducted on the experimental Mueller matrices of four biological tissues (bone, tendon, muscle and myotendinous junction) measured from a collection of 157 ex-vivo chicken samples. Moreover, we perform several non-parametric data distribution analyses to build a logistic regression-based algorithm capable to recognize, in a single and dynamic measurement, whether a sample corresponds (or not) to one of the four different tissue categories.

Genome-Wide Association Study Identifies Candidate Genes Associated with Feet and Leg Conformation Traits in Chinese Holstein Cattle

Simple Summary

Feet and leg problems are among the major reasons for dairy cows leaving the herd, as well as having direct association with production and reproduction efficiency, health (e.g., claw disorders and lameness) and welfare. Hence, understanding the genetic architecture underlying feet and conformation traits in dairy cattle offers new opportunities toward the genetic improvement and long-term selection. Through a genome-wide association study on Chinese Holstein cattle, we identified several candidate genes associated with feet and leg conformation traits. These results could provide useful information about the molecular breeding basis of feet and leg traits, thus improving the longevity and productivity of dairy cattle.

Abstract

Feet and leg conformation traits are considered one of the most important economical traits in dairy cattle and have a great impact on the profitability of milk production. Therefore, identifying the single nucleotide polymorphisms (SNPs), genes and pathways analysis associated with these traits might contribute to the genomic selection and long-term plan selection for dairy cattle. We conducted genome-wide association studies (GWASs) using the fixed and random model circulating probability unification (FarmCPU) method to identify SNPs associated with bone quality, heel depth, rear leg side view and rear leg rear view of Chinese Holstein cows. Phenotypic measurements were collected from 1000 individuals of Chinese Holstein cattle and the GeneSeek Genomic Profiler Bovine 100 K SNP chip was utilized for individual genotyping. After quality control, 984 individual cows and 84,906 SNPs remained for GWAS work; as a result, we identified 20 significant SNPs after Bonferroni correction. Several candidate genes were identified within distances of 200 kb upstream or downstream to the significant SNPs, including ADIPOR2, INPP4A, DNMT3A, ALDH1A2, PCDH7, XKR4 and CADPS. Further bioinformatics analyses showed 34 gene ontology terms and two signaling pathways were significantly enriched (p ≤ 0.05). Many terms and pathways are related to biological quality, metabolism and development processes; these identified SNPs and genes could provide useful information about the genetic architecture of feet and leg traits, thus improving the longevity and productivity of Chinese Holstein dairy cattle.

Selection Response Due to Different Combination of Antagonistic Milk, Beef, and Morphological Traits in the Alpine Grey Cattle Breed

Selection in local dual-purpose breeds requires great carefulness because of the need to preserve peculiar traits and also guarantee the positive genetic progress for milk and beef production to maintain economic competitiveness. A specific breeding plan accounting for milk, beef, and functional traits is required by breeders of the Alpine Grey cattle (AG), a local dual-purpose breed of the Italian Alps. Hereditability and genetic correlations among all traits have been analyzed for this purpose. After that, different selection indexes were proposed to identify the most suitable for this breed. Firstly, a genetic parameters analysis was carried out with different datasets. The milk dataset contained 406,918 test day records of milk, protein, and fat yields and somatic cells (expressed as SCS). The beef dataset included performance test data conducted on 749 young bulls. Average daily gain, in vivo estimated carcass yields, and carcass conformation (SEUROP) were the phenotypes obtained from the performance tests. The morphological dataset included 21 linear type evaluations of 11,320 first party cows. Linear type traits were aggregated through factor analysis and three factors were retained, while head typicality (HT) and rear muscularity (RM) were analyzed as single traits. Heritability estimates (h2) for milk traits ranged from 0.125 to 0.219. Analysis of beef traits showed h2 greater than milk traits, ranging from 0.282 to 0.501. Type traits showed a medium value of h2 ranging from 0.238 to 0.374. Regarding genetic correlation, SCS and milk traits were strongly positively correlated. Milk traits had a negative genetic correlation with the factor accounting for udder conformations (-0.40) and with all performance test traits and RM. These latter traits showed also a negative genetic correlation with udder volume (-0.28). The HT and the factor accounting for rear legs traits were not correlated with milk traits, but negatively correlated with beef traits (-0.32 with RM). We argue that the consequence of these results is that the use of the current selection index, which is mainly focused on milk attitude, will lead to a deterioration of all other traits. In this study, we propose more appropriate selection indexes that account for genetic relationships among traits, including functional traits.

Quality evaluation of Acanthopanax senticosus via quantitative analysis of multiple components by single marker and multivariate data analysis

A comprehensive method for the evaluation of Acanthopanax senticosus (AS) was established by the quantitative analysis of multiple components by single marker (QAMS), fingerprint, similarity analysis (SA), hierarchical cluster analysis (HCA), and factor analysis (FA) based on high performance liquid chromatography (HPLC). A total of 27 common peaks were identified in the standard fingerprint of 20 batches of AS from different regions in China, of which 8 peaks were identified as protocatechuic acid, syringin, chlorogenic acid, caffeic acid, eleutheroside E, hyperoside, isofrqxidin, and acacetin, and the concentrations of these eight components were determined simultaneously by QAMS. The results showed that the QAMS method was effective and feasible compared with the external standard method (ESM) (RD < 3.3 %, P ≤ 0.01). Sample 1 (S1) was used as the reference chromatogram, the similarity of other samples was between 0.765 and 0.968. Through HCA, AS could be mainly divided into two production areas, the north Liaoning (including Liaoning) and the south Liaoning areas. Furthermore, FA showed that the quality of AS in the north Liaoning area was better than that in the south Liaoning area. In summary, the method established in this study can comprehensively and systematically evaluate quality differences in AS samples, and may be used to help to improve the quality control of AS.

Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

Principal component and multivariate factor analysis of detailed sheep milk fatty acid profile

Fatty acid (FA) profile is one of the most important aspects of the nutritional properties of milk. The FA content in milk is affected by several factors such as diet, physiology, environment, and genetics. Recently, principal component analysis (PCA) and multivariate factor analysis (MFA) have been used to summarize the complex correlation pattern of the milk FA profile by extracting a reduced number of new variables. In this work, the milk FA profile of a sample of 993 Sarda breed ewes was analyzed with PCA and MFA to compare the ability of these 2 multivariate statistical techniques in investigating the possible existence of latent substructures, and in studying the influence of physiological and environmental effects on the new extracted variables. Individual scores of PCA and MFA were analyzed with a mixed model that included the fixed effects of parity, days in milking, lambing month, number of lambs born, altitude of flock location, and the random effect of flock nested within altitude. Both techniques detected the same number of latent variables (9) explaining 80% of the total variance. In general, PCA structures were difficult to interpret, with only 4 principal components being associated with a clear meaning. Principal component 1 in particular was the easiest to interpret and agreed with the interpretation of the first factor, with both being associated with the FA of mammary origin. On the other hand, MFA was able to identify a clear structure for all the extracted latent variables, confirming the ability of this technique to group FA according to their function or metabolic origin. Key pathways of the milk FA metabolism were identified as mammary gland de novo synthesis, ruminal biohydrogenation, desaturation performed by stearoyl-coenzyme A desaturase enzyme, and rumen microbial activity, confirming previous findings in sheep and in other species. In general, the new extracted variables were mainly affected by physiological factors as days in milk, parity, and lambing month; the number of lambs born had no effect on the new variables, and altitude influenced only one principal component and factor. Both techniques were able to summarize a larger amount of the original variance into a reduced number of variables. Moreover, factor analysis confirmed its ability to identify latent common factors clearly related to FA metabolic pathways.

Constructing a Talent Identification Index System and Evaluation Model for Cross-Country Skiers

A talent identification index system for male and female cross-country skiers in four age groups (11-12 years old, 13-14 years old, 15-16 years old, and 17-18 years old) was established. The system comprises five body shape indexes ( i =5): Leg-to-Body Ratio (LBR), body fat percentage, maturity status, spreaded brachia index, and upper extremity length. The physiological function indexes ( i =2) are VO_2max and haemoglobin mass (Hb). The psychological indexes ( i =5) cover reaction time, perception speed, a quality-of-will scale, an attention test, and operational thinking. The physical fitness indexes ( i =11) comprise upper limb explosiveness, vertical jump, 3000-metre run, orthostatic forward flexion, closed-eyes single-leg stand, standing long jump, 20-metre sprint, pull-ups (males), flexed arm hang (females), hexagon jump, and a Functional Movement Screen (FMS) test. The athletic performance indexes ( i =3) comprise on-snow time trials for 1.2 km, 5 km, and 10 km. The talent identification evaluation model was created using automated evaluation software. The talent identification index system and evaluation standard table for cross-country skiers passed the P₆₀ shortlist and P₉₀ elite boundaries established using the percentile method. Thus, the results of this test profile verify that the evaluative model is objectively effective.

High-density diet improves growth performance and beef yield but affects negatively on serum metabolism and visceral morphology of Holstein steers

The objective of this study was to evaluate the effect of different dietary densities on growth performance, carcass characteristics, meat quality, serum metabolism, ruminal papillae morphology and liver injuries of steers. For this purpose, a total of eighteen Holstein steers were randomly fed one of the three diets: high energy and protein diet (H), standard energy and protein diet (C), and low energy and protein diet (L) for 11 months fattening with three-step finishing strategy. Steers fed with H diet had higher (p < .05) average daily gain, feed efficiency, hot carcass weight, serum aspartate aminotransferase to alanine aminotransferase ratio, and monounsaturated fatty acids along with continuous low ruminal pH value, severer hepatic steatosis and ruminal papillae parakeratosis. Meanwhile, steers fed L diet increased the proportion of C20:0, C22:6n-3, saturated fatty acids and n-3 polyunsaturated fatty acids along with lower n-6 to n-3 ratio in longissimus dorsi muscle as compared to that of steers fed H diet. Dietary densities did not influence (p > .10) proximate nutrients and sensory characteristics of beef. The present study indicates that Holstein steers could achieve better growth and carcass performance under high-density diet, whereas they are under threat of visceral injuries and metabolic disorders. This study gives comprehensive relationship between productivity and animal health and suggests that a proper diet should be adopted for fattening Holstein steers in consideration of both beef quality and quantity and animal health.