Traits In Cattle Research Articles

Genome-Wide Association Studies for Body Conformation Traits in Korean Holstein Population.

The objective of this study was to identify quantitative trait loci (QTL) and nearby candidate genes that influence body conformation traits. Phenotypic data for 24 body conformation traits were collected from a population of 2329 Korean Holstein cattle, and all animals were genotyped using the 50 K Illumina bovine SNP chip. A total of 24 genome-wide significant SNPs associated with 24 body conformation traits were identified by genome-wide association analysis. The selection of the most promising candidate genes was based on gene ontology (GO) terms and the previously identified functions that influence various body conformation traits as determined in our study. These genes include KCNA1, RYBP, PTH1R, TMIE, and GNAI3 for body traits; ANGPT1 for rump traits; MALRD1, INHBA, and HOXA13 for feet and leg traits; and CDK1, RHOBTB1, and SLC17A1 for udder traits, respectively. These findings contribute to our understanding of the genetic basis of body conformation traits in this population and pave the way for future breeding strategies aimed at enhancing desirable traits in dairy cattle.

Candidate signatures of positive selection for environmental adaptation in indigenous African cattle: A review.

Environmental adaptation traits of indigenous African cattle are increasingly being investigated to respond to the need for sustainable livestock production in the context of unpredictable climatic changes. Several studies have highlighted genomic regions under positive selection probably associated with adaptation to environmental challenges (e.g. heat stress, trypanosomiasis, tick and tick-borne diseases). However, little attention has focused on pinpointing the candidate causative variant(s) controlling the traits. This review compiled information from 22 studies on signatures of positive selection in indigenous African cattle breeds to identify regions under positive selection. We highlight some key candidate genome regions and genes of relevance to the challenges of living in extreme environments (high temperature, high altitude, high infectious disease prevalence). They include candidate genes involved in biological pathways relating to innate and adaptive immunity (e.g. BoLAs, SPAG11, IL1RL2 and GFI1B), heat stress (e.g. HSPs, SOD1 and PRLH) and hypoxia responses (e.g. BDNF and INPP4A). Notably, the highest numbers of candidate regions are found on BTA3, BTA5 and BTA7. They overlap with genes playing roles in several biological functions and pathways. These include but are not limited to growth and feed intake, cell stability, protein stability and sweat gland development. This review may further guide targeted genome studies aiming to assess the importance of candidate causative mutations, within regulatory and protein-coding genome regions, to further understand the biological mechanisms underlying African cattle's unique adaption.

Investigating the relationship between fluctuations in daily milk yield as resilience indicators and health traits in Holstein cattle

Disease-related milk losses directly impact dairy herds' profitability and the production efficiency of the dairy industry. Therefore, this study aimed to quantify phenotypic variability in milk fluctuation periods related to diseases and to explore milk fluctuation traits as indicators of disease resilience. By combining high-frequency daily milk yield data with disease records of cows that were treated and recovered from the disease, we estimated milk variability trends within a fixed period around the treatment day of each record for 5 diseases: udder health, reproductive disorders, metabolic disorders, digestive disorders, and hoof health. The average milk yield decreased rapidly from 6 to 8 d before the treatment day for all diseases, with the largest milk reduction observed on the treatment day. Additionally, we assessed the significance of milk fluctuation periods highly related to diseases by defining milk fluctuations as a period of at least 10 consecutive days in which milk yield fell below 90% of the expected milk production values at least once. We defined the development and recovery phases of milk fluctuations using 3,847 milk fluctuation periods related to disease incidences, and estimated genetic parameters of milk fluctuation traits, including milk losses, duration of the fluctuation, variation rate in daily milk yield, and standard deviation of milk deviations for each phase and their genetic correlation with several important traits. In general, the disease-related milk fluctuation periods lasted 21.19 ± 10.36 d with a milk loss of 115.54 ± 92.49 kg per lactation. Compared with the development phase, the recovery phase lasted an average of 3.3 d longer, in which cows produced 11.04 kg less milk and exhibited a slower variation rate in daily milk yield of 0.35 kg/d. There were significant differences in milk fluctuation traits depending on the disease, and greater milk losses were observed when multiple diseases occurred simultaneously. All milk fluctuation traits evaluated were heritable with heritability estimates ranging from 0.01 to 0.10, and moderate to high genetic correlations with milk yield (0.34 to 0.64), milk loss throughout the lactation (0.22 to 0.97), and resilience indicator (0.39 to 0.95). These results indicate that cows with lower milk losses and higher resilience tend to have more stable milk fluctuations, which supports the potential for breeding for more disease-resilient cows based on milk fluctuation traits. Overall, this study confirms the high impact of diseases on milk yield variability and provides insightful information about their relationship with relevant traits in Holstein cattle. Furthermore, this study shows the potential of using high frequency automatic monitoring of milk yield to assist on breeding practices and health management in dairy cows.

Genetic and phenotypic parameters for sexual precocity and parasite resistance traits in Nellore cattle.

Indicator traits of sexual precocity are widely used as selection criteria for the genetic improvement of beef cattle; however, the impact of selection for these traits on resistance to endoparasites and ectoparasites is unknown. Therefore, this study aimed to estimate the genetic and phenotypic parameters for indicator traits of sexual precocity and parasite resistance in Nellore cattle. The sexual precocity traits evaluated were probability of first calving (PFC) and scrotal circumference at 12 and 18months of age (SC12 and SC18). The resistance-related traits included tick (TC), gastrointestinal nematode egg (NEC), and Eimeria spp. oocyst (EOC) counts. (Co)variance components were estimated by Bayesian inference using multitrait animal models. The mean heritabilities for PFC, SC12, SC18, TC, NEC, and EOC were 0.23, 0.38, 0.42, 0.14, 0.16, and 0.06, respectively, and suggest that selection will change the mean values of these traits over time. The genetic and phenotypic correlations for most pairs formed by a precocity and a resistance trait were not different from zero, suggesting that selection for sexual precocity traits will not result in changes in resistance traits. Thus, selection for indicator traits of sexual precocity does not elicit unfavorable correlated responses in resistance to endoparasites and ectoparasites, and joint selection aimed at improving these traits can be performed using multitrait selection methods, when necessary.

Integrating Omics Technologies for a Comprehensive Understanding of the Microbiome and Its Impact on Cattle Production.

Ruminant production holds a pivotal position within the global animal production and agricultural sectors. As population growth escalates, posing environmental challenges, a heightened emphasis is directed toward refining ruminant production systems. Recent investigations underscore the connection between the composition and functionality of the rumen microbiome and economically advantageous traits in cattle. Consequently, the development of innovative strategies to enhance cattle feed efficiency, while curbing environmental and financial burdens, becomes imperative. The advent of omics technologies has yielded fresh insights into metabolic health fluctuations in dairy cattle, consequently enhancing nutritional management practices. The pivotal role of the rumen microbiome in augmenting feeding efficiency by transforming low-quality feedstuffs into energy substrates for the host is underscored. This microbial community assumes focal importance within gut microbiome studies, contributing indispensably to plant fiber digestion, as well as influencing production and health variability in ruminants. Instances of compromised animal welfare can substantially modulate the microbiological composition of the rumen, thereby influencing production rates. A comprehensive global approach that targets both cattle and their rumen microbiota is paramount for enhancing feed efficiency and optimizing rumen fermentation processes. This review article underscores the factors that contribute to the establishment or restoration of the rumen microbiome post perturbations and the intricacies of host-microbiome interactions. We accentuate the elements responsible for responsible host-microbiome interactions and practical applications in the domains of animal health and production. Moreover, meticulous scrutiny of the microbiome and its consequential effects on cattle production systems greatly contributes to forging more sustainable and resilient food production systems, thereby mitigating the adverse environmental impact.

Omics Technology for Genetic Selection Towards Feed Efficiency Traits of Indigenous Cattle in Indonesia: A Review

Indigenous cattle in Indonesia seldom to reach their genetic potentials due to an interaction impact of harsh tropical climate and low-quality feed. Some indigenous breeds of cattle in Indonesia, such as Bali, Madura and Crossbred Ongole have demonstrated their successful adaptation to survive in the harsh environment, but their ultimate performances are still considered less than their genetic potentials when reared under comfortable environment like in the sub-tropical climate. This is primarily due to inefficient fermentation of feed originating from inadequate supply of essential nutrients required for optimum growth of microbes in the forestomach. A rapid advancement of omics technology has been the driver for ruminant nutritionists to use such a technology to study the interrelationship between nutrients and particular genes associated with the biochemical pathways of nutrients at molecular levels. This review highlights the current issues and challenges on the use of omics technologies to improve the efficiency of feed utilization by cattle consuming low-quality diets and its potential to be used in the genetic selection program.

Assessment of body conformation traits and their relationship with production performance of Sahiwal cows

Linear type scoring is key component in decision making process in the herd, as it focusses on the selection of animals with higher productive potential based on their body conformation/linear traits. The present study was carried out on 150 lactating Sahiwal cattle of first to fifth parity. Measurements on linear type traits were recorded 1 h before the evening milking at three different stages of lactation. The average score point of objective linear type traits was stature 5.77±0.08, chest width 4.59±0.10, body depth 5.24±0.10, rump width 5.56±0.09, rump angle 4.48±0.08, rear legs sets 4.81±0.12, foot angle 4.84±0.10, fore udder attachment 4.85±0.11, rear udder height 5.52±0.10, udder depth 5.31±0.08, rear udder width 4.27±0.09, central ligament 4.01±0.09, fore teat length 3.49±0.10, rear teat length 3.94±0.09, teat circumference 4.20±0.11, teat diameter 4.16±0.10 and udder balance 5.25±0.11. On the other hand, average score point of subjective linear type traits (1-9 scale) was angularity 4.69±0.09, rear leg rear view 5.05±0.06, body condition score 6.53±0.08, locomotion 4.88±0.06, fore teat placement 4.41±0.07 and rear teat placement 6.28±0.08. Most of the body conformation traits in Sahiwal cattle were falling under intermediate category and of desirable type. However, some traits like stature, chest width, body depth, rump width, angularity, central ligament, rear udder height, rear udder width and fore udder attachment expressed scope for further improvement.

Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Many quantitative trait loci (QTLs) are in non-coding regions. Therefore, QTLs are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription, so DNA variants changing gene expression (eVariants) or RNA splicing (sVariants) are expected to significantly affect phenotypes. We quantify the contribution of eVariants and sVariants detected from 16 tissues (n= 4,725) to 37 traits of ∼120,000 cattle (average magnitude of genetic correlation between traits= 0.13). Analyzed in Bayesian mixture models, averaged across 37 traits, cis and trans eVariants and sVariants detected from 16 tissues jointly explain 69.2% (SE= 0.5%) of heritability, 44% more than expected from the same number of random variants. This 69.2% includes an average of 24% from trans e-/sVariants (14% more than expected). Averaged across 56 lipidomic traits, multi-tissue cis and trans e-/sVariants also explain 71.5% (SE= 0.3%) of heritability, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.

Integrated Comparative Transcriptome and circRNA-lncRNA-miRNA-mRNA ceRNA Regulatory Network Analyses Identify Molecular Mechanisms Associated with Intramuscular Fat Content in Beef Cattle.

Intramuscular fat content (IMF), one of the most important carcass traits in beef cattle, is controlled by complex regulatory factors. At present, molecular mechanisms involved in regulating IMF and fat metabolism in beef cattle are not well understood. Our objective was to integrate comparative transcriptomic and competing endogenous RNA (ceRNA) network analyses to identify candidate messenger RNAs (mRNAs) and regulatory RNAs involved in molecular regulation of longissimus dorsi muscle (LDM) tissue for IMF and fat metabolism of 5 beef cattle breeds (Angus, Chinese Simmental, Luxi, Nanyang, and Shandong Black). In total, 34 circRNAs, 57 lncRNAs, 15 miRNAs, and 374 mRNAs were identified by integrating gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, 7 key subnets with 16 circRNAs, 43 lncRNAs, 7 miRNAs, and 237 mRNAs were detected through clustering analyses, whereas GO enrichment analysis of identified RNAs revealed 48, 13, and 28 significantly enriched GO terms related to IMF in biological process, molecular function, and cellular component categories, respectively. The main metabolic-signaling pathways associated with IMF and fat metabolism that were enriched included metabolic, calcium, cGMP-PKG, thyroid hormone, and oxytocin signaling pathways. Moreover, MCU, CYB5R1, and BAG3 genes were common among the 10 comparative groups defined as important candidate marker genes for fat metabolism in beef cattle. Contributions of transcriptome profiles from various beef breeds and a competing endogenous RNA (ceRNA) regulatory network underlying phenotypic differences in IMF provided novel insights into molecular mechanisms associated with meat quality.

Polymorphism of Melanocortin-4 Receptor Gene and Its Association with Growth Traits in Bali Cattle

The melanocortin-4 receptor (MC4R) is a gene that controls growth traits. This gene is embedded in the leptin-melanocortin pathway and regulates body weight. Previous studies have successfully identified the genetic diversity of the MC4R associated with growth traits. However, studies on Bali cattle are limited. This study aimed to identify the SNP markers of the MC4R gene and its effect on birth body weight, weaning body weight, weaning chest girth, weaning withers height, weaning body length, yearling body weight, yearling chest girth, yearling withers height, and yearling body length in Bali cattle (n=43). The MC4R genotype was identified by sequencing and aligned using BioEdit v.7.2.5. The association between genotype and growth traits was analyzed using the GLM procedure and DMRT in RStudio program v.2022.02. Four SNPs were identified in the exon region:  g.355GT, g.394CT, g.463GA, and g.682GA.  Based on the Chi-square test, the population was fitted with HWE (p0.05). Genotype-phenotype association based on SNPs showed no significant result (p0.05) where the g.682GA (AG) locus had values of WB (104.33+17.15 kg), WCG (112.83+3.66 kg), WBL (89.50+3.94 kg), YB (124.17+22.44 kg), YCG (120.50+5.50 kg), and YBL (92.83+4.31 kg) higher than the other genotypes. Association based on haplotype type showed significant results (p0.05) in BB, where haplotype 2 had the highest BB (21.17+0.75 kg). In conclusion, the SNP markers found in this study were polymorphic but did not affect growth traits in Bali cattle.

Multi‐trait genomic predictions using GBLUP and Bayesian mixture prior model in beef cattle

AbstractMultiple trait genomic selection incorporating correlated traits can improve the predictive ability of low‐heritability traits. In this study, we evaluated genomic prediction accuracy using multi‐trait BayesCπ method (MT‐BayesCπ), which allows for a broader range of mixture priors for important traits in beef cattle. We compared the prediction performance of MT‐BayesCπ with single‐trait genomic best linear unbiased prediction (ST‐GBLUP), multi‐trait GBLUP (MT‐GBLUP), and single‐trait BayeCπ (ST‐BayesCπ) methods. We found that ribeye area (REA) and ribeye weight (REWT) showed high heritability, while slaughter weight (SWT) and carcass weight (CWT) displayed medium heritability, and slaughter rate (SR) and feedlot average daily gain (FDG) showed low heritability. Highly positive genetic correlations were observed between CWT and SWT (0.981) and SR and REWT (0.921). Notably, the MT‐BayesCπ method showed superior predictive abilities compared to other models. Using MT‐BayesCπ method, the accuracy increased from 0.272 to 0.694 for CWT compared to ST‐GBLUP and ST‐BayesCπ. MT‐GBLUP and ST‐BayesCπ showed similar prediction accuracies, while MT‐BayesCπ showed the least biased evaluations. Additionally, our results suggested that prediction accuracy of low‐heritability traits significantly increased when they were combined with traits with high genetic correlation in a multi‐trait prediction. Our study suggests that multi‐trait genomic predictions using GBLUP and Bayesian mixture prior models is feasible for genomic selection in beef cattle. Our findings indicate that MT‐BayesCπ outperforms other models (ST‐GBLUP, MT‐GBLUP and ST‐BayesCπ), especially for low‐heritability traits.

Association between Polymorphism in the Janus Kinase 2 (JAK2) Gene and Selected Performance Traits in Cattle and Sheep.

The Janus Kinase 2 (JAK2) tyrosine kinase is an essential component of signal transduction of the class II cytokine receptors, including the growth hormone receptor. Therefore, it may play a crucial role in the signaling pathway of the somatotropic axis, which influences growth, development, and reproductive traits in ruminants. For this purpose, for three breeds of cattle (Hereford, Angus, and Limousin; a total of 781 individuals), two polymorphic sites located in exon 16 (rs210148032; p.Ile704Val, within pseudokinase (JH2)) and exon 23 (silent mutation rs211067160, within JH1 kinase domain) were analyzed. For two breeds of sheep (Pomeranian and Suffolk; 333 individuals in total), two polymorphic sites in exon 6 (rs160146162 and rs160146160; encoding the FERM domain) and one polymorphic site in exon 24 of the JAK2 gene (rs160146116; JH1 kinase domain) were genotyped. In our study, the associations examined for cattle were inconclusive. However, Hereford and Limousin cattle with genotypes AA (e16/RsaI) and AA (e23/HaeIII) tended to have the highest body weight and better daily gains (p ≤ 0.05). No clear tendency was observed in the selected reproductive traits. In the case of sheep, regardless of breed, individuals with the AA (e6/EarI), GG (e6/seq), and AA (e24/Hpy188III) genotypes had the highest body weights and daily gains in the study periods (p ≤ 0.01). The same individuals in the Pomeranian breed also had better fertility and lamb survival (p ≤ 0.01). To the best of our knowledge, these are the first association studies for all these polymorphic sites. Single-nucleotide polymorphisms in the JAK2 gene can serve as genetic markers for growth and selected reproductive traits in ruminants given that they are further investigated in subsequent populations and analyzed using haplotype and/or combined genotype systems.

DeepGBLUP: joint deep learning networks and GBLUP framework for accurate genomic prediction of complex traits in Korean native cattle

BackgroundGenomic prediction has become widespread as a valuable tool to estimate genetic merit in animal and plant breeding. Here we develop a novel genomic prediction algorithm, called deepGBLUP, which integrates deep learning networks and a genomic best linear unbiased prediction (GBLUP) framework. The deep learning networks assign marker effects using locally-connected layers and subsequently use them to estimate an initial genomic value through fully-connected layers. The GBLUP framework estimates three genomic values (additive, dominance, and epistasis) by leveraging respective genetic relationship matrices. Finally, deepGBLUP predicts a final genomic value by summing all the estimated genomic values.ResultsWe compared the proposed deepGBLUP with the conventional GBLUP and Bayesian methods. Extensive experiments demonstrate that the proposed deepGBLUP yields state-of-the-art performance on Korean native cattle data across diverse traits, marker densities, and training sizes. In addition, they show that the proposed deepGBLUP can outperform the previous methods on simulated data across various heritabilities and quantitative trait loci (QTL) effects.ConclusionsWe introduced a novel genomic prediction algorithm, deepGBLUP, which successfully integrates deep learning networks and GBLUP framework. Through comprehensive evaluations on the Korean native cattle data and simulated data, deepGBLUP consistently achieved superior performance across various traits, marker densities, training sizes, heritabilities, and QTL effects. Therefore, deepGBLUP is an efficient method to estimate an accurate genomic value. The source code and manual for deepGBLUP are available at https://github.com/gywns6287/deepGBLUP.

Genomic Regions and Candidate Genes Associated with Milk Production Traits in Holstein and Its Crossbred Cattle: A Review.

Genome-wide association studies (GWAS) are a powerful tool for identifying genomic regions and causative genes associated with economically important traits in dairy cattle, particularly complex traits, such as milk production. This is possible due to advances in next-generation sequencing technology. This review summarized information on identified candidate genes and genomic regions associated with milk production traits in Holstein and its crossbreds from various regions of the world. Milk production traits are important in dairy cattle breeding programs because of their direct economic impact on the industry and their close relationship with nutritional requirements. GWAS has been used in a large number of studies to identify genomic regions and candidate genes associated with milk production traits in dairy cattle. Many genomic regions and candidate genes have already been identified in Holstein and its crossbreds. Genes and single nucleotide polymorphisms (SNPs) that significantly affect milk yield (MY) were found in all autosomal chromosomes except chromosomes 27 and 29. Half of the reported SNPs associated with fat yield and fat percentage were found on chromosome 14. However, a large number of significant SNPs for protein yield (PY) and protein percentage were found on chromosomes 1, 5, and 20. Approximately 155 SNPs with significant influence on multiple milk production traits have been identified. Several promising candidate genes, including diacylglycerol O-acyltransferase 1, plectin, Rho GTPase activating protein 39, protein phosphatase 1 regulatory subunit 16A, and sphingomyelin phosphodiesterase 5 were found to have pleiotropic effects on all five milk production traits. Thus, to improve milk production traits it is of practical relevance to focus on significant SNPs and pleiotropic genes frequently found to affect multiple milk production traits.

Effects of DNA Methylation on Gene Expression and Phenotypic Traits in Cattle: A Review.

Gene expression in cells is determined by the epigenetic state of chromatin. Therefore, the study of epigenetic changes is very important to understand the regulatory mechanism of genes at the molecular, cellular, tissue and organ levels. DNA methylation is one of the most studied epigenetic modifications, which plays an important role in maintaining genome stability and ensuring normal growth and development. Studies have shown that methylation levels in bovine primordial germ cells, the rearrangement of methylation during embryonic development and abnormal methylation during placental development are all closely related to their reproductive processes. In addition, the application of bovine male sterility and assisted reproductive technology is also related to DNA methylation. This review introduces the principle, development of detection methods and application conditions of DNA methylation, with emphasis on the relationship between DNA methylation dynamics and bovine spermatogenesis, embryonic development, disease resistance and muscle and fat development, in order to provide theoretical basis for the application of DNA methylation in cattle breeding in the future.

Association of CXCR1 gene polymorphism with clinical mastitis, reproductive disorders and performance traits in Hardhenu (Bos taurus × Bos indicus) cattle.

The present study investigated the presence of CXCR1 gene polymorphisms and their association with clinical mastitis, reproductive disorders and performance traits in Hardhenu cattle. Genotyping of the targeted SNP rs211042414 (C>T) at the g.106216468 loci of the CXCR1 gene was performed through PCR amplification and Bsa1 restriction enzyme digestion. The genotypic frequencies revealed three genotypes: CC, CT and TT, with the C allele being the most prevalent. Significant associations were found between the targeted SNP and clinical mastitis occurrence using chi-square and logistic regression analyses. The CC genotype showed higher susceptibility to clinical mastitis with a higher odds ratio of 3.47 compared to TT (1.00) and CT (2.90) genotypes (p < .05). Furthermore, least squares analysis revealed significant associations between genotypes and performance traits such as total milk yield, 305-day milk yield and peak yield (p < .05). The CC genotype exhibited higher milk yields than CT and TT genotypes, indicating a positive association between the C allele and increased milk production. These findings have practical implications for the genetic improvement of Hardhenu cattle. Incorporating the identified CXCR1 gene polymorphisms into existing selection criteria can help enhance disease resistance and milk production traits. However, further validation with a larger sample size is necessary to strengthen the observed associations and ensure their practical applicability.

Genotype by Prenatal Environment Interaction for Postnatal Growth of Nelore Beef Cattle Raised under Tropical Grazing Conditions.

The prenatal environment is recognized as crucial for the postnatal performance in cattle. In tropical regions, pregnant beef cows commonly experience nutritional restriction during the second half of the gestation period. Thus, the present study was designed to analyze the genotype by prenatal environment interaction (G × Epn) and to identify genomic regions associated with the level and response in growth and reproduction-related traits of beef cattle to changes in the prenatal environment. A reaction norm model was applied to data from two Nelore herds using the solutions of contemporary groups for birth weight as a descriptor variable of the gestational environment quality. A better gestational environment favored weights until weaning, scrotal circumference at yearling, and days to first calving of the offspring. The G × Epn was strong enough to result in heterogeneity of variance components and genetic parameters in addition to reranking of estimated breeding values and SNPs effects. Several genomic regions associated with the level of performance and specific responses of the animals to variations in the gestational environment were revealed, which harbor QTLs and can be exploited for selection purposes. Therefore, genetic evaluation models considering G × Epn and special management and nutrition care for pregnant cows are recommended.

Metagenomic approach to infer rumen microbiome derived traits of cattle.

Ruminants enable the conversion of indigestible plant material into animal consumables, including dairy products, meat, and valuable fibers. Microbiome research is gaining popularity in livestock species because it aids in the knowledge of illnesses and efficiency processes in animals. In this study, we use WGS metagenomic data to thoroughly characterize the ruminal ecosystem of cows to infer positive and negative livestock traits determined by the microbiome. The rumen of cows from Argentina were described by combining different gene biomarkers, pathways composition and taxonomic information. Taxonomic characterization indicated that the two major phyla were Bacteroidetes and Firmicutes; in third place, Proteobacteria was highly represented followed by Actinobacteria; Prevotella, and Bacteroides were the most abundant genera. Functional profiling of carbohydrate-active enzymes indicated that members of the Glycoside Hydrolase (GH) class accounted for 52.2 to 55.6% of the total CAZymes detected, among them the most abundant were the oligosaccharide degrading enzymes. The diversity of GH families found suggested efficient hydrolysis of complex biomass. Genes of multidrug, macrolides, polymyxins, beta-lactams, rifamycins, tetracyclines, and bacitracin resistance were found below 0.12% of relative abundance. Furthermore, the clustering analysis of genera and genes that correlated to methane emissions or feed efficiency, suggested that the cows analysed could be regarded as low methane emitters and clustered with high feed efficiency reference animals. Finally, the combination of bioinformatic analyses used in this study can be applied to assess cattle traits difficult to measure and guide enhanced nutrition and breeding methods.

Association of plasma miRNAs with early life performance and aging in dairy cattle.

Early life performance traits in dairy cattle can have important influences on lifetime productivity. Poor health and fertility are of great economical and animal welfare concern. Circulating miRNAs have been linked to several livestock traits, including resistance to infection, fertility, and muscle development. This study aimed to identify circulating miRNAs associated with early life performance traits and aging in dairy cattle. Plasma samples from female calves (n = 12) identified retrospectively as differing in health, growth, and fertility outcomes prior to first calving were analyzed using PCR arrays detecting 378 miRNAs. Levels of 6 miRNAs differed significantly in calves with poor growth/fertility relative to controls (t-test: P<0.05). Additionally, general(ized) (non)linear mixed models identified 1 miRNA associated with average daily gain until weaning, 22 with live bodyweight at one year of age, 47 with age at first service, and 19 with number of infections before first calving. Out of 85 distinct miRNAs that were associated with at least one animal trait, 9 miRNAs were validated by RT-qPCR in a larger cohort (n = 91 animals), which included longitudinal plasma samples (calf, heifer, first lactation cow). Significant associations (P<0.05) involving individual miRNAs or ratios between miRNAs and early-life performance traits were identified, but did not retain significance after multiple testing adjustment. However, levels of 8 plasma miRNAs (miR-126-3p, miR-127, miR-142-5p, miR-154b, miR-27b, miR-30c-5p, miR-34a, miR-363) changed significantly with age, most prominently during the calf-to-heifer transition. Comparative RT-qPCR analyses of these miRNAs across 19 calf tissues showed that most were ubiquitously expressed. Online database mining identified several pathways involved in metabolism and cell signaling as putative biological targets of these miRNAs. These results suggest that miR-126-3p, miR-127, miR-142-5p, miR-154b, miR-27b, miR-30c-5p, miR-34a, miR-363 are involved in regulating growth and development from birth to first lactation (~2 years old) and could provide useful biomarkers of aging in cattle.

Comparing pedigree and genomic inbreeding coefficients, and inbreeding depression of reproductive traits in Japanese Black cattle

BackgroundPedigree-based inbreeding coefficients have been generally included in statistical models for genetic evaluation of Japanese Black cattle. The use of genomic data is expected to provide precise assessment of inbreeding level and depression. Recently, many measures have been used for genome-based inbreeding coefficients; however, with no consensus on which is the most appropriate. Therefore, we compared the pedigree- ({F}_{PED}) and multiple genome-based inbreeding coefficients, which were calculated from the genomic relationship matrix with observed allele frequencies ({F}_{GRM}), correlation between uniting gametes ({F}_{UNI}), the observed vs expected number of homozygous genotypes ({F}_{HOM}), runs of homozygosity (ROH) segments ({F}_{ROH}) and heterozygosity by descent segments ({F}_{HBD}). We quantified inbreeding depression from estimating regression coefficients of inbreeding coefficients on three reproductive traits: age at first calving (AFC), calving difficulty (CD) and gestation length (GL) in Japanese Black cattle.ResultsThe highest correlations with {F}_{PED} were for {F}_{ROH} (0.86) and {F}_{HBD} (0.85) whereas {F}_{GRM} and {F}_{UNI} provided weak correlations with {F}_{PED}, with range 0.33–0.55. Except for {F}_{GRM} and {F}_{UNI}, there were strong correlations among genome-based inbreeding coefficients (ge 0.94). The estimates of regression coefficients of inbreeding depression for {F}_{PED} was 2.1 for AFC, 0.63 for CD and -1.21 for GL, respectively, but {F}_{PED} had no significant effects on all traits. Genome-based inbreeding coefficients provided larger effects on all reproductive traits than {F}_{PED}. In particular, for CD, all estimated regression coefficients for genome-based inbreeding coefficients were significant, and for GL, that for {F}_{UNI} had a significant.. Although there were no significant effects when using overall genome-level inbreeding coefficients for AFC and GL, {F}_{ROH} provided significant effects at chromosomal level in four chromosomes for AFC, three chromosomes for CD, and two chromosomes for GL. In addition, similar results were obtained for {F}_{HBD}.ConclusionsGenome-based inbreeding coefficients can capture more phenotypic variation than {F}_{PED}. In particular, {F}_{ROH} and {F}_{HBD} can be considered good estimators for quantifying inbreeding level and identifying inbreeding depression at the chromosome level. These findings might improve the quantification of inbreeding and breeding programs using genome-based inbreeding coefficients.