Stress-induced epigenetic effects driven by maternal lactation in dairy cattle: a comethylation network approach.

Epigenetic marks do not follow the Mendelian laws of inheritance. The environment can alter the epigenotype of an individual when exposed to different external stressors. In lactating cows, the first stages of gestation overlap with the lactation peak, creating a negative energy balance that is difficult to overcome with diet. This negative energy balance could affect early embryo development that must compete with the mammary tissue for nutrients. We hypothesize that the methylation profiles of calves born to nonlactating heifers are different from those of calves born to lactating cows. We found 50,277 differentially methylated cytosines and 2,281 differentially methylated regions between these two groups of animals. A comethylation network was constructed to study the correlation between the phenotypes of the mothers and the epigenome of the calves, revealing 265 regions associated with the phenotypes. Our study revealed the presence of DMCs and DMRs in calves gestated by heifers and lactating cows, which were linked to the dam's lactation and the calves' ICAP and milk EBV. Gene-specific analysis highlighted associations with vasculature and organ morphogenesis and cell communication and signalling. These finding support the hypothesis that calves gestated by nonlactating mothers have a different methylation profile than those gestated by lactating cows.

Transcriptional response to an alternative diet on liver, muscle, and rumen of beef cattle.

Feed cost represents a major economic determinant within cattle production, amounting to an estimated 75% of the total variable costs. Consequently, comprehensive approaches such as optimizing feed utilization through alternative feed sources, alongside the selection of feed-efficient animals, are of great significance. Here, we investigate the effect of two diets, traditional corn-grain fed and alternative by-product based, on 14 phenotypes related to feed, methane emission and production efficiency and on multi-tissue transcriptomics data from liver, muscle, and rumen wall, derived from 52 Nellore bulls, 26 on each diet. To this end, diets were contrasted at the level of phenotype, gene expression, and gene-phenotype network connectivity. As regards the phenotypic level, at a P value < 0.05, significant differences were found in favour of the alternative diet for average daily weight gain at finishing, dry matter intake at finishing, methane emission, carcass yield and subcutaneous fat thickness at the rib-eye muscle area. In terms of the transcriptional level of the 14,776 genes expressed across the examined tissues, we found 487, 484, and 499 genes differentially expressed due to diet in liver, muscle, and rumen, respectively (P value < 0.01). To explore differentially connected phenotypes across both diet-based networks, we focused on the phenotypes with the largest change in average number of connections within diets and tissues, namely methane emission and carcass yield, highlighting, in particular, gene expression changes involving SREBF2, and revealing the largest differential connectivity in rumen and muscle, respectively. Similarly, from examination of differentially connected genes across diets, the top-ranked most differentially connected regulators within each tissue were MEOX1, PTTG1, and BASP1 in liver, muscle, and rumen, respectively. Changes in gene co-expression patterns suggest activation or suppression of specific biological processes and pathways in response to dietary interventions, consequently impacting the phenotype. The identification of genes that respond differently to diets and their associated phenotypic effects serves as a crucial stepping stone for further investigations, aiming to build upon our discoveries. Ultimately, such advancements hold the promise of improving animal welfare, productivity, and sustainability in livestock farming.

An association weight matrix identified biological pathways associated with bull fertility traits in a multi-breed population.

Using seven indicator traits, we investigated the genetic basis of bull fertility and predicted gene interactions from SNP associations. We used percent normal sperm as the key phenotype for the association weight matrix-partial correlation information theory (AWM-PCIT) approach. Beyond a simple list of candidate genes, AWM-PCIT predicts significant gene interactions and associations for the selected traits. These interactions formed a network of 537 genes: 38 genes were transcription cofactors, and 41 genes were transcription factors. The network displayed two distinct clusters, one with 294 genes and another with 243 genes. The network is enriched in fertility-associated pathways: steroid biosynthesis, p53 signalling, and the pentose phosphate pathway. Enrichment analysis also highlighted gene ontology terms associated with 'regulation of neurotransmitter secretion' and 'chromatin formation'. Our network recapitulates some genes previously implicated in another network built with lower-density genotypes. Sequence-level data also highlights additional candidate genes relevant to bull fertility, such as FOXO4, FOXP3, GATA1, CYP27B1, and EBP. A trio of regulatory genes-KDM5C, LRRK2, and PME-was deemed core to the network because of their overarching connections. This trio probably influences bull fertility through their interaction with genes, both known and unknown as to their role in male fertility. Future studies may target the trio and their target genes to enrich our understanding of male fertility further.

Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test.

BACKGROUND: The study of ancestral alleles provides insights into the evolutionary history, selection, and genetic structures of a population. In cattle, ancestral alleles are widely used in genetic analyses, including the detection of signatures of selection, determination of breed ancestry, and identification of admixture. Having a comprehensive list of ancestral alleles is expected to improve the accuracy of these genetic analyses. However, the list of ancestral alleles in cattle, especially at the whole genome sequence level, is far from complete. In fact, the current largest list of ancestral alleles (~ 42 million) represents less than 28% of the total number of detected variants in cattle. To address this issue and develop a genomic resource for evolutionary studies, we determined ancestral alleles in cattle by comparing prior derived whole-genome sequence variants to an out-species group using a population-based likelihood ratio test. RESULTS: Our study determined and makes available the largest list of ancestral alleles in cattle to date (70.1 million) and includes 2.3 million on the X chromosome. There was high concordance (97.6%) of the determined ancestral alleles with those from previous studies when only high-probability ancestral alleles were considered (29.8 million positions) and another 23.5 million high-confidence ancestral alleles were novel, expanding the available reference list to improve the accuracies of genetic analyses involving ancestral alleles. The high concordance of the results with previous studies implies that our approach using genomic sequence variants and a likelihood ratio test to determine ancestral alleles is appropriate. CONCLUSIONS: Considering the high concordance of ancestral alleles across studies, the ancestral alleles determined in this study including those not previously listed, particularly those with high-probability estimates, may be used for further genetic analyses with reasonable accuracy. Our approach that used predetermined variants in species and the likelihood ratio test to determine ancestral alleles is applicable to other species for which sequence level genotypes are available.

Phenotypic divergence between broiler and layer chicken lines is regulated at the molecular level during development.

BACKGROUND: Understanding the molecular underpinnings of phenotypic variations is critical for enhancing poultry breeding programs. The Brazilian broiler (TT) and laying hen (CC) lines exhibit striking differences in body weight, growth potential, and muscle mass. Our work aimed to compare the global transcriptome of wing and pectoral tissues during the early development (days 2.5 to 3.5) of these chicken lines, unveiling disparities in gene expression and regulation. RESULTS: Different and bona-fide transcriptomic profiles were identified for the compared lines. A similar number of up- and downregulated differentially expressed genes (DEGs) were identified, considering the broiler line as a reference. Upregulated DEGs displayed an enrichment of protease-encoding genes, whereas downregulated DEGs exhibited a prevalence of receptors and ligands. Gene Ontology analysis revealed that upregulated DEGs were mainly associated with hormone response, mitotic cell cycle, and different metabolic and biosynthetic processes. In contrast, downregulated DEGs were primarily linked to communication, signal transduction, cell differentiation, and nervous system development. Regulatory networks were constructed for the mitotic cell cycle and cell differentiation biological processes, as their contrasting roles may impact the development of distinct postnatal traits. Within the mitotic cell cycle network, key upregulated DEGs included CCND1 and HSP90, with central regulators being NF-κB subunits (RELA and REL) and NFATC2. The cell differentiation network comprises numerous DEGs encoding transcription factors (e.g., HOX genes), receptors, ligands, and histones, while the main regulatory hubs are CREB, AR and epigenetic modifiers. Clustering analyses highlighted PIK3CD as a central player within the differentiation network. CONCLUSIONS: Our study revealed distinct developmental transcriptomes between Brazilian broiler and layer lines. The gene expression profile of broiler embryos seems to favour increased cell proliferation and delayed differentiation, which may contribute to the subsequent enlargement of pectoral tissues during foetal and postnatal development. Our findings pave the way for future functional studies and improvement of targeted traits of economic interest in poultry.

Analyzing Cattle Activity Patterns with Ear Tag Accelerometer Data.

In this study, we equip two breeds of cattle located in tropical and temperate climates with smart ear tags containing triaxial accelerometers to measure their activity levels across different time periods. We produce activity profiles when measured by each of four statistical features, the mean, median, standard deviation, and median absolute deviation of the Euclidean norm of either unfiltered or high-pass-filtered accelerometer readings over five-minute windows. We then aggregate the values from the 5 min windows into hourly or daily (24 h) totals to produce activity profiles for animals kept in each of the test environments. To gain a better understanding of the variation between the peak and nadir activity levels within a 24 h period, we divide each day into multiple equal-length intervals, which can range from 2 to 96 intervals. We then calculate a statistical measure, called daily differential activity (DDA), by computing the differences in feature values for each interval pair. Our findings demonstrate that patterns within the activity profile are more clearly visualised from readings that have been subject to high-pass filtering and that the median of the acceleration vector norm is the most reliable feature for characterising activity and calculating the DDA measure. The underlying causes for these differences remain elusive and is likely attributable to environmental factors, cattle breeds, or management practices. Activity profiles produced from the standard deviation (a feature routinely applied to the quantification of activity level) showed less uniformity between animals and larger variation in values overall. Assessing activity using ear tag accelerometers holds promise for monitoring animal health and welfare. However, optimal results may only be attainable when true diurnal patterns are detected and accounted for.

Unravelling the genetic variability of host resilience to endo- and ectoparasites in Nellore commercial herds.

BACKGROUND: Host resilience (HR) to parasites can affect the performance of animals. Therefore, the aim of this study was to present a detailed investigation of the genetic mechanisms of HR to ticks (TICK), gastrointestinal nematodes (GIN), and Eimeria spp. (EIM) in Nellore cattle that were raised under natural infestation and a prophylactic parasite control strategy. In our study, HR was defined as the slope coefficient of body weight (BW) when TICK, GIN, and EIM burdens were used as environmental gradients in random regression models. In total, 1712 animals were evaluated at five measurement events (ME) at an average age of 331, 385, 443, 498, and 555 days, which generated 7307 body weight (BW) records. Of the 1712 animals, 1075 genotyped animals were used in genome-wide association studies to identify genomic regions associated with HR. RESULTS: Posterior means of the heritability estimates for BW ranged from 0.09 to 0.54 across parasites and ME. The single nucleotide polymorphism (SNP)-derived heritability for BW at each ME ranged from a low (0.09 at ME.331) to a moderate value (0.23 at ME.555). Those estimates show that genetic progress can be achieved for BW through selection. Both genetic and genomic associations between BW and HR to TICK, GIN, and EIM confirmed that parasite infestation impacted the performance of animals. Selection for BW under an environment with a controlled parasite burden is an alternative to improve both, BW and HR. There was no impact of age of measurement on the estimates of genetic variance for HR. Five quantitative trait loci (QTL) were associated with HR to EIM but none with HR to TICK and to GIN. These QTL contain genes that were previously shown to be associated with the production of antibody modulators and chemokines that are released in the intestinal epithelium. CONCLUSIONS: Selection for BW under natural infestation and controlled parasite burden, via prophylactic parasite control, contributes to the identification of animals that are resilient to nematodes and Eimeria ssp. Although we verified that sufficient genetic variation existed for HR, we did not find any genes associated with mechanisms that could justify the expression of HR to TICK and GIN.

Sequence level genome-wide associations for bull production and fertility traits in tropically adapted bulls.

BACKGROUND: The genetics of male fertility is complex and not fully understood. Male subfertility can adversely affect the economics of livestock production. For example, inadvertently mating bulls with poor fertility can result in reduced annual liveweight production and suboptimal husbandry management. Fertility traits, such as scrotal circumference and semen quality are commonly used to select bulls before mating and can be targeted in genomic studies. In this study, we conducted genome-wide association analyses using sequence-level data targeting seven bull production and fertility traits measured in a multi-breed population of 6,422 tropically adapted bulls. The beef bull production and fertility traits included body weight (Weight), body condition score (CS), scrotal circumference (SC), sheath score (Sheath), percentage of normal spermatozoa (PNS), percentage of spermatozoa with mid-piece abnormalities (MP) and percentage of spermatozoa with proximal droplets (PD). RESULTS: After quality control, 13,398,171 polymorphisms were tested for their associations with each trait in a mixed-model approach, fitting a multi-breed genomic relationship matrix. A Bonferroni genome-wide significance threshold of 5 × 10- 8 was imposed. This effort led to identifying genetic variants and candidate genes underpinning bull fertility and production traits. Genetic variants in Bos taurus autosome (BTA) 5 were associated with SC, Sheath, PNS, PD and MP. Whereas chromosome X was significant for SC, PNS, and PD. The traits we studied are highly polygenic and had significant results across the genome (BTA 1, 2, 4, 6, 7, 8, 11, 12, 14, 16, 18, 19, 23, 28, and 29). We also highlighted potential high-impact variants and candidate genes associated with Scrotal Circumference (SC) and Sheath Score (Sheath), which warrants further investigation in future studies. CONCLUSION: The work presented here is a step closer to identifying molecular mechanisms that underpin bull fertility and production. Our work also emphasises the importance of including the X chromosome in genomic analyses. Future research aims to investigate potential causative variants and genes in downstream analyses.

The identification and validation of target genes of IGFBP3 protein in sheep skeletal muscle cells.

This study aimed to identify the target genes of IGFBP3（insulin growth factor binding protein）protein and to investigate its target genes effects on the proliferation and differentiation of Hu sheep skeletal muscle cells. IGFBP3 was an RNA-binding protein that regulates mRNA stability. Previous studies have reported that IGFBP3 promotes the proliferation of Hu sheep skeletal muscle cells and inhibits differentiation, but the downstream genes that bind to it have not been reported yet. We predicted the target genes of IGFBP3 through RNAct and sequencing data, and verified by qPCR and RIP（RNA Immunoprecipitation）experiments, and demonstrated GNAI2（G protein subunit alpha i2）as one of the target gene of IGFBP3. After interference with siRNA, we carried out qPCR, CCK8, EdU, and immunofluorescence experiments, and found that GNAI2 can promote the proliferation and inhibit differentiation of Hu sheep skeletal muscle cells. This study revealed the effects of GNAI2 and provided one of the regulatory mechanisms of IGFBP3 protein underlying sheep muscle development.

Effect of CUX1 on the Proliferation of Hu Sheep Dermal Papilla Cells and on the Wnt/ß-Catenin Signaling Pathway.

CUT-like homeobox 1 protein (CUX1), also called CUX, CUTL1, and CDP, is a member of the DNA-binding protein homology family. Studies have shown that CUX1 is a transcription factor that plays an important role in the growth and development of hair follicles. The aim of this study was to investigate the effect of CUX1 on the proliferation of Hu sheep dermal papilla cells (DPCs) to reveal the role of CUX1 in hair follicle growth and development. First, the coding sequence (CDS) of CUX1 was amplified by PCR, and then CUX1 was overexpressed and knocked down in DPCs. A Cell Counting Kit-8 (CCK8), 5-ethynyl-2-deoxyuridine (EdU), and cell cycle assays were used to detect the changes in the proliferation and cell cycle of DPCs. Finally, the effects of overexpression and knockdown of CUX1 in DPCs on the expression of WNT10, MMP7, C-JUN, and other key genes in the Wnt/ß-catenin signaling pathway were detected by RT-qPCR. The results showed that the 2034-bp CDS of CUX1 was successfully amplified. Overexpression of CUX1 enhanced the proliferative state of DPCs, significantly increased the number of S-phase cells, and decreased the number of G0/G1-phase cells (p < 0.05). CUX1 knockdown had the opposite effects. It was found that the expression of MMP7, CCND1 (both p < 0.05), PPARD, and FOSL1 (both p < 0.01) increased significantly after overexpression of CUX1 in DPCs, while the expression of CTNNB1 (p < 0.05), C-JUN, PPARD, CCND1, and FOSL1 (all p < 0.01) decreased significantly. In conclusion, CUX1 promotes proliferation of DPCs and affects the expression of key genes of the Wnt/ß-catenin signaling pathway. The present study provides a theoretical basis to elucidate the mechanism underlying hair follicle development and lambskin curl pattern formation in Hu sheep.

Multi-breed genomic predictions and functional variants for fertility of tropical bulls.

Worldwide, most beef breeding herds are naturally mated. As such, the ability to identify and select fertile bulls is critically important for both productivity and genetic improvement. Here, we collected ten fertility-related phenotypes for 6,063 bulls from six tropically adapted breeds. Phenotypes were comprised of four bull conformation traits and six traits directly related to the quality of the bull's semen. We also generated high-density DNA genotypes for all the animals. In total, 680,758 single nucleotide polymorphism (SNP) genotypes were analyzed. The genomic correlation of the same trait observed in different breeds was positive for scrotal circumference and sheath score on most breed comparisons, but close to zero for the percentage of normal sperm, suggesting a divergent genetic background for this trait. We confirmed the importance of a breed being present in the reference population to the generation of accurate genomic estimated breeding values (GEBV) in an across-breed validation scenario. Average GEBV accuracies varied from 0.19 to 0.44 when the breed was not included in the reference population. The range improved to 0.28 to 0.59 when the breed was in the reference population. Variants associated with the gene HDAC4, six genes from the spermatogenesis-associated (SPATA) family of proteins, and 29 transcription factors were identified as candidate genes. Collectively these results enable very early in-life selection for bull fertility traits, supporting genetic improvement strategies currently taking place within tropical beef production systems. This study also improves our understanding of the molecular basis of male fertility in mammals.

Leveraging transcriptome and epigenome landscapes to infer regulatory networks during the onset of sexual maturation.

BACKGROUND: Despite sexual development being ubiquitous to vertebrates, the molecular mechanisms underpinning this fundamental transition remain largely undocumented in many organisms. We designed a time course experiment that successfully sampled the period when Atlantic salmon commence their trajectory towards sexual maturation. RESULTS: Through deep RNA sequencing, we discovered key genes and pathways associated with maturation in the pituitary-ovarian axis. Analyzing DNA methylomes revealed a bias towards hypermethylation in ovary that implicated maturation-related genes. Co-analysis of DNA methylome and gene expression changes revealed chromatin remodeling genes and key transcription factors were both significantly hypermethylated and upregulated in the ovary during the onset of maturation. We also observed changes in chromatin state landscapes that were strongly correlated with fundamental remodeling of gene expression in liver. Finally, a multiomic integrated analysis revealed regulatory networks and identified hub genes including TRIM25 gene (encoding the estrogen-responsive finger protein) as a putative key regulator in the pituitary that underwent a 60-fold change in connectivity during the transition to maturation. CONCLUSION: The study successfully documented transcriptome and epigenome changes that involved key genes and pathways acting in the pituitary - ovarian axis. Using a Systems Biology approach, we identified hub genes and their associated networks deemed crucial for onset of maturation. The results provide a comprehensive view of the spatiotemporal changes involved in a complex trait and opens the door to future efforts aiming to manipulate puberty in an economically important aquaculture species.

Leveraging host-genetics and gut microbiota to determine immunocompetence in pigs.

BACKGROUND: The gut microbiota influences host performance playing a relevant role in homeostasis and function of the immune system. The aim of the present work was to identify microbial signatures linked to immunity traits and to characterize the contribution of host-genome and gut microbiota to the immunocompetence in healthy pigs. RESULTS: To achieve this goal, we undertook a combination of network, mixed model and microbial-wide association studies (MWAS) for 21 immunity traits and the relative abundance of gut bacterial communities in 389 pigs genotyped for 70K SNPs. The heritability (h2; proportion of phenotypic variance explained by the host genetics) and microbiability (m2; proportion of variance explained by the microbial composition) showed similar values for most of the analyzed immunity traits, except for both IgM and IgG in plasma that was dominated by the host genetics, and the haptoglobin in serum which was the trait with larger m2 (0.275) compared to h2 (0.138). Results from the MWAS suggested a polymicrobial nature of the immunocompetence in pigs and revealed associations between pigs gut microbiota composition and 15 of the analyzed traits. The lymphocytes phagocytic capacity (quantified as mean fluorescence) and the total number of monocytes in blood were the traits associated with the largest number of taxa (6 taxa). Among the associations identified by MWAS, 30% were confirmed by an information theory network approach. The strongest confirmed associations were between Fibrobacter and phagocytic capacity of lymphocytes (r = 0.37), followed by correlations between Streptococcus and the percentage of phagocytic lymphocytes (r = -0.34) and between Megasphaera and serum concentration of haptoglobin (r = 0.26). In the interaction network, Streptococcus and percentage of phagocytic lymphocytes were the keystone bacterial and immune-trait, respectively. CONCLUSIONS: Overall, our findings reveal an important connection between gut microbiota composition and immunity traits in pigs, and highlight the need to consider both sources of information, host genome and microbial levels, to accurately characterize immunocompetence in pigs.

Chromatin accessibility and regulatory vocabulary across indicine cattle tissues.

BACKGROUND: Spatiotemporal changes in the chromatin accessibility landscape are essential to cell differentiation, development, health, and disease. The quest of identifying regulatory elements in open chromatin regions across different tissues and developmental stages is led by large international collaborative efforts mostly focusing on model organisms, such as ENCODE. Recently, the Functional Annotation of Animal Genomes (FAANG) has been established to unravel the regulatory elements in non-model organisms, including cattle. Now, we can transition from prediction to validation by experimentally identifying the regulatory elements in tropical indicine cattle. The identification of regulatory elements, their annotation and comparison with the taurine counterpart, holds high promise to link regulatory regions to adaptability traits and improve animal productivity and welfare. RESULTS: We generate open chromatin profiles for liver, muscle, and hypothalamus of indicine cattle through ATAC-seq. Using robust methods for motif discovery, motif enrichment and transcription factor binding sites, we identify potential master regulators of the epigenomic profile in these three tissues, namely HNF4, MEF2, and SOX factors, respectively. Integration with transcriptomic data allows us to confirm some of their target genes. Finally, by comparing our results with Bos taurus data we identify potential indicine-specific open chromatin regions and overlaps with indicine selective sweeps. CONCLUSIONS: Our findings provide insights into the identification and analysis of regulatory elements in non-model organisms, the evolution of regulatory elements within two cattle subspecies as well as having an immediate impact on the animal genetics community in particular for a relevant productive species such as tropical cattle.

Bias, dispersion, and accuracy of genomic predictions for feedlot and carcase traits in Australian Angus steers.

BACKGROUND: Improving feedlot performance, carcase weight and quality is a primary goal of the beef industry worldwide. Here, we used data from 3408 Australian Angus steers from seven years of birth (YOB) cohorts (2011-2017) with a minimal level of sire linkage and that were genotyped for 45,152 SNPs. Phenotypic records included two feedlot and five carcase traits, namely average daily gain (ADG), average daily dry matter intake (DMI), carcase weight (CWT), carcase eye muscle area (EMA), carcase Meat Standard Australia marbling score (MBL), carcase ossification score (OSS) and carcase subcutaneous rib fat depth (RIB). Using a 7-way cross-validation based on YOB cohorts, we tested the quality of genomic predictions using the linear regression (LR) method compared to the traditional method (Pearson's correlation between the genomic estimated breeding value (GEBV) and its associated adjusted phenotype divided by the square root of heritability); explored the factors, such as heritability, validation cohort, and phenotype that affect estimates of accuracy, bias, and dispersion calculated with the LR method; and suggested a novel interpretation for translating differences in accuracy into phenotypic differences, based on GEBV quartiles (Q1Q4). RESULTS: Heritability (h2) estimates were generally moderate to high (from 0.29 for ADG to 0.53 for CWT). We found a strong correlation (0.73, P-value < 0.001) between accuracies using the traditional method and those using the LR method, although the LR method was less affected by random variation within and across years and showed a better ability to discriminate between extreme GEBV quartiles. We confirmed that bias of GEBV was not significantly affected by h2, validation cohort or trait. Similarly, validation cohort was not a significant source of variation for any of the GEBV quality metrics. Finally, we observed that the phenotypic differences were larger for higher accuracies. CONCLUSIONS: Our estimates of h2 and GEBV quality metrics suggest a potential for accurate genomic selection of Australian Angus for feedlot performance and carcase traits. In addition, the Q1Q4 measure presented here easily translates into possible gains of genomic selection in terms of phenotypic differences and thus provides a more tangible output for commercial beef cattle producers.

Network Analyses Predict Small RNAs That Might Modulate Gene Expression in the Testis and Epididymis of Bos indicus Bulls.

Spermatogenesis relies on complex molecular mechanisms, essential for the genesis and differentiation of the male gamete. Germ cell differentiation starts at the testicular parenchyma and finishes in the epididymis, which has three main regions: head, body, and tail. RNA-sequencing data of the testicular parenchyma (TP), head epididymis (HE), and tail epididymis (TE) from four bulls (three biopsies per bull: 12 samples) were subjected to differential expression analyses, functional enrichment analyses, and co-expression analyses. The aim was to investigate the co-expression and infer possible regulatory roles for transcripts involved in the spermatogenesis of Bos indicus bulls. Across the three pairwise comparisons, 3,826 differentially expressed (DE) transcripts were identified, of which 384 are small RNAs. Functional enrichment analysis pointed to gene ontology (GO) terms related to ion channel activity, detoxification of copper, neuroactive receptors, and spermatogenesis. Using the regulatory impact factor (RIF) algorithm, we detected 70 DE small RNAs likely to regulate the DE transcripts considering all pairwise comparisons among tissues. The pattern of small RNA co-expression suggested that these elements are involved in spermatogenesis regulation. The 3,826 DE transcripts (mRNAs and small RNAs) were further subjected to co-expression analyses using the partial correlation and information theory (PCIT) algorithm for network prediction. Significant correlations underpinned the co-expression network, which had 2,216 transcripts connected by 158,807 predicted interactions. The larger network cluster was enriched for male gamete generation and had 15 miRNAs with significant RIF. The miRNA bta-mir-2886 showed the highest number of connections (601) and was predicted to down-regulate ELOVL3, FEZF2, and HOXA13 (negative co-expression correlations and confirmed with TargetScan). In short, we suggest that bta-mir-2886 and other small RNAs might modulate gene expression in the testis and epididymis, in Bos indicus cattle.

A conserved haplotype in Wagyu cattle contains RAB4A whose encoded protein regulates glucose trafficking in muscle and fat cells.

The Wagyu breed of taurine cattle possess favourable genetics for intramuscular fat (IMF) but genomic loci associated with the trait remain under characterised. Here, we report the identification of a previously unidentified genomic region possessing a particular haplotype structure in Wagyu. Through deployment of a genome-wide haplotype detection analysis that captures regions conserved in a target population but not other populations we screened 100 individual Wagyu and contrasted them with 100 individuals from two independent comparison breeds, Charolais and Angus, using high-density SNPs. An extreme level of Wagyu conservation was assigned to a single genomic window (spanning genomic coordinates BTA28:41 088-300 265 bp). In fact, a five-SNP region spanning 27 096 bp is almost perfectly conserved among the 100 Wagyu individuals assayed and partially overlaps RAB4A. Focussing in, two consecutive SNPs (genomic coordinates 236 949 and 239 950) are apparently fixed within the Wagyu (BB and AA respectively), but at mixed frequencies in the other two breeds. These SNPs are located in the two introns straddling exon 7. In a separate analysis using the 1000 Bulls database, we found that, coincident with exon 7 of RAB4A first allele frequencies were highest in the high IMF Japanese Native (Wagyu) breeds (0.78) and lowest in the low IMF indicine breeds (Nelore and Brahman), with intermediate marbling breeds (Angus and Charolais) assigned intermediate rankings (0.42). RAB4A is known to encode a protein that regulates intracellular trafficking of the insulin-regulated glucose transporter GLUT4. RAB4A can be considered an attractive new positional candidate for IMF development.

Identification of Predictor Genes for Feed Efficiency in Beef Cattle by Applying Machine Learning Methods to Multi-Tissue Transcriptome Data.

Machine learning (ML) methods have shown promising results in identifying genes when applied to large transcriptome datasets. However, no attempt has been made to compare the performance of combining different ML methods together in the prediction of high feed efficiency (HFE) and low feed efficiency (LFE) animals. In this study, using RNA sequencing data of five tissues (adrenal gland, hypothalamus, liver, skeletal muscle, and pituitary) from nine HFE and nine LFE Nellore bulls, we evaluated the prediction accuracies of five analytical methods in classifying FE animals. These included two conventional methods for differential gene expression (DGE) analysis (t-test and edgeR) as benchmarks, and three ML methods: Random Forests (RFs), Extreme Gradient Boosting (XGBoost), and combination of both RF and XGBoost (RX). Utility of a subset of candidate genes selected from each method for classification of FE animals was assessed by support vector machine (SVM). Among all methods, the smallest subsets of genes (117) identified by RX outperformed those chosen by t-test, edgeR, RF, or XGBoost in classification accuracy of animals. Gene co-expression network analysis confirmed the interactivity existing among these genes and their relevance within the network related to their prediction ranking based on ML. The results demonstrate a great potential for applying a combination of ML methods to large transcriptome datasets to identify biologically important genes for accurately classifying FE animals.

ImmuneDEX: a strategy for the genetic improvement of immune competence in Australian Angus cattle.

In animal breeding and genetics, the ability to cope with disease, here defined as immune competence (IC), with minimal detriment to growth and fertility is a desired objective which addresses both animal production and welfare considerations. However, defining and objectively measuring IC phenotypes using testing methods which are practical to apply on-farm has been challenging. Based on previously described protocols, we measured both cell-mediated immune response (Cell-IR) and antibody-mediated immune response (Ab-IR) and combined these measures to determine an animal's IC. Using a population of 2,853 Australian Angus steers and heifers, we compared 2 alternative methods to combine both metrics into a single phenotype to be used as a tool for the genetic improvement of IC. The first method, named ZMEAN, is obtained by taking the average of the individual metrics after subjecting each to a Z-score standardization. The second, ImmuneDEX (IDEX), is a weighted average that considers the correlation between Cell-IR and Ab-IR, as well as the difference in ranking of individuals by each metric, and uses these as weights in the averaging. Both simulation and real data were used to understand the behavior of ZMEAN and IDEX. To further ascertain the relationship between IDEX and other traits of economic importance, we evaluated a range of traits related to growth, feedlot performance, and carcass characteristics. We report estimates of heritability of 0.31 ± 0.06 for Cell-IR, 0.42 ± 0.06 for Ab-IR, 0.42 ± 0.06 for ZMEAN and 0.370 ± 0.06 for IDEX, as well as a unity genetic correlation (rg) between ZMEAN and IDEX. While a moderately positive rg was estimated between Cell-IR and Ab-IR (rg = 0.33 ± 0.12), strongly positive estimates were obtained between IDEX and Cell-IR (rg = 0.80 ± 0.05) and between IDEX and Ab-IR (rg = 0.85 ± 0.04). We obtained a moderately negative rg between IC traits and growth including an rg = -0.38 ± 0.14 between IDEX and weaning weight, and negligible with carcass fat measurements, including an rg = -0.03 ± 0.12 between IDEX and marbling. Given that breeding with a sole focus on production might inadvertently increase susceptibility to disease and associated antibiotic use, our analyses suggest that ImmuneDEX will provide a basis to breed animals that are both highly productive and with an enhanced ability to resist disease.