In vitro- and in vivo-produced male dairy calves show molecular differences in the hepatic and muscular energy regulation†.

In cattle, the in vitro production (IVP) of embryos is becoming more relevant than embryos produced in vivo, i.e. after multiple ovulation and embryo transfer (MOET). However, the effects of IVP on the developmental programming of specific organs in the postnatal calves are yet unknown. Previously, we reported an epigenomic and transcriptomic profile of the hypothalamus-pituitary-testicular axis compatible with its earlier activation in IVP calves compared to MOET animals. Here, we studied the hepatic and muscular epigenome and transcriptome of those same male dairy calves (n = 4 per group). Tissue samples from liver and semitendinosus muscle were obtained at 3 months of age, and the extracted gDNA and RNA were sequenced through whole-genome bisulfite sequencing and RNA-sequencing, respectively. Next, bioinformatic analyses determined differentially methylated cytosines or differentially expressed genes [false discovery rate (FDR) < 0.05] for each Omic dataset; and nonparametrically combined genes (NPCG) for both integrated omics (P < 0.05). KEGG pathways enrichment analysis showed that NPCG upregulated in the liver and the muscle of the IVP calves were involved in oxidative phosphorylation and the tricarboxylic acid cycle. In contrast, ribosome and translation were upregulated in the liver but downregulated in the muscle of the IVP calves compared to the MOET calves (FDR < 0.05). A model considering the effect of the methylation levels and the group on the expression of all the genes involved in these pathways confirmed these findings. In conclusion, the multiomics data integration approach indicated an altered hepatic and muscular energy regulation in phenotypically normal IVP calves compared to MOET calves.

Host Genome-Metagenome Analyses Using Combinatorial Network Methods Reveal Key Metagenomic and Host Genetic Features for Methane Emission and Feed Efficiency in Cattle.

Cattle production is one of the key contributors to global warming due to methane emission, which is a by-product of converting feed stuff into milk and meat for human consumption. Rumen hosts numerous microbial communities that are involved in the digestive process, leading to notable amounts of methane emission. The key factors underlying differences in methane emission between individual animals are due to, among other factors, both specific enrichments of certain microbial communities and host genetic factors that influence the microbial abundances. The detection of such factors involves various biostatistical and bioinformatics methods. In this study, our main objective was to reanalyze a publicly available data set using our proprietary Synomics Insights platform that is based on novel combinatorial network and machine learning methods to detect key metagenomic and host genetic features for methane emission and residual feed intake (RFI) in dairy cattle. The other objective was to compare the results with publicly available standard tools, such as those found in the microbiome bioinformatics platform QIIME2 and classic GWAS analysis. The data set used was publicly available and comprised 1,016 dairy cows with 16S short read sequencing data from two dairy cow breeds: Holstein and Nordic Reds. Host genomic data consisted of both 50 k and 150 k SNP arrays. Although several traits were analyzed by the original authors, here, we considered only methane emission as key phenotype for associating microbial communities and host genetic factors. The Synomics Insights platform is based on combinatorial methods that can identify taxa that are differentially abundant between animals showing high or low methane emission or RFI. Focusing exclusively on enriched taxa, for methane emission, the study identified 26 order-level taxa that combinatorial networks reported as significantly enriched either in high or low emitters. Additionally, a Z-test on proportions found 21/26 (81%) of these taxa were differentially enriched between high and low emitters (p value <.05). In particular, the phylum of Proteobacteria and the order Desulfovibrionales were found enriched in high emitters while the order Veillonellales was found to be more abundant in low emitters as previously reported for cattle (Wallace et al., 2015). In comparison, using the publicly available tool ANCOM only the order Methanosarcinales could be identified as differentially abundant between the two groups. We also investigated a link between host genome and rumen microbiome by applying our Synomics Insights platform and comparing it with an industry standard GWAS method. This resulted in the identification of genetic determinants in cows that are associated with changes in heritable components of the rumen microbiome. Only four key SNPs were found by both our platform and GWAS, whereas the Synomics Insights platform identified 1,290 significant SNPs that were not found by GWAS. Gene Ontology (GO) analysis found transcription factor as the dominant biological function. We estimated heritability of a core 73 taxa from the original set of 150 core order-level taxonomies and showed that some species are medium to highly heritable (0.25-0.62), paving the way for selective breeding of animals with desirable core microbiome characteristics. We identified a set of 113 key SNPs associated with >90% of these core heritable taxonomies. Finally, we have characterized a small set (<10) of SNPs strongly associated with key heritable bacterial orders with known role in methanogenesis, such as Desulfobacterales and Methanobacteriales.

Epigenomic and transcriptomic analyses reveal early activation of the HPG axis in in vitro-produced male dairy calves.

In cattle, several calves born after IVP ("in vitro" embryo production) present similar birthweight to those generated after MOET (multiple ovulation and embryo transfer). However, the underlying molecular patterns in organs involved in the developmental process are unknown and could indicate physiological programming. The objectives of this study were: (1) to compare epigenomic and transcriptomic modifications in the hypothalamus, pituitary, gonadal and adrenal organs between 3 months old ovum pick-up-IVP and MOET male calves (n = 4 per group) and (2) to use blood epigenomic data to proxy methylation of the inner organs. Extracted gDNA and RNA were sequenced through whole-genome bisulfite sequencing and RNA sequencing, respectively. Next, bioinformatic analyses determined differentially methylated cytosines (DMC) and differentially expressed genes (DEG) (FDR < 0.05) in IVP versus MOET samples and the KEGG pathways that were overrepresented by genes associated with DMC or DEG (FDR < 0.1). Pathways related to hypothalamus, pituitary, gonadal (HPG) axis activation (GnRH secretion in the hypothalamus, GnRH signaling in the pituitary, and steroidogenesis in the testicle) were enriched in IVP calves. Modeling the effect of the methylation levels and the group on the expression of all the genes involved in these pathways confirmed their upregulation in HPG organs in IVP calves. The application of the DIABLO method allowed the identification of 15 epigenetic and five transcriptomic biomarkers, which were able to predict the embryo origin using the epigenomic data from the blood. In conclusion, the use of an integrated epigenomic-transcriptomic approach suggested an early activation of the HPG axis in male IVP calves compared to MOET counterparts, and the identification of potential biomarkers allowed the use of blood samples to proxy methylation levels of the relevant internal organs.

Application of multi-omics data integration and machine learning approaches to identify epigenetic and transcriptomic differences between in vitro and in vivo produced bovine embryos.

Pregnancy rates for in vitro produced (IVP) embryos are usually lower than for embryos produced in vivo after ovarian superovulation (MOET). This is potentially due to alterations in their trophectoderm (TE), the outermost layer in physical contact with the maternal endometrium. The main objective was to apply a multi-omics data integration approach to identify both temporally differentially expressed and differentially methylated genes (DEG and DMG), between IVP and MOET embryos, that could impact TE function. To start, four and five published transcriptomic and epigenomic datasets, respectively, were processed for data integration. Second, DEG from day 7 to days 13 and 16 and DMG from day 7 to day 17 were determined in the TE from IVP vs. MOET embryos. Third, genes that were both DE and DM were subjected to hierarchical clustering and functional enrichment analysis. Finally, findings were validated through a machine learning approach with two additional datasets from day 15 embryos. There were 1535 DEG and 6360 DMG, with 490 overlapped genes, whose expression profiles at days 13 and 16 resulted in three main clusters. Cluster 1 (188) and Cluster 2 (191) genes were down-regulated at day 13 or day 16, respectively, while Cluster 3 genes (111) were up-regulated at both days, in IVP embryos compared to MOET embryos. The top enriched terms were the KEGG pathway "focal adhesion" in Cluster 1 (FDR = 0.003), and the cellular component: "extracellular exosome" in Cluster 2 (FDR<0.0001), also enriched in Cluster 1 (FDR = 0.04). According to the machine learning approach, genes in Cluster 1 showed a similar expression pattern between IVP and less developed (short) MOET conceptuses; and between MOET and DKK1-treated (advanced) IVP conceptuses. In conclusion, these results suggest that early conceptuses derived from IVP embryos exhibit epigenomic and transcriptomic changes that later affect its elongation and focal adhesion, impairing post-transfer survival.

Protocol for Construction of Genome-Wide Epistatic SNP Networks Using WISH-R Package.

Epistasis is the interaction between genes or genetic variants (such as Single Nucleotide Polymorphisms or SNPs) that influences a phenotype or a disease outcome. Statistically and biologically, significant evidence of epistatic loci for several traits and diseases is well known in human, animals, and plants. However, there is no straightforward way to compute a large number of pairwise epistasis among millions of variants along the whole genome, relate them to phenotypes or diseases, and visualize them. The WISH-R package (WISH-R) was developed to address this technology gap to calculate epistatic interactions using a linear or generalized linear model on a genome-wide level using genomic data and phenotype/disease data in a fully parallelized environment, and visualize genome-wide epistasis in many ways. This method protocol chapter provides an easy-to-follow systematic guide to install this R software in computers on Win OS, Mac OS, and Linux platforms and can be downloaded from https://github.com/QSG-Group/WISH with a user guide. The WISH-R package has several inbuilt functions to reduce genotype data dimensionality and hence computational demand. WISH-R software can be used to build scale-free weighted SNP interaction networks and relate them to quantitative traits or phenotypes and case-control diseases outcomes. The software leads to integrating biological knowledge to identify disease- or trait-relevant SNP or gene modules, hub genes, potential biomarkers, and pathways related to complex traits and diseases.

Impact of IL-17F 7488T/C Functional Polymorphism on Progressive Rheumatoid Arthritis: Novel Insight from the Molecular Dynamic Simulations.

Resorption of bones and cartilage coupled with structural changes in the inflamed joints are the major hallmark of rheumatoid arthritis (RA). Genetic polymorphisms in pro-inflammatory interleukins (ILs) appear to play an important role in the susceptibility towards progressive RA. We therefore aimed to investigate the association of single nucleotide polymorphisms (SNP), present in the hotspot coding/promoter regions of IL-6, -17 and -18, with RA susceptibility or severity in a larger study cohort from Pakistan together with finding clues as to how a functional SNP impacts the predisposition towards RA. TaqMan SNP genotyping approach was first used to assess IL-6 (rs1800795), IL-17 F (rs763780), IL-17A (rs2275913), and IL-18 (rs1946518) polymorphisms in 310 subjects (150 RA and 160 control). Molecular dynamic simulations (MDS) of wild- and mutant-type IL-17A with corresponding receptor were thereafter performed using AMBER-16; Chimera 1.13 was used for analyses. Our results showed the association of two SNPs, namely IL-6 - 174 G/C [allelic (OR = 0.960, 95% CI = 0.929-0.992, p = .009)] and IL-17 F 7488 T/C [allelic (OR = 0.907, 95%CI = 0.861-0.954, p = .000)] with increased RA risk in Pakistani subjects. When mapped, IL-17 F 7488 T/C was found involved in His161→Arg161 change near the C-terminus of IL-17 F. Comparative MDS revealed enhanced stability of the mutant hence advocating a potential role of IL-17F functional SNP in RA susceptibility and/or severity. This study provides a novel structural insight for SNP-derived functional mutation and its overall impact on binding with heterotrimeric receptor complex of IL-17 receptor thereby opening new avenues for understanding the biochemical basis of the disease.

GeneDMRs: An R Package for Gene-Based Differentially Methylated Regions Analysis.

DNA methylation in gene or gene body could influence gene transcription. Moreover, methylation in gene regions along with CpG island regions could modulate the transcription to undetectable gene expression levels. Therefore, it is necessary to investigate the methylation levels within the gene, gene body, CpG island regions, and their overlapped regions and then identify the gene-based differentially methylated regions (GeneDMRs). In this study, R package GeneDMRs aims to facilitate computing gene-based methylation rate using next-generation sequencing-based methylome data. The user-friendly GeneDMRs package is presented to analyze the methylation levels in each gene/promoter/exon/intron/CpG island/CpG island shore or each overlapped region (e.g., gene-CpG island/promoter-CpG island/exon-CpG island/intron-CpG island/gene-CpG island shore/promoter-CpG island shore/exon-CpG island shore/intron-CpG island shore). GeneDMRs can also interpret complex interplays between methylation levels and gene expression differences or similarities across physiological conditions or disease states. We used the public reduced representation bisulfite sequencing data of mouse (GSE62392) for evaluating software and revealing novel biologically significant results to supplement the previous research. In addition, the whole-genome bisulfite sequencing data of cattle (GSE106538) given the much larger size was used for further evaluation.

Machine learning approach to integrated endometrial transcriptomic datasets reveals biomarkers predicting uterine receptivity in cattle at seven days after estrous.

The main goal was to apply machine learning (ML) methods on integrated multi-transcriptomic data, to identify endometrial genes capable of predicting uterine receptivity according to their expression patterns in the cow. Public data from five studies were re-analyzed. In all of them, endometrial samples were obtained at day 6-7 of the estrous cycle, from cows or heifers of four different European breeds, classified as pregnant (n = 26) or not (n = 26). First, gene selection was performed through supervised and unsupervised ML algorithms. Then, the predictive ability of potential key genes was evaluated through support vector machine as classifier, using the expression levels of the samples from all the breeds but one, to train the model, and the samples from that one breed, to test it. Finally, the biological meaning of the key genes was explored. Fifty genes were identified, and they could predict uterine receptivity with an overall 96.1% accuracy, despite the animal's breed and category. Genes with higher expression in the pregnant cows were related to circadian rhythm, Wnt receptor signaling pathway, and embryonic development. This novel and robust combination of computational tools allowed the identification of a group of biologically relevant endometrial genes that could support pregnancy in the cattle.

Bovine in-vitro produced embryos: Development of embryo proper and associated membranes from day 26 to 47 of gestation.

Based on in-vitro produced (IVP) bovine embryos, embryo proper and embryonic/fetal membranes were studied in 12 pregnancies from day 26 to 47. The embryos/fetuses displayed external as well as internal development of organs and structures according to the expectations from comparable in-vivo studies. However, the embryonic/fetal membranes were shorter than those reported for in-vivo-derived embryos/fetuses on days 26-35 of calculated age, whereas on days 41-47 they were of comparable lengths.

Genetic variations (eQTLs) in muscle transcriptome and mitochondrial genes, and trans-eQTL molecular pathways in feed efficiency from Danish breeding pigs.

Feed efficiency (FE) is a key trait in pig production, as improvement in FE has positive economic and environmental impact. FE is a complex phenotype and testing animals for FE is costly. Therefore, there has been a desire to find functionally relevant single nucleotide polymorphisms (SNPs) as biomarkers, to improve our biological understanding of FE as well as accuracy of genomic prediction for FE. We have performed a cis- and trans- eQTL (expression quantitative trait loci) analysis, in a population of Danbred Durocs (N = 11) and Danbred Landrace (N = 27) using both a linear and ANOVA model based on muscle tissue RNA-seq. We analyzed a total of 1425x19179 or 2.7x107 Gene-SNP combinations in eQTL detection models for FE. The 1425 genes were from RNA-Seq based differential gene expression analyses using 25880 genes related to FE and additionally combined with mitochondrial genes. The 19179 SNPs were from applying stringent quality control and linkage disequilibrium filtering on genotype data using a GGP Porcine HD 70k SNP array. We applied 1000 fold bootstrapping and enrichment analysis to further validate and analyze our detected eQTLs. We identified 13 eQTLs with FDR < 0.1, affecting several genes found in previous studies of commercial pig breeds. Examples include MYO19, CPT1B, ACSL1, IER5L, CPT1A, SUCLA2, CSRNP1, PARK7 and MFF. The bootstrapping results showed statistically significant enrichment (p-value<2.2x10-16) of eQTLs with p-value < 0.01 in both cis and trans-eQTLs. Enrichment analysis of top trans-eQTLs revealed high enrichment for gene categories and gene ontologies associated with genomic context and expression regulation. This included transcription factors (p-value = 1.0x10-13), DNA-binding (GO:0003677, p-value = 8.9x10-14), DNA-binding transcription factor activity (GO:0003700,) nucleus gene (GO:0005634, p-value<2.2x10-16), negative regulation of expression (GO:0010629, p-value<2.2x10-16). These results would be useful for future genome assisted breeding of pigs to improve FE, and in the improved understanding of the functional mechanism of trans eQTLs.

Genome Regulation and Gene Interaction Networks Inferred From Muscle Transcriptome Underlying Feed Efficiency in Pigs.

Improvement of feed efficiency (FE) is key for Sustainability and cost reduction in pig production. Our aim was to characterize the muscle transcriptomic profiles in Danbred Duroc (Duroc; n = 13) and Danbred Landrace (Landrace; n = 28), in relation to FE for identifying potential biomarkers. RNA-seq data on the 41 pigs was analyzed employing differential gene expression methods, gene-gene interaction and network analysis, including pathway and functional analysis. We also compared the results with genome regulation in human exercise data, hypothesizing that increased FE mimics processes triggered in exercised muscle. In the differential expression analysis, 13 genes were differentially expressed, including: MRPS11, MTRF1, TRIM63, MGAT4A, KLH30. Based on a novel gene selection method, the divergent count, we performed pathway enrichment analysis. We found five significantly enriched pathways related to feed conversion ratio (FCR). These pathways were mainly related to mitochondria, and summarized in the mitochondrial translation elongation (MTR) pathway. In the gene interaction analysis, the most interesting genes included the mitochondrial genes: PPIF, MRPL35, NDUFS4 and the fat metabolism and obesity genes: AACS, SMPDL3B, CTNNBL1, NDUFS4, and LIMD2. In the network analysis, we identified two modules significantly correlated with FCR. Pathway enrichment of module genes identified MTR, electron transport chain and DNA repair as enriched pathways. The network analysis revealed the mitochondrial gene group NDUF as key network hub genes, showing their potential as biomarkers. Results show that genes related to human exercise were enriched in identified FCR related genes. We conclude that mitochondrial activity is a key driver for FCR in muscle tissue, and mitochondrial genes could be potential biomarkers for FCR in pigs.

Genetic Parameters and Genome-Wide Association Studies for Anti-Müllerian Hormone Levels and Antral Follicle Populations Measured After Estrus Synchronization in Nellore Cattle.

Reproductive efficiency plays a major role in the long-term sustainability of livestock industries and can be improved through genetic and genomic selection. This study aimed to estimate genetic parameters (heritability and genetic correlation) and identify genomic regions and candidate genes associated with anti-Müllerian hormone levels (AMH) and antral follicle populations measured after estrous synchronization (AFP) in Nellore cattle. The datasets included phenotypic records for 1099 and 289 Nellore females for AFP and AMH, respectively, high-density single nucleotide polymorphism (SNP) genotypes for 944 animals, and 4129 individuals in the pedigree. The heritability estimates for AMH and AFP were 0.28 ± 0.07 and 0.30 ± 0.09, and the traits were highly and positively genetically correlated (rG = 0.81 ± 0.02). These findings indicated that these traits can be improved through selective breeding, and substantial indirect genetic gains are expected by selecting for only one of the two traits. A total of 31 genomic regions were shown to be associated with AMH or AFP, and two genomic regions located on BTA1 (64.9-65.0 Mb and 109.1-109.2 Mb) overlapped between the traits. Various candidate genes were identified to be potentially linked to important biological processes such as ovulation, tissue remodeling, and the immune system. Our findings support the use of AMH and AFP as indicator traits to genetically improve fertility rates in Nellore cattle and identify better oocyte donors.

Integrative Analysis of Metabolomic and Transcriptomic Profiles Uncovers Biological Pathways of Feed Efficiency in Pigs.

Feed efficiency (FE) is an economically important trait. Thus, reliable predictors would help to reduce the production cost and provide sustainability to the pig industry. We carried out metabolome-transcriptome integration analysis on 40 purebred Duroc and Landrace uncastrated male pigs to identify potential gene-metabolite interactions and explore the molecular mechanisms underlying FE. To this end, we applied untargeted metabolomics and RNA-seq approaches to the same animals. After data quality control, we used a linear model approach to integrate the data and find significant differently correlated gene-metabolite pairs separately for the breeds (Duroc and Landrace) and FE groups (low and high FE) followed by a pathway over-representation analysis. We identified 21 and 12 significant gene-metabolite pairs for each group. The valine-leucine-isoleucine biosynthesis/degradation and arginine-proline metabolism pathways were associated with unique metabolites. The unique genes obtained from significant metabolite-gene pairs were associated with sphingolipid catabolism, multicellular organismal process, cGMP, and purine metabolic processes. While some of the genes and metabolites identified were known for their association with FE, others are novel and provide new avenues for further research. Further validation of genes, metabolites, and gene-metabolite interactions in larger cohorts will elucidate the regulatory mechanisms and pathways underlying FE.

Characterization of the endometrial transcriptome in early diestrus influencing pregnancy status in dairy cattle after transfer of in vitro-produced embryos.

Modifications of the endometrial transcriptome at day 7 of the estrus cycle are crucial to maintain gestation after transfer of in vitro-produced (IVP) embryos, although these changes are still largely unknown. The aim of this study was to identify genes, and their related biological mechanisms, important for pregnancy establishment based on the endometrial transcriptome of recipient lactating dairy cows that become pregnant in the subsequent estrus cycle, upon transfer of IVP embryos. Endometrial biopsies were taken from Holstein Friesian cows on day 6-8 of the estrus cycle followed by embryo transfer in the following cycle. Animals were classified retrospectively as pregnant (PR, n = 8) or nonpregnant (non-PR, n = 11) cows, according to pregnancy status at 26-47 days. Extracted mRNAs from endometrial samples were sequenced with an Illumina platform to determine differentially expressed genes (DEG) between the endometrial transcriptome from PR and non-PR cows. There were 111 DEG (false discovery rate < 0.05), which were mainly related to extracellular matrix interaction, histotroph metabolic composition, prostaglandin synthesis, transforming growth factor-ß signaling as well as inflammation and leukocyte activation. Comparison of these DEG with DEG identified in two public external data sets confirmed the more fertile endometrial molecular profile of PR cows. In conclusion, this study provides insights into the key early endometrial mechanisms for pregnancy establishment, after IVP embryo transfer in dairy cows.

Characterization of Global DNA Methylation in Different Gene Regions Reveals Candidate Biomarkers in Pigs with High and Low Levels of Boar Taint.

DNA methylation of different gene components, including different exons and introns, or different lengths of exons and introns is associated with differences in gene expression. To investigate the methylation of porcine gene components associated with the boar taint (BT) trait, this study used reduced representation bisulfite sequencing (RRBS) data from nine porcine testis samples in three BT groups (low, medium and high BT). The results showed that the methylation levels of the first exons and first introns were lower than those of the other exons and introns. The first exons/introns of CpG island regions had even lower levels of methylation. A total of 123 differentially methylated promoters (DMPs), 194 differentially methylated exons (DMEs) and 402 differentially methylated introns (DMIs) were identified, of which 80 DMPs (DMP-CpGis), 112 DMEs (DME-CpGis) and 166 DMIs (DMI-CpGis) were discovered in CpG islands. Importantly, GPX1 contained one each of DMP, DME, DMI, DMP-CpGi, DME-CpGi and DMI-CpGi. Gene-GO term relationships and pathways analysis showed DMP-CpGi-related genes are mainly involved in methylation-related biological functions. In addition, gene-gene interaction networks consisted of nodes that were hypo-methylated GPX1, hypo-methylated APP, hypo-methylated ATOX1, hyper-methylated ADRB2, hyper-methylated RPS6KA1 and hyper-methylated PNMT. They could be used as candidate biomarkers for reducing boar taint in pigs, after further validation in large cohorts.

Transcriptomic changes in bovine skeletal muscle cells after resveratrol treatment.

Skeletal muscles constitute a high proportion of the cellular mass that is essential for the growth traits in cattle. Resveratrol (RSV) is a natural polyphenol compound involved in pleiotropic biological activities of muscle. Therefore, the aim of our study was to investigate the transcriptome-level effects of RSV on bovine primary myoblast to reveal differentially expressed genes (DEGs). We treated three replicates of primary myoblasts with 20 µM mother solution containing RSV, whereas three other replicates without RSV were used as control group. Then, we conducted genome-wide transcriptome analysis for the two groups. The results of expression analysis identified 3856 DEGs of which 1805 genes were up-regulated and 2051 genes were down-regulated (adjusted P < 0.05). In addition, qRT-PCR analysis of 19 selected DEGs were consistent with the expression levels observed in the transcriptome data. Gene Ontology (GO) and pathway enrichment analysis showed 72 and 66 significant GO terms and KEGG pathways, respectively (adjusted P < 0.05). The most significant GO term was actin cytoskeleton organization (GO:0030036). The top significant KEGG pathway was focal adhesion (bta04510). Predicted protein-protein interactions (PPIs) showed that CDKN1A encoding cyclindependent kinase inhibitor 1A connects several larger protein complexes. In conclusion, our results found a list of DEGs, significant GO terms and pathways, and provided an improved and expanded understanding of the impact of RSV on cattle muscle cells at the transcriptomic level. The study elucidates the potential of using the genes enriched in pathways mediating resveratrol effects as targets in genomic selection for muscle development and growth in beef cattle.

Metabolite Genome-Wide Association Study (mGWAS) and Gene-Metabolite Interaction Network Analysis Reveal Potential Biomarkers for Feed Efficiency in Pigs.

Metabolites represent the ultimate response of biological systems, so metabolomics is considered the link between genotypes and phenotypes. Feed efficiency is one of the most important phenotypes in sustainable pig production and is the main breeding goal trait. We utilized metabolic and genomic datasets from a total of 108 pigs from our own previously published studies that involved 59 Duroc and 49 Landrace pigs with data on feed efficiency (residual feed intake (RFI)), genotype (PorcineSNP80 BeadChip) data, and metabolomic data (45 final metabolite datasets derived from LC-MS system). Utilizing these datasets, our main aim was to identify genetic variants (single-nucleotide polymorphisms (SNPs)) that affect 45 different metabolite concentrations in plasma collected at the start and end of the performance testing of pigs categorized as high or low in their feed efficiency (based on RFI values). Genome-wide significant genetic variants could be then used as potential genetic or biomarkers in breeding programs for feed efficiency. The other objective was to reveal the biochemical mechanisms underlying genetic variation for pigs' feed efficiency. In order to achieve these objectives, we firstly conducted a metabolite genome-wide association study (mGWAS) based on mixed linear models and found 152 genome-wide significant SNPs (p-value < 1.06 × 10-6) in association with 17 metabolites that included 90 significant SNPs annotated to 52 genes. On chromosome one alone, 51 significant SNPs associated with isovalerylcarnitine and propionylcarnitine were found to be in strong linkage disequilibrium (LD). SNPs in strong LD annotated to FBXL4, and CCNC consisted of two haplotype blocks where three SNPs (ALGA0004000, ALGA0004041, and ALGA0004042) were in the intron regions of FBXL4 and CCNC. The interaction network revealed that CCNC and FBXL4 were linked by the hub gene N6AMT1 that was associated with isovalerylcarnitine and propionylcarnitine. Moreover, three metabolites (i.e., isovalerylcarnitine, propionylcarnitine, and pyruvic acid) were clustered in one group based on the low-high RFI pigs. This study performed a comprehensive metabolite-based genome-wide association study (GWAS) analysis for pigs with differences in feed efficiency and provided significant metabolites for which there is significant genetic variation as well as biological interaction networks. The identified metabolite genetic variants, genes, and networks in high versus low feed efficient pigs could be considered as potential genetic or biomarkers for feed efficiency.

Identification of Differentially Expressed Gene Transcripts in Porcine Endometrium during Early Stages of Pregnancy.

During the early stages of pregnancy, the uterine endometrium undergoes dramatic morphologic and functional changes accompanied with dynamic variation in gene expression. Pregnancy-stage specific differentially expressed gene (DEG)-transcript-probes were investigated and identified by comparing endometrium transcriptome at 9th day (9D), 12th day (12D) and 16th day (16D) of early pregnancy in Polish large-white (PLW) gilts. Endometrium comparisons between 9D-vs-12D, 9D-vs-16D and 12D-vs-16D of early pregnancy identified 6049, 374 and 6034 highly significant DEG-transcript-probes (p < 0.001; >2 FC). GO term enrichment analysis identified commonly shared upregulated endometrial DEG-transcript-probes (p < 0.001; >2 FC), that were regulating the gene functions of anatomic structure development and transport (TG), DNA-binding and methyltransferase activity (ZBTB2), ion-binding and kinase activity (CKM), cell proliferation and apoptosis activity (IL1B). Downregulated DEG-transcript-probes (p < 0.001; >2 FC) were involved in regulating the gene functions of phosphatase activity (PTPN11), TC616413 gene-transcript and Sus-scrofa LOC100525539. Moreover, blastn comparison of microarray-probes sequences against sus-scrofa11 assembly identified commonly shared upregulated endometrial DEG-transcript-probes (E < 0.06; >2 FC), that were regulating the gene functions of reproduction and growth (SELENOP), cytoskeleton organization and kinase activity (CDC42BPA), phosphatase activity (MINPP1), enzyme-binding and cell-population proliferation (VAV3), cancer-susceptibility candidate gene (CASC4), cytoskeletal protein-binding (COBLL1), ion-binding, enzyme regulator activity (ACAP2) Downregulated endometrial DEG-transcript-probes (E < 0.06; >2FC) were involved in regulating the gene functions of signal-transduction (TMEM33), catabolic and metabolic processes (KLHL15). Microarray validation experiment on selected candidate genes showed complementarity to significant endometrial DEG-transcript-probes responsible for the regulation of immune response (IL1B, S100A11), lipid metabolism (FABP3, PPARG), cell-adhesion (ITGAV), angiogenesis (IL1B), intercellular transmission (NMB), cell-adhesion (OPN) and response to stimuli (RBP4) was confirmed by RT-PCR. This study provides a clue that identified pregnancy-stage specific microarray transcript probes could be considered as candidate genes for recognition and establishment of early pregnancy in the pig.

Interplay among miR-29 family, mineral metabolism, and gene regulation in Bos indicus muscle.

An interplay between gene expression, mineral concentration, and beef quality traits in Bos indicus muscle has been reported previously under a network approach. However, growing evidence suggested that miRNAs not only modulate gene expression but are also involved with mineral homeostasis. To our knowledge, understanding of the miRNA-gene expression-mineral concentration relationship in mammals is still minimal. Therefore, we carried out a miRNA co-expression and multi-level miRNA-mRNA integration analyses to predict the putative drivers (miRNAs and genes) associated with muscle mineral concentration in Nelore steers. In this study, we identified calcium and iron to be the pivotal minerals associated with miRNAs and gene targets. Furthermore, we identified the miR-29 family (miR-29a, -29b, -29c, -29d-3p, and -29e) as the putative key regulators modulating mineral homeostasis. The miR-29 family targets genes involved with AMPK, insulin, mTOR, and thyroid hormone signaling pathways. Finally, we reported an interplay between miRNAs and minerals acting cooperatively to modulate co-expressed genes and signaling pathways both involved with mineral and energy homeostasis in Nelore muscle. Although we provided some evidence to understand this complex relationship, future work should determine the functional implications of minerals for miRNA levels and their feedback regulation system.\\An interplay between gene expression, mineral concentration, and beef quality traits in Bos indicus muscle has been reported previously under a network approach. However, growing evidence suggested that miRNAs not only modulate gene expression but are also involved with mineral homeostasis. To our knowledge, understanding of the miRNA-gene expression-mineral concentration relationship in mammals is still minimal. Therefore, we carried out a miRNA co-expression and multi-level miRNA-mRNA integration analyses to predict the putative drivers (miRNAs and genes) associated with muscle mineral concentration in Nelore steers. In this study, we identified calcium and iron to be the pivotal minerals associated with miRNAs and gene targets. Furthermore, we identified the miR-29 family (miR-29a, -29b, -29c, -29d-3p, and -29e) as the putative key regulators modulating mineral homeostasis. The miR-29 family targets genes involved with AMPK, insulin, mTOR, and thyroid hormone signaling pathways. Finally, we reported an interplay between miRNAs and minerals acting cooperatively to modulate co-expressed genes and signaling pathways both involved with mineral and energy homeostasis in Nelore muscle. Although we provided some evidence to understand this complex relationship, future work should determine the functional implications of minerals for miRNA levels and their feedback regulation system.

Copy Number Variations and Expression Levels of Guanylate-Binding Protein 6 Gene Associated with Growth Traits of Chinese Cattle.

Association studies have indicated profound effects of copy number variations (CNVs) on various phenotypes in different species. In this study, we identified the CNV distributions and expression levels of guanylate-binding protein 6 (GBP6) associated with the growth traits of Chinese cattle. The results showed that the phenotypic values of body size and weight of Xianan (XN) cattle were higher than those of Nanyang (NY) cattle. The medium CNV types were mostly identified in the XN and NY breeds, but their CNV distributions were significantly different (adjusted p < 0.05). The association analysis revealed that the body weight, cannon circumference and chest circumference of XN cattle had significantly different values in different CNV types (p < 0.05), with CNV gain types (Log22-ΔΔCt > 0.5) displaying superior phenotypic values. We also found that transcription levels varied in different tissues (p < 0.001) and the CNV gain types showed the highest relative gene expression levels in the muscle tissue, consistent with the highest phenotypic values of body weight and cannon circumference among the three CNV types. Consequently, our results suggested that CNV gain types of GBP6 could be used as the candidate markers in the cattle-breeding program for growth traits.