A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse.

In manufacturing, musculoskeletal robots have gained more attention with the potential advantages of flexibility, robustness, and adaptability over conventional serial-link rigid robots. Focusing on the fundamental lifting tasks, a hybrid controller is proposed to overcome control challenges of such robots for widely applications in industry. The metaverse technology offers an available simulated-reality-based platform to verify the proposed method. The hybrid controller contains two main parts. A muscle-synergy-based radial basis function (RBF) network is proposed as the feedforward controller, which is able to characterize the phasic and the tonic muscle synergies simultaneously. The adaptive dynamic programming (ADP) is applied as the feedback controller to address the optimal control problem. The actor-critic structure is applied in the ADP-based controller, where the critic network is trained to approximate the optimal performance index and the actor network is trained to compute the optimal muscle excitations. Furthermore, the convergence and stability of the ADP algorithm are also analyzed. Finally, experiments have been designed to verify the effectiveness of this hybrid controller on an upper limb musculoskeletal system, and the comparisons with other controllers are also illustrated. The results show that the proposed controller can obtain a satisfactory performance for lifting tasks.

A compendium of genetic regulatory effects across pig tissues.

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.

Identification of Alternative Splicing Events Associated with Paratuberculosis in Dairy Cattle Using Multi-Tissue RNA Sequencing Data.

Paratuberculosis is a major endemic disease caused by Mycobacterium avium subspecies paratuberculosis (MAP) infection and leads to huge economic loss in the dairy sector worldwide. Alternative splicing (AS) events, playing indispensable regulatory roles in many protein functions and biological pathways, are shown to be associated with complex traits and diseases. In this study, by integrating the RNA sequencing (RNA-seq) data of 24 samples from three tissues (peripheral blood, jejunum and salivary gland) of Holstein cows, we obtained 2,706,541,696 uniquely mapped reads in total that represented 12,870 expressed genes, and detected 4285 differentially expressed genes (DEGs) between MAP-infected and healthy cows (p < 0.05). Of them, 92 differentially expressed splicing factors (DESFs) were included. Further, 119, 150 and 68 differential alternative splicing (DAS) events between MAP-infected and healthy cows were identified in peripheral blood, jejunum and salivary glands, respectively. Of note, six DAS events were highly and significantly correlated with the DESFs (R2 > 0.9; p < 0.01), and their corresponding genes (COPI coat complex subunit gamma 2gene (COPG2), kinesin family member 2C gene (KIF2C), exocyst complex component 7 (EXOC7), Rab9 effector protein with kelch motifs gene (RABEPK), deoxyribonuclease 1 gene (DNASE1) and early endosome antigen 1gene (EEA1)) were significantly enriched in immune response such as vesicle-mediated transport, regulation of acute inflammatory response and tuberculosis through gene ontology (GO) and KEGG analysis. KS test showed that the DAS events in the EXOC7 and KIF2C genes indeed displayed differences between MAP-infected cows and healthy cows. The DAS in EXOC7 might produce a new protein sequence with lack of 23 amino acids, and the DAS in KIF2C induced a stop codon of premature occurrence and resulted in a lack of functional domain. In summary, this study identified the DAS events and corresponding genes related to MAP-infection base on the RNA-seq data from multiple tissues of Holstein cows, providing novel insights into the regulatory mechanisms underpinning paratuberculosis in dairy cattle.

Bta-miR-106b Regulates Bovine Mammary Epithelial Cell Proliferation, Cell Cycle, and Milk Protein Synthesis by Targeting the CDKN1A Gene.

Our previous studies found that bta-miR-106b and its corresponding target gene, CDKN1A, were differentially expressed between the mammary epithelium of lactating Holstein cows with extremely high and low milk protein and fat percentage, implying the potential role of bta-miR-106b in milk composition synthesis. In this study, with luciferase assay experiment, bta-miR-106b was validated to target the 3'-untranslated region (UTR) of bovine CDKN1A, thereby regulating its expression. Moreover, in bovine mammary epithelial cells (BMECs), over-expression of bta-miR-106b significantly down-regulated the CDKN1A expression at both mRNA and protein levels, and inhibitors of bta-miR-106b increased CDKN1A expression. Of note, we observed that bta-miR-106b accelerated cell proliferation and cell cycle, and changed the expressions of protein synthesis related pathways such as JAK-STAT and PI3K/AKT/mTOR through regulating CDKN1A expression. Our findings highlight the important regulatory role of bta-miR-106b in milk protein synthesis by targeting CDKN1A in dairy cattle.

Genome-Wide DNA Methylation Profile in Jejunum Reveals the Potential Genes Associated With Paratuberculosis in Dairy Cattle.

Paratuberculosis in cattle causes substantial economic losses to the dairy industry. Exploring functional genes and corresponding regulatory pathways related to resistance or susceptibility to paratuberculosis is essential to the breeding of disease resistance in cattle. Co-analysis of genome-wide DNA methylation and transcriptome profiles is a critically important approach to understand potential regulatory mechanism underlying the development of diseases. In this study, we characterized the profiles of DNA methylation of jejunum from nine Holstein cows in clinical, subclinical, and healthy groups using whole-genome bisulfite sequencing (WGBS). The average methylation level in functional regions was 29.95% in the promoter, 29.65% in the 5' untranslated region (UTR), 68.24% in exons, 71.55% in introns, and 72.81% in the 3' UTR. A total of 3,911, 4,336, and 4,094 differentially methylated genes (DMGs) were detected in clinical vs. subclinical, clinical vs. healthy, and subclinical vs. healthy comparative group, respectively. Gene ontology (GO) and analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that these DMGs were significantly enriched in specific biological processes related to immune response, such as Th1 and Th2 cell differentiation, wnt, TNF, MAPK, ECM-receptor interaction, cellular senescence, calcium, and chemokine signaling pathways (q value <0.05). The integration of information about DMGs, differentially expressed genes (DEGs), and biological functions suggested nine genes CALCRL, TNC, GATA4, CD44, TGM3, CXCL9, CXCL10, PPARG, and NFATC1 as promising candidates related to resistance/susceptibility to Mycobacterium avium subspecies paratuberculosis (MAP). This study reports on the high-resolution DNA methylation landscapes of the jejunum methylome across three conditions (clinical, subclinical, and healthy) in dairy cows. Our investigations integrated different sources of information about DMGs, DEGs, and pathways, enabling us to find nine functional genes that might have potential application in resisting paratuberculosis in dairy cattle.

Associations between polymorphisms of SLC22A7, NGFR, ARNTL and PPP2R2B genes and Milk production traits in Chinese Holstein.

BACKGROUND: Our preliminary work confirmed that, SLC22A7 (solute carrier family 22 member 7), NGFR (nerve growth factor receptor), ARNTL (aryl hydrocarbon receptor nuclear translocator like) and PPP2R2B (protein phosphatase 2 regulatory subunit Bß) genes were differentially expressed in dairy cows during different stages of lactation, and involved in the lipid metabolism through insulin, PI3K-Akt, MAPK, AMPK, mTOR, and PPAR signaling pathways, so we considered these four genes as the candidates affecting milk production traits. In this study, we detected polymorphisms of the four genes and verified their genetic effects on milk yield and composition traits in a Chinese Holstein cow population. RESULTS: By resequencing the whole coding region and part of the flanking region of SLC22A7, NGFR, ARNTL and PPP2R2B, we totally found 20 SNPs, of which five were located in SLC22A7, eight in NGFR, three in ARNTL, and four in PPP2R2B. Using Haploview4.2, we found three haplotype blocks including five SNPs in SLC22A7, eight in NGFR and three in ARNTL. Single-SNP association analysis showed that 19 out of 20 SNPs were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage in the first and second lactations (P < 0.05). Haplotype-based association analysis showed that the three haplotypes were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage (P < 0.05). Further, we used SOPMA software to predict a SNP, 19:g.37095131C > T in NGFR, changed the structure of NGFR protein. In addition, we used Jaspar software to found that four SNPs, 19:g.37113872C > G,19:g.37113157C > T, and 19:g.37112276C > T in NGFR and 15:g.39320936A > G in ARNTL, could change the transcription factor binding sites and might affect the expression of the corresponding genes. These five SNPs might be the potential functional mutations for milk production traits in dairy cattle. CONCLUSIONS: In summary, we proved that SLC22A7, NGFR, ARNTL and PPP2R2B have significant genetic effects on milk production traits. The valuable SNPs can be used as candidate genetic markers for genomic selection of dairy cattle, and the effects of these SNPs on other traits need to be further verified.