Treatment of Donor Cells with Oxidative Phosphorylation Inhibitor CPI Enhances Porcine Cloned Embryo Development.

Somatic cell nuclear transfer (SCNT) technology holds great promise for livestock industry, life science and human biomedicine. However, the development and application of this technology is limited by the low developmental potential of SCNT embryos. The developmental competence of cloned embryos is influenced by the energy metabolic status of donor cells. The purpose of this study was to investigate the effects of CPI, an oxidative phosphorylation inhibitor, on the energy metabolism pathways of pig fibroblasts and the development of subsequent SCNT embryos. The results showed that treatment of porcine fibroblasts with CPI changed the cellular energy metabolic pathways from oxidative phosphorylation to glycolysis and enhanced the developmental ability of subsequent SCNT embryos. The present study establishes a simple, new way to improve pig cloning efficiency, helping to promote the development and application of pig SCNT technology.

A deep learning-based approach for fully automated segmentation and quantitative analysis of muscle fibers in pig skeletal muscle.

Muscle fiber properties exert a significant influence on pork quality, with cross-sectional area (CSA) being a crucial parameter closely associated with various meat quality indicators, such as shear force. Effectively identifying and segmenting muscle fibers in a robust manner constitutes a vital initial step in determining CSA. This step is highly intricate and time-consuming, necessitating an accurate and automated analytical approach. One limitation of existing methods is their tendency to perform well on high signal-to-noise ratio images of intact, healthy muscle fibers but their lack of validation on more complex image datasets featuring significant morphological changes, such as the presence of ice crystals. In this study, we undertake the fully automatic segmentation of muscle fiber microscopic images stained with myosin adenosine triphosphate (mATPase) activity using a deep learning architecture known as SOLOv2. Our objective is to efficiently derive accurate measurements of muscle fiber size and distribution. Tests conducted on actual images demonstrate that our method adeptly handles the intricate task of muscle fiber segmentation, yielding quantitative results amenable to statistical analysis and displaying reliability comparable to manual analysis.

Protein Dynamic Landscape during Mouse Mammary Gland Development from Virgin to Pregnant, Lactating, and Involuting Stages.

The mammary gland undergoes significant physiological changes as it undergoes a transition from virgin to pregnancy, lactation, and involution. However, the dynamic role of proteins in regulating these processes during mouse mammary gland development has not been thoroughly explored. In this study, we collected mouse mammary gland tissues from mature virgins aged 8-10 weeks (V), day 16 of pregnancy (P16d), day 12 of lactation (L12d), day 1 of forced weaning (FW 1d), and day 3 of forced weaning (FW 3d) stages for analysis using DIA-based quantitative proteomics technology. A total of 3,312 proteins were identified, of which 843 were DAPs that were categorized into nine clusters based on their abundance changes across developmental stages. Notably, DAPs in cluster 2, which peaked at the L12d stage, were primarily associated with mammary gland development and lactation. The protein-protein interaction network revealed that the epidermal growth factor (EGF) was central to this cluster. Our study provides a comprehensive overview of the mouse mammary gland development proteome and identifies some important proteins, such as EGF, Janus kinase 1 (JAK1), and signal transducer and activator of transcription 6 (STAT6) that may serve as potential targets for future research to provide guidelines for a deeper understanding of the developmental biology of mammary glands.

Co-delivery of Paclitaxel/Atovaquone/Quercetin to regulate energy metabolism to reverse multidrug resistance in ovarian cancer by PLGA-PEG nanoparticles.

Ovarian cancer is a malignant tumor that seriously endangers the lives of women, with chemotherapy being the primary clinical treatment. However, chemotherapy encounters the problem of generating multidrug resistance (MDR), mainly due to drug efflux induced by P-glycoprotein (P-gp), which decreases intracellular accumulation of chemotherapeutic drugs. The drugs efflux mediated by P-gp requires adenosine triphosphate (ATP) hydrolysis to provide energy. Therefore, modulating energy metabolism pathways and inhibiting ATP production may be a potential strategy to reverse MDR. Herein, we developed a PTX-ATO-QUE nanoparticle (PAQNPs) based on a PLGA-PEG nanoplatform capable of loading the mitochondrial oxidative phosphorylation (OXPHOS) inhibitor atovaquone (ATO), the glycolysis inhibitor quercetin (QUE), and the chemotherapeutic drug paclitaxel (PTX) to reverse MDR by inhibiting energy metabolism through multiple pathways. Mechanistically, PAQNPs could effectively inhibit the OXPHOS and glycolytic pathways of A2780/Taxol cells by suppressing the activities of mitochondrial complex III and hexokinase II (HK II), respectively, ultimately decreasing intracellular ATP levels in tumor cells. Energy depletion can effectively inhibit cell proliferation and reduce P-gp activity, increasing the chemotherapeutic drug PTX accumulation in the cells. Moreover, intracellular reactive oxygen species (ROS) is increased with PTX accumulation and leads to chemotherapy-resistant cell apoptosis. Furthermore, PAQNPs significantly inhibited tumor growth in the A2780/Taxol tumor-bearing NCG mice model. Immunohistochemical (IHC) analysis of tumor tissues revealed that P-gp expression was suppressed, demonstrating that PAQNPs are effective in reversing MDR in tumors by inducing energy depletion. In addition, the safety study results, including blood biochemical indices, major organ weights, and H&E staining images, showed that PAQNPs have a favorable in vivo safety profile. In summary, the results suggest that the combined inhibition of the two energy pathways, OXPHOS and glycolysis, can enhance chemotherapy efficacy and reverse MDR in ovarian cancer.

RASGRP1 targeted by H3K27me3 regulates myoblast proliferation and differentiation in mice and pigs.

Skeletal muscle is not only the largest organ in the body that is responsible for locomotion and exercise but also crucial for maintaining the body's energy metabolism and endocrine secretion. The trimethylation of histone H3 lysine 27 (H3K27me3) is one of the most important histone modifications that participates in muscle development regulation by repressing the transcription of genes. Previous studies indicate that the RASGRP1 gene is regulated by H3K27me3 in embryonic muscle development in pigs, but its function and regulatory role in myogenesis are still unclear. In this study, we verify the crucial role of H3K27me3 in RASGRP1 regulation. The gain/loss function of RASGRP1 in myogenesis regulation is performed using mouse myoblast C2C12 cells and primarily isolated porcine skeletal muscle satellite cells (PSCs). The results of qPCR, western blot analysis, EdU staining, CCK-8 assay and immunofluorescence staining show that overexpression of RASGRP1 promotes cell proliferation and differentiation in both skeletal muscle cell models, while knockdown of RASGRP1 leads to the opposite results. These findings indicate that RASGRP1 plays an important regulatory role in myogenesis in both mice and pigs.

Genomic prediction based on preselected single-nucleotide polymorphisms from genome-wide association study and imputed whole-genome sequence data annotation for growth traits in Duroc pigs.

The use of whole-genome sequence (WGS) data is expected to improve genomic prediction (GP) power of complex traits because it may contain mutations that in strong linkage disequilibrium pattern with causal mutations. However, a few previous studies have shown no or small improvement in prediction accuracy using WGS data. Incorporating prior biological information into GP seems to be an attractive strategy that might improve prediction accuracy. In this study, a total of 6334 pigs were genotyped using 50K chips and subsequently imputed to the WGS level. This cohort includes two prior discovery populations that comprise 294 Landrace pigs and 186 Duroc pigs, as well as two validation populations that consist of 3770 American Duroc pigs and 2084 Canadian Duroc pigs. Then we used annotation information and genome-wide association study (GWAS) from the WGS data to make GP for six growth traits in two Duroc pig populations. Based on variant annotation, we partitioned different genomic classes, such as intron, intergenic, and untranslated regions, for imputed WGS data. Based on GWAS results of WGS data, we obtained trait-associated single-nucleotide polymorphisms (SNPs). We then applied the genomic feature best linear unbiased prediction (GFBLUP) and genomic best linear unbiased prediction (GBLUP) models to estimate the genomic estimated breeding values for growth traits with these different variant panels, including six genomic classes and trait-associated SNPs. Compared with 50K chip data, GBLUP with imputed WGS data had no increase in prediction accuracy. Using only annotations resulted in no increase in prediction accuracy compared to GBLUP with 50K, but adding annotation information into the GFBLUP model with imputed WGS data could improve the prediction accuracy with increases of 0.00%-2.82%. In conclusion, a GFBLUP model that incorporated prior biological information might increase the advantage of using imputed WGS data for GP.

Gender Control of Mouse Embryos by Activation of TLR7/8 on X Sperm via Ligands dsRNA-40 and dsRNA-DR.

Gender control technologies are promising for enhancing the production efficiency of the farm animal industry, and preventing sex-linked hereditary diseases in humans. It has been shown that the X sperm of mammalian animals specifically expresses X-chromosome-derived toll-like receptor 7/8 (TLR7/8), and the activation of TLR7/8 on the X sperm by their agonist, R848, can separate X and Y sperm via the specific inhibition of X sperm motility. The use of R848-preselected sperm for fertilization resulted in sex-ratio-skewed embryos or offspring. In this study, we aimed to investigate whether two other TLR7/8 ligands, double-stranded RNA-40 (dsRNA-40) and double-stranded RNA-DR (dsRNA-DR), are also effective in the separation of mouse X and Y sperm and the subsequent generation of gender-ratio-skewed in vitro fertilization (IVF) embryos. Our results indicated that cholesterol modification significantly enhances the transfection of dsRNA-40 and dsRNA-DR into sperm cells. dsRNA-40 and dsRNA-DR incubation with mouse sperm could separate X and Y sperm by the specific suppression of X sperm motility by decreasing its ATP level and mitochondrial activity. The use of a dsRNA-40- or dsRNA-DR-preselected upper layer of sperm, which predominantly contains high-motility Y sperm, for IVF caused a male-biased sex ratio shift in resulting embryos (with 65.90-74.93% of embryos being male). This study develops a simple new method for the efficient separation of mammalian X and Y sperm, enabling the selective production of male or female progenies.

Genome-wide association studies for loin muscle area, loin muscle depth and backfat thickness in DLY pigs.

This study aimed at identifying genes associated with loin muscle area (LMA), loin muscle depth (LMD) and backfat thickness (BFT). We performed single-trait and multi-trait genome-wide association studies (GWASs) after genotyping 685 Duroc × (Landrace × Yorkshire) (DLY) pigs using the Geneseek Porcine 50K SNP chip. In the single-trait GWASs, we identified two, eight and two significant SNPs associated with LMA, LMD and BFT, respectively, and searched genes within the 1 Mb region near the significant SNPs with relevant functions as candidate genes. Consequently, we identified one (DOCK5), three (PID1, PITX2, ELOVL6) and three (CCR1, PARP14, CASR) promising candidate genes for LMA, LMD and BFT, respectively. Moreover, the multi-trait GWAS identified four significant SNPs associated with the three traits. In conclusion, the GWAS analysis of LMA, LMD and BFT in a DLY pig population identified several associated SNPs and candidate genes, further deepening our understanding of the genetic basis of these traits, and they may be useful for marker-assisted selection to improve the three traits in DLY pigs.

Increased Accuracy of Genomic Prediction Using Preselected SNPs from GWAS with Imputed Whole-Genome Sequence Data in Pigs.

Enhancing the accuracy of genomic prediction is a key goal in genomic selection (GS) research. Integrating prior biological information into GS methods using appropriate models can improve prediction accuracy for complex traits. Genome-wide association study (GWAS) is widely utilized to identify potential candidate loci associated with complex traits in livestock and poultry, offering essential genomic insights. In this study, a GWAS was conducted on 685 Duroc × Landrace × Yorkshire (DLY) pigs to extract significant single-nucleotide polymorphisms (SNPs) as genomic features. We compared two GS models, genomic best linear unbiased prediction (GBLUP) and genomic feature BLUP (GFBLUP), by using imputed whole-genome sequencing (WGS) data on 651 Yorkshire pigs. The results revealed that the GBLUP model achieved prediction accuracies of 0.499 for backfat thickness (BFT) and 0.423 for loin muscle area (LMA). By applying the GFBLUP model with GWAS-based SNP preselection, the average prediction accuracies for BFT and LMA traits reached 0.491 and 0.440, respectively. Specifically, the GFBLUP model displayed a 4.8% enhancement in predicting LMA compared to the GBLUP model. These findings suggest that, in certain scenarios, the GFBLUP model may offer superior genomic prediction accuracy when compared to the GBLUP model, underscoring the potential value of incorporating genomic features to refine GS models.

Composition, function, and timing: exploring the early-life gut microbiota in piglets for probiotic interventions.

BACKGROUND: The establishment of a robust gut microbiota in piglets during their early developmental stage holds the potential for long-term advantageous effects. However, the optimal timeframe for introducing probiotics to achieve this outcome remains uncertain. RESULTS: In the context of this investigation, we conducted a longitudinal assessment of the fecal microbiota of 63 piglets at three distinct pre-weaning time points. Simultaneously, we gathered vaginal and fecal samples from 23 sows. Employing 16S rRNA gene and metagenomic sequencing methodologies, we conducted a comprehensive analysis of the fluctuation patterns in microbial composition, functional capacity, interaction networks, and colonization resistance within the gut microbiota of piglets. As the piglets progressed in age, discernible modifications in intestinal microbial diversity, composition, and function were observed. A source-tracking analysis unveiled the pivotal role of fecal and vaginal microbiota derived from sows in populating the gut microbiota of neonatal piglets. By D21, the microbial interaction network displayed a more concise and efficient configuration, accompanied by enhanced colonization resistance relative to the other two time points. Moreover, we identified three strains of Ruminococcus sp. at D10 as potential candidates for improving piglets' weight gain during the weaning phase. CONCLUSIONS: The findings of this study propose that D10 represents the most opportune juncture for the introduction of external probiotic interventions during the early stages of piglet development. This investigation augments our comprehension of the microbiota dynamics in early-life of piglets and offers valuable insights for guiding forthcoming probiotic interventions.

Identification of Candidate Genes for Economically Important Carcass Cutting in Commercial Pigs through GWAS.

During the process of pork production, the carcasses of pigs are divided and sold, which provides better economic benefits and market competitiveness for pork production than selling the carcass as a whole. Due to the significant cost of post-slaughter phenotypic measurement, the genetic architecture of tenderloin weight (TLNW) and rib weight (RIBW)-important components of pig carcass economic value-remain unknown. In this study, we conducted genome-wide association studies (GWAS) for TLNW and RIBW traits in a population of 431 Duroc × Landrace × Yorkshire (DLY) pigs. In our study, the most significant single nucleotide polymorphism (SNP) associated with TLNW was identified as ASGA0085853 (3.28 Mb) on Sus scrofa chromosome 12 (SSC12), while for RIBW, it was Affx-1115046258 (172.45 Mb) on SSC13. Through haplotype block analysis, we discovered a novel quantitative trait locus (QTL) associated with TLNW, spanning a 5 kb region on SSC12, and a novel RIBW-associated QTL spanning 1.42 Mb on SSC13. Furthermore, we hypothesized that three candidate genes, TIMP2 and EML1, and SMN1, are associated with TLNW and RIBW, respectively. Our research not only addresses the knowledge gap regarding TLNW, but also serves as a valuable reference for studying RIBW. The identified SNP loci strongly associated with TLNW and RIBW may prove useful for marker-assisted selection in pig breeding programs.

Genome-Wide Association Study Identifies the Crucial Candidate Genes for Teat Number in Crossbred Commercial Pigs.

The number of teats is a crucial reproductive trait with significant economic implications on maternal capacity and litter size. Consequently, improving this trait is essential to facilitate genetic selection for increased litter size. In this study, we performed a genome-wide association study (GWAS) of the number of teats in a three-way crossbred commercial Duroc × (Landrace × Yorkshire) (DLY) pig population comprising 1518 animals genotyped with the 50K BeadChip. Our analysis identified crucial quantitative trait loci (QTL) for the number of teats, containing the ABCD4 and VRTN genes on porcine chromosome 7. Our results establish SNP variants of ABCD4 and VRTN as new molecular markers for improving the number of teats in DLY pigs. Furthermore, the most significant noteworthy single nucleotide polymorphism (SNP) (7_97568284) was identified within the ABCD4 gene, exhibiting a significant association with the total teat number traits. This SNP accounted for a substantial proportion of the genetic variance, explaining 6.64% of the observed variation. These findings reveal a novel gene on SSC7 for the number of teats and provide a deeper understanding of the genetic mechanisms underlying reproductive traits.

Identification and characterization of circRNAs in peri-implantation endometrium between Yorkshire and Erhualian pigs.

BACKGROUND: One of the most critical periods for the loss of pig embryos is the 12th day of gestation when implantation begins. Recent studies have shown that non-coding RNAs (ncRNAs) play important regulatory roles during pregnancy. Circular RNAs (circRNAs) are a kind of ubiquitously expressed ncRNAs that can directly regulate the binding proteins or regulate the expression of target genes by adsorbing micro RNAs (miRNA). RESULTS: We used the Illumina Novaseq6,000 technology to analyze the circRNA expression profile in the endometrium of three Erhualian (EH12) and three Yorkshire (YK12) pigs on day 12 of gestation. Overall, a total of 22,108 circRNAs were identified. Of these, 4051 circRNAs were specific to EH12 and 5889 circRNAs were specific to YK12, indicating a high level of breed specificity. Further analysis showed that there were 641 significant differentially expressed circRNAs (SDEcircRNAs) in EH12 compared with YK12 (FDR < 0.05). Functional enrichment of differential circRNA host genes revealed many pathways and genes associated with reproduction and regulation of embryo development. Network analysis of circRNA-miRNA interactions further supported the idea that circRNAs act as sponges for miRNAs to regulate gene expression. The prediction of differential circRNA binding proteins further explored the potential regulatory pathways of circRNAs. Analysis of SDEcircRNAs suggested a possible reason for the difference in embryo survival between the two breeds at the peri-implantation stage. CONCLUSIONS: Together, these data suggest that circRNAs are abundantly expressed in the endometrium during the peri-implantation period in pigs and are important regulators of related genes. The results of this study will help to further understand the differences in molecular pathways between the two breeds during the critical implantation period of pregnancy, and will help to provide insight into the molecular mechanisms that contribute to the establishment of pregnancy and embryo loss in pigs.

Improving the accuracy of genomic prediction for meat quality traits using whole genome sequence data in pigs.

BACKGROUND: Pork quality can directly affect customer purchase tendency and meat quality traits have become valuable in modern pork production. However, genetic improvement has been slow due to high phenotyping costs. In this study, whole genome sequence (WGS) data was used to evaluate the prediction accuracy of genomic best linear unbiased prediction (GBLUP) for meat quality in large-scale crossbred commercial pigs. RESULTS: We produced WGS data (18,695,907 SNPs and 2,106,902 INDELs exceed quality control) from 1,469 sequenced Duroc × (Landrace × Yorkshire) pigs and developed a reference panel for meat quality including meat color score, marbling score, L* (lightness), a* (redness), and b* (yellowness) of genomic prediction. The prediction accuracy was defined as the Pearson correlation coefficient between adjusted phenotypes and genomic estimated breeding values in the validation population. Using different marker density panels derived from WGS data, accuracy differed substantially among meat quality traits, varied from 0.08 to 0.47. Results showed that MultiBLUP outperform GBLUP and yielded accuracy increases ranging from 17.39% to 75%. We optimized the marker density and found medium- and high-density marker panels are beneficial for the estimation of heritability for meat quality. Moreover, we conducted genotype imputation from 50K chip to WGS level in the same population and found average concordance rate to exceed 95% and r2 = 0.81. CONCLUSIONS: Overall, estimation of heritability for meat quality traits can benefit from the use of WGS data. This study showed the superiority of using WGS data to genetically improve pork quality in genomic prediction.

The SWine IMputation (SWIM) haplotype reference panel enables nucleotide resolution genetic mapping in pigs.

Genetic mapping to identify genes and alleles associated with or causing economically important quantitative trait variation in livestock animals such as pigs is a major goal in animal genetic improvement. Despite recent advances in high-throughput genotyping technologies, the resolution of genetic mapping in pigs remains poor due in part to the low density of genotyped variant sites. In this study, we overcame this limitation by developing a reference haplotype panel for pigs based on 2259 whole genome-sequenced animals representing 44 pig breeds. We evaluated software combinations and breed composition to optimize the imputation procedure and achieved an average concordance rate in excess of 96%, a non-reference concordance rate of 88%, and an r2 of 0.85. We demonstrated in two case studies that genotype imputation using this resource can dramatically improve the resolution of genetic mapping. A public web server has been developed to allow the pig genetics community to fully utilize this resource. We expect this resource to facilitate genetic mapping and accelerate genetic improvement in pigs.

Identification of candidate genes associated with carcass component weights in commercial crossbred pigs through a combined GWAS approach.

In the pork industry chain, carcass cutting is crucial for enhancing the commercial value of pork carcasses. However, the genetic mechanisms underlying carcass component weights remain poorly understood. Here, we used a combined genome-wide association study (GWAS) approach that integrated single- and multi-locus models to map genetic markers and genes associated with the weights of seven carcass components in Duroc × Landrace × Yorkshire (DLY) pigs. As multi-locus GWAS captures more single nucleotide polymorphisms (SNPs) with large effects than single-locus GWAS, the combined GWAS approach detected more SNPs than using the single-locus model alone. We identified 177 nonredundant SNPs associated with these traits in 526 DLY pigs, including boneless butt shoulder (BBS), boneless picnic shoulder (BPS), boneless leg (BL), belly (BELLY), front fat (FF), rear fat (RF), and skin-on whole loin (SLOIN). Using single-locus GWAS, we identified a quantitative trait locus (QTL) for SLOIN on Sus scrofa chromosome 15 (SSC15). Notably, a single SNP (ASGA0069883) in the proximity of this QTL was consistently detected by all GWAS models (one single-locus and four multi-locus models) and explained more than 4% of the phenotypic variance. Our findings suggest that the involved gene, MYO3B, is proposed to be a strong candidate for SLOIN. Further analysis also identified several candidate genes related to BBS (PPP3CA and CPEB4), BPS (ECH1), FF (CACNB2 and ZNF217), BELLY (FGFRL1), BL (CHST11), and RF (LRRK2). The identified SNPs can be used as molecular markers for the genetic improvement of pork carcasses in the molecular-guided breeding of modern commercial pigs.

Carcass cutting is the most effective method for enhancing the commercial value of pork carcasses in the industry chain. However, the genetic mechanisms underlying carcass component weights remain elusive. In this study, we used a combination of single- and multi-locus models to increase the power of genome-wide association analysis. We identified 177 important genetic variants that are potentially promising candidate markers for marker-assisted selection in breeding. Further investigation revealed one quantitative trait locus region and several candidate genes (PPP3CA, CPEB4, ECH1, CACNB2, ZNF217, FGFRL1, CHST11, LRRK2) associated with the weights of seven carcass components in Duroc × Landrace × Yorkshire pigs.

Uterine luminal-derived extracellular vesicles: potential nanomaterials to improve embryo implantation.

Most pregnancy losses worldwide are caused by implantation failure for which there is a lack of effective therapeutics. Extracellular vesicles are considered potential endogenous nanomedicines because of their unique biological functions. However, the limited supply of ULF-EVs prevents their development and application in infertility diseases such as implantation failure. In this study, pigs were used as a human biomedical model, and ULF-EVs were isolated from the uterine luminal. We comprehensively characterized the proteins enriched in ULF-EVs and revealed their biological functions in promoting embryo implantation. By exogenously supplying ULF-EVs, we demonstrated that ULF-EVs improve embryo implantation, suggesting that ULF-EVs are a potential nanomaterial to treat implantation failure. Furthermore, we identified that MEP1B is important in improving embryo implantation by promoting trophoblast cell proliferation and migration. These results indicated that ULF-EVs can be a potential nanomaterial to improve embryo implantation.

Integrated Single-Trait and Multi-Trait GWASs Reveal the Genetic Architecture of Internal Organ Weight in Pigs.

Internal organ weight is an essential indicator of growth status as it reflects the level of growth and development in pigs. However, the associated genetic architecture has not been well explored because phenotypes are difficult to obtain. Herein, we performed single-trait and multi-trait genome-wide association studies (GWASs) to map the genetic markers and genes associated with six internal organ weight traits (including heart weight, liver weight, spleen weight, lung weight, kidney weight, and stomach weight) in 1518 three-way crossbred commercial pigs. In summation, single-trait GWASs identified a total of 24 significant single- nucleotide polymorphisms (SNPs) and 5 promising candidate genes, namely, TPK1, POU6F2, PBX3, UNC5C, and BMPR1B, as being associated with the six internal organ weight traits analyzed. Multi-trait GWAS identified four SNPs with polymorphisms localized on the APK1, ANO6, and UNC5C genes and improved the statistical efficacy of single-trait GWASs. Furthermore, our study was the first to use GWASs to identify SNPs associated with stomach weight in pigs. In conclusion, our exploration of the genetic architecture of internal organ weights helps us better understand growth traits, and the key SNPs identified could play a potential role in animal breeding programs.

Interaction between Microbes and Host in Sow Vaginas in Early Pregnancy.

Extensive research has explored the causes of embryo losses during early pregnancy by analyzing interaction mechanisms in sows' uterus, ignoring the importance of the lower reproductive tract in pregnancy development regulation. Despite recent progress in understanding the diversity of vaginal microbes under different physiological states, the dynamic of sows' vaginal microbiotas during pregnancy and the interaction between vaginal microbes and the host are poorly understood. Here, we performed a comprehensive analysis of sows' vaginal microbial communities in early pregnancy coupled with overall patterns of vaginal mucosal epithelium gene expression. The vaginal microbiota was analyzed by 16s rRNA or metagenome sequencing, and the vaginal mucosal epithelium transcriptome was analyzed by RNA sequencing, followed by integration of the data layers. We found that the sows' vaginal microbiotas in early pregnancy develop dynamically, and there is a homeostasis balance of Firmicutes and Proteobacteria. Subsequently, we identified two pregnancy-specific communities, which play diverse roles. The microbes in the vagina stimulate the epithelial cells, while vaginal epithelium changes its structure and functions in response to stimulation. These changes produce specific inflammation responses to promote pregnancy development. Our findings demonstrate the interaction between microbes and host in the sow vagina in early pregnancy to promote pregnancy development, meanwhile providing a reference data set for the study of targeted therapies of microbial homeostasis dysregulation in the female reproductive tract. IMPORTANCE This work sheds light on the dynamics of the sow vaginal microbiotas in early pregnancy and its roles in pregnancy development. Furthermore, this study provides insight into the functional mechanisms of reproductive tract microbes by outlining vaginal microbe-host interactions, which might identify new research and intervention targets for improving pregnancy development by modulating lower reproductive tract microbiota.

Genome-wide association study for loin muscle area of commercial crossbred pigs.

OBJECTIVE: Loin muscle area (LMA) is an important target trait of pig breeding. This study aimed to identify single nucleotide polymorphisms (SNPs) and genes associated with LMA in the Duroc×(Landrace×Yorkshire) crossbred pigs (DLY). METHODS: A genome-wide association study was performed using the Illumina 50K chip to map the genetic marker and genes associated with LMA in 511 DLY pigs (255 boars and 256 sows). RESULTS: After quality control, we detected 35,426 SNPs, including six SNPs significantly associated with LMA in pigs, with MARC0094338 and ASGA0072817 being the two key SNPs responsible for 1.77% and 2.48% of the phenotypic variance of LMA, respectively. Based on previous research, we determined two candidate genes (growth hormone receptor [GHR] and 3-oxoacid Co A-transferase 1 [OXCT1]) that are associated with fat deposition and muscle growth and found further additional genes (MYOCD, ARHGAP44, ELAC2, MAP2K4, FBXO4, FBLL1, RARS1, SLIT3, and RANK3) that are presumed to have an effect on LMA. CONCLUSION: This study contributes to the identification of the mutation that underlies quantitative trait loci associated with LMA and to future pig breeding programs based on marker-assisted selection. Further studies are needed to elucidate the role of the identified candidate genes in the physiological processes involved in LMA regulation.