Additive and Dominance Genome-Wide Association Studies Reveal the Genetic Basis of Heterosis Related to Growth Traits of Duhua Hybrid Pigs.

Heterosis has been extensively used for pig genetic breeding and production, but the genetic basis of heterosis remains largely elusive. Crossbreeding between commercial and native breeds provides a good model to parse the genetic basis of heterosis. This study uses Duhua hybrid pigs, a crossbreed of Duroc and Liangguang small spotted pigs, as materials to explore the genetic basis underlying heterosis related to growth traits at the genomic level. The mid-parent heterosis (MPH) analysis showed heterosis of this Duhua offspring on growth traits. In this study, we examined the impact of additive and dominance effects on 100 AGE (age adjusted to 100 kg) and 100 BF (backfat thickness adjusted to 100 kg) of Duhua hybrid pigs. Meanwhile, we successfully identified SNPs associated with growth traits through both additive and dominance GWASs (genome-wide association studies). These findings will facilitate the subsequent in-depth studies of heterosis in the growth traits of Duhua pigs.

Single-Cell RNA-Sequencing Reveals Heterogeneity and Transcriptional Dynamics in Porcine Circulating CD8+ T Cells.

Pigs are the most important source of meat and valuable biomedical models. However, the porcine immune system, especially the heterogeneity of CD8 T cell subtypes, has not been fully characterized. Here, using single-cell RNA sequencing, we identified 14 major cell types from peripheral blood circulating cells of pigs and observed remarkable heterogeneity among CD8 T cell types. Upon re-clustering of CD8+ T cells, we defined four CD8 T cell subtypes and revealed their potential differentiation trajectories and transcriptomic differences among them. Additionally, we identified transcription factors with potential regulatory roles in maintaining CD8 T cell differentiation. The cell-cell communication analysis inferred an extensive interaction between CD8 T cells and other immune cells. Finally, cross-species analysis further identified species-specific and conserved cell types across different species. Overall, our study provides the first insight into the extensive functional heterogeneity and state transitions among porcine CD8 T cell subtypes in pig peripheral blood, complements the knowledge of porcine immunity, and enhances its potential as a biomedical model.

Comparative transcriptome analysis of T lymphocyte subpopulations and identification of critical regulators defining porcine thymocyte identity.

Introduction: The development and migration of T cells in the thymus and peripheral tissues are crucial for maintaining adaptive immunity in mammals. However, the regulatory mechanisms underlying T cell development and thymocyte identity formation in pigs remain largely underexplored. Method: Here, by integrating bulk and single-cell RNA-sequencing data, we investigated regulatory signatures of porcine thymus and lymph node T cells. Results: The comparison of T cell subpopulations derived from porcine thymus and lymph nodes revealed that their transcriptomic differences were influenced more by tissue origin than by T cell phenotypes, and that lymph node cells exhibited greater transcriptional diversity than thymocytes. Through weighted gene co-expression network analysis (WGCNA), we identified the key modules and candidate hub genes regulating the heterogeneity of T cell subpopulations. Further, we integrated the porcine thymocyte dataset with peripheral blood mononuclear cell (PBMC) dataset to systematically compare transcriptomic differences between T cell types from different tissues. Based on single-cell datasets, we further identified the key transcription factors (TFs) responsible for maintaining porcine thymocyte identity and unveiled that these TFs coordinately regulated the entire T cell development process. Finally, we performed GWAS of cell type-specific differentially expressed genes (DEGs) and 30 complex traits, and found that the DEGs in thymus-related and peripheral blood-related cell types, especially CD4_SP cluster and CD8-related cluster, were significantly associated with pig productive and reproductive traits. Discussion: Our findings provide an insight into T cell development and lay a foundation for further exploring the porcine immune system and genetic mechanisms underlying complex traits in pigs.

H3K27ac modification and transcription characteristics of adipose and muscle tissues in Chuxiang Black pig.

The establishment of high-quality pork breeds for improving meat quality in the pig industry is needed. The Chuxiang Black (CX) pig is a new breed developed from Chinese local pigs and Western lean pigs that has a high proportion of lean meat and excellent meat quality. However, the characteristics of cis-regulatory elements in CX pigs are still unknown. In this study, cis-regulatory elements of muscle and adipose tissues in CX pigs were investigated using ChIP-seq and RNA sequencing. Compared with the reported cis-regulatory elements of muscle and adipose tissues, 1768 and 1012 highly activated enhancers and 433 and 275 highly activated promoters in CX muscle and adipose tissues were identified, respectively. Motif analysis showed that transcription factors, such as MEF2A and MEF2C, were core regulators of highly activated enhancers and promoters in muscle. Similarly, the transcription factors JUNB and CUX1 were identified as essential for highly activated enhancers and promoters in CX adipose tissue. These results enrich the resources for the analysis of cis-regulatory elements in the pig genome and provide new basic data for further meat quality improvement through breeding in pigs.

Ascorbic acid and selenium nanoparticles synergistically interplay in chromium stress mitigation in rice seedlings by regulating oxidative stress indicators and antioxidant defense mechanism.

Ascorbic acid (AsA) and selenium nanoparticles (SeNPs) were versatile plant growth regulators, playing multiple roles in promoting plant growth under heavy metal stresses. This study aimed to evaluate the beneficial role of individual and combined effects of AsA and SeNPs on morpho-physio-biochemical traits of rice with or without chromium (Cr) amendment. The results indicated that Cr negatively affected plant biomass, gas exchange parameters, total soluble sugar, proline, relative water contents, and antioxidant-related gene expression via increasing reactive oxygen species (MDA, H2O2, O2•-) formation, resulting in plant growth reduction. The application of AsA and SeNPs, individually or in combination, decreased the uptake and translocation of Cr in rice seedlings, increased seedlings with tolerance to Cr toxicity, and significantly improved the rice seedling growth. Most notably, AsA + SeNP treatment strengthened the antioxidative defense system through ROS quenching and Cr detoxification. The results collectively suggested that the application of AsA and SeNPs alone or in combination had the potential to alleviate Cr toxicity in rice and possibly other crop species.

E-GWAS: an ensemble-like GWAS strategy that provides effective control over false positive rates without decreasing true positives.

BACKGROUND: Genome-wide association studies (GWAS) are an effective way to explore genotype-phenotype associations in humans, animals, and plants. Various GWAS methods have been developed based on different genetic or statistical assumptions. However, no single method is optimal for all traits and, for many traits, the putative single nucleotide polymorphisms (SNPs) that are detected by the different methods do not entirely overlap due to the diversity of the genetic architecture of complex traits. Therefore, multi-tool-based GWAS strategies that combine different methods have been increasingly employed. To take this one step further, we propose an ensemble-like GWAS strategy (E-GWAS) that statistically integrates GWAS results from different single GWAS methods. RESULTS: E-GWAS was compared with various single GWAS methods using simulated phenotype traits with different genetic architectures. E-GWAS performed stably across traits with different genetic architectures and effectively controlled the number of false positive genetic variants detected without decreasing the number of true positive variants. In addition, its performance could be further improved by using a bin-merged strategy and the addition of more distinct single GWAS methods. Our results show that the numbers of true and false positive SNPs detected by the E-GWAS strategy slightly increased and decreased, respectively, with increasing bin size and when the number and the diversity of individual GWAS methods that were integrated in E-GWAS increased, the latter being more effective than the bin-merged strategy. The E-GWAS strategy was also applied to a real dataset to study backfat thickness in a pig population, and 10 candidate genes related to this trait and expressed in adipose-associated tissues were identified. CONCLUSIONS: Using both simulated and real datasets, we show that E-GWAS is a reliable and robust strategy that effectively integrates the GWAS results of different methods and reduces the number of false positive SNPs without decreasing that of true positive SNPs.

Pleiotropic architectures of porcine immune and growth trait pairs revealed by a self-product-based transcriptome method.

Pleiotropy is an important biological phenomenon with complicated genetic architectures for multiple traits. To date, pleiotropy has been mainly identified by multi-trait genome-wide association studies, but this method has its disadvantages, and new developments for pleiotropy detection methods are needed. Here we define a novel metric, self-product, to measure individual-level co-variation of two traits, and develop a novel self-product-based transcriptome method to detect pleiotropic genes (PGs). Our method was tested using four immune-growth trait pairs and four immune-immune trait pairs in pigs. Comparative transcriptome analyses identified hundreds of candidate PGs related to eight trait pairs from two tails of self-product distribution. Gene Ontology enrichment analysis indicated that most of identified PGs were involved in immune- or growth-related biological processes. We established PG interaction networks to exhibit core genes shared by eight trait pairs, of which CCL5 and IL-10 genes were the hub genes. Genetic association analyses showed that SmaI-polymorphisms of CCL5 and IL-10 genes had significant associations with phenotypic co-variations of multiple trait pairs, indicating that the variants in pleiotropic genes were also pleiotropic variants. Taken together, the validity of our proposed method was preliminarily verified, and our findings provide new insights into the genetic basis of pleiotropic architectures of immune and growth trait pairs in pigs.

IAnimal: a cross-species omics knowledgebase for animals.

With the exponential growth of multi-omics data, its integration and utilization have brought unprecedented opportunities for the interpretation of gene regulation mechanisms and the comprehensive analyses of biological systems. IAnimal (https://ianimal.pro/), a cross-species, multi-omics knowledgebase, was developed to improve the utilization of massive public data and simplify the integration of multi-omics information to mine the genetic mechanisms of objective traits. Currently, IAnimal provides 61 191 individual omics data of genome (WGS), transcriptome (RNA-Seq), epigenome (ChIP-Seq, ATAC-Seq) and genome annotation information for 21 species, such as mice, pigs, cattle, chickens, and macaques. The scale of its total clean data has reached 846.46 TB. To better understand the biological significance of omics information, a deep learning model for IAnimal was built based on BioBERT and AutoNER to mine 'gene' and 'trait' entities from 2 794 237 abstracts, which has practical significance for comprehending how each omics layer regulates genes to affect traits. By means of user-friendly web interfaces, flexible data application programming interfaces, and abundant functional modules, IAnimal enables users to easily query, mine, and visualize characteristics in various omics, and to infer how genes play biological roles under the influence of various omics layers.

Assessment of Hematologic and Biochemical Parameters for Healthy Commercial Pigs in China.

Hematologic and biochemical data are useful for indicating disease diagnosis and growth performance in swine. However, the assessment of these parameters in healthy commercial pigs is rare in China. Thus, blood samples were collected from 107 nursery pigs and 87 sows and were analyzed for 25 hematologic and 14 biochemical variables. After the rejection of the outliers and the detection of the data distribution, the correlations between the blood parameters were analyzed and the hematologic/biochemical RIs were preliminarily established using the 95% percentile RI. Correlation analysis showed that albumin was the hub parameter among the blood parameters investigated, and genes overlapping with key correlated variables were discovered. Most of the hematologic and biochemical parameters were significantly different between nursery pigs and sows. The 95% RIs of white blood cells and red blood cells were 7.18-24.52 × 109/L and 5.62-7.84 × 1012/L, respectively, for nursery pigs, but 9.34-23.84 × 109/L and 4.98-8.29 × 1012/L for sows. The 95% RIs of total protein and albumin were 43.16-61.23 g/dL and 19.35-37.86 g/dL, respectively, for nursery pigs, but 64.96-88.68 g/dL and 31.91-43.28 g/dL for sows. In conclusion, our study highlights the variability in blood parameters between nursery pigs and sows and provides fundamental data for the health monitoring of commercial pigs in China.

rMVP: A Memory-efficient, Visualization-enhanced, and Parallel-accelerated Tool for Genome-wide Association Study.

Along with the development of high-throughput sequencing technologies, both sample size and SNP number are increasing rapidly in genome-wide association studies (GWAS), and the associated computation is more challenging than ever. Here, we present a memory-efficient, visualization-enhanced, and parallel-accelerated R package called "rMVP" to address the need for improved GWAS computation. rMVP can 1) effectively process large GWAS data, 2) rapidly evaluate population structure, 3) efficiently estimate variance components by Efficient Mixed-Model Association eXpedited (EMMAX), Factored Spectrally Transformed Linear Mixed Models (FaST-LMM), and Haseman-Elston (HE) regression algorithms, 4) implement parallel-accelerated association tests of markers using general linear model (GLM), mixed linear model (MLM), and fixed and random model circulating probability unification (FarmCPU) methods, 5) compute fast with a globally efficient design in the GWAS processes, and 6) generate various visualizations of GWAS-related information. Accelerated by block matrix multiplication strategy and multiple threads, the association test methods embedded in rMVP are significantly faster than PLINK, GEMMA, and FarmCPU_pkg. rMVP is freely available at https://github.com/xiaolei-lab/rMVP.

Whole genome variants across 57 pig breeds enable comprehensive identification of genetic signatures that underlie breed features.

BACKGROUND: A large number of pig breeds are distributed around the world, their features and characteristics vary among breeds, and they are valuable resources. Understanding the underlying genetic mechanisms that explain across-breed variation can help breeders develop improved pig breeds. RESULTS: In this study, we performed GWAS using a standard mixed linear model with three types of genome variants (SNP, InDel, and CNV) that were identified from public, whole-genome, sequencing data sets. We used 469 pigs of 57 breeds, and we identified and analyzed approximately 19 million SNPs, 1.8 million InDels, and 18,016 CNVs. We defined six biological phenotypes by the characteristics of breed features to identify the associated genome variants and candidate genes, which included coat color, ear shape, gradient zone, body weight, body length, and body height. A total of 37 candidate genes was identified, which included 27 that were reported previously (e.g., PLAG1 for body weight), but the other 10 were newly detected candidate genes (e.g., ADAMTS9 for coat color). CONCLUSION: Our study indicated that using GWAS across a modest number of breeds with high density genome variants provided efficient mapping of complex traits.

Three functional mutation sites affect the immune response of pigs through altering the expression pattern and IgV domain of the CD4 protein.

BACKGROUND: The CD4 protein is an important surface marker of T lymphocytes, which can mediate the antigen presentation process by interacting with MHC II and TCR molecules in human and mouse. RESULTS: In this study, two haplotypes (A and B) of the CD4 gene were found within Chinese indigenous and Western commercial pig breeds. These two haplotypes were defined by 22 fully linked SNPs in the CDS region of the CD4 gene. The expression level and localization of the CD4 protein were significantly different between haplotypes A and B. Transcriptome analysis revealed that the immune response-related genes and signaling pathways were down-regulated in genotype AA. Finally, three linked functional SNPs were identified, which affected the expression level and membrane localization of the CD4 protein in pigs. These three SNPs led to the replacements of two amino acids in the IgV1 domain of the CD4 protein, and related to the function of the CD4 protein in the immune response. CONCLUSION: These three linked SNPs were the key functional mutation sites in the CD4 gene, which played important roles in the immune response, and could be utilized as new molecular markers in breeding for disease resistance in pigs.

Characterization of immune pleiotropy of ESR1 gene in pigs.

It is well known that the estrogen receptor alpha gene (ESR1) affects the reproductive traits of pigs; however, the immune role of ESR1 gene has not yet been resolved. Here, we characterized the pleiotropic aspects of ESR1 gene in immunity using the pig model. Tissue expression profile showed that the ESR1 gene had a broad ectopic expression in multiple reproductive and immune-related tissues/organs, which provided the tissue-level spatial fundamental of ESR1 gene that might function as a pleiotropic immune regulator. Using the peripheral blood cell model, a coupling transcriptome analytical strategy was proposed and verified that there existed strong positive or negative correlations of ESR1 gene with hundreds of differentially expressed genes that were involved in the immune regulation, indicating that the ESR1 gene might affect or be affected by, directly or indirectly, dozens of immune-related genes in the peripheral blood cells. Furthermore, the results of genetic association analysis showed that the SmaI-polymorphism of ESR1 gene had significant or highly significant associations with multiple immune traits, including platelet (PLT), hematocrit (HCT), the number of CD4-CD8-CD3- cells, plateletcrit (PCT), mean corpuscular volume (MCV), and mean corpuscular hemoglobin concentration (MCHC). Multiple evidences supported the immune pleiotropic roles of ESR1 gene in pigs. The study advances our understanding of the cross-species immune pleiotropic landscape of ESR1 gene and also provides a potential pleiotropic molecular marker for disease-resistant breeding in pigs.

CRISPR screening of porcine sgRNA library identifies host factors associated with Japanese encephalitis virus replication.

Japanese encephalitis virus (JEV) is a mosquito-borne zoonotic flavivirus that causes encephalitis and reproductive disorders in mammalian species. However, the host factors critical for its entry, replication, and assembly are poorly understood. Here, we design a porcine genome-scale CRISPR/Cas9 knockout (PigGeCKO) library containing 85,674 single guide RNAs targeting 17,743 protein-coding genes, 11,053 long ncRNAs, and 551 microRNAs. Subsequently, we use the PigGeCKO library to identify key host factors facilitating JEV infection in porcine cells. Several previously unreported genes required for JEV infection are highly enriched post-JEV selection. We conduct follow-up studies to verify the dependency of JEV on these genes, and identify functional contributions for six of the many candidate JEV-related host genes, including EMC3 and CALR. Additionally, we identify that four genes associated with heparan sulfate proteoglycans (HSPGs) metabolism, specifically those responsible for HSPGs sulfurylation, facilitate JEV entry into porcine cells. Thus, beyond our development of the largest CRISPR-based functional genomic screening platform for pig research to date, this study identifies multiple potentially vulnerable targets for the development of medical and breeding technologies to treat and prevent diseases caused by JEV.

A gene prioritization method based on a swine multi-omics knowledgebase and a deep learning model.

The analyses of multi-omics data have revealed candidate genes for objective traits. However, they are integrated poorly, especially in non-model organisms, and they pose a great challenge for prioritizing candidate genes for follow-up experimental verification. Here, we present a general convolutional neural network model that integrates multi-omics information to prioritize the candidate genes of objective traits. By applying this model to Sus scrofa, which is a non-model organism, but one of the most important livestock animals, the model precision was 72.9%, recall 73.5%, and F1-Measure 73.4%, demonstrating a good prediction performance compared with previous studies in Arabidopsis thaliana and Oryza sativa. Additionally, to facilitate the use of the model, we present ISwine ( http://iswine.iomics.pro/ ), which is an online comprehensive knowledgebase in which we incorporated almost all the published swine multi-omics data. Overall, the results suggest that the deep learning strategy will greatly facilitate analyses of multi-omics integration in the future.

Identification of functional mutations at FOXP3 binding site within BIC gene that alter the expression of miR-155 in pigs.

MiR-155 is an immune microRNA encoded within the BIC gene. Dozens of researches have uncovered the importance of high expression of miR-155 in promoting the development of immune organs and strengthening immune response and inflammatory response. Some natural mutations located in the miR-155/BIC region were revealed to disturb the expression level of miR-155 in several mammalian species, and our previous study also identified several mutations occurring near the miR-155/BIC region in pigs. However, the consequences of BIC locus-harbored mutations in pig genome remain unclear. In this study, we used Chinese Meishan and British Large White pigs to identify mutations within the miR-155/BIC region, and explore whether there are effects on expressions of miR-155 and its target genes. Target sequencing identified six potential FOXP3 protein binding sites (AAACA) in the BIC gene, among which there were two A/C mutations (AAACC) at the -108 bp and -305 bp upstream of the miR-155 precursors in Meishan pigs, but not in Large White pigs. A series of experiments confirmed that the FOXP3 protein mainly binds to the -305 bp position, and the binding efficiency of the CC haplotype to FOXP3 protein was higher than that of the wild type, resulting in increased expression of miR-155, and consequentially decreased the expressions of its target genes. Our newly identified mutations are functional, which explain partial reasons for the difference in immunity between Meishan and Large White pigs, and provide potential molecular markers to genetically improve the disease resistance in the pig breeding practice.

The population growth, development and metabolic enzymes of the white-backed planthopper, Sogatella furcifera (Hemiptera: Delphacidae) under the sublethal dose of triflumezopyrim.

Triflumezopyrim, a new nicotinic acetylcholine receptor (nAChR) inhibition, can effectively control piercing-sucking insect pests such as white-backed planthopper (Sogatella furcifera). At present, there has been no reports on the effects of triflumezopyrim on the population growth and development of S. furcifera. In this experiment, an age-stage two-sex life table was used to evaluate the impact of triflumezopyrim on the biological parameters of S. furcifera. The results showed that the adult preoviposition period (APOP) and total preoviposition period (TPOP) of the F1 generation were significantly higher than those of the F0 and F4 generations, on the contrary the average fecundity, intrinsic rate of increase (r) and finite rate of increase (λ) of the F4 generation were higher than those of the F0 and F1 generations. The results of synergists and enzyme activities indicated that the CarE and P450 activities in the F4 generation were significantly higher than those in the F0 generation (P < 0.05). The protein contents of vitellogenin (Vg) and vitellogenin receptor (VgR) and relative expression quality of VgR in the F4 female adults were also significantly higher than those in the F0 generation (P < 0.05). These results showed that triflumezopyrim at a low concentration could promote the growth and reproduction of S. furcifera, and that may provide a reference for the rational use of triflumezopyrim in the future.

Genome-Wide Association Study Reveals Candidate Genes for Growth Relevant Traits in Pigs.

Improvement of the growth rate is a challenge in the pig industry, the Average Daily Gain (ADG) and Days (AGE) to 100 kg are directly related to growth performance. We performed genome-wide association study (GWAS) and genetic parameters estimation for ADG and AGE using the genomic and phonemic from four breed (Duroc, Yorkshire, Landrace, and Pietrain) populations. All analyses were performed by a multi-loci GWAS model, FarmCPU. The GWAS results of all four breeds indicate that five genome-wide significant SNPs were associated with ADG, and the nearby genomic regions explained 4.08% of the genetic variance and 1.90% of the phenotypic variance, respectively. For AGE, six genome-wide significant SNPs were detected, and the nearby genomic regions explained 8.09% of the genetic variance and 3.52% of phenotypic variance, respectively. In total, nine candidate genes were identified to be associated with growth and metabolism. Among them, TRIB3 was reported to associate with pig growth, GRP, TTR, CNR1, GLP1R, BRD2, HCRTR2, SEC11C, and ssc-mir-122 were reported to associate with growth traits in human and mouse. The newly detected candidate genes will advance the understanding of growth related traits and the identification of the novel variants will suggest a potential use in pig genomic breeding programs.

Transcriptional Profiling of Leucocyte Count Variation from Porcine Peripheral Blood Reveals Differential Gene Expression.

Leucocytes have tremendous health-check importance related to the individual antiviral capacity of pigs and other mammals. However, the molecular mechanism of the immune response of blood leucocytes in pigs is not completely known. This study investigated the leucocyte-count variation before and after poly I:C stimulation in a Duroc-Erhualian F2 population. Pigs with increased and decreased differences in leucocyte counts were coded as increased responder (IR) and decreased responder (DR), respectively. Then, we used microarray technology to compare the gene-expression profiles of both groups of pigs. Transcriptomic analysis identified 129 differentially expressed genes (DEGs) in IR pigs and 136 DEGs in DR pigs. Forty-one common DEGs showed that both groups had similar expression patterns of immune responses. These results illustrated a differential expression in both groups. Furthermore, qPCR experiment was performed to verify the differential-expression profile. Functional annotation of the DEGs indicated that both IR and DR pigs were similar in several biological processes, including innate immune response, and also exhibited distinct differences in biological processes, molecular function, and pathways. These results provided insights into the mechanism underlying the antiviral capacity of pigs. Trial registration number is CAS Registry Number 24939-03-5.