Integration of multi-omics data reveals cis-regulatory variants that are associated with phenotypic differentiation of eastern from western pigs

Constructing eRNA-mediated gene regulatory networks to explore the genetic basis of muscle and fat-relevant traits in pigs

BACKGROUND

Enhancer RNAs (eRNAs) play a crucial role in transcriptional regulation. While significant progress has been made in understanding epigenetic regulation mediated by eRNAs, research on the construction of eRNA-mediated gene regulatory networks (eGRN) and the identification of critical network components that influence complex traits is lacking.

RESULTS

Here, employing the pig as a model, we conducted a comprehensive study using H3K27ac histone ChIP-seq and RNA-seq data to construct eRNA expression profiles from multiple tissues of two distinct pig breeds, namely Enshi Black (ES) and Duroc. In addition to revealing the regulatory landscape of eRNAs at the tissue level, we developed an innovative network construction and refinement method by integrating RNA-seq, ChIP-seq, genome-wide association study (GWAS) signals and enhancer-modulating effects of single nucleotide polymorphisms (SNPs) measured by self-transcribing active regulatory region sequencing (STARR-seq) experiments. Using this approach, we unraveled eGRN that significantly influence the growth and development of muscle and fat tissues, and identified several novel genes that affect adipocyte differentiation in a cell line model.

CONCLUSIONS

Our work not only provides novel insights into the genetic basis of economic pig traits, but also offers a generalizable approach to elucidate the eRNA-mediated transcriptional regulation underlying a wide spectrum of complex traits for diverse organisms.

Comprehensive Atlas of Alternative Splicing Reveals NSRP1 Promoting Adipogenesis through CCDC18

Alternative splicing (AS) plays a crucial role in regulating gene expression, function, and diversity. However, limited reports exist on the identification and comparison of AS in Eastern and Western pigs. Here, we analyzed 243 transcriptome data from eight tissues, integrating information on transcription factors (TFs), selection signals, splicing factors (SFs), and quantitative trait loci (QTL) to comprehensively study alternative splicing events (ASEs) in pigs. Five ASE types were identified, with Mutually Exclusive Exon (MXE) and Skipped Exon (SE) ASEs being the most prevalent. A significant portion of genes with ASEs (ASGs) showed conservation across all eight tissues (63.21-76.13% per tissue). Differentially alternative splicing genes (DASGs) and differentially expressed genes (DEGs) exhibited tissue specificity, with blood and adipose tissues having more DASGs. Functional enrichment analysis revealed coDASG_DEGs in adipose were enriched in pathways associated with adipose deposition and immune inflammation, while coDASG_DEGs in blood were enriched in pathways related to immune inflammation and metabolism. Adipose deposition in Eastern pigs might be linked to the down-regulation of immune-inflammation-related pathways and reduced insulin resistance. The TFs, selection signals, and SFs appeared to regulate ASEs. Notably, ARID4A (TF), NSRP1 (SF), ANKRD12, IFT74, KIAA2026, CCDC18, NEXN, PPIG, and ROCK1 genes in adipose tissue showed potential regulatory effects on adipose-deposition traits. NSRP1 could promote adipogenesis by regulating alternative splicing and expression of CCDC18. Conducting an in-depth investigation into AS, this study has successfully identified key marker genes essential for pig genetic breeding and the enhancement of meat quality, which will play important roles in promoting the diversity of pork quality and meeting market demand.

Exploring Multi-Tissue Alternative Splicing and Skeletal Muscle Metabolism Regulation in Obese- and Lean-Type Pigs

Alternative splicing (AS) is a crucial mechanism in post-transcriptional regulation, contributing significantly to the diversity of the transcriptome and proteome. In this study, we performed a comprehensive AS profile in nine tissues obtained from Duroc (lean-type) and Luchuan (obese-type) pigs. Notably, 94,990 AS events from 14,393 genes were identified. Among these AS events, it was observed that 80% belonged to the skipped exon (SE) type. Functional enrichment analysis showed that genes with more than ten AS events were closely associated with tissue-specific functions. Additionally, the analysis of overlap between differentially alternative splicing genes (DSGs) and differentially expressed genes (DEGs) revealed the highest number of overlapped genes in the heart and skeletal muscle. The novelty of our study is that it identified and validated three genes (PYGM, MAPK11 and CAMK2B) in the glucagon signaling pathway, and their alternative splicing differences were highly significant across two pig breeds. In conclusion, our study offers novel insights into the molecular regulation of diverse tissue physiologies and the phenotypic differences between obese- and lean-type pigs, which are helpful for pig breeding.

Uncovering Evolutionary Adaptations in Common Warthogs through Genomic Analyses

In the Suidae family, warthogs show significant survival adaptability and trait specificity. This study offers a comparative genomic analysis between the warthog and other Suidae species, including the Luchuan pig, Duroc pig, and Red River hog. By integrating the four genomes with sequences from the other four species, we identified 8868 single-copy orthologous genes. Based on 8868 orthologous protein sequences, phylogenetic assessments highlighted divergence timelines and unique evolutionary branches within suid species. Warthogs exist on different evolutionary branches compared to DRCs and LCs, with a divergence time preceding that of DRC and LC. Contraction and expansion analyses of warthog gene families have been conducted to elucidate the mechanisms of their evolutionary adaptations. Using GO, KEGG, and MGI databases, warthogs showed a preference for expansion in sensory genes and contraction in metabolic genes, underscoring phenotypic diversity and adaptive evolution direction. Associating genes with the QTLdb-pigSS11 database revealed links between gene families and immunity traits. The overlap of olfactory genes in immune-related QTL regions highlighted their importance in evolutionary adaptations. This work highlights the unique evolutionary strategies and adaptive mechanisms of warthogs, guiding future research into the distinct adaptability and disease resistance in pigs, particularly focusing on traits such as resistance to African Swine Fever Virus.

Transcription Factor SATB2 Regulates Skeletal Muscle Cell Proliferation and Migration via HDAC4 in Pigs

Skeletal muscle development remarkably affects meat production and growth rate, regulated by complex regulatory mechanisms in pigs. Specific AT sequence-binding protein 2 (SATB2) is a classic transcription factor and chromatin organizer, which holds a profound effect in the regulation of chromatin remodeling. However, the regulation role of SATB2 concerning skeletal muscle cell fate through chromatin remodeling in pigs remains largely unknown. Here, we observed that SATB2 was expressed higher in the lean-type compared to the obese-type pigs, which also enriched the pathways of skeletal muscle development, chromatin organization, and histone modification. Functionally, knockdown SATB2 led to decreases in the proliferation and migration markers at the mRNA and protein expression levels, respectively, while overexpression SATB2 had the opposite effects. Further, we found histone deacetylase 4 (HDAC4) was a key downstream target gene of SATB2 related to chromatin remodeling. The binding relationship between SATB2 and HDAC4 was confirmed by a dual-luciferase reporter system and ChIP-qPCR analysis. Besides, we revealed that HDAC4 promoted the skeletal muscle cell proliferation and migration at the mRNA and protein expression levels, respectively. In conclusion, our study indicates that transcription factor SATB2 binding to HDAC4 positively contributes to skeletal muscle cell proliferation and migration, which might mediate the chromatin remodeling to influence myogenesis in pigs. This study develops a novel insight into understanding the molecular regulatory mechanism of myogenesis, and provides a promising gene for genetic breeding in pigs.

Circular RNA transcriptome across multiple tissues reveal skeletal muscle-specific circPSME4 regulating myogenesis

There are significant differences in meat production, growth rate and other traits between Western commercial pigs and Chinese local pigs. Comparative transcriptome approaches have identified many coding and non-coding candidate genes associated various traits. However, the expression and function of circular RNAs (circRNAs) in different pig tissues are largely unknown. In this study, we conducted a comprehensive analysis of the genome-wide circRNA expression profile across ten tissues in Luchuan (a Chinese local breed) and Duroc (a Western commercial breed) pigs. We identified a total of 56,254 circRNAs, of which 42.9 % were not previously annotated. We found that 33.7 % of these circRNAs were differentially expressed. Enrichment analysis revealed that differentially expressed circRNAs might contribute to the phenotypic differentiation between Luchuan and Duroc pigs. We identified 538 tissue-specific circRNAs, most of which were specifically expressed in the brain and skeletal muscle. Competitive endogenous RNA network analysis suggested that skeletal muscle-specific circPSME4 was co-expressed with MYOD1 and targeted by ssc-miR-181d-3p. Functional analysis revealed that circPSME4 knockdown could promote the proliferation and differentiation of myoblasts. Together, our findings provide valuable resources of circRNAs for animal breeding and biomedical research. We demonstrated that circPSME4 is a novel regulator of skeletal muscle development.

DeepSATA: A Deep Learning-Based Sequence Analyzer Incorporating the Transcription Factor Binding Affinity to Dissect the Effects of Non-Coding Genetic Variants

Utilizing large-scale epigenomics data, deep learning tools can predict the regulatory activity of genomic sequences, annotate non-coding genetic variants, and uncover mechanisms behind complex traits. However, these tools primarily rely on human or mouse data for training, limiting their performance when applied to other species. Furthermore, the limited exploration of many species, particularly in the case of livestock, has led to a scarcity of comprehensive and high-quality epigenetic data, posing challenges in developing reliable deep learning models for decoding their non-coding genomes. The cross-species prediction of the regulatory genome can be achieved by leveraging publicly available data from extensively studied organisms and making use of the conserved DNA binding preferences of transcription factors within the same tissue. In this study, we introduced DeepSATA, a novel deep learning-based sequence analyzer that incorporates the transcription factor binding affinity for the cross-species prediction of chromatin accessibility. By applying DeepSATA to analyze the genomes of pigs, chickens, cattle, humans, and mice, we demonstrated its ability to improve the prediction accuracy of chromatin accessibility and achieve reliable cross-species predictions in animals. Additionally, we showcased its effectiveness in analyzing pig genetic variants associated with economic traits and in increasing the accuracy of genomic predictions. Overall, our study presents a valuable tool to explore the epigenomic landscape of various species and pinpoint regulatory deoxyribonucleic acid (DNA) variants associated with complex traits.