Mammalian Genome最新文献

In livestock, copy number variations (CNVs) are important structural differences that affect phenotypic variety and adaptation. The genome-wide CNVs in 72 Red Sindhi cattle, an indigenous breed prized for its disease resistance and heat tolerance, were characterised in this study using double-digest restriction-site associated DNA sequencing (ddRAD-seq). The Illumina Novaseq platform was used to sequence the genomic DNA, and CNVs were identified using CNVnator with a 1000 bp bin size. PANTHER and Animal QTLdb were then utilized for functional annotation. A total of 3,269 high-confidence CNVs were found, mostly on autosomes. The highest number of CNVs (205) was detected on chromosome 1. Duplications mainly occurred in larger size classes (100 kb-1 Mb), while deletions were frequent in the 10-100 kb range. All regions contained 253 CNV regions (CNVRs), and 46% of individuals had a significant duplication on chromosome 18 (1-4.43 Mb). These CNVs overlapped with 2,593 genes associated with 112 quantitative trait loci (QTLs) that affected environmental adaptability, immunology, milk production, and reproduction. Znrf1, Snca, and Bola loci are important genes that have been linked to immune response and stress tolerance, underscoring their importance in the robustness of the breed. This study presents the first comprehensive CNV map for Red Sindhi cattle, highlighting the affordability of ddRAD-seq as a native breed genomic research tool. These findings support the use of marker-assisted selection and conservation techniques to produce climate-smart tropical animals.

This study aims to identify palmitoylation modification-related genes involved in depression and to explore the mechanism of gene action through the mediation of immune cells. We analyzed the latest reviews on palmitoylation, integrated palmitoylation-related gene loci, and extracted expression quantitative trait locus (eQTL) data for palmitoylation genes associated with depression. Through batch analysis, we initially identified positive genes and validated them using Mendelian randomization based on summary data (SMR) to pinpoint the target genes. Subsequently, we further conducted mediation analysis to explore the downstream mechanism of action of the target gene. In the results, Thirty-one palmitoylated genes were screened from the literature. After extracting eQTL data to obtain 22 co-located loci, batch analysis with depression yielded seven positive genes. Validation using SMR analysis identified ZDHHC5 (OR = 1.136755, P = 1.14 × 10⁻⁹, P_SMR= 6.88 × 10⁻¹⁰) and ZDHHC14 (OR = 1.055997, P = 2.29 × 10⁻⁹, P_SMR=0.02409) as the final target genes. The downstream mechanisms of action were explored using 731 immune cells. The results showed that: ZDHHC5 (Zinc Finger DHHC-Type Palmitoyltransferase 5) promotes depression through the mediating effects of effector memory double negative (CD4-negative and CD8-negative) (mediation effect = 0.065386) and CD28-negative double negative (CD4-negative and CD8-negative) percentage of T cells (CD28- DN (CD4-CD8-) % T cells) (mediation effect = 0.086404). ZDHHC14 (Zinc Finger DHHC-Type Palmitoyltransferase 14) promoted depression through EM DN (CD4-CD8-) AC (effector memory double negative activated T cell, mediation effect = 0.129494). Our results indicated that double negative T cells played an important role in this study. Thus, we conclude that ZDHHC5 and ZDHHC14 promote depression via the mediation of double-negative T cells.

The yak, a livestock breed native to Qinghai Province in China. However, the low intramuscular fat (IMF) content of yak meat negatively impacts its taste and flavor, reducing its relative economic value. The experiment was conducted by inhibiting the expression of miR-127 and miR-375 in yak precursor adipocytes. To explore its effect on the proliferation and differentiation of yak adipocyte precursors, and then analyze the molecular regulatory mechanisms of miR-127 and miR-375 on IMF deposition in yak. Furthermore, using RNA-Seq analysis, this study identified the differentially expressed genes (DEGs) and functional pathways regulated by miR-127 and miR-375 that influence IMF deposition. Cellular functional validation experiments showed that inhibiting miR-127 can suppress the proliferation of yak intramuscular preadipocytes and promote their differentiation. Meanwhile, the inhibition of miR-375 had the opposite effect, promoting proliferation and inhibiting differentiation. RNA-Seq analysis revealed that miR-127 inhibition altered the expression of several DEGs, including IFNB1, IFNA2, FABP4, CCL5, ITPKA, and IP6K3. Similarly, the inhibition of miR-375 affected the expression of genes such as IFNB1, IFNA2, FABP4, CCL5, FOS, and IL6. Functional enrichment analysis revealed that many of these DEGs were involved in key signaling pathways, such as the Phosphatidylinositol 3-Kinase-Protein Kinase B (PI3K-Akt) signaling pathway, the Mitogen-Activated Protein Kinase (MAPK) signaling pathway, and the Toll-like receptor (TLR) signaling pathway. Of these, the TLR signaling pathway showed the most significant enrichment of DEGs. Notably, IFNB1, IFNA2, and IL6 appeared to regulate the proliferation and differentiation of intramuscular preadipocytes in yaks by activating the TLR signaling pathway, thereby influencing IMF deposition.

Post-transcriptional regulation is a pivotal event in controlling gene expression, modulated by various epitranscriptomic modifications and RNA secondary structures, including G-quadruplexes (G4s). Recent studies have shown the co-occurrence of various epitranscriptomic modifications with RNA G-quadruplexes (rG4s) and their potential role in regulatory pathways. However, to the best of our knowledge, no work has been carried out investigating the role of 5-methylcytosine (m⁵C) colocalization with rG4. Herein, we have demonstrated the dynamic changes in colocalization of m⁵C sites with potential quadruplexes forming sequence (PQS) capable of forming rG4 structure in mouse embryonic stem cell (mESC) and different mouse tissues. Our results indicate that variable sets of genes are modified and dynamically changing during the developmental processes. However, among these, a few genes, including oncogene Hdgf along with Med24 and Emc3 are commonly found and contains m⁵C nucleotide in almost all 10 mouse tissues (including mESC), implicating their potential role in post-transcriptional regulation. The Enrichr-based analysis shows the involvement of genes containing m⁵C colocalized PQS in key biological processes and diseases. Additionally, binding analysis of RNA binding proteins (RBP) with colocalized sites revealed that many of these colocalized sites are the binding targets of RBPs such as YY1, YTHDC2 and RBFOX2. Collectively, these analyses provide an insight into the interplay between the m⁵C modification and rG4 to fine-tune the post-transcriptional regulation during development. It also suggests the possible involvement of m⁵C colocalized sites with PQS in modulating the expression of oncogene Hdgf, as well as the oncogenic and therapeutic targets like Med24 and Emc3.

Ensuring the quality and reproducibility of biological resources is essential for advancing biomedical research and upholding animal welfare standards. The European Mouse Mutant Archive (EMMA), part of the INFRAFRONTIER research infrastructure, plays a key role in this effort by cryopreserving scientifically validated mutant mouse and rat strains and making them accessible to the global scientific community. To further enhance its processes and promote transparency, INFRAFRONTIER/EMMA has developed a set of ten Quality Principles specifically tailored to the unique requirements of cryopreserved rodent mutant strains. These principles guide EMMA's workflows by providing a structured yet flexible quality framework across its distributed nodes. They encompass both general standards-such as adherence to the 3Rs (Replace, Reduce, Refine), staff competence, and continuous improvement-and more specific areas including scientific evaluation, data curation, and intellectual property rights. Each principle is presented with contextual background, defined requirements, practical recommendations, and key references. This initiative aims to strengthen the reliability, ethical integrity, and reproducibility of preclinical research resources.

Tissue specialization in humans is driven by their characteristic gene expression programs, yet the pathway-level enrichment and functional clustering of normal tissues as a comparative analysis platform remain poorly visualized. We analyzed RNA-seq data from 6,976 samples across 21 normal human tissues from the GTEx project. For each tissue, genes were ranked by average TPM expression, and Gene Set Enrichment Analysis (GSEA) was performed using KEGG, GOBP (Gene Ontology Biological Processes), and hallmark gene sets. Normalized enrichment scores (NES) were used to build tissue-tissue correlation matrices and tissue clustering. Tissues showing concordant clustering in both KEGG- and GOBP-based analyses were further compared for differential pathway enrichment using hallmark gene sets. Functional clustering consistently separated tissues into two major groups. Cluster 1 included tissues involved in structural support, immune defence, and transport (e.g., skin, colon, adipose), while cluster 2 encompassed tissues with neuroendocrine, contractile, and metabolic roles (e.g., brain, heart, liver). Comparative analysis identified 11 hallmark pathways with significant differences (Wilcoxon p < 0.05), including interferon signaling, hormone response, metabolism, and spermatogenesis. Three pathways-interferon-alpha response, apical junction assembly, and spermatogenesis-were validated with GOBP terms. Tissue pairs such as breast-adipose and liver-pancreas showed strong coherence, whereas liver-testis displayed functional divergence. This study reveals distinct functional regulation across normal tissues and provides a pathway-level reference for interpreting physiological and disease-associated transcriptomic changes. The findings offer a foundation for future integration with single-cell and multi-omics data to refine our understanding of tissue-specific biology.

The relationship between succinylation modification and epilepsy is not yet well defined, and the potential mediation of metabolic imbalance in its regulatory pathways requires deeper investigation. This study combines Mendelian randomization (MR) and single-cell transcriptomic techniques to investigate the causal interplay between succinylation-related genes, plasma metabolites, and epilepsy. Specifically, the eQTLGen and plasma metabolite databases are utilized for two-sample MR analysis, which evaluates genetic instrumental variables and quantifies causal effects. The two-step MR approach is applied to identify potential metabolic pathways mediating these genetic effects. This study integrates single-cell data from the temporal lobe of epilepsy patients to delineate cell-type-specific gene expression and regulatory networks. MR analysis identified that elevated expression of the CTBP1 gene significantly increases the risk of epilepsy (OR = 1.052, p = 0.0026). This pathogenic effect is mediated through the dysregulation of eight metabolites: a reduction in six neuroprotective sphingolipids and ceramide (β < 0), coupled with an accumulation of the pro-epileptic metabolite Methylsuccinate (β > 0). Among these, Sphingomyelin (d18:1/21:0, d17:1/22:0, d16:1/23:0) exhibited the highest mediation ratio (25.71%). Single-cell transcriptomics further revealed that CTBP1 is specifically highly expressed in excitatory neurons. In the epileptic temporal lobe, these neurons displayed rewired intercellular communication, primarily characterized by enhanced signaling via the NRG3-ERBB4 axis, alongside alterations in neuroimmune and metabolic pathways. This study provides the first integrated multi-omics evidence that CTBP1 may promote epileptogenesis through metabolic reprogramming and neuronal heterogeneity regulation, suggesting a potential role for CTBP1-mediated metabolic reprogramming in temporal lobe excitatory neurons in the disorder's pathology.

Anestrus, an infertility condition that affects several animal' species, is characterized by failing to display estrus. In pig production, it leads to the culling of 5 to 15% of the replacement gilts, resulting in significant losses impairing the swine female longevity. Despite that, little is known about the genetic mechanisms involved with anestrus in pigs. Hence, this study evaluated cyclic and non-cyclic F1 Landrace × Large White gilts to identify genomic regions associated with failure to display pubertal estrus through a genome-wide association study (GWAS), highlighting possible candidate genes involved with this condition in swine. Tissue samples were collected at 219.8 ± 4.7 days of age and genotyped with the PorcineSNP50 BeadChip from Illumina. In the GWAS, a SNP in the EML4 gene located on chromosome 3 (SSC3) was moderately associated with anestrus. The other 14 SNPs suggestively associated with anestrus were identified on SSCs 1, 3, 6, 7, 9 and 15. Investigating the regions close to those SNPs, new candidate genes for anestrus occurrence, such as EML4, DST, SRTB, MEAF, PHF1, PPMIB and PREPL, including 11 lncRNAs and a snoRNA were identified. Therefore, our study highlighted novel genetic mechanisms involved with the failure to display pubertal estrus in pigs, contributing to unraveling the genetic architecture of anestrus in pigs and other species. The use of genomic methodologies is a promising tool to help the early identification of gilts with potential reproductive problems associated with anestrus.

Kidney transplantation is the optimal treatment for end-stage renal disease (ESRD), but acute rejection (AR) remains a major factor affecting graft survival and patient prognosis. Currently, renal biopsy is the gold standard for diagnosing AR, but its invasiveness limits the application of dynamic monitoring. This study aims to analyze changes of immune cell and gene expression in the peripheral blood of AR recipients and construct a non-invasive AR diagnosis strategy. All datasets were downloaded from the GEO database. Single cells were annotated based on the expression profiles of surface proteins and changes of immune cell in the peripheral blood of AR and stable transplant (STA) recipients were compared. The high-dimensional weighted gene co-expression network analysis (hdWGCNA) algorithm was used to analyze gene modules related to AR and to screen out hub genes by integrating bulk RNA-Seq. Based on hub genes, consensus clustering stratified recipients into two sub-clusters and a non-invasive AR diagnostic model was constructed using Convolutional Neural Networks (CNNs). Additionally, we also constructed a predictive model for long-term graft survival through combinations of 111 machine learning algorithms and validated the expression of hub genes in the rat AR model. AR recipients had higher abundance of memory B cells, effector memory T cells, terminally differentiated effector memory T cells (TEMRA), and NK T cells but lower Tregs in the peripheral blood compared to STA recipients. Through hdWGCNA analysis, we identified gene modules associated with these immune cells and screened out four hub immune-related genes (TBX21, CX3CR1, STAT1, and NKG7) after integrating bulk RNA-Seq. Based on these hub genes, recipients can be stratified into two sub-clusters with distinct clinical outcomes and biological characteristics. We also innovatively constructed a non-invasive AR diagnostic model using CNNs, which can effectively address the issues caused by batch effects and demonstrate a high diagnostic accuracy. Besides, the predictive model for long-term graft survival constructed using the RSF algorithm can divided recipients into high- and low-risk groups, with significantly higher rates of AR and long-term graft failed in the high-risk group. This study successfully identified immune cell subsets and hub genes related to AR. Based on hub genes, we successfully identified two distinct molecular sub-clusters of kidney transplant recipients, and constructed a non-invasive diagnostic model for AR and a predictive model for long-term graft survival. These models offer new tools for precise diagnosis and prognosis in kidney transplantation and may advance precision medicine.

The minor effects of many SNP interactions often determine complex traits. This interaction, known as epistasis, represents a non-additive genetic effect in which the influence of one variant depends on the presence of others. In this study, we tested for epistatic effects on the residual feed intake (RFI) and residual methane emission (RME) traits of Nelore cattle. Additionally, we evaluated the impact of these interactions in other omics layers (i.e., microorganism profiles in the rumen content and feces and mRNA and miRNA expression in the rumen wall). The genomic interaction modules identified 14 and 10 significant SNP-SNP modules associated with RME and RFI traits, respectively. The majority of these SNPs were located in intronic and intergenic regions. The top pathways and processes associated with the SNP-SNP modules were identified, with several pathways related to the immune system and actin cytoskeleton organization. Furthermore, many other omics data were correlated with these SNP-SNP modules. Our findings suggest that the immune response and cilium organization may play important roles in feed efficiency. These insights not only provide novel candidates for enhancing these traits through microbiota composition and transcriptional regulation but also underscore the power of network analysis in uncovering new functional interactions. This research provides new insights and highlights candidate features for improving cattle feed efficiency and methane emissions.