Mammalian Genome最新文献

Background: Coronary artery disease (CAD) is the leading cause of death worldwide, and aberrant phagocytosis may be involved in its development. Understanding this aspect may provide new avenues for prompt CAD diagnosis.

Methods: CAD-related information was obtained from Gene Expression Omnibus datasets GSE66360, GSE113079, and GSE59421. We identified 995 upregulated and 1086 downregulated differentially expressed genes (DEGs) in GSE66360. Weighted gene co-expression network analysis revealed a module of 503 genes relevant to CAD. Using clusterProfiler, we revealed 32 CAD-related PRFs. Eight candidate genes were identified in a protein-protein interaction network. Machine learning algorithms identified CAD biomarkers that underwent gene set enrichment analysis, immune cell analysis with CIBERSORT, microRNA (miRNA) prediction using the miRWalk database, transcription factor (TF) level predication through ChEA3, and drug prediction with DGIdb. Cytoscape visualized the miRNA -mRNA- TF, miRNA-single nucleotide polymorphism-mRNA, and biomarker-drug networks.

Results: IL1B, TLR2, FCGR2A, SYK, FCER1G, and HCK were identified as CAD biomarkers. The area under the curve of a diagnostic model based on the six biomarkers was > 0.7 for the GSE66360 and GSE113079 datasets. Gene set enrichment analysis revealed differences in their biological pathways. CIBERSORT revealed that 10 immune cell types were differentially expressed between the CAD and control groups. The TF-mRNA-miRNA network showed that has-miR-1207-5p regulates HCK and FCER1G expression and that RUNX1 and SPI may be important TFs. Ninety-five drugs were predicted, including aspirin, which influenced ILIB and FCERIG.

Conclusion: In this study, six biomarkers (IL1B, TLR2, FCGR2A, SYK, FCER1G, and HCK) related to CAD phagocytic regulatory factors were identified, and their expression regulatory relationships in CAD were further studied, providing a deeper understanding of the pathogenesis, diagnosis, and potential treatment strategies of CAD.

Non-Small Cell lung cancer (NSCLC) is known for its fast progression, metastatic potency, and a leading cause of mortality globally. At diagnosis, approximately 30-40% of NSCLC patients already present with metastasis. Epithelial to mesenchymal transition (EMT) is a developmental program implicated in cancer progression and metastasis. Transforming Growth Factor-β (TGFβ) and its signalling plays a prominent role in orchestrating the process of EMT and cancer metastasis. In present study, a comprehensive molecular interaction map of TGFβ induced EMT in NSCLC was developed through an extensive literature survey. The map encompasses 394 species interconnected through 554 reactions, representing the relationship and complex interplay between TGFβ induced SMAD dependent and independent signalling pathways (PI3K/Akt, Wnt, EGFR, JAK/STAT, p38 MAPK, NOTCH, Hypoxia). The map, built using Cell Designer and compliant with SBGN and SBML standards, was subsequently translated into a logical modelling framework using CaSQ and dynamically analysed with Cell Collective. These analyses illustrated the complex regulatory dynamics, capturing the known experimental outcomes of TGFβ induced EMT in NSCLC including the co-existence of hybrid EM phenotype during transition. Hybrid EM phenotype is known to contribute for the phenotypic plasticity during metastasis. Network-based analysis identified the crucial network level properties and hub regulators, while the transcriptome-based analysis cross validated the prognostic significance and clinical relevance of key regulators. Overall, the map developed and the subsequent analyses offer deeper understanding of the complex regulatory network governing the process of EMT in NSCLC.

Rat models have been a major model for studying complex disease mechanisms, behavioral phenotypes, environmental factors, and for drug development and discovery. Inbred rat strains control for genetic background and allow for repeated, reproducible, cellular and whole animal phenotyping. The Hybrid Rat Diversity Panel (HRDP) was designed to be a powerful panel of inbred rats with genomic, physiological, and behavioral data to serve as a resource for systems genetics. The HRDP consists of 96-98 inbred rat strains aimed to maximize power to detect specific genetic loci associated with complex traits while maximizing the genetic diversity among strains. The panel consists of 32-34 genetically diverse inbred strains and two panels of recombinant inbred panels. To establish the HRDP program, embryo resuscitation and breeding were done to establish colonies for distribution. Whole genome sequencing was performed to achieve 30X coverage. Genomic, phenotype, and strain information is available through the Hybrid Rat Diversity Panel Portal at the Rat Genome Database ( http://rgd.mcw.edu ).

Cashmere, also known as pashmina, is derived from the secondary hair follicles of Cashmere/Changthangi goats. Renowned as the world's most luxurious natural fiber, it holds significant economic value in the textile industry. This comprehensive review enhances our understanding of the complex biological processes governing cashmere/pashmina fiber development and quality, enabling advancements in selective breeding and fiber enhancement strategies. The review specifically examines the molecular determinants influencing fiber development, with an emphasis on keratins (KRTs) and keratin-associated proteins (KRTAPs). It also explores the roles of key molecular pathways, including Wnt, Notch, BMP, NF-kappa B, VEGF, cAMP, PI3K-Akt, ECM, cell adhesion, Hedgehog, MAPK, Ras, JAK-STAT, TGF-β, mTOR, melanogenesis, FoxO, Hippo, and Rap1 signaling. Understanding these intricate molecular cascades provides valuable insights into the mechanisms orchestrating hair follicle growth, further advancing the biology of this coveted natural fiber. Expanding multi-omics approaches will enhance breeding precision and deepen our understanding of molecular pathways influencing cashmere production. Future research should address critical gaps, such as the impact of environmental factors, epigenetic modifications, and functional studies of genetic variants. Collaboration among breeders, researchers, and policymakers is essential for translating genomic advancements into practical applications. Such efforts can promote sustainable practices, conserve biodiversity, and ensure the long-term viability of high-quality cashmere production. Aligning genetic insights with conservation strategies will support the sustainable growth of the cashmere industry while preserving its economic and ecological value.

Milk production traits in sheep are influenced by complex genetic factors, and understanding these traits requires the identification of candidate genes under selection. This study employed two methods, FST and XP-EHH, to identify selection signatures and candidate genes associated with milk production traits in sheep. For this purpose, 9 different breeds from the Sheep HapMap dataset generated by the International Sheep Genomics Consortium (ISGC) based on analysis of the Ovine SNP50 BeadChip were used. The dairy breeds included Brown East Friesian (n = 39), Milk Lacaune (n = 103), Chios (n = 23), Churra (n = 120), and Comisana (n = 24), while the non-dairy breeds included Afshari (n = 37), Moghani (n = 34), Galway (n = 49), and Australian Suffolk (n = 109). Genomic regions in the top 0.1 percentile of FST values revealed 71 genes, while regions with the highest positive XP-EHH values identified 69 genes. Five overlapping genes-DHRS3, TNFRSF1B, AADACL4, ARHGEF11, and LRRC71-were detected by both methods, highlighting their relevance to milk production. Several candidate genes in regions identified from FST, such as PER2, SH3PXD2A, TMEM117, DDX6, PDCD11, CALHM2, and CALHM3, have been previously associated with milk production traits. Notably, CRABP2, PEAR1, PGM1, ALG6, COX15, and OAT were identified in regions with high XP-EHH values in the dairy group. Gene ontology analysis indicated that the identified genes are enriched in pathways related to chemokine receptor activity, gap junction channel activity, and gap junction-mediated intercellular transport, as well as cellular components like the connexin complex. Further studies on these genes may improve understanding of the genetic architecture of milk production traits in sheep.

Research infrastructure is critical for advancing knowledge of health and disease, fostering innovation through world-class, cutting-edge facilities and technical expertise. Phenomics Australia is Australia's national research infrastructure provider responsible for accelerating advances in mammalian functional genomics and precision medicine through the development and delivery of services and expertise in engineered disease model production, phenotyping, and biobanking. These capabilities and resources are enabled by Australia's National Collaborative Research Infrastructure Strategy and primarily support health and medical research for significant healthcare and economic benefits. Priorities identified in the Australian Government's 2021 National Research Infrastructure Roadmap include the development and expansion of capabilities in digital research infrastructure, improved research translation, and enhanced management of biological collections, which are strongly aligned with Phenomics Australia's strategy to develop and enable access to high-quality national genetics resources at scale. Here, we comment on Phenomics Australia's response to these national strategy imperatives and the critical role of preclinical biological models research infrastructure in Australia.

CTNNB1 syndrome is a rare neurodevelopmental disorder, affecting children worldwide with a prevalence of 2.6-3.2 per 100,000 births and often misdiagnosed as cerebral palsy. De novo loss-of-function mutations in the Ctnnb1 gene result in dysfunction of the β-catenin protein, disrupting the canonical Wnt signaling pathway, which plays a key role in cell proliferation, differentiation, and tissue homeostasis. Additionally, these mutations impair the formation of cell junctions, adversely affecting tissue architecture. Motor and speech deficits, cognitive impairment, cardiovascular and visual problems are just some of the key symptoms that occur in CTNNB1 syndrome patients. There is currently no effective treatment option available for patients with CTNNB1 syndrome, with support largely focused on the management of symptoms and physiotherapy, yet recently some therapeutic approaches are being developed. Animal testing is still crucial in the process of new drug development, and mouse models are particularly important. These models provide researchers with new understanding of the disease mechanisms and are invaluable for testing the efficacy and safety of potential treatments. The development of various mouse models with β-catenin loss- and gain-of-function mutations successfully replicates key features of intellectual disability, autism-like behaviors, motor deficits, and more. These models provide a valuable platform for studying disease mechanisms and offer a powerful tool for testing the therapeutic potential and effectiveness of new drug candidates, paving the way for future clinical trials.

Type 2 diabetes mellitus (T2D) in male KK-A^y and B6-A^y mice is typically associated with hyperinsulinemia, whereas male DDD-A^y mice exhibit a marked decrease in circulating insulin levels due to the loss of pancreatic islet β-cells. T2D in male DDD-A^y mice is linked to Nidd/DDD, a significant quantitative trait locus (QTL) mapped with a 95% confidence interval (CI) between 112.44 and 151.47 Mbp on chromosome 4. Several T2D QTLs involving Nidd/SJL and Nidd/DBA have been identified on this chromosome; however, their allelic relationships remain unclear. In this study, two sets of male F₂-A^y mice produced by crossing C57BL/6J and DDD-A^y mice, and C3H/HeJ and DDD-A^y mice, were used to narrow the 95% CI of the Nidd/DDD to a 9.4 Mbp interval between 114.65 and 125.05 Mbp. Candidate genes underlying Nidd/DDD were identified, assuming that the causative variant is a nonsynonymous single nucleotide variant (nsSNV). The analysis identified 48 potential candidate nsSNVs unique to DDD-A^y mice compared to those in KK, B6, C3H, and DBA mice. Among these nsSNVs, 18 were identified in olfactory receptor genes, which have recently been implicated in the pathogenesis of T2D. The 9.4 Mbp region also contained Zfp69, a potential causative gene for Nidd/SJL, suggesting that Nidd/DDD could be allelic to Nidd/SJL but not to Nidd/DBA. In summary, the findings of this study provide insights into the allelic relationships between T2D QTLs on murine chromosome 4 and their underlying causative genetic variations.

This study aimed to identify splicing quantitative trait loci (cis-sQTL) in Nelore cattle muscle tissue and explore the involvement of spliced genes (sGenes) in immune system-related biological processes. Genotypic data from 80 intact male Nelore cattle were obtained using SNP-Chip technology, while RNA-Seq analysis was performed to measure gene expression levels, enabling the integration of genomic and transcriptomic datasets. The normalized expression levels of spliced transcripts were associated with single nucleotide polymorphisms (SNPs) through an analysis of variance using an additive linear model with the MatrixEQTL package. A permutation analysis then assessed the significance of the best SNPs for each spliced transcript. Functional enrichment analysis was performed on the sGenes to investigate their roles in the immune system. In total, 3,187 variants were linked to 3,202 spliced transcripts, with 83 sGenes involved in immune system processes. Of these, 31 sGenes were enriched for five transcription factors. Most cis-sQTL effects were found in intronic regions, with 27 sQTL variants associated with disease susceptibility and resistance in cattle. Key sGenes identified, such as GSDMA, NLRP6, CASP6, GZMA, CASP4, CASP1, TREM2, NLRP1, and NAIP, were related to inflammasome formation and pyroptosis. Additionally, genes like PIDD1, OPTN, NFKBIB, STAT1, TNIP3, and TREM2 were involved in regulating the NF-kB pathway. These findings lay the groundwork for breeding disease-resistant cattle and enhance our understanding of genetic mechanisms in immune responses.