Mammalian Genome最新文献

Prostatitis represents a common disease of the male genitourinary system, significantly impacting the physical and mental health of male patients. While numerous studies have suggested a potential link between immune cell activity and prostatitis, the exact causal role of immune cells in prostatitis remains uncertain. This study aims to explore the causal relationship between immune cell characteristics and prostatitis using a bidirectional Mendelian randomization approach. This study utilizes data from the public GWAS database and employs bidirectional Mendelian randomization analysis to investigate the causal relationship between immune cells and prostatitis. The causal relationship between 731 immune cell features and prostatitis was primarily investigated through inverse variance weighting (IVW), complemented by MR-Egger regression, a simple model, the weighted median method, and a weighted model. Ultimately, the results underwent sensitivity analysis to assess the heterogeneity, horizontal pleiotropy, and stability of Single Nucleotide Polymorphisms (SNPs) in immune cells and prostatitis. MR analysis revealed 17 immune cells exhibiting significant causal effects on prostatitis. In contrast, findings from reverse MR indicated a significant causal relationship between prostatitis and 13 immune cells. Our study utilizes bidirectional Mendelian Randomization to establish causal relationships between specific immune cell phenotypes and prostatitis, highlighting the reciprocal influence between immune system behavior and the disease. Our findings suggest targeted therapeutic approaches and the importance of including diverse populations for broader validation and personalized treatment strategies.

The demographic history of human populations in North Africa has been characterized by complex migration processes that have determined the current genetic structure of these populations. We examined the autosomal markers of eight sampled populations in northern Africa (Tunisia and Libya) to explore their genetic structure and to place them in a global context. We genotyped a set of 30 autosomal single-nucleotide polymorphisms (SNPs) extending 9.5 Mb and encompassing the 17q21 inversion region. Our data include 403 individuals from Tunisia and Libya. To put our populations in the global context, we analyzed our data in comparison with other populations, including those of the 1000 Genomes Project. To evaluate the data, we conducted genetic diversity, principal component, STRUCTURE, and haplotype analyses. The analysis of genetic composition revealed the genetic heterogeneity of North African populations. The principal component and STRUCTURE analyses converged and revealed the intermediate position of North Africans between Europeans and Asians. Haplotypic analysis demonstrated that the normal (H1) and inverted (H2) polymorphisms in the chromosome 17q21 region occur in North Africa at frequencies similar to those found in European and Southwest Asian populations. The results highlight the complex demographic history of North Africa, reflecting the influence of genetic flow from Europe and the Near East that dates to the prehistoric period. These gene flows added to demographic factors (inbreeding, endogamy), natural factors (topography, Sahara), and cultural factors that play a role in the emergence of the diverse and heterogeneous genetic structures of North African populations. This study contributes to a better understanding of the complex structure of North African populations.

Ancient DNA provides a unique frame for directly studying human population genetics in time and space. Still, since most of the ancient genomic data is low coverage, analysis is confronted with a low number of SNPs, genotype uncertainties, and reference-bias. Here, we for the first time benchmark the two distinct versions of Glimpse tools on 120 ancient human genomes from Eurasia including those largely from previously under-evaluated regions and compare the performance of genotype imputation with de facto analysis approaches for low coverage genomic data analysis. We further investigate the impact of two distinct reference panels on imputation accuracy for low coverage genomic data. We compute accuracy statistics and perform PCA and f₄-statistics to explore the behaviour of genotype imputation on low coverage data regarding (i)two versions of Glimpse, (ii)two reference panels, (iii)four post-imputation filters and coverages, as well as (iv)data type and geographical origin of the samples on the analyses. Our results reveal that even for 0.1X coverage ancient human genomes, genotype imputation using Glimpse-v2 is suitable. Additionally, using the 1000 Genomes merged with Human Genome Diversity Panel improves the accuracy of imputation for the rare variants with low MAF, which might be important not only for ancient genomics but also for modern human genomic studies based on low coverage data and for haplotype-based analysis. Most importantly, we reveal that genotype imputation of low coverage ancient human genomes reduces the genetic affinity of the samples towards human reference genome. Through solving one of the most challenging biases in data analysis, so-called reference bias, genotype imputation using Glimpse v2 is promising for low coverage ancient human genomic data analysis and for rare-variant-based and haplotype-based analysis.

The incidence of osteoporosis has rapidly increased owing to the ageing population. Cuproptosis, a novel mechanism that regulates cell death, may be a new therapeutic approach. However, the relevance of cuproptosis in the immune microenvironment and osteoporosis immunotherapy is still unknown. We intersected the differentially expressed genes from osteoporotic samples with 75 cuproptosis-related genes to identify 16 significantly expressed cuproptosis genes. We further explored the connection between the cuproptosis pattern, immune microenvironment, and immunotherapy. The weighted gene co-expression network analysis algorithm was used to identify cuproptosis phenotype-associated genes, and we used quantitative real-time PCR and immunohistochemistry in mouse femur tissues to verify hub gene (MAP2K2, FDX1, COX19, VEGFA, CDKN2A, and NFE2L2) expression. Six hub genes and 59 cuproptosis phenotype-associated genes involved in immunisation were identified among the osteoporosis and control groups, and the majority of these 59 genes were enriched in the inflammatory response, as well as in signal transducers, Janus kinase, and transcription pathway activators. In addition, two different clusters of cuproptosis were found, and immune infiltration analysis showed that gene Cluster 1 had a greater immune score and immune infiltration level. Further analysis revealed that three key genes (COX19, MAP2K2, and FDX1) were highly correlated with immune cell infiltration, and external experiments validated the association of these three genes with the prognosis of osteoporosis. We used the three key mRNAs COX19, MAP2K2, and FDX1 as a classification model that may systematically elucidate the complex connection between cuproptosis and the immune microenvironment of osteoporosis. New insights into osteoporosis pathogenesis and immunotherapy prospects may be gained from this study.

The analysis of alterations in the expression and functionality of brain-derived exosomal miRNAs within ischemic stroke lesions provides significant insights into the mechanisms that contribute to disease recovery. We assessed spontaneous motor function in a rat model of permanent middle cerebral artery occlusion (pMCAO) using motor function scores and magnetic resonance imaging (MRI). Brain-derived exosomes from the infarcted brain tissue of the animal model were extracted and high-throughput sequencing of them was performed followed by bioinformatics analysis for differentially expressed miRNAs target genes. Real-time quantitative polymerase chain reaction (qRT-PCR) was used to measure expression levels of differentially expressed miRNAs at various time points. The oxygen-glucose deprivation (OGD) model was established to investigate gene function through the assessment of cell proliferation and apoptosis using EdU proliferation and JC-1 apoptosis assay. The rat model demonstrated a spontaneous recovery of motor function and a reduction in cerebral infarction area from day 1 to day 14 post-operation. Over the course of the recovery period, miR-24-3p, miR-129-1-3p, and miR-212-5p maintained consistent expression levels, reaching their peak on the initial day following surgery. In the cell model, EdU detection indicated that miR-129-1-3p promoted cellular proliferation, while JC-1 detection revealed its suppressive impact on cellular apoptosis. The current research findings indicated the presence of spontaneous motor function restoration in a rat model of ischemic stroke. MiR-24-3p, miR-129-1-3p, and miR-212-5p were identified as pivotal genes in this recovery process, with miR-129-1-3p potentially influencing the restoration of spontaneous motor function in ischemic stroke through the regulation of neuronal proliferation and apoptosis.

MicroRNAs (miRNAs) act as key gene expression regulators, influencing intracellular biological and pathological processes. They are of significant interest in animal genetics as potential biomarkers for animal selection and health. This study aimed to unravel the complex miRNA signature involved in mastitis in in vitro cell culture. For this purpose, we constructed a control and treatment model in ovarian mammary epithelial cells to analyze miRNA responses upon Staphylococcus aureus (S. aureus) stimulation. The high-throughput Illumina Small RNA protocol was employed, generating an average of 7.75 million single-end reads per sample, totaling 46.54 million reads. Standard bioinformatics analysis, including cleaning, filtering, miRNA quantification, and differential expression was performed using the miRbase database as a reference for ovine miRNAs. The results indicated differential expression of 63 miRNAs, including 33 up-regulated and 30 down-regulated compared to the control group. Notably, miR-10a, miR-10b, miR-21, and miR-99a displayed a significant differential expression (p ≤ 0.05) associated to signal transduction, transcriptional pathways, diseases of signal transduction by growth factor receptors and second messengers, MAPK signaling pathway, NF-κB pathway, TNFα, Toll Like Receptor 4 (TLR4) cascade, and breast cancer. This study contributes expanding miRNA databases, especially for sheep miRNAs, and identifies potential miRNA candidates for further study in biomarker identification for mastitis resistance and diagnosis.

The goal of systems biology is to gain a network level understanding of how gene interactions influence biological states, and ultimately inform upon human disease. Given the scale and scope of systems biology studies, resource constraints often limit researchers when validating genome-wide phenomena and potentially lead to an incomplete understanding of the underlying mechanisms. Further, prioritization strategies are often biased towards known entities (e.g. previously studied genes/proteins with commercially available reagents), and other technical issues that limit experimental breadth. Here, heterogeneous biological information is modeled as an association graph to which a high-performance minimum dominating set solver is applied to maximize coverage across the graph, and thus increase the breadth of experimentation. First, we tested our model on retrieval of existing gene functional annotations and demonstrated that minimum dominating set returns more diverse terms when compared to other computational methods. Next, we utilized our heterogenous network and minimum dominating set solver to assist in the process of identifying understudied genes to be interrogated by the International Mouse Phenotyping Consortium. Using an unbiased algorithmic strategy, poorly studied genes are prioritized from the remaining thousands of genes yet to be characterized. This method is tunable and extensible with the potential to incorporate additional user-defined prioritizing information. The minimum dominating set approach can be applied to any biological network in order to identify a tractable subset of features to test experimentally or to assist in prioritizing candidate genes associated with human disease.

This study investigates the genomic landscape of Sika deer populations, emphasizing the detection and characterization of runs of homozygosity (ROH) and their contribution towards components of fitness. Using 85,001 high-confidence SNPs, the investigation into ROH distribution unveiled nuanced patterns of autozygosity across individuals especially in 2 out of the 8 farms, exhibiting elevated ROH levels and mean genome coverage under ROH segments. The prevalence of shorter ROH segments (0.5-4 Mb) suggests historical relatedness and potential selective pressures within these populations. Intriguingly, despite observed variations in ROH profiles, the overall genomic inbreeding coefficient (F_ROH) remained relatively low across all farms, indicating a discernible degree of genetic exchange and effective mitigation of inbreeding within the studied Sika deer populations. Consensus ROH (cROH) were found to harbor genes for important functions viz., EGFLAM gene which is involved in the vision function of the eye, SKP2 gene which regulates cell cycle, CAPSL involved in adipogenesis, SPEF2 which is essential for sperm flagellar assembly, DCLK3 involved in the heat stress. This first ever study on ROH in Sika deer, to shed light on the adaptive role of genes in these homozygous regions. The insights garnered from this study have broader implications in the management of genetic diversity in this vulnerable species.

The Mouse Metabolic Phenotyping Center (MMPC)Live Program was established in 2023 by the National Institute for Diabetes, Digestive and Kidney Diseases (NIDDK) at the National Institutes of Health (NIH) to advance biomedical research by providing the scientific community with standardized, high quality phenotyping services for mouse models of diabetes and obesity. Emerging as the next iteration of the MMPC Program which served the biomedical research community for 20 years (2001-2021), MMPCLive is designed as an outwardly-facing consortium of service cores that collaborate to provide reduced-cost consultation and metabolic, physiologic, and behavioral phenotyping tests on live mice for U.S. biomedical researchers. Four MMPCLive Centers located at universities around the country perform complex and often unique procedures in vivo on a fee for service basis, typically on mice shipped from the client or directly from a repository or vendor. Current areas of expertise include energy balance and body composition, insulin action and secretion, whole body carbohydrate and lipid metabolism, cardiovascular and renal function, food intake and behavior, microbiome and xenometabolism, and metabolic pathway kinetics. Additionally, an opportunity arose to reduce barriers to access and expand the diversity of the biomedical research workforce by establishing the VIBRANT Program. Directed at researchers historically underrepresented in the biomedical sciences, VIBRANT-eligible investigators have access to testing services, travel and career development awards, expert advice and experimental design consultation, and short internships to learn test technologies. Data derived from experiments run by the Centers belongs to the researchers submitting mice for testing which can be made publicly available and accessible from the MMPCLive database following publication. In addition to services, MMPCLive staff provide expertise and advice to researchers, develop and refine test protocols, engage in outreach activities, publish scientific and technical papers, and conduct educational workshops and training sessions to aid researchers in unraveling the heterogeneity of diabetes and obesity.

Neurodegenerative diseases are incurable conditions that lead to gradual and progressive deterioration of brain function in patients. With the aging population, the prevalence of these diseases is expected to increase, posing a significant economic burden on society. Imaging techniques play a crucial role in the diagnosis and monitoring of neurodegenerative diseases. This study utilized a two-sample Mendelian randomization (MR) analysis to assess the causal relationship between different imaging-derived phenotypes (IDP) in the brain and neurodegenerative diseases. Multiple MR methods were employed to minimize bias and obtain reliable estimates of the potential causal relationship between the variable exposures of interest and the outcomes. The study found potential causal relationships between different IDPs and Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS), and frontotemporal dementia (FTD). Specifically, the study identified potential causal relationships between 2 different types of IDPs and AD, 8 different types of IDPs and PD, 11 different types of imaging-derived phenotypes and ALS, 1 type of IDP and MS, and 1 type of IDP and FTD. This study provides new insights for the prevention, diagnosis, and treatment of neurodegenerative diseases, offering important clues for understanding the pathogenesis of these diseases and developing relevant intervention strategies.