Mammalian Genome最新文献

We analyzed the International Mouse Phenotyping Consortium (IMPC) release 19 set of 8,539 phenotyped whole-gene knockouts to identify 204 genes that alter vertebral anatomy and development. These genes are broadly grouped into six categories based on their phenotype: "vertebral number" (22 genes); "vertebral processes" (35 genes); "spine shape" (16 genes); "tail morphology" (73 genes); "vertebral form" (62 genes); and "somitogenesis" (24 genes), with minimal overlap between groups. Gene expression analysis of somite trios across six developmental stages show that 182 of these genes are expressed in somites, and 60% of them show variable expression during somite maturation. A further 54% show expression changes between developmental stages. Fourteen of the 204 genes affecting vertebral anatomy have a vertebral phenotype as their only phenotype, and for 34 genes vertebral phenotypes represent ≥ 50% of their total phenotypes. We find no evidence for a previous association of the majority of these genes with vertebral defects, and have therefore identified an extensive set of novel candidate genes for association with vertebral malformations in humans, including vertebral fusions, numerical variation, and scoliosis.

Cervical cancer (CC) remains a significant global health burden despite advances in prevention and screening. Emerging evidence highlights the critical role of long non-coding RNAs (lncRNAs) and RNA modifications in tumorigenesis. Here, we identified LINC01094 as a highly expressed lncRNA in CC through TCGA analysis and clinical specimens. Functional studies, including CCK-8 method, flow cytometry, Transwell and Western blot assays, demonstrated that LINC01094 knockdown suppressed cell proliferation, migration, and epithelial-mesenchymal transition while promoting apoptosis in CC cells (Caski and SiHa). Mechanistically, NSUN2-mediated 5-methylcytosine methylation stabilized LINC01094, enhancing its expression in CC. Furthermore, LINC01094 facilitated ZNF582-dependent transcriptional activation of SIRT1, promoted the deacetylation and degradation of p53. Rescue experiments confirmed that ectopic expression of either LINC01094 or SIRT1 reversed the tumor-suppressive effects of NSUN2 or LINC01094 knockdown, respectively. Collectively, NSUN2-mediated stabilization of LINC01094 upregulated SIRT1 expression, thereby suppressing the p53 pathway and accelerating CC progression. These findings uncover a novel NSUN2/LINC01094/SIRT1 axis as an epigenetic-transcriptional driver of CC, offering potential therapeutic targets.

This study aimed to identify candidate genes related to birth weight (BW), live weight at 90th day (90-LW), and lactation milk yield (LMY) in Hair (HAI), Honamlı (HNM), and Kabakulak (KBK) goats, providing a genome-wide basis for further selection strategies. The genome-wide efficient mixed model association approach was assessed with 309.342 bi-allelic single nucleotide polymorphisms (SNPs) across 481 animals to detect significant variants and their corresponding genomic regions. False discovery rate (FDR) correction and suggestive significance threshold were applied to identify SNPs having direct and potential effects on traits of interest, respectively. A total of 138 outlier SNPs (20 in HNM, 47 in HAI, and 71 in KBK) exceeded suggestive significance, of which 12 SNPs were identified to meet Benjamini-Hochberg's FDR criterion, suggesting that the overlapped protein-coding genes directly influence the phenotypic traits of interest. This approach revealed that the ID4 and CXCR4 genes directly affect BW and LMY traits in HNM goats, whereas no significant associations were observed regarding these traits in HAI and KBK goats. Additionally, a total of 8 protein-coding genes were identified to directly influence the 90-LW trait in HAI (MFSD1, CHMP4C, and MAP1B) and KBK (IGSF21, RALY, ZNF507, SLC38A10, and PGBD5) goats. The remaining 126 suggestive SNPs, on the other hand, either overlapped or were located near 103 protein-coding genes, indicating their potential effects on growth and milk yield. Both direct and potential protein-coding genes identified in this study seem promising for designing comprehensive selection strategies to improve growth and milk traits in Anatolian goats.

Mouse models have played a critical role in complementing human genetics research due to their genetic similarity to humans and well-annotated and tractable genome. For over 15 years, the Diversity Outbred (DO) mice have existed as a powerful tool for mapping complex traits. With eight founder strains contributing to high levels of genetic diversity, heterozygosity, and large numbers of recombination events, DO mice allow for high-resolution genetic mapping. DO mice have been used to dissect the genetic architecture of physiological traits like blood lipids, behavioral traits such as cocaine self-administration, and molecular phenotypes such as gene expression across various tissues. Here we aim to exhaustively catalog DO mouse studies over the last 15 years, including both mapping and non-mapping studies, as well as to provide an overview of software tools and online resources related to the model.

Indigenous cattle account for approximately 80% of Uganda's cattle population. These animals are well adapted to the country's ten agroecological zones and are mainly kept under pastoral and agropastoral systems. Unlike commercial breeds, they thrive on low-quality feeds, while tolerating major tropical diseases and parasites including tsetse flies, ticks, and vector-borne infections. Whole-genome sequence (WGS) analysis offers opportunities to uncover genomic regions underlying these adaptations and to trace the genetic footprints of long-term breeding decisions taken by cattle keepers. In this study, WGS data from 95 animals representing six indigenous cattle populations (Ankole, Karamojong, Nganda10, Nganda17, Nkedi, and Ntuku) were analyzed to identify genomic regions under putative selection. Two complementary approaches were applied: enumeration of the µ-statistic in RAiSD and runs of homozygosity (ROH) analysis. RAiSD identified population-level signals, while conserved ROH regions were defined using breed-specific SNP-incidence thresholds. The two methods identified 803 and 49 candidate genes respectively. The top genes identified included SLC37A1 (BTA1), CHCHD3 (BTA4), and RAB3GAP1 (BTA2) detected by RAiSD, and IL26 (BTA5), FBXL7 (BTA20), and HSPA9 (BTA7) contained in ROH. Furthermore, the regions harbored 107 novel genes (92 detected by RAiSD and 15 by ROH), corresponding to 255 quantitative trait loci. The identified genes under putative selection are associated with economically important traits including adaptation to tropical environments, resistance to parasites and diseases, and other farmer-preferred characteristics. These findings provide insights into the genetic basis of adaptation, selection and production in Ugandan indigenous cattle, supporting conservation and breeding strategies to enhance resilience and productivity.

Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are major public health challenges lacking effective therapies. To identify potential drug targets, we integrated large-scale genome-wide association studies with expression, methylation, protein, and splicing QTL datasets using Mendelian Randomization (MR) and summary-data-based MR (SMR). Colocalization analysis and machine learning were applied to prioritize candidate genes, followed by in silico druggability evaluation through molecular docking and molecular dynamics (MD) simulations. In animal models, candidate genes identified by transcriptomic analysis were further validated using integrative molecular and functional experiments. We identified several genes with potential causal links to AD (e.g., IQCE, HDHD2, ALPP) and PD (e.g., IL15, STK3, CHRNB1). Transcriptomic analyses indicated a consistent downregulation of IL-15 in PD model mice, corroborated by subsequent Western blot and immunohistochemical validation. Among predicted compounds, Prednisolone (ALPP), Sirolimus (IL15), and CHEMBL379975 (STK3) showed favorable binding affinities and stable MD trajectories, suggesting promising therapeutic relevance. Collectively, these findings highlight 12 QTL-regulated genes as promising molecular targets for further investigation in the context of NDDs. While the computational results provide a useful basis for hypothesis generation, experimental validation will be essential to determine the biological relevance and therapeutic potential of these candidate genes and compounds.