Goats have achieved global prominence as essential livestock since their initial domestication, primarily owing to their remarkable adaptability to diverse environmental and production systems. Differential selection pressures influenced by climate have led to variations in their physical attributes, leaving genetic imprints within the genomes of goat breeds raised in diverse agroecological settings. In light of this, our study pursued a comprehensive analysis, merging environmental data with single nucleotide polymorphism (SNP) variations, to unearth indications of selection shaped by climate-mediated forces in goats. Through the examination of 43,300 SNPs from 51 indigenous goat breeds adapting to different climatic conditions using four analytical methods: latent factor mixed models (LFMM), F-statistics (Fst), Extended haplotype homozygosity across populations (XPEHH), and spatial analysis method (SAM), A total of 74 genes were revealed to display clear signs of selection, which are believed to be influenced by climatic conditions. Among these genes, 32 were consistently identified by at least two of the applied methods, and three genes (DENND1A, PLCB1, and ITPR2) were confirmed by all four approaches. Moreover, our investigation yielded 148 Gene Ontology (GO) terms based on these 74 genes, underlining pivotal biological pathways crucial for environmental adaptation. These pathways encompass functions like vascular smooth muscle contraction, cellular response to heat, GTPase regulator activity, rhythmic processes, and responses to temperature stimuli. Of significance, GO terms about endocrine regulation and energy metabolic responses, key for local adaptation were also uncovered, including biological processes, such as cell differentiation, regulation of peptide hormone secretion, and lipid metabolism. These findings contribute to our knowledge of the genetic structure of climate-triggered adaptation across the goat genome and have practical implications for marker-assisted breeding in goats.

Dairy goats, a livestock species with a long history of milk production, are essential for the economic advancement of nations, particularly in regions experiencing growth. In this study, we gathered whole-genome resequencing data of 58 goats, including 34 dairy goats and 24 wild goats (Bezoar), to explore the selection signatures linked to milk production traits using ROH (Runs of homozygosity), CLR (composite likelihood ratio), Fst (Fixation index), XP-EHH (Ex-tended haplotype homozygosity across populations) and XP-CLR(Cross-population composite likelihood ratio test) methods. Analysis of five tests of selection signatures for dairy goats revealed a total of 210 genes, with 24 genes consistently identified in at least two approaches. These genes are associated with milk fat, milk protein, and fat yield. Gene enrichment analysis highlighted important GO and KEGG pathways related to milk production, such as the “acyl-CoA metabolic process”, “glycerolipid biosynthetic process”, “cellular response to fatty ac-id”, “hormone metabolic process”, “Galactose metabolism”. Additionally, genes linked to repro-duction, immune response, and environmental adaptation were identified in dairy goats. The findings from our study offer profound understanding into the critical economic features of dairy goats and offer practical guidance for the improvement and development of crossbreeding initiatives across different dairy goat breeds.

Understanding the genomic characteristics of livestock is crucial for improving breeding efficiency and conservation efforts. However, there is a relative lack of information on the genetic makeup of local goat breeds in Henan, China. In this study, we identified runs of homozygosity (ROH), genomic inbreeding coefficients (FROH), and selection signatures in four breeds including Funiu White (FNW), Huai (HG), Lushan Bullleg (LS), and Taihang black (THB). The genomic analysis utilized a dataset of 46,278 SNP markers and 102 animals. A total of 342, 567, 1285, and 180 ROH segments were detected in FNW, HG, LS, and THB, respectively, with an average of 15.55, 29.84, 32.95, and 8.18 segments per individual. The lengths of ROH segments varied from 69.36 Mb in THB to 417.06 Mb in LS, with the most common lengths being 2-4 Mb and 4-8 Mb. The highest number of longest ROH segments (> 16 Mb) were found in LS (328) and the highest average FROH value was observed in LS (0.173), followed by HG (0.128), while the lowest FROH values were in THB (0.029) and FNW (0.070). Furthermore, the analysis of ROH islands and Composite Likelihood Ratio (CLR) identified a total of 175 significant genes. Among these, 25 genes were found to overlap, detected by both methods. These genes were associated with a diverse range of traits including reproductive ability (GPRIN3), weight (CCSER1), immune response (HERC5 and TIGD2), embryo development (NAP1L5), environmental adaptation (KLHL3, TRHDE, and IFNGR1), and milk characteristics (FAM13A). Significant Gene Ontology (GO) terms related to embryo skeletal system morphogenesis, brain ventricle development, and growth were also identified. This study helps reveal the genetic architecture of Henan goat breeds and provides valuable insights for the effective conservation and breeding programs of local goat breeds in Henan.

Despite much attention on the history of goat evolution, information on origin, demographic history, and expansion route remains controversial. To address these questions, we collected 4,189 published goat DNA sequences including 1,228 sequences from 57 breeds in China and 2,961 sequences including 193 goat breeds from 71 other countries and carried out an integrated analysis. We found goat breeds from South China had the highest genetic diversity of lineage B, and subclades B2 only were found in Southwest China, suggesting that lineage B (particularly, subclade B2) probably originated from Southwest China and its surrounding areas. In addition, in this study, we found that lineage A from South China also presented higher genetic diversity and earlier expansion time (10, 606 years ago), even earlier than breeds from the Middle East. Hence, we speculated that South China and surrounding areas were the origin of lineage B and also the transportation hub for lineage A spreading to North China and Southwest Asia. Furthermore, according to the analysis of correlation between genetic differentiation value λ1 and λ2 and geographical distance, we further confirmed two phases of migration in goat breeds of North China. These results will contribute to a better understanding of the origin and migration history of domestic goat.

Background Recent studies have identified the presence of cancer-associated fibroblasts (CAFs) within glioblastoma (GBM), yet their biological roles and underlying mechanisms remain poorly understood. This study aimed to construct a CAF-related prognostic model to guide patient prognosis and treatment strategies. Method We employed various bioinformatics methods, including enrichment analysis, Weighted Gene Co-expression Network Analysis (WGCNA), Lasso regression analysis, and machine learning techniques such as XGBoost and Random Forest, to develop a novel risk index termed CAFscore. Patients were stratified into high and low CAFscore groups for subsequent survival analysis. The area under the curve (AUC) and concordance index (C-index) for CAFscore were calculated and compared against other clinical characteristics and existing prognostic models. Drug sensitivity assessments were conducted using the Oncopredict package. Functional validation of key genes was performed through scratch and invasion assays in GBM cells. Results Our analyses revealed four core CAF-related genes, leading to the establishment of CAFscore. Notably, patients in the high CAFscore group exhibited significantly reduced survival and exhibited enrichment in epithelial-mesenchymal transition (EMT) and inflammation response pathways. Furthermore, CAFscore showed a significant negative correlation with the sensitivity to irinotecan and its analogs, while demonstrating a positive correlation with sensitivity to 505,124 (a TGFβRI inhibitor). LRP10 emerged as a central gene within the CAFscore, displaying markedly elevated expression in GBM and a strong association with CAF infiltration. Silencing LRP10 significantly inhibited the invasive capabilities of GBM cells. Conclusion This study presented the first CAF related prognostic model (CAFscore) in GBM, and demonstrated that the model could effectively guide patient prognosis and potentially inform personalized treatment strategies. The core gene of CAFscore, LRP10, was significantly overexpressed in GBM and might play a pivotal role in regulating CAF infiltration as well as tumor invasion and metastasis, highlighting LRP10 as a promising therapeutic target for GBM management.

Background: Sheep (Ovis aries) tail fat serves as a crucial energy reserve for adapting to harsh environments. However, excessive deposition can reduce farming efficiency and product quality. Elucidating the regulatory mechanisms of tail fat deposition is of great significance for genetic improvement in sheep. Methods: In this study, transcriptome sequencing was conducted on tail fat tissues from fat-tailed Kazakh sheep (KAZ), thin-tailed Suffolk sheep (SFK), and their F2 hybrid sheep (CSH) (3 individuals per group). Subsequently, qRT-PCR validation, Enrichr, and KEGG database analyses were performed to investigate the molecular pathways involved in tail fat deposition. Results: High-quality clean reads were obtained from sequencing, with a genome alignment rate ranging from 76.15% to 79.43% and good data reproducibility. Differential expression analysis revealed multiple differentially expressed genes (DEGs) between KAZ and CSH groups, KAZ and SFK groups, as well as SFK and CSH groups. Five core candidate genes (BDH1, EPHX1, BCAT2, FASN, ACACA) were identified, all enriched in the fatty acid synthesis pathway and highly expressed in fat-tailed sheep, which was confirmed by qRT-PCR. Additionally, 189 lncRNAs were identified to collectively regulate target genes (e.g., FABP family, AGPAT2), along with three common differentially expressed miRNAs (novel_120, novel_171, novel_440) targeting genes enriched in lipid transport and lipid droplet formation pathways. Conclusions: This study confirms that the lncRNA-mRNA-miRNA regulatory axis is a key pathway in tail fat formation, providing important theoretical support and molecular targets for genetic improvement of ovine tail fat deposition traits.