Even before genome sequencing, genetic resources have supported species management and breeding programs. Current technologies, such as long-read sequencing, resolve complex genomic regions, like those rich in repeats or high in GC content. Improved genome contiguity enhances accuracy in identifying structural variants (SVs) and transposable elements (TEs). We present an improved genome assembly and SV catalogue for the Australasian snapper (Chrysophrys auratus). The new assembly is more contiguous, allowing for putative identification of 14 centromeres and transfer of 26,115 gene annotations from yellowfin seabream. Compared to the previous assembly, 35,000 additional SVs, including larger and more complex rearrangements, were annotated. SVs and TEs exhibit a distribution pattern skewed towards chromosome ends, likely influenced by recombination. Some SVs overlap with growth-related genes, underscoring their significance. This upgraded genome serves as a foundation for studying natural and artificial selection, offers a reference for related species, and sheds light on genome dynamics shaped by evolution.
Ketosis—a metabolic state characterized by elevated levels of ketone bodies in the blood or urine—reduces the performance and health of dairy cows and causes substantial economic losses for the dairy industry. Currently, beta-hydroxybutyric acid is the gold standard for determining ketosis in cows; however, as this method is only applicable postpartum, it is not conducive to the early intervention of ketosis in dairy cows. In this study, the sera of dry, periparturient, postpartum ketotic, and healthy cows were analyzed by both transcriptomics and metabolomics techniques. Moreover, changes of gene expression and metabolites were observed, and serum physiological and biochemical indexes were detected by ELISA. The purpose was to screen biomarkers that can be used to detect the incidence of dry or periparturient ketosis in cows. The results showed that ketotic cows had increased levels of glycolipid metabolism indexes, oxidizing factors, and inflammatory factors during dry periods and liver damage, which could be used as early biomarkers to predict the onset of ketosis. Transcriptomic results yielded 20 differentially expressed genes (DEGs) between ketotic and healthy cows during dry, peripartum, and postpartum periods. GO and KEGG enrichment analyses indicated that these DEGs were involved in amino acid metabolism, energy metabolism, and disease-related signaling pathways. The metabolomics sequencing results showed that ketotic cows mainly showed enrichment in tricarboxylic acid cycle, butyric acid metabolism, carbon metabolism, lysine degradation, fatty acid degradation, and other signaling pathways. Metabolites differed between ketotic and healthy cows in dry, pre-parturition, and post-parturition periods. Combined transcriptomics and metabolomics analyses identified significant enrichment in the glucagon signaling pathway and the lysine degradation signaling pathway in dry, periparturient, and postpartum ketotic cows. PRKAB2 and SETMAR—key DEGs of the glucagon signaling pathway and lysine degradation signaling pathway, respectively—can be used as key marker genes for determining the early onset of ketosis in dairy cows.
Patients with lung adenocarcinoma (LUAD) generally have poor prognosis. The role of striatin-interacting protein 2 (STRIP2) in LUAD remain unclear.
Liquid chromatography-mass spectrometry analyses were used to screen the STRIP2-binding proteins and co-immunoprecipitation verified these interactions. A dual luciferase reporter assay explored the transcription factor activating STRIP2 transcription. Xenograft and lung metastasis models assessed STRIP2's role in tumor growth and metastasis in vivo.
STRIP2 is highly expressed in LUAD tissues and is linked to poor prognosis. STRIP2 expression in LUAD cells significantly promoted cell proliferation, invasion, and migration in vitro and in vivo. Mechanistically, STRIP2 boosted the PI3K/AKT/mTOR/MYC cascades by binding AKT. In addition, specificity protein 1, potently activated STRIP2 transcription by binding to the STRIP2 promoter. Blocking STRIP2 reduces tumor growth and lung metastasis in xenograft models.
Our study identifies STRIP2 is a key driver of LUAD progression and a potential therapeutic target.