Genomics最新文献

Background

Patients with lung adenocarcinoma (LUAD) generally have poor prognosis. The role of striatin-interacting protein 2 (STRIP2) in LUAD remain unclear.

Methods

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.

Results

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.

Conclusions

Our study identifies STRIP2 is a key driver of LUAD progression and a potential therapeutic target.

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.

Dendrobium officinale is a rare and precious medicinal plant. Southern blight is a destructive disease in the artificial cultivation of D. officinale, and one of its pathogens is Sclerotium delphinii. S. delphinii is a phytopathogenic fungus with a wide host range with extremely strong pathogenicity. In this study, S. delphinii was isolated from D. officinale with southern blight. Subsequently, this specific strain underwent thorough whole-genome sequencing using the PacBio Sequel II platform, which employed single-molecule real-time (SMRT) technology. Comprehensive annotations were obtained through functional annotation of protein sequences using various publicly available databases. The genome of S. delphinii measures 73.66 Mb, with an N90 contig size of 2,707,110 bp, and it contains 18,506 putative predictive genes. This study represents the first report on the genome size assembly and annotation of S. delphinii, making it the initial species within the Sclerotium genus to undergo whole-genome sequencing, which can provide solid data and a theoretical basis for further research on the pathogenesis, omics of S. delphinii.

Background

Santalum album L. is an evergreen tree which is mainly distributes throughout tropical and temperate regions. And it has a great medicinal and economic value.

Results

In this study, the complete mitochondrial genome of S. album were assembled and annotated, which could be descried by a complex branched structure consisting of three contigs. The lengths of these three contigs are 165,122 bp, 93,430 bp and 92,491 bp. We annotated 34 genes coding for proteins (PCGs), 26 tRNA genes, and 4 rRNA genes. The analysis of repeated elements shows that there are 89 SSRs and 242 pairs of dispersed repeats in S. album mitochondrial genome. Also we found 20 MTPTs among the chloroplast and mitochondria. The 20 MTPTs sequences span a combined length of 22,353 bp, making up 15.52 % of the plastome, 6.37 % of the mitochondrial genome. Additionally, by using the Deepred-mt tool, we found 628 RNA editing sites in 34 PCGs. Moreover, significant genomic rearrangement is observed between S. album and its associated mitochondrial genomes. Finally, based on mitochondrial genome PCGs, we deduced the phylogenetic ties between S. album and other angiosperms.

Conclusions

We reported the mitochondrial genome from Santalales for the first time, which provides a crucial genetic resource for our study of the evolution of mitochondrial genome.

Breast cancer (BC) is a prevalent cancer of the female reproductive system and a major contributor to cancer-related mortality. The activation of NLRP3, a key inflammasome, has been extensively associated with tumor-related molecular and cellular processes; however, the regulatory mechanisms and specific role of NLRP3 in breast cancer remain incompletely elucidated. This study aimed to evaluate the molecular mechanisms of NLRP3-related genes in BC. Utilizing bioinformatics methods, the present research analyzed the TCGA-BRCA dataset, which included four groups of transcriptome sequencing data as follows, normal (WT), NLRP3 knockout (KO), non-knockout-BRCA (BC-WT), and NLRP3-knockout-BRCA (BC-KO). Results indicated that NLRP3 was significantly down-regulated in TCGA-BRCA. Key module genes were mainly enriched in leukocyte cell-cell adhesion and cytokine-cytokine receptor interaction. Moreover, correlation analysis showed that NLRP3 was positively associated with cancer-associated fibroblasts and negatively associated with CD4⁺ Th1 T-cells. In addition, the DEGs1 and DEGs2 overlapping indicated 505 feature genes, with Chac1 (negative) and Ugt8a (positive) had the strongest correlation with differential immune cells (class-switched memory B cells). Pathway intersection revealed 13 co-KEGG pathways. The BC-KO group indicated markedly reduced levels of four genes (Ccl19, Ccl20, Ccl21a, and H2-Oa) and increased levels of two genes (Il2ra and H2-Ob). This study delved into the role of NLRP3 in BC, exploring its regulatory mechanisms and the impact gene knockout. Bioinformatics approaches identified NLRP3-associated genes, their enriched pathways, and interactions within the tumor microenvironment (TME), providing novel insights into NLRP3 function, TME dynamics, and potential targets for BC prevention and treatment.

Prolonged alcohol consumption can disturb the expression of both coding and noncoding genes in the brain. These dysregulated genes may co-express in modules and interact within networks, consequently influencing the susceptibility to developing alcohol use disorder (AUD). In the present study, we performed an RNA-seq analysis of the expression of both long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in 192 postmortem tissue samples collected from eight brain regions (amygdala, caudate nucleus, cerebellum, hippocampus, nucleus accumbens, prefrontal cortex, putamen, and ventral tegmental area) of 12 AUD and 12 control subjects of European ancestry. Applying the limma-voom method, we detected a total of 57 lncRNAs and 51 mRNAs exhibiting significant differential expression (P_adj < 0.05 and fold-change ≥2) across at least one of the eight brain regions investigated. Machine learning analysis further confirmed the potential of these top genes in predicting AUD. Through Weighted Gene Co-expression Network Analysis (WGCNA), we identified distinct lncRNA-mRNA co-expression modules associated with AUD in each of the eight brain regions. Additionally, lncRNA-mRNA co-expression networks were constructed for each brain region using Cytoscape to reveal gene regulatory interactions implicated in AUD. Hub genes within these networks were found to be enriched in several key KEGG pathways, including Axon Guidance, MAPK Signaling, p53 Signaling, Adherens Junction, and Neurodegeneration. Our results underscore the significance of networks involving AUD-associated lncRNAs and mRNAs in modulating neuroplasticity in response to alcohol exposure. Further elucidating these molecular mechanisms holds promise for the development of targeted therapeutic interventions for AUD.