High-continuity genome assembly of the jellyfish Chrysaora quinquecirrha.

The Atlantic sea nettle ( Chrysaora quinquecirrha) has an important evolutionary position due to its high ecological value. However, due to limited sequencing technologies and complex jellyfish genomic sequences, the current C. quinquecirrha genome assembly is highly fragmented. Here, we used the most advanced high-throughput chromosome conformation capture (Hi-C) technology to obtain high-coverage sequencing data of the C. quinquecirrha genome. We then anchored these data to the previously published contig-level assembly to improve the genome. Finally, a high-continuity genome sequence of C. quinquecirrha was successfully assembled, which contained 1 882 scaffolds with a N50 length of 3.83 Mb. The N50 length of the genome assembly was 5.23 times longer than the previously released one, and additional analysis revealed that it had a high degree of genomic continuity and accuracy. Acquisition of the high-continuity genome sequence of C. quinquecirrha not only provides a basis for the study of jellyfish evolution through comparative genomics but also provides an important resource for studies on jellyfish growth and development.

Complete mitogenomes document substantial genetic contribution from the Eurasian Steppe into northern Pakistani Indo-Iranian speakers.

To elucidate whether Bronze Age population dispersals from the Eurasian Steppe to South Asia contributed to the gene pool of Indo-Iranian-speaking groups, we analyzed 19,568 mitochondrial DNA (mtDNA) sequences from northern Pakistani and surrounding populations, including 213 newly generated mitochondrial genomes (mitogenomes) from Iranian and Dardic groups, both speakers from the ancient Indo-Iranian branch in northern Pakistan. Our results showed that 23% of mtDNA lineages with west Eurasian origin arose in situ in northern Pakistan since ~5000 years ago (kya), a time depth very close to the documented Indo-European dispersals into South Asia during the Bronze Age. Together with ancient mitogenomes from western Eurasia since the Neolithic, we identified five haplogroups (~8.4% of maternal gene pool) with roots in the Steppe region and subbranches arising (age ~5-2 kya old) in northern Pakistan as genetic legacies of Indo-Iranian speakers. Some of these haplogroups, such as W3a1b that have been found in the ancient samples from the late Bronze Age to the Iron Age period individuals of Swat Valley northern Pakistan, even have sub-lineages (age ~4 kya old) in the southern subcontinent, consistent with the southward spread of Indo-Iranian languages. By showing that substantial genetic components of Indo-Iranian speakers in northern Pakistan can be traced to Bronze Age in the Steppe region, our study suggests a demographic link with the spread of Indo-Iranian languages, and further highlights the corridor role of northern Pakistan in the southward dispersal of Indo-Iranian-speaking groups.

Glycerophosphodiester phosphodiesterase 1 (GDE1) acts as a potential tumor suppressor and is a novel therapeutic target for non-mucin-producing colon adenocarcinoma.

Colon adenocarcinoma (COAD) represents a major public health issue due to its high incidence and mortality. As different histological subtypes of COAD are related to various survival outcomes and different therapies, finding specific targets and treatments for different subtypes is one of the major demands of individual disease therapy. Interestingly, as these different subtypes show distinct metabolic profiles, it may be possible to find specific targets related to histological typing by targeting COAD metabolism. In this study, the differential expression patterns of metabolism-related genes between COAD (n = 289) and adjacent normal tissue (n = 41) were analyzed by one-way ANOVA. We then used weighted gene co-expression network analysis (WGCNA) to further identify metabolism-related gene connections. To determine the critical genes related to COAD metabolism, we obtained 2,114 significantly differentially expressed genes (DEGs) and 12 modules. Among them, we found the hub module to be significantly associated with histological typing, including non-mucin-producing colon adenocarcinoma and mucin-producing colon adenocarcinoma. Combining survival analysis, we identified glycerophosphodiester phosphodiesterase 1 (GDE1) as the most significant gene associated with histological typing and prognosis. This gene displayed significantly lower expression in COAD compared with normal tissues and was significantly correlated with the prognosis of non-mucin-producing colon adenocarcinoma (p = 0.0017). Taken together, our study showed that GDE1 exhibits considerable potential as a novel therapeutic target for non-mucin-producing colon adenocarcinoma.

Weighted Gene Co-Expression Network Analysis Reveals Six Hub Genes Involved in and Tight Junction Function in Pancreatic Adenocarcinoma and their Potential Use in Prognosis.

Background: Pancreatic adenocarcinoma (PAAD) is an aggressive and invasive tumor with poor prognosis. Identifying prognostic biomarkers of PAAD will provide crucial information for developing treatment plans. Methods: In this analysis, a gene-expression dataset, containing RNA-sequencing data recalculated into transcripts per million, was obtained from the UCSC Xena platform. Three thousand nine hundred and seventy six differentially expressed genes were obtained with analysis of variance. Using these data a co-expression network was constructed using weighted gene co-expression network analysis, from which we obtained eight modules. Results: The blue module included 497 genes and demonstrated significant negative correlation with overall survival. Furthermore, pathway analyses demonstrated the involvement of many of these genes in the tight junction pathway, which plays a critical role in PAAD. In addition, we identified six genes in common (i.e., ANXA2 [annexin A2], EPHA2 [erythropoietin-producing hepatocellular class A2], ITGB4 [integrin beta 4], KRT19 [keratin type I cytoskeletal 19], LGALS3 [galectin-3], and S100A14 [S100 calcium binding protein A14]) between the protein-protein interaction and gene co-expression networks that may have critical functions in PAAD. These hub genes were not only highly expressed at the RNA level but also exhibited high expression in the immunohistological data in the Human Protein Atlas Database. Conclusion: Thus, this research clarified the framework of co-expressed gene modules in PAAD and highlighted potential prognostic biomarkers for the clinical diagnosis of PAAD.

Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA.

BACKGROUND: Adrenocortical carcinoma (ACC) is a rare and aggressive malignant cancer in the adrenal cortex with poor prognosis. Though previous research has attempted to elucidate the progression of ACC, its molecular mechanism remains poorly understood. METHODS: Gene transcripts per million (TPM) data were downloaded from the UCSC Xena database, which included ACC (The Cancer Genome Atlas, n = 77) and normal samples (Genotype Tissue Expression, n = 128). We used weighted gene co-expression network analysis to identify gene connections. Overall survival (OS) was determined using the univariate Cox model. A protein-protein interaction (PPI) network was constructed by the search tool for the retrieval of interacting genes. RESULTS: To determine the critical genes involved in ACC progression, we obtained 2,953 significantly differentially expressed genes and nine modules. Among them, the blue module demonstrated significant correlation with the "Stage" of ACC. Enrichment analysis revealed that genes in the blue module were mainly enriched in cell division, cell cycle, and DNA replication. Combined with the PPI and co-expression networks, we identified four hub genes (i.e., TOP2A, TTK, CHEK1, and CENPA) that were highly expressed in ACC and negatively correlated with OS. Thus, these identified genes may play important roles in the progression of ACC and serve as potential biomarkers for future diagnosis.