In this study we examine the impact of cell confluency on gene expression. We focused on Argonaute (AGO) protein dynamics and associated gene and protein expression in HEK293, A375, and SHSY5Y cell lines. As a consequence of cell confluency, AGO2 protein translocates into the nucleus. Therefore, we generated transcriptomic data using RNA sequencing to compare gene expression in subconfluent versus confluent cells, which highlighted significant alterations in gene regulation patterns directly corresponding to changes in cell density. Our study also encompasses miRNA profiling data obtained through small RNA sequencing, revealing miRNA expressional changes dependent on cellular confluency, as well as cellular localization. Finally, we derived proteomic data from mass spectrometry analyses following AGO1-4 immunoprecipitation, providing a comprehensive view of AGO interactome in both nuclear and cytoplasmic compartments under varying confluency. These datasets offer a detailed exploration of the cellular and molecular dynamics, influenced by cell confluency, presenting a valuable resource for further research in cellular biology, particularly in understanding the basic mechanisms of cell density in cancer cells.

Fish skin-associated microbial communities are highly variable among populations and species and can impact host fitness. Still, the sources of variation in microbiome composition, and particularly how they vary among and within host individuals, have rarely been investigated. To tackle this issue, we explored patterns of variation in fish skin microbiomes across different spatial scales. We conducted replicate sampling of dorsal and ventral body sites of perch (Perca fluviatilis) from two populations and characterized the variation of fish skin-associated microbial communities with 16S rRNA gene metabarcoding. Results showed a high similarity of microbiome samples taken from the left and right side of the same fish individuals, suggesting that fish skin microbiomes can be reliably assessed and characterized even using a single sample from a specific body site. The microbiome composition of fish skin differed markedly from the bacterioplankton communities in the surrounding water and was highly variable among individuals. No ASV was present in all samples, and the most prevalent phyla, Actinobacteria, Bacteroidetes, and Proteobacteria, varied in relative abundance among fish hosts. Microbiome composition was both individual- and population specific, with most of the variation explained by individual host. At the individual level, we found no diversification in microbiome composition between dorsal and ventral body sites, but the degree of intra-individual heterogeneity varied among individuals. To identify how genetic and phenotypic characteristics of fish hosts impact the rate and nature of intra-individual temporal dynamics of the skin microbiome, and thereby contribute to the host-specific patterns documented here, remains an important task for future research.

Using deep RNA sequencing, we have studied the expression of adenovirus-encoded small RNAs at different times after infection. Nineteen small RNAs which comprised more than 1% of the total pool of small RNAs at least one time point were identified. These small RNAs were between 25 and 35 nucleotides long and mapped in the region of the VA RNAI and RNAII genes. However, the overlap was incomplete and some contained a few extra nucleotides at the 3' end. This finding together with the observation that some of the small RNAs were detected before VA RNA expression had started might indicate that they are derived from other precursors than VA RNAI and II. Interestingly, the small RNAs displayed different expression profiles during the course of the infection suggesting that they have different functions. An effort was made to identify their mRNA targets by using computer prediction and deep cDNA sequencing. The most significant targets for the earliest small RNAs were genes involved in signaling pathways.

The chemokine receptors CCR2, CCR5, and CX3CR1 coordinate monocyte trafficking in homeostatic and inflammatory states. Multiple small human genetic studies have variably linked single nucleotide polymorphisms in these genes to cardiometabolic disease. We interrogated genome-wide association, exome sequencing, and exome array genotyping studies to ascertain the relationship between variation in these genes and coronary artery disease (CAD), myocardial infarction (MI), and glucometabolic traits. We interrogated the CARDIoGRAMplusC4D (Coronary ARtery DIsease Genome wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics) (60 801 cases and 123 504 controls), the MIGen and CARDIoGRAM Exome consortia (42 335 cases and 78 240 controls), and Exome Sequencing Project and Early-Onset Myocardial Infarction (ESP EOMI; 4703 cases and 5090 controls) data sets to ascertain the relationship between common, low frequency, and rare variation in CCR2, CCR5, or CX3CR1 with CAD and MI. We did not identify any variant associated with CAD or MI. We then explored common and low-frequency variation in South Asians through Pakistan Risk of Myocardial Infarction Study (PROMIS; 9058 cases and 8379 controls), identifying 6 variants associated with MI including CX3CR1 V249I. Finally, reanalysis of the European HapMap imputed Diabetes Genetics Replication and Meta-Analysis (DIAGRAM), Global Lipids Genetics Consortium (GLGC), Genetic Investigation of Anthropometric Traits (GIANT), and Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) data sets revealed no association with glucometabolic traits although 3 single nucleotide polymorphisms in PROMIS were associated with type II diabetes mellitus. No chemokine receptor variant was associated with CAD, MI, or glucometabolic traits in large European ancestry cohorts. In a South Asian cohort, we identified single nucleotide polymorphism associations with MI and type II diabetes mellitus but these did not meet significance in cohorts of European ancestry. These findings suggest the need for larger studies in South Asians but exclude clinically meaningful associations with CAD and glucometabolic traits in Europeans.

The potassium-chloride co-transporter KCC2, encoded by SLC12A5, plays a fundamental role in fast synaptic inhibition by maintaining a hyperpolarizing gradient for chloride ions. KCC2 dysfunction has been implicated in human epilepsy, but to date, no monogenic KCC2-related epilepsy disorders have been described. Here we show recessive loss-of-function SLC12A5 mutations in patients with a severe infantile-onset pharmacoresistant epilepsy syndrome, epilepsy of infancy with migrating focal seizures (EIMFS). Decreased KCC2 surface expression, reduced protein glycosylation and impaired chloride extrusion contribute to loss of KCC2 activity, thereby impairing normal synaptic inhibition and promoting neuronal excitability in this early-onset epileptic encephalopathy.

Targeted therapy (TT), together with immune checkpoint inhibitors (ICI), has significantly improved clinical outcomes for patients with advanced cutaneous malignant melanoma (CMM) during the last decade. However, the magnitude and the duration of response vary considerably. There is still a paucity of predictive biomarkers to identify patients who benefit most from treatment. To address this, we performed targeted transcriptomics of CMM tumors to identify biomarkers associated with clinical outcomes. Pre-treatment tumor samples from 28 patients with advanced CMM receiving TT (n = 13) or ICI (n = 15) were included in the study. Targeted RNA sequencing was performed using Ion AmpliSeq ™, followed by gene set enrichment analysis (GSEA) using MSigDB's Hallmark Gene Set Collection to identify gene expression signatures correlating with treatment outcome. The GSEA demonstrated that up-regulation of allograft rejection genes, together with down-regulation of E2F and MYC targets as well as G2M checkpoint genes, significantly correlated with longer progression-free survival on ICI while IFNγ and inflammatory response genes were associated with a better clinical outcome on TT. In conclusion, we identify novel genes and their expression signatures as potential predictive biomarkers for TT and ICI in patients with metastatic CMM, paving the way for clinical use following larger validation studies.

Short read massive parallel sequencing has emerged as a standard diagnostic tool in the medical setting. However, short read technologies have inherent limitations such as GC bias, difficulties mapping to repetitive elements, trouble discriminating paralogous sequences, and difficulties in phasing alleles. Long read single molecule sequencers resolve these obstacles. Moreover, they offer higher consensus accuracies and can detect epigenetic modifications from native DNA. The first commercially available long read single molecule platform was the RS system based on PacBio's single molecule real-time (SMRT) sequencing technology, which has since evolved into their RSII and Sequel systems. Here we capsulize how SMRT sequencing is revolutionizing constitutional, reproductive, cancer, microbial and viral genetic testing.