Recombination events complicate the evolutionary history of populations and species and have a significant impact on the inference of isolation-with-migration (IM) models. However, several existing methods have been developed, assuming no recombination within a locus and free recombination between loci. In this study, we investigated the effect of recombination on the estimation of IM models using genomic data. We conducted a simulation study to evaluate the consistency of the parameter estimators with up to 1,000 loci and analyze true gene trees to examine the sources of errors in estimating the IM model parameters. The results showed that the presence of recombination led to biased estimates of the IM model parameters, with population sizes being more overestimated and migration rates being more underestimated as the number of loci increased. The magnitude of the biases tended to increase with the recombination rates when using 100 or more loci. On the other hand, the estimation of splitting times remained consistent as the number of loci increased. In the absence of recombination, the estimators of the IM model parameters remained consistent.

Stevens-Johnson syndrome (SJS) produces a severe hypersensitivity reaction caused by Herpes simplex virus or mycoplasma infection, vaccination, systemic disease, or other agents. Several studies have investigated the genetic susceptibility involved in SJS. To provide further genetic insights into the pathogenesis of SJS, this study prioritized high-impact, SJS-associated pathogenic variants through integrating bioinformatic and population genetic data. First, we identified SJS-associated single nucleotide polymorphisms from the genome-wide association studies catalog, followed by genome annotation with HaploReg and variant validation with Ensembl. Subsequently, expression quantitative trait locus (eQTL) from GTEx identified human genetic variants with differential gene expression across human tissues. Our results indicate that two variants, namely rs2074494 and rs5010528, which are encoded by the HLA-C (human leukocyte antigen C) gene, were found to be differentially expressed in skin. The allele frequencies for rs2074494 and rs5010528 also appear to significantly differ across continents. We highlight the utility of these population-specific HLA-C genetic variants for genetic association studies, and aid in early prognosis and disease treatment of SJS.

Adaptation of infections and hosts has resulted in several metabolic mechanisms adopted by intracellular pathogens to combat the defense responses and the lack of fuel during infection. Human tuberculosis caused by Mycobacterium tuberculosis (MTB) is the world’s first cause of mortality tied to a single disease. This study aims to characterize and anticipate potential antigen characteristics for promising vaccine candidates for the hypothetical protein of MTB through computational strategies. The protein is associated with the catalyzation of dithiol oxidation and/or disulfide reduction because of the protein’s anticipated disulfide oxidoreductase properties. This investigation analyzed the protein's physicochemical characteristics, protein-protein interactions, subcellular locations, anticipated active sites, secondary and tertiary structures, allergenicity, antigenicity, and toxicity properties. The protein has significant active amino acid residues with no allergenicity, elevated antigenicity, and no toxicity.

Assays of clinical diagnosis and species identification using molecular markers are performed according to a quantitative method in consideration of sensitivity, cost, speed, convenience, and specificity. However, typical polymerase chain reaction (PCR) assay is difficult to quantify and have various limitations. In addition, to perform quantitative analysis with the quantitative real-time PCR (qRT-PCR) equipment, a standard curve or normalization using reference genes is essential. Within the last a decade, previous studies have reported that the digital PCR (dPCR) assay, a third-generation PCR, can be applied in various fields by overcoming the shortcomings of typical PCR and qRT-PCR assays. We selected Stilla Naica System (Stilla Technologies), Droplet Digital PCR Technology (Bio-Rad), and Lab on an Array Digital Real-Time PCR analyzer system (OPTOLANE) for comparative analysis among the various droplet digital PCR platforms currently in use commercially. Our previous study discovered a molecular marker that can distinguish Hanwoo species (Korean native cattle) using Hanwoo-specific genomic structural variation. Here, we report the pros and cons of the operation of each dPCR platform from various perspectives using this species identification marker. In conclusion, we hope that this study will help researchers to select suitable dPCR platforms according to their purpose and resources.

The mammalian sirtuin family, consisting of SIRT1–SIRT7, plays a vital role in various biological processes, including cancer, diabetes, neurodegeneration, cardiovascular disease, cellular metabolism, and cellular homeostasis maintenance. Due to their involvement in these biological processes, modulating sirtuin activity seems promising to impact immune- and aging-related diseases, as well as cancer pathways. However, more understanding is required regarding the safety and efficacy of sirtuin-targeted therapies due to the complex regulatory mechanisms that govern their activity, particularly in the context of multiple targets. In this study, the interaction landscape of the sirtuin family was analyzed using a systems biology approach. A sirtuin protein-protein interaction network was built using the Cytoscape platform and analyzed using the NetworkAnalyzer and stringApp plugins. The result revealed the sirtuin family's association with numerous proteins that play diverse roles, suggesting a complex interplay between sirtuins and other proteins. Based on network topological and functional analysis, SIRT1 was identified as the most prominent among sirtuin family members, demonstrating that 25 of its protein partners are involved in cancer, 22 in innate immune response, and 29 in aging, with some being linked to a combination of two or more pathways. This study lays the foundation for the development of novel therapies that can target sirtuins with precision and efficacy. By illustrating the various interactions among the proteins in the sirtuin family, we have revealed the multifaceted roles of SIRT1 and provided a framework for their possible roles to be precisely understood, manipulated, and translated into therapeutics in the future.

Kidney renal clear cell carcinoma (KIRC) is one of the most aggressive cancer type of the urinary system. Metastatic KIRC patients have poor prognosis and limited therapeutic options. Ankyrin 3 (ANK3) is a scaffold protein that plays important roles in maintaining physiological function of the kidney and its alteration is implicated in many cancers. In this study, we investigated differential expression of ANK3 in KIRC using GEPIA2, UALCAN, and HPA databases. Survival analysis was performed by GEPIA2, Kaplan-Meier plotter, and OSkirc databases. Genetic alterations of ANK3 in KIRC were assessed using cBioPortal database. Interaction network and functional enrichment analyses of ANK3-correlated genes in KIRC were performed using GeneMANIA and Shiny GO, respectively. Finally, the TIMER2.0 database was used to assess correlation between ANK3 expression and immune infiltration in KIRC. We found that ANK3 expression was significantly decreased in KIRC compared to normal tissues. The KIRC patients with low ANK3 expression had poorer survival outcomes than those with high ANK3 expression. ANK3 mutations were found in 2.4% of KIRC patients and were frequently co-mutated with several genes with a prognostic significance. ANK3-correlated genes were significantly enriched in various biological processes, mainly involved in peroxisome proliferator-activated receptor (PPAR) signaling pathway, in which positive correlations of ANK3 with PPARA and PPARG expressions were confirmed. Expression of ANK3 in KIRC was significantly correlated with infiltration level of B cell, CD8+ T cell, macrophage, and neutrophil. These findings suggested that ANK3 could serve as a prognostic biomarker and promising therapeutic target for KIRC.

Fusobacterium nucleatum is a gram-negative bacteria associated with diverse infections like appendicitis and colorectal cancer. It mainly attacks the epithelial cells in the oral cavity and throat of the infected individual. It has a single circular genome of 2.7 Mb. Many proteins in F. nucleatum genome are listed as “Uncharacterized.” Annotation of these proteins is crucial for obtaining new facts about the pathogen and deciphering the gene regulation, functions, and pathways along with discovery of novel target proteins. In the light of new genomic information, an armoury of bioinformatic tools were used for predicting the physicochemical parameters, domain and motif search, pattern search, and localization of the uncharacterized proteins. The programs such as receiver operating characteristics determine the efficacy of the databases that have been employed for prediction of different parameters at 83.6%. Functions were successfully assigned to 46 uncharacterized proteins which included enzymes, transporter proteins, membrane proteins, binding proteins, etc. Apart from the function prediction, the proteins were also subjected to string analysis to reveal the interacting partners. The annotated proteins were also put through homology-based structure prediction and modeling using Swiss PDB and Phyre2 servers. Two probable virulent factors were also identified which could be investigated further for potential drug-related studies. The assigning of functions to uncharacterized proteins has shown that some of these proteins are important for cell survival inside the host and can act as effective drug targets.

Aromatase inhibitors (AI) are drugs that are widely used in treating estrogen receptor (ER)–positive breast cancer patients. Drug resistance is a major obstacle to aromatase inhibition therapy. There are diverse reasons behind acquired AI resistance. This study aims at identifying the plausible cause of acquired AI resistance in patients administered with non-steroidal AIs (anastrozole and letrozole). We used genomic, transcriptomic, epigenetic, and mutation data of breast invasive carcinoma from The Cancer Genomic Atlas database. The data was then separated into sensitive and resistant sets based on patients’ responsiveness to the non-steroidal AIs. A sensitive set of 150 patients and a resistant set of 172 patients were included for the study. These data were collectively analyzed to probe into the factors that might be responsible for AI resistance. We identified 17 differentially regulated genes (DEGs) among the two groups. Then, methylation, mutation, miRNA, copy number variation, and pathway analyses were performed for these DEGs. The top mutated genes (FGFR3, CDKN2A, RNF208, MAPK4, MAPK15, HSD3B1, CRYBB2, CDC20B, TP53TG5, and MAPK8IP3) were predicted. We also identified a key miRNA - hsa-mir-1264 regulating the expression of CDC20B. Pathway analysis revealed HSD3B1 to be involved in estrogen biosynthesis. This study reveals the involvement of key genes that might be associated with the development of AI resistance in ER-positive breast cancers and hence may act as a potential prognostic and diagnostic biomarker for these patients.

Liver cancer, particularly hepatocellular carcinoma (HCC), poses a significant global threat to human lives. To advance the development of innovative diagnostic and treatment approaches, it is essential to examine the hidden features of HCC, particularly its 3D genome architecture, which is not well understood. In this study, we investigated the 3D genome organization of four HCC cell lines—Hep3B, Huh1, Huh7, and SNU449—using in situ Hi-C and assay for transposase-accessible chromatin sequencing. Our findings revealed that HCC cell lines had more long-range interactions, both intra-and interchromosomal, compared to human mammary epithelial cells (HMECs). Unexpectedly, HCC cell lines displayed cell line-specific compartmental modifications at the megabase (Mb) scale, which could potentially be leveraged in determining HCC subtypes. At the sub-Mb scale, we observed decreases in intra-TAD (topologically associated domain) interactions and chromatin loops in HCC cell lines compared to HMECs. Lastly, we discovered a correlation between gene expression and the 3D chromatin architecture of SLC8A1, which encodes a sodium-calcium antiporter whose modulation is known to induce apoptosis by comparison between HCC cell lines and HMECs. Our findings suggest that HCC cell lines have a distinct 3D genome organization that is different from those of normal and other cancer cells based on the analysis of compartments, TADs, and chromatin loops. Overall, we take this as evidence that genome organization plays a crucial role in cancer phenotype determination. Further exploration of epigenetics in HCC will help us to better understand specific gene regulation mechanisms and uncover novel targets for cancer treatment.

Immunologists have activated T cells in vitro using various stimulation methods, including phorbol myristate acetate (PMA)/ionomycin and αCD3/αCD28 agonistic antibodies. PMA stimulates protein kinase C, activating nuclear factor-κB, and ionomycin increases intracellular calcium levels, resulting in activation of nuclear factor of activated T cell. In contrast, αCD3/αCD28 agonistic antibodies activate T cells through ZAP-70, which phosphorylates linker for activation of T cell and SH2-domain-containing leukocyte protein of 76 kD. However, despite the use of these two different in vitro T cell activation methods for decades, the differential effects of chemical-based and antibody-based activation of primary human T cells have not yet been comprehensively described. Using single-cell RNA sequencing (scRNA-seq) technologies to analyze gene expression unbiasedly at the single-cell level, we compared the transcriptomic profiles of the non-physiological and physiological activation methods on human peripheral blood mononuclear cell–derived T cells from four independent donors. Remarkable transcriptomic differences in the expression of cytokines and their respective receptors were identified. We also identified activated CD4 T cell subsets (CD55+) enriched specifically by PMA/ionomycin activation. We believe this activated human T cell transcriptome atlas derived from two different activation methods will enhance our understanding, highlight the optimal use of these two in vitro T cell activation assays, and be applied as a reference standard when analyzing activated specific disease-originated T cells through scRNA-seq.