Non-coding RNAs (ncRNAs) are a class of RNA molecules that do not have the potential to encode proteins. Meanwhile, they can occupy a significant portion of the human genome and participate in gene expression regulation through various mechanisms. Gestational diabetes mellitus (GDM) is a pathologic condition of carbohydrate intolerance that begins or is first detected during pregnancy, making it one of the most common pregnancy complications. Although the exact pathogenesis of GDM remains unclear, several recent studies have shown that ncRNAs play a crucial regulatory role in GDM. Herein, we present a comprehensive review on the multiple mechanisms of ncRNAs in GDM along with their potential role as biomarkers. In addition, we investigate the contribution of deep learning-based models in discovering disease-specific ncRNA biomarkers and elucidate the underlying mechanisms of ncRNA. This might assist community-wide efforts to obtain insights into the regulatory mechanisms of ncRNAs in disease and guide a novel approach for early diagnosis and treatment of disease.

For several decades, it has been known that a substantial number of genes within human DNA exhibit overlap; however, the biological and evolutionary significance of these overlaps remain poorly understood. This study focused on investigating specific instances of overlap where the overlapping DNA region encompasses the coding DNA sequences (CDSs) of protein-coding genes. The results revealed that proteins encoded by overlapping CDSs exhibit greater disorder than those from nonoverlapping CDSs. Additionally, these DNA regions were identified as GC-rich. This could be partially attributed to the absence of stop codons from two distinct reading frames rather than one. Furthermore, these regions were found to harbour fewer single-nucleotide polymorphism (SNP) sites, possibly due to constraints arising from the overlapping state where mutations could affect two genes simultaneously.While elucidating these properties, the NR1D1-THRA gene pair emerged as an exceptional case with highly structured proteins and a distinctly conserved sequence across eutherian mammals. Both NR1D1 and THRA are nuclear receptors lacking a ligand-binding domain at their C-terminus, which is the region where these gene pairs overlap. The NR1D1 gene is involved in the regulation of circadian rhythm, while the THRA gene encodes a thyroid hormone receptor, and both play crucial roles in various physiological processes. This study suggests that, in addition to their well-established functions, the specifically overlapping CDS regions of these genes may encode protein segments with additional, yet undiscovered, biological roles.

The last decade has witnessed dramatic improvements in whole-genome sequencing capabilities coupled to drastically decreased costs, leading to an inundation of high-quality de novo genomes. For this reason, the continued development of genome quality metrics is imperative. Using the 2016 Atlantic bottlenose dolphin NCBI RefSeq annotation and mass spectrometry-based proteomic analysis of six tissues, we confirmed 10,402 proteins from 4711 protein groups, constituting nearly one-third of the possible predicted proteins. Since the identification of larger proteins with more identified peptides implies reduced database fragmentation and improved gene annotation accuracy, we propose the metric NP10, which attempts to capture this quality improvement. The NP10 metric is calculated by first stratifying proteomic results by identifying the top decile (or 10th 10-quantile) of identified proteins based on the number of peptides per protein and then returns the median molecular weight of the resulting proteins. When using the 2016 versus 2012 Tursiops truncatus genome annotation to search this proteomic data set, there was a 21% improvement in NP10. This metric was further demonstrated by using a publicly available proteomic data set to compare human genome annotations from 2004, 2013 and 2016, which showed a 33% improvement in NP10. These results demonstrate that proteomics may be a useful metrological tool to benchmark genome accuracy, though there is a need for reference proteomic datasets across species to facilitate the evaluation of new de novo and existing genome.

This review considers antiviral nucleoside analog drugs, including ribavirin, favipiravir, and molnupiravir, which induce genome error catastrophe in SARS-CoV or SARS-CoV-2 via lethal mutagenesis as a mode of action. In vitro data indicate that molnupiravir may be 100 times more potent as an antiviral agent than ribavirin or favipiravir. Molnupiravir has recently demonstrated efficacy in a phase 3 clinical trial. Because of its anticipated global use, its relative potency, and the reported in vitro \"host\" cell mutagenicity of its active principle, β-d-N4-hydroxycytidine, we have reviewed the development of molnupiravir and its genotoxicity safety evaluation, as well as the genotoxicity profiles of three congeners, that is, ribavirin, favipiravir, and 5-(2-chloroethyl)-2\'-deoxyuridine. We consider the potential genetic risks of molnupiravir on the basis of all available information and focus on the need for additional human genotoxicity data and follow-up in patients treated with molnupiravir and similar drugs. Such human data are especially relevant for antiviral NAs that have the potential of permanently modifying the genomes of treated patients and/or causing human teratogenicity or embryotoxicity. We conclude that the results of preclinical genotoxicity studies and phase 1 human clinical safety, tolerability, and pharmacokinetics are critical components of drug safety assessments and sentinels of unanticipated adverse health effects. We provide our rationale for performing more thorough genotoxicity testing prior to and within phase 1 clinical trials, including human PIG-A and error corrected next generation sequencing (duplex sequencing) studies in DNA and mitochondrial DNA of patients treated with antiviral NAs that induce genome error catastrophe via lethal mutagenesis.

Schizophrenia is a polygenic disease; however, the specific risk genetic variants of schizophrenia are still largely unknown. Single nucleotide polymorphism (SNP) is important genetic factor for the susceptibility of schizophrenia. Investigating individual candidate gene contributing to disease risk remains important.
In a case-control study, five SNPs located in 6p21.3-p23.1 including rs2021722 in human leukocyte antigen (HLA) locus and rs107822, rs383711, rs439205 and rs421446 within the upstream of microRNA-219a-1 were genotyped in 454 schizophrenia patients and 445 healthy controls to investigate the possible association between the loci and schizophrenia in a Han Chinese population.
Our results showed significant associations between the rs2021722 and schizophrenia in allele (A vs. G: adjusted OR = 1.661, 95%CI = 1.196-2.308), co-dominant (AG vs. GG: OR = 1.760, 95%CI = 1.234-2.510) and dominant genetic model (AG + AA vs. GG: OR = 1.756, 95%CI = 1.237-2.492), respectively. Haplotype analysis showed that TGGT and CAAC were protective factor for schizophrenia compared with TAAC haplotype (OR = 0.324, 95% CI = 0.157-0.672; OR = 0.423, 95% CI = 0.199-0.900).
These findings indicate that rs2021722 in HLA locus might be involved in pathogenesis of schizophrenia and that genotypes AG and allele A of the locus are risk factors for schizophrenia in the Han Chinese population, confirming the association between immune system and schizophrenia.

The Italian Peninsula, a natural pier across the Mediterranean Sea, witnessed intricate population events since the very beginning of the human occupation in Europe. In the last few years, an increasing number of modern and ancient genomes from the area have been published by the international research community. This genomic perspective started unveiling the relevance of Italy to understand the post-Last Glacial Maximum (LGM) re-peopling of Europe, the earlier phase of the Neolithic westward migrations, and its linking role between Eastern and Western Mediterranean areas after the Iron Age. However, many open questions are still waiting for more data to be addressed in full. With this review, we summarize the current knowledge emerging from the available ancient Italian individuals and, by re-analysing them all at once, we try to shed light on the avenues future research in the area should cover. In particular, open questions concern (1) the fate of pre-Villabruna Europeans and to what extent their genomic components were absorbed by the post-LGM hunter-gatherers; (2) the role of Sicily and Sardinia before LGM; (3) to what degree the documented genetic structure within the Early Neolithic settlers can be described as two separate migrations; (4) what are the population events behind the marked presence of an Iranian Neolithic-like component in Bronze Age and Iron Age Italian and Southern European samples.

Ancient human remains have the potential to explain a great deal about the prehistory of humankind. Due to recent technological and bioinformatics advances, their study, at the palaeogenomic level, can provide important information about population dynamics, culture changes, and the lifestyles of our ancestors. In this study, mitochondrial and nuclear genome data obtained from human bone remains associated with the Neolithic Globular Amphorae culture, which were recovered in the Megalithic barrow of Kierzkowo (Poland), were reanalysed to gain insight into the social organisation and use of the archaeological site and to provide information at the individual level. We were able to successfully estimate the minimum number of individuals, sex, kin relationships, and phenotypic traits of the buried individuals, despite the low level of preservation of the bone samples and the intricate taphonomic conditions. In addition, the evaluation of damage patterns allowed us to highlight the presence of \"intruders\"-that is, of more recent skeletal remains that did not belong to the original burial. Due to its characteristics, the study of the Kierzkowo barrow represented a challenge for the reconstruction of the biological profile of the human community who exploited it and an excellent example of the contribution that ancient genomic analysis can provide to archaeological reconstruction.

Gene clusters are becoming promising tools for gene identification. The study reveals the purposive genomic distribution of genes toward higher inheritance rates of intact metabolic pathways/phenotypes and, thereby, higher fitness. The co-localization of co-expressed, co-interacting, and functionally related genes was found as genome-wide trends in humans, mouse, golden eagle, rice fish, Drosophila, peanut, and Arabidopsis. As anticipated, the analyses verified the co-segregation of co-localized events. A negative correlation was notable between the likelihood of co-localization events and the inter-loci distances. The evolution of genomic blocks was also found convergent and uniform along the chromosomal arms. Calling a genomic block responsible for adjacent metabolic reactions is therefore recommended for identification of candidate genes and interpretation of cellular functions. As a case story, a function in the metabolism of energy and secondary metabolites was proposed for Slc25A44, based on its genomic local information. Slc25A44 was further characterized as an essential housekeeping gene which has been under evolutionary purifying pressure and belongs to the phylogenetic ETC-clade of SLC25s. Pathway enrichment mapped the Slc25A44s to the energy metabolism. The expression of peanut and human Slc25A44s in oocytes and Saccharomyces cerevisiae strains confirmed the transport of common precursors for secondary metabolites and ubiquinone. These results suggest that SLC25A44 is a mitochondrion-ER-nucleus zone transporter with biotechnological applications. Finally, a conserved three-amino acid signature on the cytosolic face of transport cavity was found important for rational engineering of SLC25s.

Case-only (CO) studies are a powerful means to uncover gene-environment (G × E) interactions for complex human diseases. Moreover, such studies may in principle also draw upon genotype imputation to increase statistical power even further. However, genotype imputation usually employs healthy controls such as the Haplotype Reference Consortium (HRC) data as an imputation base, which may systematically perturb CO studies in genomic regions with main effects upon disease risk. Using genotype data from 719 German Crohn Disease (CD) patients, we investigated the level of imputation accuracy achievable for single nucleotide polymorphisms (SNPs) with or without a genetic main effect, and with varying minor allele frequency (MAF). Genotypes were imputed from neighbouring SNPs at different levels of linkage disequilibrium (LD) to the target SNP using the HRC data as an imputation base. Comparison of the true and imputed genotypes revealed lower imputation accuracy for SNPs with strong main effects. We also simulated different levels of G × E interaction to evaluate the potential loss of statistical validity and power incurred by the use of imputed genotypes. Simulations under the null hypothesis revealed that genotype imputation does not inflate the type I error rate of CO studies of G × E. However, the statistical power was found to be reduced by imputation, particularly for SNPs with low MAF, and a gradual loss of statistical power resulted when the level of LD to the SNPs driving the imputation decreased. Our study thus highlights that genotype imputation should be employed with great care in CO studies of G × E interaction.

Ovarian mature cystic teratomas comprise tissues derived from all three germ layers. In rare cases, malignant tumors arise from ovarian mature cystic teratoma. A variety of tumors can arise from mature cystic teratoma, among which primary malignant melanoma (MM), for which no molecular analyses such as genomic sequencing have been reported to date, is exceedingly rare, thereby limiting possible therapeutic options using precision medicine. We used targeted gene sequencing to analyze the status of 160 cancer-related genes in a patient with MM arising from an ovarian mature cystic teratoma (MM-MCT). KRAS amplification and homozygous deletion in PTEN and RB1 were detected in tumor samples collected from the patient. No KRAS amplification has been previously reported in cutaneous MM, indicating that the carcinogenesis of MM-MCT differs from that of primary cutaneous melanomas. A better understanding of the underlying genetic mechanisms will help clarify the carcinogenesis of MM-MCT. In turn, this will enable treatment with novel targeting agents as well as the initial exploration of gene-based precision oncological therapies, which aim to improve treatment outcomes for patients with this disease.