More than 4,000 single nucleotide polymorphisms (SNP) variants have been identified in the human ZFP36L2 gene, however only a few have been studied in the context of protein function. The tandem zinc finger domain of ZFP36L2, an RNA binding protein, is the functional domain that binds to its target mRNAs. This protein/RNA interaction triggers mRNA degradation, controlling gene expression. We identified 32 non-synonymous SNPs (nsSNPs) in the tandem zinc finger domain of ZFP36L2 that could have possible deleterious impacts in humans. Using different bioinformatic strategies, we prioritized five among these 32 nsSNPs, namely rs375096815, rs1183688047, rs1214015428, rs1215671792 and rs920398592 to be validated. When we experimentally tested the functionality of these protein variants using gel shift assays, all five (Y154H, R160W, R184C, G204D, and C206F) resulted in a dramatic reduction in RNA binding compared to the WT protein. To understand the mechanistic effect of these variants on the protein/RNA interaction, we employed DUET, DynaMut and PyMOL to investigate structural changes in the protein. Additionally, we conducted Molecular Docking and Molecular Dynamics Simulations to fine tune the active behaviour of this biomolecular system at an atomic level. Our results propose atomic explanations for the impact of each of these five genetic variants identified.

Gene therapy is poised to transition from niche to mainstream medicine, with recombinant adeno-associated virus (rAAV) as the vector of choice. However, robust, scalable, industrialized production is required to meet demand and provide affordable patient access, which has not yet materialized. Closing the chasm between demand and supply requires innovation in biomanufacturing to achieve the essential step change in rAAV product yield and quality. Omics provides a rich source of mechanistic knowledge that can be applied to HEK293, the most commonly used cell line for rAAV production. In this review, the findings from a growing number of diverse studies that apply genomics, epigenomics, transcriptomics, proteomics, and metabolomics to HEK293 bioproduction are explored. Learnings from CHO-omics, application of omics approaches to improve CHO bioproduction, provide a framework to explore the potential of "HEK-omics" as a multi-omics-informed approach providing actionable mechanistic insights for improved transient and stable production of rAAV and other recombinant products in HEK293.

The human cytochrome b561 (hCytb561) family consists of electron transfer transmembrane proteins characterized by six conserved α-helical transmembrane domains and two β-type heme cofactors. These proteins contribute to the regulation of iron metabolism and numerous different physiological and pathological processes by recycling ascorbic acid and maintaining iron reductase activity. Key members of this family include cytochrome b561 (CYB561), duodenal CYB561 (Dcytb), lysosomal CYB561 (LCytb), stromal cell-derived receptor 2 (SDR2) and 101F6, which are widely expressed in human tissues and participate in the pathogenesis of several diseases and tumors. They are associated with the promotion or inhibition of tumor growth and progression in various malignancies and are potential therapeutic targets for malignant tumors. The present review summarizes the existing literature regarding the structure of the Cytb561 family, the basic functional characteristics of hCytb561 family members, and the roles of the CYB561, Dcytb, LCytb, SDR2 and 101F6 in various diseases and tumors.

Precision oncology relies on detailed molecular analysis of how diverse tumours respond to various therapies, with the aim to optimize treatment outcomes for individual patients. Patient-derived xenograft (PDX) models have been key to preclinical validation of precision oncology approaches, enabling the analysis of each tumour's unique genomic landscape and testing therapies that are predicted to be effective based on specific mutations, gene expression patterns or signalling abnormalities. To extend these standard precision oncology approaches, the field has strived to complement the otherwise static and often descriptive measurements with functional assays, termed functional precision oncology (FPO). By utilizing diverse PDX and PDX-derived models, FPO has gained traction as an effective preclinical and clinical tool to more precisely recapitulate patient biology using in vivo and ex vivo functional assays. Here, we explore advances and limitations of PDX and PDX-derived models for precision oncology and FPO. We also examine the future of PDX models for precision oncology in the age of artificial intelligence. Integrating these two disciplines could be the key to fast, accurate and cost-effective treatment prediction, revolutionizing oncology and providing patients with cancer with the most effective, personalized treatments.

RNA-binding proteins (RBPs) are integral components of cellular machinery, playing crucial roles in the regulation of gene expression and maintaining genetic stability. Their interactions with RNA molecules govern critical processes such as mRNA splicing, stability, localization, and translation, which are essential for proper cellular function. These proteins interact with RNA molecules and other proteins to form ribonucleoprotein complexes (RNPs), hence controlling the fate of target RNAs. The interaction occurs via RNA recognition motif, the zinc finger domain, the KH domain and the double stranded RNA binding motif (all known as RNA-binding domains (RBDs). These domains are found within the coding sequences (intron and exon domains), 5' untranslated regions (5'UTR) and 3' untranslated regions (3'UTR). Dysregulation of RBPs can lead to genomic instability, contributing to various pathologies, including cancer neurodegenerative diseases, and metabolic disorders. This study comprehensively explores the multifaceted roles of RBPs in genetic stability, highlighting their involvement in maintaining genomic integrity through modulation of RNA processing and their implications in cellular signalling pathways. Furthermore, it discusses how aberrant RBP function can precipitate genetic instability and disease progression, emphasizing the therapeutic potential of targeting RBPs in restoring cellular homeostasis. Through an analysis of current literature, this study aims to delineate the critical role of RBPs in ensuring genetic stability and their promise as targets for innovative therapeutic strategies.

In the individualized treatment of a patient with Coarctation of the Aorta (CoA), a non-severe case which initially exhibits no symptoms, and thus requires no treatment, could potentially become severe over time. This progression can be attributed to insufficient growth at the coarctation site relative to the overall growth of the child. Therefore, an agent-based model (ABM) to predict the aortic growth of a CoA patient is introduced. The multi-scale approach combines Computational Fluid Dynamics (CFD) and ABM to study systems that are influenced by both mechanical stimuli and biochemical responses characteristic of growth. Our focus is on ABM development; thus, CFD insights were applied solely to enhance the ABM framework. Comparative medicine was leveraged to develop a species-specific ABM by considering the rat and porcine species commonly used in cardiovascular research together with data from healthy human toddlers. The ABM luminal radius prediction accuracy was observed to be 79% for rat, above 95% for porcine and 91. 6% for the healthy toddler; while that observed for the growth rate was 38.7%, 90% and 64.3% respectively. Given its performance, the ABM was adapted to a 2.5-year-old patient-specific CoA. Subsequently, the model predicted that by age 3, the condition would worsen, marked by persistent CoA enhanced by the predicted least growth compared to growth predicted in the rest of the aorta, hypertension, and increased turbulent flow; thus, increased vessel injury risk. The findings advise for incorporating vascular remodelling into the ABM to enhance its predictive capability for intervention planning.

A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating a structured body of information about gene functions, which now includes experimental findings reported in more than 175,000 publications for human genes and genes in experimentally tractable model organisms1,2. Here, we describe the results of a large, international effort to integrate all of these findings to create a representation of human gene functions that is as complete and accurate as possible. Specifically, we apply an expert-curated, explicit evolutionary modelling approach to all human protein-coding genes. This approach integrates available experimental information across families of related genes into models that reconstruct the gain and loss of functional characteristics over evolutionary time. The models and the resulting set of 68,667 integrated gene functions cover approximately 82% of human protein-coding genes. The functional repertoire reveals a marked preponderance of molecular regulatory functions, and the models provide insights into the evolutionary origins of human gene functions. We show that our set of descriptions of functions can improve the widely used genomic technique of Gene Ontology enrichment analysis. The experimental evidence for each functional characteristic is recorded, thereby enabling the scientific community to help review and improve the resource, which we have made publicly available.

In the present era, noncoding RNAs (ncRNAs) have become a subject of considerable scientific interest, with peptides encoded by ncRNAs representing a particularly promising avenue of investigation. The identification of ncRNA-encoded peptides in human cancers is increasing. These peptides regulate cancer progression through multiple molecular mechanisms. Here, we delineate the patterns of diverse ncRNA-encoded peptides and provide a synopsis of the methodologies employed for the identification of ncRNAs that possess the capacity to encode these peptides. Furthermore, we discuss the impacts of ncRNA-encoded peptides on the biological behavior of cancer cells and the underlying molecular mechanisms. In conclusion, we describe the prospects of ncRNA-encoded peptides in cancer and the challenges that need to be overcome.

Polymerase chain reaction (PCR), a revolutionary molecular tool, has transformed genetic studies by facilitating rapid DNA amplification. The PCR process relies on several key components: a DNA template or cDNA, two primers, Taq polymerase, nucleotides, and a buffer. These elements collectively facilitate the amplification process, which comprises three stages: denaturation, annealing, and extension. These stages are repeated in cycles to exponentially amplify the target DNA sequence. Furthermore, the power of PCR lies in its ability to generate exponential copies of target DNA in a remarkably short period. Moreover, various PCR techniques are available, encompassing traditional approaches like quantitative PCR, reverse transcription PCR, and nested PCR, as well as innovative methods such as extreme PCR, inverse PCR, and touchdown PCR. These techniques are extensively utilized in molecular, biological, and medical research laboratories for both research and diagnostic applications. This review explores a comprehensive overview of PCR, covering its history, underlying principles, and diverse applications in diagnostics, research, and drug development.

LINE-1 (L1) and Alu are two families of transposable elements (TEs) occupying ~17% and ~11% of the human genome, respectively. Though only a small fraction of L1 copies is able to produce the machinery to mobilize autonomously, Alu and degenerate L1s can hijack their functional machinery and mobilize in trans. The expression and subsequent mobilization of L1 and Alu can exert pathological effects on their hosts. These features have made them promising focus subjects in studies of aging where they can become active. However, mechanisms regulating TE activity are incompletely characterized, especially in diverse human populations. To address these gaps, we leveraged genomic data from the 1000 Genomes Project to carry out a trans-ethnic GWAS of L1/Alu insertion singletons. These are rare, recently acquired insertions observed in only one person and which we used as proxies for variation in L1/Alu insertion numbers. Our approach identified SNVs in genomic regions containing genes with potential and known TE regulatory properties, and it enriched for SNVs in regions containing known regulators of L1 expression. Moreover, we identified reference TE copies and structural variants that associated with L1/Alu singletons, suggesting their potential contribution to TE insertion number variation. Finally, a transcriptional analysis of lymphoblastoid cells highlighted potential cell cycle alterations in a subset of samples harboring L1/Alu singletons. Collectively, our results suggest that known TE regulatory mechanisms may be active in diverse human populations, expand the list of loci implicated in TE insertion number variability, and reinforce links between TEs and disease.

Circular RNAs (circRNAs) are a family of covalently closed RNA transcripts ubiquitous across the eukaryotic kingdom. CircRNAs are generated by a class of alternative splicing called backsplicing, with the resultant circularization of a part of parental RNA producing the characteristic backsplice junction (BSJ). Because of the noncontiguous sequence of the BSJ with respect to the DNA genome, circRNAs remained hidden in plain sight through over a decade of RNA next-generation sequencing, yet over 3 million unique circRNA transcripts have been illuminated in the past decade alone. CircRNAs are expressed in a cell type-specific manner, are highly stable, with many examples of circRNAs being evolutionarily conserved and/or functional in specific contexts. However, circRNAs can be very lowly expressed and predictions of the circRNA context from BSJ-spanning reads alone can confound extrapolation of the exact sequence composition of the circRNA transcript. For these reasons, specific and ultrasensitive detection, combined with enrichment, bespoke bioinformatics pipelines and, more recently, long-read, highly processive sequencing is becoming critical for complete characterization of all circRNA variants. Concomitantly, the need for targeted detection and quantification of specific circRNAs has sparked numerous laboratory-based and commercial approaches to visualize circRNAs in cells and quantify them in biological samples, including biospecimens. This review focuses on advancements in the detection and quantification of circRNAs, with a particular focus on recent next-generation sequencing approaches to bolster detection of circRNA variants and accurately normalize between sequencing libraries.

DNA is a natural chemical substrate that carries genetic information, which also serves as a powerful toolkit for storing digital data. Compared to traditional storage media, DNA molecules offer higher storage density, longer lifespan, and lower maintenance energy consumption. In DNA storage process, data readout is a critical step that bridges the gap between DNA molecular/structures with stored digital information. With the continued development of strategies in DNA data storage technology, the readout techniques have evolved. However, there is a lack of systematic introduction and discussion on the readout techniques for reported DNA data storage systems, especially the correlation between the design of the data storage system and the corresponding selection of readout techniques. This review first introduces two main categories of DNA data storage units (i.e., sequence and structure) and their corresponding readout techniques (i.e., sequencing and nonsequencing methods), and then reviewed representative examples of notable advancements in DNA data storage technology, focusing on data storage unit design, and readout technique selection. It also introduces emerging approaches to assist data readout techniques, such as implementation of microfluidic and fluorescent probes. Finally, the paper discusses the limitations, challenges, and potential of DNA data readout approaches.

The rapid advancements in the field of genetics have significantly propelled the development of gene therapies, paving the way for innovative treatments of various hereditary disorders. This review focuses on the genetics of ophthalmologic conditions, highlighting the currently approved ophthalmic gene therapy and exploring emerging therapeutic strategies under development. Inherited retinal dystrophies represent a heterogeneous group of genetic disorders that manifest across a broad spectrum from infancy to late middle age. Key clinical features include nyctalopia (night blindness), constriction of the visual field, impairments in color perception, reduced central visual acuity, and rapid eye movements. Recent technological advancements, such as multimodal imaging, psychophysical assessments, and electrophysiological testing, have greatly enhanced our ability to understand disease progression and establish genotype-phenotype correlations. Additionally, the integration of molecular diagnostics into clinical practice is revolutionizing patient stratification and the design of targeted interventions, underscoring the transformative potential of personalized medicine in ophthalmology. The review also covers the challenges and opportunities in developing gene therapies for other ophthalmic conditions, such as age-related macular degeneration and optic neuropathies. We discuss the viral and non-viral vector systems used in ocular gene therapy, highlighting their advantages and limitations. Additionally, we explore the potential of emerging technologies like CRISPR/Cas9 in treating genetic eye diseases. We briefly address the regulatory landscape, concerns, challenges, and future directions of gene therapy in ophthalmology. We emphasize the need for long-term safety and efficacy data as these innovative treatments move from bench to bedside.

Viruses can inhabit their hosts in the form of an ensemble of various mutant strains. Reconstructing a robust consensus representation for these diverse mutant strains is essential for recognizing the genetic variations among strains and delving into aspects like virulence, pathogenesis, and selecting therapies. Virus genomes are typically small, often composed of only a few thousand to several hundred thousand nucleotides. While constructing a high-quality consensus of virus strains might seem feasible, most current assemblers only generated fragmented contigs. It's important to emphasize the significance of assembling a single full-length consensus contig, as it's vital for identifying genetic diversity and estimating strain abundance accurately.

In this paper, we developed FC-Virus, a de novo genome assembly strategy specifically targeting highly diverse viral populations. FC-Virus first identifies the k-mers that are common across most viral strains, and then uses these k-mers as a backbone to build a full-length consensus sequence covering the entire genome. We benchmark FC-Virus against state-of-the-art genome assemblers.

Experimental results confirm that FC-Virus can construct a single, accurate full-length consensus, whereas other assemblers only manage to produce fragmented contigs. FC-Virus is freely available at https://github.com/qdu-bioinfo/FC-Virus.git .

Recent advances in functional genomics and human cellular models have substantially enhanced our understanding of the structure and regulation of the human genome. However, our grasp of the molecular functions of human genes remains incomplete and biased towards specific gene classes. The Molecular Phenotypes of Null Alleles in Cells (MorPhiC) Consortium aims to address this gap by creating a comprehensive catalogue of the molecular and cellular phenotypes associated with null alleles of all human genes using in vitro multicellular systems. In this Perspective, we present the strategic vision of the MorPhiC Consortium and discuss various strategies for generating null alleles, as well as the challenges involved. We describe the cellular models and scalable phenotypic readouts that will be used in the consortium's initial phase, focusing on 1,000 protein-coding genes. The resulting molecular and cellular data will be compiled into a catalogue of null-allele phenotypes. The methodologies developed in this phase will establish best practices for extending these approaches to all human protein-coding genes. The resources generated-including engineered cell lines, plasmids, phenotypic data, genomic information and computational tools-will be made available to the broader research community to facilitate deeper insights into human gene functions.

The increasing availability of clinically approved genetic tests for kidney disease has spurred the growth in the use of these tests in kidney transplant practice. Neither the testing options nor the patient population where this should be deployed has been defined, and its value in kidney transplant evaluation has not been demonstrated. Transplant providers may not always be aware of the limitations of genetic testing and may need guidance on comprehending test results and providing counsel, as many centers do not have easy access to a renal genetic counselor or a clinical geneticist. In this practice resource, a working group of nephrologists, geneticists, and a genetic counselor provide a pragmatic, tailored approach to genetic testing, advocating for its use only where the genetic diagnosis or its exclusion can impact the choices available for transplantation or posttransplant management or the workup of living donor candidates at increased risk for heritable disease.

The use of next-generation sequencing technologies such as exome and genome sequencing in research and clinical care has transformed our understanding of the molecular architecture of genetic kidney diseases. Although the capability to identify and rigorously assess genetic variants and their relationship to disease has advanced considerably in the past decade, the curation of clinically relevant relationships between genes and specific phenotypes has received less attention, despite it underpinning accurate interpretation of genomic tests. Here, we discuss the need to accurately define gene-disease relationships in nephrology and provide a framework for appraising genetic and experimental evidence critically. We describe existing international programmes that provide expert curation of gene-disease relationships and discuss sources of discrepancy as well as efforts at harmonization. Further, we highlight the need for alignment of disease and phenotype terminology to ensure robust and reproducible curation of knowledge. These collective efforts to support evidence-based translation of genomic sequencing into practice across clinical, diagnostic and research settings are crucial for delivering the promise of precision medicine in nephrology, providing more patients with timely diagnoses, accurate prognostic information and access to targeted treatments.

Adverse drug reactions pose a significant threat to patient safety and public health and often become apparent only after widespread clinical use. Mendelian randomization (MR) analysis is a valuable tool that can be used to infer causality by using genetic variants as instrumental variables, which can predict the occurrence of adverse drug reactions before they occur. Compared with traditional observational studies, MR Analysis can reduce the potential bias of confounding factors. This article reviews the principles of MR Analysis and its application in the prediction of adverse drug reactions, the challenges and future directions, and summarizes how to harness the power of this innovative epidemiological method to put us at the forefront of improving drug safety assessment and personalized medicine.

LINE-1 (L1) and Alu are two families of transposable elements (TEs) occupying ~17% and ~11% of the human genome, respectively. Though only a small fraction of L1 copies is able to produce the machinery to mobilize autonomously, Alu and degenerate L1s can hijack their functional machinery and mobilize in trans. The expression and subsequent mobilization of L1 and Alu can exert pathological effects on their hosts. These features have made them promising focus subjects in studies of aging where they can become active. However, mechanisms regulating TE activity are incompletely characterized, especially in diverse human populations. To address these gaps, we leveraged genomic data from the 1000 Genomes Project to carry out a trans-ethnic GWAS of L1/Alu insertion singletons. These are rare, recently acquired insertions observed in only one person and which we used as proxies for variation in L1/Alu insertion numbers. Our approach identified SNVs in genomic regions containing genes with potential and known TE regulatory properties, and it enriched for SNVs in regions containing known regulators of L1 expression. Moreover, we identified reference TE copies and structural variants that associated with L1/Alu singletons, suggesting their potential contribution to TE insertion number variation. Finally, a transcriptional analysis of lymphoblastoid cells highlighted potential cell cycle alterations in a subset of samples harboring L1/Alu singletons. Collectively, our results suggest that known TE regulatory mechanisms may be active in diverse human populations, expand the list of loci implicated in TE insertion number variability, and reinforce links between TEs and disease.

RNA recognition motifs (RRMs) are a key class of proteins that primarily bind single-stranded RNAs. In this study, we applied standard atomistic molecular dynamics simulations to obtain insights into the intricate binding dynamics between uridine-rich RNAs and TbRGG2 RRM using the recently developed OL3-Stafix AMBER force field, which improves the description of single-stranded RNA molecules. Complementing structural experiments that unveil a primary binding mode with a single uridine bound, our simulations uncover two supplementary binding modes in which adjacent nucleotides encroach upon the binding pocket. This leads to a unique molecular mechanism through which the TbRGG2 RRM is capable of rapidly transitioning the U-rich sequence. In contrast, the presence of non-native cytidines induces stalling and destabilization of the complex. By leveraging extensive equilibrium dynamics and a large variety of binding states, TbRGG2 RRM effectively expedites diffusion along the RNA substrate while ensuring robust selectivity for U-rich sequences despite featuring a solitary binding pocket. We further substantiate our description of the complex dynamics by simulating the fully spontaneous association process of U-rich sequences to the TbRGG2 RRM. Our study highlights the critical role of dynamics and auxiliary binding states in interface dynamics employed by RNA-binding proteins, which is not readily apparent in traditional structural studies but could represent a general type of binding strategy employed by many RNA-binding proteins.

Emerging evidence demonstrates that cryptic translation from RNAs previously annotated as noncoding might generate microproteins with oncogenic functions. However, the importance and underlying mechanisms of these microproteins in alternative splicing-driven tumor progression have rarely been studied. Here, we show that the novel protein TPM3P9, encoded by the lncRNA tropomyosin 3 pseudogene 9, exhibits oncogenic activity in clear cell renal cell carcinoma (ccRCC) by enhancing oncogenic RNA splicing. Overexpression of TPM3P9 promotes cell proliferation and tumor growth. Mechanistically, TPM3P9 binds to the RRM1 domain of the splicing factor RBM4 to inhibit RBM4-mediated exon skipping in the transcription factor TCF7L2. This results in increased expression of the oncogenic splice variant TCF7L2-L, which activates NF-κB signaling via its interaction with SAM68 to transcriptionally induce RELB expression. From a clinical perspective, TPM3P9 expression is upregulated in cancer tissues and is significantly correlated with the expression of TCF7L2-L and RELB. High TPM3P9 expression or low RBM4 expression is associated with poor survival in patients with ccRCC. Collectively, our findings functionally and clinically characterize the "noncoding RNA"-derived microprotein TPM3P9 and thus identify potential prognostic and therapeutic factors in renal cancer.

Next-generation sequencing has revolutionized genome science over the last two decades. Indeed, the wealth of sequence information on our genome has deepened our understanding on cancer. Cancer is a genetic disease caused by genetic or epigenetic alternations that affect the expression of genes that control cell functions, particularly cell growth and division. Utilization of next-generation sequencing in cancer gene panels has enabled the identification of actionable gene alterations in cancer patients to guide personalized precision medicine.

The aim is to provide information that can identify actionable gene alterations, enabling personalized precision medicine for cancer patients.

Equipped with next-generation sequencing techniques, international collaboration programs on cancer genomics have identified numerous mutations, gene fusions, microsatellite variations, copy number variations, and epigenetics changes that promote the transformation of normal cells into tumors. Cancer classification has traditionally been based on cell type or tissue-of-origin and the morphological characteristics of the cancer. However, interactive genomic analyses have currently reclassified cancers based on systemic molecular-based taxonomy. Although all cancer-causing genes and mechanisms have yet to be completely understood or identified, personalized or precision medicine is now currently possible for some forms of cancer. Unlike the "one-size-fits-all" approach of traditional medicine, precision medicine allows for customized or personalized treatment based on genomic information.

Despite the availability of numerous cancer gene panels, technological innovation in genomics and expansion of knowledge on the cancer genome will allow precision oncology to manage even more types of cancers.

Transgenic mice, including those created using Bacterial Artificial Chromosomes (BACs), are artificial manipulations that have become critical tools for studying gene function. While conventional transgenic techniques face challenges in achieving precise expression of foreign genes in specific cells and tissues, BAC transgenic mice offer a solution by incorporating large DNA segments that can include entire expression units with tissue-specific enhancers. This review provides a thorough examination of BAC transgenic mouse technology, encompassing both traditional and humanized models. We explore the benefits and drawbacks of BAC transgenesis compared to other techniques such as knock-in and CRISPR/Cas9 technologies. The review emphasizes the applications of BAC transgenic mice in various disciplines, including neuroscience, immunology, drug metabolism, and disease modeling. Additionally, we address crucial aspects of generating and analyzing BAC transgenic mice, such as position effects, copy number variations, and strategies to mitigate these challenges. Despite certain limitations, humanized BAC transgenic mice have proven to be invaluable tools for studying the pathogenesis of human diseases, drug development, and understanding intricate gene regulatory mechanisms. This review discusses current topics on BAC transgenic mice and their evolving significance in biomedical research.

With the development of genome sequencing technologies, the amount of data produced has greatly increased in the last two decades. The abundance of digital sequence information (DSI) has provided research opportunities, improved our understanding of the genome, and led to the discovery of new solutions in industry and medicine. It has also posed certain challenges, i.e., how to store and handle such amounts of data. This, coupled with the need for convenience, international cooperation, and the possibility of independent validation, has led to the establishment of numerous databases. Spearheaded with the idea that data obtained with public funds should be available to the public, open access has become the predominant mode of accession. However, the increasing popularity of commercial genetic tests brings back the topic of data misuse, and patient's privacy. At the previous United Nations Biodiversity Conference (COP15, 2022), an issue of the least-developed countries exploiting their natural resources while providing DSI and the most-developed countries benefitting from this was raised. It has been proposed that financial renumeration for the data could help protect biodiversity. With the goal of introducing the topic to those interested in utilizing biological databases, in this publication, we present the history behind the biological databases, their necessity in today's scientific world, and the issues that concern them and their content, while providing scientific and policy context in relation to United Nations Biodiversity Conference (COP16, 21.10-1.11.24).

The Human Pangenome Reference Consortium, the Chinese Pangenome Consortium, and other plant and animal pangenome projects have announced the completion of pilot work aimed at constructing high-quality, haplotype-resolved reference graph genomes representative of global ethno-linguistically different populations or different plant and animal species. These graph-based, gapless pangenome references, which are enriched in terms of genomic diversity, completeness, and contiguity, have the potential for enhancing long-read sequencing (LRS)-based genomic research, as well as improving mappability and variant genotyping on traditional short-read sequencing platforms. We comprehensively discuss the advancements in pangenome-based genomic integrative genomic discoveries across forensic-related species (humans, animals, and plants) and summarize their applications in variant identification and forensic genomics, epigenetics, transcriptomics, and microbiome research. Recent developments in multiplexed array sequencing have introduced a highly efficient and programmable technique to overcome the limitations of short forensic marker lengths in LRS platforms. This technique enables the concatenation of short RNA transcripts and DNA fragments into LRS-optimal molecules for sequencing, assembly, and genotyping. The integration of new pangenome reference coordinates and corresponding computational algorithms will benefit forensic integrative genomics by facilitating new marker identification, accurate genotyping, high-resolution panel development, and the updating of statistical algorithms. This review highlights the necessity of integrating LRS-based platforms, pangenome-based study designs, and graph-based pangenome references in short-read mapping and LRS-based innovations to achieve precision forensic science.

Microorganisms, including bacteria, fungi, and viruses, that reside on and within the human body are collectively known as the human microbiome. Dysbiosis, or disruption in the microbiome, has been implicated in several disease processes, including asthma, obesity, autoimmune diseases, and numerous other conditions. While the Human Microbiome Project and the generation of descriptive studies it inspired established correlations between characteristic patterns in the composition of the microbiome and specific disease phenotypes, current research has begun to focus on elucidating the causal role of the microbiome in disease pathogenesis. Within the field of orthopaedic surgery, researchers have proposed the concept of a "gut-joint axis," whereby the intestinal microbiome influences joint health and the development of diseases, such as osteoarthritis and periprosthetic joint infection (PJI). It is theorized that intestinal dysbiosis increases gut permeability, leading to the translocation of bacteria and their metabolic products into the systemic circulation and the stimulation of proinflammatory response cascades throughout the body, including within the joints. While correlative studies have identified patterns of dysbiotic derangement associated with osteoarthritis and PJI, translational research is needed to clarify the precise mechanisms by which these changes influence disease processes. Additionally, an emerging body of literature has challenged the previously held belief that certain body sites are sterile and do not possess a microbiome, with studies identifying distinct microbial genomic signatures and a core microbiome that varies between anatomic sites. A more thorough characterization of the joint microbiome may have profound implications for our understanding of PJI pathogenesis and our ability to stratify patients based on risk. The purpose of this review was to outline our current understanding of the human microbiome to describe the gut-joint axis and its role in specific pathologies, including PJI, and to highlight the potential of microbiome-based therapeutic interventions in the field of orthopaedics.

One of the greatest scientific achievements of the twenty-first century is the completion of The Human Genome Project (HGP). Thereafter, we came to know that the human genome codes nearly 2% for making proteins and thus named as coding genes, suggesting the rest of the genome as noncoding or junk. However, research in the past two decades has shown and established that noncoding RNAs are major contributors of regulating and modulating the various function of cells as well as tissues. Noncoding RNAs can be classified as basis of their sizes in two categories, long noncoding RNAs (>200 nt) and small noncoding RNAs (<200 nt). Small nucleolar RNAs (snoRNAs) are part of the small noncoding RNA family and primarily reside inside the nucleus of eukaryotes. Sno RNAs can be divided into two major categories based on their distinguished structure and function; these are C/D box and HACA box snoRNAs. They participate in the posttranscriptional modifications on ribosomal RNAs (r-RNAs), transfer RNAs (t-RNAs), messenger RNAs (m-RNAs), and small nuclear RNAs (snRNAs). Sno RNAs act as guide RNAs to modify other noncoding RNAs by pseudouridylation or 2'O ribomethylation. We discussed in this protocol about one of the widely used techniques for detection and analysis of snoRNAs, i.e., real-time quantitative PCR (RT-qPCR).

Massively parallel sequencing technologies have been a boon to many fields of biological science, including oncology. Cancer is an umbrella term for many diseases featuring abnormal cellular growth due to genetic and epigenetic aberrations. Advances in sequencing technology allow for interrogation of the DNA and RNA of cancer cells and other cells in the tumor microenvironment down to a single-base resolution. However, these strides come after a rich history of ground-breaking biological assays, like the discovery of the Philadelphia chromosome in the context of leukemia. Many specific genetic and epigenetic modifications have been implicated in oncogenesis, cancer progression, and response to treatment. Sequencing technologies have also helped to associate populations of bacteria in the microbiome to cancer development and prognosis. However, all this new information, especially when procured via high-throughput methods, comes at the cost of being more computationally and staff-resource intensive. There is also more risk to the privacy of the individuals with sequenced genomes. Notwithstanding, the overall benefit of sequencing technologies can greatly outweigh the risks with careful advancements and continued focus on the goal: helping those affected by cancer via precision medicine. Cancer biology has been and will continue to be elucidated by sequencing innovations in ways unimaginable without it.

High-throughput sequencing technologies and innovative bioinformatics tools discovered that most of the genome is transcribed into RNA. However, only a fraction of the RNAs in cell translates into proteins, while the majority of them are categorized as noncoding RNAs (ncRNAs). The ncRNAs with more than 200 nt without protein-coding ability are termed long noncoding RNAs (lncRNAs). Hundreds of studies established that lncRNAs are a crucial RNA family regulating gene expression. Regulatory RNAs, including lncRNAs, modulate gene expression by interacting with RNA, DNA, and proteins. Several databases and computational tools have been developed to explore the functions of lncRNAs in cellular physiology. This chapter discusses the tools available for lncRNA functional analysis and provides a detailed workflow for the computational analysis of lncRNAs.

DNA-based technologies have been used in forensic practice since the mid-1980s. While PCR-based STR genotyping using Capillary Electrophoresis remains the gold standard for generating DNA profiles in routine casework worldwide, the research community is continually seeking alternative methods capable of providing additional information to enhance discrimination power or contribute with new investigative leads. Oxford Nanopore Technologies (ONT) and PacBio third-generation sequencing have revolutionized the field, offering real-time capabilities, single-molecule resolution, and long-read sequencing (LRS). ONT, the pioneer of nanopore sequencing, uses biological nanopores to analyze nucleic acids in real-time. Its devices have revolutionized sequencing and may represent an interesting alternative for forensic research and routine casework, given that it offers unparalleled flexibility in a portable size: it enables sequencing approaches that range widely from PCR-amplified short target regions (e.g., CODIS STRs) to PCR-free whole transcriptome or even ultra-long whole genome sequencing. Despite its higher error rate compared to Illumina sequencing, it can significantly improve accuracy in read alignment against a reference genome or de novo genome assembly. This is achieved by generating long contiguous sequences that correctly assemble repetitive sections and regions with structural variation. Moreover, it allows real-time determination of DNA methylation status from native DNA without the need for bisulfite conversion. LRS enables the analysis of thousands of markers at once, providing phasing information and eliminating the need for multiple assays. This maximizes the information retrieved from a single invaluable sample. In this review, we explore the potential use of LRS in different forensic genetics approaches.

Dry eye disease (DED) is a multifactorial condition with complex and incompletely understood molecular mechanisms. Advances in multi-omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and microbiomics, have provided new insights into the pathophysiology of DED. Genomic analyses have identified key genetic variants linked to immune regulation and lacrimal gland function. Transcriptomic studies reveal upregulated inflammatory pathways in ocular surface tissues, implicating these as core drivers of chronic inflammation. Proteomic research highlights significant alterations in tear protein composition, especially proteins involved in inflammation and tissue repair. Metabolomics studies focus on disrupted lipid metabolism and oxidative stress, which are crucial in maintaining tear film stability. Furthermore, microbiome research has demonstrated reduced microbial diversity and increased pathogenic bacteria, exacerbating inflammatory responses. The integration of multi-omics data allows for the identification of novel biomarkers and therapeutic targets, enabling precision diagnostics and personalized treatments. Therefore, this review highlights the critical importance of multi-omics approaches in deepening our understanding of DED's complex molecular mechanisms and their potential to transform clinical management and therapeutic innovations in this challenging field.

Alternative splicing is essential for the generation of various protein isoforms that are involved in cell differentiation and tissue development. In addition to internal coding exons, alternative splicing affects the exons with translation initiation codons; however, little is known about these exons. Here, we performed a systematic classification of human alternative exons using coding information. The analysis showed that more than 5% of cassette exons contain translation initiation codons (alternatively skipped exons harboring a 5' untranslated region and coding region, 5UC-ASEs) although their skipping causes the deletion of translation initiation sites essential for protein synthesis. The splicing of 5UC-ASEs is under the repressive control of MATR3, a DNA/RNA-binding protein associated with neurodegeneration, and is distinctly regulated particularly in the human brain, muscle, and testis. Interestingly, MATR3 represses its own translation by skipping a 5UC-ASE in MATR3 to autoregulate its expression level. 5UC-ASEs are larger than other types of alternative exons. Furthermore, evolutionary analysis revealed that 5UC-ASEs have already appeared in cartilaginous fishes, have increased in amphibians, and are concentrated in the genes involved in transcription in mammals. Taken together, our analysis identified a unique set of alternative exons, 5UC-ASEs, that have evolutionarily acquired a repression mechanism for gene expression through association with MATR3.

This review provides a comprehensive overview of the chemistries and workflows of the sequencing methods that have been or are currently commercially available, providing a very brief historical introduction to each method. The main optical genome mapping approaches are introduced in the same manner, although only a subset of these are or have ever been commercially available. The review comes with a deck of slides containing all of the figures for ease of access and consultation.

During the last decade, artificial intelligence (AI) was applied to nearly all domains of human activity, including scientific research. It is thus warranted to ask whether AI thinking should be durably involved in biomedical research. This problem was addressed by examining three complementary questions (i) What are the major barriers currently met by biomedical investigators? It is suggested that during the last 2 decades there was a shift towards a growing need to elucidate complex systems, and that this was not sufficiently fulfilled by previously successful methods such as theoretical modeling or computer simulation (ii) What is the potential of AI to meet the aforementioned need? it is suggested that recent AI methods are well-suited to perform classification and prediction tasks on multivariate systems, and possibly help in data interpretation, provided their efficiency is properly validated. (iii) Recent representative results obtained with machine learning suggest that AI efficiency may be comparable to that displayed by human operators. It is concluded that AI should durably play an important role in biomedical practice. Also, as already suggested in other scientific domains such as physics, combining AI with conventional methods might generate further progress and new applications, involving heuristic and data interpretation.

Precision oncology aims to match the right drug(s) to the right patient. Equally important is ensuring that precision therapies are offered at the right time. Transformative, rather than incremental, outcome improvement may require treatment at diagnosis rather than in the advanced/metastatic setting after genomic evolution.

Cells are essential to understanding health and disease, yet traditional models fall short of modeling and simulating their function and behavior. Advances in AI and omics offer groundbreaking opportunities to create an AI virtual cell (AIVC), a multi-scale, multi-modal large-neural-network-based model that can represent and simulate the behavior of molecules, cells, and tissues across diverse states. This Perspective provides a vision on their design and how collaborative efforts to build AIVCs will transform biological research by allowing high-fidelity simulations, accelerating discoveries, and guiding experimental studies, offering new opportunities for understanding cellular functions and fostering interdisciplinary collaborations in open science.

In 2018 we analysed the three main repositories for the human proteome, Ensembl/GENCODE, RefSeq and UniProtKB. They disagreed on the coding status of one of every eight annotated coding genes. The analysis inspired bilateral collaborations between annotation groups. Here we have repeated our analysis with updated versions of the three reference coding gene sets. Superficially, little appears to have changed. Although there are slightly fewer genes predicted as coding overall, the three groups still disagree on the status of 2,606 annotated genes. However, a comparison without read-through genes and immunoglobulin fragments shows that the three reference sets have merged or reclassified more than 700 genes since the last analysis and that just 0.6% of Ensembl/GENCODE coding genes are not also annotated by the other two reference sets. We used eight features indicative of non-coding genes to examine the 21,873 coding genes annotated across the three reference sets. We found that more than 2,000 had one or more potential non-coding features. While some of these genes will be protein coding, we believe that most are likely to be non-coding genes or pseudogenes. Our results suggest that annotators still vastly overestimate the number of true coding genes.

Whole-exome sequencing (WES) data are frequently used for cancer diagnosis and genome-wide association studies (GWAS), based on high-coverage read mapping, informative variant calling, and high-quality reference genomes. The center position of the currently used genome assembly, GRCh38, is now challenged by two newly published telomere-to-telomere (T2T) genomes, T2T-CHM13 and T2T-YAO, and it becomes urgent to have a comparative study to test population specificity using the three reference genomes based on real case WES data. Here, we report our analysis along this line for 19 tumor samples collected from Chinese patients. The primary comparison of the exon regions among the three references reveals that the sequences in up to ∼ 1% of target regions in T2T-YAO are widely diversified from GRCh38 and may lead to off-target in sequence capture. However, T2T-YAO still outperforms GRCh38 by obtaining 7.41% of more mapped reads. Due to more reliable read-mapping and closer phylogenetic relationship with the samples than GRCh38, T2T-YAO reduces half of variant calls of clinical significance which are mostly benign, while maintaining sensitivity in identifying pathogenic variants. T2T-YAO also outperforms T2T-CHM13 in reducing calls of Chinese-specific variants. Our findings highlight the critical need for employing population-specific reference genomes in genomic analysis to ensure accurate variant analysis and the significant benefits of tailoring these approaches to the unique genetic background of each ethnic group.

Genetic information will be increasingly integrated into clinical eye care within the current generation of ophthalmologists. For monogenic diseases such as retinoblastoma, genetic studies have been relatively straightforward as these conditions result from pathogenic variants in a single gene resulting in large physiological effects. However, most eye diseases result from the cumulative effects of multiple genetic variants and environmental factors. In such diseases, because each variant usually has an individually small effect, genetic studies for complex diseases are comparatively more challenging. This article aims to provide an overview of three genetic epidemiology methods for polygenic (or complex) diseases: genome-wide association studies (GWAS), Polygenic Risk Scores (PRS) and Mendelian randomisation (MR). A GWAS systematically conducts association analyses of a trait of interest against millions of genetic variants, usually in the form of single nucleotide polymorphisms, across the genome. GWAS findings can then be used for PRS construction and MR analyses. To construct a PRS, the cumulative effect of many genetic variants associated with a trait from a prior GWAS is calculated and taken as a quantitative representation of an individual's genetic risk of a complex disease. MR studies analyse an outcome measure against the genetic variants of an exposure, and are particularly useful in investigating causal relations between two traits where randomised controlled trials are not possible or ethical. In addition to explaining the principles of these three genetic epidemiology concepts, this article provides a minimally technical description of their basic methodology that is accessible to the non-expert reader.

Epigenetic modifications are chemical groups in our DNA (and chromatin) that determine which genes are active and which are shut off. Importantly, they integrate environmental signals to direct cellular function. Upon chronic environmental exposures, the epigenetic signature of lung cells gets altered, triggering aberrant gene expression programs that can lead to the development of chronic lung diseases. In addition to driving disease, epigenetic marks can serve as attractive lung disease biomarkers, due to early onset, disease specificity, and stability, warranting the need for more epigenetic research in the lung field. Despite substantial progress in mapping epigenetic alterations (mostly DNA methylation) in chronic lung diseases, the molecular mechanisms leading to their establishment are largely unknown. This review is meant as a guide for clinicians and lung researchers interested in epigenetic regulation with a focus on DNA methylation. It provides a short introduction to the main epigenetic mechanisms (DNA methylation, histone modifications and non-coding RNA) and the machinery responsible for their establishment and removal. It presents examples of epigenetic dysregulation across a spectrum of chronic lung diseases and discusses the current state of epigenetic therapies. Finally, it introduces the concept of epigenetic editing, an exciting novel approach to dissecting the functional role of epigenetic modifications. The promise of this emerging technology for the functional study of epigenetic mechanisms in cells and its potential future use in the clinic is further discussed.

Analysis of transcription factors and chromatin modifications at the genome-wide level provides insights into gene regulatory processes, such as transcription, cell differentiation and cellular response. Chromatin immunoprecipitation is the most popular and powerful approach for mapping chromatin, and other enzyme-tethering techniques have recently become available for living cells. Among these, Cleavage Under Targets and Tagmentation (CUT&Tag) is a relatively novel chromatin profiling method that has rapidly gained popularity in the field of epigenetics since 2019. It has also been widely adapted to map chromatin modifications and TFs in different species, illustrating the association of these chromatin epitopes with various physiological and pathological processes. Scalable single-cell CUT&Tag can be combined with distinct platforms to distinguish cellular identity, epigenetic features and even spatial chromatin profiling. In addition, CUT&Tag has been developed as a strategy for joint profiling of the epigenome, transcriptome or proteome on the same sample. In this review, we will mainly consolidate the applications of CUT&Tag and its derivatives on different platforms, give a detailed explanation of the pros and cons of this technique as well as the potential development trends and applications in the future.

Antiviral drugs have classically been developed by directly disrupting the functions of viral proteins. However, this strategy has been largely unsuccessful due to the rapid generation of viral escape mutants. It has been well established that as compared to the virus-centric approach, the strategy of developing antiviral drugs by targeting host-dependency factors (HDFs) minimizes drug resistance. However, recent reports have indicated that drug resistance against some of the host-targeting antiviral agents can in fact occur under some circumstances. Long-term selection pressure of a host-targeting antiviral agent may induce the virus to use an alternate cellular factor or alters its affinity towards the target that confers resistance. Alternatively, virus may synchronize its life cycle with the patterns of drug therapy. In addition, virus may subvert host's immune system to perpetuate under the limiting conditions of the targeted cellular factor. This review describes novel potential mechanisms that may account for the acquiring resistance against agents that target HDFs.

The All of Us Research Program aims to return value to participants by developing research capacity in communities. We describe a novel set of introductory exercises (Data Sandboxes) and specialized trainings to orient researchers to the Researcher Workbench to foster health equity research.

We developed a tailored training to familiarize researchers with the All of Us Research Program: (1) orientation, (2) tailored "data treasure hunt" using the Public Data Browser, and (3) overview of the analyses tools and platform.

Participants' pre- and post-knowledge of the contents and structure of the All of Us dataset scores increased significantly after training. These trainings effectively engaged researchers in exploring this rich dataset.

We describe ways of orienting and familiarizing a wide variety of researchers with the All of Us Research Program dataset, sparking their interest, and "jump-starting" their research.