The sequence of the human genome

A prioritization tool for cilia-associated genes and their in vivo resources unveils new avenues for ciliopathy research

Defects in ciliary signaling or mutations in proteins that localize to primary cilia lead to a class of human diseases known as ciliopathies. Approximately 10% of mammalian genes encode cilia-associated proteins, and a major gap in the cilia research field is knowing which genes to prioritize to study and finding the in vivo vertebrate mutant alleles and reagents available for their study. Here, we present a unified resource listing the cilia-associated human genes cross referenced to available mouse and zebrafish mutant alleles, and their associated phenotypes, as well as expression data in the kidney and functional data for vertebrate Hedgehog signaling. This resource empowers researchers to easily sort and filter genes based on their own expertise and priorities, cross reference with newly generated -omics datasets, and quickly find in vivo resources and phenotypes associated with a gene of interest.

ImageGP 2 for enhanced data visualization and reproducible analysis in biomedical research

ImageGP is an extensively utilized, open-access platform for online data visualization and analysis. Over the past 7 years, it has catered to more than 700,000 usages globally, garnering substantial user feedback. The updated version, ImageGP 2 (available at https://www.bic.ac.cn/BIC), introduces a redesigned interface leveraging cutting-edge web technologies to enhance functionality and user interaction. Key enhancements include the following: (i) Addition of modules for data format transformation, facilitating operations such as matrix merging, subsetting, and transformation between long and wide formats. (ii) Streamlined workflows with features like preparameter selection data validation and grouping of parameters with similar attributes. (iii) Expanded repertoire of visualization functions and analysis tools, including Weighted Gene Co-Expression Network Analysis, differential gene expression analysis, and FASTA sequence processing. (iv) Personalized user space for uploading large data sets, tracking analysis history, and sharing reproducible analysis data, scripts, and results. (v) Enhanced user support through a simplified error debugging feature accessible with a single click. (vi) Introduction of an R package, ImageGP, enabling local data visualization and analysis. These updates position ImageGP 2 as a versatile tool serving both wet-lab and dry-lab researchers with expanded capabilities.

Integration of Artificial Intelligence and Quantum Transport toward Stereoselective Identification of Carbohydrate Isomers

Detection of stereoisomers of carbohydrates with molecular resolution, a challenging goal analysts desire to achieve, is key to the full development of glycosciences. Despite the promise that analytical techniques made, including widely used nuclear magnetic resonance and mass spectrometry, high throughput de novo carbohydrate sequencing remains an unsolved issue. Notably, while next-generation sequencing technologies are readily available for DNA and proteins, they are conspicuously absent for carbohydrates due to the immense stereochemical and structural complexity inherent in these molecules. In this work, we report a novel computational technique that employs quantum tunneling coupled with artificial intelligence to detect complex carbohydrate anomers and stereoisomers with excellent sensitivity. The quantum tunneling footprints of carbohydrate isomers show high distinguishability with an in-depth analysis of underlying chemistry. Our findings open up a new route for carbohydrate sensing, which can be seamlessly integrated with next-generation sequencing technology for real-time analysis.

Bioinformatics in Russia: history and present-day landscape

Bioinformatics has become an interdisciplinary subject due to its universal role in molecular biology research. The current status of Russia's bioinformatics research in Russia is not known. Here, we review the history of bioinformatics in Russia, present the current landscape, and highlight future directions and challenges. Bioinformatics research in Russia is driven by four major industries: information technology, pharmaceuticals, biotechnology, and agriculture. Over the past three decades, despite a delayed start, the field has gained momentum, especially in protein and nucleic acid research. Dedicated and shared centers for genomics, proteomics, and bioinformatics are active in different regions of Russia. Present-day bioinformatics in Russia is characterized by research issues related to genetics, metagenomics, OMICs, medical informatics, computational biology, environmental informatics, and structural bioinformatics. Notable developments are in the fields of software (tools, algorithms, and pipelines), use of high computation power (e.g. by the Siberian Supercomputer Center), and large-scale sequencing projects (the sequencing of 100 000 human genomes). Government funding is increasing, policies are being changed, and a National Genomic Information Database is being established. An increased focus on eukaryotic genome sequencing, the development of a common place for developers and researchers to share tools and data, and the use of biological modeling, machine learning, and biostatistics are key areas for future focus. Universities and research institutes have started to implement bioinformatics modules. A critical mass of bioinformaticians is essential to catch up with the global pace in the discipline.

The Final Step in Molybdenum Cofactor Biosynthesis-A Historical View

Molybdenum (Mo) is an essential micronutrient across all kingdoms of life, where it functions as a key component of the active centers of molybdenum-dependent enzymes. For these enzymes to gain catalytic activity, Mo must be complexed with a pterin scaffold to form the molybdenum cofactor (Moco). The final step of Moco biosynthesis is catalyzed by the enzyme Mo-insertase. This review focuses on eukaryotic Mo-insertases, with an emphasis on those found in plants and mammals, which have been instrumental in advancing the understanding of Mo biochemistry. Additionally, a historical perspective is provided, tracing the discovery of Mo-insertase from the early 1960s to the detailed characterization of its reaction mechanism in 2021. This review also highlights key milestones in the study of Mo-insertase, including mutant characterization, gene cloning, structural elucidation at the atomic level, functional domain assignment, and the spatial organization of the enzyme within cellular protein networks.

Mycobacterium paratuberculosis: A HERV Turn-On for Autoimmunity, Neurodegeneration, and Cancer?

Human endogenous retroviruses (HERVs) are remnants of ancient retroviral infections that, over millions of years, became integrated into the human genome. While normally inactive, environmental stimuli such as infections have contributed to the transcriptional reactivation of HERV-promoting pathological conditions, including the development of autoimmunity, neurodegenerative disease and cancer. What infections trigger HERV activation? Mycobacterium avium subspecies paratuberculosis (MAP) is a pluripotent driver of human disease. Aside from granulomatous diseases, Crohn's disease, sarcoidosis and Blau syndrome, MAP is associated with autoimmune disease: type one diabetes (T1D), multiple sclerosis (MS), rheumatoid arthritis (RA) and autoimmune thyroiditis. MAP is also associated with Alzheimer's disease (AD) and Parkinson's disease (PD). Autoimmune diabetes, MS and RA are the diseases with the strongest MAP/HERV association. There are several other diseases associated with HERV activation, including diseases whose epidemiology and/or pathology would prompt speculation for a causal role of MAP. These include non-solar uveal melanoma, colon cancer, glioblastoma and amyotrophic lateral sclerosis (ALS). This article further points to MAP infection as a contributor to autoimmunity, neurodegenerative disease and cancer via the un-silencing of HERV. We examine the link between the ever-increasing number of MAP-associated diseases and the MAP/HERV intersection with these diverse medical conditions, and propose treatment opportunities based upon this association.

Machine learning and related approaches in transcriptomics

Data acquisition for transcriptomic studies used to be the bottleneck in the transcriptomic analytical pipeline. However, recent developments in transcriptome profiling technologies have increased researchers' ability to obtain data, resulting in a shift in focus to data analysis. Incorporating machine learning to traditional analytical methods allows the possibility of handling larger volumes of complex data more efficiently. Many bioinformaticians, especially those unfamiliar with ML in the study of human transcriptomics and complex biological systems, face a significant barrier stemming from their limited awareness of the current landscape of ML utilisation in this field. To address this gap, this review endeavours to introduce those individuals to the general types of ML, followed by a comprehensive range of more specific techniques, demonstrated through examples of their incorporation into analytical pipelines for human transcriptome investigations. Important computational aspects such as data pre-processing, task formulation, results (performance of ML models), and validation methods are encompassed. In hope of better practical relevance, there is a strong focus on studies published within the last five years, almost exclusively examining human transcriptomes, with outcomes compared with standard non-ML tools.

Importance of Studying Non-Coding RNA in Children and Adolescents with Type 1 Diabetes

Type 1 diabetes (T1D) mellitus is a chronic illness in children and teens, with rising global incidence rates. It stems from an autoimmune attack on pancreatic β cells, leading to insufficient insulin production. Genetic susceptibility and environmental triggers initiate this process. Early detection is possible by identifying multiple autoantibodies, which aids in predicting future T1D development. A new staging system highlights T1D's onset with islet autoimmunity rather than symptoms. Family members of T1D patients face a significantly increased risk of T1D. Italy recently passed a law mandating national T1D screening for pediatric populations. Measurements of β cell function continue to be essential in assessing efficacy, and different models have been proposed, but more appropriate biomarkers are mandatory for both progression studies before the onset of diabetes and during therapeutic monitoring. Biomarkers like microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) play key roles in T1D pathogenesis by regulating gene expression. Understanding their roles offers insights into T1D mechanisms and potential therapeutic targets. In this review, we summarized recent progress in the roles of some non-coding RNAs (ncRNAs) in the pathogenesis of T1D, with particular attention to miRNAs, lncRNAs, and circRNAs.

Body fluid multiomics in 3PM-guided ischemic stroke management: health risk assessment, targeted protection against health-to-disease transition, and cost-effective personalized approach are envisaged

Because of its rapid progression and frequently poor prognosis, stroke is the third major cause of death in Europe and the first one in China. Many independent studies demonstrated sufficient space for prevention interventions in the primary care of ischemic stroke defined as the most cost-effective protection of vulnerable subpopulations against health-to-disease transition. Although several studies identified molecular patterns specific for IS in body fluids, none of these approaches has yet been incorporated into IS treatment guidelines. The advantages and disadvantages of individual body fluids are thoroughly analyzed throughout the paper. For example, multiomics based on a minimally invasive approach utilizing blood and its components is recommended for real-time monitoring, due to the particularly high level of dynamics of the blood as a body system. On the other hand, tear fluid as a more stable system is recommended for a non-invasive and patient-friendly holistic approach appropriate for health risk assessment and innovative screening programs in cost-effective IS management. This article details aspects essential to promote the practical implementation of highlighted achievements in 3PM-guided IS management.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00376-2.

Genome assembly in the telomere-to-telomere era

Genome sequences largely determine the biology and encode the history of an organism, and de novo assembly - the process of reconstructing the genome sequence of an organism from sequencing reads - has been a central problem in bioinformatics for four decades. Until recently, genomes were typically assembled into fragments of a few megabases at best, but now technological advances in long-read sequencing enable the near-complete assembly of each chromosome - also known as telomere-to-telomere assembly - for many organisms. Here, we review recent progress on assembly algorithms and protocols, with a focus on how to derive near-telomere-to-telomere assemblies. We also discuss the additional developments that will be required to resolve remaining assembly gaps and to assemble non-diploid genomes.

Exploring the unmapped cysteine redox proteoform landscape

Cysteine redox proteoforms define the diverse molecular states that proteins with cysteine residues can adopt. A protein with one cysteine residue must adopt one of two binary proteoforms: reduced or oxidized. Their numbers scale: a protein with 10 cysteine residues must assume one of 1,024 proteoforms. Although they play pivotal biological roles, the vast cysteine redox proteoform landscape comprising vast numbers of theoretical proteoforms remains largely uncharted. Progress is hampered by a general underappreciation of cysteine redox proteoforms, their intricate complexity, and the formidable challenges that they pose to existing methods. The present review advances cysteine redox proteoform theory, scrutinizes methodological barriers, and elaborates innovative technologies for detecting unique residue-defined cysteine redox proteoforms. For example, chemistry-enabled hybrid approaches combining the strengths of top-down mass spectrometry (TD-MS) and bottom-up mass spectrometry (BU-MS) for systematically cataloguing cysteine redox proteoforms are delineated. These methods provide the technological means to map uncharted redox terrain. To unravel hidden redox regulatory mechanisms, discover new biomarkers, and pinpoint therapeutic targets by mining the theoretical cysteine redox proteoform space, a community-wide initiative termed the "Human Cysteine Redox Proteoform Project" is proposed. Exploring the cysteine redox proteoform landscape could transform current understanding of redox biology.

microRNA 21 and long non-coding RNAs interplays underlie cancer pathophysiology: A narrative review

Non-coding RNAs (ncRNAs) are a diverse group of functional RNA molecules that lack the ability to code for proteins. Despite missing this traditional role, ncRNAs have emerged as crucial regulators of various biological processes and have been implicated in the development and progression of many diseases, including cancer. MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are two prominent classes of ncRNAs that have emerged as key players in cancer pathophysiology. In particular, miR-21 has been reported to exhibit oncogenic roles in various forms of human cancer, including prostate, breast, lung, and colorectal cancer. In this context, miR-21 overexpression is closely associated with tumor proliferation, growth, invasion, angiogenesis, and chemoresistance, whereas miR-21 inactivation is linked to the regression of most tumor-related processes. Accordingly, miR-21 is a crucial modulator of various canonical oncogenic pathways such as PTEN/PI3K/Akt, Wnt/β-catenin, STAT, p53, MMP2, and MMP9. Moreover, interplays between lncRNA and miRNA further complicate the regulatory mechanisms underlying tumor development and progression. In this regard, several lncRNAs have been found to interact with miR-21 and, by functioning as competitive endogenous RNAs (ceRNAs) or miRNA sponges, can modulate cancer tumorigenesis. This work presents and discusses recent findings highlighting the roles and pathophysiological implications of the miR-21-lncRNA regulatory axis in cancer occurrence, development, and progression. The data collected indicate that specific lncRNAs, such as MEG3, CASC2, and GAS5, are strongly associated with miR-21 in various types of cancer, including gastric, cervical, lung, and glioma. Indeed, these lncRNAs are well-known tumor suppressors and are commonly downregulated in different types of tumors. Conversely, by modulating various mechanisms and oncogenic signaling pathways, their overexpression has been linked with preventing tumor formation and development. This review highlights the significance of these regulatory pathways in cancer and their potential for use in cancer therapy as diagnostic and prognostic markers.

Non-nucleoside inhibitors of DNMT1 and DNMT3 for targeted cancer therapy

DNA methylation can deactivate tumor suppressor genes thus causing cancers. Two DNA methylation inhibitors have been approved by the Food and Drug Administration (FDA) and have entered clinical use. However, these inhibitors are nucleoside analogues that can be incorporated into DNA or RNA and induce significant side effects. DNMT1 and DNMT3 are key enzymes involved in DNA methylation. In the acute myeloid leukemia model, a non-nucleoside DNMT1-specific inhibitor has shown lower toxicity and improved pharmacokinetics compared to traditional nucleoside drugs. DNMT3 is also implicated in certain specific cancers. Thus, developing non-nucleoside inhibitors for DNMT1 or DNMT3 can help in understanding their roles in carcinogenesis and provide targeted treatment options in certain cancers. Although no non-nucleoside inhibitors have yet entered clinical trials, in this review, we focus on DNMT1 or DNMT3 selective inhibitors. For DNMT1 selective inhibitors, we have compiled information on the repurposed drugs, derivative compounds and selective inhibitors identified through virtual screening. Additionally, we have outlined potential targets for DNMT1, including protein-protein complex, RNA mimics and aptamers. Compared to DNMT1, research on DNMT3-specific inhibitors has been less extensive. In this context, our exploration has identified a limited number of molecular inhibitors, and we have proposed specific long non-coding RNAs (lncRNAs) as potential contributors to the selective inhibition of DNMT3. This collective effort aims to offer valuable insights into the development of non-nucleoside inhibitors that selectively target DNMT1 or DNMT3.

Chemical Synthesis of Human Proteoforms and Application in Biomedicine

Limited understanding of human proteoforms with complex posttranslational modifications and the underlying mechanisms poses a major obstacle to research on human health and disease. This Outlook discusses opportunities and challenges of de novo chemical protein synthesis in human proteoform studies. Our analysis suggests that to develop a comprehensive, robust, and cost-effective methodology for chemical synthesis of various human proteoforms, new chemistries of the following types need to be developed: (1) easy-to-use peptide ligation chemistries allowing more efficient de novo synthesis of protein structural domains, (2) robust temporary structural support strategies for ligation and folding of challenging targets, and (3) efficient transpeptidative protein domain-domain ligation methods for multidomain proteins. Our analysis also indicates that accurate chemical synthesis of human proteoforms can be applied to the following aspects of biomedical research: (1) dissection and reconstitution of the proteoform interaction networks, (2) structural mechanism elucidation and functional analysis of human proteoform complexes, and (3) development and evaluation of drugs targeting human proteoforms. Overall, we suggest that through integrating chemical protein synthesis with in vivo functional analysis, mechanistic biochemistry, and drug development, synthetic chemistry would play a pivotal role in human proteoform research and facilitate the development of precision diagnostics and therapeutics.

Application of Pan-Omics Technologies in Research on Important Economic Traits for Ruminants

The economic significance of ruminants in agriculture underscores the need for advanced research methodologies to enhance their traits. This review aims to elucidate the transformative role of pan-omics technologies in ruminant research, focusing on their application in uncovering the genetic mechanisms underlying complex traits such as growth, reproduction, production performance, and rumen function. Pan-omics analysis not only helps in identifying key genes and their regulatory networks associated with important economic traits but also reveals the impact of environmental factors on trait expression. By integrating genomics, epigenomics, transcriptomics, metabolomics, and microbiomics, pan-omics enables a comprehensive analysis of the interplay between genetics and environmental factors, offering a holistic understanding of trait expression. We explore specific examples of economic traits where these technologies have been pivotal, highlighting key genes and regulatory networks identified through pan-omics approaches. Additionally, we trace the historical evolution of each omics field, detailing their progression from foundational discoveries to high-throughput platforms. This review provides a critical synthesis of recent advancements, offering new insights and practical recommendations for the application of pan-omics in the ruminant industry. The broader implications for modern animal husbandry are discussed, emphasizing the potential for these technologies to drive sustainable improvements in ruminant production systems.

A Draft Pacific Ancestry Pangenome Reference

Individuals of Pacific ancestry suffer some of the highest rates of health disparities yet remain vastly underrepresented in genomic research, including currently available linear and pangenome references. To begin addressing this, we developed the first Pacific ancestry pangenome reference using 23 individuals with diverse Pacific ancestry. We assembled 46 haploid genomes from these 23 individuals, resulting in highly accurate and contiguous genome assemblies with an average quality value of 55.0 and an average N50 of 40.7 Mb, marking the first de novo assembly of highly accurate Pacific ancestry genomes. We combined these assemblies to create a pangenome reference, which added 30.6 Mb of novel sequence missing from the Human Pangenome Reference Consortium (HPRC) reference. Mapping short reads to this pangenome reduced variant call errors and yielded more true-positive variants compared to the HPRC and T2T-CHM13 references. This Pacific ancestry pangenome reference serves as a resource to enhance genetic analyses for this underserved population.

Transcription of Endogenous Retroviruses: Broad and Precise Mechanisms of Control

Endogenous retroviruses (ERVs) are the remnants of retroviral germline infections and are highly abundant in the genomes of vertebrates. At one time considered to be nothing more than inert 'junk' within genomes, ERVs have been tolerated within host genomes over vast timescales, and their study continues to reveal complex co-evolutionary histories within their respective host species. For example, multiple instances have been characterized of ERVs having been 'borrowed' for normal physiology, from single copies to ones involved in various regulatory networks such as innate immunity and during early development. Within the cell, the accessibility of ERVs is normally tightly controlled by epigenetic mechanisms such as DNA methylation or histone modifications. However, these silencing mechanisms of ERVs are reversible, and epigenetic alterations to the chromatin landscape can thus lead to their aberrant expression, as is observed in abnormal cellular environments such as in tumors. In this review, we focus on ERV transcriptional control and draw parallels and distinctions concerning the loss of regulation in disease, as well as their precise regulation in early development.

Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test

Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.

Evidence for widespread translation of 5' untranslated regions

Ribosome profiling experiments support the translation of a range of novel human open reading frames. By contrast, most peptides from large-scale proteomics experiments derive from just one source, 5' untranslated regions. Across the human genome we find evidence for 192 translated upstream regions, most of which would produce protein isoforms with extended N-terminal ends. Almost all of these N-terminal extensions are from highly abundant genes, which suggests that the novel regions we detect are just the tip of the iceberg. These upstream regions have characteristics that are not typical of coding exons. Their GC-content is remarkably high, even higher than 5' regions in other genes, and a large majority have non-canonical start codons. Although some novel upstream regions have cross-species conservation - five have orthologues in invertebrates for example - the reading frames of two thirds are not conserved beyond simians. These non-conserved regions also have no evidence of purifying selection, which suggests that much of this translation is not functional. In addition, non-conserved upstream regions have significantly more peptides in cancer cell lines than would be expected, a strong indication that an aberrant or noisy translation initiation process may play an important role in translation from upstream regions.

A Chimeric ORF Fusion Phenotypic Reporter for Cryptococcus neoformans

The plethora of genome sequences produced in the postgenomic age has not resolved many of our most pressing biological questions. Correlating gene expression with an interrogatable and easily observable characteristic such as the surrogate phenotype conferred by a reporter gene is a valuable approach to gaining insight into gene function. Many reporters including lacZ, amdS, and the fluorescent proteins mRuby3 and mNeonGreen have been used across all manners of organisms. Described here is an investigation into the creation of a robust, synthetic, fusion reporter system for Cryptococcus neoformans that combines some of the most useful fluorophores available in this system with the versatility of the counter-selectable nature of amdS. The reporters generated include multiple composition and orientation variants, all of which were investigated for differences in expression. Evaluation of known promoters from the TEF1 and GAL7 genes was undertaken, elucidating novel expression tendencies of these biologically relevant C. neoformans regulators of transcription. Smaller than lacZ but providing multiple useful surrogate phenotypes for interrogation, the fusion ORF serves as a superior whole-cell assay compared to traditional systems. Ultimately, the work described here bolsters the array of relevant genetic tools that may be employed in furthering manipulation and understanding of the WHO fungal priority group pathogen C. neoformans.

Enhancing recognition and interpretation of functional phenotypic sequences through fine-tuning pre-trained genomic models

BACKGROUND

Decoding human genomic sequences requires comprehensive analysis of DNA sequence functionality. Through computational and experimental approaches, researchers have studied the genotype-phenotype relationship and generate important datasets that help unravel complicated genetic blueprints. Thus, the recently developed artificial intelligence methods can be used to interpret the functions of those DNA sequences.

METHODS

This study explores the use of deep learning, particularly pre-trained genomic models like DNA_bert_6 and human_gpt2-v1, in interpreting and representing human genome sequences. Initially, we meticulously constructed multiple datasets linking genotypes and phenotypes to fine-tune those models for precise DNA sequence classification. Additionally, we evaluate the influence of sequence length on classification results and analyze the impact of feature extraction in the hidden layers of our model using the HERV dataset. To enhance our understanding of phenotype-specific patterns recognized by the model, we perform enrichment, pathogenicity and conservation analyzes of specific motifs in the human endogenous retrovirus (HERV) sequence with high average local representation weight (ALRW) scores.

RESULTS

We have constructed multiple genotype-phenotype datasets displaying commendable classification performance in comparison with random genomic sequences, particularly in the HERV dataset, which achieved binary and multi-classification accuracies and F1 values exceeding 0.935 and 0.888, respectively. Notably, the fine-tuning of the HERV dataset not only improved our ability to identify and distinguish diverse information types within DNA sequences but also successfully identified specific motifs associated with neurological disorders and cancers in regions with high ALRW scores. Subsequent analysis of these motifs shed light on the adaptive responses of species to environmental pressures and their co-evolution with pathogens.

CONCLUSIONS

These findings highlight the potential of pre-trained genomic models in learning DNA sequence representations, particularly when utilizing the HERV dataset, and provide valuable insights for future research endeavors. This study represents an innovative strategy that combines pre-trained genomic model representations with classical methods for analyzing the functionality of genome sequences, thereby promoting cross-fertilization between genomics and artificial intelligence.

Evolution of Virus-like Features and Intrinsically Disordered Regions in Retrotransposon-derived Mammalian Genes

Several mammalian genes have originated from the domestication of retrotransposons, selfish mobile elements related to retroviruses. Some of the proteins encoded by these genes have maintained virus-like features; including self-processing, capsid structure formation, and the generation of different isoforms through -1 programmed ribosomal frameshifting. Using quantitative approaches in molecular evolution and biophysical analyses, we studied 28 retrotransposon-derived genes, with a focus on the evolution of virus-like features. By analyzing the rate of synonymous substitutions, we show that the -1 programmed ribosomal frameshifting mechanism in three of these genes (PEG10, PNMA3, and PNMA5) is conserved across mammals and originates alternative proteins. These genes were targets of positive selection in primates, and one of the positively selected sites affects a B-cell epitope on the spike domain of the PNMA5 capsid, a finding reminiscent of observations in infectious viruses. More generally, we found that retrotransposon-derived proteins vary in their intrinsically disordered region content and this is directly associated with their evolutionary rates. Most positively selected sites in these proteins are located in intrinsically disordered regions and some of them impact protein posttranslational modifications, such as autocleavage and phosphorylation. Detailed analyses of the biophysical properties of intrinsically disordered regions showed that positive selection preferentially targeted regions with lower conformational entropy. Furthermore, positive selection introduces variation in binary sequence patterns across orthologues, as well as in chain compaction. Our results shed light on the evolutionary trajectories of a unique class of mammalian genes and suggest a novel approach to study how intrinsically disordered region biophysical characteristics are affected by evolution.

Beyond the Human Genome Project: The Age of Complete Human Genome Sequences and Pangenome References

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

Deep learning approaches for non-coding genetic variant effect prediction: current progress and future prospects

Recent advancements in high-throughput sequencing technologies have significantly enhanced our ability to unravel the intricacies of gene regulatory processes. A critical challenge in this endeavor is the identification of variant effects, a key factor in comprehending the mechanisms underlying gene regulation. Non-coding variants, constituting over 90% of all variants, have garnered increasing attention in recent years. The exploration of gene variant impacts and regulatory mechanisms has spurred the development of various deep learning approaches, providing new insights into the global regulatory landscape through the analysis of extensive genetic data. Here, we provide a comprehensive overview of the development of the non-coding variants models based on bulk and single-cell sequencing data and their model-based interpretation and downstream tasks. This review delineates the popular sequencing technologies for epigenetic profiling and deep learning approaches for discerning the effects of non-coding variants. Additionally, we summarize the limitations of current approaches in variant effect prediction research and outline opportunities for improvement. We anticipate that our study will offer a practical and useful guide for the bioinformatic community to further advance the unraveling of genetic variant effects.

Efflux ABC transporters in drug disposition and their posttranscriptional gene regulation by microRNAs

ATP-binding cassette (ABC) transporters are transmembrane proteins expressed commonly in metabolic and excretory organs to control xenobiotic or endobiotic disposition and maintain their homeostasis. Changes in ABC transporter expression may directly affect the pharmacokinetics of relevant drugs involving absorption, distribution, metabolism, and excretion (ADME) processes. Indeed, overexpression of efflux ABC transporters in cancer cells or bacteria limits drug exposure and causes therapeutic failure that is known as multidrug resistance (MDR). With the discovery of functional noncoding microRNAs (miRNAs) produced from the genome, many miRNAs have been revealed to govern posttranscriptional gene regulation of ABC transporters, which shall improve our understanding of complex mechanism behind the overexpression of ABC transporters linked to MDR. In this article, we first overview the expression and localization of important ABC transporters in human tissues and their clinical importance regarding ADME as well as MDR. Further, we summarize miRNA-controlled posttranscriptional gene regulation of ABC transporters and effects on ADME and MDR. Additionally, we discuss the development and utilization of novel bioengineered miRNA agents to modulate ABC transporter gene expression and subsequent influence on cellular drug accumulation and chemosensitivity. Findings on posttranscriptional gene regulation of ABC transporters shall not only improve our understanding of mechanisms behind variable ADME but also provide insight into developing new means towards rational and more effective pharmacotherapies.

The Orphan G Protein-Coupled Receptor GPR52 is a Novel Regulator of Breast Cancer Multicellular Organization

G protein-coupled receptors (GPCRs) are the largest class of membrane-bound receptors and transmit critical signals from the extracellular to the intracellular spaces. Transcriptomic data of resected breast tumors shows that low mRNA expression of the orphan GPCR GPR52 correlates with reduced overall survival in breast cancer patients, leading to the hypothesis that loss of GPR52 supports breast cancer progression. CRISPR-Cas9 was used to knockout GPR52 in human triple-negative breast cancer (TNBC) cell lines MDA-MB-468 and MDA-MB-231, and in the non-cancerous breast epithelial cell line, MCF10A. Loss of GPR52 was found to be associated with increased cell-cell interaction in 2D cultures, altered 3D spheroid morphology, and increased propensity to organize and invade collectively in Matrigel. Furthermore, GPR52 loss was associated with features of EMT in MDA-MB-468 cells. To determine the in vivo impact of GPR52 loss, MDA-MB-468 cells were injected into zebrafish and loss of GPR52 was associated with a greater total cancer area compared to control cells. RNA-sequencing and proteomic analyses of GPR52-null breast cancer cells reveal an increased cAMP signaling signature. Consistently, we found that treatment of wild-type (WT) cells with forskolin, which stimulates production of cAMP, induces some phenotypic changes associated with GPR52 loss, and inhibition of cAMP production rescued some of the GPR52 KO phenotypes. Overall, our results reveal GPR52 loss as a potential mechanism by which breast cancer progression may occur and support the investigation of GPR52 agonism as a therapeutic option in breast cancer.

hnRNPs: roles in neurodevelopment and implication for brain disorders

Heterogeneous nuclear ribonucleoproteins (hnRNPs) constitute a family of multifunctional RNA-binding proteins able to process nuclear pre-mRNAs into mature mRNAs and regulate gene expression in multiple ways. They comprise at least 20 different members in mammals, named from A (HNRNP A1) to U (HNRNP U). Many of these proteins are components of the spliceosome complex and can modulate alternative splicing in a tissue-specific manner. Notably, while genes encoding hnRNPs exhibit ubiquitous expression, increasing evidence associate these proteins to various neurodevelopmental and neurodegenerative disorders, such as intellectual disability, epilepsy, microcephaly, amyotrophic lateral sclerosis, or dementias, highlighting their crucial role in the central nervous system. This review explores the evolution of the hnRNPs family, highlighting the emergence of numerous new members within this family, and sheds light on their implications for brain development.

Elucidating the nexus between onco-immunology and kidney transplantation: An insight from precision medicine perspective

The interplay of onco-immunology and kidney transplantation heralds a transformative era in medical science. This integration, while promising, presents significant challenges. Chief among these is the dichotomy of immunosuppression-boosting immunity against malignancies while suppressing it for graft survival. Additionally, limited clinical data on novel therapies, genetic variations influencing responses, economic concerns, and the narrow therapeutic window for post-transplant malignancies necessitate strategic addressal. Conversely, opportunities abound, including personalized immune monitoring, targeted therapies, minimized immunosuppression, and improved patient quality of life. Emphasizing collaborative research and interdisciplinary cooperation, the merging of these fields offers the potential for enhanced graft survival and reduced post-transplant malignancy risks. As we harness modern technology and promote patient-centric care, the vision for the future of kidney transplantation becomes increasingly hopeful, paving the way for more personalized and effective treatments. The article aims to elucidate the critical challenge of balancing immunosuppression to simultaneously combat malignancies and ensure graft survival. It addresses the scarcity of clinical data on novel therapies, the impact of genetic variations on treatment responses, and the economic and therapeutic concerns in managing post-transplant malignancies. Furthermore, it explores the opportunities precision medicine offers, such as personalized immune monitoring, targeted therapies, and reduced immunosuppression, which could significantly improve patient outcomes. Highlighting the importance of collaborative research and interdisciplinary efforts, the article seeks to demonstrate the potential for enhanced graft survival and reduced post-transplant malignancy risks. By leveraging modern technology and prioritizing patient-centric care, it envisions a future where kidney transplantation is more personalized and effective, offering hope for advancements in this field.

From complete genomes to pangenomes

Highlighting the Distinguished Speakers Symposium on "The Future of Human Genetics and Genomics," this collection of articles is based on presentations at the ASHG 2023 Annual Meeting in Washington, DC, in celebration of all our field has accomplished in the past 75 years, since the founding of ASHG in 1948.

Revealing Differential RNA Editing Specificity of Human ADAR1 and ADAR2 in Schizosaccharomyces pombe

Adenosine-to-inosine (A-to-I) RNA editing is an important post-transcriptional modification mediated by the adenosine deaminases acting on RNA (ADAR) family of enzymes, expanding the transcriptome by altering selected nucleotides A to I in RNA molecules. Recently, A-to-I editing has been explored for correcting disease-causing mutations in RNA using therapeutic guide oligonucleotides to direct ADAR editing at specific sites. Humans have two active ADARs whose preferences and specificities are not well understood. To investigate their substrate specificity, we introduced hADAR1 and hADAR2, respectively, into Schizosaccharomyces pombe (S. pombe), which lacks endogenous ADARs, and evaluated their editing activities in vivo. Using transcriptome sequencing of S. pombe cultured at optimal growth temperature (30 °C), we identified 483 A-to-I high-confident editing sites for hADAR1 and 404 for hADAR2, compared with the non-editing wild-type control strain. However, these sites were mostly divergent between hADAR1 and hADAR2-expressing strains, sharing 33 common sites that are less than 9% for each strain. Their differential specificity for substrates was attributed to their differential preference for neighboring sequences of editing sites. We found that at the -3-position relative to the editing site, hADAR1 exhibits a tendency toward T, whereas hADAR2 leans toward A. Additionally, when varying the growth temperature for hADAR1- and hADAR2-expressing strains, we observed increased editing sites for them at both 20 and 35 °C, compared with them growing at 30 °C. However, we did not observe a significant shift in hADAR1 and hADAR2's preference for neighboring sequences across three temperatures. The vast changes in RNA editing sites at lower and higher temperatures were also observed for hADAR2 previously in budding yeast, which was likely due to the influence of RNA folding at these different temperatures, among many other factors. We noticed examples of longer lengths of dsRNA around the editing sites that induced editing at 20 or 35 °C but were absent at the other two temperature conditions. We found genes' functions can be greatly affected by editing of their transcripts, for which over 50% of RNA editing sites for both hADAR1 and hADAR2 in S. pombe were in coding sequences (CDS), with more than 60% of them resulting in amino acid changes in protein products. This study revealed the extensive differences in substrate selectivity between the two active human ADARS, i.e., ADAR1 and ADAR2, and provided novel insight when utilizing the two different enzymes for in vivo treatment of human genetic diseases using the RNA editing approach.

ADAR-Mediated A>I(G) RNA Editing in the Genotoxic Drug Response of Breast Cancer

Epitranscriptomics is a field that delves into post-transcriptional changes. Among these modifications, the conversion of adenosine to inosine, traduced as guanosine (A>I(G)), is one of the known RNA-editing mechanisms, catalyzed by ADARs. This type of RNA editing is the most common type of editing in mammals and contributes to biological diversity. Disruption in the A>I(G) RNA-editing balance has been linked to diseases, including several types of cancer. Drug resistance in patients with cancer represents a significant public health concern, contributing to increased mortality rates resulting from therapy non-responsiveness and disease progression, representing the greatest challenge for researchers in this field. The A>I(G) RNA editing is involved in several mechanisms over the immunotherapy and genotoxic drug response and drug resistance. This review investigates the relationship between ADAR1 and specific A>I(G) RNA-edited sites, focusing particularly on breast cancer, and the impact of these sites on DNA damage repair and the immune response over anti-cancer therapy. We address the underlying mechanisms, bioinformatics, and in vitro strategies for the identification and validation of A>I(G) RNA-edited sites. We gathered databases related to A>I(G) RNA editing and cancer and discussed the potential clinical and research implications of understanding A>I(G) RNA-editing patterns. Understanding the intricate role of ADAR1-mediated A>I(G) RNA editing in breast cancer holds significant promise for the development of personalized treatment approaches tailored to individual patients' A>I(G) RNA-editing profiles.

Coding and Non-Coding Transcriptomic Landscape of Aortic Complications in Marfan Syndrome

Marfan syndrome (MFS) is a rare congenital disorder of the connective tissue, leading to thoracic aortic aneurysms (TAA) and dissection, among other complications. Currently, the most efficient strategy to prevent life-threatening dissection is preventive surgery. Periodic imaging applying complex techniques is required to monitor TAA progression and to guide the timing of surgical intervention. Thus, there is an acute demand for non-invasive biomarkers for diagnosis and prognosis, as well as for innovative therapeutic targets of MFS. Unraveling the intricate pathomolecular mechanisms underlying the syndrome is vital to address these needs. High-throughput platforms are particularly well-suited for this purpose, as they enable the integration of different datasets, such as transcriptomic and epigenetic profiles. In this narrative review, we summarize relevant studies investigating changes in both the coding and non-coding transcriptome and epigenome in MFS-induced TAA. The collective findings highlight the implicated pathways, such as TGF-β signaling, extracellular matrix structure, inflammation, and mitochondrial dysfunction. Potential candidates as biomarkers, such as miR-200c, as well as therapeutic targets emerged, like Tfam, associated with mitochondrial respiration, or miR-632, stimulating endothelial-to-mesenchymal transition. While these discoveries are promising, rigorous and extensive validation in large patient cohorts is indispensable to confirm their clinical relevance and therapeutic potential.

Evolution and advancements in genomics and epigenomics in OA research: How far we have come

OBJECTIVE

Osteoarthritis (OA) is the most prevalent musculoskeletal disease affecting articulating joint tissues, resulting in local and systemic changes that contribute to increased pain and reduced function. Diverse technological advancements have culminated in the advent of high throughput "omic" technologies, enabling identification of comprehensive changes in molecular mediators associated with the disease. Amongst these technologies, genomics and epigenomics - including methylomics and miRNomics, have emerged as important tools to aid our biological understanding of disease.

DESIGN

In this narrative review, we selected articles discussing advancements and applications of these technologies to OA biology and pathology. We discuss how genomics, deoxyribonucleic acid (DNA) methylomics, and miRNomics have uncovered disease-related molecular markers in the local and systemic tissues or fluids of OA patients.

RESULTS

Genomics investigations into the genetic links of OA, including using genome-wide association studies, have evolved to identify 100+ genetic susceptibility markers of OA. Epigenomic investigations of gene methylation status have identified the importance of methylation to OA-related catabolic gene expression. Furthermore, miRNomic studies have identified key microRNA signatures in various tissues and fluids related to OA disease.

CONCLUSIONS

Sharing of standardized, well-annotated omic datasets in curated repositories will be key to enhancing statistical power to detect smaller and targetable changes in the biological signatures underlying OA pathogenesis. Additionally, continued technological developments and analysis methods, including using computational molecular and regulatory networks, are likely to facilitate improved detection of disease-relevant targets, in-turn, supporting precision medicine approaches and new treatment strategies for OA.

Genome editing using CRISPR, CAST, and Fanzor systems

Genetic engineering technologies are essential not only for basic science but also for generating animal models for therapeutic applications. The clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein (Cas) system, derived from adapted prokaryotic immune responses, has led to unprecedented advancements in the field of genome editing because of its ability to precisely target and edit genes in a guide RNA-dependent manner. The discovery of various types of CRISPR-Cas systems, such as CRISPR-associated transposons (CASTs), has resulted in the development of novel genome editing tools. Recently, research has expanded to systems associated with obligate mobile element guided activity (OMEGA) RNAs, including ancestral CRISPR-Cas and eukaryotic Fanzor systems, which are expected to complement the conventional CRISPR-Cas systems. In this review, we briefly introduce the features of various CRISPR-Cas systems and their application in diverse animal models.

Membrane Epilipidome-Lipid Modifications, Their Dynamics, and Functional Significance

Lipids are characterized by extremely high structural diversity translated into a wide range of physicochemical properties. As such, lipids are vital for many different functions including organization of cellular and organelle membranes, control of cellular and organismal energy metabolism, as well as mediating multiple signaling pathways. To maintain the lipid chemical diversity and to achieve rapid lipid remodeling required for the responsiveness and adaptability of cellular membranes, living systems make use of a network of chemical modifications of already existing lipids that complement the rather slow biosynthetic pathways. Similarly to biopolymers, which can be modified epigenetically and posttranscriptionally (for nucleic acids) or posttranslationally (for proteins), lipids can also undergo chemical alterations through oxygenation, nitration, phosphorylation, glycosylation, etc. In this way, an expanded collective of modified lipids that we term the "epilipidome," provides the ultimate level of complexity to biological membranes and delivers a battery of active small-molecule compounds for numerous regulatory processes. As many lipid modifications are tightly controlled and often occur in response to extra- and intracellular stimuli at defined locations, the emergence of the epilipidome greatly contributes to the spatial and temporal compartmentalization of diverse cellular processes. Accordingly, epilipid modifications are observed in all living organisms and are among the most consistent prerequisites for complex life.

Deciphering the diagnostic dilemma: A comprehensive review of the Taiwanese cardiac variant in Fabry disease

Molecular diagnosis has undergone rapid and significant advancements in recent years. But because molecular diagnosis can be conducted independently of phenotype, it can engender ambiguity and potential misinterpretations in disease diagnosis. Fabry disease, an X-linked lysosomal storage disorder, arises from a deficiency in α-galactosidase A. In 2002, Ishii and colleagues uncovered a variant (IVS4+919G > A) deep within intron 4 of the GLA gene that could lead to aberrant splicing of the GLA mRNA. This variant is present in 1:875 males in Taiwan, and many patients with hypertrophic cardiomyopathy and the IVS4+919G > A variant are currently treated by enzyme replacement therapy, an expensive treatment. Unfortunately, till now only one article published in 2013 described the outcome of treatment. This review summarized the conflicting evidence about the clinical relevance of the IVS4+919G > A variant, and suggest a multifactorial model, rather than a monogenic model, for the involvement of the IVS4+919G > A variant in hypertrophic cardiomyopathy. The diagnostic dilemma for this Taiwanese cardiac variant in Fabry disease clearly emphasizes the need for precise interpretation and application of molecular diagnostic results.

Lowering pH optimum of activity of SshEstI, a slightly alkaliphilic archaeal esterase of the hormone-sensitive lipase family

SshEstI, a carboxylesterase from the thermoacidophilic archaeon Saccharolobus shibatae, is a member of the hormone-sensitive lipase family that displays slightly alkaliphilic activity with an optimum activity at pH 8.0. In this study, three distinct strategies were explored to confer acidophilic properties to SshEstI. The first strategy involved engineering the oxyanion hole by replacing Gly81 with serine or aspartic acid. The G81S mutant showed optimum activity at pH 7.0, whereas the aspartic acid mutant (G81D) rendered the enzyme slightly acidophilic with optimum activity observed at pH 6.0; however, kcat and kcat/Km values were reduced by these substitutions. The second strategy involved examining the effects of surfactant additives on the pH-activity profiles of SshEstI. The results showed that cetyltrimethylammonium bromide (CTAB) enhanced wild-type enzyme (WT) activity at acidic pH values. In the presence of 0.1 mM CTAB, G81S and G81D were acidophilic enzymes with optimum activity at pH 6.0 and 4.0, respectively, although their enzyme activities were low. The third strategy involved engineering the active site to resemble that of kumamolisin-As (kuma-As), an acidophilic peptidase of the sedolisin family. The catalytic triad of kuma-As was exchanged into SshEstI using site-directed mutagenesis. X-ray crystallographic analysis of the mutants (H274D and H274E) revealed that the potential hydrogen donor-acceptor distances around the active site of WT were fully maintained in these mutants. However, these mutants were inactive at pH 4-8.

p38-MAPK is prerequisite for the synthesis of SARS-CoV-2 protein

The inhibition of p38 mitogen-activated protein kinase (p38-MAPK) by small molecule chemical inhibitors was previously shown to impair severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication, however, mechanisms underlying antiviral activity remains unexplored. In this study, reduced growth of SARS-CoV-2 in p38-α knockout Vero cells, together with enhanced viral yield in cells transfected with construct expressing p38α, suggested that p38-MAPK is essential for the propagation of SARS-CoV-2. The SARS-CoV-2 was also shown to induce phosphorylation (activation) of p38, at time when transcription/translational activities are considered to be at the peak levels. Further, we demonstrated that p38 supports viral RNA/protein synthesis without affecting viral attachment, entry, and budding in the target cells. In conclusion, we provide mechanistic insights on the regulation of SARS-CoV-2 replication by p38 MAPK.

G-quadruplex propensity in H. neanderthalensis, H. sapiens and Denisovans mitochondrial genomes

Current methods of processing archaeological samples combined with advances in sequencing methods lead to disclosure of a large part of H. neanderthalensis and Denisovans genetic information. It is hardly surprising that the genome variability between modern humans, Denisovans and H. neanderthalensis is relatively limited. Genomic studies may provide insight on the metabolism of extinct human species or lineages. Detailed analysis of G-quadruplex sequences in H. neanderthalensis and Denisovans mitochondrial DNA showed us interesting features. Relatively similar patterns in mitochondrial DNA are found compared to modern humans, with one notable exception for H. neanderthalensis. An interesting difference between H. neanderthalensis and H. sapiens corresponds to a motif found in the D-loop region of mtDNA, which is responsible for mitochondrial DNA replication. This area is directly responsible for the number of mitochondria and consequently for the efficient energy metabolism of cell. H. neanderthalensis harbor a long uninterrupted run of guanines in this region, which may cause problems for replication, in contrast with H. sapiens, for which this run is generally shorter and interrupted. One may propose that the predominant H. sapiens motif provided a selective advantage for modern humans regarding mtDNA replication and function.

UHRF1P contributes to IL-17A-mediated systemic lupus erythematosus via UHRF1-MAP4K3 axis

Inflammatory T cells contribute to the pathogenesis of autoimmune diseases such as systemic lupus erythematosus (SLE). Analysis of the T-cell transcriptomics data of two independent SLE patient cohorts by three machine learning models revealed the pseudogene UHRF1P as a novel SLE biomarker. The pseudogene-encoded UHRF1P protein was overexpressed in peripheral blood T cells of SLE patients. The UHRF1P protein lacks the amino-terminus of its parental UHRF1 protein, resulting in missing the proteasome-binding ubiquitin-like (Ubl) domain of UHRF1. T-cell-specific UHRF1P transgenic mice manifested the induction of IL-17A and autoimmune inflammation. Mechanistically, UHFR1P prevented UHRF1-induced Lys48-linked ubiquitination and degradation of MAP4K3 (GLK), which is a kinase known to induce IL-17A. Consistently, IL-17A induction and autoimmune phenotypes of UHRF1P transgenic mice were obliterated by MAP4K3 knockout. Collectively, UHRF1P overexpression in T cells inhibits the E3 ligase function of its parental UHRF1 and induces autoimmune diseases.

A novel method addressing NGS-based mappability bias for sensitive detection of DNA alterations

A turning point in cancer research is the introduction of massively parallel sequencing technology which greatly reduced the cost and time for genome sequencing. This enhanced the scope for detecting and analyzing the role of structural alterations in cancer. However, certain bias exists in NGS-based approaches, which badly affects the CNV identification process. Moreover, DNA repeats existing in CNV regions need special attention as they will degrade the performance of majority of the existing CNV detection tools, even after applying generalized bias correction method. This motivated this work, where a novel method has been designed to address the issue of DNA repeats and thereby mappability bias existing in regions of CNV. The method consists of three phases, where the first phase computes the alignment information of uniquely mapped DNA reads, considering the base quality and base mismatch parameters at nucleotide level precision. The second and the third phase use a novel approach to allocate the non-uniquely mapped reads to an optimal region of the DNA repeats based on a probabilistic membership model. The proposed method is capable of identifying CNVs present in coding, as well as non-coding region of the DNA, and is also capable of detecting CNVs existing in DNA repeat regions. The methodology achieves a sensitivity greater than [Formula: see text] during the performed simulations, and on real data, the detected variants are validated with the database of genomic variants, where the percentage overlap is also greater than 95%, and has achieved much better breakpoint prediction, as compared with other popular bias correction CNV detection methods.

A chromosome-level genome of mango exclusively from long-read sequence data

Improvements in long-read sequencing techniques have greatly accelerated plant genome sequencing. Current de novo assemblies are routinely achieved by assembling long-read sequence data into contigs that are assembled to chromosome level by chromatin conformation capture. We report here a chromosome-level mango genome using only PacBio high-fidelity (HiFi) long reads. HiFi reads at high coverage (204x) resulted in the assembly of 17 chromosomes, each as a single contig with telomeres at both ends. The remaining three chromosomes were represented each by two contigs, with telomeres at one end and ribosomal repeats at the other end. Analyzing contig ends allowed them to be paired and linked to generate the remaining three complete chromosomes, telomere-to-telomere but with ribosomal repeats of uncertain length. The assembled genome was 365 Mb with 100% completeness as assessed by Benchmarking Universal Single-Copy Orthologs analysis. The haplotypes assembled demonstrated extensive structural differences. This approach using very high genome coverage may be useful for assembling high-quality genomes for many other plants.

An eQTL-based approach reveals candidate regulators of LINE-1 RNA levels in lymphoblastoid cells

Long interspersed element 1 (LINE-1; L1) are a family of transposons that occupy ~17% of the human genome. Though a small number of L1 copies remain capable of autonomous transposition, the overwhelming majority of copies are degenerate and immobile. Nevertheless, both mobile and immobile L1s can exert pleiotropic effects (promoting genome instability, inflammation, or cellular senescence) on their hosts, and L1's contributions to aging and aging diseases is an area of active research. However, because of the cell type-specific nature of transposon control, the catalogue of L1 regulators remains incomplete. Here, we employ an eQTL approach leveraging transcriptomic and genomic data from the GEUVADIS and 1000Genomes projects to computationally identify new candidate regulators of L1 RNA levels in lymphoblastoid cell lines. To cement the role of candidate genes in L1 regulation, we experimentally modulate the levels of top candidates in vitro, including IL16, STARD5, HSD17B12, and RNF5, and assess changes in TE family expression by Gene Set Enrichment Analysis (GSEA). Remarkably, we observe subtle but widespread upregulation of TE family expression following IL16 and STARD5 overexpression. Moreover, a short-term 24-hour exposure to recombinant human IL16 was sufficient to transiently induce subtle, but widespread, upregulation of L1 subfamilies. Finally, we find that many L1 expression-associated genetic variants are co-associated with aging traits across genome-wide association study databases. Our results expand the catalogue of genes implicated in L1 RNA control and further suggest that L1-derived RNA contributes to aging processes. Given the ever-increasing availability of paired genomic and transcriptomic data, we anticipate this new approach to be a starting point for more comprehensive computational scans for regulators of transposon RNA levels.

Comprehensive Identification and Characterization of HML-9 Group in Chimpanzee Genome

Endogenous retroviruses (ERVs) are related to long terminal repeat (LTR) retrotransposons, comprising gene sequences of exogenous retroviruses integrated into the host genome and inherited according to Mendelian law. They are considered to have contributed greatly to the evolution of host genome structure and function. We previously characterized HERV-K HML-9 in the human genome. However, the biological function of this type of element in the genome of the chimpanzee, which is the closest living relative of humans, largely remains elusive. Therefore, the current study aims to characterize HML-9 in the chimpanzee genome and to compare the results with those in the human genome. Firstly, we report the distribution and genetic structural characterization of the 26 proviral elements and 38 solo LTR elements of HML-9 in the chimpanzee genome. The results showed that the distribution of these elements displayed a non-random integration pattern, and only six elements maintained a relatively complete structure. Then, we analyze their phylogeny and reveal that the identified elements all cluster together with HML-9 references and with those identified in the human genome. The HML-9 integration time was estimated based on the 2-LTR approach, and the results showed that HML-9 elements were integrated into the chimpanzee genome between 14 and 36 million years ago and into the human genome between 18 and 49 mya. In addition, conserved motifs, cis-regulatory regions, and enriched PBS sequence features in the chimpanzee genome were predicted based on bioinformatics. The results show that pathways significantly enriched for ERV LTR-regulated genes found in the chimpanzee genome are closely associated with disease development, including neurological and neurodevelopmental psychiatric disorders. In summary, the identification, characterization, and genomics of HML-9 presented here not only contribute to our understanding of the role of ERVs in primate evolution but also to our understanding of their biofunctional significance.

Deorphanization of G Protein Coupled Receptors: A Historical Perspective

Counting over 800 members, G protein coupled receptors (GPCRs) form the largest family of membrane receptors encoded in the human genome. Since the discovery of G proteins and GPCRs in the late 1970s and early 1980s, a significant portion of the GPCR research has been focused on identifying ligand/receptor pairs in parallel to studies related to their signaling properties. Despite significant advancements, about a fourth of the ∼400 nonodorant GPCRs are still considered orphan because their natural or endogenous ligands have yet to be identified. We should consider that every GPCR was once an orphan and that endogenous ligands have often been associated with biologic effects without a complete understanding of the molecular identity of their target receptors. Within this framework, this review offers a historical perspective on deorphanization processes for representative GPCRs, including the ghrelin receptor, γ aminobutyric acid B receptor, apelin receptor, cannabinoid receptors, and GPR15. It explores three main scenarios encountered in deorphanization efforts and discusses key questions and methodologies employed in elucidating ligand-receptor interactions, providing insights for future research endeavors. SIGNIFICANCE STATEMENT: Understanding how scientists have historically approached the issue of GPCR deorphanization and pairing of biologically active ligands with their cognate receptors are relevant topics in pharmacology. In fact, the biology of each GPCR, including its pathophysiological involvement, has often been uncovered only after its deorphanization, illuminating druggable targets for various diseases. Furthermore, uncovered endogenous ligands have therapeutic value as many ligands-or derivates thereof-are developed into drugs.

Acute strength exercise training impacts differently the HERV-W expression and inflammatory biomarkers in resistance exercise training individuals

BACKGROUND

Human Endogenous Retroviruses (HERVs) are fossil viruses that composes 8% of the human genome and plays several important roles in human physiology, including muscle repair/myogenesis. It is believed that inflammation may also regulate HERV expression, and therefore may contribute in the muscle repair, especially after training exercise. Hence, this study aimed to assess the level of HERVs expression and inflammation profile in practitioners' resistance exercises after an acute strength training session.

METHODS

Healthy volunteers were separated in regular practitioners of resistance exercise training group (REG, n = 27) and non-trained individuals (Control Group, n = 20). All individuals performed a strength exercise section. Blood samples were collected before the exercise (T0) and 45 minutes after the training session (T1). HERV-K (HML1-10) and W were relatively quantified, cytokine concentration and circulating microparticles were assessed.

RESULTS

REG presented higher level of HERV-W expression (~2.5 fold change) than CG at T1 (p<0.01). No difference was observed in the levels of HERV-K expression between the groups as well as the time points. Higher serum TNF-α and IL-10 levels were verified post-training session in REG and CG (p<0.01), and in REG was found a positive correlation between the levels of TNF-α at T1 and IL-10 at T0 (p = 0.01). Finally, a lower endothelial microparticle percentage was observed in REG at T1 than in T0 (p = 0.04).

CONCLUSION

REG individuals exhibited a significant upregulation of HERV-W and modulation of inflammatory markers when compared to CG. This combined effect could potentially support the process of skeletal muscle repair in the exercised individuals.

Lessons from genetic studies in Alzheimer disease

Research on Alzheimer disease (AD) genetics has provided critical advances to the knowledge of AD pathophysiological mechanisms. The etiology of AD can be divided into monogenic (autosomal dominant inheritance) and complex (multifactorial determinism). In monogenic AD, recent advances mainly concern mutation-associated mechanisms, presymptomatic clinical studies, and the search for modifiers of ages of onset that are still ongoing. In complex AD, genetic factors can be further categorized into three classes: (i) the APOE-ɛ4 and ɛ2 common alleles that represent a category by themselves as they are both common and with a strong impact on AD risk; (ii) common variants with a modest effect, identified in genome-wide association studies (GWAS); and (iii) rare variants with a moderate-to-strong effect, identified in case-control sequencing studies. Regarding APOE, odds ratios, available in multiple ethnicities, can now be converted into penetrance curves, although such curves remain to be performed in diverse ethnicities. In addition, advances in the understanding of mechanisms have been recently reported and rare APOE variants add to the complexity. In the GWAS category, novel loci have been discovered thanks to larger studies, doubling the number of hits as compared to the previous reference meta-analysis. However, such modest risk factors cannot be used in the clinic, neither individually, nor in genetic risk scores. In the category of rare variants, two novel genes, ABCA1 and ATP8B4 now add to the three main ones, TREM2, SORL1, and ABCA7. The study of such rare variants suggests oligogenic inheritance in some families, as also suggested by digenic penetrance curves for SORL1 loss-of-function variants with APOE-ɛ4. Cumulate frequencies of definite (so-called) rare risk factors are 2.3% to 3.6% (depending on thresholds on odds ratios) in control databases and many more remain to be classified and identified, showing how important these risk factors may be as part of the complex determinism of AD. A better understanding of these rare risk factors and their combined effects on each other, with common variants, and with environmental factors, should allow for a prediction of AD risk and, eventually, preventive medicine. Taken together, most genetic determinants of AD, in monogenic and in complex forms, point toward the aggregation of Aβ as a pivotal triggering factor, such that targeting it may be efficient as prevention in at-risk individuals. The role of neuroinflammation, microglia, and Tau pathology modulation are important sources of research for disease modification.

Nanomedomics

Nanomaterials have attractive physicochemical properties. A variety of nanomaterials such as inorganic, lipid, polymers, and protein nanoparticles have been widely developed for nanomedicine via chemical conjugation or physical encapsulation of bioactive molecules. Superior to traditional drugs, nanomedicines offer high biocompatibility, good water solubility, long blood circulation times, and tumor-targeting properties. Capitalizing on this, several nanoformulations have already been clinically approved and many others are currently being studied in clinical trials. Despite their undoubtful success, the molecular mechanism of action of the vast majority of nanomedicines remains poorly understood. To tackle this limitation, herein, this review critically discusses the strategy of applying multiomics analysis to study the mechanism of action of nanomedicines, named nanomedomics, including advantages, applications, and future directions. A comprehensive understanding of the molecular mechanism could provide valuable insight and therefore foster the development and clinical translation of nanomedicines.