Post-genomic Era Research Articles

Advancing vegetable genetics with gene editing: a pathway to food security and nutritional resilience in climate-shifted environments.

As global populations grow and climate change increasingly disrupts agricultural systems, ensuring food security and nutritional resilience has become a critical challenge. In addition to grains and legumes, vegetables are very important for both human and animals because they contain vitamins, minerals, and fibre. Enhancing the ability of vegetables to withstand climate change threats is essential; however, traditional breeding methods face challenges due to the complexity of the genomic clonal multiplication process. In the postgenomic era, gene editing (GE) has emerged as a powerful tool for improving vegetables. GE can help to increase traits such as abiotic stresstolerance, herbicide tolerance, and disease resistance; improve agricultural productivity; and improve nutritional content and shelf-life by fine-tuning key genes. GE technologies such as Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9 (CRISPR-Cas9) have revolutionized vegetable breeding by enabling specific gene modifications in the genome. This review highlights recent advances in CRISPR-mediated editing across various vegetable species, highlighting successful modifications that increase their resilience to climatic stressors. Additionally, it explores the potential of GE to address malnutrition by increasing the nutrient content of vegetable crops, thereby contributing to public health and food system sustainability. Additionally, it addresses the implementation of GE-guided breeding strategies in agriculture, considering regulatory, ethical, and public acceptance issues. Enhancing vegetable genetics via GE may provide a reliable and nutritious food supply for an expanding global population under more unpredictable environmental circumstances.

Elucidating role of long non-coding RNAs of Tamarindus indica Linn. in post-transcriptional gene regulation

Tamarindus indica Linn., commonly known as tamarind, is a rich source of carbohydrates, proteins, lipids, fatty acids, vitamins, minerals and bioactive compounds. It is well established that long non-coding RNAs (lncRNAs) plays an important role in transcriptional, post-transcriptional and epigenetic regulation. Despite the availability of tamarind genome information, a handful of studies have been done on its non-coding genome, especially lncRNAs. In this study, we have computationally predicted lncRNAs from the coding DNA sequences of T. indica and analysed the sequences. We experimentally validated seven randomly chosen lncRNAs by performing quantitative Real Time Polymerase Chain Reaction (qRT-PCR). 320 lncRNAs have been predicted and sequence analysis of these predicted, lncRNAs reveals the presence of different motifs and tandem repeats. Along with the experimental validation of 7 randomly chosen lncRNAs, functional analysis of the predicted lncRNAs and their targets elucidated their roles in various biological pathways. We believe prediction and validation of the lncRNAs along with their interaction with mRNAs will enhance our knowledge about the non-coding genome of tamarind and their involvement in post transcriptional gene regulation, medicinal properties, metabolic engineering, stress tolerance and genome editing.

Overview and Prospects of DNA Sequence Visualization.

Due to advances in big data technology, deep learning, and knowledge engineering, biological sequence visualization has been extensively explored. In the post-genome era, biological sequence visualization enables the visual representation of both structured and unstructured biological sequence data. However, a universal visualization method for all types of sequences has not been reported. Biological sequence data are rapidly expanding exponentially and the acquisition, extraction, fusion, and inference of knowledge from biological sequences are critical supporting technologies for visualization research. These areas are important and require in-depth exploration. This paper elaborates on a comprehensive overview of visualization methods for DNA sequences from four different perspectives-two-dimensional, three-dimensional, four-dimensional, and dynamic visualization approaches-and discusses the strengths and limitations of each method in detail. Furthermore, this paper proposes two potential future research directions for biological sequence visualization in response to the challenges of inefficient graphical feature extraction and knowledge association network generation in existing methods. The first direction is the construction of knowledge graphs for biological sequence big data, and the second direction is the cross-modal visualization of biological sequences using machine learning methods. This review is anticipated to provide valuable insights and contributions to computational biology, bioinformatics, genomic computing, genetic breeding, evolutionary analysis, and other related disciplines in the fields of biology, medicine, chemistry, statistics, and computing. It has an important reference value in biological sequence recommendation systems and knowledge question answering systems.

Phyto-nutraceutical promise of Brassica vegetables in post-genomic era: a comprehensive review.

Brassica vegetables are one of the possible solutions to tackle the emerging human diseases and malnutrition due to their rich content of phyto-nutraceutaical compounds. The genomics enabled tools have facilitated the elucidation of molecular regulation, mapping of genes/QTLs governing nutraceutical compounds, and development of nutrient-rich Brassica vegetables. The enriched food products or foods as whole termed as functional foods are intended to provide health benefits. The 2500year old Hippocratic phrase 'let thy food be thy medicine and thy medicine be thy food' remained in anonymity due to lack of sufficient evidence. However, today, we are facing reappraisal of healthy nutritious functional foods in battling diseases. In this context, the Brassica vegetables represent the most extensively investigated class of functional foods. An optimal consumption of Brassica vegetables is associated with lowering the risks of several types of cancer, chronic diseases, cardiovascular disease, and help in autism. In the post-genomic era, the integration of genetic and neoteric omics tools like transcriptomics, metabolomics, and proteomics have illuminated the downstream genetic mechanisms governing functional food value of Brassica vegetables. In this review, we have summarized in brief the phyto-nutraceutical profile and their functionality in Brassica vegetables. This review also highlights the progress made in identification of candidate genes/QTLs for accumulation of bioactive compounds in Brassica vegetables. We summarize the molecular regulation of major phytochemicals and breeding triumphs in delivering multifunctional Brassica vegetables.

Phylogenetic patterns of understudied species within the plant genus Brassica: Future prospects in the post genomics-era

Phylogenetic patterns of understudied species within the plant genus Brassica: Future prospects in the post genomics-era

Orientia tsutsugamushi infection reduces host gluconeogenic but not glycolytic substrates.

Orientia tsutsugamushi a causal agent of scrub typhus, is an obligate intracellular bacterium that, akin to other rickettsiae, is dependent on host cell-derived nutrients for survival and thus pathogenesis. Based on limited experimental evidence and genome-based in silico predictions, O. tsutsugamushi is hypothesized to parasitize host central carbon metabolism (CCM). Here, we (re-)evaluated O. tsutsugamushi dependency on host cell CCM as initiated by glucose and glutamine. Orientia infection had no effect on host glucose and glutamine consumption or lactate accumulation, indicating no change in overall flux through CCM. However, host cell mitochondrial activity and ATP levels were reduced during infection and correspond with lower intracellular glutamine and glutamate pools. To further probe the essentiality of host CCM in O. tsutsugamushi proliferation, we developed a minimal medium for host cell cultivation and paired it with chemical inhibitors to restrict the intermediates and processes related to glucose and glutamine metabolism. These conditions failed to negatively impact O. tsutsugamushi intracellular growth, suggesting the bacterium is adept at scavenging from host CCM. Accordingly, untargeted metabolomics was utilized to evaluate minor changes in host CCM metabolic intermediates across O. tsutsugamushi infection and revealed that pathogen proliferation corresponds with reductions in critical CCM building blocks, including amino acids and TCA cycle intermediates, as well as increases in lipid catabolism. This study directly correlates O. tsutsugamushi proliferation to alterations in host CCM and identifies metabolic intermediates that are likely critical for pathogen fitness.IMPORTANCEObligate intracellular bacterial pathogens have evolved strategies to reside and proliferate within the eukaryotic intracellular environment. At the crux of this parasitism is the balance between host and pathogen metabolic requirements. The physiological basis driving O. tsutsugamushi dependency on its mammalian host remains undefined. By evaluating alterations in host metabolism during O. tsutsugamushi proliferation, we discovered that bacterial growth is independent of the host's nutritional environment but appears dependent on host gluconeogenic substrates, including amino acids. Given that O. tsutsugamushi replication is essential for its virulence, this study provides experimental evidence for the first time in the post-genomic era of metabolic intermediates potentially parasitized by a scrub typhus agent.

Genetic research and precision medicine practice of childhood epilepsy in the post-genomic era

Genetic research and precision medicine practice of childhood epilepsy in the post-genomic era

Perturbation-specific transcriptional mapping for unbiased target elucidation of antibiotics

The rising prevalence of antibiotic resistance threatens human health. While more sophisticated strategies for antibiotic discovery are being developed, target elucidation of new chemical entities remains challenging. In the postgenomic era, expression profiling can play an important role in mechanism-of-action (MOA) prediction by reporting on the cellular response to perturbation. However, the broad application of transcriptomics has yet to fulfill its promise of transforming target elucidation due to challenges in identifying the most relevant, direct responses to target inhibition. We developed an unbiased strategy for MOA prediction, called perturbation-specific transcriptional mapping (PerSpecTM), in which large-throughput expression profiling of wild-type or hypomorphic mutants, depleted for essential targets, enables a computational strategy to address this challenge. We applied PerSpecTM to perform reference-based MOA prediction based on the principle that similar perturbations, whether chemical or genetic, will elicit similar transcriptional responses. Using this approach, we elucidated the MOAs of three molecules with activity against Pseudomonas aeruginosa by comparing their expression profiles to those of a reference set of antimicrobial compounds with known MOAs. We also show that transcriptional responses to small-molecule inhibition resemble those resulting from genetic depletion of essential targets by clustered regularly interspaced short palindromic repeats interference (CRISPRi) by PerSpecTM, demonstrating proof of concept that correlations between expression profiles of small-molecule and genetic perturbations can facilitate MOA prediction when no chemical entities exist to serve as a reference. Empowered by PerSpecTM, this work lays the foundation for an unbiased, readily scalable, systematic reference-based strategy for MOA elucidation that could transform antibiotic discovery efforts.

Metabolomics in Cardiovascular Diseases

Review Metabolomics in Cardiovascular Diseases Shan Lu 1,†, Zisheng Huang 2,†, Baitao Liu 3, and Yan Zhang 1,* 1 Institute of Cardiovascular Sciences and Key Laboratory of Molecular Cardiovascular Sciences, School of Basic Medical Sciences, Ministry of Education, Peking University Health Science Center, Beijing 100871, China 2 School of Basic Medical Sciences, Peking University, Beijing 100871, China 3 Aerospace School of Clinical Medicine, Peking University, Beijing 100871, China † These authors contributed equally to this work. * Correspondence: zhangyan9876@pku.edu.cn Received: 10 July 2023; Revised: 25 September 2024; Accepted: 26 September 2024; Published: 25 October 2024 Abstract: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and disorders of cardiac energy metabolism are the main contributors to many cardiovascular pathologies. Metabolomics is a science that examines the types and amounts of metabolites and the patterns of change in biological systems after stimulation or perturbation. Metabolites are widely distributed in the body and have universal regulatory effects on a wide range of physiological activities. Metabolism is at the end of the regulation of life activities, so metabolomics is closer to phenotypes than genomics and transcriptom-ics, and can reflect the state of biological systems more accurately. Metabolomics, a cross-cutting dis-cipline emerging in the post-genomics era, has rapidly penetrated into many fields of medicine, im-proves understanding of complex diseases and generates more new discoveries and hypotheses. Therefore, metabolomics helps detect metabolic changes in the course of CVDs, search for biomarkers, and further study the pathogenesis of CVDs. In this review, we intend to comprehensively summarize the principles, classification and applications in CVDs of metabolomics.

The current status and improvement directions of legal rules regarding Chinese national gene banks for farm animal genetic resources.

A gene bank for farm animal genetic resources (FAGR) is an important facility for the diversity conservation of FAGR. The primary purpose of gene banks for FAGR is the reconstruction of those breeds. With the advent of the post-genomic era, gene banks for FAGR have increasingly become an infrastructure for the support of livestock research and animal breeding, and a platform for international research collaboration. China is one of the richest countries in the world in terms of FAGR. Chinese National Gene Banks for FAGR (CNGBFs) have an important legal status and play an important function in the Chinese FAGR protection system. In this paper, we reviewed the current situation of CNGBFs construction, and systematically collected and analyzed legal rules related to CNGBFs. As results, those legal rules were categorized into two types: (a) organization and management, (b) activities. We summarized problems existing in the current legal rules for CNGBFs from three levels: institution, practical operation, and digital development. Improvement directions of legal rules regarding CNGBFs are proposed. They include clarifying the utilization function of CNGBFs and the ownership of FAGR in CNGBFs. Moreover, improving the mechanism of administrative management, rules on domestic and international access and benefit-sharing, and the system of digital sequence information management are also suggested. The improvements in those legal rules will contribute to the appropriate utilization of Chinese FAGR and international collaborations.

323 Advances in using membrane vesicles for studying intestinal functions

Abstract Enterocytes are the major cell lineage of the small intestinal epithelia along the crypt-villus axis in gut mucosa. Enterocytes participate in the gut terminal nutrient digestion and absorption; and have essential roles in nutrient and metabolite recycling and efflux, nutrient and hormonal sensing, interactions with symbiotic microbiome and binding to infectious viruses, thus influencing the host homeostasis and whole-body physiological status. Intestinal membrane vesicles have been widely used for studying various gut functions in the past several decades. Villus enterocytic brush border membrane and the apical membrane vesicles along the crypt-villus axis in gut mucosa can be prepared and isolated by Mg2+- and Ca2+-precipitation and differential centrifugation procedures. Whereas, gut mucosal basolateral membrane vesicles can be prepared, fractionated and differentiated from other intracellular organelles such as the mitochondrial inner membrane by the Percoll gradient ultracentrifugation. Nutrient transport and exchange activities in the membrane vesicles in vitro are conducted often by rapid hand filtration, and in excess, in an automated fast sampling apparatus. Nutrient transport and exchange activity kinetics are derived according to the well-established classic Michaelis-Menten and the tracer inhibitory kinetic models with a simple linear diffusional component. Physiological and biochemical properties associated with various nutrient uptake systems such as pH optimum, requirements for co-transported ions (e.g., Na+, K+, Cl-), transporter affinity and substrate specificity can be effectively investigated in vitro with the membrane vesicles by altering the compositions of uptake buffers and intra-vesicular pre-loading buffers. Some of the fundamental gut functions are established via using the membrane vesicles in different mammalian species. And these include H+-peptide cotransport, Na+-cotransport and Na+-independent systems of hexose uptake across the apical membrane and the low-affinity Na+-independent hexose bidirectional uptake across the basolateral membrane that were characterized in rodents; Na+-dependent cotransport and Na+-independent systems of amino acid (AA) transport across the apical membrane that were revealed in rodents and pigs; as well as the Na+-hexose and AA cotransport and the co-expression of the coronavirus SARS-CoV-2 host epithelial apical membrane binding receptor, i.e., the angiotensin-converting enzyme-2 (ACE2), along the gut crypt-villus axis that were identified in liquid formula-fed piglets. In the post genomic and metagenomic sequencing era, further research efforts need to pursue understanding of expression and various functionality of the gut terminal hydrolases, nutrient transporters, nutrient exchangers, nutrient sensors, substrate and particle receptors, taste receptors, viral binding receptors such as ACE2 and hormonal receptors and their interactions with luminal factors such as nutrient, metabolites, symbiotic bacterial outer membrane vesicles etc., along the longitudinal and crypt-villus axes, through using the mammalian primary enterocytic apical and the basolateral membrane vesicles under various research settings.

Radiotherapy and breast cancer: finally, an lncRNA perspective on radiosensitivity and radioresistance.

Radiotherapy (RT) serves as one of the key adjuvant treatments in management of breast cancer. Nevertheless, RT has two major problems: side effects and radioresistance. Given that patients respond differently to RT, it is imperative to understand the molecular mechanisms underlying these differences. Two-thirds of human genes do not encode proteins, as we have realized from genome-scale studies conducted after the advent of the genomic era; nevertheless, molecular understanding of breast cancer to date has been attained almost entirely based on protein-coding genes and their pathways. Long non-coding RNAs (lncRNAs) are a poorly understood but abundant class of human genes that yield functional non-protein-coding RNA transcripts. Here, we canvass the field to seek evidence for the hypothesis that lncRNAs contribute to radioresistance in breast cancer. RT-responsive lncRNAs ranging from "classical" lncRNAs discovered at the dawn of the post-genomic era (such as HOTAIR, NEAT1, and CCAT), to long intergenic lncRNAs such as LINC00511 and LINC02582, antisense lncRNAs such as AFAP-AS1 and FGD5-AS1, and pseudogene transcripts such as DUXAP8 were found during our screen of the literature. Radiation-related pathways modulated by these lncRNAs include DNA damage repair, cell cycle, cancer stem cells phenotype and apoptosis. Thus, providing a clear picture of these lncRNAs' underlying RT-relevant molecular mechanisms should help improve overall survival and optimize the best radiation dose for each individual patient. Moreover, in healthy humans, lncRNAs show greater natural expression variation than protein-coding genes, even across individuals, alluding to their exceptional potential for targeting in truly personalized, precision medicine.

Distribution rules of 8-mer spectra and characterization of evolution state in animal genome sequences

BackgroundStudying the composition rules and evolution mechanisms of genome sequences are core issues in the post-genomic era, and k-mer spectrum analysis of genome sequences is an effective means to solve this problem.ResultWe divided total 8-mers of genome sequences into 16 kinds of XY-type due to XY dinucleotides number in 8-mers. Previous works explored that the independent unimodal distributions observed only in three CG-type 8-mer spectra, while non-CG type 8-mer spectra have not the universal phenomenon from prokaryotes to eukaryotes. On this basis, we analyzed the distribution variation of non-CG type 8-mer spectra across 889 animal genome sequences. Following the evolutionary order of animals from primitive to more complex, we found that the spectrum distributions gradually transition from unimodal to tri-modal. The relative distance from the average frequency of each non-CG type 8-mers to the center frequency is different within a species and among different species. For the 8-mers contain CG dinucleotides, we further divided these into 16 subsets, where each 8-mer contains both CG and XY dinucleotides, called XY1_CG1 subsets. We found that the separability values of XY1_CG1 spectra are closely related to the evolution and specificity of animals. Considering the constraint of Chargaff’s second parity rule, we finally obtained 10 separability values as the feature set to characterize the evolution state of genome sequences. In order to verify the rationality of the feature set, we used 14 common classification algorithms to perform binary classification tests. The results showed that the accuracy (Acc) ranged between 98.70% and 83.88% among birds, other vertebrates and mammals.ConclusionWe proposed a credible feature set to characterizes the evolution state of genomes and obtained satisfied results by the feature set on large scale classification of animals.

A Review of the Regulatory Challenges of Personalized Medicine.

Personalized medicine integrates genomics with clinical and familial histories, revolutionizing healthcare by tailoring treatments to individual patient characteristics. At its core, pharmacogenomics enables the customization of medication prescriptions based on genetic profiles, enhancing drug efficacy and safety. This precision medicine approach addresses disease diagnosis, prevention, and treatment, offering targeted therapies for conditions like autoimmune disorders, rheumatoid arthritis, and neoplastic conditions. Examples of pharmacogenomics and personalized medicine include treatment for certain conditions like blood clotting disorders (warfarin (blood thinner), genetic variability, acute lymphoblastic leukemia (ALL), and thiopurine methyltransferase (TPMT) testing) in leukemia treatment. Historically, personalized medicine has evolved from Hippocrates' humoral theories to modern molecular diagnostics. The shift from cellular to molecular-level investigations has led to the current post-genomic era, emphasizing the four chemical components of DNA in understanding and treating disorders. This evolution enhances our ability to predict disease susceptibility, treatment response, and potential adverse reactions, demanding advancements in privacy laws, payment systems, regulatory standards, and education. Personalized healthcare optimizes treatment by considering genetic, environmental, and lifestyle factors, reducing adverse reactions, and improving patient satisfaction. It drives genomic and biotechnological research, fostering the development of targeted therapies and diagnostic tools, and streamlining drug development. Applications in lung cancer, renal carcinoma, and rheumatoid arthritis (RA) illustrate the efficacy of personalized medicine. Targeted therapies, such as tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs), show significant success in lung cancer. Biomarkers guide renal carcinoma treatments, while gene expression profiles predict rheumatoid arthritis outcomes with tumor necrosis factor-alpha (TNF-α) blockers. The US FDA's increasing approvals of personalized treatments underscore its commitment to precision medicine. However, regulatory challenges persist, necessitating clear processes and policies. Ethical considerations, including equitable access and privacy, are critical for responsible implementation. The FDA's increasing approvals of personalized treatments highlight its commitment to advancing precision medicine, yet regulatory challenges remain, requiring the development of clear processes and policies to manage innovation safely. While these hurdles are being addressed through evolving guidelines and collaborative efforts, ethical considerations, including equitable access and privacy, are critical for responsible implementation. Early examples, such as warfarin and imatinib, demonstrate the role of genetic information in guiding treatment, illustrating the potential of personalized medicine to optimize healthcare outcomes.

Precision Cancer Medicine 2.0-Oncology in the postgenomic era.

Genomic medicine has transformed the lives of patients with cancer byenabling individualised and evidence-based clinical decision-making. Despite this progress, the implementation of precision cancer medicine is limited by its dependence on isolated biomarkers. The development of bulk and single-cell multiomic technologies has revealed the enormous complexity of the cancer ecosystem. Beyond the cancer cell, the tumour microenvironment, macroenvironment and host factors, including the microbiome, profoundly influence the cancer phenotype, and accounting for these enhances the resolution of precision medicine. The advent of robust multiomic profiling and interpretable machine learning algorithms mark the dawn of a new postgenomic era of personalised cancer medicine. In Precision Cancer Medicine 2.0, high-resolution personalised clinical decision-making is informed by the comprehensive multiomic profiling of tumour and host, integrated using artificial intelligence.

Triumphs and Challenges of Natural Product Discovery in the Postgenomic Era.

Natural products have played significant roles as medicine and food throughout human history. Here, we first provide a brief historical overview of natural products, their classification and biosynthetic origins, and the microbiological and genetic methods used for their discovery. We also describe and discuss the technologies that revolutionized the field, which transitioned from classic genetics to genome-centric discovery approximately two decades ago. We then highlight the most recent advancements and approaches in the current postgenomic era, in which genome mining is a standard operation and high-throughput analytical methods allow parallel discovery of genes and molecules at an unprecedented pace. Finally, we discuss the new challenges faced by the field of natural products and the future of systematic heterologous expression and strain-independent discovery, which promises to deliver more molecules in vials than ever before.

'Wild Type'.

In this opinion piece, we consider the meaning of the term 'wild type' in the context of microbiology. This is especially pertinent in the post-genomic era, where we have a greater awareness of species diversity than ever before. Genomic heterogeneity, in vitro evolution/selection pressures, definition of 'the wild', the size and importance of the pan-genome, gene-gene interactions (epistasis), and the nature of the 'wild-type gene' are all discussed. We conclude that wild type is an outdated and even misleading phrase that should be gradually phased out.

Revisiting Epigenetics Fundamentals and Its Biomedical Implications.

In light of the post-genomic era, epigenetics brings about an opportunity to better understand how the molecular machinery works and is led by a complex dynamic set of mechanisms, often intricate and complementary in many aspects. In particular, epigenetics links developmental biology and genetics, as well as many other areas of knowledge. The present work highlights substantial scopes and relevant discoveries related to the development of the term from its first notions. To our understanding, the concept of epigenetics needs to be revisited, as it is one of the most relevant and multifaceted terms in human knowledge. To redirect future novel experimental or theoretical efforts, it is crucial to compile all significant issues that could impact human and ecological benefit in the most precise and accurate manner. In this paper, the reader can find one of the widest compilations of the landmarks and epistemic considerations of the knowledge of epigenetics across the history of biology from the earliest epigenetic formulation to genetic determinism until the present. In the present work, we link the current body of knowledge and earlier pre-genomic concepts in order to propose a new definition of epigenetics that is faithful to its regulatory nature.

Systemic Therapy in Breast Cancer.

Therapeutic advances in breast cancer have significantly improved outcomes in recent decades. In the early setting, there has been a gradual shift from adjuvant-only to neoadjuvant strategies, with a growing focus on customizing post-neoadjuvant treatments through escalation and de-escalation based on pathologic response. At the same time, the transition from a pre-genomic to a post-genomic era, utilizing specific assays in the adjuvant setting and targeted sequencing in the advanced stage, has deepened our understanding of disease biology and aided in identifying molecular markers associated with treatment benefit. Finally, the introduction of new drug classes such as antibody-drug conjugates, and the incorporation in the (neo)adjuvant setting of therapies previously investigated in the advanced stage, like immunotherapy and CDK4-6 inhibitors, poses new challenges in treatment sequencing.

Emerging roles of long non-coding RNAs in human epilepsy.

Genome-scale biological studies conducted in the post-genomic era have revealed that two-thirds of human genes do not encode proteins. Most functional non-coding RNA transcripts in humans are products of long non-coding RNA (lncRNA) genes, an abundant but still poorly understood class of human genes. As a result of their fundamental and multitasking regulatory roles, lncRNAs are associated with a wide range of human diseases, including neurological disorders. Approximately 40% of lncRNAs are specifically expressed in the brain, and many of them exhibit distinct spatiotemporal patterns of expression. Comparative genomics approaches have determined that 65%-75% of human lncRNA genes are primate-specific and hence can be posited as a contributing potential cause of the higher-order complexity of primates, including human, brains relative to those of other mammals. Although lncRNAs present important mechanistic examples of epileptogenic functions, the human/primate specificity of lncRNAs questions their relevance in rodent models. Here, we present an in-depth review that supports the contention that human lncRNAs are direct contributors to the etiology and pathogenesis of human epilepsy, as a means to accelerate the integration of lncRNAs into clinical practice as potential diagnostic biomarkers and therapeutic targets. Meta-analytically, the major finding of our review is the commonality of lncRNAs in epilepsy and cancer pathogenesis through mitogen-activated protein kinase (MAPK)-related pathways. In addition, neuroinflammation may be a relevant part of the common pathophysiology of cancer and epilepsy. LncRNAs affect neuroinflammation-related signaling pathways such as nuclear factor kappa- light- chain- enhancer of activated B cells (NF-κB), Notch, and phosphatidylinositol 3- kinase/ protein kinase B (Akt) (PI3K/AKT), with the NF-κB pathway being the most common. Besides the controversy over lncRNA research in non-primate models, whether neuroinflammation is triggered by injury and/or central nervous system (CNS) toxicity during epilepsy modeling in animals or is a direct consequence of epilepsy pathophysiology needs to be considered meticulously in future studies.