Gene regulatory network analysis identifies MYL1, MDH2, GLS, and TRIM28 as the principal proteins in the response of mesenchymal stem cells to Mg2+ ions

Magnesium (Mg)-based implants have emerged as a promising alternative for orthopedic applications, owing to their bioactive properties and biodegradability. As the implants degrade, Mg2+ ions are released, influencing all surrounding cell types, especially mesenchymal stem cells (MSCs). MSCs are vital for bone tissue regeneration, therefore, it is essential to understand their molecular response to Mg2+ ions in order to maximize the potential of Mg-based biomaterials. In this study, we conducted a gene regulatory network (GRN) analysis to examine the molecular responses of MSCs to Mg2+ ions. We used time-series proteomics data collected at 11 time points across a 21-day period for the GRN construction. We studied the impact of Mg2+ ions on the resulting networks and identified the key proteins and protein interactions affected by the application of Mg2+ ions. Our analysis highlights MYL1, MDH2, GLS, and TRIM28 as the primary targets of Mg2+ ions in the response of MSCs during 1-21 days phase. Our results also identify MDH2-MYL1, MDH2-RPS26, TRIM28-AK1, TRIM28-SOD2, and GLS-AK1 as the critical protein relationships affected by Mg2+ ions. By offering a comprehensive understanding of the regulatory role of Mg2+ ions on MSCs, our study contributes valuable insights into the molecular response of MSCs to Mg-based materials, thereby facilitating the development of innovative therapeutic strategies for orthopedic applications.

Computation-guided transcription factor biosensor specificity engineering for adipic acid detection

Transcription factor (TF)-based biosensors that connect small-molecule sensing with readouts such as fluorescence have proven to be useful synthetic biology tools for applications in biotechnology. However, the development of specific TF-based biosensors is hindered by the limited repertoire of TFs specific for molecules of interest since current construction methods rely on a limited set of characterized TFs. In this study, we present an approach for engineering the specificity of TFs through a computation-based workflow using molecular docking that enables targeted alteration of TF ligand specificity. Using this method, we engineer the LysR family BenM TF to alter its specificity from its cognate ligand cis,cis-muconic acid to adipic acid through a single amino acid substitution identified by our computational workflow. When implemented in a cell-free system, the engineered biosensor shows higher ligand sensitivity, expanding the potential applications of this circuit. We further investigate ligand binding through molecular dynamics to analyze the substitution, elucidating the impact of modulating a single amino acid position on the mechanism of BenM ligand binding. This study represents the first application of biomolecular modeling methods for altering BenM specificity and for gaining insights into how mutations influence the structural dynamics of BenM. Such methods can potentially be applied to other TFs to alter specificity and analyze the dynamics responsible for these changes, highlighting the applicability of computational tools for informing experiments. In addition, our developed adipic acid biosensor can be applied for the identification and engineering of enzymes to produce adipic acid.

Computational modeling for deciphering tissue microenvironment heterogeneity from spatially resolved transcriptomics

Spatial transcriptomics techniques, while measuring gene expression, retain spatial location information, aiding in situ studies of organismal tissue architecture and the progression of pathological processes. These techniques generate vast amounts of omics data, necessitating the development of computational methods to reveal the underlying tissue microenvironment heterogeneity. The main directions in spatial transcriptomics data analysis are spatial domain detection and spatial deconvolution, which can identify spatial functional regions and parse the distribution of cell types in spatial transcriptomics data by integrating single-cell transcriptomics data. In these two research directions, many computational methods have been successively proposed. This article will categorize them into three types: machine learning-based methods, probabilistic models-based methods, and deep learning-based methods. It will list and discuss the representative algorithms of each type along with their advantages and disadvantages and describe the datasets and evaluation metrics used to assess these computational methods, facilitating researchers in selecting suitable computational methods according to their research needs. Finally, combining the latest technological developments and the advantages and disadvantages of current algorithms, this article will look forward to the future directions of computational method development.

Analysis of Haemonchus embryos at single cell resolution identifies two eukaryotic elongation factors as intervention target candidates

Advances in single cell technologies are allowing investigations of a wide range of biological processes and pathways in animals, such as the multicellular model organism Caenorhabditis elegans - a free-living nematode. However, there has been limited application of such technology to related parasitic nematodes which cause major diseases of humans and animals worldwide. With no vaccines against the vast majority of parasitic nematodes and treatment failures due to drug resistance or inefficacy, new intervention targets are urgently needed, preferably informed by a deep understanding of these nematodes' cellular and molecular biology - which is presently lacking for most worms. Here, we created the first single cell atlas for an early developmental stage of Haemonchus contortus - a highly pathogenic, C. elegans-related parasitic nematode. We obtained and curated RNA sequence (snRNA-seq) data from single nuclei from embryonating eggs of H. contortus (150,000 droplets), and selected high-quality transcriptomic data for > 14,000 single nuclei for analysis, and identified 19 distinct clusters of cells. Guided by comparative analyses with C. elegans, we were able to reproducibly assign seven cell clusters to body wall muscle, hypodermis, neuronal, intestinal or seam cells, and identified eight genes that were transcribed in all cell clusters/types, three of which were inferred to be essential in H. contortus. Two of these genes (i.e. Hc-eef-1A and Hc-eef1G), coding for eukaryotic elongation factors (called Hc-eEF1A and Hc-eEF1G), were also demonstrated to be transcribed and expressed in all key developmental stages of H. contortus. Together with these findings, sequence- and structure-based comparative analyses indicated the potential of Hc-eEF1A and/or Hc-eEF1G as intervention targets within the protein biosynthesis machinery of H. contortus. Future work will focus on single cell studies of all key developmental stages and tissues of H. contortus, and on evaluating the suitability of the two elongation factor proteins as drug targets in H. contortus and related nematodes, with a view to finding new nematocidal drug candidates.

Genome-wide analysis reveals the contributors to fast molecular evolution of the Chinese hook snout carp (Opsariichthys bidens)

Variations in molecular evolutionary rate have been widely investigated among lineages and genes. However, it remains an open question whether fast rate of molecular evolution is driven by natural selection or random drift, and how the fast rate is linked to metabolic rate. Additionally, previous studies on fast molecular evolution have been largely restricted to concatenated matrix of genes or a few specifically selected genes, but less is known for individual genes at the genome-wide level. Here we addressed these questions using more than 5000 single-copy orthologous (SCO) genes through comparative genomic and phylogenetic analyses among fishes, with a special focus on a newly-sequenced clupeocephalan fish the Chinese hook snout carp Opsariichthys bidens. We showed O. bidens displays significantly higher mean substitution rate and more fast-evolving SCO genes (2172 genes) than most fishes studied here. The rapidly evolving genes are enriched in highly conserved and very basic functions such as translation and ribosome that are critical for biological fitness. We further revealed that ∼25 % of these fast-evolving genes exhibit a constant increase of substitution rate from the common ancestor down to the present, suggesting a neglected but important contribution from ancestral states. Model fitting showed that ∼85 % of fast-evolving genes exclusive to O. bidens and related species follow the adaptive evolutionary model rather than random-drift model, and 7.6 % of fast-evolving genes identified in O. bidens have experienced positive selection, both indicating the reflection of adaptive selection. Finally, metabolic rate was observed to be linked with substitution rate in a gene-specific manner. Overall, our findings reveal fast molecular evolution of SCO genes at genome-wide level in O. bidens, and uncover the evolutionary and ecological contributors to it.

MIMOSA: a resource consisting of improved methylome prediction models increases power to identify DNA methylation-phenotype associations

Although DNA methylation (DNAm) has been implicated in the pathogenesis of numerous complex diseases, from cancer to cardiovascular disease to autoimmune disease, the exact methylation sites that play key roles in these processes remain elusive. One strategy to identify putative causal CpG sites and enhance disease etiology understanding is to conduct methylome-wide association studies (MWASs), in which predicted DNA methylation that is associated with complex diseases can be identified. However, current MWAS models are primarily trained using the data from single studies, thereby limiting the methylation prediction accuracy and the power of subsequent association studies. Here, we introduce a new resource, MWAS Imputing Methylome Obliging Summary-level mQTLs and Associated LD matrices (MIMOSA), a set of models that substantially improve the prediction accuracy of DNA methylation and subsequent MWAS power through the use of a large summary-level mQTL dataset provided by the Genetics of DNA Methylation Consortium (GoDMC). Through the analyses of GWAS (genome-wide association study) summary statistics for 28 complex traits and diseases, we demonstrate that MIMOSA considerably increases the accuracy of DNA methylation prediction in whole blood, crafts fruitful prediction models for low heritability CpG sites, and determines markedly more CpG site-phenotype associations than preceding methods. Finally, we use MIMOSA to conduct a case study on high cholesterol, pinpointing 146 putatively causal CpG sites.

Databases and computational methods for the identification of piRNA-related molecules: A survey

Piwi-interacting RNAs (piRNAs) are a class of small non-coding RNAs (ncRNAs) that plays important roles in many biological processes and major cancer diagnosis and treatment, thus becoming a hot research topic. This study aims to provide an in-depth review of computational piRNA-related research, including databases and computational models. Herein, we perform literature analysis and use comparative evaluation methods to summarize and analyze three aspects of computational piRNA-related research: (i) computational models for piRNA-related molecular identification tasks, (ii) computational models for piRNA-disease association prediction tasks, and (iii) computational resources and evaluation metrics for these tasks. This study shows that computational piRNA-related research has significantly progressed, exhibiting promising performance in recent years, whereas they also suffer from the emerging challenges of inconsistent naming systems and the lack of data. Different from other reviews on piRNA-related identification tasks that focus on the organization of datasets and computational methods, we pay more attention to the analysis of computational models, algorithms, and performances that aim to provide valuable references for computational piRNA-related identification tasks. This study will benefit the theoretical development and practical application of piRNAs by better understanding computational models and resources to investigate the biological functions and clinical implications of piRNA.

Animal models of lupus nephritis: the past, present and a future outlook

Lupus nephritis (LN) is the most severe end-organ pathology in Systemic Lupus Erythematosus (SLE). Research has enhanced our understanding of immune effectors and inflammatory pathways in LN. However, even with the best available therapy, the rate of complete remission for proliferative LN remains below 50%. A deeper understanding of the resistance or susceptibility of renal cells to injury during the progression of SLE is critical for identifying new targets and developing effective long-term therapies. The complex and heterogeneous nature of LN, combined with the limitations of clinical research, make it challenging to investigate the aetiology of this disease directly in patients. Hence, multiple murine models resembling SLE-driven nephritis are utilised to dissect LN's cellular and genetic mechanisms, identify therapeutic targets, and screen novel compounds. This review discusses commonly used spontaneous and inducible mouse models that have provided insights into pathogenic mechanisms and long-term maintenance therapies in LN.

Advanced computational predictive models of miRNA-mRNA interaction efficiency

The modeling of miRNA-mRNA interactions holds significant implications for synthetic biology and human health. However, this research area presents specific challenges due to the multifaceted nature of mRNA downregulation by miRNAs, influenced by numerous factors including competition or synergism among miRNAs and mRNAs. In this study, we present an improved computational model for predicting miRNA-mRNA interactions, addressing aspects not previously modeled. Firstly, we integrated a novel set of features that significantly enhanced the predictor's performance. Secondly, we demonstrated the cell-specific nature of certain aspects of miRNA-mRNA interactions, highlighting the importance of designing models tailored to specific cell types for improved accuracy. Moreover, we introduce a miRNA binding site interaction model (miBSIM) that, for the first time, accounts for both the distribution of miRNA binding sites along the mRNA and their respective strengths in regulating mRNA stability. Our analysis suggests that distant miRNA sites often compete with each other, revealing the intricate interplay of binding site interactions. Overall, our new predictive model shows a significant improvement of up to 6.43% over previous models in the field. The code of our model is available at https://www.cs.tau.ac.il/~tamirtul/miBSIM.

Techniques for assessing telomere length: A methodological review

Telomeres are located at the ends of chromosomes and have specific sequences with a distinctive structure that safeguards genes. They possess capping structures that protect chromosome ends from fusion events and ensure chromosome stability. Telomeres shorten in length during each cycle of cell division. When this length reaches a certain threshold, it can lead to genomic instability, thus being implicated in various diseases, including cancer and neurodegenerative disorders. The possibility of telomeres serving as a biomarker for aging and age-related disease is being explored, and their significance is still under study. This is because post-mitotic cells, which are mature cells that do not undergo mitosis, do not experience telomere shortening due to age. Instead, other causes, for example, exposure to oxidative stress, can directly damage the telomeres, causing genomic instability. Nonetheless, a general agreement has been established that measuring telomere length offers valuable insights and forms a crucial foundation for analyzing gene expression and epigenetic data. Numerous approaches have been developed to accurately measure telomere lengths. In this review, we summarize various methods and their advantages and limitations for assessing telomere length.

RIscoper 2.0: A deep learning tool to extract RNA biomedical relation sentences from literature

RNA plays an extensive role in a multi-dimensional regulatory system, and its biomedical relationships are scattered across numerous biological studies. However, text mining works dedicated to the extraction of RNA biomedical relations remain limited. In this study, we established a comprehensive and reliable corpus of RNA biomedical relations, recruiting over 30,000 sentences manually curated from more than 15,000 biomedical literature. We also updated RIscoper 2.0, a BERT-based deep learning tool to extract RNA biomedical relation sentences from literature. Benefiting from approximately 100,000 annotated named entities, we integrated the text classification and named entity recognition tasks in this tool. Additionally, RIscoper 2.0 outperformed the original tool in both tasks and can discover new RNA biomedical relations. Additionally, we provided a user-friendly online search tool that enables rapid scanning of RNA biomedical relationships using local and online resources. Both the online tools and data resources of RIscoper 2.0 are available at http://www.rnainter.org/riscoper.

FOXA1 co-activates circODC1 and ODC1 in HPV-positive cervical cancer cell growth

As demonstrated in previous research, hsa_circ_0052602 (circODC1) is dynamically expressed in HPV-positive cervical cancer (CC). CircODC1 expression was quantified using qRT-PCR, and its role in CC cell growth was assessed via loss-of-function assays. Interactions between miR-607 and circODC1 or ODC1 were confirmed using bioinformatics and mechanistic assays. The association of FOXA1 with the circODC1 promoter was validated through ChIP and luciferase reporter assays. CircODC1 was highly expressed in HPV-positive CC cell lines, and its depletion significantly impeded malignant processes such as proliferation, migration, and invasion. We found that ODC1 also played an oncogenic role in HPV-positive CC cells. CircODC1 was shown to positively regulate ODC1 as a ceRNA, competitively binding to miR-607 to counteract its suppression of ODC1. HPV-associated FOXA1 was identified as a potential transcription factor of circODC1. Restoration experiments showed that overexpression of circODC1 could counterbalance the inhibitory effect of FOXA1 knockdown. These findings offer new insights into therapeutic strategies for HPV-positive CC patients.

The interregulatory circuit between non-coding RNA and apoptotic signaling in diabetic cardiomyopathy

Diabetes mellitus has surged in prevalence, emerging as a prominent epidemic and assuming a foremost position among prevalent medical disorders. Diabetes constitutes a pivotal risk element for cardiovascular maladies, with diabetic cardiomyopathy (DCM) standing out as a substantial complication encountered by individuals with diabetes. Apoptosis represents a physiological phenomenon observed throughout the aging and developmental stages, giving rise to the programmed cell death, which is implicated in DCM. Non-coding RNAs assume significant functions in modulation of gene expression. Their deviant expression of ncRNAs is implicated in overseeing diverse cellular attributes such as proliferation, apoptosis, and has been postulated to play a role in the progression of DCM. Notably, ncRNAs and the process of apoptosis can mutually influence and cooperate in shaping the destiny of human cardiac tissues. Therefore, the exploration of the interplay between apoptosis and non-coding RNAs holds paramount importance in the formulation of efficacious therapeutic and preventive approaches for managing DCM. In this review, we provide a comprehensive overview of the apoptotic signaling pathways relevant to DCM and subsequently delve into the reciprocal regulation between apoptosis and ncRNAs in DCM. These insights contribute to an enhanced comprehension of DCM and the development of therapeutic strategies.

Noncoding RNAs in chronic obstructive pulmonary disease: From pathogenesis to therapeutic targets

Chronic obstructive pulmonary disease (COPD) is the most prevalent chronic respiratory disorder that is becoming the leading cause of morbidity and mortality on a global scale. There is an unmet need to investigate the underlying pathophysiological mechanisms and unlock novel therapeutic avenues for COPD. Recent research has shed light on the significant roles played by diverse noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), in orchestrating the development and progression of COPD. This review provides an overview of the regulatory roles of ncRNAs in COPD, elucidating their underlying mechanisms, and illuminating the potential prospects of RNA-based therapeutics in the management of COPD.

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

A global view of altered ligand-receptor interactions in bone marrow aging based on single-cell sequencing

Altered cell-cell communication is a hallmark of aging, but its impact on bone marrow aging remains poorly understood. Based on a common and effective pipeline and single-cell transcriptome sequencing, we detected 384,124 interactions including 2575 ligand-receptor pairs and 16 non-adherent bone marrow cell types in old and young mouse and identified a total of 5560 significantly different interactions, which were then verified by flow cytometry and quantitative real-time PCR. These differential ligand-receptor interactions exhibited enrichment for the senescence-associated secretory phenotypes. Further validation demonstrated supplementing specific extracellular ligands could modify the senescent signs of hematopoietic stem cells derived from old mouse. Our work provides an effective procedure to detect the ligand-receptor interactions based on single-cell sequencing, which contributes to understand mechanisms and provides a potential strategy for intervention of bone marrow aging.

Thousands of oscillating LncRNAs in the mouse testis

The long noncoding RNAs (lncRNAs) are involved in numerous fundamental biological processes, including circadian regulation. Although recent studies have revealed insights into the functions of lncRNAs, how the lncRNAs regulate circadian rhythms still requires a deeper investigation. In this study, we generate two datasets of RNA-seq profiles of the mouse (Mus musculus) testis under light-dark (LD) cycle. The first dataset included 18,613 unannotated transcripts measured at 12 time points, each with duplicate samples, under LD conditions; while the second dataset included 21,414 unannotated transcripts measured at six time points, each with three replicates, under desynchronized and control conditions. We identified 5964 testicular lncRNAs in each dataset by BLASTing these transcripts against the known mouse lncRNAs from the NONCODE database. MetaCycle analyses were performed to identify 519, 475, and 494 rhythmically expressed mouse testicular lncRNAs in the 12-time-point dataset, the six-time-point control dataset, and the six-time-point desynchronized dataset, respectively. A comparison of the expression profiles of the lncRNAs under desynchronized and control conditions revealed that 427 rhythmically expressed lncRNAs from the control condition became arrhythmic under the desynchronized condition, suggesting a possible loss of rhythmicity. In contrast, 446 arrhythmic lncRNAs from the control condition became rhythmic under the desynchronized condition, suggesting a possible gain of rhythmicity. Interestingly, 48 lncRNAs were rhythmically expressed under both desynchronized and control conditions. These oscillating lncRNAs were divided into morning lncRNAs, evening lncRNAs, and night lncRNAs based on their time-course expression patterns. We interrogated the promoter regions of these rhythmically expressed mouse testicular lncRNAs to predict their possible regulation by the E-box, D-box, or RORE promoter motifs. GO and KEGG analyses were performed to identify the possible biological functions of these rhythmically expressed mouse testicular lncRNAs. Further, we conducted conservation analyses of the rhythmically expressed mouse testicular lncRNAs with lncRNAs from humans, rats, and zebrafish, and uncovered three mouse testicular lncRNAs conserved across these four species. Finally, we computationally predicted the conserved lncRNA-encoded peptides and their 3D structures from each of the four species. Taken together, our study revealed thousands of rhythmically expressed lncRNAs in the mouse testis, setting the stage for further computational and experimental validations.

Biomaterial engineering strategies for modeling the Bruch's membrane in age-related macular degeneration

Age-related macular degeneration, a multifactorial inflammatory degenerative retinal disease, ranks as the leading cause of blindness in the elderly. Strikingly, there is a scarcity of curative therapies, especially for the atrophic advanced form of age-related macular degeneration, likely due to the lack of models able to fully recapitulate the native structure of the outer blood retinal barrier, the prime target tissue of age-related macular degeneration. Standard in vitro systems rely on 2D monocultures unable to adequately reproduce the structure and function of the outer blood retinal barrier, integrated by the dynamic interaction of the retinal pigment epithelium, the Bruch's membrane, and the underlying choriocapillaris. The Bruch's membrane provides structural and mechanical support and regulates the molecular trafficking in the outer blood retinal barrier, and therefore adequate Bruch's membrane-mimics are key for the development of physiologically relevant models of the outer blood retinal barrier. In the last years, advances in the field of biomaterial engineering have provided novel approaches to mimic the Bruch's membrane from a variety of materials. This review provides a discussion of the integrated properties and function of outer blood retinal barrier components in healthy and age-related macular degeneration status to understand the requirements to adequately fabricate Bruch's membrane biomimetic systems. Then, we discuss novel materials and techniques to fabricate Bruch's membrane-like scaffolds for age-related macular degeneration in vitro modeling, discussing their advantages and challenges with a special focus on the potential of Bruch's membrane-like mimics based on decellularized tissue.

A review of machine learning-based methods for predicting drug-target interactions

The prediction of drug-target interactions (DTI) is a crucial preliminary stage in drug discovery and development, given the substantial risk of failure and the prolonged validation period associated with in vitro and in vivo experiments. In the contemporary landscape, various machine learning-based methods have emerged as indispensable tools for DTI prediction. This paper begins by placing emphasis on the data representation employed by these methods, delineating five representations for drugs and four for proteins. The methods are then categorized into traditional machine learning-based approaches and deep learning-based ones, with a discussion of representative approaches in each category and the introduction of a novel taxonomy for deep neural network models in DTI prediction. Additionally, we present a synthesis of commonly used datasets and evaluation metrics to facilitate practical implementation. In conclusion, we address current challenges and outline potential future directions in this research field.

PML Nuclear bodies: the cancer connection and beyond

Promyelocytic leukemia (PML) nuclear bodies, membrane-less organelles in the nucleus, play a crucial role in cellular homeostasis. These dynamic structures result from the assembly of scaffolding PML proteins and various partners. Recent crystal structure analyses revealed essential self-interacting domains, while liquid-liquid phase separation contributes to their formation. PML bodies orchestrate post-translational modifications, particularly stress-induced SUMOylation, impacting target protein functions. Serving as hubs in multiple signaling pathways, they influence cellular processes like senescence. Dysregulation of PML expression contributes to diseases, including cancer, highlighting their significance. Therapeutically, PML bodies are promising targets, exemplified by successful acute promyelocytic leukemia treatment with arsenic trioxide and retinoic acid restoring PML bodies. Understanding their functions illuminates both normal and pathological cellular physiology, guiding potential therapies. This review explores recent advancements in PML body biogenesis, biochemical activity, and their evolving biological roles.

A Copernican revolution of multigenic analysis: A retrospective study on clinical exome sequencing in unclear genetic disorders

Despite the inevitable shift in medical practice towards a deeper understanding of disease etiology and progression through multigenic analysis, the profound historical impact of Mendelian diseases cannot be overlooked. These diseases, such as cystic fibrosis and thalassemia, are characterized by a single variant in a single gene leading to clinical conditions, and have significantly shaped our medical knowledge and treatments. In this respect, the monogenic approach inevitably results in the underutilization of Next-Generation Sequencing (NGS) data. Herein, a retrospective study was performed to assess the diagnostic value of the clinical exome in 32 probands with specific phenotypic characteristics (patients with autoinflammation and immunological dysregulation, N = 20; patients diagnosed with Hemolytic uremic syndrome N = 9; and patients with Waldenström macroglobulinemia, N = 3). A gene enrichment analysis was performed using the *. VCF file generated by SOPHiA-DDM-v4. This analysis selected a subset of genes containing pathogenic or likely pathogenic variants with autosomal dominant (AD) inheritance. In addition, all variants of uncertain significance (VUS) were included, filtered by AD inheritance mode, the presence of compound heterozygotes, and a minor allele frequency (MAF) cutoff of 0.05 %. The aim of the pipeline described here is based on a perspective shift that focuses on analyzing patients' gene assets, offering new light on the complex interplay between genetics and disease presentation. Integrating this approach into clinical practices could significantly enhance the management of patients with rare genetic disorders.

Application of multi-omics techniques to androgenetic alopecia: Current status and perspectives

The rapid advancement of sequencing technologies has enabled the generation of vast datasets, allowing for the in-depth analysis of sequencing data. This analysis has facilitated the validation of novel pathogenesis hypotheses for understanding and treating diseases through ex vivo and in vivo experiments. Androgenetic alopecia (AGA), a common hair loss disorder, has been a key focus of investigators attempting to uncover its underlying mechanisms. Abnormal changes in mRNA, proteins, and metabolites have been identified in individuals with AGA, and future developments in sequencing technologies may reveal new biomarkers for AGA. By integrating multiple omics analysis datasets such as genomics, transcriptomics, proteomics, and metabolomics-along with clinical phenotype data-we can achieve a comprehensive understanding of the molecular underpinnings of AGA. This review summarizes the data-mining studies conducted on various omics analysis datasets as related to AGA that have been adopted to interpret the biological data obtained from different omics layers. We herein discuss the challenges of integrative omics analyses, and suggest that collaborative multi-omics studies can enhance the understanding of the complete pathomechanism(s) of AGA by focusing on the interaction networks comprising DNA, RNA, proteins, and metabolites.

Plant bioactive compounds driven microRNAs (miRNAs): A potential source and novel strategy targeting gene and cancer therapeutics

Irrespective of medical technology improvements, cancer ranks among the leading causes of mortality worldwide. Although numerous cures and treatments exist, creating alternative cancer therapies with fewer adverse side effects is vital. Since ancient times, plant bioactive compounds have already been used as a remedy to heal cancer. These plant bioactive compounds and their anticancer activity can also deregulate the microRNAs (miRNAs) in the cancerous cells. Therefore, the deregulation of miRNAs in cancer cells by plant bioactive compounds and the usage of the related miRNA could be a promising approach for cancer cure, mainly to prevent cancer and overcome chemotherapeutic side effect problems. Hence, this review highlights the function of plant bioactive compounds as an anticancer agent through the underlying mechanism that alters the miRNA expression in cancer cells, ultimately leading to apoptosis. Moreover, this review provides insight into using plant bioactive compounds -driven miRNAs as an anticancer agent to develop miRNA-based cancer gene therapy. They can be the potential resource for gene therapy and novel strategies targeting cancer therapeutics.

New mechanism of LncRNA: In addition to act as a ceRNA

Long non-coding RNAs (LncRNAs) are a class of RNA molecules with nucleic acid lengths ranging from 200 bp to 100 kb that cannot code for proteins, which are diverse and widely expressed in both animals and plants. Scholars have found that lncRNAs can regulate human physiological processes at the gene and protein levels, mainly through the regulation of epigenetic, transcriptional and post-transcriptional levels of genes and proteins, as well as in the immune response by regulating the expression of immune cells and inflammatory factors, and thus participate in the occurrence and development of a variety of diseases. From the downstream targets of lncRNAs, we summarize the new research progress of lncRNA mechanisms other than miRNA sponges in recent years, aiming to provide new ideas and directions for the study of lncRNA mechanisms.

Repressing iron overload ameliorates central post-stroke pain via the Hdac2-Kv1.2 axis in a rat model of hemorrhagic stroke

JOURNAL/nrgr/04.03/01300535-202412000-00027/figure1/v/2024-04-08T165401Z/r/image-tiff Thalamic hemorrhage can lead to the development of central post-stroke pain. Changes in histone acetylation levels, which are regulated by histone deacetylases, affect the excitability of neurons surrounding the hemorrhagic area. However, the regulatory mechanism of histone deacetylases in central post-stroke pain remains unclear. Here, we show that iron overload leads to an increase in histone deacetylase 2 expression in damaged ventral posterolateral nucleus neurons. Inhibiting this increase restored histone H3 acetylation in the Kcna2 promoter region of the voltage-dependent potassium (Kv) channel subunit gene in a rat model of central post-stroke pain, thereby increasing Kcna2 expression and relieving central pain. However, in the absence of nerve injury, increasing histone deacetylase 2 expression decreased Kcna2 expression, decreased Kv current, increased the excitability of neurons in the ventral posterolateral nucleus area, and led to neuropathic pain symptoms. Moreover, treatment with the iron chelator deferiprone effectively reduced iron overload in the ventral posterolateral nucleus after intracerebral hemorrhage, reversed histone deacetylase 2 upregulation and Kv1.2 downregulation, and alleviated mechanical hypersensitivity in central post-stroke pain rats. These results suggest that histone deacetylase 2 upregulation and Kv1.2 downregulation, mediated by iron overload, are important factors in central post-stroke pain pathogenesis and could serve as new targets for central post-stroke pain treatment.

Omonijo F, A Ganai N, M. Ibeagha-Awemu E, Mudasir Ahmad S. Immunotherapy in mastitis: state of knowledge, research gaps and way forward

Mastitis is an inflammatory condition that affects dairy cow's mammary glands. Traditional treatment approaches with antibiotics are increasingly leading to challenging scenarios such as antimicrobial resistance. In order to mitigate the unwanted side effects of antibiotics, alternative strategies such as those that harness the host immune system response, also known as immunotherapy, have been implemented. Immunotherapy approaches to treat bovine mastitis aims to enhance the cow's immune response against pathogens by promoting pathogen clearance, and facilitating tissue repair. Various studies have demonstrated the potential of immunotherapy for reducing the incidence, duration and severity of mastitis. Nevertheless, majority of reported therapies are lacking in specificity hampering their broad application to treat mastitis. Meanwhile, advancements in mastitis immunotherapy hold great promise for the dairy industry, with potential to provide effective and sustainable alternatives to traditional antibiotic-based approaches. This review synthesizes immunotherapy strategies, their current understanding and potential future perspectives. The future perspectives should focus on the development of precision immunotherapies tailored to address individual pathogens/group of pathogens, development of combination therapies to address antimicrobial resistance, and the integration of nano- and omics technologies. By addressing research gaps, the field of mastitis immunotherapy can make significant strides in the control, treatment and prevention of mastitis, ultimately benefiting both animal and human health/welfare, and environment health.

Epigenetic landscape of 5-hydroxymethylcytosine and associations with gene expression in placenta

5-hydroxymethylcystosine (5hmC), is an intermediate product in the DNA demethylation pathway, but may act as a functional epigenetic modification. We have conducted the largest study of site-specific 5hmC in placenta to date using parallel bisulphite and oxidative bisulphite modification with array-based assessment. Incorporating parallel RNA-sequencing data allowed us to assess associations between 5hmC and gene expression, using expression quantitative trait hydroxymethylation (eQTHM) analysis. We identified ~ 47,000 loci with consistently elevated (systematic) 5hmC proportions. Systematic 5hmC was significantly depleted (p < 0.0001) at CpG islands (CGI), and enriched (p < 0.0001) in 'open sea' regions (CpG >4 kb from CGI). 5hmC was most and least abundant at CpGs in enhancers and active transcription start sites (TSS), respectively (p < 0.05). We identified 499 significant (empirical-p <0.05) eQTHMs within 1 MB of the assayed gene. At most (75.4%) eQTHMs, the proportion of 5hmC was positively correlated with transcript abundance. eQTHMs were significantly enriched among enhancer CpGs and depleted among CpGs in active TSS (p < 0.05 for both). Finally, we identified 107 differentially hydroxymethylated regions (DHMRs, p < 0.05) across 100 genes. Our study provides insight into placental distribution of 5hmC, and sheds light on the functional capacity of this epigenetic modification in placenta.

Human lncRNAs harbor conserved modules embedded in different sequence contexts

We analyzed the structure of human long non-coding RNA (lncRNAs) genes to investigate whether the non-coding transcriptome is organized in modular domains, as is the case for protein-coding genes. To this aim, we compared all known human lncRNA exons and identified 340 pairs of exons with high sequence and/or secondary structure similarity but embedded in a dissimilar sequence context. We grouped these pairs in 106 clusters based on their reciprocal similarities. These shared modules are highly conserved between humans and the four great ape species, display evidence of purifying selection and likely arose as a result of recent segmental duplications. Our analysis contributes to the understanding of the mechanisms driving the evolution of the non-coding genome and suggests additional strategies towards deciphering the functional complexity of this class of molecules.

Combined analysis of cross-population healthy adult human microbiome reveals consistent differences in gut microbial characteristics between Western and non-Western countries

Despite extensive research on the gut microbiome of healthy individuals from a single country, there are still a limited number of population-level comparative studies. Moreover, the sequencing approach used in most related studies involves 16 S ribosomal RNA (rRNA) sequencing with a limited resolution, which cannot provide detailed functional profiles. In the present study, we applied a combined analysis approach to analyze whole metagenomic shotgun sequencing data from 2035 healthy adult samples from six countries across four continents. Analysis of core species revealed that 13 species were present in more than 90 % of all investigated individuals, the majority of which produced short-chain fatty acids (SCFA)-producing bacteria. Our analysis revealed consistently significant differences in gut microbial species and pathways between Western and non-Western countries, such as Escherichia coli and the relation of MetaCyc pathways to the TCA cycle. Specific changes in microbial species and pathways are potentially related to lifestyle and diet. Furthermore, we identified several noteworthy microbial species and pathways that exhibit distinct characteristics specific to China. Interestingly, we observed that China (CHN) was more similar to the United States (USA) and United Kingdom (GBR) in terms of the taxonomic and functional composition of the gut microbiome than India (IND) and Madagascar (MDG), which were more similar to the China (CHN) diet. The current study identified consistent microbial features associated with population and geography, which will inspire further clinical translations that consider paying attention to differences in microbiota backgrounds and confounding factors.

DeepCORE: An interpretable multi-view deep neural network model to detect co-operative regulatory elements

Gene transcription is an essential process involved in all aspects of cellular functions with significant impact on biological traits and diseases. This process is tightly regulated by multiple elements that co-operate to jointly modulate the transcription levels of target genes. To decipher the complicated regulatory network, we present a novel multi-view attention-based deep neural network that models the relationship between genetic, epigenetic, and transcriptional patterns and identifies co-operative regulatory elements (COREs). We applied this new method, named DeepCORE, to predict transcriptomes in various tissues and cell lines, which outperformed the state-of-the-art algorithms. Furthermore, DeepCORE contains an interpreter that extracts the attention values embedded in the deep neural network, maps the attended regions to putative regulatory elements, and infers COREs based on correlated attentions. The identified COREs are significantly enriched with known promoters and enhancers. Novel regulatory elements discovered by DeepCORE showed epigenetic signatures consistent with the status of histone modification marks.

Cardiopulmonary bypass associated acute kidney injury: better understanding and better prevention

Cardiopulmonary bypass (CPB) is a common technique in cardiac surgery but is associated with acute kidney injury (AKI), which carries considerable morbidity and mortality. In this review, we explore the range and definition of CPB-associated AKI and discuss the possible impact of different disease recognition methods on research outcomes. Furthermore, we introduce the specialized equipment and procedural intricacies associated with CPB surgeries. Based on recent research, we discuss the potential pathogenesis of AKI that may result from CPB, including compromised perfusion and oxygenation, inflammatory activation, oxidative stress, coagulopathy, hemolysis, and endothelial damage. Finally, we explore current interventions aimed at preventing and attenuating renal impairment related to CPB, and presenting these measures from three perspectives: (1) avoiding CPB to eliminate the fundamental impact on renal function; (2) optimizing CPB by adjusting equipment parameters, optimizing surgical procedures, or using improved materials to mitigate kidney damage; (3) employing pharmacological or interventional measures targeting pathogenic factors.

Calling the question: what is mammalian transgenerational epigenetic inheritance?

While transgenerational epigenetic inheritance has been extensively documented in plants, nematodes, and fruit flies, its existence in mammals remains controversial. Several factors have contributed to this debate, including the lack of a clear distinction between intergenerational and transgenerational epigenetic inheritance (TEI), the inconsistency of some studies, the potential confounding effects of in-utero vs. epigenetic factors, and, most importantly, the biological challenge of epigenetic reprogramming. Two waves of epigenetic reprogramming occur: in the primordial germ cells and the developing embryo after fertilization, characterized by global erasure of DNA methylation and remodelling of histone modifications. Consequently, TEI can only occur if specific genetic regions evade this reprogramming and persist through embryonic development. These challenges have revived the long-standing debate about the possibility of inheriting acquired traits, which has been strongly contested since the Lamarckian and Darwinian eras. As a result, coupled with the absence of universally accepted criteria for transgenerational epigenetic studies, a vast body of literature has emerged claiming evidence of TEI. Therefore, the goal of this study is to advocate for establishing fundamental criteria that must be met for a study to qualify as evidence of TEI. We identified five criteria based on the consensus of studies that critically evaluated TEI. To assess whether published original research papers adhere to these criteria, we examined 80 studies that either claimed or were cited as supporting TEI. The findings of this analysis underscore the widespread confusion in this field and highlight the urgent need for a unified scientific consensus on TEI requirements.

SOX6 AU controls myogenesis by cis-modulation of SOX6 in cattle

Long non-coding RNAs (lncRNAs) have been shown to be involved in the regulation of skeletal muscle development through multiple mechanisms. The present study revealed that the lncRNA SOX6 AU (SRY-box transcription factor 6 antisense upstream) is reverse transcribed from upstream of the bovine sex-determining region Y (SRY)-related high-mobility-group box 6 (SOX6) gene. SOX6 AU was significantly differentially expressed in muscle tissue among different developmental stages in Xianan cattle. Subsequently, knockdown and overexpression experiments discovered that SOX6 AU promoted primary skeletal muscle cells proliferation, apoptosis, and differentiation in bovine. The overexpression of SOX6 AU in bovine primary skeletal muscle cells resulted in 483 differentially expressed genes (DEGs), including 224 upregulated DEGs and 259 downregulated DEGs. GO functional annotation analysis showed that muscle development-related biological processes such as muscle structure development and muscle cell proliferation were significantly enriched. KEGG pathway analysis revealed that the PI3K/AKT and MAPK signaling pathways were important pathways for DEG enrichment. Notably, we found that SOX6 AU inhibited the mRNA and protein expression levels of the SOX6 gene. Moreover, knockdown of the SOX6 gene promoted the proliferation and apoptosis of bovine primary skeletal muscle cells. Finally, we showed that SOX6 AU promoted the proliferation and apoptosis of bovine primary skeletal muscle cells by cis-modulation of SOX6 in cattle. This work illustrates our discovery of the molecular mechanisms underlying the regulation of SOX6 AU in the development of beef.

Epigenetic editing of BRCA1 promoter increases cisplatin and olaparib sensitivity of ovarian cancer cells

Drug resistance is the primary contributor to the high mortality rate of ovarian cancer (OC). The loss of BRCA1/2 function is linked to drug sensitivity in OC cells. The aim of this study is to enhance the drug sensitivity of OC cells by inducing BRCA1 dysfunction through promoter epigenetic editing. Epigenetic regulatory regions within the BRCA1 promoter, affecting gene expression, were initially discerned through analysis of clinical samples. Subsequently, we designed and rigorously validated epigenetic editing tools. Ultimately, we evaluated the cisplatin and olaparib sensitivity of the OC cells after editing. The BRCA1 promoter contains two CpG-rich regions, with methylation of the region covering the transcription start site (TSS) strongly correlating with transcription and influencing OC development, prognosis, and homologous recombination (HR) defects. Targeting this region in OC cells using our designed epigenetic editing tools led to substantial and persistent DNA methylation changes, accompanied by significant reductions in H3K27ac histone modifications. This resulted in a notable suppression of BRCA1 expression and a decrease in HR repair capacity. Consequently, edited OC cells exhibited heightened sensitivity to cisplatin and olaparib, leading to increased apoptosis rates. Epigenetic inactivation of the BRCA1 promoter can enhance cisplatin and olaparib sensitivity of OC cells through a reduction in HR repair capacity, indicating the potential utility of epigenetic editing technology in sensitization therapy for OC.

Long non-coding RNAs: roles in cellular stress responses and epigenetic mechanisms regulating chromatin

Most of the genome is transcribed into RNA but only 2% of the sequence codes for proteins. Non-coding RNA transcripts include a very large number of long noncoding RNAs (lncRNAs). A growing number of identified lncRNAs operate in cellular stress responses, for example in response to hypoxia, genotoxic stress, and oxidative stress. Additionally, lncRNA plays important roles in epigenetic mechanisms operating at chromatin and in maintaining chromatin architecture. Here, we address three lncRNA topics that have had significant recent advances. The first is an emerging role for many lncRNAs in cellular stress responses. The second is the development of high throughput screening assays to develop causal relationships between lncRNAs across the genome with cellular functions. Finally, we turn to recent advances in understanding the role of lncRNAs in regulating chromatin architecture and epigenetics, advances that build on some of the earliest work linking RNA to chromatin architecture.

Silencing of CircTRIM25/miR-138-5p/CREB1 axis promotes chondrogenesis in osteoarthritis

BACKGROUND

Dysregulated circular RNAs (circRNAs) are involved in osteoarthritis (OA) progression.

OBJECTIVE

We aimed to explore the effect of hsa_circ_0044719 (circTRIM25) on the ferroptosis of chondrocytes.

METHODS

Chondrocytes were treated with interleukin (IL)-1β to generate cell model. Cellular behaviours were measured using cell counting kit-8, enzyme-linked immunosorbent assay, relevant kits, propidium iodide staining, and immunofluorescence assay. Quantitative real-time polymerase chain reaction was performed to examine the expression of circTRIM25, miR-138-5p, and cAMP responsive element binding protein 1 (CREB1), and their interactions were assessed using luciferase reporter analysis and RNA pull-down assay.

RESULTS

CircTRIM25 was upregulated in OA tissues and IL-1β-stimulated chondrocytes. Knockdown of circTRIM25 facilitated the viability and suppressed ferroptosis and inflammation of IL-1β-induced cells. CircTRIM25 served as a sponge of miR-138-5p, which directly targets CREB1. Downregulation of miR-138-5p abrogated the effect induced by knockdown of circTRIM25. Furthermore, enforced CREB1 reversed the miR-138-5p induced effect. Moreover, knockdown of circTRIM25 attenuated cartilage injury in vivo.

CONCLUSION

Silencing of circTRIM25 inhibited ferroptosis of chondrocytes via the miR-138-5p/CREB axis and thus attenuated OA progression.

Differential amplification and contraction of satellite DNAs in the distinct lineages of the beetle Euchroma gigantea

Satellite DNA (satDNA) consists of tandem repeat sequences that typically evolve rapidly through evolutionary mechanisms, including unequal crossover, transposition events, and others. The evolutionary history of Euchroma gigantea is marked by complex chromosomal evolution between lineages, making this species an interesting model for understanding satDNA evolution at intraspecies level. Therefore, our aim was to comprehend the potential contribution of satDNAs to the greater chromosomal differentiation of evolutionary lineages in E. gigantea by investigating the differential patterns of amplification and contraction of the repeats. To achieve this, we employed de novo identification of satDNA using RepeatExplorer and TAREAN, allowing the satellitome characterization between lineages. A total of 26 satDNA families were identified, ranging from 18 to 1101 nucleotides in length, with most families being shared between individuals/lineages, as predicted by the library hypothesis, except for the satDNA EgiSat21-168 that was absent for Northeast Lineage. The total satDNA content of the individuals was less than 11.2%, and it appeared to increase in two directions following the chromosomal evolution model. Thirteen satDNAs exhibited different patterns of amplification, and nine ones were contracted among individuals. Additionally, most repeats showed a divergence of about 10% for these satDNAs, indicating satellitome differentiation for each lineage/individual. This scenario suggests that the expansion of the satellitome occurred differentially among individuals/lineages of E. gigantea, with the contribution of various DNA turnover mechanisms after geographical isolation, and that they could be involved with karyotype evolution.

Screening of reference genes for gene expression study in different tissues from the transcriptome data of the vector leafhopper Psammotettix striatus

Selecting appropriate reference genes is crucial for ensuring the accuracy and reliability of gene expression study using reverse transcription-quantitative PCR (RT-qPCR). To screen the optimal reference genes for analyzing gene expression in different tissues of the vector leafhopper Psammotettix striatus which causes extensive damage to a wide range of crops by vectoring multiple plant pathogenic microorganisms, the transcriptome data from Malpighian tubules (MTs) of P. striatus were mined. Twenty alternative candidate reference genes were initially selected for screening, among which seven genes with diverse Gene Ontology (GO) annotations were choosed as candidate reference genes, i.e., ribosomal protein L7A (RPL7A), ribosomal protein S28 (RPS28), ribosomal protein L22 (RPL22), ribosomal protein LP2 (RPLP2), H3 histone family 3A (H3F3A), elongation factor 1γ (EF-1γ), and elongation factor 1α (EF-1α). Gene expression levels in different tissues of P. striatus adults were examined using RT-qPCR, and their expression stability was analyzed using multiple reference gene screening software. This study revealed EF-1α as the most abundantly expressed gene, while RPL22 exhibited the lowest expression levels. EF-1α showed the most stable expression, whereas RPS28 showed the least stability. Various software tools confirmed EF-1α as the most stable single reference gene, and EF-1α and RPLP2 an optimal combination. This study provides a foundation for future investigation of the transmission of pathogenic microorganisms mediated by the vector leafhoppers, the function of the MTs, the biosynthesis of brochosomes, the coevolutionary processes and nutritional interactions of symbionts and host insects, and the gene expression study of other sap-sucking insects.

A comprehensive review of the applications of RNA sequencing in celiac disease research

RNA sequencing (RNA-seq) has undergone substantial advancements in recent decades and has emerged as a vital technique for profiling the transcriptome. The transition from bulk sequencing to single-cell and spatial approaches has facilitated the achievement of higher precision at cell resolution. It provides valuable biological knowledge about individual immune cells and aids in the discovery of the molecular mechanisms that contribute to the development of autoimmune diseases. Celiac disease (CeD) is an autoimmune disorder characterized by a strong immune response to gluten consumption. RNA-seq has led to significantly advanced research in multiple fields, particularly in CeD research. It has been instrumental in studies involving comparative transcriptomics, nutritional genomics and wheat research, cancer research in the context of CeD, genetic and noncoding RNA-mediated epigenetic insights, disease monitoring and biomarker discovery, regulation of mitochondrial functions, therapeutic target identification and drug mechanism of action, dietary factors, immune cell profiling and the immune landscape. This review offers a comprehensive examination of recent RNA-seq technology research in the field of CeD, highlighting future challenges and opportunities for its application.

RNA-binding protein AZGP1 inhibits epithelial cell proliferation by regulating the genes of alternative splicing in COPD

BACKGROUND

Chronic Obstructive Pulmonary Disease (COPD) is characterized by high morbidity, disability, and mortality rates worldwide. RNA-binding proteins (RBPs) might regulate genes involved in oxidative stress and inflammation in COPD patients. Single-cell transcriptome sequencing (scRNA-seq) offers an accurate tool for identifying intercellular heterogeneity and the diversity of immune cells. However, the role of RBPs in the regulation of various cells, especially AT2 cells, remains elusive.

MATERIALS AND METHODS

A scRNA-seq dataset (GSE173896) and a bulk RNA-seq dataset acquired from airway tissues (GSE124180) were employed for data mining. Next, RNA-seq analysis was performed in both COPD and control patients. Differentially expressed genes (DEGs) were identified using criteria of fold change (FC ≥ 1.5 or ≤ 1.5) and P value ≤ 0.05. Lastly, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and alternative splicing identification analyses were carried out.

RESULTS

RBP genes exhibited specific expression patterns across different cell groups and participated in cell proliferation and mitochondrial dysfunction in AT2 cells. As an RBP, AZGP1 expression was upregulated in both the scRNA-seq and RNA-seq datasets. It might potentially be a candidate immune biomarker that regulates COPD progression by modulating AT2 cell proliferation and adhesion by regulating the expression of SAMD5, DNER, DPYSL3, GBP5, GBP3, and KCNJ2. Moreover, AZGP1 regulated alternative splicing events in COPD, particularly DDAH1 and SFRP1, holding significant implications in COPD.

CONCLUSION

RBP gene AZGP1 inhibits epithelial cell proliferation by regulating genes participating in alternative splicing in COPD.

Advances in post-translational modifications and recurrent spontaneous abortion

Recurrent spontaneous abortion (RSA) is defined as two or more pregnancy loss, which affects approximately 1-2% of women's fertility. The etiology of RSA has not yet been fully revealed, which poses a great problem for clinical treatment. Post- translational modifications(PTMs) are chemical modifications that play a crucial role in the functional proteome. A considerable number of published studies have shown the relationship between post-translational modifications of various proteins and RSA. The study of PTMs contributes to elucidating the role of modified proteins in the pathogenesis of RSA, as well as the design of more effective diagnostic/prognostic tools and more targeted treatments. Most reviews in the field of RSA have only focused on RNA epigenomics research. The present review reports the latest research developments of PTMs related to RSA, such as glycosylation, phosphorylation, Methylation, Acetylation, Ubiquitination, etc.

Preeclampsia and STOX1 (storkhead-box protein 1): Molecular evaluation of STOX1 in preeclampsia

Preeclampsia (PE) is clinically defined as a part of pregnancy characterized by hypertension and multiple organ failure. PE is broadly categorized into two types: "placental" and "maternal". Placental PE is associated with fetal growth restriction and adverse maternal and neonatal outcomes. STOX1 (Storkhead box 1), a transcription factor, discovered through a complete transcript analysis of the PE susceptibility locus of 70,000 bp on chromosome 10q22.1. So far, studies investigating the relationship between STOX1 and PE have focused on STOX1 overexpression, STOX1 isoform imbalance, and STOX1 variations that could have clinical consequence. Initially, the Y153H variation of STOX was associated with the placental form of PE. Additionally, studies focusing on the maternal and fetal interface have shown that NODAL and STOX1 variations play a role together in the unsuccessful remodeling of the spiral arteries. Research specifically addressing the overexpression of STOX1 has shown that its disruption of cellular hemoastasis, leading to impaired hypoxia response, disruption of the cellular antioxidant system, and nitroso/redox imbalance. Furthermore, functional studies have been conducted showing that the imbalance between STOX1 isoforms contributes to the pathogenesis of placental PE. Research indicates that STOX1B competes with STOX1A and that the overexpression of STOX1B reverses cellular changes that STOX1A induces to the pathogenesis of PE. In this review, we aimed at elucidating the relationship between STOX1 and PE as well as function of STOX1. In conclusion, based on a comprehensive literature review, numerous studies support the role of STOX1 in the pathogenesis of PE.

Assemble and comparative analysis of the mitochondrial genome of Rhododendron delavayi: Insights into phylogenetic relationships and genomic variations

Rhododendron delavayi, a notable ornamental plant primarily found in regions of China like Yunnan and Guizhou provinces, holds substantial horticultural value. To elucidate the systematic phylogenetic relationships and organelle genomic differences within R. delavayi and related Rhododendron species, we conducted sequencing and assembly of the complete mitochondrial genome of R. delavayi. The full-length mitochondrial genome of it was a singular circular molecule spanning 1,009,263 bp, comprising 53 protein-coding genes, including 18 transfer RNA (tRNA) genes, 3 ribosomal RNA (rRNA) genes, and 32 protein-coding genes. A total of 1,182 simple sequence repeats (SSRs) loci were identified in the R. delavayi mitochondrial genome, primarily consisting of single nucleotide, dinucleotide, and trinucleotide repeats. Nucleotide diversity analysis highlighted five genes (atp6, atp9, cox2, nad1, and rpl10) with the highest diversity within the mitochondrial genomes of Rhododendron genus. Comparative analysis of the mitochondrial genome of R. delavayi with those of four other Rhododendron species indicated complex rearrangements in 21 genes, including rps4, nad6, rps3, atp6, cob, atp9, nad7, among others. The mitochondrial phylogenetic tree revealed a close relationship between R. delavayi and R. decorum, forming a sister clade to R. × pulchrum and R. simsii. Furthermore, 126 plastid-to-mitochondrial gene transfers in R. delavayi were identified, ranging from 30 bp to 19,385 bp. These fragments collectively constituted 47.54 % and 9.52 % of the chloroplast and mitochondrial genomes (202,169 bp), respectively. Complex mitochondrial-to-mitochondrial transfers were also observed, with 843 identified fragments totaling 312,036 bp (30.92 % of the mitochondrial genome). Segments exceeding 10 kb may mediate homologous recombination within the mitochondrial molecules. Remarkably, our study underscores that the mitochondrial genome of R. delavayi was the largest reported within the Rhododendron genus to date. The intricate rearrangements observed in the mitochondrial genomes of Rhododendron species, alone with the identification of five potential molecular marker sites, provided valuable insights for species classification and parentage identification within the Rhododendron genus.

Copy number variations affecting growth curve parameters in a crossbred chicken population

Copy number variations (CNVs) are key structural variations in the genome and may contribute to phenotypic differences. In this study, we used a F2 chicken population created from reciprocal crossing between fast-growing Arian broiler line and Urmia native chickens. The chickens were genotyped by 60 K SNP BeadChip, and PennCNV algorithm was used to detect genome-wide CNVs. The growth curve parameters of W0, k, L, Wf, Wi, ti and average GR were used as phenotypic data. The association between CNV and growth curve parameters was carried out using the CNVRanger R/Bioconductor package. Five CNV regions (CNVRs) were chosen for the validation experiment using qPCR. Gene enrichment analysis was done using WebGestalt. The STRING database was used to search for significant pathways. The results identified 966 CNVs and 600 CNVRs including 468 gains, 67 losses, and 65 both events on autosomal chromosomes. Validation of the CNVRs obtained from the qPCR assay were 79 % consistent with the prediction by PennCNV. A total of 43 significant CNVs were obtained for the seven growth curve parameters. The 416 genes annotated for significant CNVs. Six genes out of 416 genes were most related to growth curve parameters. These genes were LCP2, Dock2, CD80, CYFIP1, NIPA1 and NIPA2. Some of these genes in their biological process were associated with the growth, reproduction and development of cells or organs that ultimately lead to the growth of the body. The results of the study could pave the way for better understanding the molecular process of CNVs and growth curve parameters in birds.

The evolution of contemporary livestock species: Insights from mitochondrial genome

The domestication of animals marks a pivotal moment in human history, profoundly influencing our demographic and cultural progress. This process has led to significant genetic, behavioral, and physical changes in livestock species compared to their wild ancestors. Understanding the evolutionary history and genetic diversity of livestock species is crucial, and mitochondrial DNA (mtDNA) has emerged as a robust marker for investigating molecular diversity in animals. Its highly conserved gene content across animal species, minimal duplications, absence of introns, and short intergenic regions make mtDNA analysis ideal for such studies. Mitochondrial DNA analysis has uncovered distinct cattle domestication events dating back to 8000 years BC in Southwestern Asia. The sequencing of water buffalo mtDNA in 2004 provided important insights into their domestication history. Caprine mtDNA analysis identified three haplogroups, indicating varied maternal origins. Sheep, domesticated 12,000 years ago, exhibit diverse mtDNA lineages, suggesting multiple domestication events. Ovine mtDNA studies revealed clades A, B, C, and a fourth lineage, group D. The origins of domestic pigs were traced to separate European and Asian events followed by interbreeding. In camels, mtDNA elucidated the phylogeographic structure and genetic differentiation between wild and domesticated species. Horses, domesticated around 3500 BC, show significant mtDNA variability, highlighting their diverse origins. Yaks exhibit unique adaptations for high-altitude environments, with mtDNA analysis providing insights into their adaptation. Chicken mtDNA studies supported a monophyletic origin from Southeast Asia's red jungle fowl, with evidence of multiple origins. This review explores livestock evolution and diversity through mtDNA studies, focusing on cattle, water buffalo, goat, sheep, pig, camel, horse, yak and chicken. It highlights mtDNA's significance in unraveling maternal lineages, genetic diversity, and domestication histories, concluding with insights into its potential application in improving livestock production and reproduction dynamics.

Genome-wide identification of the Hsp70 gene family in Penaeus chinensis and their response to environmental stress

The heat shock protein 70 (HSP70) gene family plays a crucial role in the response of organisms to environmental stress. However, it has not been systematically characterized in shrimp. In this study, we identified 25 PcHsp70 genes in the Penaeus chinensis genome. The encoded proteins were categorized into six subgroups based on phylogenetic relationships. Tandem duplication was the main driver of amplification in the PcHsp70 family, and the genes have experienced strong purifying selection during evolution. Transcriptome data analysis revealed that the 25 PcHsp70 members have different expression patterns in shrimp under conditions of low temperature, low salinity, and white spot syndrome virus infection. Among them, PcHsp70.11 was significantly induced under all three stress conditions, suggesting that this gene plays an important role in response to environmental stress in P. chinensis. To the best of our knowledge, this is the first study to systematically analyze the Hsp70 gene family in shrimp. The results provide important information on shrimp Hsp70s, contributing to a better understanding of the role of these genes in environmental stress and providing a basis for further functional studies.

Exome-wide comparative analyses revealed differentiating genomic regions for performance traits in Indian native buffaloes

In India, 20 breeds of buffalo have been identified and registered, yet limited studies have been conducted to explore the performance potential of these breeds, especially in the Indian native breeds. This study is a maiden attempt to delineate the important variants and unique genes through exome sequencing for milk yield, milk composition, fertility, and adaptation traits in Indian local breeds of buffalo. In the present study, whole exome sequencing was performed on Chhattisgarhi (n = 3), Chilika (n = 4), Gojri (n = 3), and Murrah (n = 4) buffalo breeds and after stringent quality control, 4333, 6829, 4130, and 4854 InDels were revealed, respectively. Exome-wide FST along 100-kb sliding windows detected 27, 98, 38, and 35 outlier windows in Chhattisgarhi, Chilika, Gojri, and Murrah, respectively. The comparative exome analysis of InDels and subsequent gene ontology revealed unique breed specific genes for milk yield (CAMSAP3), milk composition (CLCN1, NUDT3), fertility (PTGER3) and adaptation (KCNA3, TH) traits. Study provides insight into mechanism of how these breeds have evolved under natural selection, the impact of these events on their respective genomes, and their importance in maintaining purity of these breeds for the traits under study. Additionally, this result will underwrite to the genetic acquaintance of these breeds for breeding application, and in understanding of evolution of these Indian local breeds.

Whole-genome resequencing reveals new mutations in candidate genes for Beichuan-white goat prolificacya

In this study, we evaluated the copy number variation in the genomes of two groups of Beichuan-white goat populations with large differences in litter size by FST method, and identified 1739 genes and 485 missense mutations in the genes subject to positive selection. Through functional enrichment, ITGAV, LRP4, CDH23, TPRN, RYR2 and CELSR1 genes, involved in embryonic morphogenesis, were essential for litter size trait, which received intensive attention. In addition, some mutation sites of these genes have been proposed (ITGAV: c.38C > T; TPRN: c.133A > T, c.1192A > G, c.1250A > C; CELSR1: c.7640T > C), whose allele frequencies were significantly changed in the high fecundity goat group. Besides, we found that new mutations at these sites altered the hydrophilicity and 3D structure of the protein. Candidate genes related to litter size in this study and their missense mutation sites were identified. These candidate genes are helpful to understand the genetic mechanism of fecundity in Beichuan white goat, and have important significance for future goat breeding.

Weighted single step GWAS reveals genomic regions associated with economic traits in Murrah buffaloes

The objective of the present study was to identify genomic regions influencing economic traits in Murrah buffaloes using weighted single step Genome Wide Association Analysis (WssGWAS). Data on 2000 animals, out of which 120 were genotyped using a double digest Restriction site Associated DNA (ddRAD) sequencing approach. The phenotypic data were collected from NDRI, India, on growth traits, viz., body weight at 6M (month), 12M, 18M and 24M, production traits like 305D (day) milk yield, lactation length (LL) and dry period (DP) and reproduction traits like age at first calving (AFC), calving interval (CI) and first service period (FSP). The biallelic genotypic data consisted of 49353 markers post-quality check. The heritability estimates were moderate to high, low to moderate, low for growth, production, reproduction traits, respectively. Important genomic regions explaining more than 0.5% of the total additive genetic variance explained by 30 adjacent SNPs were selected for further analysis of candidate genes. In this study, 105 genomic regions were associated with growth, 35 genomic regions with production and 42 window regions with reproduction traits. Different candidate genes were identified in these genomic regions, of which important are OSBPL8, NAP1L1 for growth, CNTNAP2 for production and ILDR2, TADA1 and POGK for reproduction traits.