Mechanisms Of Gene Regulation Research Articles

Concordant B and T Cell Heterogeneity Inferred from the Multiomic Landscape of Peripheral Blood Mononuclear Cells in a Crohn's Disease Cohort.

Crohn's disease is characterized by inflammation in the gastrointestinal tract due to a combination of genetic, immune, and environmental factors. Transcriptomic and epigenomic profiling of intestinal tissue of Crohn's disease patients have revealed valuable insights into pathology, however have not been conducted jointly on less invasive peripheral blood mononuclear cells (PBMCs). Furthermore, the heterogeneous responses to treatments among individuals with Crohn's disease imply hidden diversity of pathological mechanisms. We employed single nucleus multiomic analysis, integrating both snRNA-seq and snATAC-seq of PBMCs with a variety of open source bioinformatics applications. Our findings reveal a diverse range of transcriptional signatures among individuals, highlighting the heterogeneity in PBMC profiles. Nevertheless, striking concordance between three heterogeneous groups was observed across B cells and T cells. Differential gene regulatory mechanisms partially explain these profiles, notably including a signature involving TGFß signaling in two individuals with Crohn's disease. A mutation mapped to a transcription factor binding site within a differentially accessible peak associated with the expression of this pathway, with implications for a personalized approach to understanding disease pathology. This study highlights how multiomic analysis can reveal common regulatory mechanisms that underlie heterogeneity of PBMC profiles, one of which may be specific to inflammatory disease.

Comparative transcriptomic analysis delineates adaptation strategies of Rana kukunoris toward cold stress on the Qinghai-Tibet Plateau

BackgroundCold hardiness is fundamental for amphibians to survive during the extremely cold winter on the Qinghai-Tibet plateau. Exploring the gene regulation mechanism of freezing-tolerant Rana kukunoris could help us to understand how the frogs survive in winter.ResultsTranscriptome of liver and muscle of R. kukunoris collected in hibernation and spring were assisted by single molecule real-time (SMRT) sequencing technology. A total of 10,062 unigenes of R. kukunoris were obtained, and 9,924 coding sequences (CDS) were successfully annotated. Our examination of the mRNA response to whole body freezing and recover in the frogs revealed key genes concerning underlying antifreeze proteins and cryoprotectants (glucose and urea). Functional pathway analyses revealed differential regulated pathways of ribosome, energy supply, and protein metabolism which displayed a freeze-induced response and damage recover. Genes related to energy supply in the muscle of winter frogs were up-regulated compared with the muscle of spring frogs. The liver of hibernating frogs maintained modest levels of protein synthesis in the winter. In contrast, the liver underwent intensive high levels of protein synthesis and lipid catabolism to produce substantial quantity of fresh proteins and energy in spring. Differences between hibernation and spring were smaller than that between tissues, yet the physiological traits of hibernation were nevertheless passed down to active state in spring.ConclusionsBased on our comparative transcriptomic analyses, we revealed the likely adaptive mechanisms of R. kukunoris. Ultimately, our study expands genetic resources for the freezing-tolerant frogs.

Abstract LE21: Mechanisms of gene regulation by chromatin adaptors in development and disease

Abstract Complex biological processes, such as organismal development, are directly influenced by the interplay between genes and the cellular structures and environmental factors that regulate them. Key players in this regulation are chromatin adaptor proteins, which can impact the genetic and epigenetic programs of cells. However, our understanding of how these proteins interact with chromatin - the physiological form of our genomes - and regulate gene activity is limited, especially in the context of diseases like cancer. To test our central hypothesis and to understand how chromatin adaptors contribute to cell function, we are developing innovative high-throughput and biochemical approaches. These will help us systematically identify specific histone modifications that affect the binding of Menin and other adaptors to chromatin. Our experimental approach includes profiling, validation, and functional characterization using advanced genomic and epigenomic technologies, transcriptional profiling, and CRISPR gene editing. The application of these techniques will reveal, for the first time, the molecular mechanisms by which these proteins bind to specific parts of the genome and regulate gene activity. Our findings will enhance our understanding of how chromatin adaptors, like Menin, interact with chromatin and regulate gene activity in different tissues, and how these functions are disrupted by cancer-associated mutations. This will also contribute to the development of potential new therapies that target these altered mechanisms. Furthermore, our findings can be extended to other proteins involved in chromatin and epigenetic regulation, enabling a broader application in understanding and treating cancer and other human diseases. Citation Format: Yadira Marie Soto-Feliciano. Mechanisms of gene regulation by chromatin adaptors in development and disease [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LE21.

Multi-System-Level Analysis Reveals Differential Expression of Stress Response-Associated Genes in Inflammatory Solar Lentigo.

Although the pathogenesis of solar lentigo (SL) involves chronic ultraviolet (UV) exposure, cellular senescence, and upregulated melanogenesis, underlying molecular-level mechanisms associated with SL remain unclear. The aim of this study was to investigate the gene regulatory mechanisms intimately linked to inflammation in SL. Skin samples from patients with SL with or without histological inflammatory features were obtained. RNA-seq data from the samples were analyzed via multiple analysis approaches, including exploration of core inflammatory gene alterations, identifying functional pathways at both transcription and protein levels, comparison of inflammatory module (gene clusters) activation levels, and analyzing correlations between modules. These analyses disclosed specific core genes implicated in oxidative stress, especially the upregulation of nuclear factor kappa B in the inflammatory SLs, while genes associated with protective mechanisms, such as SLC6A9, were highly expressed in the non-inflammatory SLs. For inflammatory modules, Extracellular Immunity and Mitochondrial Innate Immunity were exclusively upregulated in the inflammatory SL. Analysis of protein-protein interactions revealed the significance of CXCR3 upregulation in the pathogenesis of inflammatory SL. In conclusion, the upregulation of stress response-associated genes and inflammatory pathways in response to UV-induced oxidative stress implies their involvement in the pathogenesis of inflammatory SL.

RNAi-based drug design: considerations and future directions.

More than 25 years after its discovery, the post-transcriptional gene regulation mechanism termed RNAi is now transforming pharmaceutical development, proved by the recent FDA approval of multiple small interfering RNA (siRNA) drugs that target the liver. Synthetic siRNAs that trigger RNAi have the potential to specifically silence virtually any therapeutic target with unprecedented potency and durability. Bringing this innovative class of medicines to patients, however, has been riddled with substantial challenges, with delivery issues at the forefront. Several classes of siRNA drug are under clinical evaluation, but their utility in treating extrahepatic diseases remains limited, demanding continued innovation. In this Review, we discuss principal considerations and future directions in the design of therapeutic siRNAs, with a particular emphasis on chemistry, the application of informatics, delivery strategies and the importance of careful target selection, which together influence therapeutic success.

Automatic design of gene regulatory mechanisms for spatial pattern formation

Gene regulatory mechanisms (GRMs) control the formation of spatial and temporal expression patterns that can serve as regulatory signals for the development of complex shapes. Synthetic developmental biology aims to engineer such genetic circuits for understanding and producing desired multicellular spatial patterns. However, designing synthetic GRMs for complex, multi-dimensional spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given two-dimensional spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms—including the number of genes necessary for the formation of the target spatial pattern—we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover complex genetic circuits producing spatial patterns.

Identifying gene expression programs in single-cell RNA-seq data using linear correlation explanation

ObjectiveGene expression analysis through single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of gene regulation in diverse cell types, tissues, and organisms. While existing methods primarily focus on identifying cell type-specific gene expression programs (GEPs), the characterization of GEPs associated with biological processes and stimuli responses remains limited. In this study, we aim to infer biologically meaningful GEPs that are associated with both cellular phenotypes and activity programs directly from scRNA-seq data. MethodsWe applied linear CorEx, a machine-learning-based approach, to infer GEPs by grouping genes based on total correlation optimization function in simulated and real-world scRNA-seq datasets. Additionally, we utilized a transfer learning approach to project CorEx-inferred GEPs to other scRNA-seq datasets. ResultsBy leveraging total correlation optimization, linear CorEx groups genes and demonstrates superior performance in identifying cell types and activity programs compared to similar methods using simulated data. Furthermore, we apply this same approach to real-world scRNA-seq data from the mouse dentate gyrus and embryonic colon development, uncovering biologically relevant GEPs related to cell types, developmental ages, and cell cycle programs. We also demonstrate the potential for transfer learning by evaluating similar datasets, showcasing the cross-species sensitivity of linear CorEx. ConclusionOur findings validate linear CorEx as a valuable tool for comprehensively analyzing complex signals in scRNA-seq data, leading to deeper insights into gene expression dynamics, cellular heterogeneity, and regulatory mechanisms.

Epigenetic programming of stochastic olfactory receptor choice.

The mammalian sense of smell relies upon a vast array of receptor proteins to detect odorant compounds present in the environment. The proper deployment of these receptor proteins in olfactory sensory neurons is orchestrated by a suite of epigenetic processes that remodel the olfactory genes in differentiating neuronal progenitors. The goal of this review is to elucidate the central role of gene regulatory processes acting in neuronal progenitors of olfactory sensory neurons that lead to a singular expression of an odorant receptor in mature olfactory sensory neurons. We begin by describing the principal features of odorant receptor gene expression in mature olfactory sensory neurons. Next, we delineate our current understanding of how these features emerge from multiple gene regulatory mechanisms acting in neuronal progenitors. Finally, we close by discussing the key gaps in our understanding of how these regulatory mechanisms work and how they interact with each other over the course of differentiation.

Enhancing Transcription Factor Prediction through Multi-Task Learning (Student Abstract)

Transcription factors (TFs) play a fundamental role in gene regulation by selectively binding to specific DNA sequences. Understanding the nature and behavior of these TFs is essential for insights into gene regulation dynamics. In this study, we introduce a robust multi-task learning framework specifically tailored to harness both TF-specific annotations and TF-related domain annotations, thereby enhancing the accuracy of TF predictions. Notably, we incorporate cutting-edge language models that have recently garnered attention for their outstanding performance across various fields, particularly in biological computations like protein sequence modeling. Comparative experimental analysis with existing models, DeepTFactor and TFpredict, reveals that our multi-task learning framework achieves an accuracy exceeding 92% across four evaluation metrics on the TF prediction task, surpassing both competitors. Our work marks a significant leap in the domain of TF prediction, enriching our comprehension of gene regulatory mechanisms and paving the way for the discovery of novel regulatory motifs.

Abstract 1733: SET-NUP214 rearranges the DNA-methylation landscape to upregulate the HOX-gene cluster in acute myeloid leukemia

Abstract The SET-NUP214 (S/N) fusion gene, which results from either cryptic t(9:9) (q34;q34) or del(9) (q34.11q34.13), is found in a very narrow spectrum of patients diagnosed with Acute Myeloid Leukemia (AML) or T-cell acute lymphoblastic leukemia (T-ALL). AML patients with S/N fusion were reported to have relatively poor prognostic outcomes despite receiving myeloablative conditioning. While previously, the fusion has been described to overrepresent HOX cluster genes, the underlying mechanism of gene regulation that contributes to the pathology remains elusive due to the rare incidence of the disease. The current study used the MEGAL (ACC719, DSMZ) cell line, identified as the solo megakaryocytic AML line expressing the S/N-fusion, for determining genome-wide DNA methylation (DNAm) and gene expression using 935K Infinium MethylationEPIC v2.0 BeadChip array and RNA-sequencing, respectively. The differential DNAm and expression data were analyzed and compared to the hematopoietic stem progenitor cells (HSPC) or normal megakaryocytes (MK). The ChIP-sequencing data from the S/N positive T-ALL cell line LOUCY has been used to represent the coincidence of regulatory chromatin marks and differentially methylated CpG (mC) sites. We observed n=1934 genes upregulated and n=2396 downregulated in MEGAL, compared to both HSPC and MK. The direction of expression changes between MEGAL and HSPC and MEGAL and MK showed a high correlation (r=0.92, p< 0.01). Per the previous literature, we observed an overrepresentation of HOX genes (n=19) in MEGAL. Based on DNAm profiling, we noticed a propensity of hypermethylation in MEGAL across the promoters (93%±0.6), bodies (93%±0.8), and intergenic (85%±0.3) regions, compared to HSPC/MK. Next, we integrated the mC and expression at the promoters and identified that the majority (75%±3) of the genes belong to the hyper-down (n=2563 against HPSC; n=1907 against MK) or hyper-up (n=965 against HPSC; n=923 against MK) clusters. We further investigated the HOXB (HOXB7, HOXB8, HOXB9) and HOXC (HOXC10, HOXC12, HOXC13, HOXC13-AS, HOXC4, HOXC5, HOC6, HOXC8, HOXC9, HOXC-AS1, HOXC-AS2, and HOXC-AS3) cluster genes, where hypermethylated CpGs mainly were concentrated at the CpG islands and overlapped with active promoter (H3K4me3, H3K4me1) signatures or enhancer-like (CTCF bound) elements. We also observed frequent overlaps between mC and H3K36me3 across the observed genes. The differentially expressed genes in this AML subtype were enriched for the hippo-signaling pathway, calcium signaling, focal adhesion, and PI3-Akt pathways. Collectively, our data showed that S/N favors genome-wide hypermethylation, which, in conjunction with the cis-regulatory elements, induces overrepresentation of the HOX cluster genes. These novel epigenetic vulnerabilities are worth pursuing for investigating the cellular function and pathophysiology of the disease. Citation Format: Samrat Roy Choudhury, Akhilesh Kaushal. SET-NUP214 rearranges the DNA-methylation landscape to upregulate the HOX-gene cluster in acute myeloid leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1733.

Abstract 5633: Unravelling the pleiotropic role of HNF4α in invasive mucinous adenocarcinoma of the lung (IMA)

Abstract IMA is a distinct subtype of lung adenocarcinoma (LUAD), marked by a cellular identity shift from a pulmonary to a gastric lineage with the loss of the pulmonary lineage specifier NKX2-1. This distinctive transformation underscores the complexity of lung cancer heterogeneity and highlights the critical role of lineage-specifying transcription factors in dictating tumor behavior. Notably, both human and murine models of IMA overexpress HNF4α, a known lineage specifier for gastric differentiation in the adult mouse mucosa. Also, concomitant deletion of Hnf4a and Nkx2-1 at tumor initiation impairs tumor growth and the extent of HNF4α in regulating IMA tumor growth, cellular identity and drug response remains unknown at large. Here, we utilized genetically engineered mouse models (GEMM) that relies on a sequential recombination strategy to delete Hnf4a in established tumors. We induce tumor formation through intratracheal delivery of Flp-O virus, activating the expression of mutant KRASG12D and Cre in lung epithelial cells. Tamoxifen administration recombines either Nkx2-1 alone (KN) or in combination with Hnf4a (KNH). We have extensively studied the phenotypic role of HNF4α in GEMM and organoids and identified gene sets regulated by HNF4α in IMA at the bulk level. To complement our findings, we profiled both the tumor and stromal compartments via scRNAseq analysis on our GEMM to gain insights into the cellular diversity within the tumor microenvironment (TME) and the role HNF4α plays. Additionally, we performed ChIPSeq in organoids to elucidate the genome occupancy of HNF4α and determine the mechanisms of gene regulation in IMA. We find that deletion of Hnf4a impairs tumor growth in GEMM and this is phenocopied in organoids. We identified numerous differentially expressed genes (DEGs) in KNH compared to KN and validated several DEGs in vivo. GSEA analysis reveals a significant involvement in regulating cellular identity and suggests a potential impact on anti-tumor immune responses. To this, our scRNAseq data revealed an enrichment of N2-TAN (tumor associated neutrophils) associated genes in KNH compared to KN, suggesting a nuanced interplay between HNF4α and the TME. Additionally, HNF4α exhibited dual functionality, acting as an activator and indirectly as a repressor by modulating the activity of other transcription factors like FOXA1. FOXA1 was found to bind de novo target genes following the loss of HNF4α. These findings so far collectively illuminate the multifaceted role of HNF4α in IMA, primarily driving tumorigenesis in a cell autonomous manner and secondarily skewing the TME towards a protumor via N2-TAN following loss of HNF4α in tumors. Citation Format: Headtlove Essel Dadzie, Gabriela Fort, Katherine Gillis, Pengshu Fang, Walter Orellana, Eric L. Snyder. Unravelling the pleiotropic role of HNF4α in invasive mucinous adenocarcinoma of the lung (IMA) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5633.

Abstract 4411: Enhancing scalability and consistency in clinical multiomics via an optimized fixed cell ATAC-seq method​

Abstract ATAC-seq has an emerging role in decoding mechanisms of gene regulation, offering valuable insights into pathology and treatment response in disease models. However, clinical adoption of ATAC-seq methods has been limited by logistical hurdles, including time-sensitive processing of fresh samples and compromised viability of cryopreserved cells. These constraints, compounded by changes in open chromatin regions (OCRs) following cryopreservation, introduce unintended bias and pose significant obstacles for the translational impact of ATAC-seq experiments. ​ Here, we introduce an optimized fixed-cell ATAC-seq approach to overcome these limitations and unlock new sample types for ATAC-seq analyses. Our solution improves and simplifies the workflow from sample collection to clinical deliverable. This method enables ATAC-seq investigation of a diverse range of samples and facilitates the execution of complex experimental designs, including time course studies and high throughput screening.​To demonstrate the effectiveness of this method, we compared our optimized fixed-cell method with traditional ATAC-seq preparations in both fresh and cryopreserved GM12878 cells in parallel. Human GM12878 cell line was obtained from Coriell Institute for Medical Research5. Remarkably, we observed consistent genome-wide patterns of OCR enrichment at key regulatory elements across the three sample preparation methods. We observed consistent OCR enrichment across the promoter region of known highly-expressed B-cell genes including CD48 and LCP1, underscoring this assay’s ability to detect chromatin changes at key genes in human disease models. ​ To investigate the potential for multiomic analysis using this method, we prepared RNA-seq libraries from fixed-cell samples in parallel to ATAC-seq. We observed significantly elevated gene expression related to B-cell function and B-cell diseases, demonstrating our method’s compatibility with RNA-seq data collection and integration. This optimized fixed-cell ATAC-seq approach offers enhanced scalability and consistency over conventional methods and presents new opportunities for the multiomic analysis of chromatin and transcriptional activity genome-wide from a single sample in both clinical and research settings. Citation Format: Dafne Alves Winders, Riley Graham, Xiangying Mao, Ilaria De Vito, Andrea O'Hara, Laure Turner, Haythem Latif. Enhancing scalability and consistency in clinical multiomics via an optimized fixed cell ATAC-seq method​ [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4411.

Proteins à la carte: riboproteogenomic exploration of bacterial N-terminal proteoform expression.

With the emerging theme of genes within genes comprising the existence of alternative open reading frames (ORFs) generated by translation initiation at in-frame start codons, mechanisms that control the relative utilization of annotated and alternative TIS need to be unraveled and our molecular understanding of resulting proteoforms broadened. Utilizing complementary ribosome profiling strategies to map ORF boundaries, we uncovered dual-encoding ORFs generated by in-frame TIS usage in Salmonella. Besides demonstrating that alternative TIS usage may generate proteoforms with different characteristics, such as differential localization and specialized function, quantitative aspects of conditional retapamulin-assisted ribosome profiling (Ribo-RET) translation initiation maps offer unprecedented insights into the relative utilization of annotated and alternative TIS, enabling the exploration of gene regulatory mechanisms that control TIS usage and, consequently, the translation of N-terminal proteoform pairs.

Conserved Noncoding Elements Evolve Around the Same Genes Throughout Metazoan Evolution.

Conserved noncoding elements (CNEs) are DNA sequences located outside of protein-coding genes that can remain under purifying selection for up to hundreds of millions of years. Studies in vertebrate genomes have revealed that most CNEs carry out regulatory functions. Notably, many of them are enhancers that control the expression of homeodomain transcription factors and other genes that play crucial roles in embryonic development. To further our knowledge of CNEs in other parts of the animal tree, we conducted a large-scale characterization of CNEs in more than 50 genomes from three of the main branches of the metazoan tree: Cnidaria, Mollusca, and Arthropoda. We identified hundreds of thousands of CNEs and reconstructed the temporal dynamics of their appearance in each lineage, as well as determining their spatial distribution across genomes. We show that CNEs evolve repeatedly around the same genes across the Metazoa, including around homeodomain genes and other transcription factors; they also evolve repeatedly around genes involved in neural development. We also show that transposons are a major source of CNEs, confirming previous observations from vertebrates and suggesting that they have played a major role in wiring developmental gene regulatory mechanisms since the dawn of animal evolution.

Diet-induced hyperhomocysteinemia causes sex-dependent deficiencies in offspring musculature and brain function.

Hyperhomocysteinemia (HHcy), characterized by elevated homocysteine (Hcy) levels, is a known risk factor for cardiovascular, renal, and neurological diseases, as well as pregnancy complications. Our study aimed to investigate whether HHcy induced by a high-methionine (high-Met) diet exacerbates cognitive and behavioral deficits in offspring and leads to other breeding problems. Dietary HHcy was induced four weeks before mating and continued throughout gestation and post-delivery. A battery of behavioral tests was conducted on offspring between postnatal days (PNDs) 5 and 30 to assess motor function/activity and cognition. The results were correlated with brain morphometric measurements and quantitative analysis of mammalian target of rapamycin (mTOR)/autophagy markers. The high-Met diet significantly increased parental and offspring urinary tHcy levels and influenced offspring behavior in a sex-dependent manner. Female offspring exhibited impaired cognition, potentially related to morphometric changes observed exclusively in HHcy females. Male HHcy pups demonstrated muscle weakness, evidenced by slower surface righting, reduced hind limb suspension (HLS) hanging time, weaker grip strength, and decreased activity in the beaker test. Western blot analyses indicated the downregulation of autophagy and the upregulation of mTOR activity in HHcy cortexes. HHcy also led to breeding impairments, including reduced breeding rate, in-utero fetal death, lower pups' body weight, and increased mortality, likely attributed to placental dysfunction associated with HHcy. In conclusion, a high-Met diet impairs memory and cognition in female juveniles and weakens muscle strength in male pups. These effects may stem from abnormal placental function affecting early neurogenesis, the dysregulation of autophagy-related pathways in the cortex, or epigenetic mechanisms of gene regulation triggered by HHcy during embryonic development.

A scalable and cost-efficient rRNA depletion approach to enrich RNAs for molecular biology investigations.

Transcriptomics analyses play pivotal roles in understanding the complex regulatory networks that govern cellular processes. The abundance of rRNAs, which account for 80-90% of total RNA in eukaryotes, limits the detection and investigation of other transcripts. While mRNAs and long non-coding RNAs have polyA(+) tails that are often used for positive selection, investigations of polyA(-) RNAs, such as circular RNAs, histone mRNAs, and small RNAs, typically require the removal of the abundant rRNAs for enrichment. Current approaches to deplete rRNAs for downstream molecular biology investigations are hampered by restrictive RNA input masses and high cost. To address these challenges, we developed rRNA Removal by RNase H (rRRR), a method to efficiently deplete rRNA from a wide range of human, mouse, and rat RNA inputs and qualities at a cost 10-20-fold cheaper than other approaches. We employed probe-based hybridization and enzymatic digestion to selectively target and remove rRNA molecules while preserving the integrity of non-rRNA transcripts. Comparison between rRRR to two commercially available approaches found that they had similar efficiencies at depleting rRNAs and comparable off-target effects. Our developed method provides researchers with a valuable tool for investigating gene expression and regulatory mechanisms across a wide range of biological systems at an affordable price that increases the accessibility for researchers to enter the field, ultimately advancing our understanding of cellular processes.

The potential crosstalk genes and molecular mechanisms between glioblastoma and periodontitis.

Despite clinical and epidemiological evidence suggestive of a link between glioblastoma (GBM) and periodontitis (PD), the shared mechanisms of gene regulation remain elusive. In this study, we identify differentially expressed genes (DEGs) that overlap between the GEO datasets GSE4290 [GBM] and GSE10334 [PD]. Functional enrichment analysis was conducted, and key modules were identified using protein-protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA). The expression levels of CXCR4, LY96, and C3 were found to be significantly elevated in both the test dataset and external validation dataset, making them key crosstalk genes. Additionally, immune cell landscape analysis revealed elevated expression levels of multiple immune cells in GBM and PD compared to controls, with the key crosstalk genes negatively associated with Macrophages M2. FLI1 was identified as a potential key transcription factor (TF) regulating the three key crosstalk genes, with increased expression in the full dataset. These findings contribute to our understanding of the immune and inflammatory aspects of the comorbidity mechanism between GBM and PD.

Integrated metabolome and transcriptome revealed the metabolite characteristics and potential gene regulation mechanism in muscle of different ages male Chinese soft-shelled turtles (Pelodiscus sinensis)

The Chinese soft-shelled turtle (Pelodiscus sinensis) is a medicine-food homology aquatic product and has a long growth cycle. In this paper, the compound features and its accumulation mechanisms in male P. sinensis muscle from 3 to 6 years of age (M3 to M6) were clarified based on metabolomic and transcriptomic. 261 metabolites identified are meat matrices in P. sinensis. In M3, IMP and GMP were most abundant. Free amino acid, monosaccharides, and highly unsaturated fatty acid (HUFA) accumulation are respectively dominant between sequential ever two groups from M3 to M6 by collagen synthesis genes down-regulated, glycogen synthesis inhibited, and fatty acid highly desaturated enhancement. col1a1, col1a2, and col6a2 were identified as arachidic acid-related genes. Overall, nutrients and antioxidants were utmost in oldest ones of 6 years of age, though flavoring substances abundant in M3 and M4, which was inextricably associated with diverse gene regulation in different ages P. sinensis.

Osteoarthritis as an Enhanceropathy: Gene Regulation in Complex Musculoskeletal Disease.

Osteoarthritis is a complex and highly polygenic disease. Over 100 reported osteoarthritis risk variants fall in non-coding regions of the genome, ostensibly conferring functional effects through the disruption of regulatory elements impacting target gene expression. In this review, we summarise the progress that has advanced our knowledge of gene enhancers both within the field of osteoarthritis and more broadly in complex diseases. Advances in technologies such as ATAC-seq have facilitated our understanding of chromatin states in specific cell types, bolstering the interpretation of GWAS and the identification of effector genes. Their application to osteoarthritis research has revealed enhancers as the principal regulatory element driving disease-associated changes in gene expression. However, tissue-specific effects in gene regulatory mechanisms can contribute added complexity to biological interpretation. Understanding gene enhancers and their altered activity in specific cell and tissue types is the key to unlocking the genetic complexity of osteoarthritis. The use of single-cell technologies in osteoarthritis research is still in its infancy. However, such tools offer great promise in improving our functional interpretation of osteoarthritis GWAS and the identification of druggable targets. Large-scale collaborative efforts will be imperative to understand tissue and cell-type specific molecular mechanisms underlying enhancer function in disease.

Dynamic Model Inference of Gene Regulatory Network based on Hybrid Parallel Genetic Algorithm and Threshold Qualification Method

Gene regulation is the process by which various substances in cells regulate the behaviour of gene expression, thereby controlling almost all cellular activities. Therefore, studying gene regulation not only helps to uncover the internal laws governing life processes but also plays a crucial role in predicting, diagnosing, treating, and designing drugs for genetic diseases. By utilizing multi-source biological information such as gene expression profiles, transcription factor information, and protein interaction data, a network model can be developed to depict the regulatory relationships between genes, facilitating further research. To address the limitations of traditional gene regulatory network construction methods, a novel dynamic model has been created by combining hybrid genetics and threshold restriction. This model comprises two parts: solution space reduction and parameter fitting. During solution space reduction, singular value decomposition is employed to define a mathematically feasible gene regulatory network, reducing unnecessary calculations. Subsequently, the control genes of each gene are constrained within a certain range using threshold limitation, enhancing computational efficiency while adhering to bioinformatics principles. In the parameter fitting phase, parallel genetic algorithms are utilized to expediently optimize the entire solution space. The mountain climbing method is then applied to solve problems meticulously within a limited scope, improving calculation accuracy. In this study, this approach was applied to establish genetic regulatory systems for complex skin melanoma and type 2 diabetes. Through comparison with actual networks, the validity of the method was confirmed. Compared to traditional genetic and particle swarm optimization methods, the effectiveness of the proposed method was verified. This paper models the intricate mechanism of gene regulation and elucidates the regulatory process involving genes, proteins, and small biological molecules in greater detail than other models, aligning more closely with intracellular dynamics laws.