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At least 919 records · Page 51Linked to original sources
PubMed2003

Microarray analysis of E2Fa-DPa-overexpressing plants uncovers a cross-talking genetic network between DNA replication and nitrogen assimilation.

Previously we have shown that overexpression of the heterodimeric E2Fa-DPa transcription factor in Arabidopsis thaliana results in ectopic cell division, increased endoreduplication, and an early arrest in development. To gain a better insight into the phenotypic behavior of E2Fa-DPa transgenic plants and to identify E2Fa-DPa target genes, a transcriptomic microarray analysis was performed. Out of 4,390 unique genes, a total of 188 had a twofold or more up- (84) or down-regulated (104) expression level in E2Fa-DPa transgenic plants compared to wild-type lines. Detailed promoter analysis allowed the identification of novel E2Fa-DPa target genes, mainly involved in DNA replication. Secondarily induced genes encoded proteins involved in cell wall biosynthesis, transcription and signal transduction or had an unknown function. A large number of metabolic genes were modified as well, among which, surprisingly, many genes were involved in nitrate assimilation. Our data suggest that the growth arrest observed upon E2Fa-DPa overexpression results at least partly from a nitrogen drain to the nucleotide synthesis pathway, causing decreased synthesis of other nitrogen compounds, such as amino acids and storage proteins.

Arabidopsis↗
PubMed2026

Single-cell transcriptomics reveals heterogeneous stress responses and Mg2+-mediated survival mechanisms in Lactobacillus delbrueckii subsp. bulgaricus during freeze-drying and storage.

Maintaining the viability of lactic acid bacteria during dehydration and subsequent storage remains a significant challenge. Here, we employed single-cell RNA sequencing to reveal the heterogeneous stress responses of Lactobacillus delbrueckii subsp. bulgaricus, identifying seven distinct transcriptional clusters across the liquid culture, freeze-drying, and storage phases. The dominant clusters in the freeze-drying and storage were not completely consistent, showing significant functional differentiation. Genomic stability may be important for survival during freeze-drying and storage, while intracellular energy homeostasis appears important for viability during storage. The magnesium transporter mgtB was highly expressed in clusters tolerant to freeze-drying and storage, suggesting a critical role for Mg2+ homeostasis. Further experimental validation confirmed that Mg2+ treatment significantly bolstered stress resistance, increasing immediate post-freeze-drying survival by over 2-fold (up to 92.90%) and post-storage survival by over 5-fold (up to 5.98%). Proteomic data indicated that Mg2+ supplementation correlated with the maintenance of several biological functions potentially relevant to bacterial survival during freeze-drying and storage, including DNA repair, translation, and central carbon metabolism. These findings provide a map of microbial stress resistance through population heterogeneity and offer a potential strategy that may be adapted for enhancing the stability of other industrial lactic acid bacteria products.

Freeze Drying↗
PubMed2026

Multilevel genomic, transcriptomic, and epidemiologic evidence linking diabetic retinopathy to Alzheimer disease.

BACKGROUND: Diabetic retinopathy (DR) and Alzheimer disease (AD) share metabolic and vascular dysfunctions, but the extent to which they reflect overlapping genetic susceptibility and neurovascular-metabolic regulatory pathways remains unclear. We combined multi-omics analyses with population-based data to examine the genetic convergence, cellular pathways, and longitudinal association between DR and AD. METHODS: We performed a two-sample Mendelian randomisation (MR) to estimate the association between genetically predicted DR liability and AD risk. We used Bayesian colocalisation analysis to identify shared genomic loci, and summary-data-based MR (SMR) to detect expression-mediated genes jointly associated with DR and AD. We analysed single-cell RNA sequencing data to characterise shared cellular features and related biological pathways. We also conducted an MR-based mediation analysis to explore whether lipid-related, metabolic, or inflammatory traits mediated the observed DR-AD association, and a longitudinal analysis of the UK Biobank cohort to assess the association between DR and incident AD. RESULTS: With the MR analysis, we found that genetically predicted liability to DR was associated with a modest increase in AD risk. Colocalisation analysis supported a shared genetic signal. We identified three genes with shared expression-mediated associations across DR and AD through SMR. Functional enrichment analyses revealed partially overlapping neurovascular and metabolic pathways. Using MR-based mediation analysis, we found no significant intermediary traits linking DR and AD. Findings from the UK Biobank cohort were directionally consistent with the genetic analyses. CONCLUSIONS: Genetic liability to DR is associated with an increased risk of AD and is accompanied by shared expression-mediated effects and convergent neurovascular-metabolic pathways. These findings support the possibility that DR may serve as a clinically accessible indicator of increased neurodegenerative vulnerability.

Humans↗
PubMed2006

Cloning and characterization of protease inhibitor-like cDNAs from the Hessian fly mayetiola destructor (SAY).

Analysis of transcriptomes from the salivary glands and midgut of Hessian fly larvae Mayetiola destructor (say) identified a set of diverse cDNAs that encode proteins with a relatively high percentage (over 10%) of cysteinyl residues. Structural comparison of these putative proteins with known sequences in GenBank revealed that the positions of the cysteinyl residues in the identified proteins were highly conserved within a family of proteinase inhibitors despite very little overall sequence similarity. Phylogenetic analysis sorted this set of cDNAs into five different groups. To determine if these cDNAs indeed encode proteinase inhibitors, recombinant proteins were generated with two cDNAs from two different groups. Biochemical analysis of the recombinant proteins against commercial and insect gut proteinases demonstrated that the recombinant proteins are strong proteinase inhibitors with different specificities. Northern blot and real-time PCR analysis revealed that the different genes were expressed at different developmental stages and in different tissues. The overall results indicated that M. destructor contains a complex of genes that code for proteinase inhibitors which may regulate proteinase activities in different regulatory pathways. The GenBank accession numbers for the cDNAs in this paper were DQ232690 to DQ232718.

Amino Acid Sequence↗
PubMed2006

Connexin43 and the brain transcriptome of newborn mice.

Our previously reported cDNA array datasets from neonatal wild-type and Cx43-/- (approved gene symbol Gja1) mouse brains were further analyzed to identify underlying interlinkages in the brain transcriptome. The analysis revealed that no gene cohort sharing either primary function or chromosomal location was significantly altered (up-and down-regulation were roughly balanced) in Cx43-/- brains, but each cohort exhibited significant perturbation of transcript abundance proportions and reduced expression variability and coordination. By comparing pairwise expression correlations of all genes with one another in wild-type brains, we found genes exhibiting remarkable similarity or opposition to the coordination profile (set of synergistically, antagonistically, and independently expressed partners) of Cx43, one of the most similar being pannexin1, a vertebrate homolog of invertebrate gap junction proteins. This study indicates striking redundancy of expression controls over functional pathways and suggests that certain genes may play roles similar to or opposite that of Cx43 in organizing the brain transcriptome.

Animals↗
PubMed2026

Repeated emergence and fitness heterogeneity of KPC-33 in ST11 Klebsiella pneumoniae under ceftazidime-avibactam pressure.

Ceftazidime-avibactam (CZA) is an important therapeutic option for infections caused by Klebsiella pneumoniae carbapenemase (KPC)-producing Klebsiella pneumoniae. However, CZA exposure also selects for emergent KPC variants. Their in vivo evolutionary patterns, fitness consequences, and underlying molecular mechanisms remain unclear. We performed a longitudinal multiomics analysis of 35 clonally related ST11 KPC-producing K. pneumoniae isolates collected from eight hospitalized patients during clinical follow-up, most of whom had received CZA therapy. Whole-genome sequencing, antimicrobial susceptibility testing, in vitro competition assays, enzyme kinetic analysis, and transcriptomic sequencing were used to systematically characterize the within-host evolutionary dynamics of KPC variants and the fitness heterogeneity of KPC-33. Multiple KPC variants were identified during longitudinal follow-up, among which KPC-33 was the most frequently detected. Among the seven patients who received CZA treatment, KPC-33 was detected in longitudinal isolates from four patients. It was also identified in patient P3, who had not received CZA, whereas other variants were only sporadically identified. Biochemical analysis showed that KPC-33 exhibited an altered kinetic profile relative to KPC-2, characterized by reduced catalytic turnover and altered substrate affinity. KPC-33 did not exhibit a uniform and pronounced fitness defect but instead showed marked strain-dependent heterogeneity. Strains with higher competitive fitness generally showed only limited transcriptional changes, whereas those with lower fitness were accompanied by broader transcriptional remodeling. In this longitudinal cohort, KPC-33 was repeatedly detected, predominantly under CZA-associated selective conditions. Its fitness consequences were clearly strain background dependent and may be associated with the extent of transcriptional remodeling. These findings provide new evidence for understanding the in vivo evolution of CZA resistance.

KPC-33↗
PubMed2006

Assessment of representational difference analysis (RDA) to construct informative cDNA microarrays for gene expression analysis of species with limited transcriptome information, using red and green tomatoes as a model.

Microarray technology makes it feasible to analyse the expression of thousands of different gene elements in a single experiment. Most informative are 'whole genome' arrays, where all gene expression products of a single species or variety are represented. Such arrays are now available for a limited number of model species. However, for other, less well-documented species other routes are still necessary to obtain informative arrays. This includes the use of cDNA libraries. To enhance the amount of information that can be obtained from cDNA libraries, redundancy needs to be minimised, and the number of cDNAs relevant for the conditions of interest needs to be increased. Here, we used representational difference analysis (RDA), a mRNA subtraction procedure, as a tool to enhance the efficiency of cDNA libraries to be used to generate microarrays. Tomato was chosen as a model system for a less well-documented species. cDNA libraries for two distinct physiological conditions of tomato fruits, red and green, were made. The libraries were characterized by sequencing and hybridisation analysis. The RDA procedure was shown to be effective in selecting for genes of relevance for the physiological conditions under investigation, and against constitutively expressed genes. At the same time, redundancy was reduced, but complete normalisation was not obtained, and subsequent sequence analysis will be required to obtain non-redundant arrays. Further, known and putative ripening-related cDNAs were identified in hybridisation experiments on the basis of RNA populations as isolated from the green and red stage of ripening.

Fruit↗
PubMed2005

Analysis of methylation-sensitive transcriptome identifies GADD45a as a frequently methylated gene in breast cancer.

Treatment of the breast cancer cell line, MDAMB468 with the DNA methylation inhibitor, 5-azacytidine (5-AzaC) results in growth arrest, whereas the growth of the normal breast epithelial line DU99 (telomerase immortalized) is relatively unaffected. Comparing gene expression profiles of these two lines after 5-AzaC treatment, we identified 36 genes that had relatively low basal levels in MDAMB468 cells compared to the DU99 line and were induced in the cancer cell line but not in the normal breast epithelial line. Of these genes, 33 have associated CpG islands greater than 300 bp in length but only three have been previously described as targets for aberrant methylation in human cancer. Northern blotting for five of these genes (alpha-Catenin, DTR, FYN, GADD45a, and Zyxin) verified the array results. Further analysis of one of these genes, GADD45a, showed that 5-AzaC induced expression in five additional breast cancer cell lines with little or no induction in three additional lines derived from normal breast epithelial cells. The CpG island associated with GADD45a was analysed by bisulfite sequencing, sampling over 100 CpG dinucleotides. We found that four CpG's, located approximately 700 bp upstream of the transcriptional start site are methylated in the majority of breast cancer cell lines and primary tumors but not in DNA from normal breast epithelia or matched lymphocytes from cancer patients. Therefore, this simple method of dynamic transcriptional profiling yielded a series of novel methylation-sensitive genes in breast cancer including the BRCA1 and p53 responsive gene, GADD45a.

Azacitidine↗
PubMed2001

Parallel and comparative analysis of the proteome and transcriptome of sorbic acid-stressed Saccharomyces cerevisiae.

Exposure of Saccharomyces cerevisiae to 0.9 mM sorbic acid at pH 4.5 resulted in the upregulation of 10 proteins; Hsp42, Atp2, Hsp26, Ssa1 or Ssa2, Ssb1 or Ssb2, Ssc1, Ssa4, Ach1, Zwf1 and Tdh1; and the downregulation of three proteins; Ade16, Adh3 and Eno2. In parallel, of 6144 ORFs, 94 (1.53%) showed greater than a 1.4-fold increase in transcript level after exposure to sorbic acid and five of these were increased greater than two-fold; MFA1, AGA2, HSP26, SIP18 and YDR533C. Similarly, of 6144 ORFs, 72 (1.17%) showed greater than a 1.4-fold decrease in transcript level and only one of these, PCK1, was decreased greater than two-fold Functional categories of genes that were induced by sorbic acid stress included cell stress (particularly oxidative stress), transposon function, mating response and energy generation. We found that proteomic analysis yielded distinct information from transcript analysis. Only the upregulation of Hsp26 was detected by both methods. Subsequently, we demonstrated that a deletion mutant of Hsp26 was sensitive to sorbic acid. Thus, the induction of Hsp26, which occurs during adaptation to sorbic acid, confers resistance to the inhibitory effects of this compound.

DNA, Complementary↗
PubMed2006

Analysis of the bovine neutrophil transcriptome during glucocorticoid treatment.

The objective of this study was to characterize a large portion of the bovine neutrophil transcriptome following treatment with the anti-inflammatory glucocorticoid dexamethasone (Dex). Total RNA was isolated from blood neutrophils of healthy cattle (5 castrated male Holsteins) immediately following cell purification (0 h) or after ex vivo aging for 4 h with or without added Dex. Additional neutrophils were cotreated with a glucocorticoid receptor (GR) antagonist (RU486) and Dex for 4 h. RNA was amplified, dye labeled (Cy3 or Cy5), and hybridized to a series of National Bovine Functional Genomics Consortium (NBFGC) microarrays. LOWESS data normalization followed by mixture model analyses showed that 11.15% of the spotted NBFGC cDNAs (2,036/18,263) were expressed in 4-h (untreated) neutrophils. Subsequent two-step mixed-model analysis detected (P < or = 0.05) 1,109 differentially expressed genes, of which contrast analysis indicated those that were independently responsive to aging (1,064), Dex (502), RU486 + Dex (141), or RU486 (357). In silico analysis revealed that 416 of the differentially expressed genes are unknown, 59 did not cluster well based on known function, and 634 clustered into 20 ontological categories. Independent validation of differential expression was done for 14 of the putatively Dex-responsive genes across these categories. Results showed that Dex induced rapid translocation of GR into the neutrophil nucleus and signaled dramatic alterations in expression of genes that delay apoptosis, enhance bactericidal activity, and promote tissue remodeling without inflammation or fibrosis. Thus these findings revealed hitherto unappreciated plasticity of blood neutrophils and potentially novel anti-inflammatory/wound-healing actions of glucocorticoids.

Animals↗
PubMed2025

PLAID: ultrafast single-sample gene set enrichment scoring.

SUMMARY: In recent years, computational methods have emerged that calculate enrichment of gene signatures within individual samples. These signatures offer critical insights into the coordinated activity of functionally related genes, proteins or metabolites, enabling the identification of unique molecular profiles in individual cells and patients. This strategy is pivotal for patient stratification and advancement of personalized medicine. However, the rise of large-scale datasets, including single-cell profiles and population biobanks, has exposed significant computational inefficiencies in existing methods. Current methods often demand excessive runtime and memory resources, becoming impractical for large datasets. Overcoming these limitations is a focus of current efforts by bioinformatics teams in academia and the pharmaceutical industry, as essential to support basic and clinical biomedical research. To address this critical need, we developed PLAID (Pathway Level Average Intensity Detection), an ultrafast and memory optimized single sample gene set enrichment algorithm that utilizes sparse matrix computation. PLAID delivers highly accurate gene set scoring and surpasses the performance of current methods in single-cell and bulk transcriptomics, and proteomics data. PLAID uniquely integrates the most widely used gene set scoring algorithms, enabling researchers to apply multiple methods for cross-validation with outstanding runtime efficiency and minimal memory requirement. AVAILABILITY AND IMPLEMENTATION: PLAID is implemented in the R language for statistical computing. PLAID source code and installation instructions are available with no restrictions at https://github.com/bigomics/plaid.

Algorithms↗
PubMed2025

Blood phenylalanine lowering partially reverses white matter changes in a mouse model of phenylketonuria.

Phenylketonuria (PKU) is a genetic defect caused by lack of the liver enzyme phenylalanine hydroxylase (PAH). This deficiency results in elevated blood phenylalanine (Phe) levels and neurotoxicity, which is manifested by reduced brain size, lower neurotransmitter levels, and reduced myelination. The goal of this study was to investigate brain myelination defects and their reversibility upon blood Phe lowering by analyzing the corpus callosum (CC) of adult Pahenu2 (PAH-deficient) mice. MRI and immunostaining demonstrated a significant reduction in CC volume in Pahenu2 mice. Treatment with an adeno-associated vector (AAV) encoding mouse PAH for 3.5 months improved but did not completely normalize CC volume. Total cholesterol, a major component of myelin, was unchanged in the CC of Pahenu2 mouse, while some sterol intermediates were significantly reduced by treatment. Single-nuclei transcriptomics showed an upregulation of oxidative stress-related pathways and increased expression of transthyretin, ApoE, Cst3, and Cd81 in CC in Pahenu2 mice. Normalization of blood Phe restored gene expression to levels comparable to those of heterozygous mice and was associated with the generation of differentiated myelin-producing oligodendrocyte subtypes and neuroprotective astrocytes. In summary, Pahenu2 mice showed white matter abnormalities and changes in transcriptome and sterol profiles, which were partially corrected by the normalization of blood Phe.

Animals↗
PubMed2005

Gene expression profiling of cultured human NF1 heterozygous (NF1+/-) melanocytes reveals downregulation of a transcriptional cis-regulatory network mediating activation of the melanocyte-specific dopachrome tautomerase (DCT) gene.

One of the major primary features of the neurocutaneous genetic disorder Neurofibromatosis type 1 are the hyperpigmentary café-au-lait macules where disregulation of melanocyte biology is supposed to play a key etiopathogenic role. To gain better insight into the possible role of the tumor suppressor gene NF1, a transcriptomic microarray analysis was performed on human NF1 heterozygous (NF1+/-) melanocytes of a Neurofibromatosis type 1 patient and NF1 wild type (NF1+/+) melanocytes of a healthy control patient, both cultured from normally pigmented skin and hyperpigmented lesional café-au-lait skin. From the magnitude of gene effects, we found that gene expression was affected most strongly by genotype and less so by lesional type. A total of 137 genes had a significant twofold or more up- (72) or downregulated (65) expression in NF1+/- melanocytes compared with NF1+/+ melanocytes. Melanocytes cultured from hyperpigmented café-au-lait skin showed 37 upregulated genes whereas only 14 were downregulated compared with normal skin melanocytes. In addition, significant genotype xlesional type interactions were observed for 465 genes. Differentially expressed genes were mainly involved in regulating cell proliferation and cell adhesion. A high number of transcription factor genes, among which a specific subset important in melanocyte lineage development, were downregulated in the cis-regulatory network governing the activation of the melanocyte-specific dopachrome tautomerase (DCT) gene. Although the results presented have been obtained with a restricted number of patients (one NF1 patient and one control) and using cDNA microarrays that may limit their interpretation, the data nevertheless addresses for the first time the effect of a heterozygous NF1 gene on the expression of the human melanocyte transcriptome and has generated several interesting candidate genes helpful in elucidating the etiopathology of café-au-lait macules in NF1 patients.

Cells, Cultured↗
PubMed2026

Hepatic metabolic adaptation to endurance exercise: temporal and sex differences by multiomics integration and validation.

BACKGROUND: Although endurance exercise benefits liver health, sex-specific adaptive trajectories remain unclear. This study mapped dynamic liver adaptation in males and females during prolonged training and identified underlying molecular programs. METHODS: Using publicly available time-resolved liver multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), we established a computational pipeline for differential analysis of transcriptomic, proteomic, phosphoproteomic, and metabolomic data with FDR correction, followed by FGSEA pathway enrichment. Kinase activities were inferred through ortholog mapping and PhosphoSitePlus. Cross-omics co-expression networks were constructed using WGCNA and topological overlap to link omics features with physiological phenotypes. For experimental validation, liver tissues were collected from endurance-trained Sprague-Dawley rats, and key nodes were confirmed by Western blotting, qRT-PCR, and immunofluorescence/immunohistochemical staining. Public scRNA-seq data were further integrated to map multi-omics signals to single-cell resolution and assess functional changes in specific cell types. RESULTS: The hepatic response to exercise stress was stage-specific, shifting from early transcriptional activation to later proteomic and metabolic remodeling. Multi-omics integration revealed distinct sex-associated adaptive trajectories: males were more strongly associated with energy metabolism, redox-related programs, and amino acid/organic acid catabolism, whereas females showed prominent membrane lipid remodeling, proteostasis -related programs, and mitochondrial/ribosomal translational features. Single-cell analysis showed that tissue remodeling occurred without major lineage turnover, instead involving altered communication among pre-existing cell communities. Validation of PPP1R3G identified a protein-dominant exercise-responsive marker, supporting the contribution of post-transcriptional or protein-level regulation. CONCLUSIONS: Hepatic adaptation to endurance stress follows a cross-omics evolutionary pattern with sex-specific reprogramming of energy supply and homeostatic maintenance. This time-resolved framework clarifies how exercise improves liver function and supports sex-oriented metabolic interventions and therapeutic target discovery.

Animals↗
PubMed2006

Analysis of the Leishmania donovani transcriptome reveals an ordered progression of transient and permanent changes in gene expression during differentiation.

Leishmania donovani is an intracellular protozoan parasite that causes kala-azar in humans. During infection the extracellular insect forms (promastigotes) undergo rapid differentiation to intracellular amastigotes that proliferates in phagolysosomes of mammalian macrophages. We used microarray-based expression profiling to investigate the time-course of changes in RNA abundance during promastigote-to-amastigote differentiation in a host-free system that mimics this process. These studies revealed that several hundred genes underwent an ordered progression of transient or permanent up- and down-regulation during differentiation. Genes that were permanently up-regulated in amastigotes were enriched for transporters and surface proteins, but under-represented in genes involved in protein and other metabolism. Most of these changes occurred late in the differentiation process, when morphological differentiation was essentially complete. Down-regulated genes were over-represented in those involved in cell motility, growth and/or maintenance, and these changes generally occurred earlier in the process. Genes that were transiently up- or down-regulated during differentiation included those encoding heat shock proteins, ubiquitin hydrolases, RNA binding proteins, protein kinases, a protein phosphatase, and a histone deacetylase. These results suggest that changes in mRNA abundance may be important in signal transduction, as well as protein and mRNA turnover, during differentiation. In addition to these mRNA changes, other transcripts including one or more rRNAs and snoRNAs, and non-coding RNAs from several telomeres, also showed substantial changes in abundance during the differentiation process. This paper provides the first genome-scale quantitative analysis of gene expression during the transition from promastigotes to amastigotes and demonstrates the utility of the host-free differentiation system.

Animals↗
PubMed2005

Expression of copper-responsive genes in HepG2 cells.

The hypothesis that copper modulates the activity of intracellular signal transduction pathways to affect transcription, which ultimately disrupts normal development was investigated. Preliminary analysis of transcriptomes from HepG2 cells exposed to copper for 4 and 24 h identified 19 and 7 up-regulated genes (twofold; p <or= 0.05), respectively. Among the up-regulated genes, several have been previously reported to be responsive to metals or oxidative stress. Differentially expressed genes were grouped by the functional categories based on gene ontology (GO). Significantly enriched GO categories (p < 0.01) included copper ion homeostasis, cadmium and copper ion binding, and heme oxygenase and oxidoreductase activities. Real-time RT-PCR confirmed the effect of copper on the levels of MT2A, HSPA1A, CYP1A1 and HMOX1 expression.

Carcinoma, Hepatocellular↗
PubMed2025

Multi-omics technologies: Novel tools and methods for assessing nerve injury and regeneration.

Recently, with the rapid advancement of multi-omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, new tools and approaches have been introduced for studying nerve injury and regeneration. This review highlights the application and progress of multi-omics in uncovering the mechanisms of nerve injury, guiding the development of regenerative strategies, and promoting clinical translation. By integrating multi-omics datasets, researchers can comprehensively track dynamic molecular changes following nerve injury, including abnormal gene expression, disrupted protein signaling, altered metabolic programs, and shifts in the immune microenvironment. Single-cell multi-omics technologies resolve cellular heterogeneity, revealing the distinct functions of neurons, glial cells, and immune cell subpopulations during the injury response. Spatially resolved transcriptomics maintain the spatial context of lesion and regeneration sites, enabling precise localization for targeted interventions. Multi-omics technologies not only identify key molecular players involved in nerve regeneration but also create opportunities for personalized medicine. Nonetheless, integrating multi-omics data poses technical challenges, including high dimensionality, batch effects, and algorithmic constraints, while ethical concerns related to stem cell therapy and gene editing require stringent oversight. To transition from structural reconstruction to functional remodeling, future research should emphasize artificial intelligence-driven data integration, organ-on-a-chip modeling, and cross-disciplinary collaboration to overcome existing technical barriers and accelerate the clinical application of neuroregenerative therapies.

artificial intelligence↗
PubMed2006

Computational models with thermodynamic and composition features improve siRNA design.

BACKGROUND: Small interfering RNAs (siRNAs) have become an important tool in cell and molecular biology. Reliable design of siRNA molecules is essential for the needs of large functional genomics projects. RESULTS: To improve the design of efficient siRNA molecules, we performed a comparative, thermodynamic and correlation analysis on a heterogeneous set of 653 siRNAs collected from the literature. We used this training set to select siRNA features and optimize computational models. We identified 18 parameters that correlate significantly with silencing efficiency. Some of these parameters characterize only the siRNA sequence, while others involve the whole mRNA. Most importantly, we derived an siRNA position-dependent consensus, and optimized the free-energy difference of the 5' and 3' terminal dinucleotides of the siRNA antisense strand. The position-dependent consensus is based on correlation and t-test analyses of the training set, and accounts for both significantly preferred and avoided nucleotides in all sequence positions. On the training set, the two parameters' correlation with silencing efficiency was 0.5 and 0.36, respectively. Among other features, a dinucleotide content index and the frequency of potential targets for siRNA in the mRNA added predictive power to our model (R = 0.55). We showed that our model is effective for predicting the efficiency of siRNAs at different concentrations. We optimized a neural network model on our training set using three parameters characterizing the siRNA sequence, and predicted efficiencies for the test siRNA dataset recently published by Novartis. On this validation set, the correlation coefficient between predicted and observed efficiency was 0.75. Using the same model, we performed a transcriptome-wide analysis of optimal siRNA targets for 22,600 human mRNAs. CONCLUSION: We demonstrated that the properties of the siRNAs themselves are essential for efficient RNA interference. The 5' ends of antisense strands of efficient siRNAs are U-rich and possess a content similarity to the pyrimidine-rich oligonucleotides interacting with the polypurine RNA tracks that are recognized by RNase H. The advantage of our method over similar methods is the small number of parameters. As a result, our method requires a much smaller training set to produce consistent results. Other mRNA features, though expensive to compute, can slightly improve our model.

Artificial Intelligence↗