Variability In Expression Research Articles

Deciphering genetic variability and phenotype expression, assessing drought stress tolerance and multi-trait stability index of ( Vigna radiata ) genotypes in Chitwan, Nepal

Deciphering genetic variability and phenotype expression, assessing drought stress tolerance and multi-trait stability index of ( <i>Vigna radiata</i> ) genotypes in Chitwan, Nepal

Metabolic Adaptations in Phosphine-Resistant Tribolium castaneum Driven by Mitochondrial Enzyme Variability and Gene Expression.

Phosphine fumigation is essential for controlling storage pests like Tribolium castaneum, but its frequent application has resulted in resistance, primarily due to mutations in the Dihydrolipoamide dehydrogenase (DLD) gene associated with the rph2 allele. This study demonstrates that the Patiala population exhibits homozygous resistance variations across populations, contrasting with the susceptibility observed in laboratory cultures. Our assessment of mitochondrial DLD and Cytochrome c oxidase (COX) activities showed significantly elevated levels in the Patiala population, with increases of approximately sevenfold for DLD and 6.92-fold for COX, indicating mitochondrial adaptations for enhanced energy production. Kinetic analyses of DLD in the resistant Patiala population showed a higher Vmax (0.005 mmol/min) and a significantly increased Km (16.66 mM), indicating variations in maximal enzyme activity and substrate affinity. Furthermore, resistant T. castaneum populations displayed substantial upregulation of DLD and COX gene expression, with DLD expression increasing by 10.53-fold and COX expression peaking at 102.57-fold in Patiala. Pearson correlation analysis indicated strong positive correlations (r > 0.8) between enzymatic activity and gene expression for both DLD and COX, suggesting a coordinated role in resistance mechanisms. The PCA biplot illustrated distribution patterns of enzymatic activity and gene expression among field-resistant populations, highlighting the association between increased resistance and elevated enzymatic activity and gene expression levels. Therefore, the upregulation of DLD and COX activities in resistant populations underscores their critical roles in counteracting phosphine, reflecting metabolic reprogramming for improved energy production under stress.

Self-supervised learning for characterising histomorphological diversity and spatial RNA expression prediction across 23 human tissue types

As vast histological archives are digitised, there is a pressing need to be able to associate specific tissue substructures and incident pathology to disease outcomes without arduous annotation. Here, we learn self-supervised representations using a Vision Transformer, trained on 1.7 M histology images across 23 healthy tissues in 838 donors from the Genotype Tissue Expression consortium (GTEx). Using these representations, we can automatically segment tissues into their constituent tissue substructures and pathology proportions across thousands of whole slide images, outperforming other self-supervised methods (43% increase in silhouette score). Additionally, we can detect and quantify histological pathologies present, such as arterial calcification (AUROC = 0.93) and identify missing calcification diagnoses. Finally, to link gene expression to tissue morphology, we introduce RNAPath, a set of models trained on 23 tissue types that can predict and spatially localise individual RNA expression levels directly from H&E histology (mean genes significantly regressed = 5156, FDR 1%). We validate RNAPath spatial predictions with matched ground truth immunohistochemistry for several well characterised control genes, recapitulating their known spatial specificity. Together, these results demonstrate how self-supervised machine learning when applied to vast histological archives allows researchers to answer questions about tissue pathology, its spatial organisation and the interplay between morphological tissue variability and gene expression.

Controlled Noise: Evidence of epigenetic regulation of Single-Cell expression variability.

Understanding single-cell expression variability (scEV) or gene expression noise among cells of the same type and state is crucial for delineating population-level cellular function. While epigenetic mechanisms are widely implicated in gene expression regulation, a definitive link between chromatin accessibility and scEV remains elusive. Recent advances in single-cell techniques enable the study of single-cell multiomics data that include the simultaneous measurement of scATAC-seq and scRNA-seq within individual cells, presenting an unprecedented opportunity to address this gap. This paper introduces an innovative testing pipeline to investigate the association between chromatin accessibility and scEV. With single-cell multiomics data of scATAC-seq and scRNA-seq, the pipeline hinges on comparing the prediction performance of scATAC-seq data on gene expression levels between highly variable genes (HVGs) and non-highly variable genes (non-HVGs). Applying this pipeline to paired scATAC-seq and scRNA-seq data from human hematopoietic stem and progenitor cells, we observed a significantly superior prediction performance of scATAC-seq data for HVGs compared to non-HVGs. Notably, there was substantial overlap between well-predicted genes and HVGs. The gene pathways enriched from well-predicted genes are highly pertinent to cell type-specific functions. Our findings support the notion that scEV largely stems from cell-to-cell variability in chromatin accessibility, providing compelling evidence for the epigenetic regulation of scEV and offering promising avenues for investigating gene regulation mechanisms at the single-cell level. The source code and data used in this paper can be found at https://github.com/SiweiCui/EpigeneticControlOfSingle-CellExpressionVariability. Supplementary data are available at Bioinformatics online.

Wildfire Evacuation Challenges in Multi-ethnic Communities: An Information Communication Perspective

The areas with high wildfire risk of wildfire are inhabited by multiple ethnic groups in China. In the event of a wildfire, there are many challenges for the government to release evacuation information to residents in multi-ethnic communities. Based on the Shannon-Weaver model of communication, a whole-process communication model of evacuation information is constructed to reflect the challenges during the whole process, including the dynamic variability, regional difference and cross-language expression of evacuation information at the stage of information generation, the inadequate communication capability of information carriers and instability of communication infrastructures at the stage of information transmission, and comprehension impairment and irrational perception at the stage of information perception. In response to these challenges, the authors also make some suggestions from the intelligent information technology, crisis response system and offline communication channels.

Evaluation of a large-scale aptamer proteomics platform among patients with kidney failure on dialysis

Background Patients with kidney failure suffer high mortality, and we currently lack markers for risk stratification for these patients. We carried out a quality control study of a modified aptamer assay (SomaScan v.4.0) that measures ~ 5000 proteins, in preparation for a larger study using this platform in cohorts with kidney failure. Methods Forty participants from the Cardiac, Endothelial Function and Arterial Stiffness in End-Stage Renal Disease (CERES study) were selected to analyze technical and short-term biological variability, orthogonal correlations and differential protein expression in plasma from patients who died during 2.5 year follow-up. Long-term (one year) variability was studied in 421 participants in the Chronic Renal Insufficiency Cohort. We evaluated 4849 aptamers (4607 unique proteins) using data formats including raw data and data formatted using Adaptive Normalization by Maximum Likelihood (ANML), an algorithm developed for SomaScan data in individuals with normal kidney function. Results In ANML format, median[IQR] intra-assay coefficient of variation (CV) was 2.38%[1.76, 3.40] and inter-assay CV was 7.38%[4.61, 13.12]. Short-term within-subject CV was 5.76% [3.35, 9.72]; long-term CV was 8.71%[5.91, 13.37]. Spearman correlations between aptamer and traditional assays for PTH, NT-proBNP, FGF-23 and CRP were all &gt; 0.7. Fold-change (FC) in protein levels among non-survivors, significant after Bonferroni correction, included SVEP1 (FC[95% CI] 2.14 [1.62, 2.82]), keratocan (1.74 [1.40, 2.15]) and LanC-like protein 1 (0.56 [0.45, 0.70]). Compared to raw aptamer data, technical and short-term biological variability in paired samples was lower in ANML-formatted data. ANML formatting had minimal impact on orthogonal correlations with traditional assays or the associations of proteins with the phenotype of mortality. Conclusions SomaScan had excellent technical variability and low within-subject short-term variability. ANML formatting could facilitate comparison of biomarker results with other studies that utilize this format. We expect SomaScan to provide novel and reproducible information in patients with kidney failure on dialysis.

Comparing the effect of larval dispersal strategies on morphological versus genetic differentiation in two neotropical fiddler crabs

AbstractThe dispersal mode of estuarine invertebrates has a strong effect on genetic variability and phenotypic expression, potentially maintaining gene flow among widely separated populations or limiting connectivity among close ones. Understanding the dispersal strategies effects can support adequate strategies for environment management and understand the evolutionary history of the studied species. A comparative study on the effect of larval dispersal strategies (export vs retention) along the overall geographic distribution ranges of adult populations of two co‐distributed fiddler crab species was performed. Geometric morphometric techniques were used to evaluate morphological differentiation in the shape of the carapace and major cheliped propodus in 10 populations of Minuca mordax and five populations of Leptuca leptodactyla. Potential genetic differentiation was assessed using DNA sequence data from up to 170 fiddler crab specimens, corresponding to the mitochondrial gene cytochrome c oxidase subunit 1 (COX1). Patterns of genetic and morphological characteristics diverged among populations of both species. In terms of morphology, populations of both species showed intraspecific variation in the shape of the carapace and, to a lesser extent, in the major cheliped propodus. This observed intraspecific variation followed a clear geographic pattern of morphometric differentiation, in which the geographic origin is associated with a phenotypic response to the environmental diversity along the extended Brazilian coast. In contrast, there are shared haplotypes in populations separated by more than 4000 km, but with significant ΦST values among most populations of L. leptodactyla and M. mordax, suggesting a moderate to high level of gene flow. Therefore, it can be concluded that the split of the Central South Equatorial Current has not acted as an efficient long‐term barrier to the dispersal of larvae in both species. In M. mordax, a slight limitation of genetic exchange can be observed between the southernmost populations and the remaining ones. This first evidence of genetic structuring within this widely distributed species is consistent with its documented strategy to retain larvae in the estuarine environments. However, occasional transport of larvae to more open coastal waters seems to maintain stepwise gene flow between neighboring populations. Overall, our results still provide evidence of more pronounced genetic homogeneity in a species with a larval export strategy (L. leptodactyla) compared to a species with a larval retention strategy (M. mordax). This suggests that larval dispersal strategies, coupled with the microhabitat in which the respective species occur, have a noticeable effect on the degree of gene flow. Most likely, these biological aspects are further influenced by the estuarine and coastline geomorphology.

Gene expression variability in long-term survivors of childhood cancer and cancer-free controls in response to ionizing irradiation

BackgroundDifferential expression analysis is usually adjusted for variation. However, most studies that examined the expression variability (EV) have used computations affected by low expression levels and did not examine healthy tissue. This study aims to calculate and characterize an unbiased EV in primary fibroblasts of childhood cancer survivors and cancer-free controls (N0) in response to ionizing radiation.MethodsHuman skin fibroblasts of 52 donors with a first primary neoplasm in childhood (N1), 52 donors with at least one second primary neoplasm (N2 +), as well as 52 N0 were obtained from the KiKme case–control study and exposed to a high (2 Gray) and a low dose (0.05 Gray) of X-rays and sham- irradiation (0 Gray). Genes were then classified as hypo-, non-, or hyper-variable per donor group and radiation treatment, and then examined for over-represented functional signatures.ResultsWe found 22 genes with considerable EV differences between donor groups, of which 11 genes were associated with response to ionizing radiation, stress, and DNA repair. The largest number of genes exclusive to one donor group and variability classification combination were all detected in N0: hypo-variable genes after 0 Gray (n = 49), 0.05 Gray (n = 41), and 2 Gray (n = 38), as well as hyper-variable genes after any dose (n = 43). While after 2 Gray positive regulation of cell cycle was hypo-variable in N0, (regulation of) fibroblast proliferation was over-represented in hyper-variable genes of N1 and N2+. In N2+, 30 genes were uniquely classified as hyper-variable after the low dose and were associated with the ERK1/ERK2 cascade. For N1, no exclusive gene sets with functions related to the radiation response were detected in our data.ConclusionN2+ showed high degrees of variability in pathways for the cell fate decision after genotoxic insults that may lead to the transfer and multiplication of DNA-damage via proliferation, where apoptosis and removal of the damaged genome would have been appropriate. Such a deficiency could potentially lead to a higher vulnerability towards side effects of exposure to high doses of ionizing radiation, but following low-dose applications employed in diagnostics, as well.

The effect of microRNA on protein variability and gene expression fidelity

Small regulatory RNA molecules such as microRNA modulate gene expression through inhibiting the translation of messenger RNA (mRNA). Such post-transcriptional regulation has been recently hypothesized to reduce the stochastic variability of gene expression around average levels. Here we quantify noise in stochastic gene expression models with and without such regulation. Our results suggest that silencing mRNA post-transcriptionally will always increase rather than decrease gene expression noise when the silencing of mRNA also increases its degradation as is expected for microRNA interactions with mRNA. In that regime we also find that silencing mRNA generally reduces the fidelity of signal transmission from deterministically varying upstream factors to protein levels. These findings suggest that microRNA binding to mRNA does not generically confer precision to protein expression.

The effect of microRNA on protein variability and gene expression fidelity

Small regulatory RNA molecules such as microRNA modulate gene expression through inhibiting the translation of messenger RNA (mRNA). Such posttranscriptional regulation has been recently hypothesized to reduce the stochastic variability of gene expression around average levels. Here, we quantify noise in stochastic gene expression models with and without such regulation. Our results suggest that silencing mRNA posttranscriptionally will always increase, rather than decrease, gene expression noise when the silencing of mRNA also increases its degradation, as is expected for microRNA interactions with mRNA. In that regime, we also find that silencing mRNA generally reduces the fidelity of signal transmission from deterministically varying upstream factors to protein levels. These findings suggest that microRNA binding to mRNA does not generically confer precision to protein expression.

HSF1 is involved in immunotherapeutic response through regulating APOJ/STAT3-mediated PD-L1 expression in hepatocellular carcinoma

ABSTRACT Hepatocellular cancer (HCC) is a serious illness with high prevalence and mortality throughout the whole world. For advanced HCC, immunotherapy is somewhat impactful and encouraging. Nevertheless, a substantial proportion of patients with advanced HCC are still unable to achieve a durable response, owing to heterogeneity from clonal variability and differential expression of the PD-1/PD-L1 axis. Recently, heat shock factor 1 (HSF1) is recognized as an important component of tumor immunotherapeutic response as well as related to PD-L1 expression in cancer. However, the mechanism of HSF1 regulating PD-L1 in cancer, especially in HCC, is still not fully clear. In this study, we observed the significantly positive correlation between HSF1 expression and PD-L1 expression in HCC samples; meanwhile combination expressions of HSF1 and PD-L1 served as the signature for predicting prognosis of patients with HCC. Mechanistically, HSF1 upregulated PD-L1 expression by inducing APOJ expression and activating STAT3 signaling pathway in HCC. In addition, we explored further the potential values of targeting the HSF1-APOJ-STAT3 axis against CD8+ T cells-mediated cancer cells cytotoxicity. These findings unveiled the important involvement of HSF1 in regulating PD-L1 expression in HCC as well as provided a novel invention component for improving the clinical response rate and efficacy of PD-1/PD-L1 blockade.

Variations in phenotypic plasticity in a cosmopolitan copepod species across latitudinal hydrographic gradients

Studies assessing latitudinal variations in habitat conditions and phenotypic plasticity among populations yield evidence of the mechanisms governing differentiation in the potential to adapt to current/future habitat changes. The cosmopolitan copepod species Acartia tonsa thrives across ocean clines delimiting Seasonal (30–40° S) and Permanent (10–30° S) Upwelling coastal provinces established during the middle–late Pliocene (3.6–1.8 Ma) alongshore the South East Pacific (SEP), nowadays exhibiting contrasting variability features related to several ocean drivers (temperature, salinity, pH, and food availability). Latitudinal variation across the range of environmental conditions of the coastal provinces can contribute toward shaping divergent A. tonsa’s phenotypes, for example, through specific patterns of phenotypic plasticity in morphological and physiological traits and tolerance to environmental drivers. With the aim of contributing to the understanding of these adaptive processes in a relatively little studied oceanic region, here we compared the expression of parental (i.e., adult size, egg production, and ingestion rate) and offspring (i.e., egg size) traits in relation to variation in environmental habitat conditions across different cohorts of two distant (&amp;gt; 15° latitude) A. tonsa populations inhabiting estuarine and upwelling habitats located in the Seasonal and Permanent Upwelling province, respectively. Mean conditions and ranges of variability in the habitat conditions and phenotypic plasticity of parental and offspring traits within and among cohorts of A. tonsa populations varied significantly across the different examined regions (i.e., Seasonal vs. Permanent). We also found significant differences in the coupling of habitat variability and trait expression, suggesting that the differences in trait expressions might be related to habitat variability. The phenotypic divergence was translated to cohort-related patterns of trait trade-offs regulating reproduction and tolerance of egg production efficiency that can jointly determine the level of plasticity, genetic structure, or local adaptation. The current findings provide novel evidence of how divergent phenotypes might sustain A. tonsa populations across variable coastal provinces of the SEP.

Critical evaluation of an autologous peripheral blood mononuclear cell-based humanized cancer model.

The use of humanized mouse models for oncology is rapidly expanding. Autologous patient-derived systems are particularly attractive as they can model the human cancer's heterogeneity and immune microenvironment. In this study, we developed an autologous humanized mouse cancer model by engrafting NSG mice with patient-derived xenografts and infused matched peripheral blood mononuclear cells (PBMCs). We first defined the time course of xenogeneic graft-versus-host-disease (xGVHD) and determined that only minimal xGVHD was observed for up to 8 weeks. Next, colorectal and pancreatic cancer patient-derived xenograft bearing NSG mice were infused with 5x106 human PBMCS for development of the humanized cancer models (iPDX). Early after infusion of human PBMCs, iPDX mice demonstrated engraftment of human CD4+ and CD8+ T cells in the blood of both colorectal and pancreatic cancer patient-derived models that persisted for up to 8 weeks. At the end of the experiment, iPDX xenografts maintained the features of the primary human tumor including tumor grade and cell type. The iPDX tumors demonstrated infiltration of human CD3+ cells with high PD-1 expression although we observed significant intra and inter- model variability. In summary, the iPDX models reproduced key features of the corresponding human tumor. The observed variability and high PD-1 expression are important considerations that need to be addressed in order to develop a reproducible model system.

Deciphering Haplotypic Variation and Gene Expression Dynamics Associated with Nutritional and Cooking Quality in Rice

Nutritional quality improvement of rice is the key to ensure global food security. Consequently, enormous efforts have been made to develop genomics and transcriptomics resources for rice. The available omics resources along with the molecular understanding of trait development can be utilized for efficient exploration of genetic resources for breeding programs. In the present study, 80 genes known to regulate the nutritional and cooking quality of rice were extensively studied to understand the haplotypic variability and gene expression dynamics. The haplotypic variability of selected genes were defined using whole-genome re-sequencing data of ~4700 diverse genotypes. The analytical workflow identified 133 deleterious single-nucleotide polymorphisms, which are predicted to affect the gene function. Furthermore, 788 haplotype groups were defined for 80 genes, and the distribution and evolution of these haplotype groups in rice were described. The nucleotide diversity for the selected genes was significantly reduced in cultivated rice as compared with that in wild rice. The utility of the approach was successfully demonstrated by revealing the haplotypic association of chalk5 gene with the varying degree of grain chalkiness. The gene expression atlas was developed for these genes by analyzing RNA-Seq transcriptome profiling data from 102 independent sequence libraries. Subsequently, weighted gene co-expression meta-analyses of 11,726 publicly available RNAseq libraries identified 19 genes as the hub of interactions. The comprehensive analyses of genetic polymorphisms, allelic distribution, and gene expression profiling of key quality traits will help in exploring the most desired haplotype for grain quality improvement. Similarly, the information provided here will be helpful to understand the molecular mechanism involved in the development of nutritional and cooking quality traits in rice.

A pan-cancer analysis of the oncogenic role of secreted phosphoprotein 1 (SPP1) in human cancers.

BackgroundEmerging evidence suggests that secreted phosphoprotein 1 (SPP1) is involved in tumor cell progression in multiple cancer types. However, the role of SPP1 in different cancers is still not clear.MethodsWe used data from The Cancer Genome Atlas (TCGA) to analyze the multiomic roles of SPP1, including RNA expression, DNA methylation, protein phosphorylation, immune infiltration, and overall survival (OS) in 33 tumor types.ResultsSPP1 is highly expressed in most cancer types, and its methylation variability and mRNA expression level are both correlated with prognosis in multiple cancer types. A higher S234 phosphorylation level was observed in 4 types of tumors, including colon adenocarcinoma (COAD) and lung adenocarcinoma (LUAD). SPP1 expression level was positively associated with the infiltration level of dendritic cells, neutrophils, and macrophages in multiple cancer types. It was also significantly positively correlated with hepatitis A virus cellular receptor 2 (HAVCR2), which was observed in most tumor types, including brain lower grade glioma (LGG) and ovarian serous cystadenocarcinoma (OV). Moreover, myeloid cell differentiation and leukocyte migration were observed in the enrichment analysis, suggesting that SPP1 might induce immune escape.ConclusionsPan-cancer analysis using a multiomic approach offered a comprehensive overview of SPP1. This protein plays an important role in most of the analyzed tumor types and could be a valuable prognostic marker across different types of cancer.

Genome-Wide Differential DNA Methylomes Provide Insights into the Infertility of Triploid Oysters.

Chromosomal incompatibility and gene expression changes would affect the development of polyploid gonad and gamete formation. The role of epigenetics like DNA methylation in reproductive development is fully demonstrated in diploid animals. The lack of polyploid species and the infertility of polyploid animals, especially the odd ploidy, limit the study of epigenetic regulation mechanism of polyploid reproduction. Fertile and infertile individuals exist in triploid Pacific oyster Crassostrea gigas, which provide an interesting model for studies on the effect of epigenetic regulation on gonadal development. The whole genome single base resolution DNA methylomes in gonads of triploid females α (F-3nα), triploid females β (F-3nβ), triploid males α (M-3nα), triploid hermaphrodite predominantly males (HPM-3n), diploid females (F-2n), and diploid males (M-2n) were generated by using bisulfite-sequencing. The overall DNA methylation profiles in gene regions and transposable regions of fertile and infertile triploid oysters were consistent with those of diploid oysters. The DNA methylation level of CG context decreased in infertile triploid oysters, with more hypomethylated than hypermethylated regions, and the opposite is true in fertile triploid oysters. Genes harbored with differentially methylated regions (DMRs) in infertile triploids were mainly related to the metabolism pathways and the signal pathways. Correlation analysis indicated that the expression of gene transcriptions was generally positively associated with DNA methylation in gene body regions, and DMRs in infertile triploid oysters played significant roles in gonadal development as a possible critical epigenetic regulator of gonadal development gene transcriptional activity. These findings indicate a potential relationship between DNA methylation variability and gene expression plasticity in newly formed polyploidy. As far as we know, this is the first study revealing the epigenetic regulation of gonadal development in invertebrates based on fertile and infertile models, meanwhile providing a new mentality to explore the regulatory mechanisms of infertility in triploids.

Integrated analysis of gait parameters and gene expression profiles in a murine model of subarachnoid hemorrhage.

Gait analysis has been widely used to examine the behavioral presentation of numerous neurological disorders. Thorough murine model evaluation of the subarachnoid hemorrhage (SAH)-associated gait deficits is missing. This study measures gait deficits using a clinically relevant murine model of SAH to examine associations between gait variability and SAH-associated gene expressions. A total of 159 dynamic and static gait parameters from the endovascular perforation murine model for simulating clinical human SAH were determined using the CatWalk system. Eighty gait parameters and the mRNA expression levels of 35 of the 88 SAH-associated genes were differentially regulated in the diseased models. Totals of 42 and 38 gait parameters correlated with the 35 SAH-associated genes positively and negatively with Pearson's correlation coefficients of >0.7 and <-0.7, respectively. p-SP1453 expression in the motor cortex in SAH animal models displays a significant correlation with a subset of gait parameters associated with muscular strength and coordination of limb movements. Our data highlights a strong correlation between gait variability and SAH-associated gene expression. p-SP1453 expression could act as a biomarker to monitor SAH pathological development and a therapeutic target for SAH.

Abstract P796: Integrated Analysis of Gait Parameters and Gene Expression Profiles in a Murine Model of Subarachnoid Hemorrhage

Objective: Gait variability analysis has been adopted in clinical settings to characterize the presentation of various neurological diseases. However, literature and practice lack a comprehensive murine model assessment of the gait deficits that result from subarachnoid hemorrhage (SAH). Further, correlations between gait parameters and the gene expression profiles associated with SAH have yet to be identified. The present study quantitatively assesses gait deficits through a clinically relevant murine model of SAH to determine associations between gait deficits and SAH-related gene expressions. Methods: A total of 159 dynamic and static gait parameters from the endovascular perforation murine model for simulating clinical human SAH were measured using the CatWalk system. Pearson’s correlation analysis was applied, and 88 genes associated with SAH were identified from the Ingenuity Pathway Analysis database to aid the investigation of the relationship between gait variability and gene expression profiles. Results: Eighty gait parameters and the mRNA expression levels of 35 of the 88 SAH-associated genes exhibited significant change in the SAH models (p &lt; 0.05). Totals of 42 and 38 gait parameters correlated with the 35 SAH-associated genes positively and negatively with Pearson’s correlation coefficients of &gt; 0.7 and &lt; -0.7, respectively. p-SP1 453 expression in the motor cortex in SAH animal models displays a significant correlation with a subset of gait parameters associated with muscular strength and coordination of limb movements. Conclusion: This examination of gait variability and its strong correlation to gene expression profiles provides a quantitative and reliable assessment of the SAH model’s motor performance. This research provides valuable insights into the study of disease progression and offers novel therapeutic interventions in the murine modeling of SAH. p-SP1 453 expression could act as a biomarker to monitor SAH pathological development and a therapeutic target for SAH.

Interplay between genetic, epigenetic, and gene expression variability: Considering complexity in evolvability.

Genetic variability, epigenetic variability, and gene expression variability (noise) are generally considered independently in their relationship with phenotypic variation. However, they appear to be intrinsically interconnected and influence it in combination. The study of the interplay between genetic and epigenetic variability has the longest history. This article rather considers the introduction of gene expression variability in its relationships with the two others and reviews for the first time experimental evidences over the four relationships connected to gene expression noise. They show how introducing this third source of variability complicates the way of thinking evolvability and the emergence of biological novelty. Finally, cancer cells are proposed to be an ideal model to decipher the dynamic interplay between genetic, epigenetic, and gene expression variability when one of them is either experimentally increased or therapeutically targeted. This interplay is also discussed in an evolutionary perspective in the context of cancer cell drug resistance.

NMR-based metabolomic analysis of the seasonal and regional variability of phytochemical compounds in Curtisia dentata stem bark

Traditional medicine markets are provided with medicinal plant material throughout the year, however, internal (e.g. plant age, genetic variability and differential expression of genes) and external factors (e.g. water and nutrient availability, rainfall, photoperiod and herbivory), affect secondary metabolite production in plants. In this study, seasonal variability in metabolite production in Curtisia dentata trees from two geographically separated regions in South Africa are compared. NMR analysis of C. dentata stem bark samples yielded spectral data which were processed in MestReNova to perform multivariate data analysis using Soft Independent Modeling of Class Analogy (SIMCA) software. This study shows that there are not only seasonal, regional and yearly differences in secondary metabolite production in C. dentata trees, but that production patterns of hydrophilic and lipophilic chemical compounds in individual trees also vary. Sucrose, isoeugenol and betulinic acid have been used in a targeted analysis to show the variation in individual compounds in the individual trees as a response to seasonal and geographical differences. Therefore, the season and year, as well as the region, harvesting site and specific trees from which plant material is collected affect the concentrations of chemical compounds extracted from C. dentata stem bark for the preparation of remedies.