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Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers─as caused by the additional burden of artificial genetic circuits─shifts a cell's priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state model of gene expression, capturing characteristics like energy dissipation─which we link to the entropy production rate─and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit's functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energetic costs of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.

Exercise has been recognized as a beneficial factor for cognitive health, particularly in relation to the hippocampus, a vital brain region responsible for learning and memory. Previous research has demonstrated that exercise-mediated improvement of learning and memory in humans and rodents correlates with increased adult neurogenesis and processes related to enhanced synaptic plasticity. Nevertheless, the underlying molecular mechanisms are not fully understood. With the aim to further elucidate these mechanisms, we provide a comprehensive dataset of the mouse hippocampal transcriptome at the single-cell level after 4 weeks of voluntary wheel-running. Our analysis provides a number of interesting observations. For example, the results suggest that exercise affects adult neurogenesis by accelerating the maturation of a subpopulation of Prdm16-expressing neurons. Moreover, we uncover the existence of an intricate crosstalk among multiple vital signaling pathways such as NF-κB, Wnt/β-catenin, Notch, and retinoic acid (RA) pathways altered upon exercise in a specific cluster of excitatory neurons within the Cornu Ammonis (CA) region of the hippocampus. In conclusion, our study provides an important resource dataset and sheds further light on the molecular changes induced by exercise in the hippocampus. These findings have implications for developing targeted interventions aimed at optimizing cognitive health and preventing age-related cognitive decline. [ABSTRACT FROM AUTHOR]

ABSTRACT Heat stress can affect several biological pathways. This study aimed to compare the effects of chronic and acute heat stress on the oxidative status and inflammatory responses of chick’s hearts. Chronic and acute heat stress were induced in chicks, heart tissues were examined for morphological changes, and gene expression was analyzed in heart samples. Our results showed that prolonged heat exposure caused a dramatic reduction in chicks body weight, increased lesions, and ruptured cardiac muscle fibers in the hearts, confirming that chronic heat stress damages heart tissues and causes inflammation. Our gene expression results confirmed that heat stress induces oxidative stress and inflammation in the hearts of chicks, and this is evidenced by changes in the expression of NRF2 and CAT as antioxidant factors, NFκB and LITAF as anti-inflammatory factors, and changes in the expression of Leptin as an activator of Reactive Oxygen Species production and induction of proinflammatory factors. Our study also showed that the induction of anti-inflammatory and antioxidant genes was greater upon exposure to chronic heat stress than acute heat stress. These findings confirm that chickens generally tolerate chronic heat stress better than acute heat stress.

Abstract Background Horizontal gene transfer inference approaches are usually based on gene sequences: parametric methods search for patterns that deviate from a particular genomic signature, while phylogenetic methods use sequences to reconstruct the gene and species trees. However, it is well-known that sequences have difficulty identifying ancient transfers since mutations have enough time to erase all evidence of such events. In this work, we ask whether character-based methods can predict gene transfers. Their advantage over sequences is that homologous genes can have low DNA similarity, but still have retained enough important common motifs that allow them to have common character traits, for instance the same functional or expression profile. A phylogeny that has two separate clades that acquired the same character independently might indicate the presence of a transfer even in the absence of sequence similarity. Our contributions We introduce perfect transfer networks, which are phylogenetic networks that can explain the character diversity of a set of taxa under the assumption that characters have unique births, and that once a character is gained it is rarely lost. Examples of such traits include transposable elements, biochemical markers and emergence of organelles, just to name a few. We study the differences between our model and two similar models: perfect phylogenetic networks and ancestral recombination networks. Our goals are to initiate a study on the structural and algorithmic properties of perfect transfer networks. We then show that in polynomial time, one can decide whether a given network is a valid explanation for a set of taxa, and show how, for a given tree, one can add transfer edges to it so that it explains a set of taxa. We finally provide lower and upper bounds on the number of transfers required to explain a set of taxa, in the worst case.

Cocaine self-administration is a complexly determined trait, with a substantial proportion of individual differences being determined by genetic variation. However, the relevant genetic variants that drive heritable differences in cocaine use remain undiscovered. Cocaine intravenous self-administration (IVSA) procedures in laboratory animals provide opportunities to prospectively investigate neurogenetic influences on the acquisition of voluntary cocaine use. Here, we provide information on cocaine (or saline-as a control) IVSA in 84 members of the hybrid mouse diversity panel (HMDP), an array of genetically distinct classical or recombinant inbred strains. We found cocaine IVSA to be substantially heritable in this population, with strain-level intake ranging for near 0 to >25 mg/kg/session. Though saline IVSA was also found to be heritable, a modest genetic correlation between cocaine and saline IVSA indicates that operant responding for the cocaine reinforcer was influenced, at least in part, by unique genetic variants. Genome-wide association studies (GWAS) of infusions earned in cocaine and saline groups revealed significant quantitative trait loci (QTL) on Chromosomes 3 and 14 for cocaine, but not saline, IVSA. Positional candidates were further prioritized through use of bulk RNA sequencing data that revealed genes with cis-eQTL and genetic correlation to number of infusions. Additionally, these data identify reference strains with extreme cocaine IVSA phenotypes, revealing them as polygenic models of risk and resilience to cocaine reinforcement. This work is part of an ongoing effort to characterize genetic variation that moderates cocaine IVSA that may, in turn, provide a more comprehensive understanding of cocaine risk genetics and neurobiology.

Background and aim: The complex dynamic interplay between different biological pathways involved in atherosclerosis development has rendered the identification of specific therapeutic targets a challenging quest. We aimed to identify specific genes and mechanistic pathways associated with the early development of fibro-atheromas in a swine model of atherosclerosis. Methods: The Wisconsin Miniature Swine™ model of Familial Hypercholesterolemia (WMS-FH, n = 11) and genetically related WMS controls (WMS-N, n = 11) were used. The infrarenal aorta was harvested from both groups for histopathologic and transcriptomic profiling at 12 months. Bioinformatic analysis was performed to identify hub genes and pathways central to disease pathophysiology. The expression of ITGB2, the top ranked hub gene, was manipulated in cell culture and the expression of interconnected genes was tested. Results: Fibro-atheromatous lesions were documented in all WMS-FH aortic tissues and displayed internal elastic lamina (IEL) disruption, significant reduction of myofibroblast presence and disorganized collagen deposition. No fibro-atheromas were observed in the control group. A total of 266 differentially expressed genes (DEGs) were upregulated in WMS-FH aortic tissues, while 29 genes were downregulated. Top identified hub genes included ITGB2, C1QA, LCP2, SPI1, CSF1R, C5AR1, CTSS, MPEG1, C1QC, and CSF2RB. Overexpression of ITGB2 resulted in elevated expression of other interconnected genes expressed in porcine endothelial cells. Conclusion: In a swine translational model of atherosclerosis, transcriptomic analysis identified ITGB2 as a central hub gene associated inflammation and early fibroatheroma development making it a potential therapeutic target at this stage of disease.

In this investigation, the study focused on the RNAseq data generated in response to Fusarium oxysporum f.sp. cubense (Foc) race1 (Cavendish infecting strain VCG 0124), targeting both resistant (cv. Rose, AA) and susceptible cultivars (Namarai, AA), and Tropical Race 4 (TR4, strain VCG 01213/16), involving resistant (cv. Rose, AA) and susceptible cultivars (Matti, AA). The respective contrasting cultivars were independently challenged with Foc race1 and TR4, and the root and corm samples were collected in two replications at varying time intervals [0th (control), 2nd, 4th, 6th, and 8th days] in duplicates. The RNA samples underwent stringent quality checks, with all 80 samples meeting the primary parameters, including a satisfactory RNA integrity number (>7). Subsequent library preparation and secondary quality control steps were executed successfully for all samples, paving the way for the sequencing phase. Sequencing generated an extensive amount of data, yielding a range of 10 to 31 million paired-end raw reads per sample, resulting in a cumulative raw data size of 11–50 GB. These raw reads were aligned against the reference genome of Musa acuminata ssp. malaccensis version 2 (DH Pahang), as well as the pathogen genomes of Foc race 1 and Foc TR4, using the HISAT2 alignment tool. The focal point of this study was the investigation of differential gene expression patterns of Musa spp. upon Foc infection. In Foc race1 resistant and susceptible root samples across the designated day intervals, a significant number of genes displayed up-regulation (ranging from 1 to 228) and down-regulation (ranging from 1 to 274). In corm samples, the up-regulated genes ranged from 1 to 149, while down-regulated genes spanned from 3 to 845. For Foc TR4 resistant and susceptible root samples, the expression profiles exhibited a notable up-regulation of genes (ranging from 31 to 964), along with a down-regulation range of 316–1315. In corm samples, up-regulated genes ranged from 57 to 929, while down-regulated genes were observed in the range of 40–936. In addition to the primary analysis, a comprehensive secondary analysis was conducted, including Gene Ontology (GO), euKaryotic Orthologous Groups (KOG) classification, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and investigations into Simple Sequence Repeats (SSRs), Single Nucleotide Polymorphisms (SNPs), and microRNA (miRNA). The complete dataset was carefully curated and housed at ICAR-NRCB, Trichy, ensuring its accuracy and accessibility for the duration of the study. Further, the raw transcriptome read datasets have been successfully submitted to the National Center for Biotechnology Information - Sequence Read Archive (NCBI-SRA) database, ensuring the accessibility and reproducibility of this valuable dataset for further research endeavors

The limited specificity of standard inflammatory biomarkers poses a challenge for the diagnosis and monitoring of sepsis. The differential gene expression patterns of Vascular Endothelial Growth Factor A and B (VEGF-A and B) are promising candidates. This study aimed to elucidate variations in VEGF-A/B gene expression following SARS-CoV MA15 disease initiation. Biomarker tracking was examined in a murine C57BL wild-type (WT) genotype MA15 (SARS-CoV) nasal instillation model. In [GSE40824], the expression of TNF and VEGF-A significantly differed between the groups (p = 1.53e-07, and 0.0043) and over time. In [GSE40827], [GSE51386], [GSE51387], and [GSE40840], the expression of TNF, VEGF-A, and VEGF-B was significantly different between groups, but not over time. In [GSE50878] and [GSE68220], TNF, NF-κB1, and VEGF-B showed significant differences in expression between the groups. The difference in VEGF-A expression was significant between the groups in [GSE68220] but not in [GSE50878]. However, the change over time from day 2 to day 4 was significant. In [GSE49262], TNF, NF-κB1, and VEGF-A significantly differed between the groups, and the changes in NF-κB1 and VEGF-A over time were significant. In [GSE49263], four genes differed significantly between the groups. In [GSE50000], TNF, NF-κB1, VEGF-A, and VEGF-B showed non-significant upregulation in the group with the higher dose. TNF, NF-κB1, and VEGF-A levels decreased from days 1–4 and increased from days 4–7. VEGF-B decreased from days 1–2 and increased from days 2–4 and from days 4–7. In [GSE33266], NF-κB1, VEGF-A, and VEGF-B levels varied between doses and time points. Our findings suggest that VEGF-A exhibits a more consistent and pronounced response to SARS MA15 infection regarding dose dependency and temporal expression changes.

Alzheimer's disease (AD) is a progressive neuroinflammatory and neurodegenerative disorder that affects different regions of the brain. Its pathophysiology includes the accumulation of β-amyloid protein, formation of neurofibrillary tangles, and inflammatory processes. Genetic factors are involved in the onset of AD, but they are not fully elucidated. Identification of gene expression in encephalic tissues of patients with AD may help elucidate its development. Our objectives were to characterize and compare the gene expression of CDK10, CDK11, FOXO1, and FOXO3 in encephalic tissue samples from AD patients and elderly controls, from the auditory cortex and cerebellum. RT-qPCR was used on samples from 82 individuals (45 with AD and 37 controls). We observed a statistically significant increase in CDK10 (p = 0.029*) and CDK11 (p = 0.048*) gene expression in the AD group compared to the control, which was most evident in the cerebellum. Furthermore, the Spearman test demonstrated the presence of a positive correlation of gene expression both in the auditory cortex in the AD group (r = 0.046/p = 0.004) and control group (r = 0.454/p = 0.005); and in the cerebellum in the AD group (r = 0.654 /p < 0.001). There was no statistically significant difference and correlation in the gene expression of FOXO1 and FOXO3 in the AD group and the control. In conclusion, CDK10 and CDK11 have high expression in AD patients compared to control, and they present a positive correlation of gene expression in the analyzed groups and tissues, which suggests that they play an important role in the pathogenesis of AD. [ABSTRACT FROM AUTHOR]

Ob/ob mice are leptin-deficient animals with uninhibited food intake and susceptibility to gain weight and develop type 2 diabetes. The mice have been used to study obesity and diabetes. We generated a dataset of different tissue gene expressions from wild-type and ob/ob mice with a normal diet (ND) or high-fat diet (HFD). The gene expression was profiled at a genome-scale using RNA-seq. We deposited the raw data to the short read archive and the processed data to the gene expression omnibus. In this manuscript, we describe generating the dataset and technical validation of the gene expression profiles. We assessed the quality of the reads, alignment, and the quantification of gene expression. We found that the tissue of origin explained the most variance between samples. Non-coding features differed in their contribution to the mice profiles. Gene expression profiles diverged between the experimental groups. To sum, this dataset can be used to study tissue-specific gene expression in weight gain susceptible mice and the response to HFD.

Summary: Studies prior to next‐generation sequencing (NGS) showed that the frequent indolent course of chronic lymphocytic leukaemia (CLL) is related to most cells remaining quiescent in the G0–G1 cell cycle phase, due to the expression of dysregulated cyclin genes. Of note, the activating nature of the NOTCH1 mutation in T lymphoblastic leukaemia also drives the dysregulation of cell cycle genes. Our goal was to comprehensively revisit the cell cycle in NOTCH1‐mutated CLL (NOTCH1MUT) to test for potential therapeutic targets. Among 378 NGS‐annotated CLL cases, NOTCH1MUT cells displayed a unique transcriptome profile of G0–G1 cell cycle components, with an overexpression of early‐phase effectors, reaching a 38‐, 27‐ and ninefold change increase for the complex elements CCND3, CDK4 and CDK6, respectively. This NOTCH1MUT cells' profile was related to more cells traversing through the cell cycle. In‐vitro targeted inhibition of NOTCH1 gamma‐secretase and CDK4/6 reversed the distribution of cells through the cycle phases and enhanced the killing of NOTCH1MUT CLL cells, suggesting new therapeutic approaches. [ABSTRACT FROM AUTHOR]

The intertidal sea mussel Mytilus californianus inhabits the Pacific coastline of North America. As a sessile organism it must cope with daily fluctuations of the marine and terrestrial environments. Organisms in stressful environments are commonly faced with energetic trade-offs between somatic and reproductive growth and stress management. Although, this energetic theory is generally accepted for mussels as well, the spectrum of mechanisms underlying this framework have not been widely investigated. In the current study we hypothesized that mussels acclimated to a cyclical moderately warm aerial environment would display enhanced transcript abundance of genes related to metabolism and exhibit resilient digestive enzyme activity (energy acquisition). Following acclimation to simulated tidal regimes in the laboratory we observed higher gene-expression of citrate synthase (CS), citrate lyase (ACLY), and mammalian target of rapamycin (MTOR) in heat stressed mussels. The expression of CS and MTOR was not elevated under acute thermal stress, suggestive that repeated stress is required for robust expression of these genes given that all other environmental variables are constant. We also observed reduced activity of the digestive enzyme, amylase in heat-shocked acclimated mussels (a proxy for energy acquisition). Our results suggest that mussels that settle high on shore not only face the challenge of thermal stress repair and limited access to food but may also be compromised by reduced digestive performance. Mussels may have adapted to cyclical energetic stress by overexpressing particular energy-related genes that can mitigate the disturbance to energy balance once the abundant transcripts are translated into functional proteins.

Members of the myxovirus resistance (Mx) protein family play an essential role in antiviral immunity. They are Dynamin-like GTPases, induced by interferons. In the current study, we have characterized two predicted MX genes (MX 1 and MX 2) from lumpfish (Cyclopterus lumpus L.), having 12 and 13 exons, respectively. Mx2 has two isoforms (Mx2-X1 and Mx2-X2) which differ in exon 1. The lumpfish Mx proteins contain an N-terminal Dynamin-like GTPase domain, the middle domain (MD) and GTPase effector domain (GED) characteristic for Mx proteins. Phylogenetic analyses grouped all the lumpfish Mx sequences in group 1, and synteny analyses showed that both genes were localized at chromosome 5 in proximity to the genes Tohc7, Atxn7 and Psmd6. In vitro stimulation experiment showed that both MX1 and MX2 -X2 were highly upregulated upon exposure to poly(I:C), but not bacteria, 24 h post exposure, indicating their role in antiviral immunity. • Lumpfish have two functional MX genes. MX 1 and MX 2. • Isoforms exhibit distinct exon patterns, suggesting functional specialization. • In vitro stimulation experiment highlights their crucial role in antiviral immunity. • Establishment of qPCR assays provide an important tool to study antiviral responses in lumpfish in future studies. [ABSTRACT FROM AUTHOR]

Introduction: Kawasaki disease (KD) is the most common vasculitis in young children, with coronary artery lesions (CALs) and coronary aneurysms (CAAs) being responsible for most KD-related deaths. Objective: We hypothesized that Vascular Endothelial Growth Factors (VEGFs) are pivotal in KD inflammation and coronary artery lesions. This study assessed VEGF-A and VEGF-B gene expression (GE) as potential biomarkers in KD inflammation. Study design: We analyzed NCBI-GEO datasets, categorizing gene expression patterns as ''inflammatory'' or ''non-inflammatory''. We focused on TNF-, NFKB1, VEGF-A, and VEGF-B GEs. Datasets were filtered based on differential changes in TNF and NFKB1 levels to isolate those with inflammatory shifts. Results: Inflammatory datasets (GSE63881, GSE73464, and GSE68004) displayed elevated TNF, NFKB1, and VEGF-A GE levels during acute KD. VEGF-B GE exhibited a distinctive trend: an initial drop and subsequent rise during recovery, a pattern that was missing in the non-inflammatory group. The treatment response was also studied, with intravenous immunoglobulin (IVIG) responders showing significant downregulation of NFKB1 GE after treatment: GSE16797 [IVIG ± methylprednisolone; p = 8.6443-03], GSE48498 [IVIG; p = 6.618e-02, infliximab; p = 3.240e-03], and GSE18606 [IVIG; p = 3.518e-02]. Considering the similar binding of VEGF-A and VEGF-B to the VEGFR1 receptor, a co-variate and inverse relationship is suggested. Conclusion: Temporal VEGF-A, VEGF-B, and GE changes show promise as new post-inflammatory biomarkers for KD. Novelty results with the biomarker approach, with the potential for a dual temporal relationship between VEGF-A and VEGF-A. A comprehensive exploration of VEGF-A and VEGF-B genes and protein analysis in KD is warranted to understand the functional aspects of these changes and how best to utilize the pattern of changes for therapeutic benefit.

Sporadic amyotrophic lateral sclerosis (sALS) is the most common form of ALS, however, the molecular mechanisms underlying cellular damage and motor neuron degeneration remain elusive. To identify molecular signatures of sALS we performed genome-wide expression profiling in laser capture microdissection-enriched surviving motor neurons (MNs) from lumbar spinal cords of sALS patients with rostral onset and caudal progression. After correcting for immunological background, we discover a highly specific gene expression signature for sALS that is associated with phosphorylated TDP-43 (pTDP-43) pathology. Transcriptome-pathology correlation identified casein kinase 1ε (CSNK1E) mRNA as tightly correlated to levels of pTDP-43 in sALS patients. Enhanced crosslinking and immunoprecipitation in human sALS patient- and healthy control-derived frontal cortex, revealed that TDP-43 binds directly to and regulates the expression of CSNK1E mRNA. Additionally, we were able to show that pTDP-43 itself binds RNA. CK1E, the protein product of CSNK1E, in turn interacts with TDP-43 and promotes cytoplasmic accumulation of pTDP-43 in human stem-cell-derived MNs. Pathological TDP-43 phosphorylation is therefore, reciprocally regulated by CK1E activity and TDP-43 RNA binding. Our framework of transcriptome-pathology correlations identifies candidate genes with relevance to novel mechanisms of neurodegeneration.

Simple Summary: Radiation therapy (RT) is an established therapeutic regimen for prostate cancer patients which aims for the direct elimination of tumor cells in the prostate gland and occasionally at distant anatomic sites. In this study, we performed next-generation sequencing-based gene expression analysis in peripheral blood from prostate cancer patients obtained pre- and post-radiotherapy and found six independently down-regulated genes including CCR7, FCGR2B, BTLA, CD6, CD3D, and CD3E. The analysis of the expression of the 6-genes as a signature also revealed significantly lower levels post- vs. pre-radiotherapy. Data extracted from the PRAD (PRostate ADenocarcinomas) dataset linked low levels of the 6-gene signature to better survival. More importantly, this 6-gene signature strongly correlated with a favorable prognosis regardless of poor standard clinicopathological parameters (i.e., Gleason score ≥ 8 and T3), thus highlighting its potential predictive value. Radiotherapy for localized prostate cancer has increased the cure and survival rates of patients. Besides its local tumoricidal effects, ionizing radiation has been linked to mechanisms leading to systemic immune activation, a phenomenon called the abscopal effect. In this study, we performed gene expression analysis on peripheral blood from prostate cancer patients obtained post- radiotherapy and showed that 6 genes, including CCR7, FCGR2B, BTLA, CD6, CD3D, and CD3E, were down-regulated by a range of 1.5–2.5-fold as compared to pre-radiotherapy samples. The expression of the signature consisting of these six genes was also significantly lower post- vs. pre-radiotherapy. These genes are involved in various tumor-promoting immune pathways and their down-regulation post-radiotherapy could be considered beneficial for patients. This is supported by the fact that low mRNA expression levels for the 6-gene signature in the prostate tumor tissue was linked to better survival. Importantly, we report that this 6-gene signature strongly correlated with a favorable prognosis regardless of poor standard clinicopathological parameters (i.e., Gleason score ≥ 8 and T3 (including T3a and T3b). Our pioneering data open the possibility that the 6-gene signature identified herein may have a predictive value, but this requires further long-term studies. [ABSTRACT FROM AUTHOR]

Epidermal growth factor receptor (EGFR) pathway has been shown to play a crucial role in several inflammatory conditions and host immune-inflammation status is related to tumor prognosis. This study aims to evaluate the prognostic significance of a four-gene inflammatory signature in recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) patients treated with the EGFR inhibitor cetuximab plus chemotherapy. The inflammatory signature was assessed on 123 R/M HNSCC patients, enrolled in the multicenter trial B490 receiving first-line cetuximab plus platinum-based chemotherapy. The primary endpoint of the study was progression free survival (PFS), while secondary endpoints were overall survival (OS) and objective response rate (ORR). The patient population was subdivided into 3 groups according to the signature score groups. The four-genes-signature proved a significant prognostic value, resulting in a median PFS of 9.2 months in patients with high vs. 6.2 months for intermediate vs. 3.9 months for low values (p = 0.0016). The same findings were confirmed for OS, with median time of 18.4, 13.4, and 7.5 months for high, intermediate, and low values of the score, respectively (p = 0.0001). When ORR was considered, the signature was significantly higher in responders than in non-responders (p = 0.0092), reaching an area under the curve (AUC) of 0.65 (95% CI: 0.55–0.75). Our findings highlight the role of inflammation in the response to cetuximab and chemotherapy in R/M-HNSCC and may have translational implications for improving treatment selection. [ABSTRACT FROM AUTHOR]

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the transcription factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the transcription factor ChIP experiment and the signed statistics from gene expression profiling with transcription factor perturbation. We further extend BETA to integrate two sets of data from two transcription factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two transcription factors, which were found to be, on average, more cooperatively regulated.

Thriving freshwater fish populations contribute to people's economic prosperity and wellbeing. Yet, freshwater fish populations are in critical condition around the globe. Most stressors to freshwater fishes, fisheries, and culture stem from habitat impacts, water-quality issues, and aquatic invasive species. Logistical difficulties of monitoring fish health are compounded by the limitations of conventional (capture-based) sampling methods, which provide only a temporal "snapshot" and generate data lacking in sensitivity and prognostic ability. Here, we propose an innovative genomics approach to develop a health toolkit that will allow resource-sector users to determine the health status of freshwater fishes, including their coping capacity, to environmental stressors. The stress-response transcription profile (STP)-chip is a suite of quantitative gene transcription assays that represents key gene pathways broadly associated with fish functional responses to environmental stress; therefore, the differential expression of well-selected genes can provide sensitive fish-health status indicators. Despite the scientific achievement of using genomics tools, actualizing the toolkit in practice is only successful if resource-sector users have full buy-in. We present seven case studies representing different practitioners and resource users – Indigenous rightsholders, environmental consultants (industry), commercial aquaculture, environmental charities (ENGO), and fishery commissions and managers (government) where each explores the benefits and risks associated with the adoption of a genomics fish-health toolkit. Using a co-production approach, wherein practitioners and resource users are engaged from the outset, these case studies reveal translational pathways that would be needed to overcome barriers to technological adoption and, hence, accelerate the responsible uptake of genomics-based applications in fisheries assessment, management, and conservation. [ABSTRACT FROM AUTHOR]

The cell adhesion molecule 2 (CADM2) gene has appeared among the top associations in a wide range of genome-wide association studies (GWASs). This study aims to: (1) examine how widespread the role of CADM2 is in behavioural traits, and (2) investigate trait-specific effects on CADM2 expression levels across tissues. We conducted a phenome-wide association study in UK Biobank (N = 12,211–453,349) on 242 psycho-behavioral traits, both at the SNP and the gene-level. For comparison, we repeated the analyses for other large (and high LD) genes. We found significant associations between CADM2 and 50 traits (including cognitive, risk taking, and dietary traits), many more than for the comparison genes. We show that many trait associations are reduced when taking geographical stratification into account. S-Predixcan revealed that CADM2 expression in brain tissues was significantly associated with many traits; highly significant effects were also observed for lung, mammary, and adipose tissues. In conclusion, this study shows that the role of CADM2 extends to a wide range of psycho-behavioral traits, suggesting these traits may share a common biological denominator. [ABSTRACT FROM AUTHOR]

To ensure welfare-friendly and effective internal tagging, the tagging process should not cause a long-term burden on individuals given that tagged fish serve as representatives for the entire population in telemetry applications. To some extent, stress is inevitable within regular aquaculture practices, and thus, the consequences of long-term stress should be described in terms of their effects on internal tagging. In fish, stressors activate the Hypothalamus-Pituitary-Interrenal (HPI) and Brain-Sympathetic-Chromaffin Cell (BSC) axes, leading to neuroimmunoendocrine communication and paracrine interactions among stress hormones. The interrelation between wound healing and stress is complex, owing to their shared components, pathways, and energy demands. This study assessed 14 genes (mmp9 , mmp13 , il-2 , il-4 , il-8a , il-10 , il-12 , il-17d , il-1b , tnfa , ifng , leg-3 , igm , and crh) in the skin (1.5 cm from the wound) and head kidney over eight weeks. These genes, associated with cell signaling in immunity, wound healing, and stress, have previously been identified as influenced and regulated by these processes. Half of a group of Atlantic salmon (n = 90) with surgically implanted dummy smart-tags were exposed to daily crowding stress. The goal was to investigate how this gene panel responds to a wound alone and then to the combined effects of wounding and daily crowding stress. Our observations indicate that chronic stress impacts inflammation and impedes wound healing, as seen through the expression of matrix metalloproteinases genes in the skin but not in the head kidney. This difference is likely due to the ongoing internal wound repair, in contrast to the externally healed wound incision. Cytokine expression, when significant in the skin, was mainly downregulated in both treatments compared to control values, particularly in the study's first half. Conversely, the head kidney showed initial cytokine downregulation followed by upregulation. Across all weeks observed and combining both tissues, the significantly expressed gene differences were 12 % between the Wound and Stress+ groups, 28 % between Wound and Control, and 25 % between Stress+ and Control. Despite significant fluctuations in cytokines, sustained variations across multiple weeks are only evident in a few select genes. Furthermore, Stress+ individuals demonstrated the most cytokine correlations within the head kidney, which may suggest that chronic stress affects cytokine expression. This investigation unveils that the presence of stress and prolonged activation of the HPI axis in an eight weeklong study has limited yet detectable effects on the selected gene expression within immunity, wound healing, and stress, with notable tissue-specific differences. • Daily stress delays wound healing by upregulating the expression of mmp9 and mmp13 in the skin. • Internal wound healing upregulates mmp9 and mmp13 expression in the head kidney. • Cytokines are downregulated 7 days post-surgery and later upregulated, mainly in treatment groups and in the head kidney. • i l-2 and il-8a correlate with many cytokines amid the treatment groups, indicating their importance within wound healing. • Chronic stress subtly yet significantly alters the expression of specific genes, impacting immune function. [ABSTRACT FROM AUTHOR]

This paper presents an approach based on emerging pattern mining to analyse cancer through genomic data. Unlike existing approaches, mainly focused on predictive purposes, the proposal aims to improve the understanding of cancer descriptively, not requiring either any prior knowledge or hypothesis to be validated. Additionally, it enables to consider high‐order relationships, so not only essential genes related to the disease are considered, but also the combined effect of various secondary genes that can influence different pathways directly or indirectly related to the disease. The prime hypothesis is that splitting genomic cancer data into two subsets, that is, cases and controls, will allow us to determine which genes, and their expressions, are associated with different cancer types. The possibilities of the proposal are demonstrated by analyzing RNA‐Seq data for six different types of cancer: breast, colon, lung, thyroid, prostate, and kidney. Some of the extracted insights were already described in the related literature as good cancer bio‐markers, while others have not been described yet mainly due to existing techniques are biased by prior knowledge provided by biological databases. [ABSTRACT FROM AUTHOR]

The hepatic cytochrome p450’s (CYP) are of major importance for the metabolism of xenobiotics and knowledge about their regulation is crucial. This knowledge often originates from cell models; primary human hepatocytes (PHH) being the gold standard. However, due to limited availability of high-quality human donor organs, basic knowledge on alternative models are needed. Primary porcine hepatocytes (PPH) have been suggested as an alternative to PHH. Unfortunately, data comparing the response in gene-transcription to standard CYP inducers between PHH and PPH are missing. In the present study we, cultured PHH and PPH under the same conditions, treated them with standard inducers of the CYP1-3 and determined the response in gene and protein expression. The results demonstrated that in both species TCDD and omeprazole caused an increase in CYP1A/B expression. In PPH, CITCO increased the content of CYP1A/B. For the CYP2B/C/D’s, phenobarbital and rifampicin caused increases in expression. For the CYP2D’s, TCDD and omeprazole caused increased gene expression in PPH, which were not the case for PHH. Both phenobarbital, rifampicin and omeprazole increased CYP3A expression in PHH and PPH. Moreover, TCDD increased the gene expression of CYP3A in PPH; this was not the case for PHH. Multivariate data analysis found no difference in gene expression between PHH and PPH for phenobarbital, rifampicin and CITCO. However, differential clustering was observed for TCDD and omeprazole. In conclusion, despite model specificity, there are a high number of similar responses, and experiments investigating mRNA regulation made in PPH permits for a reliable translation into human setting.

Ob/ob mice are leptin-deficient animals with uninhibited food intake and susceptibility to gain weight and develop type 2 diabetes. The mice have been used to study obesity and diabetes. We generated a dataset of different tissue gene expressions from wild-type and ob/ob mice with a normal diet (ND) or high-fat diet (HFD). The gene expression was profiled at a genome-scale using RNA-seq. We deposited the raw data to the short read archive and the processed data to the gene expression omnibus. In this manuscript, we describe generating the dataset and technical validation of the gene expression profiles. We assessed the quality of the reads, alignment, and the quantification of gene expression. We found that the tissue of origin explained the most variance between samples. Noncoding features differed in their contribution to the mice profiles. Gene expression profiles diverged between the experimental groups. To sum, this dataset can be used to study tissue-specific gene expression in weight gain susceptible mice and the response to HFD. [ABSTRACT FROM AUTHOR]

The 3T3-L1 cell line is used as an adipocyte differentiation model for the analysis of genes specifically expressed during the differentiation course. This cell model has several applications in obesity and insulin resistance research. We built a data resource to model gene expression of differentiating and mature adipocytes in response to several drugs and gene manipulations. We surveyed the literature survey for microarray datasets of differentiating 3T3-L1 cell line sampled at one or more time points under genetic or pharmacological perturbations. Data and metadata were obtained from the gene expression omnibus. The metadata were manually curated using unified language across the studies. Probe intensities were mapped and collapsed to genes using a reproducible pipeline. Samples were classified into none, genetically or pharmacologically modified. In addition to the clean datasets, two aggregated sets were further homogenized for illustration purposes. The curated datasets are available as an R/Bioconductor experimental data package curatedAdipoArray. The package documents the source code of the data collection, curation and processing. Finally, we used a subset of the data to effectively remove batch effects and reproduce biological observations. Database URL https://bioconductor.org/packages/curatedAdipoArray

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the transcription factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the transcription factor ChIP experiment and the signed statistics from gene expression profiling with transcription factor perturbation. We further extend BETA to integrate two sets of data from two transcription factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two transcription factors, which were found to be, on average, more cooperatively regulated.

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the factor ChIP experiment and the signed statistics from gene expression profiling with factor perturbation. We further extend BETA to integrate two sets of data from two factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two factors, which were found to be, on average, more cooperatively regulated.

Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers -as caused by the additional burden of artificial genetic circuits- shifts a cell's priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state (NESS) model of gene expression, capturing characteristics like energy dissipation -which we link to the entropy production rate- and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit's functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37 . 2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energy efficiency of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo ., Competing Interests: Competing Interests The authors declare no competing interests.

Microarray analysis in glioblastomas is done using either cell lines or patient samples as starting material. A survey of the current literature points to transcript-based microarrays and immunohistochemistry (IHC)-based tissue microarrays as being the preferred methods of choice in cancers of neurological origin. Microarray analysis may be carried out for various purposes including the following: i. To correlate gene expression signatures of glioblastoma cell lines or tumors with response to chemotherapy (DeLay et al., Clin Cancer Res 18(10):2930-2942, 2012). ii. To correlate gene expression patterns with biological features like proliferation or invasiveness of the glioblastoma cells (Jiang et al., PLoS One 8(6):e66008, 2013). iii. To discover new tumor classificatory systems based on gene expression signature, and to correlate therapeutic response and prognosis with these signatures (Huse et al., Annu Rev Med 64(1):59-70, 2013; Verhaak et al., Cancer Cell 17(1):98-110, 2010). While investigators can sometimes use archived tumor gene expression data available from repositories such as the NCBI Gene Expression Omnibus to answer their questions, new arrays must often be run to adequately answer specific questions. Here, we provide a detailed description of microarray methodologies, how to select the appropriate methodology for a given question, and analytical strategies that can be used. Experimental methodology for protein microarrays is outside the scope of this chapter, but basic sample preparation techniques for transcript-based microarrays are included here.

Epidermal growth factor receptor (EGFR) pathway has been shown to play a crucial role in several inflammatory conditions and host immune-inflammation status is related to tumor prognosis. This study aims to evaluate the prognostic significance of a four-gene inflammatory signature in recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) patients treated with the EGFR inhibitor cetuximab plus chemotherapy. The inflammatory signature was assessed on 123 R/M HNSCC patients, enrolled in the multicenter trial B490 receiving first-line cetuximab plus platinum-based chemotherapy. The primary endpoint of the study was progression free survival (PFS), while secondary endpoints were overall survival (OS) and objective response rate (ORR). The patient population was subdivided into 3 groups according to the signature score groups. The four-genes-signature proved a significant prognostic value, resulting in a median PFS of 9.2 months in patients with high vs. 6.2 months for intermediate vs. 3.9 months for low values (p = 0.0016). The same findings were confirmed for OS, with median time of 18.4, 13.4, and 7.5 months for high, intermediate, and low values of the score, respectively (p = 0.0001). When ORR was considered, the signature was significantly higher in responders than in non-responders (p = 0.0092), reaching an area under the curve (AUC) of 0.65 (95% CI: 0.55–0.75). Our findings highlight the role of inflammation in the response to cetuximab and chemotherapy in R/M-HNSCC and may have translational implications for improving treatment selection.

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the factor ChIP experiment and the signed statistics from gene expression profiling with factor perturbation. We further extend BETA to integrate two sets of data from two factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two factors, which were found to be, on average, more cooperatively regulated.

Neurodegenerative diseases, including Alzheimer’s disease, are prevalent in diabetic patients. DA-9801 is a standardized extract of Dioscorea japonica Thunb. and Dioscorea nipponica Makino, which has been shown to reduce blood glucose levels and exert protective effects against diabetic peripheral neuropathy. Here, we aimed to investigate whether DA-9801 could protect hyperglycemia-induced central neuropathy and to elucidate the underlying mechanisms. DA-9801 protected rat cortical primary neurons against hyperglycemia-induced neurotoxicity by lowering the levels of reactive oxygen species. In addition, we identified the genes whose expression in high glucose-treated primary neurons was significantly altered by DA-9801 treatment. Moreover, the major saponins of DA-9801, dioscin and protodioscin, protected neurons from hyperglycemia-induced toxicity, suggesting that these may be the most important active neuroprotective components of DA-9801. Our results showed that DA-9801 protects neurons derived from the central nervous system and that it may be useful to treat and delay the development of neurodegenerative diseases in diabetic patients.

The 3T3-L1 pre-adipocyte cell line is widely used to study the fat cell differentiation in vitro. Researchers also use this cell model to study obesity and insulin resistance. We surveyed the literature, the gene expression omnibus and the sequence read archive for RNA-Seq and ChIP-Seq datasets of MDI-induced 3T3-L1 differentiating cells sampled at one or more time points. The metadata of the relevant datasets were manually curated using unified language across the original studies. The raw reads were collected and pre-processed using a reproducible state-of-the-art pipeline. The final datasets are presented as reads count in genes for the RNA-Seq and reads count in peaks for the ChIP-Seq dataset. The curated datasets are available as two Bioconductor experimental data packages curatedAdipoRNA and curatedAdipoChIP. In addition, the packages document the source code of the data collection and the pre-processing pipelines. Here, we provide a descriptive analysis of the datasets with context and technical validation.

Background The post-mortem interval (PMI) is the time elapsed since the dead of an individual until the body is found, which is relevant for forensic purposes. The miRNAs regulate the expression of some genes; and due to their small size, they can better support degradation, which makes them suitable for forensic analysis. In the present work, we evaluated the gene expression of miR-381-3p, miR-23b-3p, and miR-144-3p in skeletal muscle in a murine model at the early PMI. Methods We designed a rat model to evaluate the early PMI under controlled conditions. This model consisted in 25 rats divided into five groups of rats, that correspond to the 0, 3, 6, 12 and 24 hours of PMI. The 0 h-PMI was considered as the control group. Muscle samples were taken from each rat to analyze the expression of miR-381-3p, miR-23b-3p, and miR-144-3p by quantitative RT-PCR. The gene expression of each miRNA was expressed as Fold Change (FC) and compared among groups. To find the targets of these miRNAs and the pathways where they participate, we performed an in-silico analysis. From the gene targets of miR-381-3p identified in the silico analysis, the EPC1 gene was selected for gene expression analysis by quantitative RT-PCR in these samples. Also, to evaluate if miR-381-3p could predict the early PMI, a mixed effects model was calculated using its gene expression. Results An upregulation of miR-381-3p was found at 24 h-PMI compared with the control group of 0 h-PMI and (FC = 1.02 vs. FC = 1.96; p = 0.0079). This was the opposite for miR-23b-3p, which had a down-regulation at 24 h-PMI compared to 0 h-PMI (FC = 1.22 vs. FC = 0.13; p = 0.0079). Moreover, the gene expression of miR-381-3p increased throughout the first 24 h of PMI, contrary to miR-23b-3p. The targets of these two miRNAs, participate in biological pathways related to hypoxia, apoptosis, and RNA metabolism. The gene expression of EPC1 was found downregulated at 3 and 12 h of PMI, whereas it remained unchanged at 6 h and 24 h of PMI. Using a multivariate analysis, it was possible to predict the FC of miR-381-3p of all but 6 h-PMI analyzed PMIs. Discussion The present results suggest that miR-23b-3p and miR-381-3p participate at the early PMI, probably regulating the expression of some genes related to the autolysis process as EPC1 gene. Although the miR-381-3p gene expression is a potential estimator of PMI, further studies will be required to obtain better estimates.

Background. The post-mortem interval (PMI) is the time elapsed since the dead of an individual until the body is found, which is relevant for forensic purposes. The miRNAs regulate the expression of some genes; and due to their small size, they can better support degradation, which makes them suitable for forensic analysis. In the present work, we evaluated the gene expression of miR-381-3p, miR-23b-3p, and miR-144-3p in skeletal muscle in a murine model at the early PMI. Methods. We designed a rat model to evaluate the early PMI under controlled conditions. This model consisted in 25 rats divided into five groups of rats, that correspond to the 0, 3, 6, 12 and 24 hours of PMI. The 0 h-PMI was considered as the control group. Muscle samples were taken from each rat to analyze the expression of miR-381-3p, miR-23b-3p, and miR-144-3p by quantitative RT-PCR. The gene expression of each miRNA was expressed as Fold Change (FC) and compared among groups. To find the targets of these miRNAs and the pathways where they participate, we performed an in-silico analysis. From the gene targets of miR-381-3p identified in the silico analysis, the EPC1 gene was selected for gene expression analysis by quantitative RT-PCR in these samples. Also, to evaluate if miR-381-3p could predict the early PMI, a mixed effects model was calculated using its gene expression. Results. An upregulation of miR-381-3p was found at 24 h-PMI compared with the control group of 0 h-PMI and (FC = 1.02 vs. FC = 1.96; p D 0:0079). This was the opposite for miR-23b-3p, which had a down-regulation at 24 h-PMI compared to 0 h-PMI (FC D 1.22 vs. FC D 0.13; pD0:0079). Moreover, the gene expression of miR-381-3p increased throughout the first 24 h of PMI, contrary to miR-23b-3p. The targets of these two miRNAs, participate in biological pathways related to hypoxia, apoptosis, and RNA metabolism. The gene expression of EPC1 was found downregulated at 3 and 12 h of PMI, whereas it remained unchanged at 6 h and 24 h of PMI. Using a multivariate analysis, it was possible to predict the FC of miR-381-3p of all but 6 h-PMI analyzed PMIs. Discussion. The present results suggest that miR-23b-3p and miR-381-3p participate at the early PMI, probably regulating the expression of some genes related to the autolysis process as EPC1 gene. Although the miR-381-3p gene expression is a potential estimator of PMI, further studies will be required to obtain better estimates. [ABSTRACT FROM AUTHOR]