Gene co-expression networks reveal sex-biased differences in musculoskeletal ageing.

Aging is a universal and progressive process involving the deterioration of physiological functions and the accumulation of cellular damage. Gene regulation programs influence how phenotypes respond to environmental and intrinsic changes during aging. Although several factors, including sex, are known to impact this process, the underlying mechanisms remain incompletely understood. Here, we investigate the functional organization patterns of skeletal muscle genes across different sexes and ages using gene co-expression networks (GCNs) to explore their influence on aging. We constructed GCNs for three different age groups for male and female samples, analyzed topological similarities and differences, inferred significant associated processes for each network, and constructed null models to provide statistically robust results. We found that each network is topologically and functionally distinct, with young women having the most associated processes, likely due to reproductive tasks. The functional organization and modularity of genes decline with age, starting from middle age, potentially leading to age-related deterioration. Women maintain better gene functional organization throughout life compared to men, especially in processes like macroautophagy and sarcomere organization. The study suggests that the loss of gene co-expression could be a universal aging marker. This research offers insights into how gene organization changes with age and sex, providing a complementary method to analyze aging.

Gene ontology functional annotation datasets for the ITAG3.2 and ITAG4.0 tomato (Solanum lycopersicum) genome annotations.

Functional annotation based on Gene Ontology has provided a structured and comprehensive system to access the current knowledge about the function of genes. For model plants such as Arabidopsis thaliana, there is a constant updating and restructuring of the functional annotation that increases the reliability of the analyses that use it. For tomato (Solanum lycopersicum), a crop widely used as a model plant for the study of fleshy fruits, there is no functional annotation, at least not freely accessible, even though its genome has long been sequenced and annotated. In this work, we generated, using a simplified version of the maize GAMER pipeline, a tomato Gene Ontology functional annotation with 72.42% (ITAG3.2) and 74.2% (ITAG4.0) of protein-coding genes with at least one GO term association. With this dataset, we share a reliable and easy-to-use tool with the tomato community.

A System Biology Approach Reveals New Targets for Human Thyroid Gland Toxicity in Embryos and Adult Individuals.

Compounds of natural or synthetic origin present in personal care products, food additives, and packaging may interfere with hormonal regulation and are called endocrine-disrupting chemicals (EDCs). The thyroid gland is an important target of these compounds. The objective of this study was to analyze public data on the human thyroid transcriptome and investigate potential new targets of EDCs in the embryonic and adult thyroid glands. We compared the public transcriptome data of adult and embryonic human thyroid glands and selected 100 up- or downregulated genes that were subsequently subjected to functional enrichment analysis. In the embryonic thyroid, the most highly expressed gene was PRMT6, which methylates arginine-4 of histone H2A (86.21%), and the downregulated clusters included plasma lipoprotein particles (39.24%) and endopeptidase inhibitory activity (24.05%). For the adult thyroid gland, the most highly expressed genes were related to the following categories: metallothionein-binding metals (56.67%), steroid hormone biosynthetic process (16.67%), and cellular response to vascular endothelial growth factor stimulus (6.67%). Several compounds ranging from antihypertensive drugs to enzyme inhibitors were identified as potentially harmful to thyroid gland development and adult function.

Expression and Clinical Significance of CLCA2 in Pan-Cancer / Expresión y Significado Clínico de CLCA2 en Pan-Cáncer

SUMMARY: The calcium-activated chloride channel (CLCA2) performs a vital function in the intricate process of tumorigenesis. Using a bioinformatics analysis system, we conducted a pan-cancer investigation on CLCA2 to explore its association with tumor prognosis and its involvement in immunology. In order to achieve this objective, we examined the prognostic significance and expression level of CLCA2 in multiple cancer types using the TIMER and Sangerbox databases. The analysis of protein interaction networks revealed proteins linked to CLCA2. To investigate the potential biological functions and enrichment pathways of CLCA2 in cancer, the SangerBox and GSCA databases were utilized. Furthermore, the expression of CLCA2 in different cancer subtypes was evaluated during the analysis. Various functional conditions of cancer cells were then compared with CLCA2 in the CancerSEA database. Using online tools like TISIDB and Assistant for Clinical Bioinformatics, the investigation explored the link between CLCA2 and immune subtypes. Additionally, it assessed immune cell infiltration as part of the analysis. In addition, the application of GDSA was employed to investigate the predictive significance of CLCA2 in relation to drug sensitivity. The research outcomes uncovered abnormal expression patterns of CLCA2 in diverse tumor categories, with its expression level demonstrating a correlation with distinct subtypes of tumors. Strong associations have been observed between enhanced patient survival rates and CLCA2 in specific tumor types. There is a noteworthy connection observed among diverse tumor types, immune cell infiltration, immune subtypes, and CLCA2. The enrichment analysis of KEGG indicates that there may exist a connection between the expression of CLCA2 and renin secretion, pancreatic secretion, as well as other pathways in pan-cancer. CLCA2 appears to primarily activate pathways such as EMT (epithelial-mesenchymal transition), RAS/MAPK, RTK, apoptosis, TSC/mTOR, and PI3K/ AKT in pan-cancer. On the other hand, it seems to inhibit pathways like cell cycle, DNA damage, hormone AR, and hormone ER. Through single-cell functional analysis, it has been confirmed that CLCA2 is associated with diverse cellular functional states, encompassing DNA repair, EMT, hypoxia, invasion, metastasis, and quiescence. Furthermore, a substantial correlation has been observed between the expression of CLCA2 and drug sensitivity towards bosutinib, tipifarnib-P1, as well as other therapeutic agents. This research affirms that various cancer types express CLCA2 and its involvement in tumor advancement and immune penetration. CLCA2 possesses the capability to function as a noteworthy biomarker and target for therapeutic intervention in diverse cancer forms.

El canal de cloruro activado por calcio (CLCA2) desempeña una función vital en el proceso de tumorigénesis. Utilizando un sistema de análisis bioinformático, llevamos a cabo una investigación pan-cáncer en CLCA2 para explorar su asociación con el pronóstico tumoral y su participación en la inmunología. Para lograr este objetivo, examinamos la importancia pronóstica y el nivel de expresión de CLCA2 en múltiples tipos de cáncer utilizando las bases de datos TIMER y Sangerbox. El análisis de las redes de interacción de proteínas reveló proteínas vinculadas a CLCA2. Para investigar las posibles funciones biológicas y las vías de enriquecimiento de CLCA2 en el cáncer, se utilizaron las bases de datos SangerBox y GSCA. Además, durante el análisis se evaluó la expresión de CLCA2 en diferentes subtipos de cáncer. Luego se compararon varias condiciones funcionales de las células cancerosas con CLCA2 en la base de datos CancerSEA. Utilizando herramientas en línea como TISIDB y Assistant for Clinical Bioinformatics, la investigación exploró el vínculo entre CLCA2 y los subtipos inmunes. Además, evaluó la infiltración de células inmunitarias como parte del análisis y se empleó la aplicación de GDSA para investigar la importancia predictiva de CLCA2 en relación con la sensibilidad al fármaco. Los resultados de la investigación descubrieron patrones de expresión anormales de CLCA2 en diversas categorías de tumores, y su nivel de expresión demuestra una correlación con distintos subtipos de tumores. Se han observado fuertes asociaciones entre mayores tasas de supervivencia de los pacientes y CLCA2 en tipos de tumores específicos. Se observa una conexión notable entre diversos tipos de tumores, infiltración de células inmunitarias, subtipos inmunitarios y CLCA2. El análisis de enriquecimiento de KEGG indica que puede existir una conexión entre la expresión de CLCA2 y la secreción de renina, la secreción pancreática y otras vías en el pancáncer. CLCA2 parece activar principalmente vías como EMT (transición epitelial-mesenquimatosa), RAS/MAPK, RTK, apoptosis, TSC/mTOR y PI3K/AKT en pan-cáncer. Por otro lado, parece inhibir vías como el ciclo celular, el daño del ADN, la hormona AR y la hormona ER. Mediante análisis funcional unicelular, se ha confirmado que CLCA2 está asociado con diversos estados funcionales celulares, que abarcan la reparación del ADN, la EMT, la hipoxia, la invasión, la metástasis y la inactividad. Además, se ha observado una correlación sustancial entre la expresión de CLCA2 y la sensibilidad al fármaco hacia bosutinib, tipifarnib-P1, así como a otros agentes terapéuticos. Esta investigación indica que varios tipos de cáncer expresan CLCA2 y su participación en el avance tumoral y la penetración inmune. CLCA2 posee la capacidad de funcionar como un biomarcador notable y como un objetivo para la intervención terapéutica en diversas formas de cáncer.

Phylogenetically diverse wild plant species use common biochemical strategies to thrive in the Atacama Desert.

The best ideotypes are under mounting pressure due to increased aridity. Understanding the conserved molecular mechanisms that evolve in wild plants adapted to harsh environments is crucial in developing new strategies for agriculture. Yet our knowledge of such mechanisms in wild species is scant. We performed metabolic pathway reconstruction using transcriptome information from 32 Atacama and phylogenetically related species that do not live in Atacama (sister species). We analyzed reaction enrichment to understand the commonalities and differences of Atacama plants. To gain insights into the mechanisms that ensure survival, we compared expressed gene isoform numbers and gene expression patterns between the annotated biochemical reactions from 32 Atacama and sister species. We found biochemical convergences characterized by reactions enriched in at least 50% of the Atacama species, pointing to potential advantages against drought and nitrogen starvation, for instance. These findings suggest that the adaptation in the Atacama Desert may result in part from shared genetic legacies governing the expression of key metabolic pathways to face harsh conditions. Enriched reactions corresponded to ubiquitous compounds common to extreme and agronomic species and were congruent with our previous metabolomic analyses. Convergent adaptive traits offer promising candidates for improving abiotic stress resilience in crop species.

Proteomic-Based Studies on Memory Formation in Normal and Neurodegenerative Disease-Affected Brains.

A critical aspect of cognition is the ability to acquire, consolidate, and evoke memories, which is considerably impaired by neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. These mnemonic processes are dependent on signaling cascades, which involve protein expression and degradation. Recent mass spectrometry (MS)-based proteomics has opened a range of possibilities for the study of memory formation and impairment, making it possible to research protein systems not studied before. However, in the context of synaptic proteome related to learning processes and memory formation, a deeper understanding of the synaptic proteome temporal dynamics after induction of synaptic plasticity and the molecular changes underlying the cognitive deficits seen in neurodegenerative diseases is needed. This review analyzes the applications of proteomics for understanding memory processes in both normal and neurodegenerative conditions. Moreover, the most critical experimental studies have been summarized using the PANTHER overrepresentation test. Finally, limitations associated with investigations of memory studies in physiological and neurodegenerative disorders have also been discussed.

A Systematic Review of Gene Expression Studies in Critically Ill Patients with Sepsis and Community-Acquired Pneumonia.

(1) Background: Sepsis is present in nearly 90% of critically ill patients with community-acquired pneumonia (CAP). This systematic review updates the information on studies that have assessed gene expression profiles in critically ill septic patients with CAP. (2) Methods: We searched for studies that satisfied the following criteria: (a) expression profile in critically ill patients with sepsis due to CAP, (b) presence of a control group, and (c) adult patients. Over-representation analysis was performed with clusterProfiler using the Hallmark and Reactome collections. (3) Results: A total of 4312 differentially expressed genes (DEGs) and sRNAs were included in the enrichment analysis. In the Hallmark collection, genes regulated by nuclear factor kappa B in response to tumor necrosis factor, genes upregulated by signal transducer and activator of transcription 5 in response to interleukin 2 stimulation, genes upregulated in response to interferon-gamma, genes defining the inflammatory response, a subgroup of genes regulated by MYC-version 1 (v1), and genes upregulated during transplant rejection were significantly enriched in critically ill septic patients with CAP. Moreover, 88 pathways were identified in the Reactome database. (4) Conclusions: This study summarizes the reported DEGs in critically ill septic patients with CAP and investigates their functional implications. The results highlight the complexity of immune responses during CAP.

Network Toxicology and Molecular Docking to Investigate the Non-AChE Mechanisms of Organophosphate-Induced Neurodevelopmental Toxicity.

Organophosphate pesticides (OPs) are toxic substances that contaminate aquatic environments, interfere with the development of the nervous system, and induce Neurodevelopmental Toxicity (NDT) in animals and humans. The canonical mechanism of OP neurotoxicity involves the inhibition of acetylcholinesterase (AChE), but other mechanisms non-AChE are also involved and not fully understood. We used network toxicology and molecular docking to identify molecular targets and toxicity mechanisms common to OPs. Targets related to diazinon-oxon, chlorpyrifos oxon, and paraoxon OPs were predicted using the Swiss Target Prediction and PharmMapper databases. Targets related to NDT were compiled from GeneCards and OMIM databases. In order to construct the protein-protein interaction (PPI) network, the common targets between OPs and NDT were imported into the STRING. Network topological analyses identified EGFR, MET, HSP90AA1, and SRC as hub nodes common to the three OPs. Using the Reactome pathway and gene ontology, we found that signal transduction, axon guidance, cellular responses to stress, and glutamatergic signaling activation play key roles in OP-induced NDT.

The let-7b-5p, miR-326, and miR-125a-3p are associated with left ventricular systolic dysfunction in post-myocardial infarction.

Background: Acute ST-elevation myocardial infarction (STEMI) can lead to adverse cardiac remodeling, resulting in left ventricular systolic dysfunction (LVSd) and heart failure. Epigenetic regulators, such as microRNAs, may be involved in the physiopathology of LVSd. Objective: This study explored microRNAs in peripheral blood mononuclear cells (PBMC) of post-myocardial infarction patients with LVSd. Methods: Post-STEMI patients were grouped as having (LVSd, n = 9) or not LVSd (non-LVSd, n = 16). The expression of 61 microRNAs was analyzed in PBMC by RT-qPCR and the differentially expressed microRNAs were identified. Principal Component Analysis stratified the microRNAs based on the development of dysfunction. Predictive variables of LVSd were investigated through logistic regression analysis. A system biology approach was used to explore the regulatory molecular network of the disease and an enrichment analysis was performed. Results: The let-7b-5p (AUC: 0.807; 95% CI: 0.63-0.98; p = 0.013), miR-125a-3p (AUC: 0.800; 95% CI: 0.61-0.99; p = 0.036) and miR-326 (AUC: 0.783; 95% CI: 0.54-1.00; p = 0.028) were upregulated in LVSd (p < 0.05) and discriminated LVSd from non-LVSd. Multivariate logistic regression analysis showed let-7b-5p (OR: 16.00; 95% CI: 1.54-166.05; p = 0.020) and miR-326 (OR: 28.00; 95% CI: 2.42-323.70; p = 0.008) as predictors of LVSd. The enrichment analysis revealed association of the targets of these three microRNAs with immunological response, cell-cell adhesion, and cardiac changes. Conclusion: LVSd alters the expression of let-7b-5p, miR-326, and miR-125a-3p in PBMC from post-STEMI, indicating their potential involvement in the cardiac dysfunction physiopathology and highlighting these miRNAs as possible LVSd biomarkers.

Shared Molecular Signatures Across Zika Virus Infection and Multiple Sclerosis Highlight AP-1 Transcription Factor as a Potential Player in Post-ZIKV MS-Like Phenotypes.

Zika virus (ZIKV) is an arbovirus of the Flaviviridae genus that has rapidly disseminated from across the Pacific to the Americas. Robust evidence has indicated a crucial role of ZIKV in congenital virus syndrome, including neonatal microcephaly. Moreover, emerging evidence suggests an association between ZIKV infection and the development of an extensive spectrum of central nervous system inflammatory demyelinating diseases (CNS IDD), such as multiple sclerosis-like clinical phenotypes. However, the underlying mechanisms of host-pathogen neuro-immune interactions remain to be elucidated. This study aimed to identify common transcriptional signatures between multiple sclerosis (MS) and ZIKV infection to generate molecular interaction networks, thereby leading to the identification of deregulated processes and pathways, which could give an insight of these underlying molecular mechanisms. Our investigation included publicly available transcriptomic data from MS patients in either relapse or remission (RR-MS) and datasets of subjects acutely infected by ZIKV for both immune peripheral cells and central nervous system cells. The protein-protein interaction (PPI) analysis showed upregulated AP-1 transcription factors (JUN and FOS) among the top hub and bottleneck genes in RR-MS and ZIKV data. Gene enrichment analysis retrieved a remarkable presence of ontologies and pathways linked to oxidative stress responses, immune cell function, inflammation, interleukin signaling, cell division, and transcriptional regulation commonly enriched in both scenarios. Considering the recent findings concerning AP-1 function in immunological tolerance breakdown, regulation of inflammation, and its function as an oxidative stress sensor, we postulate that the ZIKV trigger may contribute as a boost for the activation of such AP-1-regulated mechanisms that could favor the development of MS-like phenotypes following ZIKV infection in a genetically susceptible individual.

Quantitative Proteomics of Nervous System Regeneration: From Sample Preparation to Functional Data Analyses.

Mammals have a limited regenerative capacity, especially of the central nervous system. Consequently, any traumatic injury or neurodegenerative disease results in irreversible damage. An important approach to finding strategies to promote regeneration in mammals has been the study of regenerative organisms like Xenopus, the axolotl, and teleost fish. High-throughput technologies like RNA-Seq and quantitative proteomics are starting to provide valuable insight into the molecular mechanisms that drive nervous system regeneration in these organisms. In this chapter, we present a detailed protocol for performing iTRAQ proteomics that can be applied to the analysis of nervous system samples, using Xenopus laevis as an example. The quantitative proteomics protocol and directions for performing functional enrichment data analyses of gene lists (e.g., differentially abundant proteins from a proteomic study, or any type of high-throughput analysis) are aimed at the general bench biologist and do not require previous programming knowledge.

Whole-Blood Gene Expression Profiles Associated with Mortality in Community-Acquired Pneumonia.

(1) Background: Information regarding gene expression profiles and the prognosis of community-acquired pneumonia (CAP) is scarce. We aimed to examine the differences in the gene expression profiles in peripheral blood at hospital admission between patients with CAP who died during hospitalization and those who survived. (2) Methods: This is a multicenter study of nonimmunosuppressed adult patients who required hospitalization for CAP. Whole blood samples were obtained within 24 h of admission for genome-expression-profile analysis. Gene expression profiling identified both differentially expressed genes and enriched gene sets. (3) Results: A total of 198 samples from adult patients who required hospitalization for CAP were processed, of which 13 were from patients who died. Comparison of gene expression between patients who died and those who survived yielded 49 differentially expressed genes, 36 of which were upregulated and 13 downregulated. Gene set enrichment analysis (GSEA) identified four positively enriched gene sets in survivors, mainly associated with the interferon-alpha response, apoptosis, and sex hormone pathways. Similarly, GSEA identified seven positively enriched gene sets, associated with the oxidative stress, endoplasmic reticulum stress, oxidative phosphorylation, and angiogenesis pathways, in the patients who died. Protein-protein-interaction-network analysis identified FOS, CDC42, SLC26A10, EIF4G2, CCND3, ASXL1, UBE2S, and AURKA as the main gene hubs. (4) Conclusions: We found differences in gene expression profiles at hospital admission between CAP patients who died and those who survived. Our findings may help to identify novel candidate pathways and targets for potential intervention and biomarkers for risk stratification.

GOCompare: An R package to compare functional enrichment analysis between two species.

Functional enrichment analysis is a cornerstone in bioinformatics as it makes possible to identify functional information by using a gene list as source. Different tools are available to compare gene ontology (GO) terms, based on a directed acyclic graph structure or content-based algorithms which are time-consuming and require a priori information of GO terms. Nevertheless, quantitative procedures to compare GO terms among gene lists and species are not available. Here we present a computational procedure, implemented in R, to infer functional information derived from comparative strategies. GOCompare provides a framework for functional comparative genomics starting from comparable lists from GO terms. The program uses functional enrichment analysis (FEA) results and implement graph theory to identify statistically relevant GO terms for both, GO categories and analyzed species. Thus, GOCompare allows finding new functional information complementing current FEA approaches and extending their use to a comparative perspective. To test our approach GO terms were obtained for a list of aluminum tolerance-associated genes in Oryza sativa subsp. japonica and their orthologues in Arabidopsis thaliana. GOCompare was able to detect functional similarities for reactive oxygen species and ion binding capabilities which are common in plants as molecular mechanisms to tolerate aluminum toxicity. Consequently, the R package exhibited a good performance when implemented in complex datasets, allowing to establish hypothesis that might explain a biological process from a functional perspective, and narrowing down the possible landscapes to design wet lab experiments.

Bioinformatic Analysis of Human Cumulus Cells to Unravel Cellular's Processes that Could Be Used to Establish Oocyte Quality Biomarkers with Clinical Application.

Metadata analysis of public microarray datasets using bioinformatics tools has been successfully used in several biomedical fields in the search for biomarkers. In reproductive science, there is an urgent need for the establishment of oocyte quality biomarkers that could be used in the clinical environment to increase the chances of successful outcomes in treatment cycles. Adaptive cellular processes observed in cumulus oophorus cells reflect the conditions of the follicular microenvironment and may thus bring relevant information of oocyte's conditions. Here we analyzed human cumulus cells gene expression datasets in search of predictors of oocyte quality, a strategy which uncovered several cellular processes positively and negatively associated with embryo development and pregnancy potential. Secondly, the expression levels of genes that were present in the majority of processes observed were validated in house with clinical samples. Our data confirmed the association of the selected biomarkers with blastocyst formation and pregnancy potential rates, independently of patients' clinical characteristics such as diagnosis, age, BMI, and stimulation protocol applied. This study shows that bioinformatic analysis of cellular processes can be successfully used to elucidate possible oocyte quality biomarkers. Our data reinforces the need to consider clinical characteristics of patients when selecting relevant biomarkers to be used in the clinical environment and suggests a combination of positive (PTGS2) and negative (CYPB1) quality biomarkers as a robust strategy for a complementary oocyte selection tool, potentially increasing assisted reproduction success rates. Also, GPX4 expression as pregnancy potential biomarker is indicated here as a possibility for further investigations.

Transcriptome Meta-Analysis Confirms the Hidradenitis Suppurativa Pathogenic Triad: Upregulated Inflammation, Altered Epithelial Organization, and Dysregulated Metabolic Signaling.

Hidradenitis suppurativa (HS) is an inflammatory skin condition clinically characterized by recurrent painful deep-seated nodules, abscesses, and sinus tracks in areas bearing apocrine glands, such as axillae, breasts, groins, and buttocks. Despite many recent advances, the pathophysiological landscape of HS still demands further clarification. To elucidate HS pathogenesis, we performed a meta-analysis, set analysis, and a variant calling on selected RNA-Sequencing (RNA-Seq) studies on HS skin. Our findings corroborate the HS triad composed of upregulated inflammation, altered epithelial differentiation, and dysregulated metabolism signaling. Upregulation of specific genes, such as KRT6, KRT16, serpin-family genes, and SPRR3 confirms the early involvement of hair follicles and the impairment of barrier function in HS lesioned skin. In addition, our results suggest that adipokines could be regarded as biomarkers of HS and metabolic-related disorders. Finally, the RNA-Seq variant calling identified several mutations in HS patients, suggesting potential new HS-related genes associated with the sporadic form of this disease. Overall, this study provides insights into the molecular pathways involved in HS and identifies potential HS-related biomarkers.

The regulatory landscape of retinoblastoma: a pathway analysis perspective.

Retinoblastoma (Rb) is a rare intraocular tumour in early childhood, with an approximate incidence of 1 in 18 000 live births. Experimental studies for Rb are complex due to the challenges associated with obtaining a normal retina to contrast with diseased tissue. In this work, we reanalyse a dataset that contains normal retina samples. We identified the individual genes whose expression is different in Rb in contrast with normal tissue, determined the pathways whose global expression pattern is more distant from the global expression observed in normal tissue, and finally, we identified which transcription factors regulate the highest number of differentially expressed genes (DEGs) and proposed as transcriptional master regulators (TMRs). The enrichment of DEGs in the phototransduction and retrograde endocannabinoid signalling pathways could be associated with abnormal behaviour of the processes leading to cellular differentiation and cellular proliferation. On the other hand, the TMRs nuclear receptor subfamily 5 group A member 2 and hepatocyte nuclear factor 4 gamma are involved in hepatocyte differentiation. Therefore, the enrichment of aberrant expression in these transcription factors could suggest an abnormal retina development that could be involved in Rb origin and progression.

Effects of PIM3 in prognosis of colon cancer.

PURPOSE: PIM kinase is called proto-oncogene, but there are less research on PIM family in colon cancer. This study was designed to explore the prognosis of PIM3 in colon cancer. METHODS: In this study, we downloaded RNA-seq and clinical information of colon cancer from the Gene Expression Omnibus (GEO) database. Kaplan-Meier method was used for analyzing the impact of PIM3 on the survival of patients with colon cancer. Single-factor and multi-factor cox regression analysis were used for verifying the prognostic value of PIM3. Spearman correlation analysis was used for screening PIM3 related genes. Functional enrichment analysis was used for analyzing the biological functions and pathways in which PIM3 related genes may be involved. STRING online tools were used for building a co-expression network. Cytoscape was used for co-expression network visualization. RESULTS: Compared with the low expression group, the patients in the PIM3 high expression group lived longer time. Single-factor and multi-factor cox regression analysis indicated that PIM3 was an independent prognostic factor for colon cancer. Sixty-two PIM3 related genes were screened, and GO and KEGG enrichment analyses suggested that PIM3 related genes might be involved in the MAPK and WNT pathways. The co-expression network showed a strong correlation between PIM3 and MLKL, MYL5, PPP3R1 and other genes. CONCLUSIONS: PIM3 is an independent prognostic factor of colon cancer and may be a target for the diagnosis and treatment of colon cancer.

Network analysis uncovers putative genes affecting resistance to tick infestation in Braford cattle skin.

BACKGROUND: Genetic resistance in cattle is considered a suitable way to control tick burden and its consequent losses for livestock production. Exploring tick-resistant (R) and tick-susceptible (S) hosts, we investigated the genetic mechanisms underlying the variation of Braford resistance to tick infestation. Skin biopsies from four-times-artificially infested R (n = 20) and S (n = 19) hosts, obtained before the first and 24 h after the fourth tick infestation were submitted to RNA-Sequencing. Differential gene expression, functional enrichment, and network analysis were performed to identify genetic pathways and transcription factors (TFs) affecting host resistance. RESULTS: Intergroup comparisons of hosts before (Rpre vs. Spre) and after (Rpost vs. Spost) tick infestation found 51 differentially expressed genes (DEGs), of which almost all presented high variation (TopDEGs), and 38 were redundant genes. Gene expression was consistently different between R and S hosts, suggesting the existence of specific anti-tick mechanisms. In the intragroup comparisons, Rpost vs. Rpre and Spost vs. Spre, we found more than two thousand DEGs in response to tick infestation in both resistance groups. Redundant and non-redundant TopDEGs with potential anti-tick functions suggested a role in the development of different levels of resistance within the same breed. Leukocyte chemotaxis was over-represented in both hosts, whereas skin degradation and remodeling were only found in TopDEGs from R hosts. Also, these genes indicated the participation of cytokines, such as IL6 and IL22, and the activation of Wingless (WNT)-signaling pathway. A central gene of this pathway, WNT7A, was consistently modulated when hosts were compared. Moreover, the findings based on a genome-wide association study (GWAS) corroborate the prediction of the WNT-signaling pathway as a candidate mechanism of resistance. The regulation of immune response was the most relevant pathway predicted for S hosts. Members of Ap1 and NF-kB families were the most relevant TFs predicted for R and S, respectively. CONCLUSION: This work provides indications of genetic mechanisms presented by Braford cattle with different levels of resistance in response to tick infestation, contributing to the search of candidate genes for tick resistance in bovine.

Mining Regional Imaging Genetic Associations via Voxel-wise Enrichment Analysis.

Brain imaging genetics aims to reveal genetic effects on brain phenotypes, where most studies examine phenotypes defined on anatomical or functional regions of interest (ROIs) given their biologically meaningful annotation and modest dimensionality compared with voxel-wise approaches. Typical ROI-level measures used in these studies are summary statistics from voxel-wise measures in the region, without making full use of individual voxel signals. In this paper, we propose a flexible and powerful framework for mining regional imaging genetic associations via voxel-wise enrichment analysis, which embraces the collective effect of weak voxel-level signals within an ROI. We demonstrate our method on an imaging genetic analysis using data from the Alzheimers Disease Neuroimaging Initiative, where we assess the collective regional genetic effects of voxel-wise FDGPET measures between 116 ROIs and 19 AD candidate SNPs. Compared with traditional ROI-wise and voxel-wise approaches, our method identified 102 additional significant associations, some of which were further supported by evidences in brain tissue-specific expression analysis. This demonstrates the promise of the proposed method as a flexible and powerful framework for exploring imaging genetic effects on the brain.

Comparative genome analysis of Phyllosticta citricarpa and Phyllosticta capitalensis, two fungi species that share the same host.

BACKGROUND: Citrus are among the most important crops in the world. However, there are many diseases that affect Citrus caused by different pathogens. Citrus also hosts many symbiotic microorganisms in a relationship that may be advantageous for both organisms. The fungi Phyllosticta citricarpa, responsible for citrus black spot, and Phyllosticta capitalensis, an endophytic species, are examples of closely related species with different behavior in citrus. Both species are always biologically associated and are morphologically very similar, and comparing their genomes could help understanding the different lifestyles. In this study, a comparison was carried to identify genetic differences that could help us to understand the biology of P. citricarpa and P. capitalensis. RESULTS: Drafts genomes were assembled with sizes close to 33 Mb for both fungi, carrying 15,206 and 14,797 coding sequences for P. citricarpa and P. capitalensis, respectively. Even though the functional categories of these coding sequences is similar, enrichment analysis showed that the pathogenic species presents growth and development genes that may be necessary for the pathogenicity of P. citricarpa. On the other hand, family expansion analyses showed the plasticity of the genome of these species. Particular families are expanded in the genome of an ancestor of P. capitalensis and a recent expansion can also be detected among this species. Additionally, evolution could be driven by environmental cues in P. citricarpa. CONCLUSIONS: This work demonstrated genomic differences between P. citricarpa and P. capitalensis. Although the idea that these differences could explain the different lifestyles of these fungi, we were not able to confirm this hypothesis. Genome evolution seems to be of real importance among the Phyllosticta isolates and it is leading to different biological characteristics of these species.