Cardiac troponin I release after a basketball match in elite, amateur and junior players

BACKGROUND: Available scientific data related to cardiac troponin I (cTnI) release after intermittent exercise is limited. It is also of interest to determine what personal or environmental factors mediate the exercise-induced release of cTnI. This study had two objectives: 1) to examine the individual release of cTnI to a basketball match; and 2) to establish the influence of athlete status as well as biological age on cTnI release. METHODS: Thirty-six basketball players (12 adult elite [PBA]: 27.3±4.1 years, 12 adult amateur [ABA]: 29.6±2.9 years, and 12 junior elite [JBA]: 16.6±0.9 years) participated in a simulated basketball match with serial assessment of cTnI at rest, immediately post- and at 1, 3, 6, 12, and 24 h post-exercise. RESULTS: The basketball match increased cTnI levels (pre: median [range]; 0.006 [0.001-0.026]; peak post: 0.024 [0.004-0.244] μg/L; p=0.000), with substantial individual variability in peak values. PBA and JBA players showed higher baseline and post-exercise cTnI values than ABA (all p<0.05). Peak cTnI exceeded the upper reference limit (URL) in the 26% of players (3 PBA; 6 JBA). CONCLUSIONS: The current results suggest that intermittent exercise can promote the appearance of cTnI and that this is potentially mediated by athlete status

The effects of death and post-mortem cold ischemia on human tissue transcriptomes

Post-mortem tissues samples are a key resource for investigating patterns of gene expression. However, the processes triggered by death and the post-mortem interval (PMI) can significantly alter physiologically normal RNA levels. We investigate the impact of PMI on gene expression using data from multiple tissues of post-mortem donors obtained from the GTEx project. We find that many genes change expression over relatively short PMIs in a tissue-specific manner, but this potentially confounding effect in a biological analysis can be minimized by taking into account appropriate covariates. By comparing ante- and post-mortem blood samples, we identify the cascade of transcriptional events triggered by death of the organism. These events do not appear to simply reflect stochastic variation resulting from mRNA degradation, but active and ongoing regulation of transcription. Finally, we develop a model to predict the time since death from the analysis of the transcriptome of a few readily accessible tissues.Peer ReviewedPostprint (published version

Intra- and inter-individual genetic differences in gene expression

Genetic variation is known to influence the amount of mRNA produced by a gene. Given that the molecular machines control mRNA levels of multiple genes, we expect genetic variation in the components of these machines would influence multiple genes in a similar fashion. In this study we show that this assumption is correct by using correlation of mRNA levels measured independently in the brain, kidney or liver of multiple, genetically typed, mice strains to detect shared genetic influences. These correlating groups of genes (CGG) have collective properties that account for 40-90% of the variability of their constituent genes and in some cases, but not all, contain genes encoding functionally related proteins. Critically, we show that the genetic influences are essentially tissue specific and consequently the same genetic variations in the one animal may up-regulate a CGG in one tissue but down-regulate the same CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. The implication of this study is that this class of genetic variation can result in complex inter- and intra-individual and tissue differences and that this will create substantial challenges to the investigation of phenotypic outcomes, particularly in humans where multiple tissues are not readily available.&#xd;&#xa;&#xd;&#xa

Structural basis for the RING catalyzed synthesis of K63 linked ubiquitin chains

This work was supported by grants from Cancer Research UK (C434/A13067), the Wellcome Trust (098391/Z/12/Z) and Biotechnology and Biological Sciences Research Council (BB/J016004/1).The RING E3 ligase catalysed formation of lysine 63 linked ubiquitin chains by the Ube2V2–Ubc13 E2 complex is required for many important biological processes. Here we report the structure of the RING domain dimer of rat RNF4 in complex with a human Ubc13~Ub conjugate and Ube2V2. The structure has captured Ube2V2 bound to the acceptor (priming) ubiquitin with Lys63 in a position that could lead to attack on the linkage between the donor (second) ubiquitin and Ubc13 that is held in the active “folded back” conformation by the RING domain of RNF4. The interfaces identified in the structure were verified by in vitro ubiquitination assays of site directed mutants. This represents the first view of the synthesis of Lys63 linked ubiquitin chains in which both substrate ubiquitin and ubiquitin-loaded E2 are juxtaposed to allow E3 ligase mediated catalysis.PostprintPeer reviewe

Structural insight into SUMO chain recognition and manipulation by the ubiquitin ligase RNF4

The small ubiquitin-like modifier (SUMO) can form polymeric chains that are important signals in cellular processes such as meiosis, genome maintenance and stress response. The SUMO-targeted ubiquitin ligase RNF4 engages with SUMO chains on linked substrates and catalyses their ubiquitination, which targets substrates for proteasomal degradation. Here we use a segmental labelling approach combined with solution nuclear magnetic resonance (NMR) spectroscopy and biochemical characterization to reveal how RNF4 manipulates the conformation of the SUMO chain, thereby facilitating optimal delivery of the distal SUMO domain for ubiquitin transfer

Transcriptome analyses identify five transcription factors differentially expressed in the hypothalamus of post-versus prepubertal Brahman heifers

Puberty onset is a developmental process influenced by genetic determinants, environment, and nutrition. Mutations and regulatory gene networks constitute the molecular basis for the genetic determinants of puberty onset. The emerging knowledge of these genetic determinants presents opportunities for innovation in the breeding of early pubertal cattle. This paper presents new data on hypothalamic gene expression related to puberty in Bos indicus (Brahman) in age-and weight-matched heifers. Six postpubertal heifers were compared with 6 prepubertal heifers using whole-genome RNA sequencing methodology for quantification of global gene expression in the hypothalamus. Five transcription factors (TF) with potential regulatory roles in the hypothalamus were identified in this experiment: E2F8, NFAT5, SIX5, ZBTB38, and ZNF605. These TF genes were significantly differentially expressed in the hypothalamus of postpubertal versus prepubertal heifers and were also identified as significant according to the applied regulatory impact factor metric (P < 0.05). Two of these 5 TF, ZBTB38 and ZNF605, were zinc fingers, belonging to a gene family previously reported to have a central regulatory role in mammalian puberty. The SIX5 gene belongs to the family of homologues of Drosophila sine oculis (SIX) genes implicated in transcriptional regulation of gonadotrope gene expression. Tumor-related genes such as E2F8 and NFAT5 are known to affect basic cellular processes that are relevant in both cancer and developmental processes. Mutations in NFAT5 were associated with puberty in humans. Mutations in these TF, together with other genetic determinants previously discovered, could be used in genomic selection to predict the genetic merit of cattle (i.e., the likelihood of the offspring presenting earlier than average puberty for Brahman). Knowledge of key mutations involved in genetic traits is an advantage for genomic prediction because it can increase its accuracy

Serological autoimmune profile of systemic lupus erythematosus in deep and non-deep endometriosis patients

Several studies have reported a high prevalence of autoimmune diseases such as systemic lupus erythematosus (SLE) in endometriosis patients. The aim of this study was to evaluate the SLE autoimmune antibody profile in patients with deep (DE) and non-deep endometriosis (Non-DE).Four groups of premenopausal patients were evaluated: patients with DE (n = 50); patients with ovarian endometriomas (Non-DE; n = 50); healthy patients without endometriosis (C group; n = 45); and SLE patients without endometriosis (SLE group; N = 46). Blood samples were obtained and the standard SLE autoimmune profile was evaluated in all patients. Pain symptoms related to endometriosis and clinical SLE manifestations were also recorded.The DE group presented a statistically significant higher proportion of patients with antinuclear antibodies (ANA) (20%) compared to the Non-DE group (4%) and C group (2.2%). Levels of complement were more frequently lower among DE and Non-DE patients although differences did not reach statistical significance. Similarly, anti-dsDNA antibodies and anticoagulant lupus were positive in more patients of the DE group but did not reach statistical significance. The DE group complained of more arthralgia and asthenia compared to the Non-DE and C groups.The results of this study showed higher positivity of ANA and greater arthralgia and asthenia in patients with DE compared with Non-DE patients and healthy controls, suggesting that they may have a higher susceptibility to autoimmune diseases and present more generalized pain.Copyright © 2023. Published by Elsevier B.V

A functional SUMO-interacting motif in the transactivation domain of c-Myb regulates its myeloid transforming ability

c-Myb is an essential hematopoietic transcription factor that controls proliferation and differentiation of progenitors during blood cell development. Whereas sumoylation of the C-terminal regulatory domain (CRD) is known to have a major impact on the activity of c-Myb, no role for noncovalent binding of small ubiquitin-like modifier (SUMO) to c-Myb has been described. Based on the consensus SUMO-interacting motif (SIM), we identified and examined putative SIMs in human c-Myb. Interaction and reporter assays showed that the SIM in the in the transactivation domain of c-Myb (V 267 NIV) is functional. This motif is necessary for c-Myb to be able to interact noncovalently with SUMO, preferentially SUMO2/3. Destroying the SUMO-binding properties by mutation resulted in a large increase in the transactivation potential of c-Myb. Mutational analysis and overexpression of conjugation-defective SUMO argued against intramolecular repression caused by sumoylated CRD and in favor of SUMO-dependent repression in trans. Using both a myeloid cell line-based assay and a primary hematopoietic cell assay, we addressed the transforming abilities of SUMO binding and conjugation mutants. Interestingly, only loss of SUMO binding, and not SUMO conjugation, enhanced the myeloid transformational potential of c-Myb. c-Myb with the SIM mutated conferred a higher proliferative ability than the wild-type and caused an effective differentiation block. This establishes SUMO binding as a mechanism involved in modulating the transactivation activity of c-Myb, and responsible for keeping the transforming potential of the oncoprotein in check

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.Postprint (published version

Evaluation and improvement of the regulatory inference for large co-expression networks with limited sample size

Abstract Background Co-expression has been widely used to identify novel regulatory relationships using high throughput measurements, such as microarray and RNA-seq data. Evaluation studies on co-expression network analysis methods mostly focus on networks of small or medium size of up to a few hundred nodes. For large networks, simulated expression data usually consist of hundreds or thousands of profiles with different perturbations or knock-outs, which is uncommon in real experiments due to their cost and the amount of work required. Thus, the performances of co-expression network analysis methods on large co-expression networks consisting of a few thousand nodes, with only a small number of profiles with a single perturbation, which more accurately reflect normal experimental conditions, are generally uncharacterized and unknown. Methods We proposed a novel network inference methods based on Relevance Low order Partial Correlation (RLowPC). RLowPC method uses a two-step approach to select on the high-confidence edges first by reducing the search space by only picking the top ranked genes from an intial partial correlation analysis and, then computes the partial correlations in the confined search space by only removing the linear dependencies from the shared neighbours, largely ignoring the genes showing lower association. Results We selected six co-expression-based methods with good performance in evaluation studies from the literature: Partial correlation, PCIT, ARACNE, MRNET, MRNETB and CLR. The evaluation of these methods was carried out on simulated time-series data with various network sizes ranging from 100 to 3000 nodes. Simulation results show low precision and recall for all of the above methods for large networks with a small number of expression profiles. We improved the inference significantly by refinement of the top weighted edges in the pre-inferred partial correlation networks using RLowPC. We found improved performance by partitioning large networks into smaller co-expressed modules when assessing the method performance within these modules. Conclusions The evaluation results show that current methods suffer from low precision and recall for large co-expression networks where only a small number of profiles are available. The proposed RLowPC method effectively reduces the indirect edges predicted as regulatory relationships and increases the precision of top ranked predictions. Partitioning large networks into smaller highly co-expressed modules also helps to improve the performance of network inference methods. The RLowPC R package for network construction, refinement and evaluation is available at GitHub: https://github.com/wyguo/RLowPC