Systematic variation in mRNA 3′-processing signals during mouse spermatogenesis

Gene expression and processing during mouse male germ cell maturation (spermatogenesis) is highly specialized. Previous reports have suggested that there is a high incidence of alternative 3′-processing in male germ cell mRNAs, including reduced usage of the canonical polyadenylation signal, AAUAAA. We used EST libraries generated from mouse testicular cells to identify 3′-processing sites used at various stages of spermatogenesis (spermatogonia, spermatocytes and round spermatids) and testicular somatic Sertoli cells. We assessed differences in 3′-processing characteristics in the testicular samples, compared to control sets of widely used 3′-processing sites. Using a new method for comparison of degenerate regulatory elements between sequence samples, we identified significant changes in the use of putative 3′-processing regulatory sequence elements in all spermatogenic cell types. In addition, we observed a trend towards truncated 3′-untranslated regions (3′-UTRs), with the most significant differences apparent in round spermatids. In contrast, Sertoli cells displayed a much smaller trend towards 3′-UTR truncation and no significant difference in 3′-processing regulatory sequences. Finally, we identified a number of genes encoding mRNAs that were specifically subject to alternative 3′-processing during meiosis and postmeiotic development. Our results highlight developmental differences in polyadenylation site choice and in the elements that likely control them during spermatogenesis

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

The glutathione redox system is essential to prevent ferroptosis caused by impaired lipid metabolism in clear cell renal cell carcinoma

The publisher's final edited version of this article is available at Oncogene. 2018 Oct;37(40):5435-5450. doi: 10.1038/s41388-018-0315-z. Epub 2018 Jun 5. Non-commercial use onlyThis study was funded by Cancer Research UK, the German Research Foundation (FOR2314) and the German Cancer Aid (111917)

The Gene Ontology in 2010: extensions and refinements

The Gene Ontology (GO) Consortium (http://www.geneontology.org) (GOC) continues to develop, maintain and use a set of structured, controlled vocabularies for the annotation of genes, gene products and sequences. The GO ontologies are expanding both in content and in structure. Several new relationship types have been introduced and used, along with existing relationships, to create links between and within the GO domains. These improve the representation of biology, facilitate querying, and allow GO developers to systematically check for and correct inconsistencies within the GO. Gene product annotation using GO continues to increase both in the number of total annotations and in species coverage. GO tools, such as OBO-Edit, an ontology-editing tool, and AmiGO, the GOC ontology browser, have seen major improvements in functionality, speed and ease of use.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Oxford University Press. The published article can be found at: http://nar.oxfordjournals.org/

DFLAT: functional annotation for human development.

BACKGROUND: Recent increases in genomic studies of the developing human fetus and neonate have led to a need for widespread characterization of the functional roles of genes at different developmental stages. The Gene Ontology (GO), a valuable and widely-used resource for characterizing gene function, offers perhaps the most suitable functional annotation system for this purpose. However, due in part to the difficulty of studying molecular genetic effects in humans, even the current collection of comprehensive GO annotations for human genes and gene products often lacks adequate developmental context for scientists wishing to study gene function in the human fetus. DESCRIPTION: The Developmental FunctionaL Annotation at Tufts (DFLAT) project aims to improve the quality of analyses of fetal gene expression and regulation by curating human fetal gene functions using both manual and semi-automated GO procedures. Eligible annotations are then contributed to the GO database and included in GO releases of human data. DFLAT has produced a considerable body of functional annotation that we demonstrate provides valuable information about developmental genomics. A collection of gene sets (genes implicated in the same function or biological process), made by combining existing GO annotations with the 13,344 new DFLAT annotations, is available for use in novel analyses. Gene set analyses of expression in several data sets, including amniotic fluid RNA from fetuses with trisomies 21 and 18, umbilical cord blood, and blood from newborns with bronchopulmonary dysplasia, were conducted both with and without the DFLAT annotation. CONCLUSIONS: Functional analysis of expression data using the DFLAT annotation increases the number of implicated gene sets, reflecting the DFLAT\u27s improved representation of current knowledge. Blinded literature review supports the validity of newly significant findings obtained with the DFLAT annotations. Newly implicated significant gene sets also suggest specific hypotheses for future research. Overall, the DFLAT project contributes new functional annotation and gene sets likely to enhance our ability to interpret genomic studies of human fetal and neonatal development. BMC Bioinformatics 2014; 15:45

Protein-centric connection of biomedical knowledge: Protein Ontology research and annotation tools

The Protein Ontology (PRO) web resource provides an integrative framework for protein-centric exploration and enables specific and precise annotation of proteins and protein complexes based on PRO. Functionalities include: browsing, searching and retrieving, terms, displaying selected terms in OBO or OWL format, and supporting URIs. In addition, the PRO website offers multiple ways for the user to request, submit, or modify terms and/or annotation. We will demonstrate the use of these tools for protein research and annotation

ATP and heat production in human skeletal muscle during dynamic exercise: higher efficiency of anaerobic than aerobic ATP resynthesis

The aim of the present study was to simultaneously examine skeletal muscle heat production and ATP turnover in humans during dynamic exercise with marked differences in aerobic metabolism. This was done to test the hypothesis that efficiency is higher in anaerobic than aerobic ATP resynthesis. Six healthy male subjects performed 90 s of low intensity knee-extensor exercise with (OCC) and without thigh occlusion (CON-LI) as well as 90 s of high intensity exercise (CON-HI) that continued from the CON-LI bout. Muscle heat production was determined by continuous measurements of muscle heat accumulation and heat release to the blood. Muscle ATP production was quantified by repeated measurements of thigh oxygen uptake as well as blood and muscle metabolite changes. All temperatures of the thigh were equalized to ≈37 °C prior to exercise by a water-perfused heating cuff. Oxygen uptake accounted for 80 ± 2 and 59 ± 4 %, respectively, of the total ATP resynthesis in CON-LI and CON-HI, whereas it was negligible in OCC. The rise in muscle temperature was lower (P < 0.05) in OCC than CON-LI (0.32 ± 0.04 vs. 0.37 ± 0.03 °C). The mean rate of heat production was also lower (P < 0.05) in OCC than CON-LI (36 ± 4 vs. 57 ± 4 J s−1). Mechanical efficiency was 52 ± 4 % after 15 s of OCC and remained constant, whereas it decreased (P < 0.05) from 56 ± 5 to 32 ± 3 % during CON-LI. During CON-HI, mechanical efficiency transiently increased (P < 0.05) to 47 ± 4 %, after which it decreased (P < 0.05) to 36 ± 3 % at the end of CON-HI. Assuming a fully coupled mitochondrial respiration, the ATP turnover per unit of work was calculated to be unaltered during OCC (≈20 mmol ATP kJ−1), whereas it increased (P < 0.05) from 21 ± 4 to 29 ± 3 mmol ATP kJ−1 during CON-LI and further (P < 0.05) to 37 ± 3 mmol ATP kJ−1 during CON-HI. The present data confirm the hypothesis that heat loss is lower in anaerobic ATP resynthesis than in oxidative phosphorylation and can in part explain the finding that efficiency declines markedly during dynamic exercise. In addition, the rate of ATP turnover apparently increases during constant load low intensity exercise. Alternatively, mitochondrial efficiency is lowered as exercise progresses, since ATP turnover was unaltered during the ischaemic exercise bout