HGNC: The Why and How of Standardised Gene Nomenclature

The HUGO Gene Nomenclature Committee (HGNC) aims to approve a unique gene symbol and gene name for every human gene. Standardisation of gene symbols is necessary to allow researchers and curators to refer to the same gene without ambiguity. Consistent use of gene symbols in publications and across different websites makes it easy for researchers to find all relevant information for a particular gene and facilitates data mining and retrieval. For each gene that we name we curate relevant information including symbol aliases, chromosomal location, locus type, sequence accessions and links to relevant databases. Therefore, our website is a central resource for human genetics. 
 
We endeavour to approve gene symbols that are acceptable to researchers to encourage widespread use of our symbols. In order to achieve this, we contact researchers that work on particular genes for advice before approving symbols and allow researchers to submit gene symbols to us directly for our consideration. We attend conferences to discuss difficult nomenclature matters and to gain community agreement. We interact with annotators of genes and proteins to provide symbols and names that accurately reflect the nature of each gene and its products. We also work with the gene nomenclature committees for other organisms, and aim to approve equivalent gene symbols for orthologous genes in human and other vertebrate species, especially mouse and rat. 
 
We will demonstrate the steps that are required to name a gene, and will show how and where the nomenclature of a particular gene is used. We will also explain the nature of our collaborations with particular journals and other databases in striving to achieve the use of a common gene nomenclature by all

Exenatide Improves Bone Quality in a Murine Model of Genetically Inherited Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is associated with skeletal complications, including an increased risk of fractures. Reduced blood supply and bone strength may contribute to this skeletal fragility. We hypothesized that long-term administration of Exenatide, a glucagon- like peptide-1 receptor agonist, would improve bone architecture and strength of T2DM mice by increasing blood flow to bone, thereby stimulating bone formation. In this study, we used a model of obesity and severe T2DM, the leptin receptor-deficient db/db mouse to assess alterations in bone quality and hindlimb blood flow and to examine the beneficial effects of 4 weeks administration of Exenatide. As expected, diabetic mice showed marked alterations in bone structure, remodeling and strength, and basal vascular tone compared with lean mice. Exenatide treatment improved trabecular bone mass and architecture by increasing bone formation rate, but only in diabetic mice. Although there was no effect on hindlimb perfusion at the end of this treatment, exenatide administration acutely increased tibial blood flow. While Exenatide treatment did not restore the impaired bone strength, intrinsic properties of the matrix, such as collagen maturity, were improved. The effects of Exenatide on in vitro bone formation were further investigated in primary osteoblasts cultured under high-glucose conditions, showing that Exenatide reversed the impairment in bone formation induced by glucose. In conclusion, Exenatide improves trabecular bone mass by increasing bone formation and could protect against the development of skeletal complications associated with T2DM

Caenorhabditis nomenclature

Genetic nomenclature allows the genetic features of an organism to be structured and described in a uniform and systematicway. Genetic features, including genes, variations (both natural and induced), and gene products, are assigned descriptorsthat inform on the nature of the feature. These nomenclature designations facilitate communication among researchers (in publications,presentations, and databases) to advance understanding of the biology of the genetic feature and the experimental utilizationof organisms that contain the genetic feature. The nomenclature system that is used for C. elegans was first employed by Sydney Brenner (1974) in his landmark description of the genetics of this model organism, and then substantially extended and modified in Horvitz et al., 1979. The gene, allele, and chromosome rearrangement nomenclature, described below, is an amalgamation of that from bacteria andyeast, with the rearrangement types from Drosophila. The nomenclature avoids standard words, subscripts, superscripts, and Greek letters and includes a hyphen (-) to separatethe gene name from gene number (distinct genes with similar phenotypes or molecular properties). As described by Jonathan Hodgkin, ‘the hyphen is about 1 mm in length in printed text and therefore symbolizes the 1 mm long worm’. These nomenclature propertiesmake C. elegans publications highly suitable for informatic text mining, as there is minimal ambiguity. From the founding of the CaenorhabditisGenetics Center (CGC) in 1979 until 1992, Don Riddle and Mark Edgley acted as the central repository for genetic nomenclature. Jonathan Hodgkin was nomenclature czar from 1992 through 2013; this was a pivotal period with the elucidation of the genome sequence of C. elegans, and later that of related nematodes, and the inception of WormBase. Thus, under the guidance of Hodgkin, the nomenclature system became a central feature of WormBase and the number and types of genetic features significantly expanded. The nomenclature system remains dynamic, with recentadditions including guidelines related to genome engineering, and continued reliance on the community for input. WormBase assigns specific identifying codes to each laboratory engaged in dedicated long-term genetic research on C. elegans. Each laboratory is assigned a laboratory/strain code for naming strains, and an allele code for naming genetic variation(e.g., mutations) and transgenes. These designations are assigned to the laboratory head/PI who is charged with supervisingtheir organization in laboratory databases and their associated biological reagents that are described on WormBase, in publications, and distributed to the scientific community on request. The laboratory/strain code is used: a) to identifythe originator of community-supplied information on WormBase, which, in addition to attribution, facilitates communicationbetween the community/curators and the originator if an issue related to the information should arise at a later date; andb) to provide a tracking code for activities at the CGC. The laboratory/strain designation consists of 2-3 uppercase letters while the allele designation has 1-3 lowercase letters.The final letter of a laboratory code should not be an “O” or an “I” so as not to be mistaken for the numbers “0” or “1” respectively.Additionally, allele designations should also not end with the letter “l” which could also be mistaken for the number “1.” These codes are listed at the CGC and in WormBase. Investigators generating strains, alleles, transgenes, and/or defining genes require these designations and should applyfor them at [email protected]. Information for several other nematode species, in addition to C. elegans, is curated at WormBase. All species are referred to by their Linnean binomial names (e.g,. Caenorhabditis elegans or C. elegans). Details of all the genomes available at WormBase and the degree of their curation can be found at www.wormbase.org/species/al

Towards a New Science of a Clinical Data Intelligence

In this paper we define Clinical Data Intelligence as the analysis of data generated in the clinical routine with the goal of improving patient care. We define a science of a Clinical Data Intelligence as a data analysis that permits the derivation of scientific, i.e., generalizable and reliable results. We argue that a science of a Clinical Data Intelligence is sensible in the context of a Big Data analysis, i.e., with data from many patients and with complete patient information. We discuss that Clinical Data Intelligence requires the joint efforts of knowledge engineering, information extraction (from textual and other unstructured data), and statistics and statistical machine learning. We describe some of our main results as conjectures and relate them to a recently funded research project involving two major German university hospitals.Comment: NIPS 2013 Workshop: Machine Learning for Clinical Data Analysis and Healthcare, 201

The phytocannabinoid, Δ(9) -tetrahydrocannabivarin, can act through 5-HT1 A receptors to produce antipsychotic effects

Funded by: •GW Pharmaceuticals Acknowledgements: The authors wish to thank Mrs Lesley Stevenson for technical support and Dr John Raymond, Dr Keith Parker and Dr Ethan Russo for providing human 5-HT1A CHO cells. This research was supported by a grant from GW Pharmaceuticals to M. G. C. and R. G. P.Peer reviewedPostprin

Soluble ST2 levels and left ventricular structure and function in patients with metabolic syndrome

Background: A biomarker that is of great interest in relation to adverse cardiovascular events is soluble ST2 (sST2), a member of the interleukin family. Considering that metabolic syndrome (MetS) is accompanied by a proinflammatory state, we aimed to assess the relationship between sST2 and left ventricular (LV) structure and function in patients with MetS. Methods: A multicentric, cross-sectional study was conducted on180 MetS subjects with normal LV ejection fraction as determined by echocardiography. LV hypertrophy (LVH) was defined as an LV mass index greater than the gender-specific upper limit of normal as determined by echocardiography. LV diastolic dysfunction (DD) was assessed by pulse-wave and tissue Doppler imaging. sST2 was measured by using a quantitative monoclonal ELISA assay. Results: LV mass index (β=0.337, P<0 .001, linear regression) was independently associated with sST2 concentrations. Increased sST2 was associated with an increased likelihood of LVH [Exp (B)=2.20, P=0.048, logistic regression] and increased systolic blood pressure [Exp (B)=1.02, P=0.05, logistic regression]. Comparing mean sST2 concentrations (adjusted for age, body mass index, gender) between different LV remodeling patterns, we found the greatest sST2 level in the group with concentric hypertrophy. There were no differences in sST2 concentration between groups with and without LV DD. Conclusions: Increased sST2 concentration in patients with MetS was associated with a greater likelihood of exhibiting LVH. Our results suggest that inflammation could be one of the principal triggering mechanisms for LV remodeling in MetS

Reporting guidelines, review of methodological standards, and challenges toward harmonization in bone marrow adiposity research. Report of the Methodologies Working Group of the International Bone Marrow Adiposity Society

The interest in bone marrow adiposity (BMA) has increased over the last decade due to its association with, and potential role, in a range of diseases (osteoporosis, diabetes, anorexia, cancer) as well as treatments (corticosteroid, radiation, chemotherapy, thiazolidinediones). However, to advance the field of BMA research, standardization of methods is desirable to increase comparability of study outcomes and foster collaboration. Therefore, at the 2017 annual BMA meeting, the International Bone Marrow Adiposity Society (BMAS) founded a working group to evaluate methodologies in BMA research. All BMAS members could volunteer to participate. The working group members, who are all active preclinical or clinical BMA researchers, searched the literature for articles investigating BMA and discussed the results during personal and telephone conferences. According to the consensus opinion, both based on the review of the literature and on expert opinion, we describe existing methodologies and discuss the challenges and future directions for (1) histomorphometry of bone marrow adipocytes, (2

Duplicated membrane estrogen receptors in the European sea bass (Dicentrarchus labrax): Phylogeny, expression and regulation throughout the reproductive cycle

The numerous estrogen functions reported across vertebrates have been classically explained by their binding to specific transcription factors, the nuclear estrogen receptors (ERs). Rapid non-genomic estrogenic responses have also been recently identified in vertebrates including fish, which can be mediated by membrane receptors such as the G protein-coupled estrogen receptor (Gper). In this study, two genes for Gper, namely gpera and gperb, were identified in the genome of a teleost fish, the European sea bass. Phylogenetic analysis indicated they were most likely retained after the 3R teleost-specific whole genome duplication and raises questions about their function in male and female sea bass. Gpera expression was mainly restricted to brain and pituitary in both sexes while gperb had a widespread tissue distribution with higher expression levels in gill filaments, kidney and head kidney. Both receptors were detected in the hypothalamus and pituitary of both sexes and significant changes in gpers expression were observed throughout the annual reproductive season. In female pituitaries, gpera showed an overall increase in expression throughout the reproductive season while gperb levels remained constant. In the hypothalamus, gpera had a higher expression during vitellogenesis and decreased in fish entering the ovary maturation and ovulation stage, while gperb expression increased at the final atresia stage. In males, gpers expression was constant in the hypothalamus and pituitary throughout the reproductive cycle apart from the mid- to late testicular development stage transition when a significant up-regulation of gpera occurred in the pituitary. The differential sex, seasonal and subtype-specific expression patterns detected for the two novel gper genes in sea bass suggests they may have acquired different and/or complementary roles in mediating estrogens actions in fish, namely on the neuroendocrine control of reproduction.info:eu-repo/semantics/publishedVersio

Connexin36 knockout mice display increased sensitivity to pentylenetetrazol-induced seizure-like behaviors

Large-scale synchronous firing of neurons during seizures is modulated by electrotonic coupling between neurons via gap junctions. To explore roles for connexin36 (Cx36) gap junctions in seizures, we examined the seizure threshold of connexin36 knockout (Cx36KO) mice using a pentylenetetrazol (PTZ) model