scholarly journals Genenames.org: the HGNC and VGNC resources in 2021

2020 ◽  
Vol 49 (D1) ◽  
pp. D939-D946 ◽  
Author(s):  
Susan Tweedie ◽  
Bryony Braschi ◽  
Kristian Gray ◽  
Tamsin E M Jones ◽  
Ruth L Seal ◽  
...  
Keyword(s):  
Olfactory Receptors ◽  
Gene Nomenclature ◽  
Online Data ◽  
Protein Coding ◽  
Nomenclature Committee ◽  
Core Species ◽  
Human Genes ◽  
Core Set ◽  
Disease Associated Genes ◽  
Current Database

Abstract The HUGO Gene Nomenclature Committee (HGNC) based at EMBL’s European Bioinformatics Institute (EMBL-EBI) assigns unique symbols and names to human genes. There are over 42,000 approved gene symbols in our current database of which over 19 000 are for protein-coding genes. While we still update placeholder and problematic symbols, we are working towards stabilizing symbols where possible; over 2000 symbols for disease associated genes are now marked as stable in our symbol reports. All of our data is available at the HGNC website https://www.genenames.org. The Vertebrate Gene Nomenclature Committee (VGNC) was established to assign standardized nomenclature in line with human for vertebrate species lacking their own nomenclature committee. In addition to the previous VGNC core species of chimpanzee, cow, horse and dog, we now name genes in cat, macaque and pig. Gene groups have been added to VGNC and currently include two complex families: olfactory receptors (ORs) and cytochrome P450s (CYPs). In collaboration with specialists we have also named CYPs in species beyond our core set. All VGNC data is available at https://vertebrate.genenames.org/. This article provides an overview of our online data and resources, focusing on updates over the last two years.

scholarly journals Conserved long-range base pairings are associated with pre-mRNA processing of human genes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Svetlana Kalmykova ◽  
Marina Kalinina ◽  
Stepan Denisov ◽  
Alexey Mironov ◽  
Dmitry Skvortsov ◽  
...  
Keyword(s):  
Long Range ◽  
Rna Folding ◽  
Current Knowledge ◽  
Rna Structures ◽  
Base Pairs ◽  
Protein Coding ◽  
Proximity Ligation ◽  
Transcriptional Suppression ◽  
Human Genes ◽  
Cleavage And Polyadenylation

AbstractThe ability of nucleic acids to form double-stranded structures is essential for all living systems on Earth. Current knowledge on functional RNA structures is focused on locally-occurring base pairs. However, crosslinking and proximity ligation experiments demonstrated that long-range RNA structures are highly abundant. Here, we present the most complete to-date catalog of conserved complementary regions (PCCRs) in human protein-coding genes. PCCRs tend to occur within introns, suppress intervening exons, and obstruct cryptic and inactive splice sites. Double-stranded structure of PCCRs is supported by decreased icSHAPE nucleotide accessibility, high abundance of RNA editing sites, and frequent occurrence of forked eCLIP peaks. Introns with PCCRs show a distinct splicing pattern in response to RNAPII slowdown suggesting that splicing is widely affected by co-transcriptional RNA folding. The enrichment of 3’-ends within PCCRs raises the intriguing hypothesis that coupling between RNA folding and splicing could mediate co-transcriptional suppression of premature pre-mRNA cleavage and polyadenylation.

scholarly journals Disrupting upstream translation in mRNAs is associated with human disease

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
David S. M. Lee ◽  
Joseph Park ◽  
Andrew Kromer ◽  
Aris Baras ◽  
Daniel J. Rader ◽  
...  
Keyword(s):  
Protein Expression ◽  
Biological Significance ◽  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Protein Coding ◽  
Stop Codons ◽  
Human Genes ◽  
Strong Negative Selection ◽  
Disease Associations ◽  
Reading Frames

AbstractRibosome-profiling has uncovered pervasive translation in non-canonical open reading frames, however the biological significance of this phenomenon remains unclear. Using genetic variation from 71,702 human genomes, we assess patterns of selection in translated upstream open reading frames (uORFs) in 5’UTRs. We show that uORF variants introducing new stop codons, or strengthening existing stop codons, are under strong negative selection comparable to protein-coding missense variants. Using these variants, we map and validate gene-disease associations in two independent biobanks containing exome sequencing from 10,900 and 32,268 individuals, respectively, and elucidate their impact on protein expression in human cells. Our results suggest translation disrupting mechanisms relating uORF variation to reduced protein expression, and demonstrate that translation at uORFs is genetically constrained in 50% of human genes.

scholarly journals Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes

2014 ◽  
Author(s):  
Daniel S Himmelstein ◽  
Sergio E Baranzini
Keyword(s):  
Data Integration ◽  
Protein Interactions ◽  
Heterogeneous Network ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Protein Coding ◽  
Multiple Node ◽  
Pathogenic Variants ◽  
Disease Associated Genes

The first decade of Genome Wide Association Studies (GWAS) has uncovered a wealth of disease-associated variants. Two important derivations will be the translation of this information into a multiscale understanding of pathogenic variants, and leveraging existing data to increase the power of existing and future studies through prioritization. We explore edge prediction on heterogeneous networks—graphs with multiple node and edge types—for accomplishing both tasks. First we constructed a network with 18 node types—genes, diseases, tissues, pathophysiologies, and 14 MSigDB (molecular signatures database)collections—and 19 edge types from high-throughput publicly-available resources. From this network composed of 40,343 nodes and 1,608,168 edges, we extracted features that describe the topology between specific genes and diseases. Next, we trained a model from GWAS associations and predicted the probability of association between each protein-coding gene and each of 29 well-studied complex diseases. The model, which achieved 132-fold enrichment in precision at 10% recall, outperformed any individual domain, highlighting the benefit of integrative approaches. We identified pleiotropy, transcriptional signatures of perturbations, pathways, and protein interactions as fundamental mechanisms explaining pathogenesis. Our method successfully predicted the results (with AUROC = 0.79) from a withheld multiple sclerosis (MS) GWAS despite starting with only 13 previously associated genes. Finally, we combined our network predictions with statistical evidence of association to propose four novel MS genes, three of which (JAK2, REL, RUNX3) validated on the masked GWAS. Furthermore, our predictions provide biological support highlighting REL as the causal gene within its gene-rich locus. Users can browse all predictions online (http://het.io). Heterogeneous network edge prediction effectively prioritized genetic associations and provides a powerful new approach for data integration across multiple domains.

scholarly journals Loss of critical developmental and human disease-causing genes in 58 mammals

2019 ◽  
Author(s):  
Yatish Turakhia ◽  
Heidi I. Chen ◽  
Amir Marcovitz ◽  
Gill Bejerano
Keyword(s):  
Evolutionary Biology ◽  
Large Scale ◽  
Gene Annotation ◽  
Synonymous Substitution ◽  
Specific Gene ◽  
High Confidence ◽  
Protein Coding ◽  
Congenital Diseases ◽  
Manual Curation ◽  
Human Genes

Gene losses provide an insightful route for studying the morphological and physiological adaptations of species, but their discovery is challenging. Existing genome annotation tools and protein databases focus on annotating intact genes and do not attempt to distinguish nonfunctional genes from genes missing annotation due to sequencing and assembly artifacts. Previous attempts to annotate gene losses have required significant manual curation, which hampers their scalability for the ever-increasing deluge of newly sequenced genomes. Using extreme sequence erosion (deletion and non-synonymous substitution) as an unambiguous signature of loss, we developed an automated approach for detecting high-confidence protein-coding gene loss events across a species tree. Our approach relies solely on gene annotation in a single reference genome, raw assemblies for the remaining species to analyze, and the associated phylogenetic tree for all organisms involved. Using the hg38 human assembly as a reference, we discovered over 500 unique human genes affected by such high-confidence erosion events in different clades across 58 mammals. While most of these events likely have benign consequences, we also found dozens of clade-specific gene losses that result in early lethality in outgroup mammals or are associated with severe congenital diseases in humans. Our discoveries yield intriguing potential for translational medical genetics and for evolutionary biology, and our approach is readily applicable to large-scale genome sequencing efforts across the tree of life.

scholarly journals An Improved Human smORF Annnotation Workflow Combining De Novo Transcriptome Assembly and Ribo-Seq

2019 ◽  
Author(s):  
Thomas F. Martinez ◽  
Qian Chu ◽  
Cynthia Donaldson ◽  
Dan Tan ◽  
Maxim N. Shokhirev ◽  
...  
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Human Leukocyte ◽  
Open Reading Frames ◽  
Translation Efficiency ◽  
Proteomics Data ◽  
Protein Coding ◽  
Leukocyte Antigen ◽  
Human Genes ◽  
Small Open Reading Frames

Protein-coding small open reading frames (smORFs) are emerging as an important class of genes, however, the coding capacity of smORFs in the human genome is unclear. By integrating de novo transcriptome assembly and Ribo-Seq, we confidently annotate thousands of novel translated smORFs in three human cell lines. We find that smORF translation prediction is noisier than for annotated coding sequences, underscoring the importance of analyzing multiple experiments and footprinting conditions. These smORFs are located within non-coding and antisense transcripts, the UTRs of mRNAs, and unannotated transcripts. Analysis of RNA levels and translation efficiency during cellular stress identifies regulated smORFs, providing an approach to select smORFs for further investigation. Sequence conservation and signatures of positive selection indicate that encoded microproteins are likely functional. Additionally, proteomics data from enriched human leukocyte antigen complexes validates the translation of hundreds of smORFs and positions them as a source of novel antigens. Thus, smORFs represent a significant number of important, yet unexplored human genes.

scholarly journals Toward a Catalog of Human Genes and Proteins: Sequencing and Analysis of 500 Novel Complete Protein Coding Human cDNAs

2001 ◽  
Vol 11 (3) ◽  
pp. 422-435 ◽  
Author(s):  
Stefan Wiemann ◽  
Bernd Weil ◽  
Ruth Wellenreuther ◽  
Johannes Gassenhuber ◽  
Sabine Glassl ◽  
...  
Keyword(s):  
Protein Coding ◽  
Human Genes ◽  
Complete Protein

scholarly journals Novel SARS-CoV-2 encoded small RNAs in the passage to humans

2020 ◽  
Author(s):  
Gabriela A Merino ◽  
Jonathan Raad ◽  
Leandro A Bugnon ◽  
Cristian Yones ◽  
Laura Kamenetzky ◽  
...  
Keyword(s):  
Mature Mirnas ◽  
Human Cells ◽  
Species Boundaries ◽  
Rna Seq ◽  
New Host ◽  
Single Nucleotide ◽  
Stem Loop ◽  
Protein Coding ◽  
Transcriptional Reprogramming ◽  
Human Genes

Abstract Motivation The Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) has recently emerged as the responsible for the pandemic outbreak of the coronavirus disease (COVID-19). This virus is closely related to coronaviruses infecting bats and Malayan pangolins, species suspected to be an intermediate host in the passage to humans. Several genomic mutations affecting viral proteins have been identified, contributing to the understanding of the recent animal-to-human transmission. However, the capacity of SARS-CoV-2 to encode functional putative microRNAs (miRNAs) remains largely unexplored. Results We have used deep learning to discover 12 candidate stem-loop structures hidden in the viral protein-coding genome. Among the precursors, the expression of eight mature miRNAs-like sequences was confirmed in small RNA-seq data from SARS-CoV-2 infected human cells. Predicted miRNAs are likely to target a subset of human genes of which 109 are transcriptionally deregulated upon infection. Remarkably, 28 of those genes potentially targeted by SARS-CoV-2 miRNAs are down-regulated in infected human cells. Interestingly, most of them have been related to respiratory diseases and viral infection, including several afflictions previously associated with SARS-CoV-1 and SARS-CoV-2. The comparison of SARS-CoV-2 pre-miRNA sequences with those from bat and pangolin coronaviruses suggests that single nucleotide mutations could have helped its progenitors jumping inter-species boundaries, allowing the gain of novel mature miRNAs targeting human mRNAs. Our results suggest that the recent acquisition of novel miRNAs-like sequences in the SARS-CoV-2 genome may have contributed to modulate the transcriptional reprogramming of the new host upon infection.

The HUGO Gene Nomenclature Committee (HGNC)

2001 ◽  
Vol 109 (6) ◽  
pp. 678-680 ◽  
Author(s):  
Sue Povey ◽  
Ruth Lovering ◽  
Elspeth Bruford ◽  
Mathew Wright ◽  
Michael Lush ◽  
...  
Keyword(s):  
Hugo Gene Nomenclature Committee ◽  
Gene Nomenclature ◽  
Nomenclature Committee

scholarly journals Mammalian Septins Nomenclature

2002 ◽  
Vol 13 (12) ◽  
pp. 4111-4113 ◽  
Author(s):  
Ian G. Macara ◽  
Richard Baldarelli ◽  
Christine M. Field ◽  
Michael Glotzer ◽  
Yasuhide Hayashi ◽  
...  
Keyword(s):  
Human Genome ◽  
Gene Product ◽  
Genome Organization ◽  
Splice Variants ◽  
Gene Products ◽  
Gene Nomenclature ◽  
Nomenclature System ◽  
Nomenclature Committee ◽  
Human And Mouse ◽  
Mouse Genomic

There are 10 known mammalian septin genes, some of which produce multiple splice variants. The current nomenclature for the genes and gene products is very confusing, with several different names having been given to the same gene product and distinct names given to splice variants of the same gene. Moreover, some names are based on those of yeast or Drosophilaseptins that are not the closest homologues. Therefore, we suggest that the mammalian septin field adopt a common nomenclature system, based on that adopted by the Mouse Genomic Nomenclature Committee and accepted by the Human Genome Organization Gene Nomenclature Committee. The human and mouse septin genes will be namedSEPT1–SEPT10 and Sept1–Sept10, respectively. Splice variants will be designated by an underscore followed by a lowercase “v” and a number, e.g., SEPT4_v1.

scholarly journals Revealing missing isoforms encoded in the human genome by integrating genomic, transcriptomic and proteomic data

2014 ◽  
Author(s):  
Zhiqiang Hu ◽  
Hamish S. Scott ◽  
Guangrong Qin ◽  
Guangyong Zheng ◽  
Xixia Chu ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Shotgun Proteomics ◽  
Proteomics Data ◽  
Protein Coding ◽  
Novel Proteins ◽  
Proteomic Data ◽  
Human Genes ◽  
Human Proteins ◽  
Novel Transcripts ◽  
Coding Potential

Biological and biomedical research relies on comprehensive understanding of protein-coding transcripts. However, the total number of human proteins is still unknown due to the prevalence of alternative splicing and is much larger than the number of human genes. In this paper, we detected 31,566 novel transcripts with coding potential by filtering our ab initio predictions with 50 RNA-seq datasets from diverse tissues/cell lines. PCR followed by MiSeq sequencing showed that at least 84.1% of these predicted novel splice sites could be validated. In contrast to known transcripts, the expression of these novel transcripts were highly tissue-specific. Based on these novel transcripts, at least 36 novel proteins were detected from shotgun proteomics data of 41 breast samples. We also showed L1 retrotransposons have a more significant impact on the origin of new transcripts/genes than previously thought. Furthermore, we found that alternative splicing is extraordinarily widespread for genes involved in specific biological functions like protein binding, nucleoside binding, neuron projection, membrane organization and cell adhesion. In the end, the total number of human transcripts with protein-coding potential was estimated to be at least 204,950.

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