FlyBase at 25: looking to the future.

Since 1992, FlyBase (flybase.org) has been an essential online resource for the Drosophila research community. Concentrating on the most extensively studied species, Drosophila melanogaster, FlyBase includes information on genes (molecular and genetic), transgenic constructs, phenotypes, genetic and physical interactions, and reagents such as stocks and cDNAs. Access to data is provided through a number of tools, reports, and bulk-data downloads. Looking to the future, FlyBase is expanding its focus to serve a broader scientific community. In this update, we describe new features, datasets, reagent collections, and data presentations that address this goal, including enhanced orthology data, Human Disease Model Reports, protein domain search and visualization, concise gene summaries, a portal for external resources, video tutorials and the FlyBase Community Advisory Group

Bovine growth hormone releasing hormone gene: Structure, polymorphism and data management

The objective of this study was to sequence the bovine growth hormone releasing hormone (GHRH) gene, to screen for polymorphisms using single strand conformation polymorphism technique, to evaluate the association of any detected polymorphisms with genetic merit for production traits in a group of 200 dairy sires, and to develop a relational database program capable of organizing genetic data. ^ Genomic DNA for GHRH gene from three overlapping fragments was cloned and sequenced. The 9356-nucleotide sequence (GenBank accession number: AF242855) contained 306 nucleotides which encode a protein of 102 amino acids. Designing primers from this sequence, we amplified fragments of 200–400 bp covering 95% of the entire bovine GHRH gene, and discovered five polymorphic sites (A: 2063 in intron 1; B: 4193 in intron 1; C: in intron 1; D: 6905 in intron 4 and E: 8074 in intron 4). Four of those polymorphisms (A, B, D and E) were confirmed by sequencing, while the other (C) was not. Two substitutions occurred with restriction enzyme recognition sites (B with Taq I and D with Tfi I), and digestion of DNA samples from putative homologous and heterozygous individuals using those two enzymes agreed with our SSCP and sequence data. ^ Association between GHRH polymorphic and genetic merit was analyzed using the General Linear Model of the SAS program. Association between polymorphic site B with fat percentage (P = 0.029) was found. No significant differences were detected for all other sites (p \u3e 0.05). ^ Based on the relatively small number half-sibling information, thirteen from sixteen theoretically possible haplotypes had been found, and four of the thirteen constituted 93.2% of the haplotypes observed in this study. Genotypes for 55.7% (98/176) of the bulls were inferred. Haplotype B was found to have an association with protein yield (p \u3c 0.05). ^ A relational database to manage all research data in this study was created using Oracle. Using JAVA and extensive markup language, an intuitive graphic user interface incorporating three levels of user expertise was designed. The database and interfaces allow the user to accomplish the tasks such as extensive viewing, searching, and updating the database.

Gene Model Annotations for Drosophila melanogaster: The Rule-Benders

In the context of the FlyBase annotated gene models in Drosophila melanogaster, we describe the many exceptional cases we have curated from the literature or identified in the course of FlyBase analysis. These range from atypical but common examples such as dicistronic and polycistronic transcripts, noncanonical splices, trans-spliced transcripts, noncanonical translation starts, and stop-codon readthroughs, to single exceptional cases such as ribosomal frameshifting and HAC1-type intron processing. In FlyBase, exceptional genes and transcripts are flagged with Sequence Ontology terms and/or standardized comments. Because some of the rule-benders create problems for handlers of high-throughput data, we discuss plans for flagging these cases in bulk data downloads

ATG3-dependent autophagy mediates mitochondrial homeostasis in pluripotency acquirement and maintenance

<p>Pluripotent stem cells, including induced pluripotent and embryonic stem cells (ESCs), have less developed mitochondria than somatic cells and, therefore, rely more heavily on glycolysis for energy production.<a href="#cit0001 cit0002 cit0003" target="_blank">^1-3</a> However, how mitochondrial homeostasis matches the demands of nuclear reprogramming and regulates pluripotency in ESCs is largely unknown. Here, we identified ATG3-dependent autophagy as an executor for both mitochondrial remodeling during somatic cell reprogramming and mitochondrial homeostasis regulation in ESCs. Dysfunctional autophagy by <i>Atg3</i> deletion inhibited mitochondrial removal during pluripotency induction, resulting in decreased reprogramming efficiency and accumulation of abnormal mitochondria in established iPSCs. In <i>Atg3</i> null mouse ESCs, accumulation of aberrant mitochondria was accompanied by enhanced ROS generation, defective ATP production and attenuated pluripotency gene expression, leading to abnormal self-renewal and differentiation. These defects were rescued by reacquisition of wild-type but not lipidation-deficient <i>Atg3</i> expression. Taken together, our findings highlight a critical role of ATG3-dependent autophagy for mitochondrial homeostasis regulation in both pluripotency acquirement and maintenance.</p

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