hLGDB: A database of human lysosomal genes and their regulation

Alessandro Brozzi, Lorena Urbanelli, Pierre Luc Germain, Alessandro Magini, Carla Emiliani

Research output: Contribution to journalArticlepeer-review

Abstract

Lysosomes are cytoplasmic organelles present in almost all eukaryotic cells, which play a fundamental role in key aspects of cellular homeostasis such as membrane repair, autophagy, endocitosis and protein metabolism. The characterization of the genes and enzymes constituting the lysosome represents a central issue to be addressed toward a better understanding of the biology of this organelle. In humans, mutations that cause lysosomal enzyme deficiencies result in >50 different disorders and severe pathologies. So far, many experimental efforts using different methodologies have been carried out to identity lysosomal genes. The Human Lysosome Gene Database (hLGDB) is the first resource that provides a comprehensive and accessible census of the human genes belonging to the lysosomal system. This database was developed by collecting and annotating gene lists from many different sources. References to the studies that have identified each gene are provided together with cross databases gene related information. Special attention has been given to the regulation of the genes through microRNAs and the transcription factor EB. The hLGDB can be easily queried to retrieve, combine and analyze information on different lists of lysosomal genes and their regulation by microRNA (binding sites predicted by five different algorithms). The hLGDB is an open access dynamic project that will permit in the future to collapse in a unique publicly accessible resource all the available biological information about lysosome genes and their regulation.

Original languageEnglish
Article numberbat024
JournalDatabase : the journal of biological databases and curation
Volume2013
DOIs
Publication statusPublished - 2013

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Information Systems

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