An ERF/AP2-type transcription factor (CaPF1) was isolated by differential-display reverse transcription-PCR, following inoculation of the soybean pustule pathogen Xanthomonas axonopodis pv glycines 8ra, which induces hypersensitive response in pepper (Capsicum annuum) leaves. CaPF1 mRNA was induced under conditions of biotic and abiotic stress. Higher levels of CaPF1 transcripts were observed in disease-resistant tissue compared with susceptible tissue. CaPF1 expression was additionally induced using various treatment regimes, including ethephon, methyl jasmonate, and cold stress. To determine the role of CaPF1 in plants, transgenic Arabidopsis and tobacco (Nicotiana tabacum) plants expressing higher levels of CaPF1 were generated. Gene expression analyses of transgenic Arabidopsis and tobacco revealed that the CaPF1 level in transgenic plants affects expression of genes that contain either a GCC or a CRT/DRE box in their promoter regions. Furthermore, transgenic Arabidopsis plants expressing CaPF1 displayed tolerance against freezing temperatures and enhanced resistance to Pseudomonas syringae pv tomato DC3000. Disease tolerance was additionally observed in CaPF1 transgenic tobacco plants. The results collectively indicate that CaPF1 is an ERF/AP2 transcription factor in hot pepper plants that may play dual roles in response to biotic and abiotic stress in plants.

The core mission of ELIXIR is to build a stable and sustainable infrastructure for biological information across Europe. At the heart of this are the data resources, tools and services that ELIXIR offers to the life-sciences community, providing stable and sustainable access to biological data. ELIXIR aims to ensure that these resources are available long-term and that the life-cycles of these resources are managed such that they support the scientific needs of the life-sciences, including biological research.

Molecular biology and literature databases represent essential infrastructure for life science research. Effective integration of these data resources requires that there are structured cross-references at the level of individual articles and biological records. Here, we describe the current patterns of how database entries are cited in research articles, based on analysis of the full text Open Access articles available from Europe PMC. Focusing on citation of entries in the European Nucleotide Archive (ENA), UniProt and Protein Data Bank, Europe (PDBe), we demonstrate that text mining doubles the number of structured annotations of database record citations supplied in journal articles by publishers. Many thousands of new literature-database relationships are found by text mining, since these relationships are also not present in the set of articles cited by database records. We recommend that structured annotation of database records in articles is extended to other databases, such as ArrayExpress and Pfam, entries from which are also cited widely in the literature. The very high precision and high-throughput of this text-mining pipeline makes this activity possible both accurately and at low cost, which will allow the development of new integrated data services.