Finding the Subcellular Location of Barley, Wheat, Rice and Maize Proteins: The Compendium of Crop Proteins with Annotated Locations (cropPAL)

Abstract

Barley, wheat, rice and maize provide the bulk of human nutrition and have extensive industrial use as agricultural products. The genomes of these crops each contains >40,000 genes encoding proteins; however, the major genome databases for these species lack annotation information of protein subcellular location for >80% of these gene products. We address this gap, by constructing the compendium of crop protein subcellular locations called crop Proteins with Annotated Locations (cropPAL). Subcellular location is most commonly determined by fluorescent protein tagging of live cells or mass spectrometry detection in subcellular purifications, but can also be predicted from amino acid sequence or protein expression patterns. The cropPAL database collates 556 published studies, from >300 research institutes in >30 countries that have been previously published, as well as compiling eight pre-computed subcellular predictions for all Hordeum vulgare, Triticum aestivum, Oryza sativa and Zea mays protein sequences. The data collection including metadata for proteins and published studies can be accessed through a search portal http://crop-PAL.org. The subcellular localization information housed in cropPAL helps to depict plant cells as compartmentalized protein networks that can be investigated for improving crop yield and quality, and developing new biotechnological solutions to agricultural challenges.

LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell

“…Therefore, we took the manually curated cropPAL database which features the subcellular localization of rice, wheat, maize and barley proteins24. We used only those proteins that are supported by GFP studies and localize to one subcellular compartment, resulting in a test set of 530 sequences.…”

“…We downloaded the set of crop plant proteins (barley, wheat, rice, maize) from the cropPal database24 and chose those that have a subcellular localization of either ‘plastid’ (100 proteins), ‘mitochondrion’ (61 proteins), ‘nucleus’ (165 proteins), ‘peroxisome’ (11 proteins), ‘vacuole’ (18 proteins), ‘plasma membrane’ (84 proteins, ‘endoplasmic reticulum’ (43 proteins) and ‘cytosol’ (48 proteins) determined by GFP-tagging. We only kept those sequences that started with an ‘M’.…”

SUBA4: the interactive data analysis centre for Arabidopsis subcellular protein locations

“…The smaller fraction of crop research using SUBA highlights the importance of improving the linkage of SUBA across species-specific borders as well as the need to improve linkage of comprehensive subcellular data collections for non-model crop species (9,10). …”

A Proteomic View on the Role of Legume Symbiotic Interactions

“…Several databases give either access to proteome sequence information of fully sequenced genomes and their functional annotation such as the Universal Protein Resource (UniProt, http://www.uniprot.org) or even of mass spectrometry spectral identification like ProMEX (Hummel et al, 2007; Wienkoop et al, 2012). Nevertheless, to date genomic databases for most plant model species, including legumes, lack proteome subcellular localization annotation (Hooper et al, 2016). One of the best-characterized subcellular proteome is that of the non-legume model plant A. thaliana , which is stored in the SUBA3 database (Tanz et al, 2013).…”

“…Recently, subcellular localization data based on gene co-expression have been extended for agriculturally relevant plants including soybean (Obayashi et al, 2014). An extension of this database integrating proteomic data of those species has been also made publically available (Hooper et al, 2016). …”