Citation: Klees, S.; Heinrich, F.; Schmitt, A.O.; Gültas, M. agReg-SNPdb-Plants: A Database of Regulatory SNPs for Agricultural Plant Species. Biology 2022, 11, 684. https://doi.org/10.3390/ biology11050684 Academic Editor: M. Gonzalo Claros Received: 25 March 2022 Accepted: 27 April 2022 Published: 29 April 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). biology Article agReg-SNPdb-Plants: A Database of Regulatory SNPs for Agricultural Plant Species Selina Klees 1,2, * , Felix Heinrich 1 , Armin Otto Schmitt 1,2 and Mehmet Gültas 2,3, * 1 Breeding Informatics Group, Department of Animal Sciences, Georg-August University, Margarethe von Wrangell-Weg 7, 37075 Göttingen, Germany; felix.heinrich@uni-goettingen.de (F.H.); armin.schmitt@uni-goettingen.de (A.O.S.) 2 Center for Integrated Breeding Research (CiBreed), Carl-Sprengel-Weg 1, Georg-August University, 37075 Göttingen, Germany 3 Faculty of Agriculture, South Westphalia University of Applied Sciences, Lübecker Ring 2, 59494 Soest, Germany * Correspondence: selina.klees@uni-goettingen.de (S.K.); gueltas.mehmet@fh-swf.de (M.G.) Simple Summary: In breeding research, the investigation of regulatory SNPs (rSNPs) is becoming increasingly important due to their potential causal role for specific functional traits. Especially for crop species, there is still a lack of systematic analyses to detect rSNPs and their predicted effects on the binding of transcription factors. In this study, we present agReg-SNPdb-Plants, a database storing genome-wide collections of regulatory SNPs for agricultural plant species which can be queried via a web interface. Abstract: Single nucleotide polymorphisms (SNPs) that are located in the promoter regions of genes and affect the binding of transcription factors (TFs) are called regulatory SNPs (rSNPs). Their identifi- cation can be highly valuable for the interpretation of genome-wide association studies (GWAS), since rSNPs can reveal the biologically causative variant and decipher the regulatory mechanisms behind a phenotype. In our previous work, we presented agReg-SNPdb, a database of regulatory SNPs for agriculturally important animal species. To complement this previous work, in this study we present the extension agReg-SNPdb-Plants storing rSNPs and their predicted effects on TF-binding for 13 agri- culturally important plant species and subspecies (Brassica napus, Helianthus annuus, Hordeum vulgare, Oryza glaberrima, Oryza glumipatula, Oryza sativa Indica, Oryza sativa Japonica, Solanum lycopersicum, Sorghum bicolor, Triticum aestivum, Triticum turgidum, Vitis vinifera, and Zea mays). agReg-SNPdb-Plants can be queried via a web interface that allows users to search for SNP IDs, chromosomal regions, or genes. For a comprehensive interpretation of GWAS results or larger SNP-sets, it is possible to download the whole list of SNPs and their impact on transcription factor binding sites (TFBSs) from the website chromosome-wise. Keywords: regulatory SNP; transcription factor; transcription factor binding site; gene regulation; GWAS; database; agricultural plant species; crops 1. Introduction Climate change and its anticipated consequences pose severe challenges to mankind. For agriculture, global warming means that pathogens previously restricted to warmer climates will threaten local animal and plant species as well as expose plants to drought stress due to the increasing water shortage. A rapid and effective adaptation to the new environmental conditions is of paramount importance and can only be achieved through supportive plant breeding programs [1,2]. While breeding once used to be a relatively slow process limited by the generation interval of the species under study, the advent of molecular biology technologies, particularly large-scale genotyping at the whole-genome level, has turned the tide [3,4]. Today, genomic predictions aid the selection process in Biology 2022, 11, 684. https://doi.org/10.3390/biology11050684 https://www.mdpi.com/journal/biology