Figure 7. Mining Ca²⁺ data using a novel online resource .

(A) 3073 islet proteins significantly correlated to islet Ca²⁺ parameters of interest. Among the proteins, 647 had orthologues containing single-nucleotide polymorphisms (SNPs) for glycemic traits. Of these, 478 showed no results in our starting triage (see Methods) under any alias, suggesting they may be understudied in islet biology. (B) Of these 478 proteins, 198 were found to be secreted either as soluble proteins or in exosomes (Bateman et al., 2021; Thul et al., 2017; Uhlén et al., 2019; Navajas et al., 2022; Wang et al., 2013; Chen et al., 2019; Gonzales et al., 2009), 52 have existing knockout mice with annotated glycemia or pancreatic phenotypes (Groza et al., 2023; Blake et al., 2021), and 45 have existing compounds that target them (Stanford et al., 2021; Coker et al., 2019; Davies et al., 2015; Gaulton et al., 2017; Santos et al., 2017; Zhou et al., 2022). To make these data more accessible, we have developed an online resource that enables individuals to query the Ca²⁺ and proteomic data simultaneously. The user can select proteins and calcium traits (C) and display strain and sex distribution of these traits to determine the ideal backgrounds on which to test their traits or proteins of interest. In this example, GALNS is highly correlated to 8G/QLA/GIP A_D, with the highest and lowest abundance strains for GALNS being AJ (yellow arrow) and CAST (green arrow), respectively. (D) The user can also query for the correlations between Ca²⁺ traits and proteins against one another or other traits of the same category. (E) The user can also see which of the traits or proteins has the largest change and most significant effects by sex, strain, or sex and strain.