(m)RNA spatiotemporal pattern of distribution is of key importance to decipher gene function. In this post-genomic era, numerous transcriptomic studies are made publicly available, sometimes reaching a tissular resolution and even more rarely the cellular level. This "one tissue-numerous genes" information can be completed by the reverse "one gene-numerous tissues" picture through traditional RNA in situ hybridization (ISH). Here, we present a method including (1) principles of transcriptomic data mining to be performed prior and following ISH and (2) a detailed step-by-step medium-throughput ISH protocol performed on serial sections from tissue microarrays. In a recent work, we implemented this method for 39 selected genes studied by medium-throughput ISH complementing an existing tissue-specific transcriptomic dataset focused on the model plant Arabidopsis seed development kinetics (Francoz et al., Scientific Reports 6:24644, 2016). This full integration of ISH and transcriptomics demonstrated the complementarity of both techniques in terms of tissue/cell specificity, signal sensitivity, gene specificity, and spatiotemporal resolution.
Keywords: Arabidopsis; Data integration; Digoxigenin-labeled riboprobes; Medium-throughput RNA in situ hybridization; Plants; Seed development; Slide scanner; Tissue microarray paraffin serial sections; Tissue-specific transcriptomics.