Cellular specialization in abiotic stress responses is an important regulatory feature driving plant acclimation. Our in silico approach of iterative coexpression, interaction, and enrichment analyses predicted root cell-specific regulators of phosphate starvation response networks in Arabidopsis (Arabidopsis thaliana). This included three uncharacterized genes termed Phosphate starvation-induced gene interacting Root Cell Enriched (PRCE1, PRCE2, and PRCE3). Root cell-specific enrichment of 12 candidates was confirmed in promoter-GFP lines. T-DNA insertion lines of 11 genes showed changes in phosphate status and growth responses to phosphate availability compared with the wild type. Some mutants (cbl1, cipk2, prce3, and wdd1) displayed strong biomass gain irrespective of phosphate supply, while others (cipk14, mfs1, prce1, prce2, and s6k2) were able to sustain growth under low phosphate supply better than the wild type. Notably, root or shoot phosphate accumulation did not strictly correlate with organ growth. Mutant response patterns markedly differed from those of master regulators of phosphate homeostasis, PHOSPHATE STARVATION RESPONSE1 (PHR1) and PHOSPHATE2 (PHO2), demonstrating that negative growth responses in the latter can be overcome when cell-specific regulators are targeted. RNA sequencing analysis highlighted the transcriptomic plasticity in these mutants and revealed PHR1-dependent and -independent regulatory circuits with gene coexpression profiles that were highly correlated to the quantified physiological traits. The results demonstrate how in silico prediction of cell-specific, stress-responsive genes uncovers key regulators and how their manipulation can have positive impacts on plant growth under abiotic stress.Forward and reverse genetics are powerful approaches for the discovery and characterization of gene function. While forward genetics is greatly facilitated by next-generation sequencing-assisted mapping, it is still limited by the design of appropriate screens that involve tens of thousands of plants. Conversely, reverse genetics involves phenotypic characterization of defined mutants, hence attributing the phenotype to the mutation (Winkler et al., 1998;Krysan et al., 1999). The preeminent model plant, Arabidopsis (Arabidopsis thaliana), has an extensive mutant library with substantial genome coverage (Sessions et al., 2002;Rosso et al., 2003), making reverse genetics an attractive strategy for investigating gene function (WilsonSánchez et al., 2014). A challenge of reverse genetics is selecting candidates that are biologically relevant to the field of research. One approach is to identify these from large-scale data sets, which are increasingly being generated in the postgenomics era (Ajjawi et al., 2010). Molecular profiling of genotypes on the omics scale has been carried out extensively. However, these studies tend to sample whole plants or plant organs, masking more subtle responses that occur within discrete cell populations. Fluorescence-activated cell sorting (FACS;Birnbaum et ...