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. 2015 Jul 10;10(7):e0129321.
doi: 10.1371/journal.pone.0129321. eCollection 2015.

Transcriptomic-Wide Discovery of Direct and Indirect HuR RNA Targets in Activated CD4+ T Cells

Patsharaporn Techasintana  1 , J Wade Davis  2 , Matthew M Gubin  3 , Joseph D Magee  4 , Ulus Atasoy  1
Affiliations

Transcriptomic-Wide Discovery of Direct and Indirect HuR RNA Targets in Activated CD4+ T Cells

Patsharaporn Techasintana et al. PLoS One. .

Abstract

Due to poor correlation between steady state mRNA levels and protein product, purely transcriptomic profiling methods may miss genes posttranscriptionally regulated by RNA binding proteins (RBPs) and microRNAs (miRNAs). RNA immunoprecipitation (RIP) methods developed to identify in vivo targets of RBPs have greatly elucidated those mRNAs which may be regulated via transcript stability and translation. The RBP HuR (ELAVL1) and family members are major stabilizers of mRNA. Many labs have identified HuR mRNA targets; however, many of these analyses have been performed in cell lines and oftentimes are not independent biological replicates. Little is known about how HuR target mRNAs behave in conditional knock-out models. In the present work, we performed HuR RIP-Seq and RNA-Seq to investigate HuR direct and indirect targets using a novel conditional knock-out model of HuR genetic ablation during CD4+ T activation and Th2 differentiation. Using independent biological replicates, we generated a high coverage RIP-Seq data set (>160 million reads) that was analyzed using bioinformatics methods specifically designed to find direct mRNA targets in RIP-Seq data. Simultaneously, another set of independent biological replicates were sequenced by RNA-Seq (>425 million reads) to identify indirect HuR targets. These direct and indirect targets were combined to determine canonical pathways in CD4+ T cell activation and differentiation for which HuR plays an important role. We show that HuR may regulate genes in multiple canonical pathways involved in T cell activation especially the CD28 family signaling pathway. These data provide insights into potential HuR-regulated genes during T cell activation and immune mechanisms.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Venn diagram of RNA-Seq, RIP-Seq, and BioGRID reported ELAVL1 target genes.
Results from the RNA-Seq and RIP-Seq experiments were compared to genes experimentally verified in the literature to interact with ELAVL1, as curated in the BioGRID database. Results from BioGRID were limited to genes with mouse orthologs to make the results more compatible with our experiments.
Fig 2
Fig 2. Top canonical pathway (iCOS-iCOSL Signaling in T Helper Cells) overlaid with hits from union of RIP-Seq and RNA-Seq analyses.
Significant pathway nodes are shaded according to size of fold change (red >1; green <1), with white nodes indicating genes that were not detected in the samples and gray indicating genes that were detected, but not significant. Nodes with multicolor gradients denote nodes with significant genes with fold changes in different directions (see Table 2 for more details). Fold change is defined as KO/CTL (RNA-Seq) or IP/CTL (RIP-Seq). Colored double borders indicate that the molecule is a complex.
Fig 3
Fig 3. Canonical pathway for CD28 Signaling in T Helper Cells overlaid with hits from union of RIP-Seq and RNA-Seq analyses.
Significant pathway nodes are shaded according to size of fold change (red >1; green <1), with white nodes indicating genes that were not detected in the samples and gray indicating genes that were detected, but not significant. Nodes with multicolor gradients denote nodes with significant genes with fold changes in different directions (see Table 3 for more details). Fold change is defined as KO/CTL (RNA-Seq) or IP/CTL (RIP-Seq). Colored double borders indicate that the molecule is a complex.
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