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Comparison of mRNA populations between mutants with and without active HIF-1, and with and without functional nonsense-mediated decay.

ABSTRACT: This study looked at the interactions between the conserved hypoxia response pathway (controlled by EGL-9 and HIF-1) and the conserved nonsense-mediated decay (NMD) pathway in C. elegans. Given the role of HIF-1 as a transcription factor, and the role of NMD in degrading mRNA, we hypothesized that changes in both of these pathways would impact mRNA levels. To identify specific mRNAs that might be regulated by HIF-1 and/or NMD, we performed whole animal RNA-sequencing of samples of nine different genotypes, which had active or inactive HIF-1, and functional or nonfunctional NMD. Specifically, for HIF-1 activation samples were: wildtype [HIF-1 inactive], egl-9(-) [HIF-1 perpetually active] or egl-9(-) hif-1(-) [HIF-1 inactive]; and for NMD functionality samples were: wild type [functional NMD], smg-1(-) [NMD deficient] or smg-2(-) [NMD deficient]. Comparisons between genotypes can be used to identify HIF-1-dependent and NMD-dependent target mRNA.

ORGANISM(S): Caenorhabditis elegans

PROVIDER: GSE330000 | GEO | 2026/05/06

REPOSITORIES: GEO

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Project description:Purpose: We present a genome-wide investigation to distinguish mRNA substrates directly regulated by nonsense-mediated mRNA decay (NMD) from indirect secondary effects using true NMD null alleles Methods: mRNA profiles of wild type (N2), smg-1(r910), and smg-1(r910) smg-2(r915) animals were generated by deep sequencing, in triplicate, using Illumina HiSeq2000. We further performed deep sequencing in triplicate on RNAs that co-immunoprecipitate with the central effector of NMD, SMG-2, in both smg-1(r910) and smg-1(r910) smg-2(r915) mutant animals. The sequence reads that passed quality filters were analyzed at both the gene level and the intron level using Tophat2 and edgeR. qRT-PCR validation was performed using SYBR Green assays. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions: We found that a significant portion of genes with increased expression in an NMD-deficient background are direct substrates of SMG-2. Among the list of direct targets, we find many mRNAs from pseudogenes, alternative splice isoforms harboring PTCs, mRNAs encoding RNA processing factors, and two recently expanded gene families are directly regulated by the NMD pathway.

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Comparison of mRNA populations between mutants with and without active HIF-1, and with and without functional nonsense-mediated decay.

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