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Von Hippel-Lindau Acts as a Metabolic Switch Controlling Nephron Progenitor Differentiation

ABSTRACT: RNA sequencing was performed on VHLNP+/- and VHLNP-/- E17.5 isolated nephron progenitors. E17.5 kidneys were dissected and screened using the GFP expression. Dissected kidneys that expressed GFP were dissociated into single cell suspensions and FACS sorted; each sample consisted of approximately 150,000 pooled nephron progenitor cells. RNA was extracted using the RNeasy Micro Kit (Qiagen). The Health Sciences Sequencing Core at Children’s Hospital of Pittsburgh performed library construction and RNA sequencing (single-end reads, 75bp). Bioinformatics quality control was performed using FastQC (version 0.11.5), and adapters were trimmed using BBDuk from the BBMap software package (version 37.41). Reads were aligned to transcripts assembled from the mm10 genome (GRCm38, GENCODE M17 ) using the Spliced Transcripts Alignments to a Reference software package (STAR, version 2.5.3a). Reads aligned to known transcripts were counted using the Bioconductor GenomicAlignments R package (version 1.10.1), and differential expression between VHLNP+/- and VHLNP-/- kidney samples was calculated using DESeq2 (version 1.18.1). Expression levels of 245 genes were identified as significantly altered between VHLNP+/- and VHLNP-/- samples (padj <= 0.05, fc > 2).

ORGANISM(S): Mus musculus

PROVIDER: GSE122900 | GEO | 2019/05/31

REPOSITORIES: GEO

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Project description:Purpose: The goal of this study are to investigate the TRPM1-regulated genes using RNAseq to compare the transcriptome profiling between 661W cells expressing TRPM1 and control vectors Methods: RNAs were isolatedusing the RNeasy Mini kit (Qiagen). RNA-seq libraries were prepared using the KAPA mRNA HyperPrep Kit (KAPA Biosystems, Roche, Basel, Switzerland) and validated using the Qsep 100 DNA/RNA Analyzer (BiOptic Inc., Taiwan). Libraries were sequenced on a NovaSeq 6000 sequencer (Illumina, CA, USA). Clean reads were aligned to the mouse genome (GRCm38) using HISAT2 (version 2.1.0) after removing low-quality reads. The differential expression of genes between TRPM1-overexpression and control cells was computed using the fragments per kilobase of transcript per million mapped reads calculated by featureCounts (version 2.0.0). Raw read counts were imported into edgeR (version 3.28.1) and analyzed by using R package of DESeq (version 1.40.0). Genes with false discovery rate (FDR) p-value < 0.05 adjusted by using Benjamini–Hochberg (BH) method were considered as differentially expressed genes (DEGs). Gene set enrichment analysis of the genes differentially expressed upon TRPM1 expression was done using the Gene Set Knowledgebase（GSKB）hallmark gene sets. Results: We had 40,922,040 clean reads in the control group and 44,244,608 clean reads in the TRPM1-overexpressing group. We mapped 43,253, 668 (97.76%) sequence reads in the control group and 39,942,649 (97.6%) sequence reads in the TRPM1-overexpressing group. We identified 16,014 transcripts. 76 transcripts showed differential expression between the vector control group and TRPM1-expressing group, with a fold change ≥1.5 and p value <0.01. Gene set enrichment analysis of the genes differentially expressed upon TRPM1 expression uncovered several TRPM1-regulated genes that may contribute to photoreceptor function, such as retina morphogenesis and JAK-STAT cascade. Conclusions: Our study represents the genes associated with TRPM1 overexpression in 661W photoreceptor cells using RNA-seq approach. The overexpression of TRPM1 may contribute to regulate the photoreceptor morphogenesis and function

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Von Hippel-Lindau Acts as a Metabolic Switch Controlling Nephron Progenitor Differentiation

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