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Custom selection of reference genes for transcriptomic analysis

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NIAID Data Ecosystem2026-03-11 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE136038
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We developed a R-based script to select internal control genes based solely on read counts and gene sizes. We used this method to pick custom reference genes for the differential expression analysis of three transcriptome sets from transgenic Arabidopsis plants expressing heterologous fungal effector proteins tagged with GFP (using GFP alone as the control). The custom reference genes showed lower covariance and fold change as well as a broader range of expression levels than commonly used reference genes. When analyzed with NormFinder, both typical and custom reference genes were considered suitable internal controls, but the custom selected genes were more stable. geNorm produced a similar result in which most custom selected genes ranked higher (i.e. were more stable) than commonly used reference genes. Transgenic Arabidopsis thaliana Columbia-0 plants expressing GFP alone (Control) or fused to a candidate secreted effector protein of the fungus Melampsora larici-populina (Mlp37347 or Mlp124499) were used for the transcriptome analysis. RNA was extracted from pooled aerial tissue of 2-week-old soil-grown plants, doing four replicates per genotype. Libraries were generated using the TruSeq Stranded mRNA Library Prep kit (Illumina) and 100 ng of total RNA. The libraries were sequenced with Illumina HiSeq 4000 Sequencer paired-end reads of 100nt. Trimmomatic (LEADING:4 TRAILING:4 SLIDINGWINDOW:4:20 MINLEN:20) and then the surviving paired reads were aligned to the TAIR10 assembly of the genome of A. thaliana with TopHat v2.0.14 in Galaxy (default options, with average mate inner distance varying for each replicate and standard deviation of distance between pairs of 50 base pairs). Further analyses were done using R software v.3.2.5. Genomic ranges of Arabidopsis transcripts were obtained from Ensembl plants with GenomicFeatures and overlaps of sequencing reads with the transcripts were counted using GenomicAlignments, using options for paired-end reads and union mode.
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2019-08-24
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