GEO Series: GSE69701
Purpose: To identify orthologous genes in Xenopus that are implicated in deafness and vestibular disorders in humans and to compare RNA-Seq and microarray to determine the advantages of each technology for Xenopus transcriptomic analysis. Methods: Inner ear RNA from X. laevis stages 56-58 was isolated with the Qiagen® RNeasy® Mini Kit. RNA quality was assessed using the Agilent 2100 Bioanalyzer. The RNA was sent to the National Center for Genome Resources, for Illumina-Solexa sequencing using the genome analyzer II and to MIT for microarray processing usign the Affymetrix GeneChip® X. laevis Genome 2.0 Array. The OMIM database was mined for identification of genes causing deafness and vestibular disorder in humans. Human sequences for each of the deafness and vestibular disorders genes were downloaded from Ensembl. Blast-2.2.27+ was used to mapped the human sequences against X. tropicalis predicted proteins from JGI or to Xenopus consensus sequences downloaded from Affymetrix. The alignment of the human sequences to the predicted proteins resulted in the identification of the protein designation number. The protein designation number was used to obtain the sacaffold number and coordinates from JGI genome browser. The scaffold number and coordinates were input into Alpheus sequence variant detection pipeline to obtain the number of reads associated with each gene. The reads were log2 transformed for comparison to the microarray. In the case of the alignment of the human sequences to the Xenopus consensus sequences resulted in the PSID. The PSID was used to obtain the GCRMA intensity value. The GCRMA value and the number of reads were compared to determine which technology detected more genes. Results: Using Affymetrix GeneChip® X. laevis Genome 2.0 Arrays and Illumina-Solexa sequencing methods, we determined that the transcriptional profile of the Xenopus inner ear comprises hundreds of genes that are orthologous to OMIM® genes implicated in deafness and vestibular disorders in humans. Analysis of genes that mapped to both technologies showed that RNA-Seq detected more of both deafness and vestibular disorder than the Microarray. RNA-Seq and microarray detected 108 genes but RNA-Seq detected 48 genes that were below threshold criteria for microarray. While the microarray detected 11 genes that were below the expression criteria for RNA-Seq and 23 genes were below the threshold criteria for both technologies. Further analysis of the 108 genes detected by both technologies showed a minor correlation between the two technologies. Conclusions: As part of this study we identified candidate scaffold regions of the Xenopus tropicalis genome that can be used for gene mutagenesis. Furthermore, results from this study showed that the two technologies can complement each other and that a combination of both approaches can provide a more complete analysis of gene expression than either method alone.
Contributors: Daniel Ramire-Gordillo, Daniel Ramirez-Gordillo, TuShun Powers, Casilda Trujillo-Provencio, Jennifer van Velkinburgh, Faye Schilkey, Elba Serrano
Experiment Type: Inner ear RNA from X. laevis larval stages 56-58 was isolated and shipped to the National Center for Genome Resources, for Illumina-Solexa sequencing or to the Massachusetts Institute of Technology BioMicro Center for microarray analysis with the Affymetrix GeneChip® X. laevis Genome 2.0 Array. RNA-Sequencing was completed using the Illumina-Solexa platform for sequencing by synthesis. Short-insert paired end (SIPE) libraries were prepared from total RNA according to Illumina’s mRNA-Seq Sample Prep Protocol v2.0 (Illumina, San Diego, CA, USA). The resultant double-stranded cDNA concentration was measured on a NanoDrop spectrophotometer, and size and purity were determined on the 2100 Bioanalyzer using a DNA 1000 Nano kit. The cDNA libraries were cluster amplified on Illumina flowcells, sequenced on the GAII Sequencer as 36-cycle single-end reads, and processed using Illumina software v1.0. Illumina reads were aligned to the X. tropicalis genome using the algorithm for genomic mapping and alignment program (GMAP) and Alpheus® Sequence Variant Detection System v3.1.
Article: XB-ART-51592, PubMed
Source: NCBI GEO, Xenbase FTP
Samples: (DEG = Differentially Expressed Genes; GSM = GEO Sample Number)
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