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Open Access Highly Accessed Research article

RNA-seq and microarray complement each other in transcriptome profiling

Sunitha Kogenaru, Qing Yan, Yinping Guo and Nian Wang*

Author Affiliations

Citrus Research and Education Center, Department of Microbiology and Cell Science, Institute of Food and Agricultural Sciences, University of Florida, 700 Experiment Station Road, Lake Alfred, 33850, USA

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BMC Genomics 2012, 13:629  doi:10.1186/1471-2164-13-629

Published: 15 November 2012

Additional files

Additional file 1:

The following excel format file contains the following 8 additional tables: Table S1: Summary of RNA-seq reads from wild-type and hrpX mutant strains of X. citri subsp. citri. Table S2: List of genes that are called by both RNA-seq and microarray. Table S3: List of genes that are uniquely called by RNA-seq and microarray. Table S4: List of statistically significant differentially expressed genes by RNA-seq and microarray filtered by cut-off thresholds. Table S5: List of randomly selected genes for the comparison with qRT-PCR from the statistically significant differentially expressed genes from RNA-seq and microarray. Table S6: Gene specific primers used in qRT-PCR experiment. Table S7: Summary of bioinformatics analysis of statistically significant differentially expressed genes to be part of Type III Secretion System (T3SS) and Type II Secretion System (T2SS) along with the occurrence of PIP box. Table S8: List of 90 transcriptional units from X. citri subsp. citri to which the 106 differentially regulated genes belong.

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Additional file 2:

Contains the following two additional figures, Figure FS1: Venn diagram summarizing genes called by both technologies, when comparison is carried out between the total currently annotated open reading frames (ORFs) available transcripts from the transcriptome of X. citri subsp. citri. Fold-change values are available from RNA-seq (4323) and microarray (4349). Gene’s called by both technologies are indicated by the overlap between the two circles. 4312 are found in consensus, while 11 and 37 are unique to RNA-seq and microarray respectively. Figure FS2: Venn diagram summarizing genes that are significantly differentially expressed determined by RNA-seq and microarray. Gene’s common to both methods are indicated by the overlap between the two circles.

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Additional file 3:

Figure FS3 - Comparison at the level of the functional annotations of the significantly differentially expressed genes from RNA-seq and microarray. GO term and KEGG pathway information enrichment analysis is shown for the genes from RNA-seq (left panel) and microarray (right panel). The overview of the analysis is shown in the form of pie chart for gene set from RNA-seq (A), and microarray (D). The histogram shows the number of genes associated with terms for the genes from RNA-seq (B) and microarray (E). Significantly enriched terms are indicated with ’*’. The terms that are functionally related are shown as a network with terms as nodes and relatedness is indicated with thickness of the edges that is based on their kappa score. The most significant term per group are shown for genes from RNA-seq (C) and microarray (F).

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Additional file 4:

Figure FS4 - Snapshot of the PIP box motif present in the cis-regulatory region of significantly differentially expressed genes is shown in the context of the whole genome of X. citri subsp. citri. The absolute position of each PIP box motif occurrence is shown on the whole genome map along with the −10 ‘TATA’ regions and the gene start site.

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