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Transcriptome sequencing of Eucalyptus camaldulensis seedlings subjected to water stress reveals functional single nucleotide polymorphisms and genes under selection.

Thumma BR, Sharma N, Southerton SG - BMC Genomics (2012)

Bottom Line: Of the 287 positively selected genes, ninety genes showed differential expression and 27 SNPs from 17 positively selected genes showed differential allelic expression between treatments.Correlation of allelic expression of several SNPs with total gene expression indicates that these variants may be the cis-acting variants or in linkage disequilibrium with such variants.Enrichment of apoptosis and cell death gene categories among the positively selected genes reveals the past selection pressures experienced by the populations used in this study.

View Article: PubMed Central - HTML - PubMed

Affiliation: CSIRO Plant Industry, Clunies Ross Street, Acton, ACT, Australia. reddy.thumma@csiro.au

ABSTRACT

Background: Water stress limits plant survival and production in many parts of the world. Identification of genes and alleles responding to water stress conditions is important in breeding plants better adapted to drought. Currently there are no studies examining the transcriptome wide gene and allelic expression patterns under water stress conditions. We used RNA sequencing (RNA-seq) to identify the candidate genes and alleles and to explore the evolutionary signatures of selection.

Results: We studied the effect of water stress on gene expression in Eucalyptus camaldulensis seedlings derived from three natural populations. We used reference-guided transcriptome mapping to study gene expression. Several genes showed differential expression between control and stress conditions. Gene ontology (GO) enrichment tests revealed up-regulation of 140 stress-related gene categories and down-regulation of 35 metabolic and cell wall organisation gene categories. More than 190,000 single nucleotide polymorphisms (SNPs) were detected and 2737 of these showed differential allelic expression. Allelic expression of 52% of these variants was correlated with differential gene expression. Signatures of selection patterns were studied by estimating the proportion of nonsynonymous to synonymous substitution rates (Ka/Ks). The average Ka/Ks ratio among the 13,719 genes was 0.39 indicating that most of the genes are under purifying selection. Among the positively selected genes (Ka/Ks > 1.5) apoptosis and cell death categories were enriched. Of the 287 positively selected genes, ninety genes showed differential expression and 27 SNPs from 17 positively selected genes showed differential allelic expression between treatments.

Conclusions: Correlation of allelic expression of several SNPs with total gene expression indicates that these variants may be the cis-acting variants or in linkage disequilibrium with such variants. Enrichment of apoptosis and cell death gene categories among the positively selected genes reveals the past selection pressures experienced by the populations used in this study.

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Heatmap showing differential expression of top 200 genes between control (C1) and stress (S1) treatments. Dark shades indicate higher expression and light shades indicate lower expression. Color key indicates the intensity associated with normalized expression values. Abbreviations as in Figure 2.
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Figure 3: Heatmap showing differential expression of top 200 genes between control (C1) and stress (S1) treatments. Dark shades indicate higher expression and light shades indicate lower expression. Color key indicates the intensity associated with normalized expression values. Abbreviations as in Figure 2.

Mentions: To identify genes responding to stress treatment, samples from control (C1) and stress (S1) treatments taken at the end of the stress treatment were analysed for differential gene expression. Analysis of differential gene expression revealed a total of 5270 transcripts (4320 unique genes based on E. grandis annotations) that were significantly (P ≤ 0.05; Bonferroni correction) differentially expressed between the control (C1) and stress (S1) treatments (Additional file 2). Read counts from the three libraries within each treatment are very similar (Table 2). A heatmap of gene expression of the top 200 genes is shown in Figure 3. Variance stabilized data obtained with DESeq pacckage was used to generate the heatmap. The gene expression patterns between the treatments are distinct while within each treatment they are similar. Gene identities of the most differentially expressed transcripts are shown in Table 3. Several heat shock proteins, cell wall genes such as expansins and drought stress related transcription factors (HB-12, RD26, ERF110) are among the most strongly differentially expressed genes.


Transcriptome sequencing of Eucalyptus camaldulensis seedlings subjected to water stress reveals functional single nucleotide polymorphisms and genes under selection.

Thumma BR, Sharma N, Southerton SG - BMC Genomics (2012)

Heatmap showing differential expression of top 200 genes between control (C1) and stress (S1) treatments. Dark shades indicate higher expression and light shades indicate lower expression. Color key indicates the intensity associated with normalized expression values. Abbreviations as in Figure 2.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472208&req=5

Figure 3: Heatmap showing differential expression of top 200 genes between control (C1) and stress (S1) treatments. Dark shades indicate higher expression and light shades indicate lower expression. Color key indicates the intensity associated with normalized expression values. Abbreviations as in Figure 2.
Mentions: To identify genes responding to stress treatment, samples from control (C1) and stress (S1) treatments taken at the end of the stress treatment were analysed for differential gene expression. Analysis of differential gene expression revealed a total of 5270 transcripts (4320 unique genes based on E. grandis annotations) that were significantly (P ≤ 0.05; Bonferroni correction) differentially expressed between the control (C1) and stress (S1) treatments (Additional file 2). Read counts from the three libraries within each treatment are very similar (Table 2). A heatmap of gene expression of the top 200 genes is shown in Figure 3. Variance stabilized data obtained with DESeq pacckage was used to generate the heatmap. The gene expression patterns between the treatments are distinct while within each treatment they are similar. Gene identities of the most differentially expressed transcripts are shown in Table 3. Several heat shock proteins, cell wall genes such as expansins and drought stress related transcription factors (HB-12, RD26, ERF110) are among the most strongly differentially expressed genes.

Bottom Line: Of the 287 positively selected genes, ninety genes showed differential expression and 27 SNPs from 17 positively selected genes showed differential allelic expression between treatments.Correlation of allelic expression of several SNPs with total gene expression indicates that these variants may be the cis-acting variants or in linkage disequilibrium with such variants.Enrichment of apoptosis and cell death gene categories among the positively selected genes reveals the past selection pressures experienced by the populations used in this study.

View Article: PubMed Central - HTML - PubMed

Affiliation: CSIRO Plant Industry, Clunies Ross Street, Acton, ACT, Australia. reddy.thumma@csiro.au

ABSTRACT

Background: Water stress limits plant survival and production in many parts of the world. Identification of genes and alleles responding to water stress conditions is important in breeding plants better adapted to drought. Currently there are no studies examining the transcriptome wide gene and allelic expression patterns under water stress conditions. We used RNA sequencing (RNA-seq) to identify the candidate genes and alleles and to explore the evolutionary signatures of selection.

Results: We studied the effect of water stress on gene expression in Eucalyptus camaldulensis seedlings derived from three natural populations. We used reference-guided transcriptome mapping to study gene expression. Several genes showed differential expression between control and stress conditions. Gene ontology (GO) enrichment tests revealed up-regulation of 140 stress-related gene categories and down-regulation of 35 metabolic and cell wall organisation gene categories. More than 190,000 single nucleotide polymorphisms (SNPs) were detected and 2737 of these showed differential allelic expression. Allelic expression of 52% of these variants was correlated with differential gene expression. Signatures of selection patterns were studied by estimating the proportion of nonsynonymous to synonymous substitution rates (Ka/Ks). The average Ka/Ks ratio among the 13,719 genes was 0.39 indicating that most of the genes are under purifying selection. Among the positively selected genes (Ka/Ks > 1.5) apoptosis and cell death categories were enriched. Of the 287 positively selected genes, ninety genes showed differential expression and 27 SNPs from 17 positively selected genes showed differential allelic expression between treatments.

Conclusions: Correlation of allelic expression of several SNPs with total gene expression indicates that these variants may be the cis-acting variants or in linkage disequilibrium with such variants. Enrichment of apoptosis and cell death gene categories among the positively selected genes reveals the past selection pressures experienced by the populations used in this study.

Show MeSH
Related in: MedlinePlus