Abstract
BackgroundHigh throughput methods, such as high density oligonucleotide microarray measurements of mRNA levels, are popular and critical to genome scale analysis and systems biology. However understanding the results of these analyses and in particular understanding the very wide range of levels of transcriptional changes observed is still a significant challenge. Many researchers still use an arbitrary cut off such as two-fold in order to identify changes that may be biologically significant. We have used a very large-scale microarray experiment involving 72 biological replicates to analyze the response of soybean plants to infection by the pathogen Phytophthora sojae and to analyze transcriptional modulation as a result of genotypic variation.ResultsWith the unprecedented level of statistical sensitivity provided by the high degree of replication, we show unambiguously that almost the entire plant genome (97 to 99% of all detectable genes) undergoes transcriptional modulation in response to infection and genetic variation. The majority of the transcriptional differences are less than two-fold in magnitude. We show that low amplitude modulation of gene expression (less than two-fold changes) is highly statistically significant and consistent across biological replicates, even for modulations of less than 20%. Our results are consistent through two different normalization methods and two different statistical analysis procedures.ConclusionOur findings demonstrate that the entire plant genome undergoes transcriptional modulation in response to infection and genetic variation. The pervasive low-magnitude remodeling of the transcriptome may be an integral component of physiological adaptation in soybean, and in all eukaryotes.
Highlights
High throughput methods, such as high density oligonucleotide microarray measurements of mRNA levels, are popular and critical to genome scale analysis and systems biology
How many genes are truly involved in the response of organism to a challenge such as pathogen infection, and what are the roles of those genes? Global assays of gene expression, for example by microarray analysis, are typically conducted to test the hypothesis that a small, defined set of genes are responsible for an organism's response to some challenge
Linear Mixed-Model Analysis (LMMA) indicated that 89% of the detectable genes were significantly affected by infection in both the upper and lower infection courts, even when using the most conservative False Discovery Rate (FDR) method (BH-FDR) at a level of 0.0001 (Table 1)
Summary
High throughput methods, such as high density oligonucleotide microarray measurements of mRNA levels, are popular and critical to genome scale analysis and systems biology. We have used a very large-scale microarray experiment involving 72 biological replicates to analyze the response of soybean plants to infection by the pathogen Phytophthora sojae and to analyze transcriptional modulation as a result of genotypic variation. Global assays of gene expression, for example by microarray analysis, are typically conducted to test the hypothesis that a small, defined set of genes are responsible for an organism's response to some challenge. A major challenge in evaluating the importance of low magnitude transcriptional changes is that the level of replication used in a typical microarray experiment is insufficient to detect small changes given the technical and biological variability in the system. High-density oligonucleotide arrays such as Affymetrix GeneChips can detect up to 90% of all the mRNAs in a transcriptome [3,4,5]. 26,500 of the soybean genes (70%) on the Affymetrix GeneChip could be detected in soybean cyst nematode (SCN)-colonized root pieces[4]
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