title: Infection and genotype remodel the entire soybean transcriptome.
abstract: BACKGROUND
  High 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.
  
  
  RESULTS
  With 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.
  
  
  CONCLUSIONS
  Our 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.
authors.affiliation: Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. lzhou@vbi.vt.edu
authors.forename: Lecong
authors.initials: L
authors.lastname: Zhou
authors.forename: Santiago X
authors.initials: SX
authors.lastname: Mideros
authors.forename: Lei
authors.initials: L
authors.lastname: Bao
authors.forename: Regina
authors.initials: R
authors.lastname: Hanlon
authors.forename: Felipe D
authors.initials: FD
authors.lastname: Arredondo
authors.forename: Sucheta
authors.initials: S
authors.lastname: Tripathy
authors.forename: Konstantinos
authors.initials: K
authors.lastname: Krampis
authors.forename: Adam
authors.initials: A
authors.lastname: Jerauld
authors.forename: Clive
authors.initials: C
authors.lastname: Evans
authors.forename: Steven K
authors.initials: SK
authors.lastname: St Martin
authors.forename: M A Saghai
authors.initials: MA
authors.lastname: Maroof
authors.forename: Ina
authors.initials: I
authors.lastname: Hoeschele
authors.forename: Anne E
authors.initials: AE
authors.lastname: Dorrance
authors.forename: Brett M
authors.initials: BM
authors.lastname: Tyler
mesh_terms: D020869:Gene Expression Profiling; D018506:Gene Expression Regulation, Plant; D017343:Genes, Plant; D018745:Genome, Plant; D005838:Genotype; D054884:Host-Pathogen Interactions; D016014:Linear Models; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D010838:Phytophthora / Q000472:pathogenicity*; D010935:Plant Diseases / Q000235:genetics; D018749:RNA, Plant / Q000235:genetics; D012680:Sensitivity and Specificity; D013025:Glycine max / Q000235:genetics* / Q000378:metabolism / Q000382:microbiology
chemical_list: D018749:RNA, Plant