Peer Review #1 of "Meta-analysis of transcriptomic responses to biotic and abiotic stress in tomato (v0.1)"

Abstract

A wide range of biotic and abiotic stresses adversely affects plant growth and productivity worldwide. The study of individual genes cannot consider as an effective approach for the understanding of tolerance mechanisms since these stresses frequently, often in combination and a large number of genes involved in these mechanisms. The availability of high-throughput genomic data has enabled the discovery of the role of transcription factors in regulatory networks. A meta-analysis of biotic and abiotic stress responses was performed by analyzing a total of 391 microarray samples from 23 different experiments and 2336 differentially expressed genes involved in multiple stresses were identified. We identified 1862 genes differentially regulated in response to biotic stresses was much greater than that regulated by abiotic stresses, 835 genes, and found 15.4% or 361 differentially expressed genes with the conserved expression between abiotic and biotic stresses. The greatest percent of genes related to the cellular process (>76% genes), metabolic process (>76% genes) and response to stimulus (>50%). About 4.2% of genes involved in biotic and abiotic stress responses belonged to the transcription factor families. We identified several genes, which encode transcription factors that play an important role in abiotic and biotic stress responses. These proteins included JERF1, SlGRAS6, MYB48, SlERF4, EIL2, protein LHY, SlERF1, WRKY 26, bZIP transcription factor, ICE1-like, pti6, EIL3 and WRKY 11. Six of these proteins, JERF1, MYB48, protein LHY, EIL3, EIL2 and SlGRAS6 play central roles in these mechanisms. This research promoted a new approach to clarify the expression profiles of various genes under different conditions in plants, detected common genes from differentially regulated in response to these conditions and introduced them as candidate genes for improving plant tolerance through genetic engineering approach.