Stress-induced and epigenetic-mediated maize transcriptome regulation study by means of transcriptome reannotation and differential expression analysis

Abstract

Plant’s response and adaptation to abiotic stresses involve sophisticated genetic and epigenetic regulatory systems. To obtain a global view of molecular response to osmotic stresses, including the non-coding portion of genome, we conducted a total leaf transcriptome analysis on maize plants subjected to prolonged drought and salt stresses. Stress application to both B73 wild type and the epiregulator mutant rpd1-1/rmr6 allowed dissection of the epigenetic component of stress response. Coupling total RNA-Seq and transcriptome re-assembly we annotated thousands of new maize transcripts, together with 13,387 lncRNAs that may play critical roles in regulating gene expression. Differential expression analysis revealed hundreds of genes modulated by long-term stress application, including also many lncRNAs and transposons specifically induced by stresses. The amplitude and dynamic of the stress-modulated gene sets are very different between B73 and rpd1-1/rmr6 mutant plants, as result of stress-like effect on genome regulation caused by the mutation itself, which activates many stress-related genes even in control condition. The analyzed extensive set of total RNA-Seq data, together with the improvement of the transcriptome and the identification of the non-coding portion of the transcriptome give a revealing insight into the genetic and epigenetic mechanism responsible for maize molecular response to abiotic stresses.

Epigenetic signatures of stress adaptation and flowering regulation in response to extended drought and recovery in Zea mays

“…Time course analysis during progressive dehydration indeed revealed that B73 plants start to perceive the stress after 4 days and then gradually decreased all physiological parameters, reaching a quasi‐complete stomatal closure at the 10 th day of treatment, while more than 4 days of recovery are necessary for a complete restoration of all the analyzed parameters. Plants were therefore regularly watered to pot capacity until the V5/V6 developmental stage, when dehydration treatment was applied: non‐stressed plants (NS) were grown at a water content of 75% available water capacity, replenishing the water lost by evapotranspiration every day, while drought‐stressed plants (WS) were watered replenishing only 60% of daily evapotranspiration to a minimum water content threshold of 25% of the available water capacity (Forestan et al, ; Morari et al, ). The treatment caused progressive shrivelling of WS plants starting from days 5–6 and well visible after 10 days of treatment (T0), when the youngest wrapped leaf (arrows in Figure A) was harvested from a subset of randomly selected plants.…”

“…Transcriptome analysis was performed reanalysing previously produced RNA‐Seq reads (Forestan et al, ), corresponding to control and stressed samples harvested at end of stress application (NST0 and WST0) and of the recovery period (NST7 and WST7). Total RNA extraction and processing, libraries preparation and sequencing on an Illumina Hiseq2000 platform, together with the bioinformatics analysis are therefore fully described in Forestan et al, .…”

“…Transcriptome analysis was performed reanalysing previously produced RNA-Seq reads , corresponding to control and stressed samples harvested at end of stress application (NST0 and WST0) and of the recovery period (NST7 and WST7). Total RNA extraction and processing, libraries preparation and sequencing on an Illumina Hiseq2000 platform, together with the bioinformatics analysis are therefore fully described in Forestan et al, 2016. In brief, the sequenced reads were pre-processed for adapter clipping using Cutadapt 1.2.1 (Martin, 2011) and then trimmed on low sequence quality bases and filtered from rRNA contaminant reads with ERNE-FILTER 1.2 (Del Fabbro, Scalabrin, Morgante, & Giorgi, 2013). High quality reads (Supplemental Data S1) were mapped against the maize B73 reference genome (RefGen ZmB73 Assembly AGPv4 and Zea_mays.AGPv4.34.gtf Gramene transcript annotation; Jiao et al, 2017) with Tophat 2.0.13 (Kim et al, 2013).…”

A systems genetics approach reveals environment-dependent associations between SNPs, protein co-expression and drought-related traits in maize

“…This region also contained the pQTL hotspot Hs52d. Both GRMZM2G111136 and GRMZM2G148772 were previously shown to be induced by drought in maize (Mao et al 2016; Forestan et al 2016). In addition, SBP genes constitute a functionally diverse family of transcription factors involved in plant growth and development (Preston and Hileman 2013).…”

“…One is a squamosa promoter-binding (SBP) gene (GRMZM2G111136) shown to be induced by various abiotic stresses including drought (Mao et al 2016). The other, a C2C2-CO-like transcription factor (GRMZM2G148772), was shown to be significantly induced by drought and salinity stress in B73 leaves (Forestan et al 2016). Hotspot Hs52d covered a region of ca 4 Mb in which we detected 26 pQTLs, many of which were located between the SBP gene and the C2C2-CO-like transcription factor (Figure 6B).…”