Summary: Plant secondary cell walls constitute the majority of plant biomass and are an important source of biomaterials. Secondary cell walls are particularly prominent in xylem cells present in the vascular tissue. Although the process of vascularization has been extensively studied in the dicot Arabidopsis thaliana, remarkably little is known about these processes in grass species despite their emerging importance as biomass feedstocks. The targeted biofuel crop Sorghum bicolor has a sequenced and well-annotated genome, making it an ideal monocot model for addressing vascularization and biomass deposition. Here we generated tissue-specific transcriptome data using laser capture microdissection in the developing vascular and non-vascular tissues of the sorghum root. Many sorghum genes with enriched expression in developing vasculature were orthologous to genes previously associated with vascular development in other species. However, a number of transcription factor families, including NAC domain, MYB and ARF varied in their complement of vascular expressed genes to a considerable degree in sorghum compared to Arabidopsis and/or maize. Differential expression of genes associated with DNA methylation and chromatin modification were identified between vascular and non-vascular cell types, implying that changes in DNA methylation may be a feature of sorghum root vascularization. To profile DNA methylation in these tissues, sodium bisulfite sequencing of laser capture microdissected tissue was performed. DNA methylation was enriched in genic regions of genes demonstrating higher expression in non-vascular tissues. Methylation in genic and intergenic regions varied by tissue type and gene expression level. Furthermore, genes involved in cell elongation showed differences in methylation levels concomitant with expression between non-vascular and vascular tissue types suggesting a novel mode by which root growth in distinct tissues may be modulated. Our results provide both a genetic and epigenetic framework for studying vascularization and secondary cell wall development in sorghum.
Overall Design: Eight samples of paired-end reads were analyzed across four tissue types, four samples for RNASeq and four for bisulfite sequencing of Sorghum bicolor (L.) Moench (BTx623) 3 day old seedlings. Whole root, whole shoot, vascular and nonvascular samples were analyzed with three replicates per tissue type for both RNASeq and bisulfite sequencing.
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Growth Protocol: | For all experiments carried out in this manuscript, Sorghum bicolor (L.) Moench (BTx623) seeds were separated into three biological replicates prior to germination under sterile conditions at ( 28C for N/NV LCM) while maintained in a 16/8 light/dark cycle for 3 days. |
Treatment Protocol: | No treatment |
Extract Protocol: | For whole root and whole shoot transcriptomes RNA was isolated using TRIzol reagent (Life Technologies) according to the manufacturer's instructions followed by DNase treatment using RQ1 enzyme (Promega).For RNA extraction (Vascular and Nonvascular) a RNAqueous-Micro Kit (Ambion) was used. |
Library Construction Protocol: | LCM RNA-seq libraries were prepared by removing rRNA from 10-50ng of total RNA using Ribo-Zero™ rRNA Removal Kit (Epicentre). |
Molecule Type: | rRNA- RNA |
Library Source: | |
Library Layout: | PAIRED |
Library Strand: | Forward |
Platform: | ILLUMINA |
Instrument Model: | NextSeq 500 |
Strand-Specific: | Specific |
Data Resource | GEN Sample ID | GEN Dataset ID | Project ID | BioProject ID | Sample ID | Sample Name | BioSample ID | Sample Accession | Experiment Accession | Release Date | Submission Date | Update Date | Species | Race | Ethnicity | Age | Age Unit | Gender | Source Name | Tissue | Cell Type | Cell Subtype | Cell Line | Disease | Disease State | Development Stage | Mutation | Phenotype | Case Detail | Control Detail | Growth Protocol | Treatment Protocol | Extract Protocol | Library Construction Protocol | Molecule Type | Library Layout | Strand-Specific | Library Strand | Spike-In | Strategy | Platform | Instrument Model | Cell Number | Reads Number | Gbases | AvgSpotLen1 | AvgSpotLen2 | Uniq Mapping Rate | Multiple Mapping Rate | Coverage Rate |
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