Transcriptome analysis in switchgrass discloses ecotype difference in photosynthetic efficiency.

BACKGROUND: Switchgrass, a warm-season perennial grass studied as a potential dedicated biofuel feedstock, is classified into two main taxa - lowland and upland ecotypes - that differ in morphology and habitat of adaptation. But there is limited information on their inherent molecular variations. RESULTS: Transcriptome analysis by RNA-sequencing (RNA-Seq) was conducted for lowland and upland ecotypes to document their gene expression variations. Mapping of transcriptome to the reference genome (Panicum virgatum v1.1) revealed that the lowland and upland ecotypes differ substantially in sets of genes transcribed as well as levels of expression. Differential gene expression analysis exhibited that transcripts related to photosynthesis efficiency and development and photosystem reaction center subunits were upregulated in lowlands compared to upland genotype. On the other hand, catalase isozymes, helix-loop-helix, late embryogenesis abundant group I, photosulfokinases, and S-adenosyl methionine synthase gene transcripts were upregulated in the upland compared to the lowlands. At ≥100x coverage and ≥5% minor allele frequency, a total of 25,894 and 16,979 single nucleotide polymorphism (SNP) markers were discovered for VS16 (upland ecotype) and K5 (lowland ecotype) against the reference genome. The allele combination of the SNPs revealed that the transition mutations are more prevalent than the transversion mutations. CONCLUSIONS: The gene ontology (GO) analysis of the transcriptome indicated lowland ecotype had significantly higher representation for cellular components associated with photosynthesis machinery controlling carbon fixation. In addition, using the transcriptome data, SNP markers were detected, which were distributed throughout the genome. The differentially expressed genes and SNP markers detected in this study would be useful resources for traits mapping and gene transfer across ecotypes in switchgrass breeding for increased biomass yield for biofuel conversion.

Transcriptome Profiling of Rust Resistance in Switchgrass Using RNA-Seq Analysis.

Switchgrass rust caused by Puccinia emaculata is a major limiting factor for switchgrass (Panicum virgatum L.) production, especially in monoculture. Natural populations of switchgrass displayed diverse reactions to P. emaculata when evaluated in an Ardmore, OK, field. To identify the differentially expressed genes during the rust infection process and the mechanisms of switchgrass rust resistance, transcriptome analysis using RNA-Seq was conducted in two pseudo-F1 parents ('PV281' and 'NFGA472'), and three moderately resistant and three susceptible progenies selected from a three-generation, four-founder switchgrass population (K5 × A4) × (AP13 × VS16). On average, 23.5 million reads per sample (leaf tissue was collected at 0, 24, and 60 h post-inoculation (hpi)) were obtained from paired-end (2 × 100 bp) sequencing on the Illumina HiSeq2000 platform. Mapping of the RNA-Seq reads to the switchgrass reference genome (AP13 ver. 1.1 assembly) constructed a total of 84,209 transcripts from 98,007 gene loci among all of the samples. Further analysis revealed that host defense-related genes, including the nucleotide binding site-leucine-rich repeat domain containing disease resistance gene analogs, play an important role in resistance to rust infection. Rust-induced gene (RIG) transcripts inherited across generations were identified. The rust-resistant gene transcripts can be a valuable resource for developing molecular markers for rust resistance. Furthermore, the rust-resistant genotypes and gene transcripts identified in this study can expedite rust-resistant cultivar development in switchgrass.