DOI: 10.5061/dryad.xksn02vdv
title: Characterization and improvement of novel bioenergy grasses (Tripidium spp.)

description: Growing economies, limited fossil fuel reserves, and environmental
 concerns have justified expanded research on renewable energy sources,
 including bioenergy crops.  Taxa in the Poaceae Subtribe
 Saccharinae have gained attention as bioenergy crops based on their broad
 adaptability, pest resistance, and high biomass yields.
  Tripidium (syn. Erianthus, syn. Saccharum) is of particular
 interest due to perenniality, cold-hardiness, and high biomass yields.
  Tripidium ravennae is a cold-hardy, diploid species (2n = 2x =
 20).  Tripidium arundinaceum is a sub-tropical polyploid species
 (2n = 3x, 4x, 6x = 30, 40, 60) with high biomass yields. 
 Conventional breeding efforts focused on developing Tripidium as a
 competitive bioenergy feedstock for temperate climates.  Advanced
 interspecific hybrids between T. arundinaceum and T. ravennae were
 evaluated in field plots relative to Miscanthus ×giganteus over three
 years.  Collected data evaluated biomass yield, plant fertility,
 cytogenetics, and compositional analyses for lignocellulosic ethanol and
 forage utility.  Cytology and cytometry confirmed hybrids were
 tetraploid with 2n = 4x = 40 (2C genome size = 5.06 pg).  Dry
 biomass yields varied as a function of year and accession and increased
 each year, ranging 3.4 - 10.6, 8.6 - 37.3, and 23.7 - 60.6 Mg/ha for
 Tripidium hybrids compared to 2.3, 16.2, and 27.9 Mg/ha for M. ×giganteus
 in 2016, 2017, and 2018, respectively.  Variations in yield and
 compositional analyses contributed to variations in theoretical ethanol
 yields ranging from 10,181 to 27,546 L/ha for Tripidium accessions
 compared to 13,095 L/ha for M. ×giganteus.  These initial
 findings for Tripidium hybrids are promising and warrant further
 development of Tripidium as a temperate bioenergy feedstock. A robust
 understanding of the molecular mechanism of flowering in Tripidium will
 enable future biotechnology applications by harnessing floral and seed
 development.  Therefore, a differential gene expression (DGE)
 analysis was conducted to identify the differentially expressed genes
 (DEGs) associated with flower and seed development in T. ravennae.
  In the early phases of inflorescence development, the type II
 subfamily of MADS-box transcription factors were over-represented in both
 GO enrichment and differential expression analyses.  As
 developing inflorescences matured, there was increased expression of
 inflorescence determinacy regulators, as well as transcripts related to
 meiotic, and multicellular organism developmental processes.  In
 seed developmental samples, transcripts of multiple unigenes related to
 oxidative-reductive processes were identified.  These results
 provide insights into the molecular regulation of reproductive development
 of Tripidium and provide a foundational database for future investigations
 and analyses, including genome annotation, functional genomics
 characterization, gene family evolutionary studies, comparative genomics,
 and precision breeding. The ability to improve value-added traits of
 Tripididum hybrids via biotechnology would significantly enhance crop
 improvement opportunities.  The objective of this portion of the
 research was to develop an efficient regeneration and transformation
 procedure for genetic modification of Tripidium hybrids. 
 Multiple studies investigated the effects of various hormones, tissue
 culture media adjuncts, culture duration, Agrobacterium density, and
 hygromycin concentration on callus induction, maintenance, regeneration,
 and transformation efficiency.  Callus induction media containing
 10 - 40 µM 2,4-D with 12.5 mM L-proline generated callus that maximized
 the number of regenerated shoots (mean of 37 to 45
 shoots٠explant-1).  Callus maintenance media containing four µM
 2,4-D and 12.5 mM L-proline for durations less than 12 weeks resulted in
 callus that maximized shoot number (mean of 13 to 18 shoots٠explant-1)
 following regeneration.  Final experiments evaluating hygromycin
 concentration on selection efficiency and bacterial density on
 transformation efficiency are in progress. Collectively, these research
 projects served to 1) evaluate and characterize new Tripidium hybrids as
 potential bioenergy crops, 2) establish foundational transcriptomic
 resources on flowering and reproductive development of Tripidium, and 3)
 develop a regeneration and transformation system to enable future
 biotechnology applications in these crops.  These efforts will
 enable strategic advances in the development of Tripidium as a new
 bioenergy crop.
description: <strong>Plant
 material and sample collection</strong> Vegetative and inflorescence
 meristems were collected from three plants on the week of August 9th,
 2017, from the North Carolina Arboretum, Asheville, NC.  Inflorescence
 meristematic tissue from reproductive culms was collected at various
 heights from the ground representing a progression of floral development. 
 Inflorescences had emerged from more developed culms, but inflorescence
 meristems at earlier stages of development were apparent within the leaf
 sheath of less developed culms.  Floral development tissues were collected
 at the floret boot stage, pre-anthesis, and anthesis stages as well as
 mature stamens.  Spikelets containing immature and mature seeds were
 collected from the same plants in September and October of 2017,
 respectively.  Culm segments, inflorescences, and developing seed samples
 containing target tissues were collected and immediately placed in 15 or
 50 mL centrifuge tubes vials with 5 – 20 mL of RNAlater® Stabilization
 Solution (Ambion®, Life Technologies TM).  Centrifuge tubes containing
 sample tissue were frozen in the field on a bed of dry ice before
 transport to the laboratory and stored at -80ºC (Table 2.1).  Excess plant
 tissue was trimmed and removed or enriched under a stereomicroscope in
 sterile 100 mm Petri dishes containing approximately ~5-10 mL fresh
 RNAlater®.  Immature floret tissue samples (FT) were purified from bulk
 collected inflorescence tissue prior to emergence from the flag leaf
 sheath.  Pre-anthesis floret tissue samples (PAF) were purified from bulk
 collected inflorescence tissue that had emerged from the flag leaf
 sheath.  The observation of spikelet expansion and glume extrusion
 identified PAF samples, but no evidence of anther or stigma extrusion was
 observed.  Stamen tissue samples (ST) were purified from bulk collected
 floral spikelet tissues when anthers were exposed entirely outside of the
 glumes, and pollen was visibly dehiscing.  Samples of florets at anthesis
 (ANT) were purified from bulk collected floral spikelet tissues by
 amassing florets showing stigma protrusion from the lemma and palea of the
 floret.  Immature and mature seeds were processed by removing first and
 second order rachilla from the bulk collected tissue before tissue lysis
 and homogenization.  Sample tissue lysis and homogenization were processed
 in liquid nitrogen by mortar and pestle.  <strong>RNA
 isolation, library preparation, and
 sequencing</strong> Total RNA was extracted from all
 tissues using the Spectrum® Plant Total RNA Kit (Sigma-Aldrich, Burlington
 MA).  DNA was digested on-column with the Sigma-Aldrich DNase10 (DNASE10)
 kit per the manufacturer's instructions.  RNA concentration and
 integrity were quantitated with the QubitTM fluorimeter (Life
 TechnologiesTM) and the 2100 Bioanalyzer (Agilent) before library
 preparation, respectively.  RNA samples were poly-adenylation purified,
 and cDNA libraries prepared using the BiooScientific (a PerkinElmer Co.)
 NEXTFlex Rapid Directional RNA-Seq kit with a target insert size of
 200-300 bp.  Libraries were sequenced using the Illumina HiSeq 4000, 150bp
 PE by Novogene (Sacramento, CA).  The RNA of all samples were mixed and
 used to construct Pacific Biosciences Iso-Seq libraries (Protocol #
 101-070-200 version 6) with three size fractions (no size selected,
 &lt; 4 kb, and &gt; 4 kb). The libraries were sequenced with four
 cells of a PacBio Sequel I system at NC State Genomic Sciences
 Laboratory. <strong>Transcriptome assembly and functional annotation</strong> Read quality was inspected for quality with FastQC (hyperlink).  Trimming was conducted with CLC Genomics WB (CLC – GWB, V11.0.1, QIAGEN) to remove adapter sequences and low-quality reads (Q &lt; 20).  Multiple <em>de novo</em> transcriptome assemblies were constructed with the CLC – GWB using different <em>k-mer</em> (word size) and bubble size of <em>de Bruijn</em> graph combinations and assessed for the number of contigs, contiguity, and N50.  The assembly with the lowest number of contigs but the largest N50 was selected. The final assembly was mapped (GMAP, V2015-07-23) to a draft genome assembly of <em>T. ravennae </em>(Maren et al., Unpub.) as well as multiple reference genomic assemblies within the Andropogoneae tribe, including <em>Sorghum bicolor</em>, <em>Saccharum officinarum</em>, and <em>Zea mays</em>.  The GMAP mapping was carried out to enrich the transcriptome for plant transcripts and eliminate the transcripts of sample surface contaminants.  Contigs with a 95% identity and match score to two or more reference genomes were retained.  The transcriptome was analyzed for redundancy and cluster enriched with CD-HIT software with 95% identity to make a nonredundant set.  Error corrected Iso-Seq transcripts derived from the SAM file using the CUPCAKE package (https://github.com/Magdoll/cDNA_Cupcake).  Non-redundant <em>de novo</em> assembled transcripts were concatenated with the collapsed Iso-seq set and reanalyzed for redundancy and cluster enriched with CD-HIT software with 95% identity to make a nonredundant set.  Functional annotation was carried out on a local server using BLASTx and the nr (NCBI non-redundant protein 12/2018 version) database.  Searches were limited to the first 20 significant results with an E-cutoff value of 1.0E-6.  Unitigs were functionally annotated utilizing default annotation rules in the BLAST2GO package.  The unitigs and their BLASTX results were imported into the BLAST2GO package for functional gene annotation.  Gene ontology (GO) term and functional annotation assignments followed InterPro scan, using the European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI) database, KEGG pathway analysis, Rfam annotation, and GO mapping based characterizations online on the BLAST2GO package. <strong>Differentially expressed gene (DEG) and gene ontology (GO) enrichment analysis</strong> Quality trimmed and filtered reads from all samples were mapped to the final cluster enriched transcriptome assembly with default parameters in the CLC – GWB.  Statistical tests for the determination of differential gene expression utilize an exact test-like generalized linear model (GLM) similar to that performed in DESeq and EdgeR.  In developing inflorescences, the test of differential expression utilized non-flowering controls for comparison. The statistical tests for differential expression in developing floral spikelets utilized two or more pair-wise comparisons between developing inflorescences and the sample query (e.g., FT, PAF, ST, ANT).  Two or more pair-wise statistical tests between inflorescence controls, floral samples, and developing seeds comprise DEG calls.  Genes of interest were filtered from differentially expressed genes table in CLC-GWB using a threshold p ≤ 0.05 and a two-fold threshold change.  <strong>Gene expression analysis by RT-qPCR</strong> Bioinformatically derived differential expression statistics of inflorescence, floret, and seed development were screened for novel and putative genes in reproductive development to validate the sample set with RT-qPCR.  GO enrichment by Fisher's exact test (FDR p ≤ 0.05; BLAST2GO) aided in selecting sequences from the test set for over-representation (Supplementary Table S2, S3, & S4).  Unigenes were filtered for significant differential expression (FDR p ≤ 0.05) within the subset of relevant inflorescence samples.  Final transcript selections were made on the unique mapping (GMAP; V2015-07-23) of the transcript to the reference genome assembly with concomitant support for gene architecture from the PacBio Iso-Seq data set.  Primers were designed for each gene to maximize coverage for gene structures, which uniquely identified the isoform of interest.  Multiple internal controls were selected from the RNA-seq data set by filtering the expression data set for unigenes with a minimum expression value of 200 transcripts per million (TPM), a mean value of less than 2000 TPM, and having a CV less than 0.35.  Relative gene expression analysis was used in the evaluation of PCR data in the determination of gene expression values and calculated following the 2-∆∆Ct method. Wu TD, Watanabe CK: GMAP: a genomic mapping and alignment program for mRNA and EST sequences. Bioinformatics 2005, 21(9):1859-1875. Garsmeur O, Droc G, Antonise R, Grimwood J, Potier B, Aitken K, Jenkins J, Martin G, Charron C, Hervouet C et al: A mosaic monoploid reference sequence for the highly complex genome of sugarcane. Nat Commun 2018, 9(1):2638. Schnable PS, Ware D, Fulton RS, Stein JC, Wei F, Pasternak S, Liang C, Zhang J, Fulton L, Graves TA et al: The B73 maize genome: complexity, diversity, and dynamics. Science 2009, 326(5956):1112-1115. Li W, Godzik A: Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 2006, 22(13):1658-1659. Fu LM, Niu BF, Zhu ZW, Wu ST, Li WZ: CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 2012, 28(23):3150-3152. Conesa A, Gotz S: Blast2GO: A comprehensive suite for functional analysis in plant genomics. Int J Plant Genomics 2008, 2008:619832. Kanehisa M, Goto S: KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research 2000, 28(1):27-30. Nawrocki EP, Burge SW, Bateman A, Daub J, Eberhardt RY, Eddy SR, Floden EW, Gardner PP, Jones TA, Tate J et al: Rfam 12.0: updates to the RNA families database. Nucleic Acids Res 2015, 43(Database issue):D130-137. Gotz S, Garcia-Gomez JM, Terol J, Williams TD, Nagaraj SH, Nueda MJ, Robles M, Talon M, Dopazo J, Conesa A: High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Research 2008, 36(10):3420-3435. Robinson MD, McCarthy DJ, Smyth GK: edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26(1):139-140. Robinson MD, Smyth GK: Small-sample estimation of negative binomial dispersion, with applications to SAGE data. Biostatistics 2008, 9(2):321-332. Cheng Y, Bian W, Pang X, Yu J, Ahammed GJ, Zhou G, Wang R, Ruan M, Li Z, Ye Q et al: Genome-Wide Identification and Evaluation of Reference Genes for Quantitative RT-PCR Analysis during Tomato Fruit Development. Front Plant Sci 2017, 8:1440. Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001, 25(4):402-408. <strong>Preparation of plasmids and Agrobacterium. </strong> A copy of the GUSPlusTM was obtained from the Gateway-compatible vector 6B described in Mann et al. (2012) and cloned into pCR8/GW/TOPO per the manufacturer's instructions (Invitrogen).  The GUSPlusTM gene was recombined using the Gateway® LR Clonase® II enzyme mix (Invitrogen) into the destination 6A overexpression cassette described by Mann et al. (2012).  Resulting vectors were transformed into DH5α by standard heat shock methods and selected on kanamycin containing LB media.  Transformation competent Agrobacterium preparations followed the freeze-thaw method with strain EHA105 containing pTok47 (Hofgen and Willmitzer, 1988; Jin et al., 1987; Lu et al., 2008).  Single colony selections were placed in 1.5 mL microcentrifuge tubes containing one mL of YEP and an additional 50 mg • L-1 kanamycin to grow overnight at 28 ºC.  The following day, one mL starter cultures were added to flasks containing 100 mL of YEP and 50 mg • L-1 kanamycin.  Forty-five ml of YEP medium and 200 µM acetosyringone (final concentration) was added to the overnight cultures, and growth continued until a colony density of OD600 ~ 0.8 was reached.  Mann, D.G.J., P.R. Lafayette, L.L. Abercrombie, Z.R. King, M. Mazarei, M.C. Halter, C.R. Poovaiah, H. Baxter, H. Shen, R.A. Dixon, W.A. Parrott, and C. Neal Stewart Jr. 2012. Gateway-compatible vectors for high-throughput gene functional analysis in switchgrass (Panicum virgatum L.) and other monocot species. Plant Biotech. J. 10:226-236. doi: 10.1111/j.1467-7652.2011.00658.x. Hofgen, R. and L. Willmitzer. 1988. Storage of competent cells for Agrobacterium transformation. Nucleic Acids Research 16:9877-9877. doi: 10.1093/nar/16.20.9877. Jin, S.G., T. Komari, M.P. Gordon, and E.W. Nester. 1987. Genes responsible for the supervirulence phenotype of Agrobacterium tumefaciens a281. J. Bact. 169:4417-4425. doi: 10.1128/jb.169.10.4417-4425.1987. Lu, J., E. Sivamani, K. Azhakanandam, P. Samadder, X. Li, and R. Qu. 2008. Gene expression enhancement mediated by the 5' UTR intron of the rice rubi3 gene varied remarkably among tissues in transgenic rice plants. Mol. Genet. Genomics 279:563-572. doi: 10.1007/s00438-008-0333-6.