SND1 is a higher order activator expressed in xylem cells that activates the biosynthesis of cellulose, matrix polysaccharides, and lignin (Zhong et al. 2006). Repression of SND1 leads to abnormal Arabidopsis plants lacking vascular and interfascicular fibers; whereas, overexpression lines display ectopic expression of genes involved in secondary wall biosynthesis. Zhao et al. (2010) also found that SND1 directly regulates the expression of F5H, one of the key enzymes in lignin biosynthesis. The genes encoding MYB46, MYB83, MYB103, MYB32, SND3 and KNAT7 possess the Secondary wall NAC Binding Element (SNBE) cis-element and appear to also be direct targets of SND1 (Zhong et al. 2007; Zhong et al. 2011; Zhong et al. 2012).

Other NAC transcription factors, including NST1/2, VND6, and VND7, also play a key role in regulation of secondary cell wall synthesis. They all positively regulate similar downstream targets compared with SND1, including MYB46, MYB83, MYB103, MYB58, and SND3 (Zhong et al. 2010). NST1 and NST2 are involved in regulating secondary wall thickening in anther walls as well as stems (Mitsuda et al. 2007). NST2 especially is strongly expressed in anther tissue. VND6 and VND7 act as a key regulator of xylem differentiation. Overexpression of the VNDs prompts the differentiation of non-vascular tissues into treachery elements (Kubo et al. 2005). VND6 physically binds to the Trachery Element Regulating cis-Element (TERE), which is possessed by a number of genes involved in tissue-specific trachery cell wall biosynthesis and programmed cell death. VND7 is negatively regulated by VNI2 (VND-INTERACTING2 NAC PROTEIN2), which is another recently characterized NAC domain transcription factor (Yamaguchi et al. 2010). The secondary wall regulatory network that functions in xylem differentiation also includes ASL19 (ASSYMETRIC LEAVES2-LIKE19) and ASL20. Expression of these proteins is activated by VND6 and VND7 and also forms a positive feedback loop in turn up-regulating expression of the VND genes (Soyano et al. 2008).

MYB46 and MYB83, which are controlled by NACs, act as positive regulators of secondary cell wall synthesis (Zhong et al. 2012). Among the transcription factors downstream of these MYB proteinss, MYB52, MYB54, MYB58, and MYB63, are important for secondary cell wall synthesis. Promoter deletion coupled with transactivation analysis revealed the Secondary wall MYB Responsive Element (SMRE), a cis-element that is enriched in the promoters of known targets of MYB46 and MYB83. In a further regulatory layer, MYB58 and MYB63, controlled by both NACs and MYB46/83, are implicated in regulating lignin biosynthesis. These proteins target AC-rich elements, which are enriched in the promoters of at least some lignin biosynthesis genes (Lois et al. 1989; Zhong et al. 2012).

More recently a handful of transcriptional regulators in protein families other than NAC and MYB R2R3 have also been determined to have central roles in regulating secondary wall biosynthesis. For example, Wang et al. found that WRKY12 appears to function as a high level negative regulator of secondary cell wall biosynthesis in stems. Medicago and Arabidopsis wrky12 mutants have thickened cell walls in stem pith cells and increased biomass with abnormal deposition of lignin, xylan, and cellulose (Wang et al. 2010). Another example is KNAT7 which is a KNOX-type homeodomain transcription factor that also negatively regulates cell wall thickening and lignin biosynthesis (Li et al. 2011). Loss-of-function knat7 mutants exhibit increased cell wall synthesis gene expression. Besides SND1, MYB75 physically interacts with KNAT7 to restrain cell wall biosynthesis (Bhargava et al. 2010).

A number of secondary wall regulators in grasses have been characterized via heterologous expression in Arabidopsis, but very few have been examined in situ. Heterologous overexpression of ZmMYB31 and ZmMYB42 in Arabidopsis leads to reduced lignin content (Fornale et al.

2010) . Arabidopsis lines that overexpress ZmMYB42 exhibit reduced plant stature, leaf size, tertiary venation, and S-unit lignin content. ZmMYB31 directly interacts with an element similar to the AC-element present in the ZmCOMT promoter (Sonbol et al. 2009). The orthologs of the Arabidopsis SWNs and MYB46 from rice and maize are able to activate secondary wall biosynthesis in Arabidopsis (Zhong et al. 2011). Consistent with conservation of regulatory mechanisms, the promoters of OsMYB46 and ZmMYB46 contain SNBE cis-elements and the rice and maize SWNs directly bind these elements to activate gene expression (Zhong et al. 2011). Another example is expression of an AP2 transcription factor from Arabidopsis, AtSHN2, which in rice significantly enhances cellulose content while reducing lignin content and resulting in improved saccharification yields (Ambavaram et al. 2011). Promoter analysis and binding assays suggest that AtSHN2 may repress expression of the rice orthologs of SND1, NST1/2 and VND6, and activate expression of MYB20 and MYB43.

Dixon and colleagues recently reported that the switchgrass protein, PvMYB4A, an ortholog to the Arabidopsis MYB4 and the maize MYB31 proteins, acts as a repressor of lignin biosynthesis in switchgrass (Shen et al. 2012). Overexpression of PvMYB4 in switchgrass reduced the total lignin content and the amount of cell wall ester-linked p-coumarate. The efficiency of sugar release from transgenic biomass was increased by almost 3-fold. An element similar to the AC-element found in dicots is also the probable binding site of PvMYB4. This discovery demonstrates that manipulating transcription factors that control enzymes that function in cell wall biosynthesis is a good alternative way to reduce the recalcitrance of switchgrass and improve lignocellulosic biomass. Still, the differences in cell wall content between grasses and dicots might be consistent with some divergence in the factors that regulate cell walls. Certainly, given the high ploidy level of switchgrass (4n, 6n, or 8n) and its outcrossing nature, heterozygosity that could have functional consequences has evolved. For example, five distinct, but closely related PvMYB4 sequences were identified from a single switchgrass genotype (Shen et al. 2012; Shen personal communication).

Independent of the possibility of grass-diverged mechanisms of regulation, the continual flow of new publications about cell wall regulators suggests that all factors, and certainly the interactions among them, have yet to be uncovered. Due to space constraints we are not able to elaborate on posttranscriptional and posttranslational regulatory mechanisms in cell wall synthesis, the study of which is still in its infancy (Humphrey et al. 2007; Wolf et al. 2012).

Apart from linkage analysis and QTL mapping, association mapping is another commonly used tool for genetic analysis of genetic factors for quantitative characteristics. In contrast to QTL analysis, which has been typically derived from a bi-parentally crossed population, association mapping takes advantage of the fact that historic recombination within a population which has decreased linkage disequilibrium (LD) to short chromosomal intervals, enabling potentially statistically strong and robust marker-trait associations to be detected. It offers three advantages over QTL analysis: 1) much higher mapping resolution; 2) greater allele number and broader reference population; and 3) less research time in establishing an association (Yu and Buckler 2006). However, two major drawbacks exist in association mapping. First, false positive associations between markers and traits can be obtained due to the presence of population structure. Population structure can be assessed with marker information from genome-wide genetic markers (such as SSRs), and then association tests can be conditioned on the population structure to reduce the false positive rate (Pritchard et al. 2000). Second, a higher density of markers is needed to identify linked QTL because LD spans over shorter distances in the genome, compared to linkage-based QTL mapping analyses. Loci that are more closely located on a chromosome (or that have a low level of recombination between them) will be more likely to be in LD than loci located further apart. The genetic distance over which LD is present along a chromosome depends on the population history: populations that have undergone many rounds of recombination will show less LD than populations that have had little recombination (Yu and Buckler 2006).

In the first attempt of association mapping study in plants, DNA sequence polymorphisms within the D8 locus were associated with flowering time (Thornsberry et al. 2001). Later it has also been used to associate candidate gene Y1 with maize endosperm color (Palaisa et al. 2004). In forage crops, association mapping successfully identified flowering time genes in natural populations of perennial ryegrass (Skot et al. 2005). Several SSR markers were found related to yield and quality in an elite alfalfa breeding population by associated mapping (Li et al. 2011). In Switchgrass, a project about association mapping of cell wall synthesis regulatory genes and cell wall quality is in progress (http://www. switchgrassgenomics. org//research. shtml). Although the complexity of the switchgrass genome (polyploidy, repeat-sequence rich, and highly heterozygous) poses significant challenges to the application of association mapping, ongoing genome sequencing projects will ultimately allow for a thorough genome­wide examination of nucleotide polymorphism-trait association. Two association mapping collections were assembled. One is an upland collection created by E. Buckler, M. Casler and colleagues (Casler et al. 2011). The other one is a southern collection of most lowland genotypes and some upland genotypes made by M. Saha, E. C. Brummer and colleagues at the Noble Foundation (Personal communication 2012). M. Saha and collaborators have also established a switchgrass nested association mapping (NAM) population, which was selected for funding by DOE in 2012 (http:// genomicscience. energy. gov/research/DOEUSDA/2012awards. shtml). It is expected a large amount of information will be available from these projects for associations among economically important traits and DNA markers in the near future.

As a biomass and biofuel plant, switchgrass is also considered a potential crop for production of biodegradable plastics as a value-added co-product, which can "reduce petroleum consumption and decrease plastic waste disposal issues" (Somleva et al. 2008). In such an attempt, Metabolix, Inc. introduced bacterial genes into switchgrass to produce such a plastic, polyhydroxybutyrate (PHB) (Somleva et al. 2008). The enzymes encoded by the three transgenes for PHB synthesis were targeted to plastids to enhance PHB yield as previously demonstrated. Transgenic plants containing up to 3.7% dry weight of PHB in leaf tissues and 1.2% dry weight PHB in whole tillers were obtained. The PHB granules were accumulated in chloroplasts of the leaves. Most of the transgenic plants grew normally although affected growth was also observed. Transgenes and PHB production were inherited to offspring plants through both male and female gametes. Although the yield of PHB in these transgenic plants did not meet the 7.5% dry weight threshold estimated by Metabolix to be necessary for profitable commercialization, the authors believe it is the first step towards achieving the goal. It also demonstrated the amenability to introduce multiple genes to alter metabolic pathways in this important biofuel crop.

Current studies suggest that it is feasible to generate low-lignin switchgrass, improve biomass yield, and add value to this biofuel crop. Field tests on these various transgenic plants are needed to support the claims that the low lignin content, normal or increased biomass yield, and other improved traits of the transgenic lines still hold in various field conditions.

Esterification. The carboxylic acids and aldehydes of the bio-oil can be converted into esters by removing oxygen in the form of H2O. The reaction takes place at temperatures of 50-80°C in presence of acid catalysts. Alcohols such as methanol and ethanol, obtained from fermentation of cellulosic materials, are used for the esterification process. The esterification process drastically reduces the aging rate of bio-oil. Methanol was found to reduce the aging rate by a factor of 20 (Diebold and Czernik 1997). The esterification reactions can be represented by the following equations (Bulushev and Ross 2011).

RjCOOH + R-OH^R1COOR + H2O (3)

R1CHO + 2R-OH^R1CH(OR)2 + H2O (4)

Where R and R1 are alkyl groups.

Aqueous Reforming. Recently Dumesic and others have proposed aqueous reforming techniques to selectively produce alkane products, with reduced or no need of external hydrogen. The process takes place through aldol condensation and hydrogenation of carbohydrate-derived compounds, to make large water soluble intermediates which are then converted into alkanes (Barrett et al. 2006; Chheda and Dumesic 2007; West et al. 2008).

Steam Reforming. Reforming of the bio-oil using steam produces H2-rich syngas which can be used as a source of hydrogen for hydrogenation reactions in bio-oil upgrading and conversions.

The genetic variation among ecotypes makes switchgrass challenging to model. The environmental and developmental cues that effect green up, leaf area development, and flowering time need to be well understood for each ecotype. Despite numerous field studies with many of these genetic lines at different locations, isolating the relationship between temperature, drought, and nutrient stress on green up, biomass accumulation, flowering time is difficult. This is because of variation in site-specific factors such as current management, previous management, soil type, and microclimate.

There have been two approaches taken to model biomass production of different ecotypes or groups of ecotypes. The ALMANAC model was used to simulate biomass of four groups of ecotypes (northern lowland, northern upland, southern lowland, and southern upland) at five locations (Kiniry et al. 2008). The model was parameterized with a different maximum leaf area index (LAI) for each ecotype based on how well adapted it was to the location’s climate and environmental conditions. Growing degree days also varied among groups of ecotypes. The maximum potential LAI was assumed to be larger in southern regions and largest for southern lowland ecotypes. Modeled versus measured yields at these locations show that the ALMANAC model did reasonably well at predicting yield all four types at the locations (Table 2). The model had its greatest errors when estimating biomass of the northern lowland type in KS and NE. Yields for the southern upland type were slightly overestimated at each location.

The DAYCENT model has also been used to simulate different switchgrass ecotypes; in this case two lowland ecotypes, Alamo and Kanlow, and four upland ecotypes, Blackwell, Cave-in-Rock, Sunburst, and Trailblazer (Lee et al. 2011). Simulations were validated for four locations in Central Valley of CA. It was assumed that each cultivar had the same

Field trial data from Casler et al. (2004). Table reproduced from Kiniry et al. (2008).

maximum LAI. Instead, the root to shoot ratio, baseline temperature, optimum temperature, and maximum temperature were adjusted for each cultivar. The upland types (Blackwell, Cave-in-Rock, Sunburst, Trailblazer) were assumed to allocate more primary production to root biomass than the lowland (Alamo and Kanlow) types. The lowland ecotypes were also assumed to have a higher optimum and maximum temperature. The DAYCENT model also did a reasonable job estimating the observed yields with the R2 of the one-to-one relationship between observed and measured ranging from 0.66 to 0.90.

Modeling Water Use Efficiency

Water use efficiency (WUE) can be vitally important for predicting which areas are suitable for switchgrass biofuel production. To avoid competition with farmland already used for food, fiber, and feed production, the areas most likely for switchgrass production are on less productive soils where soil, water and nutrients often limit production (Perlack et al. 2005). In dryland production systems, limited rainfall and/or limited capacity of soils to store moisture becomes an important issue for switchgrass production. Plant water use becomes a major concern in irrigated regions, where competition between agriculture and other water demands arise. Direct measurements of WUE are important but require labor-intensive procedures involving soil water measurement with neutron access tubes, gravimetric measurements of soil moisture from soil cores, or use of weighing lysimeters. Likewise, measurements of WUE require plant harvesting to determine dry weight of plants. To adequately define WUE for a range of soils, plant species, and climatic conditions will require considerable resources and time.

Mowing. Mowing for weed control in forages is generally not very effective (Miller and Strizke 1995) because it is non-selective and may occur too late to reduce competition between weeds and the seedlings. Mitchell et al. (2010a) recommended mowing just above the switchgrass canopy (typically 20 to 30 cm) near the 4th of July to reduce the leaf area of both grassy and broadleaf weeds in newly-seeded switchgrass stands. Mowing can reduce competition for light, and can prevent weeds from going to seed and contributing to the soil seed bank. It is sometimes the only option to suppress grassy weeds, especially when trying to establish switchgrass where herbicides are not effective.

Mob grazing. Mob-grazing is stocking a high density of animals in an area for a short duration (up to 1 wk). It reduces selective grazing by livestock, and thus, can be effective in the control of grass weeds and allowing sunlight to the new seedlings (Miller and Strizke 1995). However, grazing must be delayed until seedling roots are well established or the seedlings can be uprooted. Often, as with mowing, the efficacy of mob-grazing is only moderate, because it is applied too late to have maximum benefit in reducing weed competition for moisture, sunlight, and nutrients, and damage to the soil from foot traffic may be significant. Further, unpalatable weeds might not be grazed and the seedling forage may be preferred to weed species.

Cultivation (Tillage). The main use of cultivation in switchgrass has been for seedbed preparation to remove all vegetation prior to planting to help ensure good seed to soil contact. It is important to consider that tillage can bring dormant weed seeds to the surface, so it is often best plant into a stale seedbed after tillage. Under certain unique circumstances, tillage could be used post-planting to non-selectively control weeds between rows of switchgrass planted on wide row spacings.

Companion Crops. Companion crops are planted along with switchgrass to provide protection from wind and water erosion. Hintz et al. (1998) also reported companion crops could reduce weed competition during switchgrass establishment. For example, they reported that corn planted in perpendicular orientation at reduced seeding rates of 24,700 to 49,400 seeds ha1 on either 76 or 114 cm spacing did not reduce switchgrass establishment. They concluded that atrazine reduced weed emergence early season while the corn shaded the weeds during late season. It is important to illustrate that in this study, they planted following soybeans, and although grass weeds (foxtail) were present, they were not detrimental to the switchgrass in the control plots. Companion crops generally are not recommended except in extreme environments and conditions; cover crops may be best used when terminated prior to shading of the switchgrass seedlings. In Oklahoma, cowpea (Vigna unguiculata L. Walp) and forage sorghum (Sorghum bicolor (L.) Moench.) planted in perpendicular or alternating drill row orientations were too competitive with switchgrass seedlings and complete stand failure occurred when these crops were harvested at the end of season (T. J. Butler, unpublished data). Cowpea could be a viable cover crop if planted with an alternating row pattern, since it can be removed with 2,4-D amine once it begins to shade the switchgrass seedlings (Fig. 3). This alternating row pattern can be accomplished with drill containing two seed boxes, one for each species, and plugging every other hole of each drill box. However, care should be taken to ensure each planter unit is calibrated at the appropriate depth for each species.

Both bacterial and fungal endophyte-plant interactions involve modifications of plant gene expression and overall plant physiology/biochemistry to beneficially impact growth and stress tolerance. While monitoring specific gene expression during beneficial endophyte-sugarcane interactions, Arencibia et al. (2006) identified 47 differentially expressed sequence tags (EST) using cDNA-AFLP analysis. The transcripts showed significant genetic homologies to major signaling pathways such as the ethylene signaling pathway. For example, PYK10 encodes for a root — and hypocotyl-specific P-glucosidase/myrosinase and is important during the endophyte P. indica and Arabidopsis beneficial bio-control against herbivores and pathogens (Sherameti et al. 2008). NoxA was found to be crucial in regulating hyphal morphogenesis and growth in the mutualistic symbiotic interaction between the fungal endophyte Epicho festucae and perennial ryegrass (Tanaka et al. 2008). Functional genomics research will help scientists understand and elucidate mechanisms under which beneficial microorganisms promote host plant growth and enhance stress tolerance. Currently we are carrying out studies of mechanisms of plant growth promotion by bacterial endophytes using the responsive switchgrass cultivar Alamo and non-responsive cultivar Cave-in-Rock to Burkholderia phytofirmans strain PsJN (Kim et al.

2012) . Comparative global gene expression profiling is being conducted using both cultivars following B. phytofirmans strain PsJN inoculation with DOE-funded switchgrass EST microarray chips by Genomics Core Facility in the Noble Foundation. Approximately 35,200 switchgrass ID probes were identified to show significant differences between switchgrass cultivars Alamo and Cave-In-Rock after B. phytofirmans strain PsJN inoculation. Using the rice genome as a model for the analysis of the data along with the MapMan (Usadel et al. 2005) and the PageMap (Usadel et al. 2006) software, we are currently analyzing this large data set. Results showed that in Alamo almost 2000 genes were unique up-regulated at 0.5 day. On the other hand, in Cave-in-Rock, the number of unique up-regulated genes for 0.5 day was only 901. The significant changes are found in transcription factor genes, plant hormone and cell wall metabolism (unpublished data).

Bacterial and Fungal endophytes exhibit a diverse range of growth promoting mechanisms. In many cases, endophytes, primarily bacteria, possess multiple mechanisms of action and differentially express these traits at different stages of plant growth and development. Under stress conditions, endophytes help the host plant survive and flourish, as in the case of ACC deaminase activity and bio-control compound production. Under normal conditions, endophytes help fix atmospheric di-nitrogen and produce plant hormones to help the plant grow to its maximum potential.

Together, under both stress and normal conditions, endophytes ensure its host plant thrives, and its nutrient rich environment is maintained.

To optimize improvements to deconstruction due to overexpression of lignocellulolytic enzymes in planta, researchers have sought to increase the percent of plant total soluble protein (TSP) that the enzymes represent and to decrease detrimental plant phenotypes caused by enzyme accumulation. In many studies, hydrolase levels remain relatively low (1-5% TSP) as do the % increases in saccharification. Figure 7 summarizes strategies being used to improve in planta expression of GHs. These include organelle targeting, codon optimization, promoter enhancement, and transient expression. Some of these methods as well as other approaches to regulate hydrolase activity, such as use of inteins, are also being tested for their ability to mitigate plant dwarfism or other physical defects that can accompany in planta GH expression.

Organelle targeting is a key factor in optimal accumulation of cell wall degrading enzymes in plants. Most previous studies have examined accumulation of enzymes in the apoplast, cytosol, and vacuole (Sticklen 2006; Taylor et al. 2008; Sainz 2009). Targeting the transgene to incorporate into the chloroplast genome has also been shown to induce accumulation of large amounts of foreign proteins (Oey et al. 2009). For example, a collection of GHs and related proteins from T. reesei expressed in the chloroplast had higher activity and pH and temperature stability compared with the same proteins expressed in E. coli (Verma et al. 2010). A crude cocktail derived from lines expressing each enzyme released up to ~3500% more glucose from biomass compared with a commercial enzyme cocktail, though it is not clear that the study was conducted with the same amount of protein in both samples (Verma et al. 2010). Another study showed that with chloroplast targeting, tobacco could accumulate four cell wall degrading enzymes at levels up to 40% TSP (Petersen et al. 2011). However, if selected for homoplasty, meaning all chloroplasts were transformed, this resulted

Figure 7. Strategies for improving glycosyl hydrolase expression in plants to enhance the quality of biomass for biochemical production of biofuels.

in pigment-deficient mutants unable to grow autotrophically. Even if heteroplastic, transformant had to be grown on a sucrose-rich medium. This is in contrast to the 70% TSP achieved without any severe phenotype when the tobacco expressed a protein antibiotic (Oey et al. 2009). The authors suggest that the chloroplastic GHs might sequester intermediates needed in plant metabolism. Based on these results, chloroplast transformation harbors the following promises: a significantly better biological enzyme factory than bacteria; an environment suitable for high accumulation of enzymes versus the apoplast, vacuole, cytosol, etc.; and a setting amendable for producing plants that could express a multitude of cell wall degrading enzymes. However, further strategies are needed to combat deleterious growth effects.

Codon optimization is a simple way to enhance heterologous expression levels. All organisms and DNA-containing organelles contain particular preferences for codon usage. Foreign genes may not adhere to these preferences and likely due to depletion of rare tRNAs these codons may diminish expression. Arabidopsis expressing codon optimized

D. thermophilum XynA and XynB resulted in a TSP of 14% and 3%, respectively, and a 14% improvement in xylose release compared with the wild-type plant (Borkhardt et al. 2010). The codon optimized expression of XynA and XynB in the apoplast allowed for significantly higher accumulation of these enzymes than what was seen in earlier un-optimized examinations with similar xylanases from S. olivaceoviridis (Yang et al. 2007).

Increasing promoter activity is another key target to improving TSP levels of heterologous GHs. The ideal promoters are those with strong location specific and/or inducible activity (Taylor et al. 2008). For instance, accumulation of 5.8% TSP was obtained by driving the gene encoding a thermostable fi-glucosidase, BglB from Thermotoga mamma, under the control of the rbcS-1A promoter and with targeting to the chloroplast (Jung et al. 2010). This is a light-regulated promoter that controls the transcription of Ribulose-1,5-bisphosphate carboxylase oxygenase small subunit. In another study, a TSP of 6.1% for the E1 cellulase under the control of the synthetic Mac promoter was achieved for apoplast targeting in rice (Chou et al. 2011). This was higher than the 4.9% TSP obtained in another study using the Cauliflower Mosaic Virus 35S promoter (Oraby et al. 2007).

Besides enhancing expression of heterologous hydrolases, other challenges associated with GH expression are developmental defects including stunted growth, severe pigment deficiency, enhanced disease susceptibility, poor seeds, and poor growth (Dai et al. 1999; Skjot et al. 2002; Harholt et al. 2010; Gray et al. 2011). Common strategies to avoid these deleterious effects are conceptually similar to those used to enhance expression and include selectively targeting hydrolase expression to storage organelles, use of inducible or developmentally regulated promoters, as well as employing thermophilic enzymes with low activity at ambient temperatures, as mentioned previously (Taylor et al. 2008; Jung et al. 2012). Inteins are another effective means to regulate in planta GH activity. An intein is a protein that can catalyze its own removal from and the subsequent rejoining of two flanking protein segments, i. e., the exteins (Sharma et al.

2006) . Inteins have been engineered to be activated by a variety of different external stimuli, including pH, temperature, and small molecules, providing good potential for use as a means to control activity of celluolytic enzymes in plants (Skretas et al. 2005; Sharma et al. 2006). Recently, a thermo-regulated intein was used to control the activity of a thermostable xylanase, XynB from Dictyoglomus thermophilum, expressed in maize (Shen et al. 2012). Without the intein the xylanase greatly reduced the plant seed mass and fertility, but these deleterious phenotypes were largely restored by the insertion of the intein. Xylanase activity was retained after the temperature was elevated to induce intein excision. Biomass from the xylanase-intien expressing plants released approximately 45% more sugar than that from the unmodified plants (Shen et al. 2012). Future directions might be to express a cocktail of hydrolases without any significant effects on phenotype.

Dayong Li,[13]‘[14] Man Zhou,2 Zhigang Li2 and Hong Luo2’*

Introduction

With the rapid development of genomics and bioinformatics, recent studies have suggested that the number of protein-coding genes is similar in many model eukaryotes whose whole genome sequences have been obtained and analyzed in detail (Matera et al. 2007; Ponting et al. 2009). Genome-wide transcriptional analyses have identified large numbers of non-coding RNAs (ncRNAs) in humans, animals and plants (Hirsch et al. 2006; Ravasi et al. 2006; The ENCODE Project Consortium 2007; Guttman et al. 2009; Amor et al. 2009; Jouannet et al. 2011). Based on their length, ncRNAs can be arbitrarily divided into small ncRNAs, intermediate-size ncRNAs and long ncRNAs (Amor et al. 2009; Jouannet et al. 2011; Liu et al. 2013). To date, the best characterized of all the ncRNAs has been small RNAs (sRNAs). Endogenous small RNAs are about 19-30 nucleotides (nt) RNA molecules that modulate

gene expression at the transcriptional and/or posttranscriptional levels and play key roles in many developmental and physiological processes in eukaryotic organisms (Zamore and Haley 2005; Bonnet et al. 2006; Zhang et al. 2006; Ramachandran and Chen 2008; Poethig 2009).

In plants, sRNAs can mainly be classified into small interfering RNAs (siRNAs) and microRNAs (miRNAs) based on their precursor structures and biogenesis processes (Vazquez 2006; Vaucheret 2006; Sunkar and Zhu 2007; Ramachandran and Chen 2008; Jin and Zhu 2010; Vazquez et al. 2010). The siRNAs are derived from double stranded RNA precursors and can be divided into heterochromatic siRNAs (hc-siRNAs), trans-acting siRNAs (ta-siRNAs), long siRNAs (lsiRNAs), natural antisense transcripts-derived siRNAs (nat-siRNAs), and others (Bonnet et al. 2006; Zhang et al. 2012). The miRNAs are distinguished from the siRNAs since they are derived from the processing of longer primary miRNA transcripts, which fold into hairpin-like stem-loop structures (Bartel 2009; Chen 2009; Chuck et al. 2009; Poethig 2009; Voinnet 2009; Zhu et al. 2009).

Switchgrass (Panicum virgatum L.) is a warm-season perennial grass and has been recognized as a dedicated cellulosic biofuel crop because of its broad adaptation to marginal lands and high biomass production (Vogel 2004; McLaughlin and Kszos 2005; Bouton 2007; Li and Qu 2011; Mann et al. 2012). Although switchgrass has attracted great attention, little is known about its many aspects on basic biology, including ncRNAs. In this chapter, we will provide an overview of the miRNAs in this biofuel plant species and discuss their potential applications in switchgrass genetic improvement.

One of the biggest advantages of thermochemical conversion technologies is that these can produce many fuels and chemicals—many of which can supplement the demand currently met by petroleum industry. Fuels include hydrocarbons such as gasoline, diesel, jet, charcoal, alcohols and fuel additives. Recently, hydrocarbon fuels and higher alcohols have become preferred forms of biofuels because these are more compatible with petroleum infrastructure and have higher energy density than ethanol. Several demonstrations for hydrocarbon production through thermochemical conversion processes are currently underway (Regalbuto 2009). Chemicals include hydrogen, ammonia-based fertilizer, alcohols such as methanol, ethanol and butanol, acetone, activated carbon, fine chemicals, lubricants, food additives and resins (Balat et al. 2009a, b; Brown et al. 2012). Electrical power can be produced using intermediates, i. e., syngas and bio-oil using internal combustion engines such as reciprocating engines and gas turbines, steam-based external combustion engine, or fuels cells such as solid oxide fuel cells (SOFC). Heat production can be done in conjunction with electrical power production or separately through direct combustion.