It is well established that switchgrass has a base chromosome number of x= nine (Gould 1975). Diploid (2n=2x=18) was reported once by Nielsen (1944), but not confirmed for its existence in recent extensive investigations (Riley and Vogel 1982; Hopkins et al. 1996; Hultquist et al. 1996; Lu et al. 1998; Costich et al. 2010). Tetraploid (2n=4x=36) is the sole ploidy level in lowland ecotype and also one of the two major ploidy levels (2n=4x=36 and 2n=8x=72) in upland ecotype (Church 1940; Nielsen 1944; McMillan and Weiler 1959; Porter 1966; Riley and Vogel 1982; Hopkins et al. 1996; Hultquist et al. 1996; Lu et al. 1998; Costich et al. 2010). Hexaploid

(2n=6x=54) was reported for upland plants in several studies, but not confirmed in the recent extensive investigation by Costich et al. (2010). This may be interpreted by Martinez-Reyna and Vogel (2002) reporting a post-fertilization incompatibility system that exists in crosses of tetraploid

by octoploid in preventing the production of hexaploid progeny. Octoploid occurs at a higher frequency than tetraploid in upland plants (Church 1940; Nielsen 1944; McMillan and Weiler 1959; Porter 1966; Riley and Vogel 1982; Hopkins et al. 1996; Hultquist et al. 1996; Lu et al. 1998; Costich et al. 2010). Higher ploidy levels (2n=10x=90 and 2n=12x=108) was only reported in an early study (Nielsen 1944), but not confirmed in recent studies (Riley and Vogel 1982; Hopkins et al. 1996; Hultquist et al. 1996; Lu et al. 1998; Costich et al. 2010). Using flow cytometry, chromosome counting and florescent in situ hybridization, Costich et al. (2010) reported extensive aneuploidy chromosome numbers in both upland and lowland switchgrass. They reported observations of aneuploidy at 86% of octoploid chromosome counts, but only 23% for tetraploid counts, suggesting a less stable genome in the octoploid upland switchgrass.

Homologous chromosome pairing and segregation behavior provide critical information with respect to sexual reproduction, chromosome homology and species evolution, and breeding procedures. Chromosome pairing in meiosis of tetraploid plants in both lowland and upland types is regular (Barnett and Carver 1967; Brunken and Estes 1975; Lu et al. 1998). Various studies all reported consistent bivalent pairing in tetraploid switchgrass plants. Martinez-Reyna et al. (2001) reported that chromosome pairing of hybrids between lowland and upland tetraploid parents was primarily bivalent. The regularity of tetraploid chromosomes in meiosis was substantiated by high vigor of pollen grains and good set of seeds (Barnett and Carver 1967; Martinez-Reyna et al. 2001). One important result of Martinez-Reyna et al. (2001) revealed that the genomes of tetraploid upland and tetraploid lowland are highly similar. More recently, two independent groups reported nuclear genome inheritance of lowland tetraploid is disomic (Okada et al. 2010b; Liu and Wu 2012; Liu et al. 2012). Using a population of 279 first-generation selfed progeny of a lowland tetraploid plant genotyped by 12 simple sequence repeat markers, Liu and Wu (2012) demonstrated segregation of the polymorphic codominant markers was consistent with a typical diploid "1:2:1" Mendelian segregation ratio (Fig. 4). More recently experimental results revealed that tetraploid switchgrass is an allotetraploid containing two distinct ("A" and "B") genomes (Young et al. 2010; Liu et al. 2012; Triplett et al. 2012).

Working with octoploids and its aneuploids, and a hexaploid, Barnett and Carver (1967) observed more univalents than with tetraploids. Trivalents and quadrivalents occur at a low number of cells in octoploids and its aneuploids, but were not observed in tetraploid cells (Barnett and Carver 1967). They observed much higher frequencies of abnormal pollen grains in octoploids and aneuploids than in tetraploids and a hexaploid. More studies indicated homologous chromosome pairing of octoploids is primarily of bivalent associations although univalent and multivalents

also occurred at a lower rate (Brunken and Estes 1975; Lu et al. 1998). The prevalence of bivalent associations in meioses of octoploid switchgrass may suggest that some mechanism(s) have evolved to insure the pairing behavior if octoploids are autopolyploid (Lu et al. 1998). Inheritance of octoploid is not known yet.

In addition to the pairing behavior and inheritance information of chromosomes in switchgrass, the mode of inheritance of chloroplast DNA in tetraploids was determined. Using upland x lowland reciprocal hybrids and their DNA samples hybridized with a special chloroplast DNA probe, Martinez-Reyna et al. (2001) indicated the maternal inheritance of chloroplast DNA in tetraploid switchgrass, which is consistent with those of most angiosperm species.

The normal functioning of miRNAs is a prerequisite for plant development. The loss of function of the key genes involved in miRNA biogenesis would cause significant mutant phenotypes in plant growth and development (Jacobsen et al. 1999; Lu et al. 2000; Park et al. 2002; Vaucheret et al. 2004). For example, the loss of function of DCL1, an important gene directly involved in the processing of pri-miRNAs and pre-miRNAs, would impact the maturation of miRNAs causing multiple deficiencies in plant development, such as abnormal leaf shape, delayed flowering and early embryo arrest (Reinhart et al. 2002; Dugas and Bartel 2004; Liu et al. 2005; Nodine and Bartel 2010). The mutants of other miRNA biogenesis-related genes including hyl1, hen1, and hst, all showed developmental deficiencies (Han et al. 2004; Park et al. 2005). These data demonstrated that miRNAs are largely involved in regulating plant development and play vital roles.

In recent years, the impacts of miRNAs on plant development have been extensively studied, especially in the model specie Arabidopsis thaliana. For example, Palatnik et al. (2003) found that miR319/JAW could target some members of TCP family, affecting leaf shape formation. Overexpression of miR319 led to down regulation of several TCP targets, resulting in uneven leaf shape and curvature, cotyledon epinasty, a modest delay in flowering and crinkled fruits phenotypes (Palatnik et al. 2003). Similarly, our study in creeping bentgrass (Agrostis stolonifera) also demonstrated that over expression of a rice miR319 gene causes pleiotropic phenotypes in transgenic plants including increased leaf expansion and stem diameter, which are associated with down regulation of at least four putative target TCP genes (Zhou et al. 2013). MiR165/166 targets some members of Class III HD — Zip and KANADI families, of which PHABULOSA (PHB), PHAVOLUTA (PHV), REVOLUTA (REV), KAN1, KAN2, and KAN3 play important roles in regulating leaf and flower development and vascular polarity (Chen 2005). miR172 regulats floral organ identity, reproductive development through regulating its targets APETALA2 (AP2) and AP2-like genes, such as TOE1, TOE2 and TOE3 (Chen 2004, Zhu et al. 2009).

John H. Fike, h* Twain J. Butler[3] [4] and Rob Mitchell[5]

Introduction

An intimate association with grasses has been important to human evolution (Cerling et al. 2011) and a key part of the subsequent rise of civilizations. Grasses historically have been a primary contributor to the human food supply—both directly, namely as sources of grains, and indirectly, as forages for livestock and wildlife. Grasses also have served an important and historical role in human transportation in as much they were the primary "fuel" for horses and the other beasts of burden used to move people and goods. This role changed substantially with the discovery of fossil fuels and the development of internal combustion engines.

There is, however, some promise that humanity will reengage with grasses as a source of fuels. As we look "back to the future" (Vogel 1996)—to avoid crises related to over-exploited fossil resources and the consequences of their combustion—grasses are reemerging as alternative sources of clean, renewable fuels. While grasses alone can by no means replace the more than 27,000 Exajoule (>26,000 trillion Btu) of fossil energy currently consumed in the US transportation sector (USEIA 2011), they can play an

important role in reducing our reliance on fossil energy sources and perhaps buy humanity some time in the search for more abundant sources of clean, renewable energy (Parrish and Fike 2005).

Among the many grasses and other crops explored for biomass — to-bioenergy systems, switchgrass has garnered some of the greatest attention for its potential as a biofuel feedstock. High productivity, broad adaptability and nativity to North America have all been important factors in the choice of switchgrass as a model energy crop. There have been important challenges associated with growing switchgrass, however, and in the remaining sections of the chapter, we will discuss the agronomic considerations and potential associated with its use as a bioenergy crop.

A focus on endophyte and mycorrhizal enhancement of switchgrass growth and stress tolerance, as well as other plants, requires the establishment of a stable plant-microbe interaction. Hence, the initial microbial infection and subsequent colonization of the plant is requisite for the eventual beneficial impact of the microbe on plant performance. While the focus of this chapter is on switchgrass, little work has been carried out to describe microbial infection and colonization processes with switchgrass systems. Therefore, literature relating to the mechanisms of infection and colonization of other plant species forms the bulk of this section, with the assumption that similar mechanisms are operational during switchgrass-beneficial microbe interactions.

Endophytic microbes and mycorrhizal fungi can inhabit various parts of the plant, such as the root, stem and leaves, and can also be found in flowers, fruits and seeds (Zakria et al. 2008; Rodriguez et al. 2009; Compant et al. 2011; Kim et al. 2012). However, most efforts have focused on microbes located within the soil compartment, and more specifically the beneficial bacteria living in this region and their interactions with the root system of the plant. As we explore the steps associated with bacterial infection and colonization, it is worth noting that many studies have followed these processes through the use of readily visible tags in the bacteria of interest, such as GFP (Compant et al. 2008; Prieto and Mercado-Blanco 2008; Kim et al. 2012; Weyens et al. 2012). However, care must be taken when using such tagged microbes, as it has been shown that GFP-tagging can modify the natural behavior of the microbe (Weyens et al. 2012).

Differences also exist between dicot and grass cell walls in the thicker, secondary cell walls that accumulate upon growth cessation. Secondary walls are especially abundant in three polymers—cellulose, xylan, and the phenylpropanoid-derived polymer, lignin. As explained above, the xylan of grasses is modified by arabinose, which is nearly lacking in dicot xylan (Scheller et al. 2010). Instead, dicot xylan is modified by glucuronic acid, which is less frequent in grass xylan (Fig. 2). As in primary walls, arabinose residues of xylan in grass secondary walls are acylated with ferulic acid and p-coumaric acid. Indeed, the presence of ether bonds between feruloyl esters from glucuronoarabinoxylan and lignin suggests that feruloylated arabinose could act as a nucleation site for lignin formation in grasses (Bunzel et al. 2004). Dicot xylan has a 5-sugar oligosaccharide at the reducing end; however, this sequence has not been identified in grasses, despite concerted efforts (Scheller et al. 2010) (Fig. 2).

Due to its abundance and high energy content, lignin represents an attractive byproduct of biochemical biofuel production for conversion to electricity, thermochemical biofuels, or higher value chemicals. Lignin is deposited in interstices of the cell wall during secondary development (Terashima et al. 2004). Xylem and schlerenchyma cells are particularly rich in lignin, but in switchgrass internodes closer to the plant base, all cell walls stain for lignin (Shen et al. 2009). The working model for lignin polymerization is that monomers are released into the wall where they are enzymatically oxidized to form radical ions that form covalent bonds with each other and other nearby alcohols (Boerjan et al. 2003). Grass lignin varies from the lignin of dicot walls in that it includes significant amounts of p-hydroxyphenyl (H) subunits in addition to the typical guaiacyl (G) subunits and syringyl (S) subunits also present in dicot walls (Fig. 3) (Vogel 2008). Each of the lignin subunits has a different number of potential bonding sites, with four, three, or one bond observed, respectively, in model studies (Fig. 3) (Boerjan et al. 2003). Thus, higher amounts of H and G lignin have the potential to lead to a more branched lignin structure. Nonetheless, the amount of H lignin in switchgrass stems, for example, has been found to be low, with typical ratios of 0.1:1.0:0.8 (H:G:S) in mature stems (Shen et al.

2009) . Lignin is the major polymer that blocks digestion of cell walls, with the lignin of grasses being no exception. Switchgrass stem lignin content is inversely correlated with digestibility (Shen et al. 2009).

A further distinguishing characteristic of grass cell walls is that grass monolignols are acylated by p-coumaric acid at the alcohol at the end of the propanoid "carbon tail" (Fig. 3) (Ralph 2010). Bioechemical analysis

suggests that the function of these modifications may be to indirectly enhance lignin polymerization (Ralph 2010). Though p-coumaric acid is readily oxidized to its radical, bonds with p-coumaroyl pendant groups have not been observed in planta (Ralph et al. 1994). Rather, p-coumaroyl esters may act as "radical catalysts", rapidly passing the radical to sinapyl alcohols, potentially facilitating lignin polymerization (Takahama et al. 1994; Ralph 2010). In switchgrass stems, approximately 20% of monomers are esterified to a hydroxycinnamate residue (Yan et al. 2010).

Generally speaking, young tissues that are richer in primary walls have long been recognized as being easier to digest than more mature tissues. This trend has also been observed for switchgrass stem tissues (Shen et al. 2009). Indeed, overexpression of a microRNA that represses the juvenile to mature transition, miRNA156 or Cg1, fixes the resulting switchgrass in a juvenile state and increases saccharification yields (Chuck et al. 2011). Somewhat unexpectedly, the most dramatic change in weakly overexpressing Cg1 switchgrass is a 250% increase in starch, which is made of valuable glucose residues, resulting in an overall increase in sugar yield in the presence of starch degrading enzymes of ~200% (Chuck et al. 2011). Thus, the improved sugar yields with young tissues may not be only a consequence of changes in cell wall quality, but of other physiological properties. The absence of simple correlation between lignin content and recalcitrance is also demonstrated by the fact that leaf material is more recalcitrant than stems, despite lower amounts of lignin in leaves versus stems (Fu et al. 2011).

Biomass Content Variation with Environment and Genotype

In addition to varying across development and among organs, switchgrass biomass content varies with environmental conditions and natural, selected, and engineered genetic variation. Genetic engineering to improve cell wall quality is extensively discussed below in the context of what is known about grass cell wall synthesis and regulation. This section briefly analyzes observations of other factors that influence cell wall quality. With the implementation of modern genetic methods, the authors predict that these observations may soon be moved toward understanding and harnessing molecular mechanisms.

Studies aimed at describing environmental effects on switchgrass biomass quality are few. Schmer and colleagues recently reported the year-to-year and site-to-site variability observed for their well-studied, large-scale switchgrass experiment in the Northern Great Plains (Schmer et al. 2012). In that experiment with ten upland switchgrass fields scattered in eastern North Dakota, South Dakota and Nebraska, significant variation existed among plots and among harvest years for theoretical ethanol yield in liters per megagram (L per Mg) (Schmer et al. 2012), as determined by near infrared spectroscopic analysis (Vogel et al. 2010). Note that this calculation of theoretical yield is based only on cell wall content, not structure. The year-to-year differences were as much as 20%, with theoretical ethanol yields being especially low in the establishment year in some fields, though more typically they varied by less than 10%. Though genetic differences among stands cannot be ruled out, theoretical yields per unit mass were lower in more northerly fields compared to more southerly fields, which is another possible indication of environmental influences, such as temperature, on cell wall content at maturity. Similarly, lower sugar extractability for switchgrass grown at higher latitudes was also observed in another less extensive study, though in that case the ecotypes were also different (Kim et al. 2011). Schmer and associates (2012) observed that drought increased biomass xylose content, which typically decreased ethanol yields. On the other hand, within-field variation among subsamples taken in a single year was typically only 2 to 3%, suggesting that biomass content is not particularly sensitive to the soil and moisture variability that might occur within a single field (Schmer et al. 2012). From a biofuel production perspective, this suggests that within field bail-to-bail variation in switchgrass biomass content is not expected to be large.

Compared to characterizing environmental variability, relatively more work has been done to measure the influence of genetic variation, i. e., cultivar-to-cultivar or genotype-to-genotype variation, on switchgrass cell wall quality. Molecular analysis has found that most switchgrass cultivars are relatively poorly defined genetically, with more variability observed within a particular cultivar than among cultivars (Cortese et al.

2010) . Similarly, several studies have also observed little difference among cultivars in terms of biomass quality when grown side-by-side. Out of eight cultivars grown in a randomized trial in Alabama, differences in biomass quality were observed for lowland vs. upland ecotypes, but not for most parameters within each ecotype (Sladden et al. 1991). In that study, lowland types showed both higher lignin and cellulose compared with the uplands. Similarly, in a study of small plots of 20 switchgrass genotypes grown in Iowa, researchers observed few statistically significant differences in biomass content among cultivars over three growing season (Lemus et al. 2002). The lowland cultivars, Alamo and Kanlow, had ~12% less lignin and ~14% less ash compared with the other, mostly upland cultivars in the trial (Lemus et al. 2002). Cellulose did not vary significantly among cultivars, but, as with other studies, significant biomass quality variation was observed in all cultivars depending on the year and harvest date. Another small — scale trial of lowland cultivars in Georgia revealed no major differences in internode cell wall content or structure (Yan et al. 2010). Finally, in the large-scale experiment by Schmer et al. (2012), though biomass glucose and xylose content differed significantly among the three upland cultivars grown in three sites in Nebraska, differences in theoretical ethanol yield per Mg among the cultivars only appeared at one site. An absence of differences among cultivars is not surprising given the genetic variability of switchgrass that might lead to apparent homogenization in populations of traits with potential fitness effects, such as those related to cell wall function.

However because cell wall content is genetically determined, recurrent selection for switchgrass genotypes with divergent digestibility has been successful. In particular, Vogel, Sarath and colleagues at the University of Nebraska have developed and characterized upland switchgrass populations with decreased and increased digestibility relative to the parental population (Hopkins et al. 1993). The realized heritability coefficient for digestibility was 0.31 (Hopkins et al. 1993). In general, plants bread for high digestibility exhibit lower lignin content and vice versa (Sarath et al. 2008). Low-lignin plants appear to possess less lignified stem cortex cells and give ~40% higher actual ethanol yields per gram compared with divergently selected, high — lignin genotypes (Sarath et al. 2011). These genotypes show that genetic improvement for biomass quality traits is possible through breeding. Such studies would be accelerated with the use of molecular markers (reviewed in Bartley et al. 2013b). Mapping the loci responsible would provide specific insight into control of cell wall synthesis in switchgrass. Unfortunately, in the case cited here, this is non-trivial because the divergent genotypes are octoploid, though a similar experiment has been conducted for a tetraploid population (G. Sarath, personal communication). Nonetheless, these results provide insight into achieving robust switchgrass plants with improved

digestibility. For example, reducing the lignin outside of the vasculature appears to be a good way to achieve improved cell wall quality.

From Preliminary to Saturated Linkage Maps

The early generation of genetic maps include only morphological and isozyme markers, and later they were integrated through cytological markers and anchor markers shared by different maps. In switchgrass, the first publicly available genetic maps possesses totally 102 RFLP markers, among which 45 are on female map, and 57 on male map (Missaoui et al. 2005b). Then a higher density male and female framework maps were constructed, and their lengths were 1,645 and 1,376 cM with the genome estimated to be within 10 cM of a mapped marker in both maps (Okada et al. 2010). The present longest linkage map is 2,085 cM, with an average marker interval of 4.2 cM (Liu et al. 2012). The recent map consists of 18 linkage groups and is arranged into nine homoeologous pairs (Liu et al. 2012) (Table 1). ESTs from sequencing of switchgrass tissues, including young crowns and roots, were produced and made publicly available, which provide the resource for new marker development (Srivastava et al. 2010; Palmer et al. 2012). Recently, over 50,000 genomic-SSRs (Sharma et al. 2012) and 2,000 EST-SSRs (Wang et al. 2012) were respectively identified through high-resolution sequencing, and some of them were validated by PCR experiment for testing effective amplification and product-length polymorphism (Liu et al. 2013b). High throughput marker technologies including SNPs are available (Ersoz et al. 2012) and genotyping by sequencing is under development. Thus, the availability of an ultra high-density map in switchgrass is possible in the near future if more markers are added.

Biotechnology approaches using recombinant DNA and transgenic technologies are effective strategies for plant genetic improvement and have been successfully adopted in various crop species. Their use for trait modification in switchgrass has also been demonstrated (Somleva et al. 2008; Chuck et al. 2011; Fu et al. 2011; Xu et al. 2011; Fu et al. 2012) and are expected to play an increasingly important role in switchgrass genetic improvement. However, they can also raise serious ecological concerns because of the possibility of transgene escape (Scott and Wilkinson 1999; Koivu et al. 2001). To address these concerns, various molecular strategies have been developed for gene containment by altering different biological pathways impacting plant flowering (Koivu et al. 2001; Daniell 2002). Genetic engineering of male sterility for controlling pollen grain movement is one of the most important measures for preventing gene flow. In recent years, with the increasing knowledge of miRNAs, genetic manipulation of miRNAs and their targets in transgenic plants could also be one of the useful strategies for inducing male sterility.

MiR159 is a conserved miRNA and negatively regulates the expression of GAMYB genes (Achard et al. 2004; Millar et al. 2005; Tsuji et al. 2006; Alonso-Peral et al. 2010). It has been reported that GAMYB genes are predominantly expressed in the anthers both in rice and Arabidopsis (Millar et al. 2005; Tsuji et al. 2006). Transgenic Arabidopsis overexpressing miR159 causes anther defects (male sterility) due to the down-regulation of its targets, AtMYB33 and AtMYB65 (Achard et al. 2004; Alonso-Peral et al. 2010). Similarly, overexpression of miR159 in rice results in flower malformation and male sterility by decreased expression of OsGAMYB (Tsuji et al. 2006). Recently, Wang et al. (2012) reported that overexpression of the wheat miR159, TamiR159, resulted in delayed heading time and male sterility in transgenic rice plants. We also cloned a switchgrass miR164 (Pvi-miR164a) precursor by PCR based on its EST sequence, and found that overexpression of the Pvi-miR164a precursor driven by the rice Actin promoter led to semi-dwarf and male sterility in transgenic rice plants (Li et al. unpublished). These data suggest the great potential of miRNAs and their target genes for use in switchgrass to induce male sterility as an effective strategy for preventing transgene escape.

Fertilization for Establishing Stands

Since switchgrass is slow to establish and often does not compete well with weeds during the establishment phase. Most annual weeds are responsive to fertilizer applications, and particularly to nitrogen (N), whereas switchgrass displays little response to N during establishment (Sanderson and Reed 2000). Thus, the general recommendation is to defer N fertilizer applications until switchgrass is considered established—typically this means waiting until the second growing season (Jung et al. 1988; Brejda 2000; Sanderson and Reed 2000).

Soil phosphorus (P) and potassium (K) levels (> 20 soil P and > 200 soil K by the Mehlich 3 index) should be sufficient for establishment. Although general recommendations for P and K are to have these nutrients at moderate levels at planting, there is little data to suggest that adding K fertility can boost seedling growth at establishment. Soil P has been implicated in increased plant size and first-season yield, but this response may be short-lived (McKenna and Wolf 1990).

Switchgrass is moderately tolerant of soil acidity, but liming is generally recommended prior to planting if soil pH is below 5.0 to ensure other plant nutrients like P and K are more available. The literature equivocates, however. Several studies report no benefits from liming (Harper and Spooner 1983; Bona and Belesky 1992; Hopkins and Taliaferro 1997), although McKenna and Wolf (1990) found that limestone (2016 kg ECCE ha1) increased first-harvest yield in one year but not the second.

Responses to lime are more likely to be observed when it is applied in combination with nutrients such as N or P. For example, yields were maximized when a combination of limestone and P were applied (McKenna and Wolf 1990). Similarly, on highly acidic (pH 4.3-4.9) soil in Pennsylvania, USA, switchgrass grown on untreated plots yielded about 50% of that receiving limestone and fertilizer (Jung et al. 1988). In a greenhouse pot experiment with five acidic soils (pH 4.5-5.2), yield did not increase when soil pH was brought to 6.5 with limestone, however, a yield response was reported when N and P or N, P, and K were co-applied with limestone (Taylor and Allinson 1982).

As plants are sessile organisms, the wide diversity of mutually beneficial plant-microbe interactions represents an ancient evolutionary partnership, helping the host plant survive and thrive, even in some of the harshest environments on the planet. Mechanisms of growth promotion by bacterial and fungal endophytes as well as AM fungi have been investigated in grasses for decades, and various mechanisms play roles in promoting plant growth and development. Bacterial endophytes are capable of producing or regulating plant hormones, helping acquire vital nutrients, and bio-control of pathogens (Sturz et al. 2000). Plant associated fungi, both endophytic and mycorrhizal, also confer a range of growth promotion benefits to their host plant including nutrient acquisition. Furthermore, a particular bacterial or fungal endophyte may utilize one or more mechanisms to promote plant growth and may even utilize different mechanisms at various points during the life cycle of plants. While it is clear that endophytes can benefit the host plant in many ways, establishing clear-cut growth promotion in the field can be difficult due to a number of factors including the diversity of native microorganisms in the soil and soil conditions. A more profound understanding of these mechanisms is allowing scientists to discover new ways to integrate their use into increasing yields of bioenergy crops like switchgrass. Also, by utilizing tools of modern molecular biology and functional genomics to understand the complexity of growth promotion at the genetic level, additional light will be shed on these complex interactions. As more is learned about the biochemistry, molecular biology, and physiology of microbe-plant interactions, it is evident that bacterial and fungal microorganisms will be important components for sustainable bioenergy feedstock production in the future.

Plant growth promotion can generally be achieved directly by interactions between the microorganism and host and/or indirectly through antagonistic activity against plant and environmental pathogens (Berg 2009). In this section, we will discuss both mechanisms and how different beneficial microbes may work together to benefit the host plant simultaneously (Muller et al. 2009), as well as how microorganisms, especially bacteria, may share mechanisms of actions genetically through horizontal gene transfer.

Cellulose hydrolysis requires enzymatic cleavage of p-1,4-glycosidic bonds between D-glucose units. GHs with this function are generally called cellulases, and can be divided into three classes based on their enzymatic activities (Lynd et al. 2002). The known classes of cellulose­degrading enzymes are summarized in Table 3 and illustrated in Fig. 6. Endoglucanases randomly cleave interior glycosidic bonds in cellulose, releasing oligosaccharides of varied lengths with new reducing and non­reducing ends. This function greatly contributes to solubilizing the cellulose polymer by reducing molecular size and creating accessible chain ends for further attack. Cel48F, CelC, Cel7B proteins are typical endoglucanses critical in cellulose degradation in Clostridium cellulolyticum (Perret et al. 2004), C. thermocellum (Wang et al. 1993) and Trichoderma reesei (Kleman-Leyer et al.1996), respectively. RNAi-based repression of Ce148F C. cellulolyticum resulted in a 30% decrease in the activity of the cellulolytic system on microcrystalline cellulose (Perret et al. 2004). In contrast, exoglucanases act from chain ends of cellulose oligosaccharides to processively chip off glucose or cellobiose (di-glucose) units (Lynd et al. 2002). Glucose- and cellobiose-releasing exoglucanases are also called exo-1,4-p-glucosidases and cellobiohydrolases, respectively. p-glucosidases typically split cellobiose dimers, or sometimes cellotrioses, into individual glucose units, thereby releasing the inhibitory effect of accumulated cellobiose on exo — and endo-glucanases (Gruno et al. 2004; Yue et al. 2004). These three classes of cellulases are critical to cellulose degradation and have been applied in different industries (Kuhad et al. 2011). In addition, some bacteria, like C. stercorarium and C. thermocellum, also encode other enzymes that act in cellulose degradation. Cellobiose phosphorylases are able to phosphorylate cellobiose to produce one glucose molecule and another activated glucose- 1-phosphate molecule without using ATP (Alexander 1968; Reichenbecher et al. 1997). Recently, a cellobiose dehydrogenase from Neurospora crassa was found to enhance cellulose degradation by coupling the oxidation of cellobiose to the reductive activation of a copper-dependent polysaccharide monooxygenase (Sygmund et al. 2012). Cellulolytic microorganisms produce a diversity of these enzymes for synergistic catalysis to significantly accelerate cellulose degradation (Doi 2008; Fontes et al. 2010).