Bioenergy production will become increasingly important in the future to relieve dependence on fossil fuels and lower greenhouse gas emissions because fossil-based energy is limited and its demand is continually increasing due to economic and population growth around the world. Switchgrass is one of the most promising bioenergy crops due to persistent high yields and its ability to grow on marginal land. Development of a low input and sustainable switchgrass feedstock production system is imperative as the use of chemical fertilizers causes deleterious environmental effects, such as water pollution and N2O release to atmosphere, a potential greenhouse gas. Endophytes and AM fungi have the potential to help address these challenges due to their enhancement of nutrient acquisition, including nitrogen fixation and mobilization of mineral nutrients as well as increased biotic and abiotic stress tolerance, which together will reduce the amount of fertilizer application and/or pesticide and fungicide use. It will also open a door to growing potential bioenergy crops, such as switchgrass on marginal land or achieving the same yield while reducing fertilizer use, resulting in lower cost and contributing to sustainable rural development.

Plants live in complex environmental conditions containing various microorganisms, both beneficial and detrimental. Although endophytes and AM fungi could benefit plant growth, other microorganisms may have negative effects, and different endophytes and AM fungi may not be compatible, therefore the specific functional compatibility of endophytes and AM fungi needs to be further investigated to develop multi-functional bio-inoculants (Podile and Kishore 2007) in switchgrass production. Additionally, while studies with endophytes as well as other plant growth promoting microorganisms in laboratories have been encouraging, there have also been reports of a general decrease in performance from the laboratory to the field (Riggs et al. 2001; Gyaneshwar et al. 2002). As with any ecosystem, the variables of field conditions and native microbial populations will have to be addressed to maximize the beneficial effects of bacteria and fungi. Therefore, screening endophytes having a broad spectrum of growth promotion that continues throughout the life of the plant will be another topic for endophyte application.

Genotype specific responses of host plants to endophytes are also a large barrier in application. For example, in poplar, different cultivars had different responses to different endophytes (Taghavi et al. 2009). One of the most studied plant growth promoting bacterium, B. phytofirmans strain PsJN, has a beneficial effect on many species, such as potato, tomato, and grape. However, PsJN is also genotype specific. In switchgrass, PsJN promoted growth of the lowland cultivar Alamo but not the upland cultivar Cave-in-Rock (Kim et al. 2012). Understanding these differences will also help in developing a more reliable, stable, and broad spectrum of growth promotion in plants.

Complete understanding of the mechanisms of various beneficial symbioses is the foundation for effectively applying these microorganisms in a sustainable switchgrass feedstock production and to achieve their synergistic activities (Podile and Kishore 2007). As more is learned from functional genomics of endophytic microorganisms in growth promotion, it may be possible to share these important genes between similar microorganisms through horizontal gene transfer via transformation, conjugation, or transduction, all common occurrences in the bacterial world. Researchers first reported in planta horizontal gene transfer in the bioenergy crop hybrid poplar when they found Burkholderia cepacia VM1468 transferred its toluene degradation gene to other endophytes (Taghavi et al.

2005) . This suggests that such transfer may be used to modify and improve the growth-promoting effects of other endophytes via gene sharing. The phenomenon of horizontal gene transfer may also occur in nature between different genera as the gene encoding the anti-fungal agent pyrrolnitrin in Burkholderia was likely horizontally transferred from Pseudomonas (de Souza and Raaijmakers 2003). Since AM fungi are coenocytic (many nuclei coexist in a common cytoplasm), genetic exchange was recently reported in different AM fungus Glomus intraradices strains (Colard et al. 2011), which could be beneficial for host plant growth. Generating novel AM fungus genotypes through genetic exchange will be a powerful tool in developing AM fungi that are more beneficial in bioenergy crop production.

Compared with plant genetic engineering, it is much easier for microorganisms to be genetically modified. One could easily transform some useful foreign genes into bacteria or fungi. For instance, the Bacillus thuringiensis cry1Ac7 and Serratia marcescens chiA genes were transformed to sugarcane-associated endophytic bacteria, which helped increase the tolerance of sugarcane plant to the sugarcane borer Eldana saccharina (Downing et al. 2000). These applications indicate that we may be able to genetically engineer endophytes with useful genes, such as the Bacillus thuringiensis toxin gene, to protect host plants against herbivorous insects, herbicide resistance genes to impart host plant resistance to herbicides, and genes related to abiotic stress tolerance to enhance host plant tolerance to abiotic stresses. An efficient endophyte transformation method by Agrobacterium was developed by Abello et al. (2008), which will help in the transfer and expression of agronomically important genes in host plants via endophytes. As functional genomics research is continually advanced, scientists will better understand the mechanisms under which beneficial microorganisms promote host plant growth and enhance stress tolerance to effectively utilize these microbes in bioenergy crop production. For example, endophytes having the ability to fix atmospheric nitrogen could be combined with endophytes having the ability to enhance host plant tolerance to abiotic stresses or endophytes inhibiting pathogen growth or with an AM fungus to improve nutrient uptake or, possibly, all could be combined.

Since 1999, over 15 new patents have been registered for microbial endophytes (Mei and Flinn 2010). The worldwide market for microbial inoculants is experiencing an annual growth rate of approximately 10% (Berg 2009). As world population demand for food is continually increasing, bioenergy crops should be grown on poor or marginal lands or contaminated soil, not competing with food crops for fertile lands. The use of endophytes and AM fungi may help bioenergy crops, such as switchgrass, grow on these lands via their normal mechanisms of action or genetic modification by introducing nitrogen fixation genes, heavy metal accumulation genes, or contaminated compound degradation genes.

Acknowledgements

This work was funded through Special Grants (2003-38891-02112, 2008­38891-19353 and 2009-38891-20092) and HATCH funds (Project No. VA — 135816) from the United States Department of Agriculture, the Office of Science (BER), U. S. Department of Energy for Plant Feedstock Genomics for Bioenergy Program (DE-SC0004951), and operating funds from the Commonwealth of Virginia to the Institute for Advanced Learning and Research.

Linglong Liu1’2[9] [10] and Yanqi Wu1

Introduction

Switgrass, a C4 perennial grass widely distributed in North America, has become one of the main bioenergy crops for production of cellulosic biofuels. Due to its relatively short history in research, the advance of molecular genetics and breeding of switchgrass is lagging behind that of the other major row crops (such as rice, wheat, and corn). However, with the increase of investment from public agencies and private organizations, many achievements have been attained, especially in recent years (Bouton

2007) . This chapter will focus on switchgrass classical molecular genetics including development of molecular markers, construction of linkage groups, and application of molecular breeding. Transgenic researches are not presented here, but are addressed in a separate chapter of this book.

As described above, bioinformatics predictions for switchgrass miRNAs might be limited by the lack of large genomic data and the number of available ESTs. Direct cloning is a possible experimental approach to discover not only conserved, but also novel switchgrass-specific miRNAs. Several groups have used this method to identify plant miRNAs in different plant species (Sunkar and Zhu 2004; Sunkar et al. 2005; Yao et al. 2007; Sunkar et al. 2008; Zhao et al. 2010; Kulcheski et al. 2011; Li et al. 2012).

The cloning methods involve in small RNA library construction (including isolation of small RNAs, ligation of adaptor oligonucleotides, reverse transcription, and amplification) and sequencing. Matts et al.

(2010) pooled equal molar amounts of total RNA from three-month-old switchgrass seedlings and inflorescences for small RNA library construction. The amplification products were then subjected to pyrosequencing following Sunkar et al. (Sunkar et al. 2008). A total of 21,999 raw sequences was generated and subjected to further analysis to discard duplicates, degradation products from ribosomal RNAs, transfer RNAs, small nuclear RNAs and mRNAs (Sunkar et al. 2008; Matts et al. 2010). The remaining small RNAs were subsequently analyzed for distinguishing miRNAs from siRNAs, and conserved miRNAs were identified by searching against miRBase (Matts et al. 2010).

Most common routes available for conversion of syngas into hydrocarbon fuels are Fischer-Tropsch (FT) process, and syngas to methanol to gasoline (MTG). FT conversion of syngas into hydrocarbons is one of the most recognized technologies with first plant operation in Germany in 1938. Currently three plans use the FT process to produce gasoline, diesel and chemicals from coal and natural gas. FT process uses Fe — or Co-based catalysts for the conversion. The resulting product is a wide range of primarily linear hydrocarbons from C1 compounds to high molecular mass waxes, which need reprocessing to obtain hydrocarbons in the range of diesel or gasoline. Diesel is the most appropriate fuel because the FT product contains mostly linear hydrocarbon which results in diesel with high cetane number (Dry 2004). However, due to the need to additional processing of long chain hydrocarbons (waxes), the capital cost is high (Spath and Dayton 2003). FT process is optimum at syngas H2/CO of 2, which is difficult to achieve in biomass generated syngas without steam reforming. Conversion of syngas to methanol is a well-known process. However, since methanol cannot be used directly because of its toxicity, methanol can be converted into gasoline through methanol to gasoline (MTG) process developed by Mobile Oil Corporation in 1970s. The process uses zeolite-based catalysts (ZSM-5) resulting in higher than 85% selectivity to gasoline-range hydrocarbons (Spath and Dayton 2003).

Biochemical pathways such as aerobic respiration, anaerobic respiration and fermentation within microoganisms efficiently convert organic substrates into chemicals or biofuels such as ethanol. Aerobic respiration pathways convert carbon source such as glucose to produce ATP through series of the Embden-Meyerhof pathway, the tri-carboxylic acid pathway and the electron transport chain, with oxygen acting as the terminal electron acceptor. In anaerobic respiration (absence of oxygen), the terminal electron acceptors are replaced with inorganic compounds such as sulfate or nitrate to produce ATP. In fermentation, internally balanced oxidation and reduction of organic compounds occur with the biochemical pathway under anaerobic conditions, but without utilization of the electron transport system. However, bioprocessing industries often call both aerobic and anaerobic respiration fermentation processes where the term generally entails any bioconversion process.

Cellulosic ethanol fermentation may be performed using a wide range of microorganisms. Yeast such as Sacharomyces cerevisiae and bacteria such as Zymomonas mobilis are well known for utilizing glucose, fructose and sucrose for ethanol fermentation under anaerobic conditions with higher ethanol tolerance. Z. mobilis has a higher metabolic rate with less biomass production through the Entner-Doudoroff pathway (Fig. 3) compared to S. cerevisiae through the Embden-Meyerhof-Parnas (EMP) pathway (Fig. 4). The faster rates occur from decoupling energy generation from ethanol production with the absence of the highly-regulated enzyme phosphofructokinase (PFK) present in the EMP pathway. However, a number of disadvantages

exist for use of Z. mobilis, mainly in the production of byproducts such as levan catalyzed by levansucrase and other fructose polymers that tend to foul distillation columns downstream (Drapcho et al. 2008). S. cerevisiae is the most widely used microorganism for cellulosic ethanol production due to high ethanol tolerance and the remaining biomass being more suitable for use as animal feed than biomass from Z. mobilis fermentation. The hydrolysis of lignocellulosic biomass generates a mixture of both sugars (hexoses and pentoses) during the process. The simultaneous utilization of both sugars is the most challenging part for the cellulosic ethanol production. Therefore, other strains of yeast, bacteria and fungi have been explored or genetically modified for simultaneous utilization of both glucose and xylose in cellulosic ethanol fermentation. In literature, numerous microorganisms have been studied using xylose as the carbon source (Table 4). However, the performance of these microorganisms varies on hydrolyzed lignocellulosic broth due to variations in sugar utilization from the presence of inhibitors that depends on the chemical composition of lignocellulosic feedstock, chemical pretreatment and the extent of recirculation in the process (Table 5). A preprocessing or detoxification of these inhibitors from the hydrolyzed broth before or after the fermentation could be an energy-intensive step (Olsson and Hahn-Hagerdal 1996). However, these inhibitory effects could be resolved using fermenting microorganisms with high cell densities (Olsson and Hahn-Hagerdal 1996). A list of different microorganisms with their optimal ethanol yield and productivity is given for ethanol fermentation using enzymatic hydrolysate of lignocellulosic feedstock (Table 6).

In addition, fermentation can be performed in batch, semi-batch and continuous mode. The selection of the fermentation mode for optimal ethanol yields is based on the kinetic properties of microorganisms used and the integration of the cellulosic ethanol production process.

Many second generation bioenergy crops are lauded for their contribution to climate change mitigation efforts, particularly those involving minimizing greenhouse gas emissions and enhancing carbon sequestration. As a bioenergy crop, switchgrass rates well in a number of climate mitigation metrics (see Vadas et al. 2008). It is a perennial crop with deep roots (Lemus and Lal 2005), which are often implicated in its carbon sequestration abilities. Switchgrass performs better than maize in its carbon sequestration rates (Searchinger et al. 2008; Davis et al. 2012; but see Follett et al. 2012), and when combined with human health costs associated with fine particulate matter emissions in biofuel feedstock growth and processing, switchgrass comes across as far superior to maize (Hill et al. 2009). Not only does switchgrass perform better than a number of other bioenergy crop alternatives with respect to CO2 emissions (Monti et al. 2009), but production of agronomic switchgrass has also been tied to low NO2 and CH4 emissions when compared to most alternatives (Monti et al. 2012). Surely, different crop management strategies will contribute to variability in greenhouse gas emissions metrics (Monti et al. 2012), but overall it would appear that switchgrass is a leading bioenergy crop candidate in this critical area.

The high regard bestowed on switchgrass for its production-associated greenhouse emissions metrics may be tempered, however, by repercussions of landscape and land-use change that would be necessary to provide mandated amounts of ethanol in the U. S. The estimated amount of current non-agricultural land that would need to shift to second generation bioenergy crops to reach government mandates in ethanol production is upwards of 200,000 km2 to possibly three times that number (McDonald et al. 2009). This shift is typically not integrated into life cycle analyses of climate mitigation aspects of switchgrass production, but its impact cannot be overlooked. The clearing of forests and the changeover of range-, hay-, and pasture-lands to accommodate dedicated bioenergy crops, like switchgrass, would immediately result in substantial net CO2 emissions, which some studies have estimated to amount to approximately 350 Mt/ converted ha (Searchinger et al. 2008). Future conversion of non-arable land worldwide for crop production could result in > 3 Gt/yr of greenhouse gas emissions by 2050 (Tilman et al. 2011). The difficult and multifaceted challenge here would be to have quick-establishing (e. g., rapid growth in the early growing season), highly productive perennial bioenergy crops capable of substantial carbon storage in their roots. Currently, no CO2- related cap-and-trade laws are in effect, and treatment of CO2 emissions as pollutants by the U. S. Environmental Protection Agency is in its infancy; how these issues may affect future landscape conversion to switchgrass crop fields is unknown.

Those involved with improvement efforts in switchgrass will also need to be cognizant of climate forecasts in the areas it will be grown. For one, increased atmospheric CO2 levels may not necessarily lead to increased productivity (i. e., no "CO2 fertilization" effect) in switchgrass (Fay et al.

2012) . In addition, habitat suitability and climate envelope models already have switchgrass incapable of growing in a number of regions where some of today’s highest-yielding lowland cultivars originated in the southcentral U. S. by as early as 2040 in some of the "best case" scenarios (Barney and DiTomaso 2010; Tulbure et al. 2012). The hotter conditions forecast for the southeastern U. S., which include current areas of highest predicted switchgrass biomass yields, will dictate that breeding improvements be dedicated towards better water-use efficiency (see Le et al. 2011) and related traits aimed at "climate proofing" (sensu Oliver et al. 2009) the crop. This is noteworthy and may seem perplexing, given that switchgrass currently is noted for exhibiting high water-use efficiencies, higher than some alternatives (VanLoocke et al. 2012).

Seedbed preparation is the next step following site selection. The goal prior to seeding is to have an environment that optimizes seed germination and seedling establishment. Ideal seedbeds are very firm below planting depth, have friable surface soil, and are free from competition with resident vegetation and weed seeds (Vallentine 1989). These ends can be achieved with both conventionally tilled and no-till systems.

Having clean fields with minimal weed competition can be a major factor for successful switchgrass establishment and the amount of residue also can be a factor in timing of planting. Zarnstorff (1990) reported greater stand success with later seeding dates when sowing into rye (Secale cereale L.) stubble and that shorter stubble heights supported increased seedling numbers. Excess herbage residue on fields can hinder seed placement, thus preventing proper soil-seed contact (Wolf and Fiske 2009). As seen with other crops, residues can also provide safe haven for slugs and other pests that prey on the emerging seedlings (Hammond 1996; Luna and Staben 2002; Vernava et al. 2004).

Tillage can be an effective method of seedbed preparation and residue removal, although tilling can be more expensive and has potential to expose susceptible sites to erosion. Because firm seedbeds are essential for switchgrass establishment, it is imperative that tilled fields be firmly packed at or just prior to seeding. Tillage also has the potential both to kill weed seedlings and to free weed seeds for germination; thus, weed conditions and management must be carefully considered with tillage.

No-till methods can be quite effective for switchgrass establishment. No-till systems conserve soil moisture, minimize soil erosion, require less fuel, and allow earlier entry of equipment into fields following precipitation events (Parrish and Fike 2005; Douglas et al. 2009). While no-till establishment has several advantages, residue management can be a prime concern given the issues of seed placement and pest habitat mentioned above.

Strategies of residue removal include harvest, or chemical burn followed by sufficient time to degrade the residue. Growing glyphosate-resistant crops such as soybeans on the site prior to switchgrass establishment can be an effective strategy for seedbed preparation. Glyphosate applications can decrease weed burdens, and, following harvest, the resultant stubble makes a suitable seedbed for planting switchgrass. However, caution should be used if prior production practices have utilized persistent herbicides that can prevent seed germination and growth (Douglas et al. 2009).

Burning field residues can also be an effective residue removal method for both tilled and no-till systems. In addition to removing crop residues, burns can kill small weeds and pests and reduce the size of the soil weed seed bank, thus decreasing competition for new seedlings (Wolf and Fiske

2009) . Burning may be especially useful for converting old pastures or abandoned field sites with large weed burdens, but, success is predicated on the temperature and speed of the burn.

At planting, an ideal seedbed—whether prepared with or without tillage—will enable placement of the seed at the proper depth (discussed in the following section) and in firm contact with the soil. This requires appropriate levels of soil compaction, which ensures rapid movement of water from the soil to the seed/seedling by improving capillary water flow. Increased moisture availability increases the likelihood of rapid, uniform germination, early seedling growth, and successful stand establishment (Bartholomew 2005). Too much compaction, however, can restrict the ability of seedlings and their roots to penetrate through the soil. Hudspeth and Taylor (1961) reported that switchgrass was able to germinate and emerge from 8 cm depth in loose soil, but only 10% of seeds emerged when compaction was 6.9 kPa and no seedlings emerged with pressure of 69 kPa. Too much compaction also affects oxygen diffusion, soil temperature, and light penetration, all of which influence germination and emergence (Hudspeth and Taylor 1961).

In contrast to over compacted soils, poor soil contact resulting from cloddy or loose soil or from excess residue can slow seed germination creating conditions for uneven emergence and subsequent seedling desiccation. Loose soils can also contribute to too great a seed depth when rains cause seed depths to be greater than ideal (Fig. 2). Such effects limit emergence and can lead to problems such as weed competition during the early establishment phase (Hall and Vough 2007).

Planting Depths

Proper planting depth is critical to successful switchgrass establishment, and many stand failures have occurred because seed placement was too deep. Appropriate depth maximizes emergence and seedling growth, and as a general recommendation, proper seed placement is difficult to regulate unless the seedbed is firm enough to prevent placing the seeds too deep (Masters et al. 2004), either directly or by soil washing into the planting furrow (Fig. 2). Typically seed should be covered with enough soil to maintain moist conditions for germination, but not so deep that the shoot cannot reach the surface (Zhang and Maun 1990; Roundy et al. 1993; Cosgrove and Collins 2003).

Although 1.5 cm is a common lower limit for planting depth, emergence from greater depth is possible (Zhang and Maun 1990). The ideal depth depends on soil texture and other soil physical properties (Aiken and Springer 1995; Evers and Parsons 2003), and deeper plantings are recommended for arid environments or on sandy soils where moisture limitations can slow imbibition, germination, and emergence (Newman and Moser 1988; Evers and Butler 2000; Evers and Parsons 2003).

Just as planting too deep is problematic, shallow plantings also can be the cause of stand failure. Shallow seed placement under drying conditions can cause seedlings to desiccate and die before they become established (Cosgrove and Collins 2003). This is especially so with bare soils which lose water more rapidly than those protected by litter (Winkel et al. 1991). Adventitious root formation may be compromised with shallow plantings —and the adventitious roots are the only roots that matter for the plant’s long-term survival (Parrish and Fike 2005).

Seed size can affect the appropriate seeding depth for many species, but the data on switchgrass seed size and germination, while suggestive of greater success with larger seeds, are not definitive. Larger seeds support more rapid germination and emergence (Aiken and Springer 1995) and more rapid adventitious root development (Smart and Moser 1999). However, these early advantages appear to be lost over time (Zhang and Maun 1990). Whether seed size affects competitive responses with weeds has not been definitively tested.

Endophytes, including bacteria and fungi, and arbuscular mycorrhizal (AM) fungi, directly or indirectly affect plant growth. In general, these microorganisms promote host plant growth, enhance nutrient uptake and stress tolerance, and inhibit plant pathogen growth. These three plant growth-promoting microorganisms have been studied in a broad range of plants including switchgrass, as will be detailed below.

Rather than targeting a particular cell wall synthesis enzyme, another promising direction for improving biomass quality is to modulate the expression of suites of enzymes by altering regulators of cell wall synthesis, especially transcription factors. Indeed, population genetic analyses have found that markers in known cell wall synthesis genes associate with only a few percentage points of cell wall quality variation (Wegrzyn et al.

2010) . As discussed in recent reviews, a growing network of transcription factors regulates secondary cell wall synthesis (Zhao et al. 2011; Gray et al. 2012; Handakumbura et al. 2012) (Fig. 4). As with all other aspects of cell wall biology, knowledge of cell wall transcriptional regulation networks specifically in grasses lags behind that in dicots. Still, where factors have been studied in both grass and dicot systems, it seems likely that many aspects of regulation are conserved (Handakumbura et al. 2012). Here, we will give an overview of the emerging cell wall regulatory hierarchy in Arabidopsis and grasses.

Many transcription factors implicated in secondary cell wall regulation belong to the NAC and the MYB R2R3 protein families. The relevant NAC-domain transcription factors known are known simply as NACs, or Secondary Wall NACs (SWNs), and include SND1 (SECONDARY WALL- ASSOCIATED NAC-DOMAIN PROTEIN 1, also known as NST3), NST1 (NAC SECONDARY WALL THICKENING FACTOR1), NST2, VND6 (VASCULATURE-RELATED NAC-DOMAIN 6) and VND7 (Handakumbura et al. 2012). Different secondary cell wall regulatory pathways appear to function in different cell types in different organs.

Figure 4. Schematic model of the regulatory network of secondary cell wall biosynthesis based primarily on studies in Arabidopsis. Peach circles represent transcription factors known to function in Arabidopsis. The red circles demarcate the transcription factors whose function has been studied in grasses. The yellow octagons represent enzymes. The grey squares represent secondary cell wall polymers. The green triangle represents a property of the cell wall, saccharification. Arrows signify positive regulation; whereas, dashed edges with T ends indicate negative regulation. Cis-elements are labeled on the edges as follows: Secondary wall NAC Binding Element (SNBE), Tracheary Element Responsive Element (TERE), Secondary wall MYB Responsive Element (SMRE), and the AC-rich elements found in lignin biosynthesis gene promoters (AC). See text for references and further discussion. For simplicity, not all known or suspected interactions are shown. Abbreviations are as follows: Lig Bios Enz, lignin biosynthesis enzymes; SCW Enz, secondary cell wall biosynthesis enzymes the specific identity of which has not been specified; PAL1, Phenylalanine Ammonium Lyase 1; 4CL1, 4-Coumaroyl Ligase 1; COMT, Caffeic acid O-MethylTransferase; C4H, Cinnamate 4-Hydroxylase; CESA, Cellulose Synthase A; SHN, shine/wax inducer 1; VND, Vasculature-related NAC-Domain; SND, Secondary wall-associated NAC-Domain protein; NST, NAC Secondary wall Thickening factor; VNI2, VND-interacting 2 NAC protein 2.

BSA is firstly developed by Michelmore et al. (1991) and has becomes a rapid mapping strategy suitable for monogenic or major qualitative traits. Two bulked DNA samples are generated from a segregating population that originated from a single cross. Each pool, or bulk, contains individuals (the number of individuals in each bulk varied between 10 and 20 plants) that are identical for a particular trait (e. g., disease resistant or susceptible) or genomic region but arbitrary at all unlinked regions. The two bulks are therefore genetically dissimilar in the selected region but seemingly heterozygous at all other regions. Thus, the two bulks can be made for any genomic region and from any segregating population, and they can be screened for differences the same way as near isogenic lines (NILs) (Michelmore et al. 1991). This approach is applicable both in those species where selfing is possible and in those that are obligatorily outbreeding like switchgrass. Since its invention, BSA technique has been widely used in different species for single gene and QTL analysis (Van Leeuwen et al. 2012).

Diseases had been reported to affect switchgrass biomass yields in southern Iowa (Gravert and Munkvold 2002). Thomsen et al. (2008) conducted a study in naturally infected condition caused by smut, and found biomass yield loss of an upland cultivar ‘Cave-in-Rock’ varying from 0.6% to 40.1% among fields. Other major diseases affecting biomass yields are rust (Gustafson et al. 2003) and leaf spots (Krupinsky et al. 2004). Little information is available regarding disease resistance of switchgrass cultivars. Gustafson et al. (2003) used four switchgrass populations (two were derived from cultivars ‘Summer’ and ‘Sunburst’, and the other two developed by breeder of Nebraska and Oklahoma, respectively), and evaluated rust resistance at two locations (Aurora and Kimball, SD) in two years. Significant variations for rust resistance were observed among and within populations, suggesting genetic improvement in rust resistance may be effective through selection (Gustafson et al. 2003). In an ongoing project, we found obvious differences for leaf rust resistance in a segregated population derived from selfing of ‘NL94 LYE 16Х13’. Considering that bulks screened method had been utilized for mapping resistance gene (s) initially in lettuce (Michelmore et al. 1991), and then successfully expanded in other plant species (Michelmore 1995), it can be expectedly moved to switchgrass to identify markers linked with major resistant genes. A gene mapping project of switchgrass rust resistance is on the way (Y. Q. Wu, unpublished).