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2023 Volume 3
Article Contents
Abstract
Introduction
Types of functional rice
High resistant starch rice
Colored rice
Giant embryo rice
Low glutelin rice
Golden rice
Fe and zn fortified rice
Breeding technology of functional rice
Traditional polymerization breeding
Transgenic polymerization breeding
Molecular marker-assisted selection polymerization breeding
Cultivation and regulation technology of functional rice
Effect of light on the accumulation of active components in rice
Effect of temperature on the accumulation of active components in rice
Effect of water management on the accumulation of active components in rice
Effect of fertilizer application on the accumulation of active components in rice
Effect of harvesting time on the accumulation of active components in rice
Prevention and control of pests and diseases for functional rice
Conclusions
Acknowledgments
Conflict of interest
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References
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ARTICLE   Open Access    

Overexpression of the Arabidopsis SHN3 transcription factor compromises the rust disease resistance of transgenic switchgrass plants

  • 1.

    School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, Virginia 24061, USA

  • 2.

    Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, USA

  • 3.

    Sustainable Biomaterials, Virginia Tech, Blacksburg, Virginia 24061, USA

  • 4.

    Institute of Biological Chemistry, Washington State University, Pullman, Washington 99164, USA

More Information
  • Switchgrass can generate large amounts of renewable biomass and hence is one of the most promising bioenergy crops. Improving the quality of switchgrass lignocellulosic biomass will enable its utilization for biofuels. Arabidopsis SHINE family of transcription factor SHN2 was previously identified as a master regulator of cell wall deposition in transgenic rice. However, it is unclear if the Arabidopsis SHN genes also have a similar biological function in switchgrass. Here, we generated transgenic switchgrass overexpressing the Arabidopsis SHN3 transcription factor. Compared with the wild-type, AtSHN3-overexpressing switchgrass plants were stunted in their growth. There were no significant differences in terms of lignin and cellulose content between the SHN transgenics and wild-type switchgrass plants. However, two AtSHN3 transgenic lines SHN7-2 and SHN5-2, displayed significant changes in several matrix polysaccharide monomers. Overexpression of AtSHN3 in switchgrass did not alter the stem mechanical strength when subjected to tensile-torsion analysis. Interestingly, the AtSHN3-overexpressing transgenic lines were more susceptible to switchgrass rust (Puccinia emaculata) than wild-type plants. Therefore, AtSHN3 may have a negative role in regulating disease resistance in switchgrass.

  • Introduction

    With the development of the world economy, people's lifestyles have changed dramatically, and long-term high-intensity work has put many people's bodies in a sub-healthy state. The increasing incidence of various chronic diseases has not only put enormous pressure on society's healthcare systems but also caused endless suffering to people[1]. Therefore, people's demands on the functionality and safety of food are increasing, and it has become the consensus of people that 'not just eating enough, but more importantly eating well'.

    Rice is the staple food for more than half of the world's population and the main economic source for a large number of rural people[2]. However, due to the rising cost of rice cultivation, farmers are gaining less and less economic benefits from growing rice, which seriously undermines their incentive to grow rice and poses a serious threat to world food security. Increasing the added value of rice not only helps to increase farmers' income but also helps to ensure world food security. The presence of a large number of functional ingredients in rice makes it possible to increase the added value of rice, and functional rice has therefore been widely noticed.

    Functional rice refers to rice containing certain specific components that play a regulatory and balancing role in human physiological functions in addition to the nutrients necessary for human growth and development in the endosperm, embryo, and rice bran. They can increase human physiological defense mechanisms, prevent certain diseases, help recovery, delay aging, and boost physical strength and energy levels[3]. Rice is a staple food for more than half of the world's population[4], and its functional components have a great potential to be exploited for human welfare. Using functional rice as a carrier to address health problems and realize 'medicine-food homology' is an excellent motivation for promoting functional rice. The current typical functional rice is introduced in this paper. It also summarizes the breeding and cultivation technologies of functional rice.

    Types of functional rice

    High resistant starch rice

    Rice has a high glycemic index. Its long-term consumption leads to obesity, diabetes, and colon disease in many people[5]. However, the consumption of rice rich in resistant starch (RS) can greatly reduce the risk of these diseases[6]. Therefore, breeding rice varieties with high RS content has attracted considerable attention from breeders in various countries. However, the variability of RS content between different rice varieties is low, and there are few germplasm resources available for selection, thus making it challenging to breed rice varieties with high RS content using traditional breeding methods. Combining traditional and modern molecular breeding techniques can greatly improve the successful production of high RS rice breeds. Nishi et al.[7] selected a high RS rice variety EM10 by treating fertilized egg cells of Kinmaze with N-methyl-N-nitrosourea. However, its yield was very low, and it was not suitable for commercial production. Wada et al.[8] crossed 'Fukei 2032' and 'EM129' as parents and selected Chikushi-kona 85, a high RS rice variety with a higher yield than EM10. Miura et al.[9] bred ultra-high RS BeI-BEIIB double mutant rice by crossing the Abe I and Abe IIB mutant strains, and the content of RS in the endosperm reached 35.1%. Wei et al.[10] found that the simultaneous inhibition of starch branching enzyme (SBE) genes SBEIIb and SBEI in Teqing by antisense RNA could increase the RS content in rice to 14.9%. Zhu et al.[11] used RNAi technology to inhibit the expression of SBEI and SBEII genes in rice, which increased the content of RS in rice endosperm from 0 to 14.6 %. Zhou et al.[6] found that rice RS formation is mainly controlled by soluble starch synthase (SSIIA). However, its regulation is dependent on the granule-bound starch synthase Waxy (Wx), and SSIIA deficiency combined with high expression of Wxa facilitates the substantial accumulation of RS in the rice. The results of Tsuiki et al.[12] showed that BEIB deficiency was the main reason for the increased accumulation of RS in rice. Itoh et al.[13] developed new mutant rice lines with significantly higher levels of RS in rice by introducing genes encoding starch synthase and granule-bound starch synthase in the rice into the BEIB-deficient mutant line be2b.

    Colored rice

    The accumulation of anthocyanins/proanthocyanidins in the seed coat of the rice grain gives brown rice a distinct color[14]. Most common rice varieties lack anthocyanins in the seed coat, and so far, no rice variety with colored endosperm in its natural state has been identified. However, Zhu et al.[15] bred rice with purple endosperm using transgenic technology. Red rice contains only proanthocyanidins, while black and purple rice contain anthocyanidins and proanthocyanidins[16]. Red seed coat of rice was found to be controlled by the complementary effects of two central effect genes Rc and Rd. The loss of function of the Rc gene prevented the synthesis of proanthocyanidins, while the Rd gene could enhance the effect of the Rc gene in promoting proanthocyanidins synthesis[17]. Purple seed coat color is controlled by two dominant complementary genes Pb and Pp. Pb determines the presence or absence of seed coat color, and Pp determines the depth of seed coat color[18]. In addition, phycocyanin synthesis is also regulated by transcription factors such as MYB, bHLH, HY5, and WD40[14], but the exact regulatory mechanism is not clear. Colored rice is rich in bioactive components, such as flavonoids, phenolic acids, vitamin E (VE), glutelin, phytosterols, and phytic acid (PA). It also contains large amounts of micronutrients such as Ca, Fe, Zn, and Se[19], and has a much higher nutritional and health value than ordinary white rice. In addition, Zhu et al.[20] successfully developed rice with enriched astaxanthin in the endosperm by introducing the genes sZmPSY1, sPaCrtI, sCrBKT, and sHpBHY. This achievement has laid a solid foundation for the further development of functional rice industry.

    Giant embryo rice

    Giant embryo rice refers to rice varieties whose embryo volume is more than twice that of ordinary rice[21]. Rice embryo contains more nutrients than the endosperm; therefore, the nutritional value of giant embryo rice greatly exceeds that of ordinary rice. Studies have found that the levels of γ-aminobutyric acid (GABA), essential amino acids, VE, γ-oryzanol, phenols, and trace elements in giant embryo rice are considerably higher than that in ordinary rice[21]. Satoh & Omura[22] used the chemical mutagen N-methyl-N-nitrosourea to treat the fertilized egg cells of the rice variety Kinmaze to obtain a 'giant embryo' mutant. The mutants’ embryo occupied 1/4–1/3 of the rice grain volume and was 3–4 times larger than normal rice embryo[23]. Its GABA content increased dramatically after the rice was soaked in water. Maeda et al.[24] crossed the giant embryo mutant EM40 of Kinmaze with the high-yielding variety Akenohoshi to produce the giant embryo rice variety 'Haiminori'. The embryo size of 'Haiminori' is 3–4 times that of ordinary rice, and the GABA content of its brown rice is 3–4 times higher than that of 'Nipponbare' and 'Koshihikari' after soaking for four hours in water. A few genes that can regulate the size of rice embryos have been identified, and GE is the first identified rice giant embryo gene[25]. Nagasawa et al.[26] found that the loss of GE gene function resulted in enlarged embryos and smaller endosperm in rice. Lee et al.[27] found that the inhibition of LE gene expression by RNAi technology could lead to embryo enlargement in rice, but the regulatory mechanism remains to be investigated.

    Low glutelin rice

    Protein is the second most crucial nutrient in rice, accounting for 7–10% of the grain weight, and glutenin accounts for 60%–80% of the total protein content in rice grains[28]. Compared to other proteins, glutenin is more easily digested and absorbed by the body[29]. Therefore, higher glutenin content in rice can improve its nutritional value. However, people with renal disease (a common complication of diabetes) have impaired protein metabolism, and consumption of rice with lower glutelin content can help reduce their protein intake and metabolic burden[30]. Japanese breeders treated Nihonmasari with the chemical mutagen ethyleneimine and selected the low-glutelin rice mutant NM67[31]. Iida et al.[31] developed a new rice variety LGC-1 (Low glutelin content-1) with a glutelin content of less than 4% by backcrossing the NM67 mutant with the original variety 'Nihonmasari'. According to Miyahara[32], the low glutelin trait in LGC-1 is controlled by a single dominant gene Lgc-1 located on chromosome 2. Subsequently, Nishimura et al.[33] produced two rice varieties, 'LGC Katsu' and 'LGC Jun' with lower glutelin content by crossing LGC1 with a mutant line Koshikari (γ-ray induction) lacking 26 kDa globulin (another easily digestible protein).

    Golden rice

    Vitamin A (VA) is one of the essential nutrients for the human body[34]. However, rice, a staple food, lacks VA, leading to a VA deficiency in many people. β-carotene is a precursor for VA synthesis and can be effectively converted into VA in the human body[35]. Therefore, breeding rice varieties rich in β-carotene has attracted the attention of breeders in various countries. Ye et al.[36] simultaneously transferred phytoene synthase (psy), phytoene desaturase (crt I), and lycopene β-cyclase (lcy) genes into rice using the Agrobacterium-mediated method and produced the first generation of golden rice with a β-carotene content of 1.6 µg·g−1 in the endosperm. However, due to the low content of β-carotene in rice, it is difficult to meet the human body's demand for VA. To increase β-carotene content in rice, Paine et al.[37] introduced the phytoene synthase (psy) gene from maize and the phytoene desaturase (crt I) gene from Erwinia into rice. They obtained the second generation of golden rice with 37 µg g−1 of β-carotene in the endosperm, with nearly 23-fold increase in β-carotene content compared to the first generation of golden rice.

    Fe and Zn fortified rice

    Fe and Zn are essential trace elements for human beings. The contents of Fe and Zn in common rice are about 2 μg·g−1 and 16 μg·g−1, respectively[38], which are far from meeting human needs. In 2004, to alleviate micronutrient deficiencies among underprivileged people in developing countries, the Consultative Group on International Agricultural Research launched the HarvestPlus international collaborative program for improving Fe, Zn, and β-carotene levels in staple crops, with breeding targets of 13 μg·g−1 and 28 μg·g−1 for Fe and Zn in rice, respectively. Masuda et al.[39] found that expression of the nicotianamine synthase (NAS) gene HvNAS in rice resulted in a 3-fold increase in Fe and a 2-fold increase in Zn content in polished rice. Trijatmiko et al.[38] overexpressed rice OsNAS2 gene and soybean ferritin gene SferH-1 in rice, and the Fe and Zn content in polished rice of rice variety NASFer-274 reached 15 μg·g−1 and 45.7 μg·g−1, respectively. In addition, it has been found that increasing Fe intake alone does not eliminate Fe deficiency but also decreases the amount of Fe absorption inhibitors in the diet or increases the amount of Fe absorption enhancers[40]. The negatively charged phosphate in PA strongly binds metal cations, thus reducing the bioavailability of Fe and Zn in rice[41], while the sulfhydryl group in cysteine binds Fe, thereby increasing the absorption of non-heme Fe by the body[42]. To improve the bioavailability of Fe and Zn, Lucca et al.[40] introduced a heat-tolerant phytase (phyA) gene from Aspergillus fumigatus into rice and overexpressed the cysteine-rich protein gene (rgMT), which increased the content of phytase and cysteine residues in rice by 130-fold and 7-fold, respectively[40].

    Breeding technology of functional rice

    The functional quality of rice is highly dependent on germplasm resources. Current functional rice breeding mainly adopts transgenic and mutagenic technologies, and the cultivated rice varieties are mainly enriched with only one functional substance and cannot meet the urgent demand by consumers for rice enriched with multiple active components. The diversity of rice active components determines the complexity of multifunctional rice breeding. In order to cultivate multifunctional rice, it is necessary to strengthen the application of different breeding technologies. Gene polymerization breeding is a crop breeding technology that can polymerize multiple superior traits that have emerged in recent years, mainly including traditional polymerization breeding, transgenic polymerization breeding, and molecular marker-assisted selection polymerization breeding.

    Traditional polymerization breeding

    The transfer of beneficial genes in different species during traditional polymeric breeding is largely limited by interspecific reproductive isolation, and it is challenging to utilize beneficial genes between different species effectively. Gene transfer through sexual crosses does not allow accurate manipulation and selection of a gene and is susceptible to undesirable gene linkage, and in the process of breed selection, multiple backcrosses are required[43]. Thus, the period of selecting target plants is long, the breeding cost is high, and the human resources and material resources are costly[44]. Besides, it is often difficult to continue the breakthrough after a few generations of backcrossing due to linkage drag. Thus, there are significant limitations in aggregating genes by traditional breeding methods[45].

    Transgenic polymerization breeding

    Transgenic technology is an effective means of gene polymerization breeding. Multi-gene transformation makes it possible to assemble multiple beneficial genes in transgenic rice breeding rapidly and can greatly reduce the time and workload of breeding[46]. The traditional multi-gene transformation uses a single gene transformation and hybridization polymerization method[47], in which the vector construction and transformation process is relatively simple. However, it is time-consuming, laborious, and requires extensive hybridization and screening efforts. Multi-gene-based vector transformation methods can be divided into two major categories: multi-vector co-transformation and multi-gene single vector transformation[47]. Multi-vector co-transformation is the simultaneous transfer of multiple target genes into the same recipient plant through different vectors. The efficiency of multi-vector co-transformation is uncertain, and the increase in the number of transforming vectors will increase the difficulty of genetic screening, resulting in a reduced probability of obtaining multi-gene co-transformed plants. Multi-gene single vector transformation constructs multiple genes into the T-DNA region of a vector and then transfers them into the same recipient plant as a single event. This method eliminates the tedious hybridization and backcrossing process and solves the challenges of low co-transformation frequency and complex integration patterns. It can also avoid gene loss caused by multi-gene separation and recombination in future generations[47]. The transgenic method can break through the limitations of conventional breeding, disrupt reproductive isolation, transfer beneficial genes from entirely unrelated crops to rice, and shorten the cycle of polymerizing target genes significantly. However, there are concerns that when genes are manipulated, unforeseen side effects may occur, and, therefore, there are ongoing concerns about the safety of transgenic crops[48]. Marker-free transgenic technology through which selective marker genes in transgenic plants can be removed has been developed. This improves the safety of transgenic crops, is beneficial to multiple operations of the same transgenic crop, and improves the acceptance by people[49].

    Molecular marker-assisted selection polymerization breeding

    Molecular marker-assisted selection is one of the most widely used rice breeding techniques at present. It uses the close linkage between molecular markers and target genes to select multiple genes directly and aggregates genes from different sources into one variety. This has multiple advantages, including a focused purpose, high accuracy, short breeding cycle, no interference from environmental conditions, and applicability to complex traits[50]. However, few genes have been targeted for the main effect of important agronomic traits in rice, and they are mainly focused on the regulation of rice plant type and the prevention and control of pests and diseases, and very few genes related to the synthesis of active components, which can be used for molecular marker-assisted selection are very limited. Furthermore, the current technical requirements and costs for analyzing and identifying DNA molecular markers are high, and the identification efficiency is low. This greatly limits the popularization and application of functional rice polymerization breeding. Therefore, to better apply molecular marker-assisted selection technology to breed rice varieties rich in multiple active components, it is necessary to construct a richer molecular marker linkage map to enhance the localization of genes related to functional substance synthesis in rice[51]. Additionally, it is important to explore new molecular marker technologies to improve efficiency while reducing cost.

    It is worth noting that the effects of gene aggregation are not simply additive. There are cumulative additive effects, greater than cumulative epistatic effects, and less than cumulative epistatic effects among the polymerization genes, and the effects are often smaller than the individual effect. Only with a clearer understanding of the interaction between different QTLs or genes can functional rice pyramiding breeding be carried out reasonably and efficiently. Except for RS and Se, other active components of rice mainly exist in the rice bran layer, and the content of active components in the endosperm, the main edible part, is extremely low. Therefore, cultivating rice varieties with endosperm-enriched active components have broad development prospects. In addition, because crops with high quality are more susceptible to pests and diseases[52], the improvement of rice resistance to pests and diseases should be considered during the polymerization breeding of functional rice.

    Cultivation and regulation technology of functional rice

    The biosynthesis of active components in rice is influenced by rice varieties but also depends on cultivation management practices and their growth environment.

    Effect of light on the accumulation of active components in rice

    Environmental conditions have a greater effect on protein content than genetic forces[53]. Both light intensity and light duration affect the synthesis and accumulation of active components in rice. Low light intensity in the early stage of rice growth is not conducive to the accumulation of glutelin in rice grains but favors the accumulation of amylose, while the opposite is true in the late stage of rice growth[54]. Low light intensity during the grain-filling period reduces the accumulation of total flavonoids in rice[55] and decreases Fe ions' movement in the transpiration stream and thereby the transport of Fe ions to rice grains[56]. An appropriate increase in light intensity is beneficial to the accumulation of flavonoids, anthocyanins, and Fe in rice, but the photostability of anthocyanins is poor, and too much light will cause oxidative degradation of anthocyanins[57]. Therefore, functional rice is best cultivated as mid-late rice, which would be conducive to accumulating active components in rice.

    Effect of temperature on the accumulation of active components in rice

    The temperature has a great influence on the synthesis of active components in rice. An appropriate increase in the temperature is beneficial to the accumulation of γ-oryzanol[58] and flavonoids[59] in rice. A high temperature during the grain-filling period leads to an increase in glutelin content in rice[60], but an increase in temperature decreases the total phenolic content[61]. The results regarding the effect of temperature on the content of PA in rice were inconsistent. Su et al.[62] showed that high temperatures during the filling period would increase the PA content, while Goufo & Trindade[61] reported that the increase in temperature would reduce the PA content. This may be due to the different growth periods and durations of temperature stress on rice in the two studies. The synthesis of anthocyanins/proanthocyanidins in colored rice requires a suitable temperature. Within a certain range, lower temperatures favor the accumulation of anthocyanins/proanthocyanidins in rice[63]. Higher temperatures will lead to degradation, and the thermal stability of proanthocyanidins being higher than that of anthocyanins[64]. In addition, cold or heat stress facilitates GABA accumulation in rice grains[65]. Therefore, in actual production, colored rice and low-glutelin rice are best planted as late rice, and the planting time of other functional rice should be determined according to the response of its enriched active components to temperature changes.

    Effect of water management on the accumulation of active components in rice

    Moderate water stress can significantly increase the content of glutelin[66] and GABA[67] in rice grains and promote the rapid transfer of assimilation into the grains, shorten the grain filling period, and reduce the RS content[68]. Drought stress can also induce the expression of the phytoene synthase (psy) gene and increase the carotenoid content in rice[69]. Soil moisture is an important medium in Zn diffusion to plant roots. In soil with low moisture content, rice roots have low available Zn, which is not conducive to enriching rice grains with Zn[70]. Results from studies on the effect of soil water content on Se accumulation in rice grains have been inconsistent. Li et al.[71] concluded that flooded cultivation could significantly increase the Se content in rice grains compared to dry cultivation. However, the results of Zhou et al.[72] showed that the selenium content in rice grains under aerobic and dry-wet alternative irrigation was 2.44 and 1.84 times higher than that under flood irrigation, respectively. This may be due to the forms of selenium contained in the soil and the degree of drought stress to the rice that differed between experiments[73]. In addition, it has been found that too much or too little water impacts the expression of genes related to anthocyanin synthesis in rice, which affects the accumulation of anthocyanins in rice[74]. Therefore, it is recommended to establish different irrigation systems for different functional rice during cultivation.

    Effect of fertilizer application on the accumulation of active components in rice

    Both the amount and method of nitrogen application affect the accumulation of glutelin. Numerous studies have shown that both increased and delayed application of nitrogen fertilizer can increase the accumulation of lysine-rich glutelin to improve the nutritional quality of rice (Table 1). However, this improvement is not beneficial for kidney disease patients who cannot consume high glutelin rice. Nitrogen stress can down-regulate the expression of ANDs genes related to the anthocyanins biosynthesis pathway in grains, resulting in a decrease in anthocyanins synthesis[55]. Increased nitrogen fertilizer application can also increase the Fe, Zn, and Se content in rice[75,76]. However, some studies have found that increased nitrogen fertilizer application has no significant effect on the Fe content of rice[77], while other studies have shown that increased nitrogen fertilizer application will reduce the Fe content of rice[78]. This may be influenced by soil pH and the form of the applied nitrogen fertilizer. The lower the soil pH, the more favorable the reduction of Fe3+ to Fe2+, thus promoting the uptake of Fe by rice. Otherwise, the application of ammonium fertilizer can improve the availability of soil Fe and promote the absorption and utilization of Fe by rice. In contrast, nitrate fertilizer can inhibit the reduction of Fe3+ and reduce the absorption of Fe by rice[79].

    Table 1.  Effect of nitrogen fertilizer application on glutelin content of rice.
    SampleN level
    (kg ha−1)    		Application timeGlutelin content
    (g 100 g−1)    		References
    Rough rice05.67[66]
    270Pre-transplanting : mid tillering : panicle initiation : spikelet differentiation = 2:1:1:16.92
    300Pre-transplanting : mid tillering : panicle initiation : spikelet differentiation = 5:2:2:16.88
    Brown rice05.35[83]
    90Pre-transplanting : after transplanting = 4:16.01
    Pre-transplanting : after transplanting = 1:16.60
    180Pre-transplanting : after transplanting = 4:16.53
    Pre-transplanting : after transplanting = 1:17.29
    270Pre-transplanting : after transplanting = 4:17.00
    Pre-transplanting : after transplanting = 1:17.66
    Rough rice05.59[84]
    187.5Pre-transplanting : after transplanting = 4:16.47
    Pre-transplanting : after transplanting = 1:16.64
    300Pre-transplanting : after transplanting = 4:17.02
    Pre-transplanting : after transplanting = 1:17.14
    Polished rice03.88[85]
    90Pre-transplanting : tillering : booting = 2:2:14.21
    180Pre-transplanting : tillering : booting = 2:2:14.43
    270Pre-transplanting : tillering : booting = 2:2:16.42
    360Pre-transplanting : tillering : booting = 2:2:14.87
    Brown rice09.05[86]
    120Flowering22.14
     | Show Table
    DownLoad: CSV

    Appropriate application of phosphorus fertilizer is beneficial in promoting the translocation of Fe and Zn from leaves to rice grains, thus increasing the content in rice grains[80]. However, the excessive application of phosphate fertilizer will reduce the availability of Fe and Zn in soil, resulting in less uptake by the roots and a lower content in the rice grains[81]. The content of PA in rice increased with a higher phosphorus fertilizer application rate[80]. Increasing the phosphorus fertilizer application rate would increase the values of [PA]/[Fe] and [PA]/[Zn] and reduce the effectiveness of Fe and Zn in rice[80]. Currently, there are few studies on the effect of potassium fertilization on the synthesis of active components in rice. Available studies report that increased application of nitrogen fertilizer can increase the Zn content in rice[82]. Therefore, the research in this area needs to be strengthened.

    Because the iron in soil mainly exists in the insoluble form Fe3+, the application of iron fertilizer has little effect on rice biofortification[87]. There are different opinions about the effect of Zn fertilizer application methods. Phattarakul et al.[88] believed that foliar spraying of Zn fertilizer could significantly improve the Zn content in rice grains. Jiang et al.[89] concluded that most of the Zn accumulated in rice grains were absorbed by the roots rather than from the reactivation of Zn in leaves. In contrast, Yuan et al.[90] suggested that soil application of Zn fertilizer had no significant effect on Zn content in rice grains. The different results may be affected by the form of zinc fertilizer applied and the soil conditions in the experimental sites. Studies have found that compared with the application of ZnEDTA and ZnO, zinc fertilizer in the form of ZnSO4 is most effective for increasing rice's Zn[70]. In addition, the application of zinc fertilizer reduces the concentration of PA in rice grains[70].

    The form of selenium fertilizer and the method and time of application will affect the accumulation of Se in rice grains. Regarding selenium, rice is a non-hyperaccumulative plant. A moderate application of selenium fertilizer can improve rice yield. However, the excessive application can be toxic to rice, and the difference between beneficial and harmful supply levels is slight[91]. Selenite is readily adsorbed by iron oxide or hydroxide in soil, and its effectiveness in the soil is much lower than selenite[92]. In addition, selenate can migrate to the roots and transfer to rice shoots through high-affinity sulfate transporters. In contrast, selenite is mainly assimilated into organic selenium in the roots and transferred to the shoots in smaller amounts[93]. Therefore, the biological effectiveness of Se is higher in selenate-applied soil than in selenite application[94] (Table 2). Zhang et al.[95] found that the concentration of Se in rice with soil application of 100 g Se ha-1 was only 76.8 μg·kg-1, while the concentration of Se in rice with foliar spray of 75 g Se ha-1 was as high as 410 μg·kg-1[73]. However, the level of organic selenium was lower in rough rice with foliar application of selenium fertilizer compared to soil application[96], while the bioavailability of organic selenium in humans was higher than inorganic selenium[97]. Deng et al.[73] found that the concentrations of total selenium and organic selenium in brown rice with selenium fertilizer applied at the full heading stage were 2-fold higher than those in brown rice with selenium fertilizer applied at the late tillering stage (Table 2). Although the application of exogenous selenium fertilizer can rapidly and effectively increase the Se content of rice (Table 2), it can easily lead to excessive Se content in rice and soil, which can have adverse effects on humans and the environment. Therefore, breeding Se-rich rice varieties is a safer and more reliable way to produce Se-rich rice. In summary, functional rice production should include the moderate application of nitrogen and phosphorus fertilizer and higher levels of potassium fertilizer, with consideration to the use of trace element fertilizers.

    Table 2.  Effect of selenium fertilizer application on the selenium content of rice.
    SampleSe level (g Se ha−1)Selenium fertilizer formsApplication methodSe content (μg·g−1)References
    Rough rice00.002[98]
    18SeleniteFoliar spray at full heading0.411
    Polished rice00.071[99]
    20SeleniteFoliar spray at full heading0.471
    20SelenateFoliar spray at full heading0.640
    Rough rice75SeleniteFoliar spray at late tillering0.440[73]
    75SeleniteFoliar spray at full heading1.290
    75SelenateFoliar spray at late tillering0.780
    75SelenateFoliar spray at full heading2.710
    Polished rice00.027[100]
    15SeleniteFoliar spray at full heading0.435
    45SeleniteFoliar spray at full heading0.890
    60SeleniteFoliar spray at full heading1.275
     | Show Table
    DownLoad: CSV

    Effect of harvesting time on the accumulation of active components in rice

    The content of many active components in rough rice is constantly changing during the development of rice. It was found that the content of total flavonoids in brown rice increased continuously from flowering stage to dough stage and then decreased gradually[101]. The γ-oryzanol content in rice decreased by 13% from milk stage to dough stage, and then gradually increased to 60% higher than milk stage at full maturity[101]. The results of Shao et al.[102] showed that the anthocyanin content in rice reached its highest level at two weeks after flowering and then gradually decreased. At full ripeness, and the anthocyanins content in brown rice was only about 50% of the maximum level. The content of total phenolics in rice decreased with maturity from one week after flowering to the fully ripe stage, and the loss of total phenolics reached more than 47% by the fully ripe stage. In contrast, the content of total phenolics in black rice increased with maturity[102]. Moreover, RS content in rough rice decreases during rice maturation[68]. Therefore, the production process of functional rice should be timely and early harvested to obtain higher economic value.

    Prevention and control of pests and diseases for functional rice

    Pests and diseases seriously impact the yield and quality of rice[103]. At present, the two most effective methods to control pests and diseases are the use of chemical pesticides and the planting of pest and disease-resistant rice varieties. The use of chemical pesticides has greatly reduced the yield loss of rice. However, excessive use of chemical pesticides decreases soil quality, pollutes the environment, reduces soil biodiversity[104], increases pest resistance, and aggravates the adverse effects of pests and diseases on rice production[105]. It also increases residual pesticide levels in rice, reduces rice quality, and poses a severe threat to human health[106].

    Breeding pest and disease-resistant rice varieties are among the safest and effective ways to control rice pests and diseases[107]. In recent years, many pest and disease resistance genes from rice and microorganisms have been cloned[47]. Researchers have used these genes to breed rice varieties resistant to multiple pests and diseases through gene polymerization breeding techniques. Application in production practices delivered good ecological and economic benefits[108].

    Green pest and disease control technologies must consider the synergies between rice and water, fertilizer, and pest and disease management. In this regard, the rice-frog, rice-duck, and other comprehensive rice production models that have been widely used in recent years are the most representative. These rice production models significantly reduced chemical pesticide usage and effectively controlled rice pests and diseases[109]. The nutritional imbalance will reduce the resistance of rice to pests and diseases[110]. Excessive application of nitrogen fertilizer stimulates rice overgrowth, protein synthesis, and the release of hormones, increasing its attractiveness to pests[111]. Increased soluble protein content in rice leaves is more conducive to virus replication and increases the risk of viral infection[112]. Increasing the available phosphorus content in the soil will increase crop damage by pests[113], while insufficient potassium supply will reduce crop resistance to pests and diseases[114]. The application of silica fertilizer can boost the defense against pests and diseases by increasing silicon deposition in rice tissue, inducing the expression of genes associated with rice defense mechanisms[115] and the accumulation of antifungal compounds in rice tissue[116]. The application of silica fertilizer increases the release of rice volatiles, thereby attracting natural enemies of pests and reducing pest damage[117]. Organic farming increases the resistance of rice to pests and diseases[118]. In addition, rice intercropping with different genotypes can reduce pests and diseases through dilution and allelopathy and changing field microclimate[119].

    In conclusion, the prevention and control of rice pests and diseases should be based on chemical and biological control and supplemented by fertilizer management methods such as low nitrogen, less phosphorus, high potassium and more silicon, as well as agronomic measures such as rice-aquaculture integrated cultivation, organic cultivation and intercropping of different rice varieties, etc. The combined use of multiple prevention and control measures can improve the yield and quality of functional rice.

    Conclusions

    Functional rice contains many active components which are beneficial to maintaining human health and have high economic and social value with broad market prospects. However, the current development level of the functional rice industry is low. The development of the functional rice requires extensive use of traditional and modern polymerization breeding techniques to cultivate new functional rice varieties with endosperm that can be enriched with multiple active components and have broad-spectrum resistance to pests and diseases. It is also important to select suitable planting locations and times according to the response characteristics of different functional rice active components to environmental conditions.

    Acknowledgments

    This work is supported by the National Natural Science Foundation of China (Project No. 32060430 and 31971840), and Research Initiation Fund of Hainan University (Project No. KYQD(ZR)19104).

  • The authors declare that they have no conflict of interest.

  • [1]

    Sanderson MA, Adler PR. 2008. Perennial forages as second generation bioenergy crops. International journal of molecular sciences 9:768−88

    doi: 10.3390/ijms9050768

    CrossRef   Google Scholar

    [2]

    Perlack RD, Wright LL, Turhollow AF, Graham RL, Stokes BJ, et al. 2005. Biomass as feedstock for a bioenergy and bioproducts industry: the technical feasibility of a billion-ton annual supply. Technical Report. ORNL/TM-2005/66, Oak Ridge National Laboratory, Oak Ridge, Tennessee. www.osti.gov/biblio/1216415
    [3]

    Naik SN, Goud VV, Rout PK, Dalai AK. 2010. Production of first and second generation biofuels: a comprehensive review. Renewable and Sustainable Energy Reviews 14:578−97

    doi: 10.1016/j.rser.2009.10.003

    CrossRef   Google Scholar

    [4]

    Jørgensen H, Kristensen JB, Felby C. 2007. Enzymatic conversion of lignocellulose into fermentable sugars: challenges and opportunities. Biofuels, Bioproducts and Biorefining 1:119−34

    doi: 10.1002/bbb.4

    CrossRef   Google Scholar

    [5]

    Sun Y, Cheng J. 2002. Hydrolysis of lignocellulosic materials for ethanol production: a review. Bioresource Technology 83:1−11

    doi: 10.1016/S0960-8524(01)00212-7

    CrossRef   Google Scholar

    [6]

    Lovell JT, MacQueen AH, Mamidi S, Bonnette J, Jenkins J, et al. 2021. Genomic mechanisms of climate adaptation in polyploid bioenergy switchgrass. Nature 590:438−44

    doi: 10.1038/s41586-020-03127-1

    CrossRef   Google Scholar

    [7]

    Porter CL Jr. 1966. An analysis of variation between upland and lowland switchgrass, Panicum virgatum L., in central Oklahoma. Ecology 47:980−92

    doi: 10.2307/1935646

    CrossRef   Google Scholar

    [8]

    Wullschleger SD, Davis EB, Borsuk ME, Gunderson CA, Lynd LR. 2010. Biomass production in switchgrass across the United States: database description and determinants of yield. Agronomy Journal 102:1158−68

    doi: 10.2134/agronj2010.0087

    CrossRef   Google Scholar

    [9]

    McLaughlin SB, Adams Kszos L. 2005. Development of switchgrass (Panicum virgatum) as a bioenergy feedstock in the United States. Biomass and Bioenergy 28:515−35

    doi: 10.1016/j.biombioe.2004.05.006

    CrossRef   Google Scholar

    [10]

    Bouton JH. 2007. Molecular breeding of switchgrass for use as a biofuel crop. Current opinion in genetics & development 17:553−58

    doi: 10.1016/j.gde.2007.08.012

    CrossRef   Google Scholar

    [11]

    Sanderson MA, Reed RL, McLaughlin SB, Wullschleger SD, Conger BV, et al. 1996. Switchgrass as a sustainable bioenergy crop. Bioresource Technology 56:83−93

    doi: 10.1016/0960-8524(95)00176-X

    CrossRef   Google Scholar

    [12]

    McLaughlin S, Bouton J, Bransby D, Conger B, Ocumpaugh W, et al. 1999. Developing switchgrass as a bioenergy crop. In Perspectives on New Crops and New Uses, ed. Janick J. vol 282. Alexandria, VA: ASHS Press. pp. 282-99. www.researchgate.net/profile/W-Ocumpaugh-2/publication/47649519_Developing_Switchgrass_as_a_Bioenergy_Crop/links/54ca74970cf2c70ce521d8e5/Developing-Switchgrass-as-a-Bioenergy-Crop.pdf
    [13]

    Hopkins AA, Vogel KP, Moore KJ. 1993. Predicted and realized gains from selection for in vitro dry matter digestibility and forage yield in switchgrass. Crop Science 33:253−58

    doi: 10.2135/cropsci1993.0011183X003300020007x

    CrossRef   Google Scholar

    [14]

    Taliaferro CM, Hopkins A. 2002. Breeding and selection of new switchgrass varieties for increased biomass production. Technical Report. ORNL/SUB-02-19XSY162C/01, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA. www.osti.gov/biblio/814564/
    [15]

    Sanderson MA, Adler PR, Boateng AA, Casler MD, Sarath G. 2006. Switchgrass as a biofuels feedstock in the USA. Canadian Journal of Plant Science 86:1315−25

    doi: 10.4141/P06-136

    CrossRef   Google Scholar

    [16]

    Xu B, Escamilla-Treviño LL, Sathitsuksanoh N, Shen Z, Shen H, et al. 2011. Silencing of 4-coumarate: coenzyme A ligase in switchgrass leads to reduced lignin content and improved fermentable sugar yields for biofuel production. The New Phytologist 192:611−25

    doi: 10.1111/j.1469-8137.2011.03830.x

    CrossRef   Google Scholar

    [17]

    Fu C, Xiao X, Xi Y, Ge Y, Chen F, et al. 2011. Downregulation of cinnamyl alcohol dehydrogenase (CAD) leads to improved saccharification efficiency in switchgrass. BioEnergy Research 4:153−64

    doi: 10.1007/s12155-010-9109-z

    CrossRef   Google Scholar

    [18]

    Saathoff AJ, Sarath G, Chow EK, Dien BS, Tobias CM. 2011. Downregulation of cinnamyl-alcohol dehydrogenase in switchgrass by RNA silencing results in enhanced glucose release after cellulase treatment. PloS One 6:e16416

    doi: 10.1371/journal.pone.0016416

    CrossRef   Google Scholar

    [19]

    Fu C, Mielenz JR, Xiao X, Ge Y, Hamilton CY, et al. 2011. Genetic manipulation of lignin reduces recalcitrance and improves ethanol production from switchgrass. Proceedings of the National Academy of Sciences, USA 108:3803−8

    doi: 10.1073/pnas.1100310108

    CrossRef   Google Scholar

    [20]

    Xu B, Huang L, Shen Z, Welbaum GE, Zhang X, et al. 2011. Selection and characterization of a new switchgrass (Panicum virgatum L.) line with high somatic embryogenic capacity for genetic transformation. Scientia Horticulturae 129:854−61

    doi: 10.1016/j.scienta.2011.05.016

    CrossRef   Google Scholar

    [21]

    Mele G, Ori N, Sato Y, Hake S. 2003. The knotted1-like homeobox gene BREVIPEDICELLUS regulates cell differentiation by modulating metabolic pathways. Genes & Development 17:2088−93

    doi: 10.1101/gad.1120003

    CrossRef   Google Scholar

    [22]

    Kubo M, Udagawa M, Nishikubo N, Horiguchi G, Yamaguchi M, et al. 2005. Transcription switches for protoxylem and metaxylem vessel formation. Genes & Development 19:1855−60

    doi: 10.1101/gad.1331305

    CrossRef   Google Scholar

    [23]

    Zhong R, Demura T, Ye Z. 2006. SND1, a NAC domain transcription factor, is a key regulator of secondary wall synthesis in fibers of Arabidopsis. The Plant Cell 18:3158−70

    doi: 10.1105/tpc.106.047399

    CrossRef   Google Scholar

    [24]

    Zhong R, Ye Z. 2009. Transcriptional regulation of lignin biosynthesis. Plant Signaling & Behavior 4:1028−34

    doi: 10.4161/psb.4.11.9875

    CrossRef   Google Scholar

    [25]

    Wuddineh WA, Mazarei M, Zhang J, Turner GB, Sykes RW, et al. 2016. Identification and overexpression of a Knotted1-like transcription factor in switchgrass (Panicum virgatum L.) for lignocellulosic feedstock improvement. Frontiers in Plant Science 7:520

    doi: 10.3389/fpls.2016.00520

    CrossRef   Google Scholar

    [26]

    Aharoni A, Dixit S, Jetter R, Thoenes E, van Arkel G, et al. 2004. The SHINE clade of AP2 domain transcription factors activates wax biosynthesis, alters cuticle properties, and confers drought tolerance when overexpressed in Arabidopsis. The Plant Cell 16:2463−80

    doi: 10.1105/tpc.104.022897

    CrossRef   Google Scholar

    [27]

    Shi JX, Adato A, Alkan N, He Y, Lashbrooke J, et al. 2013. The tomato SlSHINE3 transcription factor regulates fruit cuticle formation and epidermal patterning. The New phytologist 197:468−80

    doi: 10.1111/nph.12032

    CrossRef   Google Scholar

    [28]

    Meng S, Cao Y, Li H, Bian Z, Wang D, et al. 2019. PeSHN1 regulates water-use efficiency and drought tolerance by modulating wax biosynthesis in poplar. Tree Physiology 39:1371−86

    doi: 10.1093/treephys/tpz033

    CrossRef   Google Scholar

    [29]

    Djemal R, Khoudi H. 2016. TdSHN1, a WIN1/SHN1-type transcription factor, imparts multiple abiotic stress tolerance in transgenic tobacco. Environmental and Experimental Botany 131:89−100

    doi: 10.1016/j.envexpbot.2016.07.005

    CrossRef   Google Scholar

    [30]

    Martins APB, dos Santos Brito M, Mayer JLS, Llerena JPP, Oliveira JF, et al. 2018. Ectopic expression of sugarcane SHINE changes cell wall and improves biomass in rice. Biomass and Bioenergy 119:322−34

    doi: 10.1016/j.biombioe.2018.09.036

    CrossRef   Google Scholar

    [31]

    Yang Y, Shi J, Chen L, Xiao W, Yu J. 2022. ZmEREB46, a maize ortholog of Arabidopsis WAX INDUCER1/SHINE1, is involved in the biosynthesis of leaf epicuticular very-long-chain waxes and drought tolerance. Plant Science 321:111256

    doi: 10.1016/j.plantsci.2022.111256

    CrossRef   Google Scholar

    [32]

    Ambavaram MMR, Krishnan A, Trijatmiko KR, Pereira A. 2011. Coordinated activation of cellulose and repression of lignin biosynthesis pathways in rice. Plant Physiology 155:916−31

    doi: 10.1104/pp.110.168641

    CrossRef   Google Scholar

    [33]

    Liu Y, Wei M, Hou C, Lu T, Liu L, et al. 2017. Functional characterization of populus PsnSHN2 in coordinated regulation of secondary wall components in tobacco. Scientific Reports 7:42

    doi: 10.1038/s41598-017-00093-z

    CrossRef   Google Scholar

    [34]

    Bres C, Petit J, Reynoud N, Brocard L, Marion D, et al. 2022. The SlSHN2 transcription factor contributes to cuticle formation and epidermal patterning in tomato fruit. Molecular Horticulture 2:14

    doi: 10.1186/s43897-022-00035-y

    CrossRef   Google Scholar

    [35]

    Xu B, Sathitsuksanoh N, Tang Y, Udvardi MK, Zhang J, et al. 2012. Overexpression of AtLOV1 in switchgrass alters plant architecture, lignin content, and flowering time. PLoS One 7:e47399

    doi: 10.1371/journal.pone.0047399

    CrossRef   Google Scholar

    [36]

    Shen H, Poovaiah CR, Ziebell A, Tschaplinski TJ, Pattathil S, et al. 2013. Enhanced characteristics of genetically modified switchgrass (Panicum virgatum L.) for high biofuel production. Biotechnology for Biofuels 6:71

    doi: 10.1186/1754-6834-6-71

    CrossRef   Google Scholar

    [37]

    Wuddineh WA, Mazarei M, Turner GB, Sykes RW, Decker SR, et al. 2015. Identification and molecular characterization of the switchgrass AP2/ERF transcription factor superfamily, and overexpression of PvERF001 for improvement of biomass characteristics for biofuel. Frontiers in Bioengineering and Biotechnology 3:101

    doi: 10.3389/fbioe.2015.00101

    CrossRef   Google Scholar

    [38]

    Jiang F, Guo M, Yang F, Duncan K, Jackson D, et al. 2012. Mutations in an AP2 transcription factor-like gene affect internode length and leaf shape in maize. PLoS One 7:e37040

    doi: 10.1371/journal.pone.0037040

    CrossRef   Google Scholar

    [39]

    Molina A, Miedes E, Bacete L, Rodríguez T, Mélida H, et al. 2021. Arabidopsis cell wall composition determines disease resistance specificity and fitness. Proceedings of the National Academy of Sciences 118:e2010243118

    doi: 10.1073/pnas.2010243118

    CrossRef   Google Scholar

    [40]

    Buxdorf K, Rubinsky G, Barda O, Burdman S, Aharoni A, Levy M. 2014. The transcription factor SlSHINE3 modulates defense responses in tomato plants. Plant molecular biology 84:37−47

    doi: 10.1007/s11103-013-0117-1

    CrossRef   Google Scholar

    [41]

    Al-Abdallat AM, Al-Debei HS, Ayad JY, Hasan S. 2014. Over-expression of SlSHN1 gene improves drought tolerance by increasing cuticular wax accumulation in tomato. International journal of molecular sciences 15:19499−515

    doi: 10.3390/ijms151119499

    CrossRef   Google Scholar

    [42]

    Ching A, Dhugga KS, Appenzeller L, Meeley R, Bourett TM, et al. 2006. Brittle stalk 2 encodes a putative glycosylphosphatidylinositol-anchored protein that affects mechanical strength of maize tissues by altering the composition and structure of secondary cell walls. Planta 224:1174−84

    doi: 10.1007/s00425-006-0299-8

    CrossRef   Google Scholar

    [43]

    Wan G, Frazier T, Jorgensen J, Zhao B, Frazier CE. 2018. Rheology of transgenic switchgrass reveals practical aspects of biomass processing. Biotechnology for Biofuels 11:57

    doi: 10.1186/s13068-018-1056-5

    CrossRef   Google Scholar

    [44]

    Li R, Qu R. 2011. High throughput Agrobacterium-mediated switchgrass transformation. Biomass and Bioenergy 35:1046−54

    doi: 10.1016/j.biombioe.2010.11.025

    CrossRef   Google Scholar

    [45]

    Porebski S, Bailey LG, Baum BR. 1997. Modification of a CTAB DNA extraction protocol for plants containing high polysaccharide and polyphenol components. Plant Molecular Biology Reporter 15:8−15

    doi: 10.1007/BF02772108

    CrossRef   Google Scholar

    [46]

    Pradhan Mitra P, Loqué D. 2014. Histochemical staining of Arabidopsis thaliana secondary cell wall elements. Journal of Visualized Experiments:e51381

    doi: 10.3791/51381

    CrossRef   Google Scholar

    [47]

    Sluiter A, Ruiz R, Scarlata C, Sluiter J, Templeton D. 2005. Determination of extractives in biomass. Laboratory Analytical Procedure, Technical Report NREL/TP-510-42619. 1617: 1−16. www.nrel.gov/docs/gen/fy08/42619.pdf
    [48]

    Bartley LE, Peck ML, Kim SR, Ebert B, Manisseri C, et al. 2013. Overexpression of a BAHD acyltransferase, OsAt10, alters rice cell wall hydroxycinnamic acid content and saccharification. Plant Physiology 161:1615−33

    doi: 10.1104/pp.112.208694

    CrossRef   Google Scholar

    [49]

    Gustafson DM, Boe A, Jin Y. 2003. Genetic variation for Puccinia emaculata infection in switchgrass. Crop Science 43:755−59

    doi: 10.2135/cropsci2003.7550

    CrossRef   Google Scholar

  • Cite this article

    Frazier TP, Lin F, Wang G, Norris A, Toro C, et al. 2023. Overexpression of the Arabidopsis SHN3 transcription factor compromises the rust disease resistance of transgenic switchgrass plants. Grass Research 3:4 doi: 10.48130/GR-2023-0004
    Frazier TP, Lin F, Wang G, Norris A, Toro C, et al. 2023. Overexpression of the Arabidopsis SHN3 transcription factor compromises the rust disease resistance of transgenic switchgrass plants. Grass Research 3:4 doi: 10.48130/GR-2023-0004
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Overexpression of the Arabidopsis SHN3 transcription factor compromises the rust disease resistance of transgenic switchgrass plants

  • 1.

    School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, Virginia 24061, USA

  • 2.

    Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma 73019, USA

  • 3.

    Sustainable Biomaterials, Virginia Tech, Blacksburg, Virginia 24061, USA

  • 4.

    Institute of Biological Chemistry, Washington State University, Pullman, Washington 99164, USA

  • Received: 28 July 2022
  • Accepted: 15 February 2023
  • Published online: 30 March 2023
Grass Research  3,  Article number: 4  (2023)  |  Cite this article

Abstract: Switchgrass can generate large amounts of renewable biomass and hence is one of the most promising bioenergy crops. Improving the quality of switchgrass lignocellulosic biomass will enable its utilization for biofuels. Arabidopsis SHINE family of transcription factor SHN2 was previously identified as a master regulator of cell wall deposition in transgenic rice. However, it is unclear if the Arabidopsis SHN genes also have a similar biological function in switchgrass. Here, we generated transgenic switchgrass overexpressing the Arabidopsis SHN3 transcription factor. Compared with the wild-type, AtSHN3-overexpressing switchgrass plants were stunted in their growth. There were no significant differences in terms of lignin and cellulose content between the SHN transgenics and wild-type switchgrass plants. However, two AtSHN3 transgenic lines SHN7-2 and SHN5-2, displayed significant changes in several matrix polysaccharide monomers. Overexpression of AtSHN3 in switchgrass did not alter the stem mechanical strength when subjected to tensile-torsion analysis. Interestingly, the AtSHN3-overexpressing transgenic lines were more susceptible to switchgrass rust (Puccinia emaculata) than wild-type plants. Therefore, AtSHN3 may have a negative role in regulating disease resistance in switchgrass.

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    INTRODUCTION

    • To meet growing energy demands, it is estimated that 22.3 million acres of arable cropland will need to be allocated to biofuel production by the year 2030[1,2]. Perennial forage grasses grown in marginal lands are an attractive source of sustainable energy, and as such, they have been extensively studied as promising second-generation bioenergy crops[1]. These second-generation biofuel feedstocks, such as switchgrass, contain large amounts of lignocellulosic biomass that can provide an inexpensive and abundant source of renewable energy[3].

      Lignocellulosic feedstock material is comprised of three major components: lignin, matrix polysaccharides, and cellulose. In conjunction with minor components, such as minerals and proteins, these molecules function together to form the structural base of the plant cell wall[4]. The concentrations of lignin, matrix polysaccharides, and cellulose vary among plant species[4]. Grasses typically contain 25%−40% cellulose, 35%−50% hemicellulose, and 10-30% lignin[5].

      Switchgrass is a C4 perennial grass that used to be commonly found growing across the vast prairie region of North America. There are three ecotypes of switchgrass, lowland, upland, and coastal, that differ in their habitat preference[6]. Lowlands and coastals are typically found growing across the warm southern plains of the United States whereas uplands tend to grow across the northern prairies into the southern parts of Canada[7]. Morphologically, lowland ecotypes have thicker stems, wider leaves, and taller tillers than their upland counterparts[7]; whereas coastals have thin, but tall stems. The two better studied ecotypes vary significantly in overall biomass production. Lowland varieties have been shown to produce on average 12.9 Mg·ha−1 of biomass per year, while the upland varieties have been shown to produce on average 8.7 Mg·ha−1 of biomass per year[8]. Currently, several commercial varieties of switchgrass have been released that are suitable for large-scale sustainable biomass production, including lowland varieties 'Alamo' and 'Kanlow', as well as upland cultivars 'Cave-In-Rock' and 'Summer'[9,10].

      For switchgrass to be fully utilized as a bioenergy crop, the quality of the lignocellulosic component of the biomass must be improved. Significant effort has been put into identifying elite switchgrass germplasm from already existing cultivars and into developing the best management practices for optimal biomass output[11,12]. In addition, traditional breeding methods have been employed to enhance certain characteristics of switchgrass feedstock, including biomass production and forage digestibility[13,14]. Considering the time constraints of current breeding practices, it takes approximately ten years to develop a new switchgrass cultivar with enhanced characteristics using traditional methods[15].

      Recently, genetic engineering practices have been used to create transgenic switchgrass lines with altered cell wall compositions. Since lignin is a limiting factor in the use of lignocellulosic biomass for bioethanol production, several studies in switchgrass have used RNAi technology to knock down genes coding for key enzymes in the lignin biosynthesis pathway, including 4-coumarate:coenzyme A ligase (4CL)[16], cinnamyl alcohol dehydrogenase (CAD)[17,18], and caffeic acid O-methyltransferase (COMT)[19]. Xu et al. found that in comparison to the wild-type plants, transgenic switchgrass lines with reduced 4CL activity had a 22% reduction in overall lignin and released 57.2% more fermentable sugar with dilute acid pretreatment[20]. Alternatively, two independent studies found that down-regulating CAD in switchgrass results in 23% less lignin and cutin[18] or 14%−22% less lignin[17], respectively. Finally, down-regulation of the COMT gene in switchgrass produced up to 38% more ethanol using current biomass fermentation practices[19].

      An alternative to directly targeting components of the lignin pathway is to manipulate the master regulator that plays a role in regulation of cell wall composition. Several transcription factors have been identified as key regulators of cell wall biosynthesis[21−25]. The Arabidopsis SHNE family belongs to the APETALA2/ Ethylene Responsive Factor (AP2/ERF) transcription factor family that consists of three members (AtSHN1, AtSHN2, and AtSHN3)[26]. Arabidopsis shn mutants have aberrant deposition of epicuticular wax and altered flower morphology[26,27]. AtSHN1 and its orthologues can regulate wax deposition and drought tolerance in plants[26,28−31]. AtSHN2 and its orthologues function as key regulators of cutin, polysaccharides, and lignin deposition[32−34]. Overexpression of AtSHN2 in rice resulted in transgenic plants with a 34% increase in cellulose content and a 45% decrease in lignin[32]. However, unlike AtSHN1 and AtSHN2, the biological function of AtSHN3 has not been intensively characterized.

      Despite its importance as a promising bioenergy crop, only a handful of studies in switchgrass have aimed to identify transcriptional control mechanisms underlying cell wall deposition[35−37]. In this study, we created transgenic switchgrass plants overexpressing the AtSHN3 cDNA sequence from Arabidopsis. The transgenic switchgrass lines consistently displayed stunted growth, but alterations in several matrix polysaccharide monomers varied between AtSHN3 transgenic lines and the wild-type plants. Additionally, we report that overexpressing AtSHN3 in switchgrass compromised rust disease resistance. The results of this study provide insights into the biological functions of AtSHN3 that may negatively regulate the rust disease resistance in switchgrass.

    RESULTS

      Creation of AtSHN3 over-expressing transgenic switchgrass plants

    • Following Agrobacterium transformation of somatic embryogenic switchgrass callus, a total of 49 potential ZmUbi10pro: AtSHN3-overexpressing switchgrass plants were regenerated and transplanted into soil. These 49 plants were derived from seven independent transformation events. Four plants, representing four independent transformation events, were selected for further analysis. DNA samples for all four transgenic lines, as well as the wild-type HR8 control, were analyzed by Southern blot. Southern blot analysis showed that three of the four selected lines contained multiple transgene insertions (Fig. 1). SHN4-1 contained three copies of the transgene, whereas SHN5-2 and SHN7-2 contained two copies of the transgene. SHN6-3 was the only line with a single insertion copy of the transgene.

      Figure 1. 

      Southern blot confirmation of transgene insertion. A portion of the hygromycin selection gene was used as a probe. (1) HR8 negative control, (2) 1 kb positive standard, (3) SHN4-1, (4) SHN5-2, (5) SHN6-3, (6) SHN7-2.

      AtSHN3-overexpressing transgenic switchgrass are phenotypically different from wild-type plants

    • Growth and development were compared between greenhouse-grown transgenic AtSHN3-overexpressing plants and the wild-type HR8 control plants after three months. Two of the AtSHN3-overexpressing transgenic plants, SHN4-1 and SHN7-2, appeared shorter than the HR8 control (Fig. 2). Several agronomic traits were measured for all plants with three replicates to evaluate the degree of stunting. These included the number of tillers, tiller height, leaf length, leaf width, stem size, and overall biomass. The number of tillers produced was not statistically different (p > 0.01) between the transgenic lines and the wild-type plants (Table 1). All of the plants in this study possessed between 6 and 12 tillers per line. Tiller height measurements revealed that the SHN4-1 and the SHN7-2 plants were significantly shorter (p < 0.01) than the wild-type plants (Table 1).

      Figure 2. 

      AtSHN3-overexpressing transgenic switchgrass lines are smaller than wild-type plants. (a) HR8 control plant (left) in comparison to SHN 5-2 (middle) and SHN 6-3 (right). (b) HR8 control plant (left) in comparison to SHN 4-1 (middle) and SHN 7-2 (right).

      Table 1.  Comparison of agronomic trait measurements for AtSHN3-overexpressing transgenic switchgrass and HR8 control plants. Trait means were not statistically significantly different unless stated, i.e., p > 0.01.

      T0 plantsTiller numberTiller height (cm)Flag leaf length (cm)Flag leaf width (mm)Stem width (mm)Biomass (kg)*
      HR812126.0433.39.334.090.096
      SHN4-110.585.25**25.277.23**3.290.069
      SHN5-26.8126.5032.1710.134.350.087
      SHN6-39.2104.5923.478.013.930.066
      SHN7-210.675.46**24.777.993.580.073
      * = biomass of plant fresh weight; ** = statistically different at p < 0.01.

      Despite the difference in overall height, the flag leaf lengths of all transgenic lines were not statistically distinguishable from the control plants (p > 0.01, Table 1). SHN4-1 plants had a significantly smaller leaf width (p < 0.01) compared to the HR8 control (Table 1). Both the transgenic AtSHN3-overexpressing lines and the HR8 control plants had similar stem sizes (Table 1). An indicator of change in cell wall composition is the abnormal lengthening of internode stem segments[38]. In this study, we found that the second internode from the base of the plant was shorter for the SHN4-1 and SHN7-2 plants (Fig. 2). Surprisingly, despite their stunted growth, the AtSHN3-overexpressing lines produced comparable biomass to the wild-type plants under greenhouse conditions (Table 1).

      Transgene copy insertion number is associated with AtSHN3 gene expression in transgenic switchgrass plants

    • Since the SHN4-1, SHN5-2, and SHN7-2 plants have multiple copies of the transgene (Fig. 1), qPCR was performed to determine if there was a correlation between the transgene copy number and AtSHN3 gene expression. In comparison to SHN6-3, which has a single copy of the transgene, we found that AtSHN3 gene expression increased with increasing transgene copy numbers. SHN4-1 has at least three copies of transgenes (Fig. 1), and it exhibited the highest transgene expression. SHN5-2 and SHN7-2 both have two copies of transgenes. However, their expression was not statistically different from that of SHN6-3 (Fig. 3). SHN4-1 was the shortest among all of the transgenic lines. Thus, differences in the expression levels of AtSHN3 may be contributing to the stunted growth phenotype observed in SHN4-1 switchgrass plants.

      Figure 3. 

      qPCR analysis of transgene expression levels in AtSHN3 transgenic plants. Expression levels were normalized to the values obtained for SHN3 6-3, which contains one transgene insertion. N = 3, the error bars are standard deviations.

      AtSHN3-overexpressing plants have similar lignin and cellulose content to wild-type plants

    • Phloroglucinol staining of I2 sections of transgenic and wild-type switchgrass stems suggested that overexpression of AtSHN3 in switchgrass might alter lignin and cellulose content (Fig. 4). Therefore, I2 stem fragments were subjected to quantify the amount of acid-soluble and acid-insoluble lignin and overall lignin content via sulfuric acid hydrolysis assays. However, the acid-soluble and acid-insoluble lignin contents were not statistically significantly altered between the wild-type and transgenics (Table 2).

      Figure 4. 

      Phloroglucinol and calcofluor staining of I2 stem sections of wild-type and AtSHN3 transgenics. The tiller segment sections of wild-type and AtSHN3 transgenics were stained with either Phloroglucinol or calcofluor white, and observed under a microscope. Lignin stained with Phloroglucinol is in cherry pink color and the cellulose stained with calcofluor white is showing fluorescence under UV light. All experiments were performed at least twice with similar results.

      Table 2.  Acid-soluble lignin and acid-insoluble lignin measurement for the AtSHN3-overexpressing transgenic plants and the wild-type control. N = 3, error represents standard deviation.

      Switchgrass line% Acid soluble lignin% Acid insoluble lignin% Total lignin
      HR815.5 ± 1.12.2 ± 0.217.7 ± 1.0
      SHN4-113.1 ± 0.02.1 ± 0.215.2 ± 0.4
      SHN5-215.8 ± 1.12.5 ± 0.118.3 ± 1.1
      SHN6-315.1 ± 0.32.1 ± 0.417.2 ± 0.7
      SHN7-214.2 ± 0.72.1 ± 0.216.4 ± 0.9

      The cellulosic glucose content of I2R3 stem segments was also measured to determine if the transgenic lines had an increase in cellulose. However, there is no statistically difference between the wild-type and AtSHN3 transgenic plants at p < 0.01 level (Fig. 5). We further analyzed the SHN transgenics of matrix polysaccharide monomers, including arabinose, galactose, glucose, xylose, galacturonic acid, and glucuronic acid. Interestingly, we detected there were significant changes in a few of these hemicellulose sugars between the AtSHN3-overexpressing lines and the HR8 wild-type plants (Fig. 6). For example, SHN7-2 transgenic internodes had 31% more arabinose and 90% more xylose than HR8 control plants (p < 0.01). Also, SHN5-2 transgenic plants had 43% less matrix polysaccharide glucose than the wild-type HR8 plants (p < 0.01).

      Figure 5. 

      Measurement of cellulose content between AtSHN3-overexpressing transgenic switchgrass and HR8 wild-type. The cellulose content of the transgenic plants was not statistically different from the wild-type (p < 0.01). N = 3, the error bars are standard deviation.

      Figure 6. 

      Matrix polysaccharide sugars in AtSHN3-overexpressing transgenic switchgrass and HR8 wild-type. SHN7-2 transgenic plants were found to have 31% more arabinose and 90% more xylose than HR8 control plants (p < 0.01). SHN5-2 transgenic plants were found to have 43% less glucose than the wild-type HR8 plants (p < 0.01). N = 3, the error bars are standard deviations. The asterisks are the indicators of significant differences between wild-type and transgenics. Arabinose (Ara), Galactose (Gal), Glucose (Glc), Xylose (Xyl), Galacturonic acid (GalA) and Glucuronic acid (GlcA).

      Taken together, the overexpression of AtSHN3 does not significantly change the lignin and cellulose contents in switchgrass cell wall biomass; instead, it can alter the deposition of hemicellulose sugars in switchgrass.

      Overexpression of AtSHN3 in switchgrass does not alter the stiffness or mechanical strength of switchgrass stems

    • A change in cell wall composition could alter the strength of the stem, which helps the plant maintain an upright growth habit and to withstand abiotic stress such as wind. Storage modulus tests were conducted to measure if the altered hemicellulose contents of the AtSHN3 transgenics could also affect the stiffness of the AtSHN3-overexpressing stems. The test was performed by applying an oscillating stress to the sample and measuring the responding strength. Our results suggest there is no significant difference between the AtSHN3 transgenics lines and the wild-type control plants at the p <0.01 level (Table 3).

      Table 3.  Average storage modulus derived from stress sweeps at 25ºC for AtSHN3-overexpressing transgenic plants and HR8 wild-type control. The number of repetitions for this experiment is n = 2 for all biological samples.

      Storage modulus G’ (Pa)HR8SHN4-1SHN5-2SHN6-3SHN7-2
      Strain2.1E82.2E82.2E81.5E81.8E8
      Standard deviation1.8E71.1E82.9E71.5E72.6E7
      p-value0.060.890.850.34

      In addition to the stiffness, we also tested if changing the hemicellulose content of cell walls affected the overall mechanical strength of the transgenic switchgrass stems. To accomplish this, fracture tests were performed on switchgrass stem sections by continuously increasing levels of torsion force applied to the stem sections until the stems broke. From the fracture tests, two parameters correlated to the overall mechanical strength of the stem: 1) the slope of the linear region, which reflects the stiffness of the stem, and 2) the breaking point, which correlates to the strength of the stem. The results from both the linear region and breaking point analyses suggest that there was no significant difference between the transgenics and the wild-type control plants (Table 4).

      Table 4.  Initial linear strength measurement and shear stress at breaking point for the AtSHN3-overexpressing transgenic lines and the HR8 control. The number of repetitions used for this analysis was n = 5.

      MeasurementHR8SHN4-1SHN5-2SHN6-3SHN7-2
      Initial linear strength (Pa)2.0E61.7E61.3E61.7E61.6E6
      Standard deviation9.3E53.1E55.6E57.7E53.9E5
      p-value0.530.240.650.47
      Shear stress at breaking
      point (Pa)      		1.9E71.6E71.7E71.4E71.8E7
      Standard deviation5.7E62.5E63.5E64.3E68.1E5
      p-value0.390.570.270.61

      AtSHN3 over-expressing switchgrass plants are more susceptible than wild-type plants to switchgrass rust

    • The plant cell wall is the first physical barrier encountered by plant pathogens upon initiation of infection[39]. Since three of these AtSHN3-overexpressing plants (SHN5-2, SHN 6-3, and SHN7-2) have altered hemicellulose content in the cell wall biomass, we further investigated whether or not the SHN3 transgenic plants were more or less susceptible to a rust fungal pathogen. After inoculating both the transgenic lines and the wild-type control with Puccinia emaculata urediniospores, we found that all AtSHN3-overexpressing plants were more susceptible to rust than the HR8 control plants (Fig. 7).

      Figure 7. 

      Switchgrass rust disease assays of AtSHN3-overexpressing transgenic switchgrass plants and wild-type control. * Indicates lines significantly different from the wild-type at p < 0.01. N = 3, the error bars are standard deviations.

    DISCUSSION

    • Switchgrass is a promising bioenergy crop, and switchgrass cultivars that contain reduced levels of lignin and increased cellulose are desirable for cost-effective and efficient bioethanol production. It is possible to coordinate the activation and repression of these two cell wall components through genetic manipulation of specific master regulators[32]. A previous report suggests that the overexpression of Arabidopsis transcription factor AtSHN2 in rice could increase cellulose and decrease lignin contents of cell wall biomass[32]. AtSHN2 belongs to a small gene family with three members (AtSHN1, 2, and 3) that vary in their developmental and tissue-specific gene expression patterns[26]. AtSHN3 has the broadest expression pattern that is active in almost all plant organs[26]. Despite its proven role in wax accumulation, the other biological functions of AtSHN3 genes have not yet been explored. It is also unclear if AtSHN3, similar to AtSHN2, functions as a master regulator of lignin and cellulose biosynthesis in monocots.

      In this study, the Arabidopsis SHN3 cDNA was cloned and transformed into switchgrass. While others have reported a glossy phenotype of the leaf surface upon overexpression of SHN genes[26,40], this phenotype was not observed in any of the transgenic switchgrass plants created in this study. AtSHN3-overexpressing switchgrass plants, however, exhibited stunted growth in comparison to wild-type plants (Fig. 2). Transgenic tomato plants over-expressing SlSHN3, the tomato ortholog of AtSHN3, also displayed stunted growth[40]. Interestingly, the stunted growth phenotype of tomato plants was more severe in SlSHN3-overexpressing plants than in SlSHN1-overexpressing plants[41]. This suggests that while the SHN-family proteins may have similar functions, their tissue-specific expression patterns are essential for proper cell wall development.

      The SHN genes regulate wax deposition on both leaf and fruit cuticle surface[26,27]. In addition, members of the SHN family function in cell elongation and secondary cell wall thickening[27,32]. AtSHN2-overexpression can reduce lignin and increase cellulose in transgenic rice plants[32]. The overexpression of AtSHN3 in switchgrass stems might alter the lignin and cellulose contents based on the phloroglucinol and calcofluor staining (Fig. 4). However, the quantitive measurements of cellulose content did not reveal a statistically significant difference between the wild-type and transgenic plants (Fig. 5, Table 2). The phloroglucinol and calcofluor staining methods are relatively easy and cost-effective, but the data interpretation is more subjective, therefore, it is always valuable to obtain quantitative measurement as described in this study. In the future, it will be worthy to re-quantify the cellulose content by using more sample replicates that may reduce the experimental variations. Interestingly, the SHN7-2 plants possessed significantly more arabinose and xylose in their matrix polysaccharide compared to wild-type control plants (HR8). The SHN5-2 line, however, had a significant reduction in the amount of glucose present in its matrix polysaccharide, which is likely due to a reduction in amorphous cellulose or mixed linkage glucan. Further studies are needed to determine if the changes in the hemicellulose content in these lines result in enhanced bioethanol production.

      Changes in the cell wall compositions of plant stems could compromise the plant's ability to withstand extracellular forces associated with abiotic forces such as wind and rain that cause lodging. For instance, brittle stalk (bk2) mutants of maize contain less cellulose and more lignin, have compromised the mechanical strength of stems, and are easily broken with minimal applied force[42]. In this study, storage modulus and fracture tests were performed on transgenic and wild-type switchgrass lines to assess the stem stiffness and mechanical strength, respectively. These tests were recently developed and optimized for plant biology research[43]. Storage modulus tests can evaluate the stiffness of the stem by analyzing the % strain output as it correlates to a specific stress. Fracture tests utilize tensile-torsion force to apply stress to a sample, and the % strain is measured during the linear region and at the sample breaking point[43]. Our results suggest that there is no statistical difference in terms of stem stiffness and mechanical strength between the wild-type and transgenic plants (Tables 3 & 4). Therefore, the altered hemicellulose content in the AtSHN3 transgenic plants does not significantly reduce the stem stiffness and mechanical strength.

      Overexpression of SHN1 genes in transgenic Arabidopsis, tomato, and rice plants conferred greater tolerance to water restriction compared to wild-type plants[26,32,41]. This could be attributed to the accumulation of excess epicuticular waxes on the leaf surface, which contributes to the glossy leaf phenotype or to the reduced numbers of stomata in transgenic plants[41]. More studies will need to be conducted to determine if AtSHN3 can promote the accumulation of epicuticular waxes that may enhance drought tolerance in switchgrass.

      The first physical barrier that foliar pathogens encounter is the plant cell wall. Thus, we investigated if AtSHN3 over-expression affected the disease resistance response of switchgrass rust. All AtSHN3 transgenic switchgrass lines were significantly more susceptible to the rust pathogen than the wild-type controls (Fig. 7). Because there are no consistent patterns of the altered polysaccharide monomers in the AtSHN3 transgenic plants, the variation of polysaccharide monomers cannot explain the AtSHN3-mediated disease susceptibility. A previous report suggests that overexpression of SlSHN3 in tomato leaves allowed the leaves to uptake toluidine blue, suggesting that SlSHN3-overexpressing plants contained a more permeable cuticle than the wild-type[40]. It is possible that overexpression of AtSHN3 in switchgrass could also increase permeable cuticle, which might explain the disease susceptibility phenotype of the AtSHN3 transgenic plants. Thus, it will be worth measuring the permeable cuticle in the AtSHN3 transgenic plants in the future.

    CONCLUSIONS

    • Although Arabidopsis AtSHN3 shares high homology with AtSHN2 and AtSHN1, overexpression of AtSHN3 in switchgrass does not significantly alter the stem lignin and cellulose contents in transgenic switchgrass. Therefore, AtSHN3 may not have a similar function as AtSHN1 and AtSHN2 when they are overexpressed in a monocot plant species. In the future, a comprehensive analysis of all three switchgrass-specific SHN members will be necessary to understand their biological roles in switchgrass.

    MATERIALS AND METHODS

      Cloning of the AtSHN3 gene

    • A plasmid containing the AtSHN3 (TAIR accession: U51209, AT5G25390) cDNA was obtained from TAIR-ABRC. The AtSHN3 open reading frame was amplified using a 50 µl PCR reaction with the following components: 25 µl High-Fidelity iProof master mix (Bio-Rad, Hercules, CA, USA), 10 µl plasmid DNA, 10 µl ddH2O, 2.5 µl 10 µM forward primer (5'-CACCGAATTCATGGTACATTCGAAGAAGTTCC-3'), and 2.5 µL 10 µM reverse primer (5'-CGTCTGCAGGACCTGTGCAATGGATCCAGATC-3'). The PCR reaction was run with an initial denaturation step at 98 °C for 3 min, followed by 30 cycles of denaturation at 98 °C for 30 s, annealing at 57 °C for 45 s, and extension at 72 °C for 1 min, and then completed with a final extension at 72 °C for 7 min. Successful amplification of the PCR product was visualized using a 0.8% agarose gel, and the PCR product was purified using a QIAquick Gel Extraction kit (QIAGEN Sciences Inc, Germantown, MD, USA).

      Insertion of AtSHN3 into the pVT1629 Gateway-compatible binary vector

    • The purified AtSHN3 PCR product was cloned into the pENTR/D-TOPO vector (Invitrogen, Waltham, MA, USA). The AtSHN3 gene sequence was confirmed by DNA sequencing at the core facility at Virginia Tech. By using a Gateway LR® cloning kit (Invitrogen Inc), the AtSHN3 DNA fragment was subcloned into the pVT1629 destination vector that carries a maize Ubi10 promoter[16]. The final construct, pVT1629-AtSHN3, was conjugated into Agrobacterium tumefacient strain AGL1.

      Switchgrass callus formation and Agrobacterium-mediated transformation

    • The method for Agrobacterium-mediated transformation of switchgrass followed that previously described[20,44]. In brief, mature seeds of the HR8 genotype of the switchgrass cv. Alamo was dehusked with 60% sulfuric acid and sterilized with 50% bleach. The sterilized seeds were transferred to callus induction mediums. After 4−6 weeks, embryogenic calli were subcultured onto the callus induction mediums containing 20 g·l−1 proline. Ten days before transformation, embryogenic calli were subcultured again onto callus induction mediums containing proline and 200 µM acetosyringone. After two rounds of culture on selection mediums, the actively growing calli were subcultured to regeneration mediums. Following regeneration and root formation, regenerated plantlets were transplanted into pots containing MiracleGro Moisture Control soil and maintained in a greenhouse at Virginia Tech.

      Phenotypic characterization of SHN3 transgenic switchgrass lines

    • In the middle of July 2015, individual E2 to E3 stage tillers from all transgenic SHN3 switchgrass lines, along with the HR8 control, were clonally propagated by splitting a single tiller and re-planted in gallon-size pots containing Miracle-Gro® Moisture Control potting mix. The plants were maintained in a greenhouse at a 16 h photoperiod with supplemental lighting used as needed. After three months of growth, the overall height, flag leaf length, flag leaf width, and I2 stem width of four R3 stage tillers were measured for three biological replicates of each transgenic line as well as the wild-type control. Finally, all plants were harvested at ground level and weighed to determine fresh biomass yield.

      DNA extraction and confirmation of transgenic switchgrass plants

    • Leaves of putative transgenic and wild-type switchgrass plants were collected and immediately frozen in liquid nitrogen. Genomic DNA was extracted using a modified 2× CTAB protocol as previously described[45]. The quality and quantity of the DNA was assessed using agarose gels and a Nanodrop-D1000 (Nanodrop, Wilmington, DE, USA). The switchgrass DNA was then sent to Lofstrand Labs Ltd (Gaithersburg, MD, USA) for Southern blot analysis. Briefly, a total of 10 µg of genomic DNA was restriction enzyme digested with HindIII. DNA fragments were separated using gel electrophoresis and probed with a portion of the hygromycin selection gene to detect transgene insertion[16].

      RNA extractions and qPCR analysis

    • Flag leaves of R3 stage switchgrass tillers were collected from greenhouse-grown switchgrass plants and immediately frozen in liquid nitrogen. The tissue was stored at −80 °C until further analysis. Tissue samples were collected for three biological replicates of both the transgenic and wild-type plants. Total RNA was extracted using the TRIzol reagent (Invitrogen, Grand Island, NY, USA) according to the manufacturer's protocol. The quality and quantity of the RNA was assessed using a Nanodrop-D1000 (Nanodrop, Wilmington, DE, USA).

      The relative expression AtSHEN3 in transgenic plants was analyzed by qPCR with primers pPCRfor, 5'-TCTCTTGAAGAGAAGAGTGT-3', and qPCRrev, 5'-ACGGTGTCTGGTCTTTACAG-3'. The switchgrass ELF1a gene was used as the reference gene (5'-TCAGGATGTGTACAAGATTGGTG-3' and 5'-GCCTGTCAATCTTGGTAATAAGC-3'). First strand cDNA was synthesized using a DyNAmo cDNA synthesis kit (Thermo Fisher, Waltham, MA, USA). Quantitative Real Time-PCR (qPCR) was performed using an Applied Biosystems Power SYBR Green PCR Master Mix (Grand Island, NY, USA). The PCR reactions were performed on an Applied Biosystems 7300 Real-Time PCR machine with the following conditions: 1) an initial denaturation and enzyme activation step at 95 °C for 10 min and 2) 40 cycles of denaturation (95 °C for 30 s), annealing (60 °C for 30 s), and extension (72 °C for 1 min and 30 s). After the reactions had completed, the threshold was manually set to 3.0, and the data was exported for analysis.

      Stem sectioning and histochemical staining for lignin and cellulose

    • The second internode (I2) of R3 stage tillers was selected for histochemical staining. I2 was characterized as the first full-length stem segment, located between the first and second distinguishable nodes, from the base of the plant. The I2 segments of transgenic and wild-type plants were cut into 40 µm sections using a microtome. The lignin and polysaccharide content of the transgenic switchgrass plants was visualized using Weisner (phloroglucinol) reactions and calcofluor staining, respectively. The protocols for these reactions were performed as previously described[46]. The Weisner stained stem sections were visualized using a Zeiss compound light microscope and the calcofluor stained stem sections were visualized using a fluorescence Zeiss AxioImager.M1 microscope mounted with a Zeiss AxioCam MRm (Carl Zeiss Microscopy Inc, Oberkochen, Germany).

      Measurement of acid-soluble and acid-insoluble lignin

    • I2 segments of R3 stage tillers for three biological replicates of each transgenic line, as well as the HR8 control, were dried in an oven at 48 °C and then ground into a coarse powder using a coffee grinder. Acid-soluble and insoluble lignin content were determined using the procedure established by the National Renewable Energy Laboratory[47]. In brief, 300 mg of ground switchgrass samples were added to a pressure tube along with 3 mL of 72% sulfuric acid to hydrolyze the tissue. The tubes were incubated at 30 °C for 1 h with manual stirring every 5 min. Following incubation, 84 mL of deionized water was added to each tube to dilute the sulfuric acid to a concentration of 4%. The tubes were then autoclaved at 121 °C for 1 h. Next, the tubes were cooled to room temperature, and the mixture was vacuum-filtered through a porcelain crucible. The filtrate, which contained the acid-soluble lignin, was collected and diluted to a volume sufficient to obtain a UV absorption value of 0.7−1.0 at 205 nm. The acid-insoluble reside, which remained in the porcelain crucible, was dried in an oven at 105 °C overnight and then weighed to determine the acid-insoluble lignin content.

      Measurement of cellulose and hemicellulose

    • A second set of I2 samples of R3 stage tillers for three biological replicates of control and transgenic plants were also dried in an oven at 48 °C. The samples were ground with a SPEX 2010 GenoGrinder (SPEX SamplePrep, Metuchen, NJ, USA) at 1,500 rpm. The fine powder was then made into alcohol insoluble residue (AIR) and de-starched as described previously[48]. The de-starched AIR was used for cellulose and hemicellulose assays. Hemicellulose monosaccharides were released by 4M TFA treatment for 2 h and then measured by HPLC. The pellets after TFA treatment were used for an anthrone cellulose assay as described previously[48]. Briefly, pellets were hydrolyzed by 72% sulfuric acid to release cellulosic glucose. The cellulosic glucose was quantified by a colorimetric reaction with an anthrone reagent and read on a plate reader at OD625nm.

      Solvent-submersion tensile-torsion measurements to determine stem stiffness and mechanical strength

    • Fresh I2 stem segments of R3 stage switchgrass tillers were subjected to solvent-submersion tensile-torsion analysis using an AR G2 rheometer (TA Instruments, New Castle, DE, USA). The I2 segments were cut into 2 cm long fragments and then split longitudinally into four different sections. The samples were then fully saturated with ethylene glycol and stored at room temperature for future analysis. On the day of analysis, the samples were secured with tension clamps using 15cNxm torque and 1N static tensile force.

      All of the testing steps were operated at a frequency of 0.5 Hz and a stress setting of 50,000 Pa. Storage modulus analysis, which is a reflection of stem stiffness, was conducted at room temperature by equilibrating the samples at 25 ºC for 5 min and then running the stress sweep. At least three observations were recorded for each sample type. Ultimate fracture tests of ethylene glycol saturated stem samples were conducted in tensile-torsion mode at room temperature. The specimens were clamped at both ends with slight tensile force (1N) to hold the sample vertically straight. Fracture tests were performed under continuous flow conditions with shear stress increasing from 1E5 Pa to 1E8 Pa. The tests were performed four times per sample. Data acquisition was performed in linear mode with a total collection time of 33 min and a total point set at 300. Tests were concluded once the specimens failed.

      Rust disease assays of AtSHN3 transgenic plants

    • The AtSHN3-overexpressing transgenic lines and the HR8 control plant were clonally split into three biological replicates. Each biological replicate was planted in a pot containing MiracleGro Moisture Control soil and grown in the greenhouse under a 16 h photoperiod. Freshly collected Puccinia emaculata urediniospores were mixed 1:10 with talcum powder and hand inoculated on the first fully expanded leaf of E2 stage tillers. The plants were placed in a chamber with a humidifier and kept under 100% humidity for 16 h. Ten days post-inoculation, the severity of rust disease was scored according to the scale established by Gustafson et al.[49]

      Statistical analyses

    • All statistical analyses were performed using Student's ANOVA-tests with a significance level of 0.01, chosen to compensate for multiple testing.

      Acknowledgments

      • The project was supported by USDA-NIFA Grant Number 2011-67009-30133 (B. Zhao). The project was also partially supported by a Virginia Tech CALS integrative grant, a seed grant of the Institute for Critical Technology and Applied Science at Virginia Tech, and Virginia Agricultural Experiment Station (VA135872) to B. Zhao, and by a USDA South Central Sungrant to L. Bartley.

      Conflict of interest

      • The authors declare that they have no conflict of interest.

      Rights and permissions
      • Copyright: © 2023 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (7)  Table (4) References (49)
  • About this article
    Cite this article
    Frazier TP, Lin F, Wang G, Norris A, Toro C, et al. 2023. Overexpression of the Arabidopsis SHN3 transcription factor compromises the rust disease resistance of transgenic switchgrass plants. Grass Research 3:4 doi: 10.48130/GR-2023-0004
    Frazier TP, Lin F, Wang G, Norris A, Toro C, et al. 2023. Overexpression of the Arabidopsis SHN3 transcription factor compromises the rust disease resistance of transgenic switchgrass plants. Grass Research 3:4 doi: 10.48130/GR-2023-0004
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  • Introduction
  • Results

  • Creation of atshn3 over-expressing transgenic switchgrass plants

  • atshn3-overexpressing transgenic switchgrass are phenotypically different from wild-type plants

  • Transgene copy insertion number is associated with atshn3 gene expression in transgenic switchgrass plants

  • atshn3-overexpressing plants have similar lignin and cellulose content to wild-type plants

  • Overexpression of atshn3 in switchgrass does not alter the stiffness or mechanical strength of switchgrass stems

  • atshn3 over-expressing switchgrass plants are more susceptible than wild-type plants to switchgrass rust

  • Discussion
  • Conclusions
  • Materials and methods

  • Cloning of the atshn3 gene

  • Insertion of atshn3 into the pvt1629 gateway-compatible binary vector

  • Switchgrass callus formation and agrobacterium-mediated transformation

  • Phenotypic characterization of shn3 transgenic switchgrass lines

  • Dna extraction and confirmation of transgenic switchgrass plants

  • Rna extractions and qpcr analysis

  • Stem sectioning and histochemical staining for lignin and cellulose

  • Measurement of acid-soluble and acid-insoluble lignin

  • Measurement of cellulose and hemicellulose

  • Solvent-submersion tensile-torsion measurements to determine stem stiffness and mechanical strength

  • Rust disease assays of atshn3 transgenic plants

  • Statistical analyses

  • Acknowledgments
  • Conflict of interest
  • Rights and permissions
  • About this article
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