Plant Physiology Preview. Published on March 13, 2019, as DOI:10.1104/pp.18.01224
1 Genetic Engineering for Disease Resistance in Plants: Recent Progress and Future
2 Perspectives
3 Oliver Xiaoou Dong1,2, Pamela C. Ronald1,2 *
4 1. Department of Plant Pathology and the Genome Center, University of California,
5 Davis, CA 95616, USA.
6 2. Innovative Genomics Institute, Berkeley, CA 94704, USA
7 *For correspondence: [email protected]
8 One Sentence Summary:
9 A review of the recent progress in plant genetic engineering for disease resistance
10 highlights future challenges and opportunities in the field.
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15 Background
16 Modern agriculture must provide sufficient nutrients to feed the world’s growing
17 population, which is projected to increase from 7.3 billion in 2015 to at least 9.8 billion
18 by 2050 (UN 2017). This goal is made even more challenging because of crop loss to
19 diseases. Bacterial and fungal pathogens reduce crop yields by about 15% and viruses
20 reduce yields by 3% (Oerke and Dehne, 2004). For some crops, such as potatoes, the loss
21 caused by microbial infection is estimated to be as high as 30% (Oerke and Dehne, 2004).
22 As an alternative to the application of chemical agents, researchers are altering plants’
23 genetic composition to enhance resistance to microbial infection.
24 Conventional breeding plays an essential role in crop improvement, but usually
25 entails growing and examining large populations of crops over multiple generations, a
26 lengthy and labor-intensive process. Genetic engineering, which refers to the direct
27 alteration of an organism’s genetic material using biotechnology (Christou, 2013),
28 possesses several advantages compared with conventional breeding. First, it enables the
29 introduction, removal, modification or fine-tuning of specific genes of interest and causes
30 minimal undesired changes to the rest of the crop genome. As a result, crops specifically
31 exhibiting desired agronomic traits can be obtained in fewer generations compared with
32 conventional breeding. Second, genetic engineering allows interchange of genetic
33 material across species. Thus, the raw genetic materials that can be exploited for this
34 process is not restricted to the genes available within the species. Third, plant
35 transformation during genetic engineering allows the introduction of new genes into
36 vegetatively propagated crops such as banana (Musa sp.), cassava (Manihot esculenta),
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37 and potato (Solanum tuberosum). These features make genetic engineering a powerful
38 tool for enhancing resistance against plant pathogens.
39 Most cases of plant genetic engineering rely on conventional transgenic
40 approaches or the more recent genome editing technologies. In conventional transgenic
41 methods, genes that encode desired agronomic traits are inserted into the genome at
42 random locations through plant transformation (Lorence and Verpoorte, 2004). These
43 methods typically result in varieties containing foreign DNA. In contrast, genome editing
44 allows changes to the endogenous plant DNA, such as deletions, insertions, and
45 replacements of DNA of various lengths, at designated targets (Barrangou and Doudna,
46 2016). Depending on the type of edits introduced, the product may or may not contain
47 foreign DNA. In some areas of the world including the US (USDA, 2018),
48 Argentina (Secretariat of Agriculture, Livestock, Fishing and Food, Argentina, 2015),
49 and Brazil (CTNBio, 2018), genome-edited plants that do not contain foreign DNA are
50 regarded as equivalent to plants produced by conventional breeding, which exempts them
51 from additional regulatory measures applied to transgenic plants (Orozco, 2018).
52 Regardless of this distinction in regulatory policies, both conventional transgenic
53 techniques and genome editing continue to be powerful tools for crop improvement.
54 Plants have evolved multi-layered defense mechanisms against microbial
55 pathogens (Chisholm et al., 2006; Jones and Dangl, 2006). For example, pre-formed
56 physical and physiological barriers and their reinforcements prevent potential pathogens
57 from gaining access inside the cell (Collinge, 2009; Uma et al., 2011). Plasma
58 membrane-bound and intracellular immune receptors initiate defense responses upon the
59 perception of pathogens either directly through physically interacting with pathogen-
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60 derived elicitors, or indirectly by monitoring modifications of host targets incurred by
61 pathogens (Bentham et al., 2017; Jones and Dangl, 2006; Kourelis and van der Hoorn,
62 2018; Zhang et al., 2017). Plant-derived anti-microbial peptides and other compounds can
63 suppress pathogenicity by direct detoxification or through inhibition of the activity of
64 virulence factors (Ahuja et al., 2012; Kitajima and Sato, 1999; Thomma et al., 2002).
65 Plants also employ RNA silencing (RNAi) to detect invading viral pathogens and target
66 the viral RNA for cleavage (Rosa et al., 2018).
67 On the other side, successful pathogens have evolved strategies to overcome the
68 defense responses of their plant hosts. For instance, many bacterial and fungal pathogens
69 produce and release cell wall-degrading enzymes (Kubicek et al., 2014). Pathogens can
70 also deliver effectors into the host cytoplasm (Franceschetti et al., 2017; Xin and He,
71 2013); some of these effectors suppress host defenses and the others promote
72 susceptibility. To counteract plant RNAi-based defenses, almost all plant viruses produce
73 viral suppressors of RNAi (Zamore, 2004). Some viruses can also hijack the host RNAi
74 system to silence host genes to promote viral pathogenicity (Wang et al., 2012).
75 These aspects of host-microbe interactions provide opportunities for genetic engineering
76 for disease resistance (Dangl et al., 2013). For example, genes can be introduced into
77 plants that encode proteins capable of breaking down mycotoxins (Karlovsky, 2011) or
78 inhibiting the activity of cell wall-degrading enzymes (Juge, 2006), or nucleic acid
79 species that can sequester viral suppressors of RNAi (Wang et al., 2012) to reduce
80 microbial virulence. Plants can be engineered to synthesize and secrete antimicrobial
81 peptides or compounds that directly inhibit colonization (Osusky et al., 2000). The RNAi
82 machinery can be exploited to confer robust viral immunity by targeting viral RNA for
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83 degradation (Rosa et al., 2018). Natural or engineered immune receptors that recognize
84 diverse strains of a pathogen can be introduced individually or in combination for robust,
85 broad-spectrum disease resistance (Fuchs, 2017). Essential defense hub regulatory genes
86 can be reprogramed to fine-tune defense responses (Pieterse and Van Loon, 2004).
87 Susceptible host targets can be modified to evade recognition and manipulation by
88 pathogens (Li et al., 2012). Similarly, host decoy proteins, which serve to trap pathogens,
89 can be modified through genetic engineering for altered specificity in pathogen
90 recognition (Kim et al., 2016). For a more comprehensive overview of various aspects of
91 engineered disease resistance plants, the readers are referred to previously published
92 review articles (Collinge et al., 2010; Cook et al., 2015).
93 Increased knowledge regarding the molecular mechanism underlying plant-
94 pathogen interactions and advancements in biotechnology have provided new
95 opportunities for engineering resistance to microbial pathogens in plants. In the following
96 section of this review, we update recent breakthroughs in genetic engineering in plants
97 for enhanced disease resistance and highlight several strategies that have proven
98 successful in field trials.
99 Highlights of recent breakthroughs in genetic engineering for disease resistance in
100 plants
101 Pathogen-derived resistance and RNA silencing
102 Researchers have long observed that transgenic plants expressing genes derived
103 from viral pathogens often display immunity to the pathogen and its related
104 strains (Lomonossoff, 1995). These results led to the hypothesis that ectopic expression
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105 of genes encoding wild-type or mutant viral proteins could interfere with the viral life
106 cycle (Sanford and Johnston, 1985). More recent studies demonstrated that this immunity
107 is mediated by RNAi, which plays a major role in antiviral defense in plants.
108 The detailed molecular mechanism of RNAi in anti-viral defense has been
109 described in several excellent reviews (Galvez et al., 2014; Katoch and Thakur, 2013;
110 Wang et al., 2012). Activation of RNAi has proven to be an effective approach for
111 engineering resistance to viruses (Lindbo and Dougherty, 2005; Lindbo and Falk, 2017)
112 as they rely on the host cellular machinery to complete their life cycle. Most plant viruses
113 contain single-stranded RNA (ssRNA) as their genetic information. Double-stranded
114 RNA (dsRNA) replicative intermediates often form during the replication of the viral
115 genome, triggering RNAi in the host.
116 Transgenic over-expression of viral RNA often leads to the formation of dsRNA
117 mediated by RNA-dependent RNA polymerase, which in turn triggers RNAi (Galvez et
118 al., 2014). This process is often known as co-suppression (Box 1). By far, most existing
119 cases of genetically engineered crops with resistance to viral pathogens that have been
120 approved for cultivation and consumption were generated following this concept (Table
121 1). Notably, transgenic squash (Cucurbita sp.) and papaya (Carica papaya) varieties
122 created using this approach have been grown commercially in the US for more than
123 twenty years. Field data indicate that disease resistance achieved through RNAi-mediated
124 strategies is highly durable (Fuchs and Gonsalves, 2007). The RNAi strategy has also
125 been effective in generating squash varieties that are resistant to multiple viral species
126 (Table 1). These varieties were produced by gene stacking (i.e., transgenic expression of
127 two distinct RNAi constructs targeted to different viruses) (Tricoli et al., 1995).
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128 The knowledge that dsRNA effectively induces RNAi (Lindbo and Dougherty,
129 2005) inspired the design of transgenes encoding inverted repeat sequences, the
130 transcripts of which form dsRNA (Box 1) (Waterhouse et al., 1998). This strategy was
131 used to develop a transgenic common bean variety exhibiting resistance to the DNA virus
132 Bean golden mosaic virus (BGMV) (Bonfim et al., 2007). BGMV contains single-
133 stranded DNA (ssDNA) as its genetic material, which is converted to double-stranded
134 DNA (dsDNA) in the host, transcribed, and translated to produce the essential proteins
135 required for its replication (Hanley-Bowdoin et al., 2013). To generate siRNA targeting
136 the viral transcripts, sense and anti-sense sequences of part of the BGMV replication gene
137 AC1 were directionally cloned into an intron-spliced hairpin RNA expression
138 cassette (Bonfim et al., 2007). The resulting genetically engineered bean exhibited strong
139 and robust resistance in greenhouse conditions (Bonfim et al., 2007) as well as field
140 conditions (Aragao and Faria, 2009). The BGMV-resistant bean was deregulated in 2011
141 in Brazil (Table 1), which allows farmers to grow the crop. It is to date the only example
142 of a deregulated genetically engineered crop showing resistance to a DNA virus.
143 Compared with the co-suppression strategy, transgenic expression of an artificially
144 designed inverted repeat allows simultaneous generation of heterogenous siRNAs
145 targeting multiple transcripts in a relatively simple manner.
146 The discovery of microRNAs (miRNAs), a class of endogenous noncoding
147 regulatory RNAs (Ambros, 2001; Reinhart et al., 2002) led to further refinements of
148 genetic engineering for viral resistance. The miRNA machinery (Xie et al., 2015) has
149 been exploited in engineering resistance to RNA viruses by replacing specific nucleotides
150 in the miRNA-encoding genes to alter targeting specificity (Box 1). Such artificial
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151 miRNAs (amiRNAs) have been used in many lab studies in engineering resistance to a
152 wide range of plant viral pathogens such as Turnip mosaic virus (Niu et al., 2006),
153 Cucumber mosaic virus (Duan et al., 2008; Qu et al., 2007; Zhang et al., 2011), Potato
154 virus X and Potato virus Y (Ai et al., 2011). These results suggest that amiRNA-based
155 anti-viral strategies are highly promising. Disease resistance engineered by this strategy
156 awaits future field tests.
157
158 Harnessing CRISPR-Cas to target viral pathogens directly
159 In recent years, the bacterially-derived Clustered Regularly Interspaced Short
160 Palindromic Repeats (CRISPR)-CRISPR-associated (Cas) technology has proven to be a
161 promising approach for engineering resistance against plant viruses (Box 2) (Wright et al.,
162 2016). In many bacterial species, CRISPR-Cas acts as antiviral defense machinery. In
163 this process, an RNA-guided nuclease (often a Cas protein) cleaves at specific target sites
164 on the substrate viral DNA or RNA, leading to their degradation. The specificity of the
165 cleavage is governed by base complementarity between the CRISPR RNA (crRNA) and
166 the target DNA or RNA molecules. A number of Cas proteins with sequence-specific
167 nuclease activity have been identified (Wu et al., 2018). For example, the RNA-guided
168 endonuclease Cas9 from Streptococcus pyogenes (SpCas9) induces double-stranded
169 breaks in DNA in vivo (Jinek et al., 2012) and the RNA-guided RNases Cas13a from
170 Leptotrichia shahii (LshCas13a) or Leptotrichia wadei (LwaCas13a) target RNA in
171 vivo (Abudayyeh et al., 2017; Cox et al., 2017). Cas9 from Francisella novicida (FnCas9)
172 exhibits in vivo activity in cleaving both DNA and RNA (Price et al., 2015).
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173 The ability of CRISPR-Cas to act like molecular scissors, creating breaks at
174 sequence-specific targets in the substrate DNA or RNA molecules makes it an excellent
175 candidate tool for engineering for anti-viral defense in plants. CRISPR-Cas platforms
176 based on Cas9 or Cas13a have been successfully harnessed to engineer resistance to
177 DNA viruses or RNA viruses in planta (Figure 1).
178 The Tomato Yellow Leaf Curl Virus (TYLCV) belongs to the Geminiviridae, a
179 major family of plant viruses with single-stranded circular DNA genomes (Dry et al.,
180 1993). The viral genome forms double-stranded intermediates during replication inside
181 the host cell nuclei. Overexpression of SpCas9 and artificially designed guide RNAs
182 targeting various regions of TYLCV conferred resistance to the virus in Nicotiana
183 benthamiana and tomato (Solanum lycopersicum) (Ali et al., 2015; Mahfouz et al., 2017).
184 One potential caveat of this approach is that alterations to the viral DNA sequence may
185 occur near the cleavage target due to DNA repair within the host cell. These mutations
186 could shield the viral DNA from recognition by the guide RNA. Among all the guide
187 RNAs used against TYLCV, the ones targeting the stem-loop sequence within the
188 replication of origin were the most effective, possibly because of the reduced occurrence
189 of viable escapee variants of the virus with mutations in this region (Ali et al., 2015; Ali
190 et al., 2016). A separate lab study demonstrated that overexpression of SpCas9 and guide
191 RNAs in Nicotiana benthamiana and Arabidopsis conferred resistance to the geminivirus
192 family member Beet Severe Curly Top Virus (BSCTV) (Ji et al., 2015). CRISPR-Cas has
193 also been used to engineer resistance to RNA viruses, which comprise most known plant
194 viral pathogens.
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195 Targeting viral RNA using CRISPR-Cas has broad applicability since the
196 majority of known plant viruses contain RNA as their genetic material (Mahas and
197 Mahfouz, 2018). For example, stable expression of the RNA-targeting nuclease Cas13a
198 and the corresponding guide RNA in Nicotiana benthamiana conferred resistance to the
199 RNA virus Turnip Mosaic Virus (TuMV) (Aman et al., 2018). Using Cas13a to target
200 viral RNA substrates does not induce DNA breakage, and thus would not introduce
201 undesired off-target mutations to the host genome (Abudayyeh et al., 2017). Similarly,
202 FnCas9 has been used to demonstrate engineered resistance against RNA viruses
203 Cucumber Mosaic Virus (CMV) and Tobacco Mosaic Virus (TMV) in Nicotiana
204 benthamiana and Arabidopsis (Zhang et al., 2018).
205 Although a field test of CRISPR-Cas-based anti-viral resistance on crop species
206 has not been reported, the above lab studies have demonstrated its potential as an anti-
207 viral tool in plant genetic engineering. To ensure durable resistance, it is important to
208 consider potential viral evasions from the surveillance by the specific guide RNA used.
209 Choosing genomic targets essential for the replication or movement of the viral pathogen
210 minimizes viral evasions (Ali et al., 2016). Multiplexing the guide RNAs can also
211 improve the robustness. In addition, it has been hypothesized that the used of Cas12a
212 (also known as Cpf1) may reduce the occurrence of escapee viral variants because
213 mutations caused by CRISPR-Cas12a tend to be located outside the critical region for
214 guide RNA recognition (Ali et al., 2016). Future efforts on improving CRISPR-Cas for
215 anti-virus resistance may also be focused on establishing an in planta adaptive immunity
216 by exploiting the spacer acquisition machinery in the CRISPR-Cas adaptive immune
217 system in prokaryotes (McGinn and Marraffini, 2019).
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218
219 Deploying resistance genes for broad-spectrum and durable resistance
220 Pioneering genetic studies in plant-pathogen interaction using flax and flax rust
221 fungus by Flor in the early 1940s (Flor, 1956) established the classic “gene-for-gene”
222 theory, which states that the outcome of any given plant-pathogen interaction is largely
223 determined by a resistance (R) locus from the host and the matching avirulence factor
224 (avr) from the pathogen (Flor, 1971). When both the R gene in the plant host and the
225 cognate avr in the pathogen are present, the plant-pathogen interaction is incompatible
226 and the host exhibits full resistance to the pathogen (Flor, 1971). The effectiveness of R
227 gene-mediated resistance was first demonstrated by British scientist Rowland Biffen in
228 wheat (Triticum sp.) breeding in the early twentieth century (Biffen, 1905).
229 Since that time numerous R genes have been cloned and introduced into varieties
230 of the same species (Dewit et al., 1985), across species boundaries (Song et al., 1995) and
231 across genera (Tai et al., 1999). For example, the introduction of the maize (Zea mays) R
232 gene Rxo1 into rice (Oryza sativa) conferred resistance to bacterial streak under lab
233 conditions (Zhao et al., 2005). In tomato, multi-year fields trials under commercial type
234 growth conditions have demonstrated that tomatoes expressing the pepper Bs2 R gene
235 confer robust resistance to bacterial spot disease (Horvath et al., 2015; Kunwar et al.,
236 2018). Wheat transgenically expressing various alleles of the wheat resistance locus Pm3
237 exhibited race-specific resistance to stem rust in the field (Brunner et al., 2012). Potatoes
238 transgenically expressing wild potato R gene RB or Rpi-vnt1.1 display strong field
239 resistance to Phytophthora infestans, the causal agent of potato late blight (Bradeen et al.,
240 2009; Foster et al., 2009; Halterman et al., 2008; Jones et al., 2014). Notably, transgenic
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241 potato expressing Rpi-vnt1.1 developed by J. R. Simplot is to date the only case of a
242 genetically engineered crop with enhanced resistance to a non-viral pathogen that has
243 been approved for commercial use (Table 1).
244 Successful pathogens often evade detection by host R genes (Jones and Dangl,
245 2006). Thus, disease resistance conferred by a single R gene often lacks durability in the
246 field because pathogens can evolve to evade recognition by mutating the corresponding
247 avr gene. For improved durability and widened spectrum of disease resistance, multiple R
248 genes are often introduced simultaneously, which is commonly known as stacking (Fuchs,
249 2017; Li et al., 2001; Mundt, 2018). Resistance conferred by stacked R genes is predicted
250 to be long-lasting, as the evolution of a pathogen strain that could overcome resistance
251 conferred by multiple R genes simultaneously is a low occurrence event. One approach to
252 stack R genes is by cross-breeding of pre-existing R loci (Figure 2). Breeders can then use
253 marker-assisted selection to identify the progeny with the desired R gene
254 composition (Das and Rao, 2015). For example, bacterial blight in rice, caused by the
255 bacterial pathogen Xanthomonas oryzae pv. oryzae (Xoo), is a severe disease in much of
256 Asia and parts of Africa (Nino-Liu et al., 2006). Through cross-breeding and marker-
257 assisted selection, three R genes that confer resistance to bacterial blight in rice, Xa21,
258 Xa5, and Xa13 were introduced into a deepwater rice cultivar called Jalmagna (Pradhan
259 et al., 2015). The resulting line with the stacked R genes exhibited a higher level of field
260 resistance to eight Xoo isolates tested (Pradhan et al., 2015). Although marker-assisted
261 selection has largely improved the efficiency of the selection process, combining a large
262 number of loci through this approach can still be highly time-consuming.
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263 As an alternative to stacking through marker-assisted selection, molecular
264 stacking refers to the assembly of multiple R gene cassettes onto one plasmid and
265 introduction of the R gene cluster en bloc at a single genetic locus through plant
266 transformation (Figure 2) (Dafny-Yelin and Tzfira, 2007; Que et al., 2010). This
267 simplifies the selection process, as all the R genes introduced this way are inherited as a
268 single genetic locus. As an example, Zhu et al. in 2012 demonstrated molecular stacking
269 of three broad-spectrum potato late blight R genes Rpi-sto1, Rpi-vnt1.1, and Rpi-blb3
270 through Agrobacterium-based transformation of a susceptible potato cultivar (Zhu et al.,
271 2012). The resulting triple gene transformants displayed broad-spectrum resistance
272 equivalent to the sum of the strain-specific resistance conferred by all three individual
273 Rpi genes under greenhouse conditions (Zhu et al., 2012). In a related study, a single
274 DNA fragment harboring Rpi-vnt1.1 and Rpi-sto1 were introduced into three different
275 potato varieties through Agrobacterium-mediated transformation (Jo et al., 2014). The R
276 gene-stacked lines showed broad-spectrum late blight resistance because of the
277 introduction of both R genes (Jo et al., 2014). Notably, no foreign DNA such as a
278 selectable marker gene was included in the inserted DNA fragment in this study (Jo et al.,
279 2014), which gave potential regulatory advantages for the resulting products. Various R
280 gene-transformed potato lines exhibiting robust disease resistance in the greenhouse were
281 further evaluated in field trials, where the resistance was confirmed (Haverkort et al.,
282 2016). It is estimated that proper spatial and temporal deployment of late blight R gene
283 stacks in potatoes can reduce the use of fungicide by over 80% (Haverkort et al., 2016).
284 In a recent study of African highland potato varieties in Uganda, Ghislain et al. reported
285 that significant field resistance to the late blight pathogen could be achieved by molecular
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286 stacking of three R genes (RB, Rpi-blb2 and Rpi-vnt1.1) (Ghislain et al., 2018). The
287 yields of the triple R gene stacked potato varieties were three times higher than the
288 national average. These results demonstrate that resistance achieved by this strategy does
289 not negatively affect yield (Ghislain et al., 2018). The above studies show the simplicity
290 and effectiveness of molecular stacking in genetic engineering for broad-spectrum
291 disease resistance, especially in vegetatively propagated crop species, where breeding
292 stacks are not practical.
293 Despite the advantages of molecular stacking, the number of genes that can be
294 introduced through molecular stacking is often restrained by the capacity of the
295 vector (Que et al., 2010). The ability to insert exogenous DNA sequences at designated
296 targets in the plant genome would enable additional R gene cassettes to be introduced
297 nearby an existing R gene cluster (Ainley et al., 2013). Recent breakthroughs in genome
298 editing technologies in plants have allowed such targeted insertion of DNA fragments to
299 be achieved in diverse crop species (Figure 2) (Kumar et al., 2016; Puchta and Fauser,
300 2013; Rinaldo and Ayliffe, 2015; Voytas, 2017). As genome editing platforms in plants
301 continue to be improved, the efficiency of targeted insertion, the size limit of the DNA
302 inserts and the number of applicable plant species are increasing. Future advancements in
303 targeted gene insertion would offer new opportunities for stacking of large numbers of R
304 genes and engineered viral resistance at a single locus for broad-spectrum, durable
305 disease resistance and convenience in breeding.
306 Enriching the known repertoire of immune receptors
307 Plants possess immune receptors which perceive pathogens and trigger cellular
308 defense responses. Discovery of novel immune receptors recognizing major virulence
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309 factors will enrich the repertoire of known immune receptor genes that may be deployed
310 in the field. The nucleotide-binding leucine-rich repeats (NLR) family proteins comprise
311 a major category of intracellular immune receptors conserved across the plant and animal
312 kingdoms (Bentham et al., 2017; Li et al., 2015; Maekawa et al., 2011; Zhang et al.,
313 2017). A distinct hallmark for NLR-mediated defense is the onset of localized
314 programmed cell death known as the hypersensitive response (HR), which plays a crucial
315 role in restricting the movement of pathogens (del Pozo and Lam, 1998; Pontier et al.,
316 1998). The HR is often used as a marker to screen diverse plant germplasm for novel
317 functional NLRs recognizing known effectors (Vleeshouwers and Oliver, 2014). During
318 the screening, core virulence factors are delivered into plant leaves either as transiently-
319 expressed genes through Agro-infiltration (Du et al., 2014) or as peptides carried by
320 laboratory bacterial strains with a functional secretion system (Zhang and Coaker, 2017).
321 Once a collection of germplasm exhibiting various degrees of resistance to a
322 particular pathogen strain are identified, comparative genomics tools such as resistance
323 gene enrichment sequencing (RenSeq) (Jupe et al., 2014; Jupe et al., 2013) can be applied
324 to identify genomic variants in NLR genes that are linked to disease phenotypes (Box 3).
325 This leads to the cloning of new NLR genes and their potential deployment in crop
326 protection through genetic engineering. For example, RenSeq was successfully applied in
327 the accelerated identification and cloning of an anti-P. infestans NLR gene Rpi-amr3i
328 from Solanum americanum, a wild potato relative (Witek et al., 2016). Transgenic
329 expression of Rpi-amr3i in potato conferred full resistance to P. infestans in greenhouse
330 conditions (Witek et al., 2016). In a more recent study, Chen et al. described the rapid
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331 mapping of a newly identified anti-potato late blight NLR gene Rpi-ver1 by RenSeq in the
332 wild potato species Solanum verrucosum (Chen et al., 2018).
333 In addition to its application in potato research, RenSeq has also been employed
334 in the cloning of wheat NLR resistance genes against the stem rust fungus Puccinia
335 graminis f. sp tritici. As an example, Arora et al. used RenSeq to survey accessions of a
336 wild progenitor species of bread wheat, Ae. Tauschii ssp. strangulata for trait-linked
337 polymorphisms (Arora et al., 2019). This led to the rapid cloning of four stem rust (Sr)
338 resistance genes (Arora et al., 2019). In a related study, Steuernagel et al. applied RenSeq
339 to a mutagenized hexaploid bread wheat population to identify mutations disrupting
340 resistance to the stem rust fungus (Steuernage et al., 2016). The study revealed the
341 identity of two stem rust NLR genes, Sr22 and Sr45, which confer resistance to
342 commercially important races of the stem rust pathogen (Steuernage et al., 2016).
343 Although future field experiments are required to evaluate the potential of the
344 deployment of these newly identified NLR genes, the above lab studies demonstrate that
345 RenSeq is a powerful tool to rapidly identify novel NLR genes.
346 In addition to the identification of useful immune receptors from diverse plant
347 germplasm, researchers have attempted to engineer known immune receptors for new
348 ligand specificity. For example, the fusion of the ectodomain of the Arabidopsis thaliana
349 pattern recognition receptor EF-Tu Receptor (EFR) to the intracellular domain of the
350 phylogenetically-related rice receptor Xa21 yielded a functional chimeric receptor in both
351 rice and Arabidopsis (Holton et al., 2015; Schwessinger et al., 2015). This receptor
352 triggers defense markers when transgenic tissues are treated with elf18, the ligand of EFR,
353 although whole-plant resistance to the microbe was weak or undetectable (Holton et al.,
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354 2015; Schwessinger et al., 2015). Conversely, expression of a fusion receptor consisting
355 of the ectodomain of Xa21 and the cytoplasmic domain of EFR in rice conferred robust
356 resistance to Xoo expressing the cognate ligand of Xa21 (Thomas et al., 2018). Two
357 related studies reported that chimeric receptors generated by fusing the rice chitin-
358 binding protein Chitin Elicitor-Binding Protein (CEBiP) and the intracellular protein
359 kinase domain of the rice receptor-like kinase Xa21 or Pi-d2 confers disease resistance to
360 the rice blast fungus (Kishimoto et al., 2010; Kouzai et al., 2013). Although these studies
361 have not been advanced to field trials, they demonstrate that domain swapping among
362 immune receptors may be an attractive approach in engineering broadened recognition
363 specificity.
364 NLRs often perceive pathogens indirectly by monitoring the modification of host
365 target proteins caused by pathogen-derived virulence factors (Jones and Dangl, 2006).
366 Accordingly, many host target proteins have evolved as specialized decoys to facilitate
367 the perception of virulent factors by NLRs (van der Hoorn and Kamoun, 2008). In
368 Arabidopsis, the NLR protein RESISTANCE TO PSEUDOMONAS SYRINGAE 5
369 (RPS5) activates defense responses when the decoy protein AVRPPHB SUSCEPTIBLE
370 1 (PBS1), is cleaved by the virulence factor AvrPphB from the bacterial pathogen
371 Pseudomonas syringae (Simonich and Innes, 1995). A recent study reported the
372 modification of this decoy protein to widen the recognition specificity of the NLR protein
373 guarding it (Kim et al., 2016). Converting the decoy cleavage target of PBS1 into ones
374 that are recognized by other pathogen-secreted proteases conferred disease resistance to
375 the corresponding pathogens in the host plant (Kim et al., 2016). These results make
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376 decoy modification an attractive approach for engineering disease resistance (Kourelis et
377 al., 2016).
378 Altered specificity and activity of immune receptors can also be achieved by
379 directed molecular evolution (Lassner and Bedbrook, 2001). During this process, immune
380 receptor genes are subjected to mutagenesis to generate multiple variants, which are
381 screened for their immune functions. The process can be performed iteratively for
382 continuous improvement in the activity of the gene product. Two pioneering studies
383 demonstrated the potential value of directed molecular evolution in expanding the pool of
384 available immune receptor genes. In a search for gain-of-function mutants of the potato
385 late blight NLR gene R3a, Segretin et al. screened a library of R3a variants generated
386 through PCR-based mutagenesis and identified R3a mutants recognizing additional
387 Avr3a isoforms from P. infestans and the related blight pathogen P. capsici (Segretin et
388 al., 2014). In a follow-up study, the newly identified mutation in R3a was transferred into
389 its tomato ortholog I2 and expanded the recognition spectrum of the NLR encoded when
390 transiently expressed in Nicotiana benthaminana (Giannakopoulou et al., 2015).
391 Recently, a CRISPR-based mutagenesis platform known as EvolvR was
392 developed for the directed evolution of a precisely-defined window of genomic DNA in
393 vivo (Halperin et al., 2018; Sadanand, 2018). EvolvR employs the mutagenesis activity of
394 a fusion of the Cas9 nickase and an error-prone DNA polymerase to introduce nucleotide
395 diversification at specific genomic regions defined by guide RNAs (Halperin et al., 2018).
396 For example, EvolvR may be used for developing novel alleles of the rice immune
397 receptor Xa21 with the ability to recognize a broader array of Xoo strains (Pruitt et al.,
398 2015). Variants of Xa21 receptors carrying amino acid substitutions predicted to alter
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399 ligand specificity can be selected and introduced into susceptible rice cultivars. Future
400 development of high-throughput functional screening methods to quickly identify gene
401 variants conferring resistance phenotypes would broaden the application of directed
402 molecular evolution for enhanced disease resistance in plants.
403 Modifying susceptibility genes to attenuate pathogenicity
404 Many plant pathogens hijack host genes to facilitate the infection process. These
405 targeted host genes are often referred to as susceptibility genes (van Schie and Takken,
406 2014). The modification or removal of host susceptibility genes may, therefore, be
407 effective strategies to achieve resistance by preventing their manipulation by the
408 pathogens. RNAi and genome editing platforms (Box 2) enable efficient modification of
409 endogenous susceptibility genes in a relatively simple manner (Rinaldo and Ayliffe,
410 2015).
411 The highly conserved eukaryotic translation Initiation Factor 4E (eIF4E) in many
412 plant species is manipulated by a number of plant viruses to facilitate the viral infection
413 process (Robaglia and Caranta, 2006). Naturally occurring recessive alleles of eIF4E
414 confer viral resistance due to abolished protein-protein interaction with a specialized viral
415 virulence protein (Cavatorta et al., 2008). Based on this knowledge, Cavatorta et al.
416 demonstrated that transgenic overexpression of a site-directed-mutagenized viral-resistant
417 allele of the eIF4E conferred resistance to Potato virus Y in potato (Cavatorta et al.,
418 2011). In a more recent study, Chandrasekaran et al. knocked out the eIF4E gene in
419 cucumber using CRISPR-Cas and obtained homozygous mutant plants that are resistant
420 to a variety of viral pathogens under greenhouse conditions (Chandrasekaran et al., 2016).
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421 The SWEET family genes encode cross-membrane sugar transporters, many of
422 which are exploited by plant pathogens for virulence (Chen et al., 2010; Streubel et al.,
423 2013). Very often, when SWEET genes are activated, more sugar is transported outside of
424 the cell and made available to the bacteria (Chen et al., 2010; Chen et al., 2012). For
425 example, the promoters of rice SWEET11 and SWEET14 are targets of various
426 transcriptional activator-like (TAL) effectors from Xoo (Antony et al., 2010; Yang et al.,
427 2006a). Li et al. used TAL effector-like nuclease (TALEN) to mutate predicted TAL
428 effector-binding sites within the SWEET11 promoter (Li et al., 2012). The resulting rice
429 exhibits enhanced resistance to at least two strains of Xoo due to the lack of induction of
430 SWEET11 by the pathogens (Li et al., 2012). In a follow-up study, Zhou et al.
431 successfully generated rice lines carrying mutations in the promoter of SWEET11 using
432 CRISPR-Cas (Zhou et al., 2014). Mutations within the SWEET14 promoter in rice
433 protoplasts by CRISPR-Cas have also been demonstrated (Jiang et al., 2013). Besides
434 genome editing tools, RNAi has been employed to knock down SWEET11 in rice for
435 enhanced resistance to an Xoo strain with the cognate TAL effector (Yang et al., 2006b).
436 As a disease susceptibility gene for citrus bacterial canker disease, Citrus sinensis
437 Lateral Organ Boundary 1 (CsLOB1) encodes a transcription factor that regulates plant
438 growth and development (Hu et al., 2014). Deletion of the effector binding element
439 within the promoter of the susceptibility gene CsLOB1 by CRISPR-Cas conferred
440 resistance to the bacterial canker pathogen Xanthomonas citri spp. citri (Xcc) in orange
441 (Citrus sinensis) (Peng et al., 2017). Similarly, disrupting the coding region of CsLOB1
442 by CRISPR-Cas in grapefruit (Citrus paradisi) resulted in enhanced resistance to Xcc (Jia
443 et al., 2017). In both studies, the plants were raised in controlled environmental
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444 conditions. The effectiveness of disease resistance gained through mutating CsLOB1 in
445 citrus plants awaits further evaluation by field experiments.
446 Susceptibility genes are often conserved among plant species (Huibers et al.,
447 2013). Therefore, knowledge of susceptibility genes in one plant species can facilitate the
448 discovery of new susceptibility genes in another plant species. The Arabidopsis
449 susceptibility gene DOWNY MILDEW RESISTANT 6 (DMR6) encodes an oxygenase and
450 is up-regulated during pathogen infection (Van Damme et al., 2005; van Damme et al.,
451 2008; Zeilmaker et al., 2015). Through phylogeny and gene expression analysis,
452 Thomazella et al. identified a single DMR6 ortholog in tomato (SlDMR6-1) (Thomazella
453 et al., 2016). Knocking out SlDMR6-1 in tomato using CRISPR-Cas led to increased
454 resistance to the bacterial pathogen Pseudomonas syringae under greenhouse
455 conditions (Thomazella et al., 2016). In another study in 2016, Sun et al. selected eleven
456 Arabidopsis genes that had been previously shown to correlate with susceptibility to one
457 or more of six common plant pathogens (Sun et al., 2016). In a search for gene products
458 with similar amino acid sequences within the potato genome, they identified eleven
459 candidate susceptibility genes in potato (Sun et al., 2016). Silencing of six of these
460 candidate genes individually in potato using RNAi conferred enhanced or complete
461 resistance to the late blight pathogen in controlled environmental conditions (Sun et al.,
462 2016). These studies show that advancements in genomics, as well as the increasing
463 number of susceptibility genes documented, enables the discovery of additional
464 susceptibility genes in a large variety of crop species.
465 Modifying susceptibility genes to thwart virulence strategies of pathogens holds
466 great potential in crop protection. Because a given allele that confers susceptibility to one
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467 pathogen may confer resistance to another or have other essential biological
468 functions (Lorang et al., 2012; McGrann et al., 2014), it is important to evaluate the
469 potential side-effects of modification of susceptibility genes. It remains to be determined
470 whether the observed resistance in the instances discussed in the above lab studies is
471 robust or durable under field conditions or if the plants perform well in the field.
472
473 Concluding remarks
474 Since the first report of a genetically engineered crop conferring resistance to
475 disease in 1986, a virus-resistant tobacco expressing a viral coat protein gene (Abel et al.,
476 1986), there have been tremendous breakthroughs both in labs and in the field. In terms
477 of successful field applications, anti-viral resistance has had a clear head start with most
478 of the commercialized genetically engineered crops for disease resistance thus far falling
479 into this category. However, with new technologies that enable rapid identification of
480 novel immune receptor genes such as RenSeq and directed molecular evolution, the pool
481 of deployable genes for enhanced resistance to other microbes has expanded substantially.
482 In parallel, advancements in molecular stacking and targeted gene insertion through
483 genome editing are expected to play a major role in generating broad-spectrum resistance
484 against both viral and non-viral pathogens in the near future. Furthermore, the
485 increasingly versatile, accurate and efficient genome editing tools such as CRISPR-Cas
486 enable accurate modification of endogenous genes for disease resistance, including but
487 not limited to, susceptibility and the decoy genes.
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488 The challenges that we face in the future in genetic engineering for resistance
489 provide opportunities for further advancements in sustainable crop protection. In the
490 Outstanding Questions Box, we present some examples of the pending issues.
491 On the one hand, limitation in our knowledge of the underlying mechanism
492 governing plant innate immunity restricts the development of novel crop protection
493 strategies. For example, what amino acid residues determine the ligand specificity in
494 various immune receptors? What are the hub genes involved in plant defense that can be
495 over-expressed in various species to effectively confer broad-spectrum resistance without
496 compromising yield? On the other hand, many novel scientific discoveries are not
497 possible without high-throughput technologies with high accuracy. For example, how to
498 perform a high-throughput screen for sophisticated traits such as disease resistance? How
499 do we improve the efficiency and accuracy of CRISPR-Cas genome editing in plants,
500 especially for targeted insertion or gene replacement? How do we effectively screen and
501 regenerate diverse genetically engineered crop species and elite crop varieties? How do
502 we determine among the numerous genetically engineered individuals generated in the
503 laboratories which ones should be carried on for field studies? In addition, how do we
504 ensure the safety of the commercially grown genetically engineered food without
505 compromising innovative research? The answers to such questions are highly valuable to
506 genetic engineering for plant disease resistance in the future.
507
508 Acknowledgments
509 We thank Dr. Mawsheng Chern and Dr. Michael Steinwand for valuable suggestions on 510 the manuscript. This work was supported by research grants from the Innovative
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511 Genomics Institute (49411), the National Institutes of Health (R01GM122968) and the 512 United States Department of Agriculture (NIFA 2017-67013-26590) to P.C.R.
513
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522
523 Figure 1. CRISPR-Cas platforms for engineering viral resistance in plants. Plant 524 viruses complete their life cycles in the host cells. Viral particles with geminate capsids 525 and rod-shaped capsids are used as examples to illustrate DNA viruses and RNA viruses, 526 respectively. One of the Cas nuclease genes (SpCas9, FnCas9 or LshCas13a) and the 527 matching guide RNA(s) are expressed transgenically to generate sequence-specific 528 ribonucleoproteins which target viral DNA or RNA substrates for degradation. SpCas9 529 targets nuclear dsDNA while FnCas9 and LshCas13a have been used to target ssRNA 530 substrates in the cytoplasm. For simplicity, only one generic Cas nuclease is drawn.
531
532 Figure 2. Methods of R gene stacking. a) Stacking by marker-assisted breeding is 533 performed by cross-pollinating individuals with existing trait loci followed by marker- 534 assisted selection for progeny with combined trait loci. b) Stacking can be completed by 535 combining multiple genes into a single stack vector and introduce them together as a 536 single transgenic event. c) Stacking by targeted insertion aims at placing new gene(s) 537 adjacent to an existing locus. This process can be performed iteratively to stack large 538 numbers of genes. In b) and c), the stacked genes are genetically linked and thus can be 539 easily introduced into a different genetic background as a single locus through breeding.
540
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541 Table 1. Events of genetically engineered food crops with enhanced disease 542 resistance to microbial pathogens that have been approved for commercial 543 production*
544
Crop Initial Developer Target Pathogen Gene(s) Expressed** References Species Approval Seminis and Watermelon Mosaic Virus 2 and Squash 1994 USDA Coat Proteins Tricoli et al., 1995 Monsanto Zucchini Yellow Mosaic Virus Cucumber Mosaic Virus, Seminis and Squash 1996 USDA Watermelon Mosaic Virus 2 and Coat Proteins Tricoli et al., 1995 Monsanto Zucchini Yellow Mosaic Virus Cornell University and Gonsalves, 1998; Papaya 1996 USDA Papaya Ringspot Virus Coat Protein the University Gonsalves, 2006 of Hawaii Kaniewski et al., 2004; Potato Monsanto 1998 USDA Potato Leafroll Virus Replicase and Helicase Thomas et al., 1997 Sweet Beijing 1998 MOA Cucumber Mosaic Virus Coat Protein Zhu et al., 1996 Pepper University Kaniewski et al., 2004; Potato Monsanto 1999 USDA Potato Virus Y Coat Protein Newell et al., 1991 Beijing Tomato 1999 MOA Cucumber Mosaic Virus Coat Protein Yang et al., 1995 University South China Papaya Agricultural 2006 MOA Papaya Ringspot Virus Replicase Ye et al., 2010 University Ilardi et al., 2015; Plum USDA/ARS 2007 USDA Plum Pox Virus Coat Protein Scorza et al., 1994 University of Papaya 2009 USDA Papaya Ringspot Virus Coat Protein Davis et al., 2004 Florida +, - RNA of Viral Bonfim et al., 2007; Bean EMBRAPA 2011 CTNBio Bean Golden Mosaic Virus Replication Protein Tollefson, 2011 Phytophthora infestans (Late Potato J.R. Simplot 2015 USDA Resistance protein Foster et al., 2009 Blight) 545 546 * Data collected from The International Service for the Acquisition of Agri-biotech Applications (ISAAA) 547 and the United States Department of Agriculture-Animal and Plant Health Inspection Service (USDA- 548 APHIS). 549 **Only genes relevant to pathogen resistance are listed. 550 USDA, the U.S. Department of Agriculture. MOA, Ministry of Agriculture, China. ARS, Agriculture 551 Research Service. EMBRAPA, the Brazilian Agricultural Research Corporation. CTNBio, the Brazilian 552 National Technical Commission on Biosafety.
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1075 Zeilmaker T, Ludwig NR, Elberse J, Seidl MF, Berke L, Van Doorn A, Schuurink RC, Snel B, and Van 1076 den Ackerveken G (2015) DOWNY MILDEW RESISTANT 6 and DMR6-LIKE OXYGENASE 1 are 1077 partially redundant but distinct suppressors of immunity in Arabidopsis. Plant J 81, 210-222. 1078 1079 Zhang MX, and Coaker G (2017) Harnessing Effector-Triggered Immunity for Durable Disease 1080 Resistance. Phytopathology 107, 912-919. 1081 1082 Zhang T, Zheng Q, Yi X, An H, Zhao Y, Ma S, and Zhou G (2018) Establishing RNA virus resistance 1083 in plants by harnessing CRISPR immune system. Plant Biotechnol J 16, 1415-1423. 1084 1085 Zhang X, Dodds PN, and Bernoux M (2017) What Do We Know About NOD-Like Receptors in 1086 Plant Immunity? Annu Rev Phytopathol 55, 205-229. 1087 1088 Zhang XH, Li HX, Zhang JH, Zhang CJ, Gong PJ, Ziaf K, Xiao FM, and Ye ZB (2011) Expression of 1089 artificial microRNAs in tomato confers efficient and stable virus resistance in a cell-autonomous 1090 manner. Transgenic Res 20, 569-581. 1091 1092 Zhao BY, Lin XH, Poland J, Trick H, Leach J, and Hulbert S (2005) A maize resistance gene 1093 functions against bacterial streak disease in rice. P Natl Acad Sci USA 102, 15383-15388. 1094 1095 Zhou H, Liu B, Weeks DP, Spalding MH, and Yang B (2014) Large chromosomal deletions and 1096 heritable small genetic changes induced by CRISPR/Cas9 in rice. Nucleic Acids Res 42, 10903- 1097 10914. 1098 1099 Zhu SX, Li Y, Vossen JH, Visser RGF, and Jacobsen E (2012) Functional stacking of three resistance 1100 genes against Phytophthora infestans in potato. Transgenic Res 21, 89-99. 1101 1102 Zhu YX, OuYang WJ, Zhang YF, and Chen ZL (1996) Transgenic sweet pepper plants from 1103 Agrobacterium mediated transformation. Plant Cell Reports 16, 71-75. 1104 1105
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Downloaded from on March 14, 2019 - Published by www.plantphysiol.org Copyright © 2019 American Society of Plant Biologists. All rights reserved. ADVANCES
• Many aspects of plants’ multi-layered defenses against microbial pathogens can be genetically engineered to enhance disease resistance. • RNA interference (RNAi) has been exploited for anti-viral defense by transgenic expression of the plus or minus strand of the viral genome, inverted repeats or artificial microRNAs (amiRNAs). • CRISPR-Cas is useful in engineering resistance against DNA and RNA viruses. • Robust, broad-spectrum disease resistance can be achieved through R gene stacking. Molecular stacking or targeted gene insertion allows multiple R genes to be clustered, thus simplifying downstream genetic segregation. • Comparative genomics tools such as R gene enrichment sequencing (RenSeq) facilitate high- throughput screening of germplasms or mutants to rapidly identify candidate NLR genes recognizing core effectors. • Susceptibility genes can be modified to reduce pathogenicity.
Downloaded from on March 14, 2019 - Published by www.plantphysiol.org Copyright © 2019 American Society of Plant Biologists. All rights reserved. OUTSTANDING QUESTIONS
What hub genes can be over-expressed to confer broad-spectrum resistance without compromising yield? What residues/motifs of known NLRs/decoys determine their recognition specificities to core virulence factors? How can scientists best perform high- throughput screens to quickly identify novel resistance genes? Which genomic regions can transgenes be inserted and expressed in without incurring yield penalty (genomic safe harbors)? How can researchers reduce off-target mutations caused by genome editing reagents such as CRISPR-Cas? How can researchers deliver the genome editing reagents into elite crop varieties and regenerate plants at high efficiency? What is the most efficient approach to sort promising strategies and advance them to field trials? What is the most effective approach to ensure that genetically improved crops are safely deployed without impeding innovation?
Downloaded from on March 14, 2019 - Published by www.plantphysiol.org Copyright © 2019 American Society of Plant Biologists. All rights reserved. BOX 1. Various RNAi-based strategies for anti- viral resistance Co-suppression: Transgenic over-expressing genes encoding viral RNAs to trigger RNAi leading to the silencing of the viral RNAs.
Inverted repeats: Nucleotide sequences followed by its reverse complement sequence downstream, which are transcribed to produce transcripts with self-complementary. These transcripts are processed to form double-stranded RNA molecules, which triggers RNAi leading to the silencing of the corresponding viral RNAs.
Artificial microRNA (amiRNA): A type of engineered RNA exhibiting anti-viral resistance. It is designed by replacing nucleotide sequences of the intrinsic plant microRNA to achieve altered target specificity.
Downloaded from on March 14, 2019 - Published by www.plantphysiol.org Copyright © 2019 American Society of Plant Biologists. All rights reserved. BOX 2. CRISPR-Cas genome editing Repair through non-homologous end-joining The Clustered Regularly Interspaced Short (NHEJ) frequently leads to small insertions or Palindromic Repeats (CRISPR) - CRISPR-associated deletions, often creating knocking-out alleles. (Cas) is a widely-used genome editing platform. Homology-directed repair (HDR) enables gene CRISPR-Cas originates from a prokaryotic acquired replacements or gene insertions at the DNA immune system against viruses (Hille et al., 2018). breakpoint when an appropriate repair template is The CRISPR-Cas genome editing platform consists supplied (Rinaldo and Ayliffe, 2015). Besides of a sequence-specific endonuclease such as SpCas9, other Cas family nucleases that require SpCas9, and RNA molecules that determine the different PAM sequences have been identified or target specificity of the nucleases, often known as developed (Wu et al., 2018). Some Cas nucleases guide RNAs (Jinek et al., 2012). SpCas9 recognize recognize RNA as their substrates (Abudayyeh et and cuts at DNA targets complementary to the al., 2017; Cox et al., 2017; Price et al., 2015). These variable region on the guide RNA with an adjacent expand the range of targets that can be edited by protospacer adjacent motif (PAM) (Jinek et al., CRISPR-Cas. Furthermore, fusing the nuclease- 2012). The variable regions of guide RNA can thus deactivated Cas9 (dCas9) with diverse proteins be programmed to direct Cas9 to generate double- allows additional applications at specific genomic stranded breaks at specific targets in a given regions, such as epigenetic modification and genome (Jinek et al., 2012). Subsequent cellular transcriptional activation or repression (Mahas et DNA repair processes often introduce al., 2018). modifications at the DNA breakpoint.
Downloaded from on March 14, 2019 - Published by www.plantphysiol.org Copyright © 2019 American Society of Plant Biologists. All rights reserved. BOX 3. Resistance gene enrichment sequencing (RenSeq)
RenSeq is a comparative genomic tool used to identify nucleotide-binding leucine-rich repeats (NLR) gene family members that play a role in disease resistance. For RenSeq, a cDNA library of all NLRs of a given reference genome is used to capture genomic DNA encoding NLRs from the germplasm with novel disease resistance phenotypes (Jupe et al., 2014). The enriched NLR-encoding DNA is sequenced and compared with the reference genome to identify the polymorphisms in the NLR genes that potentially account for the observed disease resistance in the germplasm of interest (Jupe et al., 2013).
Downloaded from on March 14, 2019 - Published by www.plantphysiol.org Copyright © 2019 American Society of Plant Biologists. All rights reserved. DNA Viruses RNA Viruses
Cytoplasm Nucleus
Cas Guide RNA
Viral Nucleic Acid CRISPR-Cas
ssRNA ssDNA Cas nuclease and dsRNA dsDNA Guide RNA
Figure 1. CRISPR-Cas platforms for engineering viral resistance in plants. Plant viruses complete their life cycles in the host cells. Viral particles with geminate capsids and rod-shaped capsids are used as examples to illustrate DNA viruses and RNA viruses, respectively. One of the Cas nuclease genes (SpCas9, FnCas9 or LshCas13a) and the matching guide RNA(s) are expressed transgenically to generate sequence-specific ribonucleoproteins which target viral DNA or RNA substrates for degradation. SpCas9 targets nuclear dsDNADownloaded while FnCas9 from and on LshCas13a March 14, 2019 - Published by www.plantphysiol.org have been used to target ssRNA substrates in the cytoplasm. ForCopyright simplicity, © only 2019 one American generic Cas Society of Plant Biologists. All rights reserved. nuclease is drawn. a) Stacking by marker-assisted breeding Cross-pollination
Marker-assisted selection
Event A Event B
b) Stacking by introducing a vector with multiple genes
Transformation by a stack vector containing multiple genes
c) Stacking by targeted gene insertion
Insertion of additional Insertion of additional gene(s) adjacent to gene(s) adjacent to an existing locus an existing locus
Figure 2. Methods of R gene stacking. a) Stacking by marker-assisted breeding is performed by cross-pollinating individuals with existing trait loci followed by marker-assisted selection for progeny with combined trait loci. b) Stacking can be completed by combining multiple genes into a single stack vector and introduce them together as a single transgenic event. c) Stacking by targeted insertion aims at placing new gene(s) adjacent to an existing locus. This process can be performed iteratively to stack large numbers of genes. In b) and c), the stacked genes are genetically linked and thus can be easily introduced into a different genetic background as a single locus through breeding. Downloaded from on March 14, 2019 - Published by www.plantphysiol.org Copyright © 2019 American Society of Plant Biologists. All rights reserved. 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