Physiology Preview. Published on March 13, 2019, as DOI:10.1104/pp.18.01224

1 Genetic Engineering for Disease Resistance in : Recent Progress and Future

2 Perspectives

3 Oliver Xiaoou Dong1,2, Pamela C. Ronald1,2 *

4 1. Department of 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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12

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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 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 (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 (Musa sp.), cassava (Manihot esculenta),

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37 and (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 -

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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

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 ( sp.) and (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 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 (miRNAs), a class of endogenous noncoding

147 regulatory (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 (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 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 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 (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 (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 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 , 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 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 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

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 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 . 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 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 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

514

515

516

517

518

519

520

521

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 Coat Protein the University Gonsalves, 2006 of 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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• 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.

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 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.

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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).

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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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