genetic engineering for disease resistance in plants ... · 95 opportunities for engineering...

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

Perspectives 2

Oliver Xiaoou Dong1,2

, Pamela C. Ronald1,2

* 3

1. Department of Plant Pathology and the Genome Center, University of California, 4

Davis, CA 95616, USA. 5

2. Innovative Genomics Institute, Berkeley, CA 94704, USA 6

*For correspondence: [email protected] 7

One Sentence Summary: 8

A review of the recent progress in plant genetic engineering for disease resistance 9

highlights future challenges and opportunities in the field. 10

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

Copyright 2019 by the American Society of Plant Biologists

www.plantphysiol.orgon March 9, 2020 - Published by Downloaded from Copyright © 2019 American Society of Plant Biologists. All rights reserved.

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Background 15

Modern agriculture must provide sufficient nutrients to feed the world’s growing 16

population, which is projected to increase from 7.3 billion in 2015 to at least 9.8 billion 17

by 2050 (UN 2017). This goal is made even more challenging because of crop loss to 18

diseases. Bacterial and fungal pathogens reduce crop yields by about 15% and viruses 19

reduce yields by 3% (Oerke and Dehne, 2004). For some crops, such as potatoes, the loss 20

caused by microbial infection is estimated to be as high as 30% (Oerke and Dehne, 2004). 21

As an alternative to the application of chemical agents, researchers are altering plants’ 22

genetic composition to enhance resistance to microbial infection. 23

Conventional breeding plays an essential role in crop improvement, but usually 24

entails growing and examining large populations of crops over multiple generations, a 25

lengthy and labor-intensive process. Genetic engineering, which refers to the direct 26

alteration of an organism’s genetic material using biotechnology (Christou, 2013), 27

possesses several advantages compared with conventional breeding. First, it enables the 28

introduction, removal, modification or fine-tuning of specific genes of interest and causes 29

minimal undesired changes to the rest of the crop genome. As a result, crops specifically 30

exhibiting desired agronomic traits can be obtained in fewer generations compared with 31

conventional breeding. Second, genetic engineering allows interchange of genetic 32

material across species. Thus, the raw genetic materials that can be exploited for this 33

process is not restricted to the genes available within the species. Third, plant 34

transformation during genetic engineering allows the introduction of new genes into 35

vegetatively propagated crops such as banana (Musa sp.), cassava (Manihot esculenta), 36



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and potato (Solanum tuberosum). These features make genetic engineering a powerful 37

tool for enhancing resistance against plant pathogens. 38

Most cases of plant genetic engineering rely on conventional transgenic 39

approaches or the more recent genome editing technologies. In conventional transgenic 40

methods, genes that encode desired agronomic traits are inserted into the genome at 41

random locations through plant transformation (Lorence and Verpoorte, 2004). These 42

methods typically result in varieties containing foreign DNA. In contrast, genome editing 43

allows changes to the endogenous plant DNA, such as deletions, insertions, and 44

replacements of DNA of various lengths, at designated targets (Barrangou and Doudna, 45

2016). Depending on the type of edits introduced, the product may or may not contain 46

foreign DNA. In some areas of the world including the US (USDA, 2018), 47

Argentina (Secretariat of Agriculture, Livestock, Fishing and Food, Argentina, 2015), 48

and Brazil (CTNBio, 2018), genome-edited plants that do not contain foreign DNA are 49

regarded as equivalent to plants produced by conventional breeding, which exempts them 50

from additional regulatory measures applied to transgenic plants (Orozco, 2018). 51

Regardless of this distinction in regulatory policies, both conventional transgenic 52

techniques and genome editing continue to be powerful tools for crop improvement. 53

Plants have evolved multi-layered defense mechanisms against microbial 54

pathogens (Chisholm et al., 2006; Jones and Dangl, 2006). For example, pre-formed 55

physical and physiological barriers and their reinforcements prevent potential pathogens 56

from gaining access inside the cell (Collinge, 2009; Uma et al., 2011). Plasma 57

membrane-bound and intracellular immune receptors initiate defense responses upon the 58

perception of pathogens either directly through physically interacting with pathogen-59



4

derived elicitors, or indirectly by monitoring modifications of host targets incurred by 60

pathogens (Bentham et al., 2017; Jones and Dangl, 2006; Kourelis and van der Hoorn, 61

2018; Zhang et al., 2017). Plant-derived anti-microbial peptides and other compounds can 62

suppress pathogenicity by direct detoxification or through inhibition of the activity of 63

virulence factors (Ahuja et al., 2012; Kitajima and Sato, 1999; Thomma et al., 2002). 64

Plants also employ RNA silencing (RNAi) to detect invading viral pathogens and target 65

the viral RNA for cleavage (Rosa et al., 2018). 66

On the other side, successful pathogens have evolved strategies to overcome the 67

defense responses of their plant hosts. For instance, many bacterial and fungal pathogens 68

produce and release cell wall-degrading enzymes (Kubicek et al., 2014). Pathogens can 69

also deliver effectors into the host cytoplasm (Franceschetti et al., 2017; Xin and He, 70

2013); some of these effectors suppress host defenses and the others promote 71

susceptibility. To counteract plant RNAi-based defenses, almost all plant viruses produce 72

viral suppressors of RNAi (Zamore, 2004). Some viruses can also hijack the host RNAi 73

system to silence host genes to promote viral pathogenicity (Wang et al., 2012). 74

These aspects of host-microbe interactions provide opportunities for genetic engineering 75

for disease resistance (Dangl et al., 2013). For example, genes can be introduced into 76

plants that encode proteins capable of breaking down mycotoxins (Karlovsky, 2011) or 77

inhibiting the activity of cell wall-degrading enzymes (Juge, 2006), or nucleic acid 78

species that can sequester viral suppressors of RNAi (Wang et al., 2012) to reduce 79

microbial virulence. Plants can be engineered to synthesize and secrete antimicrobial 80

peptides or compounds that directly inhibit colonization (Osusky et al., 2000). The RNAi 81

machinery can be exploited to confer robust viral immunity by targeting viral RNA for 82



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degradation (Rosa et al., 2018). Natural or engineered immune receptors that recognize 83

diverse strains of a pathogen can be introduced individually or in combination for robust, 84

broad-spectrum disease resistance (Fuchs, 2017). Essential defense hub regulatory genes 85

can be reprogramed to fine-tune defense responses (Pieterse and Van Loon, 2004). 86

Susceptible host targets can be modified to evade recognition and manipulation by 87

pathogens (Li et al., 2012). Similarly, host decoy proteins, which serve to trap pathogens, 88

can be modified through genetic engineering for altered specificity in pathogen 89

recognition (Kim et al., 2016). For a more comprehensive overview of various aspects of 90

engineered disease resistance plants, the readers are referred to previously published 91

review articles (Collinge et al., 2010; Cook et al., 2015). 92

Increased knowledge regarding the molecular mechanism underlying plant-93

pathogen interactions and advancements in biotechnology have provided new 94

opportunities for engineering resistance to microbial pathogens in plants. In the following 95

section of this review, we update recent breakthroughs in genetic engineering in plants 96

for enhanced disease resistance and highlight several strategies that have proven 97

successful in field trials. 98

Highlights of recent breakthroughs in genetic engineering for disease resistance in 99

plants 100

Pathogen-derived resistance and RNA silencing 101

Researchers have long observed that transgenic plants expressing genes derived 102

from viral pathogens often display immunity to the pathogen and its related 103

strains (Lomonossoff, 1995). These results led to the hypothesis that ectopic expression 104



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of genes encoding wild-type or mutant viral proteins could interfere with the viral life 105

cycle (Sanford and Johnston, 1985). More recent studies demonstrated that this immunity 106

is mediated by RNAi, which plays a major role in antiviral defense in plants. 107

The detailed molecular mechanism of RNAi in anti-viral defense has been 108

described in several excellent reviews (Galvez et al., 2014; Katoch and Thakur, 2013; 109

Wang et al., 2012). Activation of RNAi has proven to be an effective approach for 110

engineering resistance to viruses (Lindbo and Dougherty, 2005; Lindbo and Falk, 2017) 111

as they rely on the host cellular machinery to complete their life cycle. Most plant viruses 112

contain single-stranded RNA (ssRNA) as their genetic information. Double-stranded 113

RNA (dsRNA) replicative intermediates often form during the replication of the viral 114

genome, triggering RNAi in the host. 115

Transgenic over-expression of viral RNA often leads to the formation of dsRNA 116

mediated by RNA-dependent RNA polymerase, which in turn triggers RNAi (Galvez et 117

al., 2014). This process is often known as co-suppression (Box 1). By far, most existing 118

cases of genetically engineered crops with resistance to viral pathogens that have been 119

approved for cultivation and consumption were generated following this concept (Table 120

1). Notably, transgenic squash (Cucurbita sp.) and papaya (Carica papaya) varieties 121

created using this approach have been grown commercially in the US for more than 122

twenty years. Field data indicate that disease resistance achieved through RNAi-mediated 123

strategies is highly durable (Fuchs and Gonsalves, 2007). The RNAi strategy has also 124

been effective in generating squash varieties that are resistant to multiple viral species 125

(Table 1). These varieties were produced by gene stacking (i.e., transgenic expression of 126

two distinct RNAi constructs targeted to different viruses) (Tricoli et al., 1995). 127



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The knowledge that dsRNA effectively induces RNAi (Lindbo and Dougherty, 128

2005) inspired the design of transgenes encoding inverted repeat sequences, the 129

transcripts of which form dsRNA (Box 1) (Waterhouse et al., 1998). This strategy was 130

used to develop a transgenic common bean variety exhibiting resistance to the DNA virus 131

Bean golden mosaic virus (BGMV) (Bonfim et al., 2007). BGMV contains single-132

stranded DNA (ssDNA) as its genetic material, which is converted to double-stranded 133

DNA (dsDNA) in the host, transcribed, and translated to produce the essential proteins 134

required for its replication (Hanley-Bowdoin et al., 2013). To generate siRNA targeting 135

the viral transcripts, sense and anti-sense sequences of part of the BGMV replication gene 136

AC1 were directionally cloned into an intron-spliced hairpin RNA expression 137

cassette (Bonfim et al., 2007). The resulting genetically engineered bean exhibited strong 138

and robust resistance in greenhouse conditions (Bonfim et al., 2007) as well as field 139

conditions (Aragao and Faria, 2009). The BGMV-resistant bean was deregulated in 2011 140

in Brazil (Table 1), which allows farmers to grow the crop. It is to date the only example 141

of a deregulated genetically engineered crop showing resistance to a DNA virus. 142

Compared with the co-suppression strategy, transgenic expression of an artificially 143

designed inverted repeat allows simultaneous generation of heterogenous siRNAs 144

targeting multiple transcripts in a relatively simple manner. 145

The discovery of microRNAs (miRNAs), a class of endogenous noncoding 146

regulatory RNAs (Ambros, 2001; Reinhart et al., 2002) led to further refinements of 147

genetic engineering for viral resistance. The miRNA machinery (Xie et al., 2015) has 148

been exploited in engineering resistance to RNA viruses by replacing specific nucleotides 149

in the miRNA-encoding genes to alter targeting specificity (Box 1). Such artificial 150



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miRNAs (amiRNAs) have been used in many lab studies in engineering resistance to a 151

wide range of plant viral pathogens such as Turnip mosaic virus (Niu et al., 2006), 152

Cucumber mosaic virus (Duan et al., 2008; Qu et al., 2007; Zhang et al., 2011), Potato 153

virus X and Potato virus Y (Ai et al., 2011). These results suggest that amiRNA-based 154

anti-viral strategies are highly promising. Disease resistance engineered by this strategy 155

awaits future field tests. 156

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Harnessing CRISPR-Cas to target viral pathogens directly 158

In recent years, the bacterially-derived Clustered Regularly Interspaced Short 159

Palindromic Repeats (CRISPR)-CRISPR-associated (Cas) technology has proven to be a 160

promising approach for engineering resistance against plant viruses (Box 2) (Wright et al., 161

2016). In many bacterial species, CRISPR-Cas acts as antiviral defense machinery. In 162

this process, an RNA-guided nuclease (often a Cas protein) cleaves at specific target sites 163

on the substrate viral DNA or RNA, leading to their degradation. The specificity of the 164

cleavage is governed by base complementarity between the CRISPR RNA (crRNA) and 165

the target DNA or RNA molecules. A number of Cas proteins with sequence-specific 166

nuclease activity have been identified (Wu et al., 2018). For example, the RNA-guided 167

endonuclease Cas9 from Streptococcus pyogenes (SpCas9) induces double-stranded 168

breaks in DNA in vivo (Jinek et al., 2012) and the RNA-guided RNases Cas13a from 169

Leptotrichia shahii (LshCas13a) or Leptotrichia wadei (LwaCas13a) target RNA in 170

vivo (Abudayyeh et al., 2017; Cox et al., 2017). Cas9 from Francisella novicida (FnCas9) 171

exhibits in vivo activity in cleaving both DNA and RNA (Price et al., 2015). 172



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The ability of CRISPR-Cas to act like molecular scissors, creating breaks at 173

sequence-specific targets in the substrate DNA or RNA molecules makes it an excellent 174

candidate tool for engineering for anti-viral defense in plants. CRISPR-Cas platforms 175

based on Cas9 or Cas13a have been successfully harnessed to engineer resistance to 176

DNA viruses or RNA viruses in planta (Figure 1). 177

The Tomato Yellow Leaf Curl Virus (TYLCV) belongs to the Geminiviridae, a 178

major family of plant viruses with single-stranded circular DNA genomes (Dry et al., 179

1993). The viral genome forms double-stranded intermediates during replication inside 180

the host cell nuclei. Overexpression of SpCas9 and artificially designed guide RNAs 181

targeting various regions of TYLCV conferred resistance to the virus in Nicotiana 182

benthamiana and tomato (Solanum lycopersicum) (Ali et al., 2015; Mahfouz et al., 2017). 183

One potential caveat of this approach is that alterations to the viral DNA sequence may 184

occur near the cleavage target due to DNA repair within the host cell. These mutations 185

could shield the viral DNA from recognition by the guide RNA. Among all the guide 186

RNAs used against TYLCV, the ones targeting the stem-loop sequence within the 187

replication of origin were the most effective, possibly because of the reduced occurrence 188

of viable escapee variants of the virus with mutations in this region (Ali et al., 2015; Ali 189

et al., 2016). A separate lab study demonstrated that overexpression of SpCas9 and guide 190

RNAs in Nicotiana benthamiana and Arabidopsis conferred resistance to the geminivirus 191

family member Beet Severe Curly Top Virus (BSCTV) (Ji et al., 2015). CRISPR-Cas has 192

also been used to engineer resistance to RNA viruses, which comprise most known plant 193

viral pathogens. 194



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Targeting viral RNA using CRISPR-Cas has broad applicability since the 195

majority of known plant viruses contain RNA as their genetic material (Mahas and 196

Mahfouz, 2018). For example, stable expression of the RNA-targeting nuclease Cas13a 197

and the corresponding guide RNA in Nicotiana benthamiana conferred resistance to the 198

RNA virus Turnip Mosaic Virus (TuMV) (Aman et al., 2018). Using Cas13a to target 199

viral RNA substrates does not induce DNA breakage, and thus would not introduce 200

undesired off-target mutations to the host genome (Abudayyeh et al., 2017). Similarly, 201

FnCas9 has been used to demonstrate engineered resistance against RNA viruses 202

Cucumber Mosaic Virus (CMV) and Tobacco Mosaic Virus (TMV) in Nicotiana 203

benthamiana and Arabidopsis (Zhang et al., 2018). 204

Although a field test of CRISPR-Cas-based anti-viral resistance on crop species 205

has not been reported, the above lab studies have demonstrated its potential as an anti-206

viral tool in plant genetic engineering. To ensure durable resistance, it is important to 207

consider potential viral evasions from the surveillance by the specific guide RNA used. 208

Choosing genomic targets essential for the replication or movement of the viral pathogen 209

minimizes viral evasions (Ali et al., 2016). Multiplexing the guide RNAs can also 210

improve the robustness. In addition, it has been hypothesized that the used of Cas12a 211

(also known as Cpf1) may reduce the occurrence of escapee viral variants because 212

mutations caused by CRISPR-Cas12a tend to be located outside the critical region for 213

guide RNA recognition (Ali et al., 2016). Future efforts on improving CRISPR-Cas for 214

anti-virus resistance may also be focused on establishing an in planta adaptive immunity 215

by exploiting the spacer acquisition machinery in the CRISPR-Cas adaptive immune 216

system in prokaryotes (McGinn and Marraffini, 2019). 217



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Deploying resistance genes for broad-spectrum and durable resistance 219

Pioneering genetic studies in plant-pathogen interaction using flax and flax rust 220

fungus by Flor in the early 1940s (Flor, 1956) established the classic “gene-for-gene” 221

theory, which states that the outcome of any given plant-pathogen interaction is largely 222

determined by a resistance (R) locus from the host and the matching avirulence factor 223

(avr) from the pathogen (Flor, 1971). When both the R gene in the plant host and the 224

cognate avr in the pathogen are present, the plant-pathogen interaction is incompatible 225

and the host exhibits full resistance to the pathogen (Flor, 1971). The effectiveness of R 226

gene-mediated resistance was first demonstrated by British scientist Rowland Biffen in 227

wheat (Triticum sp.) breeding in the early twentieth century (Biffen, 1905). 228

Since that time numerous R genes have been cloned and introduced into varieties 229

of the same species (Dewit et al., 1985), across species boundaries (Song et al., 1995) and 230

across genera (Tai et al., 1999). For example, the introduction of the maize (Zea mays) R 231

gene Rxo1 into rice (Oryza sativa) conferred resistance to bacterial streak under lab 232

conditions (Zhao et al., 2005). In tomato, multi-year fields trials under commercial type 233

growth conditions have demonstrated that tomatoes expressing the pepper Bs2 R gene 234

confer robust resistance to bacterial spot disease (Horvath et al., 2015; Kunwar et al., 235

2018). Wheat transgenically expressing various alleles of the wheat resistance locus Pm3 236

exhibited race-specific resistance to stem rust in the field (Brunner et al., 2012). Potatoes 237

transgenically expressing wild potato R gene RB or Rpi-vnt1.1 display strong field 238

resistance to Phytophthora infestans, the causal agent of potato late blight (Bradeen et al., 239

2009; Foster et al., 2009; Halterman et al., 2008; Jones et al., 2014). Notably, transgenic 240



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potato expressing Rpi-vnt1.1 developed by J. R. Simplot is to date the only case of a 241

genetically engineered crop with enhanced resistance to a non-viral pathogen that has 242

been approved for commercial use (Table 1). 243

Successful pathogens often evade detection by host R genes (Jones and Dangl, 244

2006). Thus, disease resistance conferred by a single R gene often lacks durability in the 245

field because pathogens can evolve to evade recognition by mutating the corresponding 246

avr gene. For improved durability and widened spectrum of disease resistance, multiple R 247

genes are often introduced simultaneously, which is commonly known as stacking (Fuchs, 248

2017; Li et al., 2001; Mundt, 2018). Resistance conferred by stacked R genes is predicted 249

to be long-lasting, as the evolution of a pathogen strain that could overcome resistance 250

conferred by multiple R genes simultaneously is a low occurrence event. One approach to 251

stack R genes is by cross-breeding of pre-existing R loci (Figure 2). Breeders can then use 252

marker-assisted selection to identify the progeny with the desired R gene 253

composition (Das and Rao, 2015). For example, bacterial blight in rice, caused by the 254

bacterial pathogen Xanthomonas oryzae pv. oryzae (Xoo), is a severe disease in much of 255

Asia and parts of Africa (Nino-Liu et al., 2006). Through cross-breeding and marker-256

assisted selection, three R genes that confer resistance to bacterial blight in rice, Xa21, 257

Xa5, and Xa13 were introduced into a deepwater rice cultivar called Jalmagna (Pradhan 258

et al., 2015). The resulting line with the stacked R genes exhibited a higher level of field 259

resistance to eight Xoo isolates tested (Pradhan et al., 2015). Although marker-assisted 260

selection has largely improved the efficiency of the selection process, combining a large 261

number of loci through this approach can still be highly time-consuming. 262



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As an alternative to stacking through marker-assisted selection, molecular 263

stacking refers to the assembly of multiple R gene cassettes onto one plasmid and 264

introduction of the R gene cluster en bloc at a single genetic locus through plant 265

transformation (Figure 2) (Dafny-Yelin and Tzfira, 2007; Que et al., 2010). This 266

simplifies the selection process, as all the R genes introduced this way are inherited as a 267

single genetic locus. As an example, Zhu et al. in 2012 demonstrated molecular stacking 268

of three broad-spectrum potato late blight R genes Rpi-sto1, Rpi-vnt1.1, and Rpi-blb3 269

through Agrobacterium-based transformation of a susceptible potato cultivar (Zhu et al., 270

2012). The resulting triple gene transformants displayed broad-spectrum resistance 271

equivalent to the sum of the strain-specific resistance conferred by all three individual 272

Rpi genes under greenhouse conditions (Zhu et al., 2012). In a related study, a single 273

DNA fragment harboring Rpi-vnt1.1 and Rpi-sto1 were introduced into three different 274

potato varieties through Agrobacterium-mediated transformation (Jo et al., 2014). The R 275

gene-stacked lines showed broad-spectrum late blight resistance because of the 276

introduction of both R genes (Jo et al., 2014). Notably, no foreign DNA such as a 277

selectable marker gene was included in the inserted DNA fragment in this study (Jo et al., 278

2014), which gave potential regulatory advantages for the resulting products. Various R 279

gene-transformed potato lines exhibiting robust disease resistance in the greenhouse were 280

further evaluated in field trials, where the resistance was confirmed (Haverkort et al., 281

2016). It is estimated that proper spatial and temporal deployment of late blight R gene 282

stacks in potatoes can reduce the use of fungicide by over 80% (Haverkort et al., 2016). 283

In a recent study of African highland potato varieties in Uganda, Ghislain et al. reported 284

that significant field resistance to the late blight pathogen could be achieved by molecular 285



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stacking of three R genes (RB, Rpi-blb2 and Rpi-vnt1.1) (Ghislain et al., 2018). The 286

yields of the triple R gene stacked potato varieties were three times higher than the 287

national average. These results demonstrate that resistance achieved by this strategy does 288

not negatively affect yield (Ghislain et al., 2018). The above studies show the simplicity 289

and effectiveness of molecular stacking in genetic engineering for broad-spectrum 290

disease resistance, especially in vegetatively propagated crop species, where breeding 291

stacks are not practical. 292

Despite the advantages of molecular stacking, the number of genes that can be 293

introduced through molecular stacking is often restrained by the capacity of the 294

vector (Que et al., 2010). The ability to insert exogenous DNA sequences at designated 295

targets in the plant genome would enable additional R gene cassettes to be introduced 296

nearby an existing R gene cluster (Ainley et al., 2013). Recent breakthroughs in genome 297

editing technologies in plants have allowed such targeted insertion of DNA fragments to 298

be achieved in diverse crop species (Figure 2) (Kumar et al., 2016; Puchta and Fauser, 299

2013; Rinaldo and Ayliffe, 2015; Voytas, 2017). As genome editing platforms in plants 300

continue to be improved, the efficiency of targeted insertion, the size limit of the DNA 301

inserts and the number of applicable plant species are increasing. Future advancements in 302

targeted gene insertion would offer new opportunities for stacking of large numbers of R 303

genes and engineered viral resistance at a single locus for broad-spectrum, durable 304

disease resistance and convenience in breeding. 305

Enriching the known repertoire of immune receptors 306

Plants possess immune receptors which perceive pathogens and trigger cellular 307

defense responses. Discovery of novel immune receptors recognizing major virulence 308



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factors will enrich the repertoire of known immune receptor genes that may be deployed 309

in the field. The nucleotide-binding leucine-rich repeats (NLR) family proteins comprise 310

a major category of intracellular immune receptors conserved across the plant and animal 311

kingdoms (Bentham et al., 2017; Li et al., 2015; Maekawa et al., 2011; Zhang et al., 312

2017). A distinct hallmark for NLR-mediated defense is the onset of localized 313

programmed cell death known as the hypersensitive response (HR), which plays a crucial 314

role in restricting the movement of pathogens (del Pozo and Lam, 1998; Pontier et al., 315

1998). The HR is often used as a marker to screen diverse plant germplasm for novel 316

functional NLRs recognizing known effectors (Vleeshouwers and Oliver, 2014). During 317

the screening, core virulence factors are delivered into plant leaves either as transiently-318

expressed genes through Agro-infiltration (Du et al., 2014) or as peptides carried by 319

laboratory bacterial strains with a functional secretion system (Zhang and Coaker, 2017). 320

Once a collection of germplasm exhibiting various degrees of resistance to a 321

particular pathogen strain are identified, comparative genomics tools such as resistance 322

gene enrichment sequencing (RenSeq) (Jupe et al., 2014; Jupe et al., 2013) can be applied 323

to identify genomic variants in NLR genes that are linked to disease phenotypes (Box 3). 324

This leads to the cloning of new NLR genes and their potential deployment in crop 325

protection through genetic engineering. For example, RenSeq was successfully applied in 326

the accelerated identification and cloning of an anti-P. infestans NLR gene Rpi-amr3i 327

from Solanum americanum, a wild potato relative (Witek et al., 2016). Transgenic 328

expression of Rpi-amr3i in potato conferred full resistance to P. infestans in greenhouse 329

conditions (Witek et al., 2016). In a more recent study, Chen et al. described the rapid 330



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mapping of a newly identified anti-potato late blight NLR gene Rpi-ver1 by RenSeq in the 331

wild potato species Solanum verrucosum (Chen et al., 2018). 332

In addition to its application in potato research, RenSeq has also been employed 333

in the cloning of wheat NLR resistance genes against the stem rust fungus Puccinia 334

graminis f. sp tritici. As an example, Arora et al. used RenSeq to survey accessions of a 335

wild progenitor species of bread wheat, Ae. Tauschii ssp. strangulata for trait-linked 336

polymorphisms (Arora et al., 2019). This led to the rapid cloning of four stem rust (Sr) 337

resistance genes (Arora et al., 2019). In a related study, Steuernagel et al. applied RenSeq 338

to a mutagenized hexaploid bread wheat population to identify mutations disrupting 339

resistance to the stem rust fungus (Steuernage et al., 2016). The study revealed the 340

identity of two stem rust NLR genes, Sr22 and Sr45, which confer resistance to 341

commercially important races of the stem rust pathogen (Steuernage et al., 2016). 342

Although future field experiments are required to evaluate the potential of the 343

deployment of these newly identified NLR genes, the above lab studies demonstrate that 344

RenSeq is a powerful tool to rapidly identify novel NLR genes. 345

In addition to the identification of useful immune receptors from diverse plant 346

germplasm, researchers have attempted to engineer known immune receptors for new 347

ligand specificity. For example, the fusion of the ectodomain of the Arabidopsis thaliana 348

pattern recognition receptor EF-Tu Receptor (EFR) to the intracellular domain of the 349

phylogenetically-related rice receptor Xa21 yielded a functional chimeric receptor in both 350

rice and Arabidopsis (Holton et al., 2015; Schwessinger et al., 2015). This receptor 351

triggers defense markers when transgenic tissues are treated with elf18, the ligand of EFR, 352

although whole-plant resistance to the microbe was weak or undetectable (Holton et al., 353



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2015; Schwessinger et al., 2015). Conversely, expression of a fusion receptor consisting 354

of the ectodomain of Xa21 and the cytoplasmic domain of EFR in rice conferred robust 355

resistance to Xoo expressing the cognate ligand of Xa21 (Thomas et al., 2018). Two 356

related studies reported that chimeric receptors generated by fusing the rice chitin-357

binding protein Chitin Elicitor-Binding Protein (CEBiP) and the intracellular protein 358

kinase domain of the rice receptor-like kinase Xa21 or Pi-d2 confers disease resistance to 359

the rice blast fungus (Kishimoto et al., 2010; Kouzai et al., 2013). Although these studies 360

have not been advanced to field trials, they demonstrate that domain swapping among 361

immune receptors may be an attractive approach in engineering broadened recognition 362

specificity. 363

NLRs often perceive pathogens indirectly by monitoring the modification of host 364

target proteins caused by pathogen-derived virulence factors (Jones and Dangl, 2006). 365

Accordingly, many host target proteins have evolved as specialized decoys to facilitate 366

the perception of virulent factors by NLRs (van der Hoorn and Kamoun, 2008). In 367

Arabidopsis, the NLR protein RESISTANCE TO PSEUDOMONAS SYRINGAE 5 368

(RPS5) activates defense responses when the decoy protein AVRPPHB SUSCEPTIBLE 369

1 (PBS1), is cleaved by the virulence factor AvrPphB from the bacterial pathogen 370

Pseudomonas syringae (Simonich and Innes, 1995). A recent study reported the 371

modification of this decoy protein to widen the recognition specificity of the NLR protein 372

guarding it (Kim et al., 2016). Converting the decoy cleavage target of PBS1 into ones 373

that are recognized by other pathogen-secreted proteases conferred disease resistance to 374

the corresponding pathogens in the host plant (Kim et al., 2016). These results make 375



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decoy modification an attractive approach for engineering disease resistance (Kourelis et 376

al., 2016). 377

Altered specificity and activity of immune receptors can also be achieved by 378

directed molecular evolution (Lassner and Bedbrook, 2001). During this process, immune 379

receptor genes are subjected to mutagenesis to generate multiple variants, which are 380

screened for their immune functions. The process can be performed iteratively for 381

continuous improvement in the activity of the gene product. Two pioneering studies 382

demonstrated the potential value of directed molecular evolution in expanding the pool of 383

available immune receptor genes. In a search for gain-of-function mutants of the potato 384

late blight NLR gene R3a, Segretin et al. screened a library of R3a variants generated 385

through PCR-based mutagenesis and identified R3a mutants recognizing additional 386

Avr3a isoforms from P. infestans and the related blight pathogen P. capsici (Segretin et 387

al., 2014). In a follow-up study, the newly identified mutation in R3a was transferred into 388

its tomato ortholog I2 and expanded the recognition spectrum of the NLR encoded when 389

transiently expressed in Nicotiana benthaminana (Giannakopoulou et al., 2015). 390

Recently, a CRISPR-based mutagenesis platform known as EvolvR was 391

developed for the directed evolution of a precisely-defined window of genomic DNA in 392

vivo (Halperin et al., 2018; Sadanand, 2018). EvolvR employs the mutagenesis activity of 393

a fusion of the Cas9 nickase and an error-prone DNA polymerase to introduce nucleotide 394

diversification at specific genomic regions defined by guide RNAs (Halperin et al., 2018). 395

For example, EvolvR may be used for developing novel alleles of the rice immune 396

receptor Xa21 with the ability to recognize a broader array of Xoo strains (Pruitt et al., 397

2015). Variants of Xa21 receptors carrying amino acid substitutions predicted to alter 398



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ligand specificity can be selected and introduced into susceptible rice cultivars. Future 399

development of high-throughput functional screening methods to quickly identify gene 400

variants conferring resistance phenotypes would broaden the application of directed 401

molecular evolution for enhanced disease resistance in plants. 402

Modifying susceptibility genes to attenuate pathogenicity 403

Many plant pathogens hijack host genes to facilitate the infection process. These 404

targeted host genes are often referred to as susceptibility genes (van Schie and Takken, 405

2014). The modification or removal of host susceptibility genes may, therefore, be 406

effective strategies to achieve resistance by preventing their manipulation by the 407

pathogens. RNAi and genome editing platforms (Box 2) enable efficient modification of 408

endogenous susceptibility genes in a relatively simple manner (Rinaldo and Ayliffe, 409

2015). 410

The highly conserved eukaryotic translation Initiation Factor 4E (eIF4E) in many 411

plant species is manipulated by a number of plant viruses to facilitate the viral infection 412

process (Robaglia and Caranta, 2006). Naturally occurring recessive alleles of eIF4E 413

confer viral resistance due to abolished protein-protein interaction with a specialized viral 414

virulence protein (Cavatorta et al., 2008). Based on this knowledge, Cavatorta et al. 415

demonstrated that transgenic overexpression of a site-directed-mutagenized viral-resistant 416

allele of the eIF4E conferred resistance to Potato virus Y in potato (Cavatorta et al., 417

2011). In a more recent study, Chandrasekaran et al. knocked out the eIF4E gene in 418

cucumber using CRISPR-Cas and obtained homozygous mutant plants that are resistant 419

to a variety of viral pathogens under greenhouse conditions (Chandrasekaran et al., 2016). 420



20

The SWEET family genes encode cross-membrane sugar transporters, many of 421

which are exploited by plant pathogens for virulence (Chen et al., 2010; Streubel et al., 422

2013). Very often, when SWEET genes are activated, more sugar is transported outside of 423

the cell and made available to the bacteria (Chen et al., 2010; Chen et al., 2012). For 424

example, the promoters of rice SWEET11 and SWEET14 are targets of various 425

transcriptional activator-like (TAL) effectors from Xoo (Antony et al., 2010; Yang et al., 426

2006a). Li et al. used TAL effector-like nuclease (TALEN) to mutate predicted TAL 427

effector-binding sites within the SWEET11 promoter (Li et al., 2012). The resulting rice 428

exhibits enhanced resistance to at least two strains of Xoo due to the lack of induction of 429

SWEET11 by the pathogens (Li et al., 2012). In a follow-up study, Zhou et al. 430

successfully generated rice lines carrying mutations in the promoter of SWEET11 using 431

CRISPR-Cas (Zhou et al., 2014). Mutations within the SWEET14 promoter in rice 432

protoplasts by CRISPR-Cas have also been demonstrated (Jiang et al., 2013). Besides 433

genome editing tools, RNAi has been employed to knock down SWEET11 in rice for 434

enhanced resistance to an Xoo strain with the cognate TAL effector (Yang et al., 2006b). 435

As a disease susceptibility gene for citrus bacterial canker disease, Citrus sinensis 436

Lateral Organ Boundary 1 (CsLOB1) encodes a transcription factor that regulates plant 437

growth and development (Hu et al., 2014). Deletion of the effector binding element 438

within the promoter of the susceptibility gene CsLOB1 by CRISPR-Cas conferred 439

resistance to the bacterial canker pathogen Xanthomonas citri spp. citri (Xcc) in orange 440

(Citrus sinensis) (Peng et al., 2017). Similarly, disrupting the coding region of CsLOB1 441

by CRISPR-Cas in grapefruit (Citrus paradisi) resulted in enhanced resistance to Xcc (Jia 442

et al., 2017). In both studies, the plants were raised in controlled environmental 443



21

conditions. The effectiveness of disease resistance gained through mutating CsLOB1 in 444

citrus plants awaits further evaluation by field experiments. 445

Susceptibility genes are often conserved among plant species (Huibers et al., 446

2013). Therefore, knowledge of susceptibility genes in one plant species can facilitate the 447

discovery of new susceptibility genes in another plant species. The Arabidopsis 448

susceptibility gene DOWNY MILDEW RESISTANT 6 (DMR6) encodes an oxygenase and 449

is up-regulated during pathogen infection (Van Damme et al., 2005; van Damme et al., 450

2008; Zeilmaker et al., 2015). Through phylogeny and gene expression analysis, 451

Thomazella et al. identified a single DMR6 ortholog in tomato (SlDMR6-1) (Thomazella 452

et al., 2016). Knocking out SlDMR6-1 in tomato using CRISPR-Cas led to increased 453

resistance to the bacterial pathogen Pseudomonas syringae under greenhouse 454

conditions (Thomazella et al., 2016). In another study in 2016, Sun et al. selected eleven 455

Arabidopsis genes that had been previously shown to correlate with susceptibility to one 456

or more of six common plant pathogens (Sun et al., 2016). In a search for gene products 457

with similar amino acid sequences within the potato genome, they identified eleven 458

candidate susceptibility genes in potato (Sun et al., 2016). Silencing of six of these 459

candidate genes individually in potato using RNAi conferred enhanced or complete 460

resistance to the late blight pathogen in controlled environmental conditions (Sun et al., 461

2016). These studies show that advancements in genomics, as well as the increasing 462

number of susceptibility genes documented, enables the discovery of additional 463

susceptibility genes in a large variety of crop species. 464

Modifying susceptibility genes to thwart virulence strategies of pathogens holds 465

great potential in crop protection. Because a given allele that confers susceptibility to one 466



22

pathogen may confer resistance to another or have other essential biological 467

functions (Lorang et al., 2012; McGrann et al., 2014), it is important to evaluate the 468

potential side-effects of modification of susceptibility genes. It remains to be determined 469

whether the observed resistance in the instances discussed in the above lab studies is 470

robust or durable under field conditions or if the plants perform well in the field. 471

472

Concluding remarks 473

Since the first report of a genetically engineered crop conferring resistance to 474

disease in 1986, a virus-resistant tobacco expressing a viral coat protein gene (Abel et al., 475

1986), there have been tremendous breakthroughs both in labs and in the field. In terms 476

of successful field applications, anti-viral resistance has had a clear head start with most 477

of the commercialized genetically engineered crops for disease resistance thus far falling 478

into this category. However, with new technologies that enable rapid identification of 479

novel immune receptor genes such as RenSeq and directed molecular evolution, the pool 480

of deployable genes for enhanced resistance to other microbes has expanded substantially. 481

In parallel, advancements in molecular stacking and targeted gene insertion through 482

genome editing are expected to play a major role in generating broad-spectrum resistance 483

against both viral and non-viral pathogens in the near future. Furthermore, the 484

increasingly versatile, accurate and efficient genome editing tools such as CRISPR-Cas 485

enable accurate modification of endogenous genes for disease resistance, including but 486

not limited to, susceptibility and the decoy genes. 487



23

The challenges that we face in the future in genetic engineering for resistance 488

provide opportunities for further advancements in sustainable crop protection. In the 489

Outstanding Questions Box, we present some examples of the pending issues. 490

On the one hand, limitation in our knowledge of the underlying mechanism 491

governing plant innate immunity restricts the development of novel crop protection 492

strategies. For example, what amino acid residues determine the ligand specificity in 493

various immune receptors? What are the hub genes involved in plant defense that can be 494

over-expressed in various species to effectively confer broad-spectrum resistance without 495

compromising yield? On the other hand, many novel scientific discoveries are not 496

possible without high-throughput technologies with high accuracy. For example, how to 497

perform a high-throughput screen for sophisticated traits such as disease resistance? How 498

do we improve the efficiency and accuracy of CRISPR-Cas genome editing in plants, 499

especially for targeted insertion or gene replacement? How do we effectively screen and 500

regenerate diverse genetically engineered crop species and elite crop varieties? How do 501

we determine among the numerous genetically engineered individuals generated in the 502

laboratories which ones should be carried on for field studies? In addition, how do we 503

ensure the safety of the commercially grown genetically engineered food without 504

compromising innovative research? The answers to such questions are highly valuable to 505

genetic engineering for plant disease resistance in the future. 506

507

Acknowledgments 508

We thank Dr. Mawsheng Chern and Dr. Michael Steinwand for valuable suggestions on 509

the manuscript. This work was supported by research grants from the Innovative 510



24

Genomics Institute (49411), the National Institutes of Health (R01GM122968) and the 511

United States Department of Agriculture (NIFA 2017-67013-26590) to P.C.R. 512

513

514

515

516

517

518

519

520

521

522

Figure 1. CRISPR-Cas platforms for engineering viral resistance in plants. Plant 523

viruses complete their life cycles in the host cells. Viral particles with geminate capsids 524

and rod-shaped capsids are used as examples to illustrate DNA viruses and RNA viruses, 525

respectively. One of the Cas nuclease genes (SpCas9, FnCas9 or LshCas13a) and the 526

matching guide RNA(s) are expressed transgenically to generate sequence-specific 527

ribonucleoproteins which target viral DNA or RNA substrates for degradation. SpCas9 528

targets nuclear dsDNA while FnCas9 and LshCas13a have been used to target ssRNA 529

substrates in the cytoplasm. For simplicity, only one generic Cas nuclease is drawn. 530

531

Figure 2. Methods of R gene stacking. a) Stacking by marker-assisted breeding is 532

performed by cross-pollinating individuals with existing trait loci followed by marker-533

assisted selection for progeny with combined trait loci. b) Stacking can be completed by 534

combining multiple genes into a single stack vector and introduce them together as a 535

single transgenic event. c) Stacking by targeted insertion aims at placing new gene(s) 536

adjacent to an existing locus. This process can be performed iteratively to stack large 537

numbers of genes. In b) and c), the stacked genes are genetically linked and thus can be 538

easily introduced into a different genetic background as a single locus through breeding. 539

540



25

Table 1. Events of genetically engineered food crops with enhanced disease 541

resistance to microbial pathogens that have been approved for commercial 542

production* 543

544

Crop

Species Developer

Initial

Approval Target Pathogen Gene(s) Expressed** References

Squash Seminis and

Monsanto 1994 USDA

Watermelon Mosaic Virus 2 and

Zucchini Yellow Mosaic Virus Coat Proteins Tricoli et al., 1995

Squash Seminis and

Monsanto 1996 USDA

Cucumber Mosaic Virus,

Watermelon Mosaic Virus 2 and

Zucchini Yellow Mosaic Virus

Coat Proteins Tricoli et al., 1995

Papaya

Cornell

University and

the University

of Hawaii

1996 USDA Papaya Ringspot Virus Coat Protein Gonsalves, 1998;

Gonsalves, 2006

Potato Monsanto 1998 USDA Potato Leafroll Virus Replicase and Helicase Kaniewski et al., 2004;

Thomas et al., 1997

Sweet

Pepper

Beijing

University 1998 MOA Cucumber Mosaic Virus Coat Protein Zhu et al., 1996

Potato Monsanto 1999 USDA Potato Virus Y Coat Protein Kaniewski et al., 2004;

Newell et al., 1991

Tomato Beijing

University 1999 MOA Cucumber Mosaic Virus Coat Protein Yang et al., 1995

Papaya

South China

Agricultural

University

2006 MOA Papaya Ringspot Virus Replicase Ye et al., 2010

Plum USDA/ARS 2007 USDA Plum Pox Virus Coat Protein Ilardi et al., 2015;

Scorza et al., 1994

Papaya University of

Florida 2009 USDA Papaya Ringspot Virus Coat Protein Davis et al., 2004

Bean EMBRAPA 2011 CTNBio Bean Golden Mosaic Virus +, - RNA of Viral

Replication Protein

Bonfim et al., 2007;

Tollefson, 2011

Potato J.R. Simplot 2015 USDA Phytophthora infestans (Late

Blight) Resistance protein Foster et al., 2009

545

* Data collected from The International Service for the Acquisition of Agri-biotech Applications (ISAAA) 546 and the United States Department of Agriculture-Animal and Plant Health Inspection Service (USDA-547 APHIS). 548

**Only genes relevant to pathogen resistance are listed. 549

USDA, the U.S. Department of Agriculture. MOA, Ministry of Agriculture, China. ARS, Agriculture 550 Research Service. EMBRAPA, the Brazilian Agricultural Research Corporation. CTNBio, the Brazilian 551 National Technical Commission on Biosafety. 552



26

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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.



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?



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.



BOX 2. CRISPR-Cas genome editing

The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) - CRISPR-associated (Cas) is a widely-used genome editing platform. CRISPR-Cas originates from a prokaryotic acquired immune system against viruses (Hille et al., 2018). The CRISPR-Cas genome editing platform consists of a sequence-specific endonuclease such as SpCas9, and RNA molecules that determine the target specificity of the nucleases, often known as guide RNAs (Jinek et al., 2012). SpCas9 recognize and cuts at DNA targets complementary to the variable region on the guide RNA with an adjacent protospacer adjacent motif (PAM) (Jinek et al., 2012). The variable regions of guide RNA can thus be programmed to direct Cas9 to generate double-stranded breaks at specific targets in a given genome (Jinek et al., 2012). Subsequent cellular DNA repair processes often introduce modifications at the DNA breakpoint.

Repair through non-homologous end-joining (NHEJ) frequently leads to small insertions or deletions, often creating knocking-out alleles. Homology-directed repair (HDR) enables gene replacements or gene insertions at the DNA breakpoint when an appropriate repair template is supplied (Rinaldo and Ayliffe, 2015). Besides SpCas9, other Cas family nucleases that require different PAM sequences have been identified or developed (Wu et al., 2018). Some Cas nucleases recognize RNA as their substrates (Abudayyeh et al., 2017; Cox et al., 2017; Price et al., 2015). These expand the range of targets that can be edited by CRISPR-Cas. Furthermore, fusing the nuclease-deactivated Cas9 (dCas9) with diverse proteins allows additional applications at specific genomic regions, such as epigenetic modification and transcriptional activation or repression (Mahas et al., 2018).



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).



ssRNA ssDNA

dsDNAdsRNA

Viral Nucleic Acid CRISPR-Cas

Guide RNA

DNA Viruses RNA Viruses

Cas Guide RNA

CytoplasmNucleus

and

Cas nuclease

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 dsDNA while FnCas9 and LshCas13a have been used to target ssRNA substrates in the cytoplasm. For simplicity, only one generic Cas nuclease is drawn.



a) Stacking by marker-assisted breeding

b) Stacking by introducing a vector with multiple genes

c) Stacking by targeted gene insertion

Event A Event B

Marker-assisted selection

Transformation by a stack vector containing multiple genes

Insertion of additional gene(s) adjacent to

an existing locus

Cross-pollination

Insertion of additional gene(s) adjacent to

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.



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