The long road to engineering durable disease resistance in wheat
Item Type Article
Authors Wulff, Brande B. H.;Krattinger, Simon G.
Citation Wulff, B. B., & Krattinger, S. G. (2022). The long road to
engineering durable disease resistance in wheat. Current Opinion in Biotechnology, 73, 270–275. doi:10.1016/j.copbio.2021.09.002 Eprint version Post-print
DOI
10.1016/j.copbio.2021.09.002Publisher Elsevier BV
Journal Current Opinion in Biotechnology
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Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Current Opinion in Biotechnology, [73, , (2021-09-24)] DOI:
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The long road to engineering durable disease resistance in wheat
1 2
Brande BH Wulff and Simon G Krattinger 3
4
Address:
5
Center for Desert Agriculture,Biological and Environmental Science and Engineering Division (BESE), 6
King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia 7
8
Corresponding author:
9
Krattinger, Simon G ([email protected]) 10
11 12
Highlights 13
Nearly half of the wheat disease resistance genes are derived from outside the bread wheat gene 14
pool.
15
Most of the known wheat disease resistance genes will be cloned in the coming 15 years.
16
Structural and molecular understanding of disease resistance will enable knowledge-guided 17
disease resistance engineering.
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19
2 Abstract
20
A rich past of generating and configuring genetic structures in wheat (Triticum aestivum) combined with 21
advances in DNA sequencing, bioinformatics and genome engineering has transformed the field of wheat 22
functional genomics. Cloning a gene from the large and complex wheat genome is no longer unattainable;
23
in the past 5 years alone, the molecular identity of 33 wheat disease resistance genes has been elucidated.
24
The next 15 years will see the cloning of most of the ~460 known wheat resistance genes and their 25
corresponding effectors. Coupled with mechanistic insights into how resistance genes, effectors and 26
pathogenicity targets interact and are affected by different genetic backgrounds, this will drive systems 27
biology and synthetic engineering studies towards the alluring goal of generating durable disease resistance 28
in wheat.
29
30
3 Introduction
31
Generating durably disease-resistant crop cultivars has been a major endeavor since the beginning of plant 32
breeding in the early 1900s. Plant diseases caused or transmitted by viruses, bacteria, oomycetes, fungi, 33
nematodes and insect are a major cause of crop production losses. Around a fifth of global bread wheat 34
(Triticum aestivum) production is lost to diseases and pests [1]. In absolute terms, these losses amount to 35
~210 million tons of wheat grain per year, a quantity sufficient to bake 290 billion loaves of bread. Many 36
of the major wheat diseases occur late during the growing season. Wheat pathogens therefore not only 37
destroy our daily bread, but also waste a lot of energy, resources and water that have been invested in raising 38
the wheat crop. For example, the energy required to grow 210 million tons of wheat could provide electricity 39
to 40–390 million households for 1 year (Supplementary Dataset). Wheat pathogens are living organisms 40
that evolve rapidly and circumvent widely deployed disease resistance genes. This has resulted in the 41
emergence of new pathogens and pathogen strains, sometimes with catastrophic consequences for certain 42
wheat-growing areas [2-4]. Dire examples include the host jump of a blast pathogen from wild grasses to 43
wheat in Brazil in 1985 and its subsequent introduction to Bangladesh in 2016 [2], and the emergence of 44
the aggressive Ug99 stem rust races [5]. The high adaptability of wheat pathogens has severely complicated 45
efficient breeding for durable disease resistance. Although some wheat cultivars show durable resistance 46
against certain pathogens [6], we have not yet accumulated enough knowledge to predict the durability of 47
resistance gene combinations or employ knowledge-based approaches for breeding wheat crops with 48
durable resistance against most wheat pathogens. In this review, we present a roadmap towards knowledge- 49
based disease resistance breeding and highlight how biotechnology can play a major role in achieving this 50
goal.
51
52
From blind watchmakers to knowledge-guided engineers 53
54
1 – The genetics era 55
4
Hexaploid bread and tetraploid pasta wheat are excellent examples of the benefits biotechnology could have 56
in breeding for disease resistance. Owing to its high genetic redundancy, polyploid wheat tolerates an 57
astonishing amount of chromosome rearrangement, including large deletions, translocations and 58
introgressions from distant relatives [7]. This ‘genetic plasticity’ has been exploited by breeders to 59
introgress wheat disease resistance genes from cultivated and wild wheat relatives. Today, these alien 60
introgressions play a pivotal role in protecting wheat from pathogens. The first cross between two wheat 61
species was performed by Edgar McFadden in 1916 [8] (Figure 1). This iconic cross between the tetraploid 62
‘Yaroslav’ emmer (Triticum turgidum ssp. dicoccum) and the bread wheat cultivar ‘Marquis’ (Triticum 63
aestivum) was so seminal for wheat research and breeding that it may well be considered the birth of wheat 64
biotechnology. From one single fertile offspring of the ‘Yaroslav’–‘Marquis’ cross, McFadden developed 65
the bread wheat cultivar ‘Hope’, which had inherited durable resistance against fungal stem rust disease 66
from ‘Yaroslav’ emmer. In the early 1900s, stem rust was the major limiting factor for wheat production 67
across many areas of the United States. This cross demonstrated for the first time that disease resistance 68
genes could be functionally transferred into bread wheat from relatives, a concept that would later be widely 69
exploited in wheat breeding.
70
From the mid-1940s onwards, the genetic basis of wheat disease resistance was studied more systematically 71
and the designation of disease resistance genes was standardized [9]. Around the same time, Harold Henry 72
Flor formulated the gene-for-gene model while working on flax–flax rust interactions [10]. This model 73
describes that inheritance of resistance is controlled by matching pairs of resistance (R) genes in the host 74
plant and corresponding avirulence (Avr) genes in the pathogen. Today, the ‘wheat gene catalogue’ lists 75
over 460 disease resistance genes, 42% of which are derived from outside the bread wheat gene pool [11].
76
Major drawbacks of introgressing genes from wheat relatives are (i) the low fertility of many interspecific 77
crosses and (ii) the co-introgression of undesired traits through linkage drag. For example, it took McFadden 78
over 20 years of selection to identify a wheat plant that showed both good stem rust resistance and good 79
agronomic performance [8]. Using biotechnology, it is now possible to move disease resistance genes 80
5
between different wheat species, significantly speeding up the introgression of alien genes without linkage 81
drag.
82
83
2 – The genomics-assisted gene cloning era 84
Wheat breeding in the 20th century was dominated by genetics. During this time, significant progress was 85
made in understanding and utilizing the genetic bases of agronomically important traits, including disease 86
resistance, without knowing the nucleotide sequences of the underlying genes. In the late 20th and early 21st 87
centuries, genomics emerged as a new and powerful scientific discipline that profoundly changed wheat 88
research and breeding, resulting in a shift from a genetic to a molecular understanding of disease resistance.
89
The first wheat disease resistance genes were molecularly cloned in 2003 [12,13]. Cloning of a gene (i.e., 90
identification of the nucleotide sequence controlling a specific trait) is a prerequisite for biotechnological 91
applications such as transgenesis and genome editing. There was one particular challenge, however, that 92
severely hampered the routine cloning of wheat disease resistance genes in the early 2000s—the size and 93
complexity of the wheat genome. The bread wheat genome (~16 Gb) is five times larger than the human 94
genome (~3.06 Gb), with 80% consisting of highly repetitive motifs. Consequently, only a few wheat 95
disease resistance genes were cloned during the first decade of the 21st century [6,11]. Initially, the key to 96
overcoming this enormous technological challenge was to develop genomics-based gene cloning protocols 97
specifically tailored to handle the large and complex wheat genomes. Many of these protocols were based 98
on reduced-representation sequencing, which reduces the size and complexity of the wheat genome by 99
sequence capture or chromosome flow sorting [14-17]. However, the drop in cost of DNA sequence 100
acquisition and improved computation now facilitate the use of whole-genome sequencing of entire 101
Triticeae diversity panels to assist gene cloning projects [18]. Together with the generation of the first 102
chromosome-scale wheat genome assemblies [7,19,20], these gene cloning protocols have been essential 103
for significantly accelerating disease resistance gene cloning in wheat. Of the 47 wheat disease resistance 104
genes cloned to date, 33 were reported during the last 5 years [11]. We propose that we now have all the 105
6
tools in hand to clone most of the known wheat disease resistance genes in the coming 15 years [11]. The 106
resulting ‘wheat resistance (R) gene atlas’ will provide the basis for making informed choices in wheat 107
disease resistance breeding and biotechnology, for example by allowing gene stacks (i.e., resistance gene 108
cassettes that are simultaneously introduced to engineer polygenic disease resistance) and modification of 109
disease resistance genes through genome editing.
110
111
3 – Understanding molecular mechanisms 112
Currently, the biggest scientific limitation to using knowledge-based biotechnological approaches for 113
engineering durable disease resistance is our poor understanding of the molecular mechanisms of pathogen 114
perception. The majority (61%) of the cloned disease resistance genes in plants encode nucleotide-binding 115
leucine-rich repeat (NLR) proteins [21]. Members of this family of intracellular receptor proteins directly 116
or indirectly perceive pathogen-secreted effector proteins [22]. In wheat, 32 of the 47 cloned disease 117
resistance genes encode NLRs. Although virulence effectors for several wheat R genes were identified 118
recently [23-29], the exact perception mechanisms remain unknown. Some exciting progress in the model 119
plant Arabidopsis thaliana and in tomato (Solanum lycopersicum) has defined the general concepts of 120
NLR–effector interactions. Probably the most seminal contribution was the formulation of the so-called 121
‘Guard Model’ (Figure 1). This model postulates that NLRs can perceive effector proteins indirectly by 122
guarding effector targets, which are often components of the basal immune response [30,31]. Modifications 123
to the ‘guardee’ caused by the effector trigger a strong immune response. The guard model provided long- 124
sought explanations for how a relatively small number of NLRs in plant genomes could detect a very large 125
number of pathogen effectors and keep up with rapidly evolving microbial pathogens. For most NLRs, 126
however, the corresponding guardee is not yet known. To achieve durable disease resistance, we need to 127
invest in a much wider understanding of guardee–NLR interactions. In particular, we must identify the 128
guardees for most NLRs of the wheat R gene atlas. Only then can we make informed choices about which 129
NLR genes would be most effective in a gene stack, for example by ensuring that the stack incorporates 130
7
NLRs guarding different effector targets. Another important contribution towards determining the 131
biochemical mechanisms of NLR-based immunity was resolving the first NLR protein structures using 132
cryo-electron microscopy. These studies revealed that NLRs form wheel-like oligomeric complexes after 133
effector perception and that these complexes move to the plasma membrane where they might serve as 134
calcium influx channels [32-35]. Functional and structural studies on NLR perception mechanisms have 135
been accompanied by recent progress in predicting protein structure based on deep learning [36]. The 136
combination of functional studies and AI-based protein structure prediction is the next big frontier in plant–
137
pathogen interaction studies and will result in a greatly improved understanding of specific NLR–effector 138
interactions. A detailed understanding of the interaction between the rice (Oryza sativa) NLR Pikp and the 139
corresponding rice blast pathogen effector AVR-Pik, for example, allowed rational design of synthetic 140
NLRs with expanded recognition capacity against rice blast [37]. These knowledge-guided approaches are 141
much more effective than previous ‘blind watchmaker’ approaches based on random mutagenesis [38-40].
142
Besides NLRs, other gene families play an important role in wheat disease resistance. Of particular interest 143
are genes conferring partial, but broad-spectrum, resistance against multiple pathogens. Examples are the 144
Lr67/Yr46/Sr55/Pm46 and Lr34/Yr18/Sr57/Pm38 genes that encode a hexose transporter and an ATP- 145
binding cassette (ABC) transporter, respectively [41-43]. Lr67 and Lr34 confer race non-specific resistance 146
against the fungal diseases leaf rust, stripe rust, stem rust and powdery mildew and are functionally 147
transferrable across multiple cereal species [42,44]. A better understanding of the molecular mechanisms 148
conferred by these durable disease resistance genes will be essential for providing durable protection to 149
wheat in combination with canonical NLRs.
150
A frequent observation in wheat disease resistance breeding is the so-called ‘genetic background effect,’
151
meaning that the phenotype conferred by a particular disease resistance gene can differ depending on the 152
wheat cultivar. In extreme cases, the genetic background effect results in a wheat cultivar being susceptible 153
despite the presence of a resistance gene [45,46]. Genetic background effects can be explained by the 154
segregation of unlinked modifiers and suppressors. Although these background effects are of great 155
8
relevance to wheat breeding and biotechnology (e.g., the optimal expression of gene stacks), their genetic 156
and molecular bases are not well understood. The only example of a cloned ‘modifier’ gene affecting wheat 157
disease resistance is SuSr-D1, a suppressor of stem rust resistance, which encodes a subunit of the mediator 158
complex that possibly plays a role in fine-tuning gene expression [46]. Genetic background effects represent 159
another important research area worth investing in to ensure broad applicability of biotechnology for 160
disease resistance breeding.
161
162
4 – Engineering durable resistance 163
The completion of the wheat R gene atlas (cloning most known disease resistance genes in wheat) and a 164
more comprehensive understanding of the biochemical and structural mechanisms of plant–pathogen 165
interactions will allow informed choices for deployment of resistance genes. An area of great promise is 166
gene stacks. A proof-of-concept study recently demonstrated that the gene stack approach works in wheat.
167
Transformation of a gene cassette consisting of five stem rust resistance genes into a susceptible wheat 168
cultivar resulted in transgenic lines with broad-spectrum stem rust resistance [47]. This stack contained four 169
NLR genes and Sr55, which encodes a hexose transporter. To maximize durability, however, the 170
corresponding guardees must be known and genes in the stack should be chosen to monitor different 171
guardees. This will ensure that the corresponding pathogen does not overcome multiple NLR genes in the 172
stack by modifying a single effector. Another example of how biotechnology can be used to engineer broad- 173
spectrum disease resistance is through knock-out of susceptibility genes. For example, natural and induced 174
mutations in the barley (Hordeum vulgare) Mlo gene result in broad-spectrum resistance against fungal 175
powdery mildew disease [48]. Simultaneous knock-out of all three Mlo homoeoalleles in hexaploid wheat 176
through genome editing had the same effect, creating wheat plants displaying broad-spectrum mildew 177
resistance [49]. A major limitation to the routine application of biotechnology in wheat is the recalcitrance 178
of most wheat cultivars to tissue culture and transformation. Until recently, only a few wheat cultivars could 179
be transformed efficiently. Recent progress using growth promoters has significantly increased regeneration 180
9
and transformation ability [50]. We expect that this and similar developments will greatly accelerate the 181
use of biotechnology in wheat.
182
183
Conclusions and outlook 184
We are at an interesting point in wheat research and the use of biotechnology in wheat. Today, no 185
genetically modified or genome-edited wheat is grown commercially. As described in this article, however, 186
several attributes make wheat an ideal crop for using biotechnology to achieve durable disease resistance.
187
(i) Wheat is one of the most widely grown crops worldwide, which might make biotechnological solutions 188
commercially viable. (ii) The functionality of disease resistance genes from distant wild wheat relatives in 189
cultivated pasta and bread wheat has been demonstrated multiple times. This unlocks the possibility of 190
exploiting a huge genetic diversity for disease resistance breeding. (iii) The large and complex wheat 191
genome is no longer a major bottleneck for wheat research. This will allow us to clone wheat genes much 192
more routinely, and we expect that the wheat R gene atlas will become a reality in the coming 15 years. (iv) 193
Proof-of-concept studies have demonstrated that gene stacks are an effective strategy for imparting 194
resistance to various pathogens and that genome editing can be used to engineer broad-spectrum disease 195
resistance. We now need to decipher the molecular mechanisms of each gene in the wheat R gene atlas so 196
that targets for gene stacking and editing can be chosen wisely. This might allow us to safeguard the ~210 197
million tons of wheat currently lost annually to pathogens.
198
199
10 Conflict of interest
200
Nothing declared 201
202
Acknowledgements 203
We would like to thank Robyn Palescandolo and Tobin Florio for help with figure preparation. This work 204
was funded by the King Abdullah University of Science and Technology.
205 206 207
11 208
Figure legend 209
Figure 1. Timeline highlighting the major achievements in wheat disease resistance breeding and 210
biotechnology. The two boxes on the left depict the two major biotechnological applications in wheat 211
disease resistance breeding, the knowledge-guided gene stack design and synthetic R gene complexes.
212
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