Sensitivity genes in wheat and corresponding effector genes in necrotrophs exhibiting inverse gene-for-gene relationship

In wheat, genes for resistance (R) as well as susceptibility (S) are now known for several diseases. The S genes also include sensitivity genes like Tsn1 in wheat. R genes follow a gene-for-gene (GFG) relationship and generally involve biotrophs and S genes particularly sensitivity genes, follow an inverse gene-for-gene relationship (IGFG), generally involving necrotroph or hemi-biotroph pathogens. The toxin (virulence factor) genes of the pathogen and the corresponding sensitivity genes have been described in some detail for the following three pathogens: (i) Paratagonospora nodorum (causing Septoria nodorum blotch or SNB); (ii) Pyrenophora tritici-repentis (tan spot) and (iii) Bipolaris sorokiniana (spot blotch). These and some other pathogens produce several necrotrophic effectors (NEs), which interact directly or indirectly with the products of S genes in the host and produce disease symptoms like necrosis and/or chlorosis. In this article we present a critical review of all the relevant information about the interactions between NEs of the above three pathogens and the corresponding S genes in wheat. The gaps in knowledge and possibilities for future research are also discussed. East, Denmark, Germany, and New Zealand). PtrHp1 perfectly matched 59 bp inverted repeat hairpin structure located downstream of the ToxA coding sequence in the 3’ UTR exon. Further examination revealed that PtrHp1 elements were distributed throughout the genome. Analysis of genomes of isolates from Australia and North America had 50–112 perfect copies of PtrHp1 that often overlap other genes. The hairpin element appears to be unique to Ptr and the lack of ancient origins in other species suggests that PtrHp1 emerged after speciation of Ptr (Moolhuijzen et al. 2018b).


Introduction
Wheat (Triticum aestivum L.) is the third most important staple food crop worldwide ( rst two being maize and rice), sometimes also consumed as animal feed (Mauseth 2014). Among cereals, wheat has been estimated to occupy maximum cultivated land area, which was 215.2 million hectares in 2019, giving 22% of the total cereal grain production (FAO 2020). The total global production of wheat grain was 732 million tonnes during 2018-19 (FAO 2019) and ~763 million tonnes in 2019-20 (FAO Release May 7, 2020); in terms of global cereal production, this production level is next to only maize (FAO 2019).
Wheat production is signi cantly reduced by various biotic and abiotic stresses. The biotic stresses mainly include pathogens like fungi, viruses, bacteria, nematodes, etc., which cause a variety of diseases Among these pathogens, fungal pathogens are alone responsible for 15-20% losses in yield (Figueroa et al. 2018). The fungal diseases include rusts, mildew, blast, bunts, blights, etc. Among these diseases, the diseases caused by necrotrophs and hemi-biotrophs include Septoria nodorum blotch or SNB (Parastagonospora nodorum), tan spot (Pyrenophora tritici-repentis) and spot blotch (Bipolaris sorokiniana) (Fig. 1). A summary of necrotrophs and hemi-biotrophs causing different diseases in wheat is presented in Table 1.
The genetics of disease resistance has been worked out in some detail, not only for diseases caused by biotophs, but also for those caused by necrotrophs and hemi-biotrophs. In case of biotrophs, mainly R genes/QTLs in the host provide resistance, but in case of some necrotrophs, the disease is facilitated by the presence of one or more sensitivity (S) genes in the host, and corresponding virulence genes in the pathogen. The necrotrophic effectors (NEs) encoded by the virulence genes of the poathogen interact directly or indirectly with the product of the dominant sensitivity genes of the host leading to necrosis and/or chlorosis (Tan et al. 2010;Oliver et al. 2012). The biotrophs cause cell death leading to hypersensitive reaction (HR) that is responsible for resistance, due to non-availability of living tissue as food and thereby restricting the pathogen multiplication and growth in the plant Liu et al. 2012). The necrotrophs, on the other hand, feed on the dead cells leading to the so-called NE-triggered susceptibility, so that resistance is generally (but not always) achieved through elimination of these dominant sensitivity genes or using their recessive resistant alleles. The differences between biotrophs and necrotrophs are listed in Table 2.
It has been shown that a gene-for-gene (GFG) relationship proposed by Flor (1942) holds good between a R gene of the host and a matching Avr gene in the pathogen, because in the absence of a matching Avr gene in the prevalent race of the pathogen, R gene can not function and provide resistance (Fig. 2a). In contrast, an inverse gene-for-gene (IGFG) relationship holds good for sensitivity genes in case of necrotrophs, because a virulence gene does not provide a As many as ~60 genes encoding NEs have been identi ed for different pathosystems involving necrotrophs (Sperschneider et al. 2018). At least 13 of these NEs in three different pathosystems (8 for SNB, 4 for tan spot and 1 for spot blotch) involving wheat as the host have already been identi ed and subjected to detailed studies  For wheat, NEs and sensitivity genes involved in the three different pathosystems have been studied in some detail (Fig.   3). The chemical nature of several NEs has also been worked out showing that all NEs are proteinaceous in nature, except ToxC associated with tan spot (P. tritici-repentis), which is a polar non-ionic metabolite with low molecular weight, although not fully characterized so far . Details of major host-pathogen interactions involving the three pathogens included in this review are summarized in Table 3.
The basic outline of the mechanism involved in compatible/incompatible interactions involving IGFG is now known. Details for individual pathosystems have also been worked out in some cases. The degree of correlation between the level of NE proteins and expression of related sensitivity genes has also been worked out using a number of wheat cultivars; these correlations were also related with eld resistance (Tan et al. 2014). In case of tan spot and spot blotch, it has been shown that a clear dominance of interaction between individual NE with corresponding sensitivity gene can cause a disease (e.g., ToxA/Tsn1; Moffat et al. 2014). It has also been reported that all current cultivars grown in Western Australia are sensitive to at least one of the following three SNB NEs: SnToxA, SnTox1 and SnTox3 (Tan et al. 2015). IGFG relationship between sensitivity gene Tsn1 of the host and ToxA gene in B. sorokiniana has also been demonstrated recently in several countries including Southern USA, Australia, India, and Mexico (Friesen et

Pathosystems involving sensitivity genes in wheat
The available literature on plant immunity largely deals with resistance R genes, such that thousands of R genes are now known for resistance against many diseases in plants. For instance, ~80 Lr genes are now known in wheat for resistance against leaf rust alone. With the availability of whole genome sequences for majority of crop plants (including wheat), we now also know that the number of R genes in a crop like wheat can be as large as >1300 (GrainGenes; https://wheat.pw.usda.gov/GG3/). A number of sensitivity genes have been identi ed for several diseases caused by necrotrophs or hemi-biotrophs. Sometimes, the same sensitivity gene may function not only for different isolates of the same pathogen, but also for more than one disease. For instance, Tsn1 functions as a sensitivity gene for at least three diseases, namely SNB, tan spot and spot blotch Navathe et al. 2020). A summary of interactions involving the above three necrotrophs/hemi-biotrophs causing diseases in wheat is provided in Table 3. However, sensitivity genes in wheat have been identi ed only for three of the ten necrotrophs/hemibotrophs listed in Table 1. In future, sensitivity genes may also be discovered for other diseases caused by necrotrophs/hemibiotrophs, including Fusarium head blight (FHB), which is one of the most important diseases of wheat causing major losses in yield in wheat (Hales et al. 2020). For necrotrophs, where wheat sensitivity genes are already known, additional sensitivity genes may also be discovered in future.
In this section of the review, we rst describe genes encoding different NEs and the corresponding sensitivity genes for each of the three pathosystems. The recessive alleles of these sensitivity genes provide resistance, but there are also R genes and QTLs which function independently of the sensitivity genes, so that the recessive alleles of sensitivity genes can be deployed along with R genes and QTLs in order to achieve improved resistance against diseases like SNB, tan spot, and spot blotch.
Effector-assisted breeding is also being recommended for disease resistance. This has become possible due to the availability of genome-wide catalogue of effectors (effectoromics) for various pathogens, which can be utilized either through MAS-assisted classical resistance breeding or through transgenic approach. The available literature on effectorassisted breeding has been reviewed by Vleeshouwers and Oliver (2014). The details of sensitivity genes, which can be utilized for future wheat breeding, along with R genes and QTLs for resistance against different diseases are listed in Table 4.
Parastagonophora nodorum-wheat pathosystem SNB occurs in warm and humid areas of the world causing yield losses of up to 30% (Bhathal et al. 2003); the disease includes both leaf blotch and glume blotch (Fig. 1a). Currently, no cultivar is available with complete resistance/immune reaction to SNB. Therefore, tillage, crop rotation and chemical control are still utilised as disease management practices for control of this disease. P. nodorum-wheat pathosystem is also the most extensively studied pathosystem involving necrotrophs, such that P. nodorum is also used as a model necrotroph for the study of host-pathogen interactions involving sensitivity genes. P. nodorum genome is 37 Mb in size with 23 chromosomes. Whole genome sequencing of pathogen has been undertaken for a number of isolates of this pathogen, which include the following: A pan-genome for Parastagonospora spp was also developed using genome sequences of 33 different isolates (including 21 isolates of P. nodorum), showing wide range of structural variations (SVs), thus providing a resource for the prediction of novel NEs (Syme et al. 2018). It was also shown that different isolates carry genes encoding different NEs. Isolates like SN79-1087 with no known gene encoding NE have also been reported (Richards et al. 2018).
In a more extensive recent study, Richards et al. (2019) conducted whole genome sequencing for 119 isolates to examine effector diversity and to identify genomic regions that are subject to selection pressure speci c to populations de ned by geographical regions. NE genes, sensitivity genes and interactions: Following nine interactions involving nine wheat sensitivity genes and eight P. Among these nine interactions, the rst, second and fourth (Tsn1-SnToxA, Snn1-SnTox1, Snn3-B1-SnTox3) have been subjected to relatively detailed studies, because the sensitivity genes and the NE genes involved in these interactions have all been cloned and characterized. A possibility of another uncon rmed interaction (Snn8-SnTox8) has also been suggested ).
The interaction of each NE with the product of a speci c sensitivity gene, as above, leads to programmed cell death, which allows the corresponding necrotroph to gain nutrients, sporulate and cause the disease ). The interactions have also been shown to be additive in nature, sometimes also exhibiting epistatic interactions, particularly in the following three interactions: (i) Snn2-SnTox2 ), (ii) Snn3-SnTox3 Phan et al. 2016) and (iii) Snn5-SnTox5 ). However, the role of epistatic interactions in the expression of these interactions is rather limited (Phan et al. 2016).
It has also been shown that, several QTLs also occur in addition to major sensitivity genes. However, the absence of one or more sensitivity genes or presence of their recessive alleles provide disease resistance. The importance of the absence of sensitivity gene in providing resistance relative to that due presence of R genes and QTLs has been shown to be rather limited (see review by Cowger et al. 2020; also see later in this review).
Distribution of NE genes in the pathogen. The distribution of each of the eight NE genes and nine sensitivity genes differs in different wheat growing regions of the world, although data is available mainly from USA, Europe (including UK and Norway) and Australia. Distribution of three NE genes, namely SnToxA, SnTox1 and SnTox3 has been examined in several studies. Some details of the distribution reported in these studies are summarized in Table 5, which suggest that the gene SnTox1 is the predominant gene, which is reported to occur in 95.4% of natural populations in USA (as above) and 84% isolates worldwide; these frequencies are not very different from the frequencies of the occurrence of the corresponding sensitivity gene Snn1 gene in wheat, which has also been reported to be 85% (McDonald et al. 2013).
The predominance of SnTox1 as above, was not universal, as apparent from the following two reports on SnToxA, where isolates were screened for NE genes. (i) Among Australian isolates, 71 (97%) of 73 isolates (collected from only one eld) carried SnToxA (Stukenbrock and McDonald 2007;McDonald et al. 2013). This was attributed to the biased sample from a single eld and may not represent the situation in whole of Australia (Oliver et al. 2009). (ii) In a diverse sample of 165 P. nodorum isolates, from Norway and 9 isolates from other countries, SnToxA was found to occur with high frequency in Norwegian P. nodorum isolates relative to other parts of Europe, suggesting that SnToxA gene is the major virulence factor in Norway (Lin et al. 2020). The disease reaction in interaction Snn1-SnTox1 has been observed to range from 0 to 58% and seems to depend on both, the genetic background of the host and that of the pathogen ( Distrubution of sensitivity genes in the host Surveys were also conducted for distribution of different sensitivity genes in wheat cultivars. Some of the available data for distribution of three major sensitivity genes is summarized in Table  6. These results suggest that Snn1 is not an important sensitivity gene for US wheat programs; instead, Tsn1 is important for hard winter wheats only, while Snn3 is important for both soft and hard wheats. Sensitivity of individual resistant and susceptible cultivars against speci c NEs was also examined. For this purpose, NEs were obtained from transgenic E. coli and Pichia pastoris. (i) In a study conducted in USA, 25 susceptible wheat cultivars (many from SE USA) and a resistant cultivar (NC-Neuse) were tested against different NEs isolated from 37 isolates from different regions of SE USA. It was found that all susceptible cultivars were sensitive to at least one NE, and that the resistant cultivar (NC-Neue) was sensitive to none. Among susceptible cultivars, 32% contained sensitivity gene Tsn1 and 64% contained sensitivity gene Snn3. None was sensitive to SnTox1. (ii) In a panel of 480 northwest European varieties (~330 were from the U.K.), sensitivity to SnTox3 (presence of Snn3) was higher than that to SnTox1, while sensitivity to SnToxA (presence of Tsn1) was rare (Downie et al. 2018). (iii) In 157 Scandinavian spring wheats (including Norwegian, Swedish and CIMMYT lines), sensitivity to SnToxA (presence of Snn1) was present in 45% wheats ).
Use of multiple sensitivity genes. Wheat genotypes with multiple sensitivity genes were also identi ed. These genotypes produce signi cantly higher disease reactions relative to those harbouring only a single sensitivity gene ). Such studies with multiple sensitivity genes need to be conducted for characterization of wheat cultivars in different parts of the world, so that we know the identity of sensitivity genes present in wheat cultivars. Results of these studies can be used to discard out parents harbouring sensitivity genes when breeding for resistance to SNB.
Use of multiple isolates. In a recent study, multiple isolates of the pathogen were used to evaluate the effects of the following three host gene-NE interactions individually and in various combinations: (i) Tsn1-SnToxA, (ii) Snn1-SnTox1, and (iii) Snn3-B1-SnTox3. These results suggested that the IGFG interactions leading to 'NE-triggered susceptibility' in wheat-P. nodorum pathosystem vary in their effects depending on the genetic backgrounds of the pathogen and the host, and that the interplay among the interactions is complex and intricately regulated (Mebrate and Cooke 2001).
Some information is also available regarding distribution of sensitivity genes in wheat genotypes used for cultivation in UK and Europe. It was shown that the host may carry one or more sensitivity genes along with R genes, the latter with a major effect. In wheat, one or more sensitivity genes (present along with R genes and QTLs) produce disease phenotype ranging in severity from 22 to 95% (Sharma 2016). SnToxA gene seems to resemble PtrToxA gene in its interaction with the sensitivity gene Tsn1, which is involved in all the three diseases including tan spot, SNB and spot blotch (Faris et al. 1996;Haen et al. 2004;).
Transcription factors regulating sensitivity gene-NE interactions. Three interactions mentioned above, namely Tsn1-SnToxA, Snn1-SnTox1 and Snn3-B1-SnTox3 have also been shown, each to be positively regulated by the transcription factor Zn2Cys6 of PnPf2 zinc nger family . Another transcription factor is SnStudA that regulates the central carbon metabolism, mycotoxin production and effector gene expression in Snn3-B1-SnTox3 interaction (IpCho et al. 2010). The target of this transcription factor is WMGGVCCGAA motif and the associated genes were shown to be involved in downregulation for plant cell wall degradation and proteolysis; the genes associated with redox control, nutrient and ion transport were also up-regulated. TFs of the PnPf2 zn nger family were also shown to regulate positively as many as 12 genes that encode effector-like proteins (Jones et al. 2019).
High resolution mapping and cloning of sensitivity genes. Following are some details about these three sensitivity genes, where the description for Tsn1 will apply for all the three pathogens: Tsn1-ToxA interaction is common among all the three pathosystems involving wheat with SNB, tan spot and spot blotch . It has been shown that at the transcription level, ToxA can activate wall associated kinases (WAKs) as a defense response (He et al. 1998). It is also possible that ToxA may utilise WAKs for recognition of the product of Tsn1 (Pandelova et al. 2009). The potential targets of ToxA is the binding protein, ToxABP1 with vitronectin-like sequence (Manning et al. 2007).
(ii) Sensitivity gene Snn1. This gene is located on chromosome arm 1BS and was earlier ne-mapped using F 2 population derived from a cross between Chinese Spring (CS) and its disomic substitution line carrying 1B chromosome from either T. dicocooides  or from wheat cultivar Hope, leading to cloning (Shi et al. 2016b). Later, it was also ne mapped as a QTL through QTL interval mapping using a Multi-parent Advanced Generation InterCross (MAGIC) population involving eight or 1(Cockram et al. 2019). The gene Snn1 was shown to encod e a member of the wall-associated kinase (WAK) class of plant receptor kinases and was therefore referred to as TaWAK. The gene is 3,045 base pairs (bp) long with three exons and a coding sequence of 2,145 bp with 5′and 3′untranslated regions (UTRs) of 164 and 102 bp, respectively. The deduced amino acid sequence indicated that the protein contains conserved wall-associated receptor kinase galacturonan binding (GUB_WAK), epidermal growth factor-calciumbinding (EGF_CA), transmembrane, and serine/threonine protein ki-nase (S/TPK) domains, with the S/TPK domain predicted to be intracellular and the GUB_WAK and EGF_CA binding domains predicted to be extracellular. Snn1 gene encodes a protein with a structure like that of PRRs (pattern recognition receptors), which recognize pathogenassociated molecular patterns (PAMPs). The PRR like protein encoded by Snn1 often resembles a wall-associated kinase (WAK) protein with domains like PK transmembrane, galacturonan binding and calcium binding domains; this allows early recognition of SnTox1 effector protein and upregulate the PTI pathway  (Tsn1 and Snn1). Like the other two cloned sensitivity genes (Tsn1 and Snn1), Snn3-D1 also carries a S/TPK domain, but it also have some other domains related to the receptor-like kinase and MAP kinase (Winterberg et al. 2014). Snn3-D1 also differed from Tsn1 and Snn1 in its light regulated and circadian expression patterns. This and other characteristics of Snn3-D1 and how it compares to Tsn1 and Snn1 will be known when results of cloning Snn3-D1 are published. However, one common feature of the above three cloned sensitivity genes is the presence of a PK domain, which indicates that signaling is necessary from the pathogen to exploit programmed cell death in the host.
Cloned NE genes for SNB. Three of the eight NE genes (SnToxA, SnTox1 and SnTox3) have also been cloned and characterized Liu et al. 2009Liu et al. , 2012. Following are some details: (i) SnToxA gene has two introns, which included a 55 bp intron located in the leader sequence and the other 50 bp intron located at the C-terminal coding region. The gene encodes a 13.2 kDa mature protein, which targets the protein PR-1-5 causing necrosis in the presence of Tsn1 gene during ToxA-Tsn1 interaction. The target protein PR-1-5 is present in both ToxA-sensitive and ToxA-insensitive wheat lines; it is only the level of expression that differs (Lu et al. 2009(Lu et al. , 2011(Lu et al. , 2014. (ii) SnTox1 gene lies in a 7.6 kb genomic region and has three exons (180 bp, 162 bp and 12 bp) associated with 58 bp long 5'UTR and 164 bp long 3' UTR (Fig 5a). The gene is associated with one downstream gene (SNOG_07153) and three upstream genes (SNOG_07154, SNOG_07155, SNOG_7156; SNOG stands for S nodorum gene) ( (iii) SnTox3 gene is 693 bp long and carries no introns. It encodes a 25.8 kD protein with 20 amino acid signal sequence and a possible pro-sequence ). Six cysteine residues were also predicted to form disul de bonds, which were shown to be important for SnTox3 activity. This gene also encodes a 230 aa long pre-pro protein. SnTox3 protein also contains a 20 aa signal peptide along with disul de bonds formed by the six cysteine residues, which help in stabilisation of mature protein and its protein activity ). The genomic location and structure of the gene SnTox3 is shown in Fig. 6. An experiment was also conducted for the identi cation of the interaction between the P. nodorum NE protein SnTox3 and PR-1-1 in wheat using yeast-two-hybrid library approach, which indicated that the interaction was associated with the necrosis on the leaves of wheat ).
Mechanism of action of NEs. The mechanism of action for different NEs may also differ and is known for at least two NEs. For instance, SnTox1 functions in the apoplast and directly recognizes Snn1 protein, thus facilitating infection by overcoming the barrier due to wheat chitinases (Liu et al. 2016). SnToxA, on the other hand, is internalized into the cytoplasm and interacts directly or indirectly with the product of gene Tsn1. In both cases the NE-Sn interactions activate MAPK signalling, which upregulates defense pathways and leads to release of reactive oxygen species (ROS), which results in cell death (Shi et al. 2016b; Fig. 7).
QTLs for SNB resistance (leaf blotch and glume blotch). P. nodorum pathogen is responsible for the development of two SNB diseases in wheat i.e., leaf blotch and glume blotch (including ag leaf and spike blotch). However, in a number of genetic studies, no distinction was made between leaf blotch and glume blotch. QTLs for resistance against SNB have been identi ed following both linkage based interval mapping and LD-based GWAS. The QTL analysis for the resistance to this disease was undertaken at two different stages [seedling (leaf blotch) and adult plant stages ( ag leaf and spike)], but most of the association mapping studies were conducted at the seedling stage (Supplementary Tables 1 and 2 Table 2). After due validation, the markers associated with QTLs and MTAs can be utilized for MAS for resistance breeding.
In a recent major detailed study conducted by Lin et al. (2020), QTLs were also identi ed using a MAGIC population (643 RILs). Sixteen QTLs were detected using IM/CIM, being located on chromosomes 2A, 2D, 5B, 6A and 7D. A QTL (QSnb.niab-5B.2) overlapping Tsn1 was also identi ed on the long arm of chromosome 5B.
High resolution ne mapping has also been undertaken for sensitivity genes for SNB. A high-density genetic linkage map was developed for the region of chromosome 2D, which narrowed down the Snn2 gene to a 4-cM region, thus facilitating the discovery of closely linked molecular markers for breeding and positional cloning of Snn2 gene ). Phenotypic variation (PV) for disease was 47% for the interaction Snn2-SnTox2, 20% for the interaction Tsn1-SnToxA, and 66% for both interactions taken together, suggesting the utility of these interactions in breeding ).
Saturated gnetic map was also prepared for the region carrying the gene Snn3 using two crosses between sensitive line Sumai3 and the corresponmding insensitive genotypes (Downie et al. 2918).
Pyrenophora tritici-repentis-wheat pathosystem Tan spot caused by P. tritici-repentis (Ptr) causes a mean yield loss of 5-10% in different parts of the world, which may approach 50% under conditions favorable for the pathogen (DeWolf et al. 1998; . The disease has been reported from different parts of the world including Australia, Canada, the USA, Mexico, South America (Argentina and Brazil), Europe, Africa, and Central Asia (Kazakhstan and Tajikistan). The wide adoption of minimum tillage practices and unconscious widespread cultivation of Tsn1-carrying wheats perhaps caused a rise in the incidence of tan spot and its severity throughout the world (Lamari et al. 2005). Tan spot is characterized by two distinct and independent symptoms in the form of necrosis and chlorosis (Fig. 1, b1, b2). It has also been shown that resistance against necrosis and chlorosis are controlled by two independent recessive factors.
Necrotrophic effectors (NEs). Three different NEs secreted by Ptr include ToxA, ToxB and ToxC. The presence of a fourth NE (Ptr ToxD) has also been suggested, but no corresponding sensitivity gene for this NE is known Ciuffetti et al. 2003). The genes encoding these three NEs were also identi ed in different isolates of the pathogen and are involved in the following three interactions: Tsn1-ToxA, Tsc1-ToxC and Tsc2-ToxB (Table 3; Faris et al. 2013). Among these three interactions, Tsn1-ToxA interaction is common with wheat-P. nodorum and wheat-B. sorokiniana pathosystem.
Among the three NEs, PtrToxA and PtrToxB are characterized as small effector proteins; ToxA produces necrosis, while ToxB produces chlorosis. ToxC, which also causes chlorosis, has not been characterized and may be the product of a secondary metabolite gene cluster. There is strong evidence that P. tritici-repentis acquired the gene ToxA from P. nodorum through hor izontal gene transfer ).
In addition to the above three toxins, as many as 38 novel toxins called triticones have been identi ed (Rawlinson et al. 2019), although only triticone A and triticone B have been puri ed from Ptr and shown to cause necrosis/chlorosis. A biosynthesis gene cluster TtcA has also been identi ed. A deletion of TtcA abolished the production of all triticones, but the pathogenicity of mutant ttcA was not visibly affected. Triticone A/B gave visisble necrotic symptoms but inhibited the growth of some bacteria like Bacillus subtilis and Rhodococcus erythropolis, when tested using disk diffusion method, suggesting their antimicrobial activity. No inhibition was observed for gram negative bacteria, like P. pastoris (Rawlinson et al. 2019).
A detailed study of the Ptr genome has also been undertaken by R.P. Oliver and his group from Western Australia (Moolhuijzen et al. 2018a, b). The genome is 40.9 Mb in size and has already been fully sequenced, using eight new Ptr isolates representing races 1, 2 and 5, and a new race (for races 1-8, see later). As much as 98% of the genome has been mapped on 10 or more chromosomes, which carry 13,797 annotated genes. Comparative analysis of the whole genome also revealed major chromosomal segmental rearrangements and fusions, highlighting intraspeci c genome plasticity PtrToxA is a single copy gene and is characterized by 900 nucleotides long cDNA (PtrNEC) producing a 19.7 kD protein precursor. Ptr ToxB, on the other hand, is a multi-copy gene (1-3 Kb in length) producing a protein with a mass of 6.6 kD (Martinez et al. 2001(Martinez et al. , 2004. The number of copies of ToxB in a race has a correlation with the level of virulence. A total of ten identical ToxB gene copies were identi ed, with nine loci associated with chromosome 10 and a single copy with chromosome 5. Multiple ToxB gene loci on chromosome 10 were separated by large segments of 31-66 kb long, and exhibit an alternating pattern involving forward and reverse DNA strands, and anked by transposable elements Genetics of sensitivity. A genetic analysis of Tox B sensitivity was conducted using an association mapping panel (n = 480) and a MAGIC population (n founders = 8, n progeny = 643) that were genotyped with a 90K SNP array. ToxB sensitivity was found to be highly heritable (h2 ≥ 0.9) and was controlled predominantly by Tsc2 locus on chromosome 2B in a 1921 kb long interval that contains 104 genes in the reference genome of ToxB-insensitive variety 'Chinese Spring' (Corsi et al. 2020). A minor ToxB sensitivity QTL was also identi ed on chromosome 2A. These resources can be used for deployment of recessive allele of Tsc2 using MAS.
As a result of extensive studies on tan spot during the last 40 years, we now have the following resources for conducting research on this disease: (i) a wheat differential set for tan spot, which included Salamouni (universal resistant), Glenlea (sensitive to Ptr ToxA), 6B365 (sensitive to Ptr ToxC), and 6B662 (sensitive to Ptr ToxB). The hard spring wheat line ND495 was included in the differentials set as a susceptible control; (ii) a rating scale for lesion type disease; (iii) basic race classi cation system involving eight races (Table 7); the four differential genotypes can differentiate between the known eight races of the pathogen. Details about three NEs-sensitivity combinations are summarized in Table 3 (Table 7). Isolates belonging to each race were collected both from bread wheat and durum wheat, although race 1 in hexaploid wheat is believed to have originated from durum wheat. Three isolates, namely Asc1 (race 1), D308 (race 3) and Alg3-24 (race 5) were found to carry genes Ptr ToxA, Ptr ToxC, and Ptr ToxB respectively. The distribution of the genes encoding three different NEs differs widely not only in different parts of the world, but also in the area occupied by the same set of wheat genotypes. Of these, ToxA is the most widely distributed, being present in ~80% of the world's isolates ); this is a small protein that induces a strong necrotic response in wheat lines Distribution of races 1-8 among isolates. The distribution of eight Ptr races in different isolates from a particular geographical region or from different geographical regions have also been examined. Following are some examples: (i) In Tunisia, using four wheat differential genotypes (mentioned above), virulence was examined for 73 single-spore isolates, and the results indicated that 68 isolates belonged to race 7; 3 belonged to race 5 and one each to race 2 and 4, suggesting that race 7 is the predominant race in Tunisia. PCR was also performed to examine the frequencies of each of the three genes (ToxA, ToxB and toxB), but not for ToxC, which has not been cloned and sequenced, so that primers could not be designed for this gene. ToxA was present in 37 (51%) isolates, ToxB was present in 71 (97%) isolates with its homolog toxB present in 68 (93%)  Assessment of sensitivity. In a recent study, 40 Australian spring wheat varieties were examined for sensitivity to ToxA and disease response to a race 1 speci c wild-type Ptr isolate carrying ToxA and ToxC (See et al. 2018). ToxA sensitivity was generally associated with disease susceptibility (compatible interaction) but did not always give the expected symptoms.
When wild type and toxA mutant isolates were used for infection, majority of Tsn1 varieties exhibited lower disease scores with toxA mutants (as expected), but several varieties exhibited no distinct differences between wild-type and toxA mutant. This pattern suggested that ToxA is not the sole major cause of tan spot disease, and that the appearance of the disease partly also depends on the background of the host. It is thus suggested that ToxA may need aditional factors to cause infection (See et al. 2018).
Cloned sensitivity genes for tan spot. Among the sensitivity genes, Tsn1 (common among three necrotrophs) has already been cloned and characterized (Fig. 4). The details of this genes were already described earlier, while describing cloned sensitivity gene for P. nodorum. The other two sensitivity genes Tsc1 and Tsc2 are yet to be cloned and characterized, but markers have been developed for these two other sensitivity genes. A variety 'Maris Dove' was also identi ed to be the historic source of Tsc2 alleles in the wheat germplasm. A minor sensitivity QTL was also identi ed on chromosome 2A. Interactions between sensitivity genes and NEs. Among the three interactions, namely Tsn1-ToxA, Tsc1-ToxC and Tsc2-ToxB, the interaction between Tsn1 and ToxA has been shown to be negatively affected when mutation occurs at different motifs of the Tsn protein (Manning et al. 2004). The interaction Tsc2-ToxB is unique to tan spot and leads to upregulation of several wheat genes encoding proteins like RLKs, pathogenicity related proteins, components of jasmonic acid, and  Table 3.
An additive interaction of sensitivity gene Tsn1 with Tsc1 and Tsc2 has also been reported for tan spot in bread wheat (Liu et al. 2017) but not in durum wheat (Virdi et al. 2016). It is therefore apparent that elimination of one or more sensitivity genes along with introgression of R genes/QTLs should be a good strategy for developing resistant cultivars. R genes and QTLs for tan spot resistance. Resistance genes (R genes or major QTLs) providing resistance against tan spot have also been identi ed. Among these R genes, Tsr7 locus was also identi ed in tetraploid wheat using a set of Langdon durum-wild emmer (Triticum turgidum ssp. dicoccoides) disomic chromosome substitution lines. Durum cultivar Langdon, which is susceptible to tan spot became resistant with the substitution of chromosome 3B from the wild emmer accession IsraelA (Faris et al. 2020). Tsr7 locus in tetraploid wheat was later found to be the same as the race-nonspeci c QTL previously identi ed in the hexaploid wheat cultivars BR34 and Penawawa. Four user-friendly SNP-based semithermal asymmetric reverse PCR (STARP) markers co-segregated with Tsr7 and should be useful for MAS (Faris et al. 2020).
More than 20 QTL studies were also conducted in hexaploid and tetraploid wheats for identi cation of QTLs for resistance against tan spot in wheat. These QTL studies resulted in identi cation of as many as >160 QTLs, a number of these QTLs explained >20% phenotypic variation (Supplementary Table 1). Utilizing the results of QTL studies, a meta-QTL analysis was also conducted leading to identi cation of 19 meta-QTLs that were derived from 104 QTLs (Liu et al. 2020a, b for details of all QTL studies and for meta-QTL analysis). Three race nonspeci c meta-QTLs were also identi ed, one each on chromosomes 2A, 3B and 5A. These three meta-QTLs had large phenotypic effects, each responsible for resistance to multiple races in both bread and durum wheats.
GWA studies were also conducted leading to identi cation of 242 signi cant MTAs (Supplementary Table 2), although a large number of these could be false positives. Most QTLs and MTAs were associated with seedling resistance and very few studies have been conducted for the identi cation of QTLs associated with adult plant resistance (Supplementary Table 1 and 2). The markers associated with the above meta-QTLs and those involved in MTAs can be utilized for MAS in wheat breeding programmes after due validation.
Candidate genes were also identi ed for 16 of the above 19 meta-QTL; the number of candidate genes for individual meta-QTL ranged from 2 to 85, many of these located on chromosome 2B. A number of these candidate genes encoded NBSand/or LRR-like proteins and co-localised with sensitivity gene Tsc2. However, none of these candidate genes could be Tsc2, because genome sequence utilized for identi cation of candidate genes belonged to CS, which is insensitive to Ptr ToxB.
PR genes. The level of the expression of most PR genes has also been shown to be up-regulated due to effector protein ToxA during infection and increases over time (Pandelova et al. 2009). Glucanases (PR-2) and chitinases (PR-4) represent the largest group of PR genes displaying differential expression in which majority of glucanases belong to the family of β-1,3-glucanases (glucan endo-1,3-β-glucosidases). A downregulation of the expression of some genes of glucanases such as (1-3,1-4)-β-glucanases has also been reported (Pandelova et al. 2009).
Bioplaris sorokiniana-wheat pathosystem: BsToxA-Tsn1system B. sorokiniana is a hemi-biotroph and is the causal organism for wheat diseases including spot blotch (Fig. 1a) and common root rot (CRR), which are responsible for major yield losses in several parts of the world (Gupta et al. 2018a, b). The gene ToxA, initially reported to be present in P. nodorum and P. tritici repentis (Friesen et  The gene ToxA is embedded in 12-kb AT-rich genomic region of each of the three pathogens. Near the edges of the gene, a decay has been reported, which has been attributed to repeat-induced polymorphism (RIP) (Fig. 9). Small indels, which differ in size in the three pathogens have also been reported in the promoter region of the gene; this indel is 148- Using bulked segregant analysis (BSA), Sb3 gene was also ne-mapped on chromosome arm 3BS near two other QTLs (QSb.bhu-3B and QSb.cim-3B; Lu et al. 2016). The fourth resistance gene Sb4 was recently identi ed and mapped on chromosome arm 4BL using segregant RNA-Seq (BSR-Seq) analysis and SNP mapping ). The locus with Sb4 carried 21 genes.
In addition to the four major genes as above, 38 QTLs (including 12 QTLs with >20% PVE) using QTL interval mapping (Supplementary Table 1) and 79 MTAs using GWAS were also identi ed (Supplementary Table 2). These QTL analysis and association studies were conducted at seedling as well as at adult plant stages (Supplementary Table 1 and 2).

Conclusions And Future Perspectives
Disease resistance in plants including wheat can be race-speci c or race non-speci c, the latter sometimes also described as adult plant resistance (APR). Both these types of disease resistance are generally controlled by R genes, which have been subjects of detailed studies. The plant immunity involving these R genes has also been subjected to detailed studies at the molecular level, leading to the development of zig-zag model involving PTI, ETS and ETI (Jones and Dangl 2006). During the last > 25 years, > 300 R genes and a number of Avr genes have also been cloned, thus providing an opportunity to study the interaction between the products of R genes of the host and the corresponding Avr genes in the pathogen at the molecular level (for a review, see Kourelis and van der Hoorn 2018). In majority of examples of R genes, gene-for-gene (GFG) relationship proposed by Flor (1942Flor ( , 1956) holds good. However, disease resistance controlled by susceptibility genes like SWEET genes for bacterial blight (BB) in rice (Gupta 2020) and sensitivity genes like Tsn1 in wheat follow an inverse gene-for-gene (IGFG) relationship with corresponding Avr genes in the pathogen (Navathe et al. 2020). This is an area of research on disease resistance, which has witnessed immense activity in recent years. As a result, a number of sensiticvity genes in wheat for three important diseases (SNB, Tan Spot and Spot Blotch) and the corresponding Avr (NE) genes in the form of toxin producing genes (Tox genes) in the pathogens (P. nodorum, P. tritici-repentis and B. sorokiniana) have been identi ed. Some of these genes (both sensitivity genes in the host and NE genes in the pathogen) have also been cloned and characterized generating information about the molecular mechanism involved in plant immunity involving these pathosystem. In this review, a comparison has rst been made between the general molecular mechanisms involved in resistance against biotrophs and necrotrophs. This was followed by a brief review of information on the above three pathosystems. In summary, perhaps only about a dozen NE genes and an equal number of corresponding sensitivity genes are now known, which have been described in this review. In future more sensitivity genes in wheat and other corps and the corresponding Tox genes in the pathogens exhibiting IGFG may be discovered.
We also believe that in the area dealing with sensitivity genes following IGFG model there are gaps, which need to be lled through future research. For instance, although much is known about the pathosystems dealing with SNB and Tan spot, the information dealing with spot blotch (caused by Bipolaris sorokiniana) has just started being generated and hardly any work is available on pathosystems involving necrotrophs causing the following diseases: (i) fusariun head blight (FHB) caused by F. graminearum; (ii) eye spot caused by Tapesia yallundae (syn Pseudocercosporella herpotrichoides, W-type anamorph); (iii) septoria tritici blotch (STB) caused by Zymoseptoria tritici. We also believe that for diseases like spot blotch caused by necrotrophs, both GFG and IGFG may operate in parallel. Further studies involving scoring of allelic states of genes involved in GFG and IGFG models need to be undertaken to resolve this issue. In a recent study on spot blotch involving analysis of Tsn1-ToxA system following IGFG, we ourselves discovered that the wheat genotypes carrying recessive allele of sensitivity gene (tsn1) can also be susceptible and vice versa; variation in the level of disease caused by ToxA positive isolates was also noticed (Navathe et al. 2020). This suggests that the relationship between a sensitivity gene in the host and the corresponding virulence gene in the pathogen is not so simple, suggesting further detailed          Genomic location and structure of SnTox1. a. The structure of SnTox1 gene containing both 5′ and 3′ untranslated regions (green bars) and three exons (purple bars) b. A graphical representation of SnTox1 gene and associated genomic region. SnTox1 gene is anked by four other genes (boxed arrows, SNOG7153 to SNOG7156) and a short, truncated molly-type retrotransposon sequence (yellow rectangle). The sequences are located within the supercontig 10 of the assembled SN15 genome sequence. An overview of the Snn1-SnTox1 and Tsn1-SnToxA interactions and known downstream events that result in NETS in the wheat-P. nodorum pathosystem. The proteins SnTox1 (blue star) and SnToxA (blue hexagon) are secreted by the fungus. SnToxA is internalized into cytoplasm of the cell, but SnTox1 is not. Upon recognition of SnTox1 and SnToxA by the Snn1 and Tsn1 proteins, respectively, signaling leads to up-regulation of defense response pathways and events resulting in programmed cell death ultimately providing a means for the pathogen to gain nutrients and reproduce. Plants with either Tsn1 or Snn1 are susceptible, and plants with both genes experience even higher levels of disease. Elimination of both genes makes the plant resistant (from Shi et al. 2016b).

Figure 8
Five different contigs of P tritici-repentis genome showing positions of 10 different ToxB loci on forward and reverse strands. Blue arrows represent Tox B loci in the forward strand and by green arrows show ToxB loci in the reverse strand.
In each case, the coding sequence is shown in yellow. Figure 9