Rice is one of the most important staple foods for developing countries in Asia and Africa (Odongo et al., 2021). African consumers increasingly replace traditional staples such as sorghum, millet, and maize with rice. Today, African farmers, 90% of which are small-scale food producers with <1 ha of land (Pandey et al., 2010), produce ~60% of local rice demand. The demand will likely increase with the expected doubling of the population until 2050. Productivity is often hampered by diseases, such as Bacterial Leaf Blight (BB), Rice Yellow Mottle Virus (RYMV), and Rice Blast (RB) (Jiang et al., 2020; Longue et al., 2018; Mutiga et al., 2021). Breeding high-yielding varieties with resistance to these diseases will be an important factor needed for food security in Africa. BB, caused by the bacterium Xanthomonas oryzae pv. oryzae (Xoo), is a devastating rice disease in many rice-growing countries. Xoo comprises a wide spectrum of pathovars with diverse virulence mechanisms. In rice, resistance (R) genes for BB have been identified and are used extensively to breed resistant varieties. However, resistance based on single R genes was rapidly overcome by new pathovars (Vera Cruz et al., 2000). Regular monitoring of the virulence of current Xoo populations on a collection of rice tester lines carrying single or combinations of R genes has provided effective guidance for stacking different R genes to obtain broad-spectrum resistance in Asian rice varieties (Arra et al., 2017; Arra et al., 2018).

In Africa, BB was first reported in Mali and Cameroon in the late 1970s, and later in several other West African countries (Buddenhagen et al., 1979; Verdier et al., 2012b). Recently, East African countries also reported BB epidemics (Duku et al., 2016). While information on the spread and severity of BB in Africa is scarce, BB is not yet considered a major threat in Africa; nevertheless, BB is an established disease. The situation is unstable, because climate change affects disease spread, and damage is expected to become more severe in the future due to climate change (Amos, 2013; Laha et al., 2016; Sere and Ouedraogo, 2005; Verdier et al., 2012b). Increased demand and the need to improve food security make it essential to generate broad-spectrum and durable resistance in local varieties specifically for Africa.

Key aspects of the mechanisms underlying BB disease have been elucidated and provide an efficient roadmap for resistance breeding. Xoo strains secrete a suite of Transcription Activator-Like effectors (TALes) into rice xylem parenchyma cells via type III secretion systems. Once inside the host cell, TALes are targeted to the nucleus, where they bind to effector binding elements (EBEs) in the promoters of specific host genes via a unique domain of tandemly arranged 34 amino-acid long repeats. TALes function as transcriptional activators that trigger ectopic induction of target genes (Richter et al., 2014). Several Xoo TALes induce one or several host SWEET sucrose uniporter genes (SWEET11a, 13 and 14), presumably causing sucrose release from the xylem parenchyma into the apoplasm at the sites where the bacteria reside and reproduce (note that due to the discovery of a previously misannotated sucrose transporting paralog, SWEET11a was renamed formerly SWEET11 Wu et al., 2022). Sucrose is consumed by the bacteria, resulting in effective reproduction (Sadoine et al., 2021). Allelic EBE variants that cannot be recognized by TALes function as recessive gene-for-gene resistance genes. Without SWEET induction, Xoo is not a potent pathogen. To date, six target EBEs in SWEET promoters have been identified in a comprehensive Xoo collection. Notably, Asian and African Xoo strains are phylogenetically distinct and use distinct TALes to target SWEETs (Oliva et al., 2019; Tran et al., 2018). African Xoo strains exclusively use TalC and TalF, which both target SWEET14, while Asian strains encode PthXo1, PthXo2 (variants A, B, C), PthXo3 and AvrXa7, which target SWEET11a, 13, and 14, respectively (Eom et al., 2019; Oliva et al., 2019). American Xoo strains lack TALes and hence are poorly virulent (Verdier et al., 2012a). Based on the information of the TALe compendium and the SWEET target sites, broad-spectrum resistance to Asian strains was successfully introduced into Oryza sativa ssp. japonica cv. Kitaake and the spp. indica varieties IR64 and Ciherang-Sub1 by genome editing the EBEs in all three SWEET promoters (Eom et al., 2019; Oliva et al., 2019). The edited lines may prove to be valuable breeding materials that could benefit small-scale producers in Asia. To prepare for emerging strains with novel virulence mechanisms, the diagnostic SWEET^R kit was developed, enabling effective characterization of causative strains and their SWEET-based disease mechanisms, and identification of suitable resistance strategies, such as the best possible SWEET^R-gene combinations for deployment in the target country (Eom et al., 2019).

First observations of BB in Africa were made as early as 1979 in Mali and Cameroon (Buddenhagen et al., 1979). Since then, the disease has been reported mostly in West Africa, including Senegal, Benin, Burkina Faso, Ivory Coast, Mali, and Niger (Afolabi et al., 2016; Gonzalez et al., 2007; Tall et al., 2020; Tekete et al., 2020). More recently, BB was also reported in the East African countries Uganda and Tanzania (Duku et al., 2016; Oliva et al., 2019). However, at present, little information on the genetic diversity and dynamics of Xoo populations is available for Africa. While pathogenic strains have sporadically been isolated from rice plants and characterized, there has been no systematic analysis of Xoo strains and BB disease severity across Africa. Moreover, diverse rice varieties are used across Africa, and there is only limited information on the acreage used for different varieties. These factors make it challenging to breed durably resistant lines for Africa. Numerous international partnerships have introduced varieties and cultivation techniques to major rice production areas in different countries in Africa. For instance, in 1975, one of the first irrigated perimeters with rice research labs and a training farm was developed in Dakawa, a major rice production zone in Tanzania, as a result of a multi-year partnership with North Korea (van et al., 2022). National (NAFCO) and international institutions (USAID, Cornell University) remain active in Dakawa to build irrigation schemes and implement The System of Rice Intensification (SRI). In 2011, a collaboration with China resulted in 50 ha of irrigated fields managed by local farmers. A Technology Demonstration Center that trains local farmers and technicians and grows Chinese varieties, including hybrid rice has been established (Makundi, 2017).

Recent disease surveys in Tanzania, described here, identified an outbreak of BB in 2019 that has spread in subsequent years. We show that the causative strains have features that distinguish them from endemic African Xoo strains, and unravelled the virulence mechanisms that make them a major threat to African rice production. Recently, Kenya and Nigeria exempted SDN-1 genome-edited crops generated using site-directed nuclease without a transgene (SDN-1) from GMO regulations (Buchholzer and Frommer, 2023). This exemption provides a regulatory framework for the introduction of genome-edited, BB-resistant rice into African countries such as Kenya and Nigeria. As a first step towards the generation of BB-resistant rice cultivars for small-scale rice producers in these countries, we used an optimized transformation protocol to edit susceptibility genes in the rice cultivar Komboka, which is popular in East African countries (Luu et al., 2020). Komboka (IRO5N-221) is a relatively new high-yielding, semi-aromatic rice variety jointly developed by IRRI (International Rice Research Institute) and KALRO (Kenya Agricultural & Livestock Research Organization; BBSRC Varieties Kenya.pdf) that grows to an average height of 110cm and has a yield potential of~7 tons/ha, - almost twice that of Basmati, another popular variety planted in Kenya and Rwanda (The Star 2020). Komboka plants mature in~115days, respond well to fertilization, and are suitable for irrigated lowland cultivation in Africa (Kitilu et al., 2019). Komboka had been classified as moderately resistant to BB, RYMV, and RB; however, detailed resistance profiles for specific strains or races are not available, rendering this information of little value for breeding resistance in the context of specific pathovars present locally. Here, BB-resistance and susceptibility genes of Komboka were analyzed, and a combination of Cas9, Cpf1 and multiplexed gRNAs was used to edit all known EBEs in the SWEET genes, resulting in broad-spectrum resistance to not only previously known African and Asian strains, but also the newly introduced Xoo strains identified from the outbreak in Tanzania.

Here, we report a rapidly spreading outbreak of BB in East Africa that was first identified in 2019 in the Morogoro region in Tanzania. Through genetic and genomic characterization, the outbreak can be ascribed to a recent colonization event by Xoo strains in the Morogoro region that are most similar to Asian strains, that is, from Yunnan province in China. Notably, strains that originated from Asia and Africa before 2019 form distinct phylogenetical groups (Lang et al., 2019; Tran et al., 2018). Before 2019, BB incidence was relatively low, and only three strains were isolated between 2011 and 2018 (Oliva et al., 2019). As shown previously, these three endemic Tanzanian strains cluster with other African Xoo strains, mostly from West Africa, based on SNP-based core genome phylogeny analyses, and all African strains make use of TalC as the major virulence TALe, some additionally use TalF to trigger SWEET14 induction (Oliva et al., 2019). At present, we cannot trace the exact history of introduction of the new Asian-type strains, which may have occurred through either major storms, animal migration or transfer of contaminated rice seeds. Xoo can be transmitted by tropical storms. Evidence for transmission within Asian countries has been provided, for example, for PXO99^A, which may have been introduced rather recently from Nepal or India to the Philippines. By contrast, rather effective continental isolation had been observed. One may hypothesize that if the new Tanzanian strains had been transmitted by storms from Asia, the strains might be more closely related to strains from India or Indonesia based on the geography (Oliva et al., 2019; Quibod et al., 2016; Tran et al., 2018). Due to the distinct evolutionary trace and the resulting absence of coevolution, it is likely that many African rice varieties do not contain suitable R-genes that protect against Asian strains. Hallmark features of the new strains identified in Tanzania are the presence of iTALes and the PthXo1 homolog PthXo1B; both are absent from endemic African strains. African rice lines carrying Xa1 may thus be resistant to endemic African strains, but will be susceptible to Asian strains, including those recently introduced to Tanzania. Surveys over several years, including preliminary data from 2022, indicate that the outbreak is gaining momentum regarding severity and spread, thus potentially becoming a threat to East Africa, and over the course of time, possibly to all of Africa. This study, which so far is based on the full analysis of only a few strains from two locations in Morogoro, shows that eight strains are genetically almost identical, intimating a single introduction event in this region. However, further analysis of a greater number of strains will be required to validate origin and relationships, as well as further evolution.

We had previously described that ectopic induction of at least one clade III SWEET by a TALe is essential for virulence of all Xoo strains characterized to date (Chen et al., 2012; Eom et al., 2019; Oliva et al., 2019; Streubel et al., 2013). A major difference between Asian and African strains is the distinct set of TALes that target SWEETs, in which endemic African strains specifically target only distinct EBEs for TalC and TalF in SWEET14 (Oliva et al., 2019). It is thus likely, due to the absence of coevolution, that many African rice varieties contain EBEs in SWEET11a, 13 and 14 promoters that can be targeted by Asian TALes. In Asia, single R genes and even combinations of several R genes are insufficient for robust resistance, because new strains evolved that break individual R genes or combinations thereof (Arra et al., 2017). Therefore, breeders test current strains against a panel of rice NILs that carry individual, or combinations of different R genes (http://www.knowledgebank.irri.org/ricebreedingcourse/Breeding_for_disease_resistance_Blight.htm)(Padmaja et al., 2017). Subsequently information on the optimal set of R gene combinations is used to stack R genes to obtain the broadest possible spectrum of resistance against local populations of the pathogen (Arra et al., 2018). Researchers and breeders use clipping assays with high bacterial titers to evaluate resistance of rice lines to BB (Kauffman et al., 1973). The assay, even when performed in greenhouses, is considered to be highly predictive of field performance of resistant varieties (Adhikari et al., 1995; Fred et al., 2016; Padmaja et al., 2017). Due to the full dependence of Xoo virulence on the activation of particular SWEET genes, a complete block of induction of these SWEET genes by introducing mutations into the EBE is deemed the most effective way to protect rice varieties against the currently known spectrum of Asian and African Xoo strains.

Due to the long timeline between identification of an elite variety, that is, the need to establish suitable transformation protocols, the actual genome editing, elimination of transgenes, transfer to countries that instated regulations for SDN-1 based genome editing, field testing and registration, target varieties have to be chosen many years before deployment. Komboka was chosen since it was predicted to become popular in Kenya, a country that established guidelines that allow the use of edited lines, provided they do not contain transgenes (Buchholzer and Frommer, 2023). While a particular rice variety may contain one or several R genes, they can be overcome by existing mechanisms, thus introduction of the combined SWEET EBE mutations will likely provide a much broader and more robust resistance to BB. Analysis of Komboka, a high yielding semi-aromatic rice line released in Kenya and Tanzania, showed resistance to endemic African strains due to Xa1 and Xa4. However, both R-genes had previously been broken in Asia. Notably, Komboka was found to be susceptible to Asian strains like PXO99^A, which carries both iTALes and PthXo1 that suppress Xa1 and induce SWEET11a, respectively. Indeed, we found Komboka samples with BB symptoms in one district in Tanzania (Mikindani, Mtwara, ∼400 km from Dakawa) in 2022. Characterization of the collected leaves is ongoing. Xa1-mediated resistance has been broken by 95% of the Asian Xoo strains (Ji et al., 2020), and Xa4-mediated resistance was overcome by the new East African Xoo strains as well as many Asian strains reported previously (Quibod et al., 2016). Thus, Xa1 and Xa4 lack durability due to shifts in the Xoo population or the emergence or introduction of new strains. Thus, new lines with broad-spectrum resistance against both Asian and African strains, including the strains found in Tanzania, is required (Quibod et al., 2020; Vera Cruz et al., 2000).

We hypothesized that editing all known EBEs for both African and Asian SWEET-targeting TALes could be used to engineer full and robust resistance in an emerging elite variety for Africa. Since this strategy requires simultaneous editing of six EBEs, optimally causing small deletions in each EBE to enhance robustness, we developed a hybrid CRISPR-Cas9/Cpf1 system that targets all six EBEs in Komboka. Both CRISPR-Cas9 and CRISPR-Cpf1 systems have been widely used in genome editing. SpCas9 is the first Cas version to offer high editing efficiency across a wide range of plant species. LbCpf1 or LbCas12 is another endonuclease which has a lower molecular weight compared to SpCas9 and requires shorter CRISPR RNA (crRNA)(Liu et al., 2017). SpCas9 and LbCpf1 both generate double-stranded breaks, but Cas9 introduces blunted cuts 3 base pairs upstream of the PAM, while Cpf1 introduces 5 bp staggered cuts downstream of the PAM (Zetsche et al., 2015). Hence, Cpf1 often produces larger mutations compared to Cas9, which mainly introduces single base pair insertions or deletions (indels). Depending on the purpose of genome editing, larger or smaller alterations may be preferred. To generate knock-out mutants, single base pair indels in the first exon that result in frameshifts or premature stop codons are sufficient. To prevent the binding of TALes to their respective EBEs on SWEET promoters, single base pair changes are not always effective due to the degenerate code and the ability to loop out central RVD repeats of the TALes (Oliva et al., 2019). In addition, Xoo evolves rapidly and, therefore, single base pair changes could be overcome quickly, as demonstrated for an xa25-like resistance gene (Xu et al., 2019). Hence, to prevent rapid break of the resistance by simple modifications of the TAL effectors, a larger mutation would be preferred. Since it is still unknown how the native SWEET expression is affected by promoter mutations, the number of base pair indels needs to be evaluated carefully. In addition, prevention of TALe binding to EBEs depends not only on the number of deleted or inserted base pairs but also on the position of the introduced mutations within the EBE. Especially, the RVDs at the 3´-end of TALes, such as N* and NS, have less specificity in nucleotide binding, therefore, mismatches at the 3´-end of an EBE can be tolerated by the RVDs (Richter et al., 2014). Here, the 1 bp deletion at the 5´-end of the TalC binding site is sufficient for resistance, while a 4 bp deletion at the 3´-end of the AvrXa7 binding site did not prevent binding of AvrXa7 to its EBE, indicating that mutations at the 5´-end of the TALe binding site are more effective than mutations at the 3´-end in preventing the binding of TALes to EBEs.

Cas9 cleaves target DNA adjacent to a G-rich PAM, while Cpf1 requires a T-rich PAM sequence (Zetsche et al., 2015; Zhang et al., 2014). Therefore, combining Cas9 and Cpf1 into a single system enables simultaneous editing in both G- and T-rich regions. Here, EBE regions used for gRNA design were comparatively short, just 23–29 bp, hence, there were a limited number of suitable gRNA design options (considering also potential unwanted off-target effects). The BB-resistant IR64 and Ciherang-Sub1 lines developed previously for Asia were generated using four gRNAs for SWEET11a, 13 and 14 promoters, but did not target the TalF EBE in SWEET14 which is targeted by African strains specifically (Eom et al., 2019; Oliva et al., 2019). The EBE in the respective promoters for TalF lacked a suitable SpCas9 NGG-PAM recognition sequence. By combining the two enzymes Cpf1 and Cas9 into a hybrid CRISPR-Cas9/Cpf1 system, it became possible to design four gRNAs (three gRNAs for Cpf1, including one for TalF; and one for Cas9 to target TalC, which lacked a suitable PAM sequence for Cpf1) that target all six known EBEs relevant for BB susceptibility. The combination of CRISPR-Cas9 and Cpf1 gRNAs in a single system increases the flexibility of choosing suitable gRNAs depending on the available PAM recognition sequences and off-target frequency. An efficient transformation protocol previously established for Komboka was used here to edit all known EBEs in three SWEET promoters (Luu et al., 2020). For four target sites (cXo1, cXo2c, gTalC, cTalF), we generated 15, 27, 16, and 21 variants, respectively using four gRNAs, demonstrating the successful application of the hybrid Cas9/Cpf1 in multiplex genome editing of the rice variety Komboka. Each variant represents a distinct R gene. Edited Komboka lines were shown to be resistant against a set of representative Asian and African Xoo strains, which harbor all known SWEET-inducing TALes.

It has been suggested that TALes can evolve rapidly to allow adaption to host resistance due to changes in the respective EBEs. It is thus conceivable that the resistance developed here can be broken by the evolution of new TALe variants that recognize elements in the edited SWEET target promoters (Perez-Quintero and Szurek, 2019). Various observations may indicate however that the velocity at which such new TALe emerge is slower than expected: although all six Clade 3 SWEETs can theoretically serve as susceptibility factors as shown by using artificial artTALes, neither African nor Asian strains seem to target SWEET11b, 12, or 15 yet (Streubel et al., 2013; Wu et al., 2022). Notably, xa13, carrying a large promoter insertion in SWEET11a, is still used widely; thus we hypothesize that no new TAL effectors that target SWEET11a have emerged and are able to break the resistance. Notwithstanding, even if such variants emerge, new promoter variants can be developed by editing at time scales not too different from that of the spread of the new strains.

Crosses and analyses for determining the reliable elimination of transgenes from the edited Komboka lines described here is in progress. In parallel, monitoring the evolution of Xoo in Africa is of critical importance for early detection of Asian strains, hybrid African-Asian strains or newly emerging strains. The diagnostic SWEET^R Kit 2.0, upgraded with the newly identified SWEET11b susceptibility gene and containing all six translational SWEET-reporter and knockout lines, can effectively be used to detect the targeted EBEs, while TALome analysis can be performed to detect the presence of SWEET-inducing TALes in the current African Xoo population (Eom et al., 2019; Wu et al., 2022). Kenya evaluates applications for the import of transgene-free lines on a case-by-case basis, thus it will be necessary to prepare suitable documentation for import. In parallel, it is planned to use the hybrid Cas9/Cpf1 strategy to expand the resistant germplasm to other rice varieties grown in African countries to be able to meet consumer-farmer preferences. This project aims to ultimately provide the material to small-scale producers. Governmental action is recommended to reduce the risk of introduction of Asian pathogens to Africa and vice versa. In parallel, improved management practices and training may also help farmers to reduce disease incidence (Mew et al., 2018).

All data supporting the results are available in the main text or supplementary materials. All data that support the findings of this study were included in the manuscript; raw data are available at Dryad (https://doi.org/10.5061/dryad.xpnvx0kk3; Summary of raw data files deposited at dryad is provided in Source Data 1). Sequencing data for strains from this study have been deposited in the NCBI Sequence Read Archive (SRA) database (Accession codes for iTz strains are provided in Supplementary File 2 - Tabs 1 and 2). Materials will be made available under MTA.

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Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting the paper "Genome editing of an African elite rice variety confers resistance against endemic and emerging Xanthomonas oryzae pv. oryzae strains" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by me as Reviewing Editor and Senior Editor. The reviewers have opted to remain anonymous.

Comments to the Authors:

After consultation with the reviewers, we have decided that this work cannot be considered in its current form for publication by eLife. However, we are interested in the work in principle and would reconsider a new version with additional key evidence, as outlined below. I very much hope that it will be possible to generate such limited additional data.

Since the advances presented here are tweaks, albeit important ones, to your own excellent prior work, the manuscript has to stand on a very clear description of the pathogens and a clear demonstration of the relevance of the edited lines in the field.

The overall framework of the manuscript, from outbreak analysis to genome-edited lines, is exemplary, but there are important questions as to the focus on a variety that is not susceptible under field conditions and also as to the inconsistent choice of pathogen strains for genome analysis and pathogenicity assays.

The inconsistency of pathogen data should hopefully be quite easily addressable by the inclusion of appropriate genomics analyses and pathogenicity assays. On the other hand, the fact that the rice variety chosen for editing is susceptible in artificial inoculation assays but not under field conditions tells us that there is more to learn on the fitness penalty that you may have missed. This brings the question of the immediate utility of these edited rice lines: The data presented here point to the need for edited lines not in the moderately resistant Komboka variety (what you have chosen), but in the varieties that are in fact susceptible to the emerging strains under field conditions.

I would happy to hear if you have justification for this, and could make an argument for this – what seemed to us – peculiar choice.

Reviewer #1 (Recommendations for the authors):

1. Citing Supplementary table 1 for the sentence on the characterization including diagnostics and pathogenicity of 833 strains might be misleading. This table contains only a subset of strains and their NCBI accession numbers. I see some publications cited here and it may be that some of these strains are part of those publications. So, it might be misleading to the readers to refer them to supplementary table 1 for the collection.

2. "We performed disease surveys in this area in 2019 and 2021 and identified two outbreaks on TXD 306 (SARO-5), a rice variety popular in irrigated ecologies in Tanzania. More recently BB was identified in Komboka. Leaves with typical BB symptoms were processed, and seven strains from Dakawa and 106 from Lukenge were isolated and validated as Xoo with diagnostic primers (Lang et al., 2010). Notably, surveys performed in subsequent years showed increased severity and spread (Supplementary Table 2)." The way this writeup is, it seems like the increased severity and spread was seen on Komboka. It might be good to clarify that disease severity of 2 (4-6%) of disease was observed on Komboka. But other varieties showed more disease severity of scales 4 or 5.

3. Check spelling in Figure for Teqing. Figure 1 supplement 2. Is it Xa4_Teping or Xa4_Teqing?

4. It might be good to include TALes in endemic and emerging strains in the table with a list of strains and their origin. Similarly, resistance gene profiles for African rice varieties sampled in surveys can be included (based on the database). To Xanthomonas oryzae readers, this may be obvious. However, to the scientific community interested in outbreak analysis and management, this study could be an excellent example to refer to.

Reviewer #2 (Recommendations for the authors):

1. The work could be strengthened with additional draft genome sequences, which may confirm that the outbreak is genetically homogenous and likely the result of a single introduction. Annotating TALes in all three sequenced strains would show if the three strains have the same effector profile. It would be helpful to include metadata in Table S1 to help the reader understand which strains were used for which experiments, and which disease outbreak they are associated with.

2. It would be helpful if outbreak data were summarized and the relationships of the various outbreaks to each other and to the work presented in this manuscript were made clearer. For example, if data were summarized and placed on a map for readers not familiar with the regions and districts of Tanzania.

On page 4, when describing the outbreaks of BB, it's unclear which outbreaks are first reported in the literature in this study versus what has been previously reported. It's not clear how supplementary table 1 relates to the rest of this sentence: "To systematically analyze these newly isolated strains and to compare them to the broader African Xoo landscape, 833 strains from rice fields sampled in nine African countries between 2003 and 2021 were collected and characterized using molecular diagnostic as well as pathogenicity assays ( Supplementary Table 1)(Afolabi et al., 2016; Gonzalez et al., 2007; Tall et al., 2020; Tekete et al., 2020). Supplementary Table 2 is cited for "two unprecedented outbreaks were identified, one in 2019 in Dakawa and another in 2022 in Lukenge" but this table only includes 2022 data. The sentence "We performed disease surveys in this area in 2019 and 2021 and identified two outbreaks on TXD 306 (SARO-5), a rice variety popular in irrigated ecologies in Tanzania.", has no supporting data, except that strains from 2019 are used. Finally, the sentence "More recently BB was identified on Komboka" is shown in Supplementary Table 2 after many pages of other reports, but the table isn't cited. Improving the clarity of presentation of these reports would be beneficial to the reader so that there isn't a need to synthesize data among text and supplementary tables to understand which outbreaks were sampled and how they are used in this study.

3. On page 5, the text says "Notably, CIX4457, CIX4458, and CIX4462 clustered with Asian Xoo isolates (Figure 2A)." But only 4462 is shown in the tree, the other strains shown are 4506 and 4509.

4. There are two hyperlinks at the top of page 4 that are not working.

Reviewer #3 (Recommendations for the authors):

The work in the manuscript under review is technically quite sound. However, the description of the work could be improved. For example, the first paragraphs of the Results section describe exclusively published and not new data. I suggest moving these passages to the Introduction section. Moreover, the manuscript has several tables and figures that are referenced but hardly described in the Results section. I would suggest that the authors provide at least a basic description of the contents of these Tables/Figures in the Results text. One cannot expect that the reader will go through the data to extract the essential information.

[Editors’ note: The authors appealed the original decision. What follows is the authors’ response to the first round of review.]

Comments to the Authors:

After consultation with the reviewers, we have decided that this work cannot be considered in its current form for publication by eLife. However, we are interested in the work in principle and would reconsider a new version with additional key evidence, as outlined below. I very much hope that it will be possible to generate such limited additional data.

Since the advances presented here are tweaks, albeit important ones, to your own excellent prior work, the manuscript has to stand on a very clear description of the pathogens and a clear demonstration of the relevance of the edited lines in the field.

The overall framework of the manuscript, from outbreak analysis to genome-edited lines, is exemplary, but there are important questions as to the focus on a variety that is not susceptible under field conditions and also as to the inconsistent choice of pathogen strains for genome analysis and pathogenicity assays.

The inconsistency of pathogen data should hopefully be quite easily addressable by the inclusion of appropriate genomics analyses and pathogenicity assays. On the other hand, the fact that the rice variety chosen for editing is susceptible in artificial inoculation assays but not under field conditions tells us that there is more to learn on the fitness penalty that you may have missed. This brings the question of the immediate utility of these edited rice lines: The data presented here point to the need for edited lines not in the moderately resistant Komboka variety (what you have chosen), but in the varieties that are in fact susceptible to the emerging strains under field conditions.

I would happy to hear if you have justification for this, and could make an argument for this – what seemed to us – peculiar choice.

We are happy to see the comments of the editor on the value and importance of this work. We substantially edited the text, added a map as new Figure 1, included new data on the close relatedness of the strains from Dakawa and Lukenge (replaced Figure 3), added a new Figure 2 Supplement that shows that besides the Dakawa strains, also a Lukenge strain is fully virulent on Komboka, and we added sections to Discussion and Methods providing more depth regarding the predictive power of the greenhouse clipping assay for field performance with references.

Some key points that we think are relevant for the interpretations made by the reviewers:

• Until now, virulence of Xoo depends fully on the ability to induce one of the three SWEET genes SWEET11a, 13 or 14.

• To our knowledge, the systematic editing of SWEET EBEs is the only effective way to obtain resistance against a large panel of Asian and African Xoo strains (many hundreds were tested by us).

• Indian breeders regularly test a panel of NIL rice lines carrying either single or combinations of R/genes against a panel of strains.

• To date, All single R genes have been broken in India.

• Similarly, all double, triple and quadruple R gene combinations have been broken.

• At present, Indian breeders have to combine at least five R loci (often genes or mechanisms are not known) to obtain resistance to the majority, but not all, strains.

• Thus, even if a variety may be resistant to a particular strain, or carries a combination of four R genes, it makes sense to edit the EBEs of all SWEETs in this variety to provide robustness.

• Komboka was chosen carefully after consulting with the key breeders in order to use the most advanced line that has a high chance of being adopted and that will be widely used at the time it can be released, which is many years only after it was successfully generated.

• Note also, that the top BB experts and breeders confirmed that leaf clipping assays in greenhouses are predictive for field performance of resistance (actually even moderate resistance in the clipping assay will behave as resistant in the field).

• Komboka is fully susceptible to the strains from the Tanzanian outbreak in clipping assays.

• The data on Komboka from the 2022 survey are first observations, and cannot be used to deduce the level of resistance in the field. This is particularly due to difficulties in assessing disease incidence in the field in such a survey: infection may have occurred early or late, with high titer, or observation may have been made late, when plants start to senesce, and thus disease could not be adequately classified. Note that due to the recent detection of the outbreak, systematic multi-year observations have only been initiated.

• Note also, that we believe it will be important to generate such edits in a wide range of varieties, since there is a lot of consumer preference in different countries and regions. Based on the large combinatorial space (if we make a low assumption, namely that only the first 15 bp are relevant, and we assume that each repeat can recognize 2 different bases, we can generate 2¹⁵ variants), we would recommend to deploy different edits in different varieties to increase the robustness.

You asked us to justify the use of Komboka. This request was likely based on a comment from Reviewer 1, who stated that Komboka is moderately resistant.

• The Reviewer bases his comment on Komboka susceptibility from our newest data from 2022 (!) from a single observation in one location. It is for obvious reasons not possible to conclude anything about the grade of susceptibility from a single observation. One needs to observe over several years and several sites. This is the first observation in the field for Komboka and it could be more severe in 2023. Komboka was originally described on websites as moderately resistant to BB. However, we do not believe that such a classification is relevant. It depends on the particular strain and the gene-for-gene interaction as well as the R gene outfit of the rice line whether the rice variety in this particular pair can be classified as susceptible or resistant, or the strain as virulent or avirulent. If you look at Figure 2, it is clear that Komboka is fully susceptible to PXO86 and the three strains isolated in 2019 in Dakawa-Tanzania, but resistant to a wide range of African strains from our collection. Note that these strains were chosen for the initial characterization of Komboka to evaluate it’s resistance/susceptibility profile. We then tried to find out why Komboka is resistant to a lot of the African stains, and found that it carries Xa1 and Xa4. Subsequent analyses showed that Komboka is also susceptible to PXO99^A and to the Lukenge strains, which were isolated in Tanzania in 2021; based on genotyping they are close relatives and possibly descendants or the strains first strains found in Dakawa, although we cannot rule out the reverse. In summary, if iTz strains ente Kenya (which we hypothesize may already happened), they will cause severe damage, faster manifestation. The edited lines will be the current best tools to help the farmers there.

• The key assay to evaluate field-relevant resistance that is used by breeders is ‘clip infection’ (Kauffman et al., 1973). This is an ‘overkill’ assay (OD600 = 0.5, so billions of bacteria), that is, according to all breeders we have talked to, e.g., in India, as well as several senior Xoo experts, highly predictive: they are not aware of any cases where a line tested with this assay and classified as resistant in greenhouses or growth chambers did not hold up in the field. It is generally even assumed that moderate resistance, so some lesion detected in this assay, will be fully resistant in the field. We added text to Results and Discussion sections, and a new section on sampling in Methods with respective references that show the correlation of data using assays with the same strains in greenhouse and field.

• Different countries have a preference for growing certain rice varieties. Since Kenya was projected to be among the first African countries to develop editing guidelines, we evaluated germplasm from Kenya. Thus, instead of using Kitaake as proof of concept, or IR64, we focused on the promising elite variety Komboka for Kenya as recommended by IRRI Africa.

• We selected Komboka in 2019 as a candidate because it was recommended as an emerging variety in Kenya with exceptionally high yield, and suitable properties relevant to the local consumers. This was a bet at that time, but the variety has indeed been widely adopted in Kenya (pers. Comm. IRRI Africa). The next step after acquiring seeds was to establish whether these can be grown and be fertile in Düsseldorf in the greenhouse (tropical variety that normally prefers neutral or short day conditions). We successfully established conditions for effective growth and reproduction in Düsseldorf and growth conditions in Montpellier for virulence tests, then needed to establish a transformation protocol, which was published recently (Luu et al. 10.21769/BioProtoc.3739).

• In India, most single, double and triple R gene combinations for BB have been broken. Thus, it is necessary, even if a variety is resistant to a particular strain, to generate robust broad spectrum resistance. Since virulence of Xoo depends critically on SWEET activation (no one has yet observed a case where SWEET11a, 13 or 14 activation was not involved – note the single manuscript that stated that has been retracted), and US strains are not virulent because they do not have TAL effectors. We thus used knowledge of the TALe repertoire of our worldwide collection to edit all known SWEET EBEs. These lines are resistant representatives trains from Asia and Africa, but most importantly, to the strains from the outbreak described here.

• We have clarify the disease spread from the outbreak, both by editing the text, as well as by adding a new Figure 1 with maps of the collection sites and % infected plants in the respective sampling years. We provide more information on the surveys and the sampling. We also clarified the nomenclature of the introduced strains and provide more data on their relationship (see also next paragraph).

• Nomenclature issues: We obviously tried something that was not very wise, we used a code (CIXnnnn) to systematically number the strains that were collected. This is beneficial, especially since before strains obtained random labels such as ‘Nati Park’. But we understand that this code can be confusing since it is hard to remember the similar strain numbers. We have thus, while keeping the code, given logical names to the isolates – i for the newly introduced Asian strains, Tz for collected in Tanzania (we have started to collect in Kenya and will expand widely, so need Tz in there), Dak for Dakawa and Luk for Lukenge, and the year of isolation (21 for 2021), plus a number for the isolate (e.g.: iTzLuk21-3). This makes it very intuitive to trace the strains used in the various experiments in publications. This should address a number of the issues brought up by the reviewers. It is also noteworthy, that the project had two parallel activties - selection of a suitable rice line (see below) for Kenya, first virulence tests with available strains, followed by characterization of the R gene outfit followed by editing. In parallel, we collected strains in Tanzania before and after the outbreak, but the iTz were not available at the beginning. We apologize for the confusion the nomenclature may have caused.

Reviewer #1 (Recommendations for the authors):

1. Citing Supplementary table 1 for the sentence on the characterization including diagnostics and pathogenicity of 833 strains might be misleading. This table contains only a subset of strains and their NCBI accession numbers. I see some publications cited here and it may be that some of these strains are part of those publications. So, it might be misleading to the readers to refer them to supplementary table 1 for the collection.

We apologize, there was indeed a disconnect. We chose 21 representative strains based on the country of origin, knowing that the genotyping of our collection of 833 strains from across Africa shows that Africain Xoo strains tend to cluster according to the geography. This is another large study that is currently being written up. We clarified this in the new version of the manuscript.

2. "We performed disease surveys in Morogoro in 2019 and 2021 and identified two outbreaks on TXD 306 (SARO-5), a rice variety popular in irrigated ecologies in Tanzania. More recently BB was identified in Komboka. Leaves with typical BB symptoms were processed, and seven strains from Dakawa and 106 from Lukenge were isolated and validated as Xoo with diagnostic primers (Lang et al., 2010). Notably, surveys performed in subsequent years showed increased severity and spread (Supplementary Table 2).

We tried to clarify the information from former Table S1 (now S2) by adding maps as the new Figure 1. We have now highlighted that these are snapshots, and infection of Komboka was detected only recently in one location (most recent collection in 2022). Komboka is fully susceptible (see clipping assay results in the various figures) to the introduced Tanzanian strains. Note the ‘overkill” nature of the clipping assay which by all experts we talked to is highly predictive for field performance. Note also that disease severity is affected by many factors such as climate conditions, nitrogen fertilizer amount, initial infection titer and path and time of infection relative to plant growth stage. Also, the observations were made at one time point, and thus could either represent an early time point after infection. It seems likely that the strains spread recently, and the disease has not fully manifested. Future surveys will clarify this. But again, the breeders and experts we talked to confirmed that the clipping assay is highly sensitive, thus our greenhouse observation that Komboka shows lesion lengths similar to PXO99^A and in the range of 15-20 cm is consistent with full susceptibility to the iTz strains. Please also see comments to editor and to comment #1 of this reviewer above. We clarified this also in the text. We added text to Results and Discussion sections and a new section on sampling in Methods with respective references that show the correlation of data from assays with the same strains in greenhouse and field.

3. Check spelling in Figure for Teqing. Figure 1 supplement 2. Is it Xa4_Teping or Xa4_Teqing?

We apologize the typo, which has been corrected.

4. It might be good to include TALes in endemic and emerging strains in the table with a list of strains and their origin. Similarly, resistance gene profiles for African rice varieties sampled in surveys can be included (based on the database). To Xanthomonas oryzae readers, this may be obvious. However, to the scientific community interested in outbreak analysis and management, this study could be an excellent example to refer to.

We are aware that it is very hard for non-experts to follow the nomenclature of strains and TALes. We have followed the suggestion, and where available, added the TALe information for all strains used in the new Supplementary Table 1 and 3 which summarizes info on the strains used here.

Reviewer #2 (Recommendations for the authors):

1. The work could be strengthened with additional draft genome sequences, which may confirm that the outbreak is genetically homogenous and likely the result of a single introduction. Annotating TALes in all three sequenced strains would show if the three strains have the same effector profile. It would be helpful to include metadata in Table S1 to help the reader understand which strains were used for which experiments, and which disease outbreak they are associated with.

As indicated above, we have provided new data resulting of the analysis of the draft genome sequences of 5 additional strains from Dakawa and Lukenge (new Figure 3), demonstrating that strains from Dakawa and Lukenge all share the same typical Asian-like virulence features: presence of pthXo1B and iTALes. Moreover, they all cluster together as one monophyletic group upon SNP-based whole genome sequence phylogeny, therefore further confirming the homogeneity of the outbreak. We have added a new Suppl. Table 3 that provides all these information. As to the 3 strains for which the chromosome could be circularized and the respective complete TALe repertoires extracted, we have provided, as requested by reviewer #2, a new Suppl. Table (Suppl. Data 1) displaying the alignments of the RVD arrays of 17 TALE groups. As expected, the 3 strains show the same effector profile.

2. It would be helpful if outbreak data were summarized and the relationships of the various outbreaks to each other and to the work presented in this manuscript were made clearer. For example, if data were summarized and placed on a map for readers not familiar with the regions and districts of Tanzania.

Thank you for the suggestion. We have followed the advice and added a new Figure 1 with the respective maps as well as photos of the infection as supplementary Figures.

On page 4, when describing the outbreaks of BB, it's unclear which outbreaks are first reported in the literature in this study versus what has been previously reported. It's not clear how supplementary table 1 relates to the rest of this sentence: "To systematically analyze these newly isolated strains and to compare them to the broader African Xoo landscape, 833 strains from rice fields sampled in nine African countries between 2003 and 2021 were collected and characterized using molecular diagnostic as well as pathogenicity assays ( Supplementary Table 1)(Afolabi et al., 2016; Gonzalez et al., 2007; Tall et al., 2020; Tekete et al., 2020).

Thanks for pointing that out. We moved this part of the Results to where it belongs – the introduction. Thus, the Results section now describe our results. We also admit that it was unclear why we mention the large African collection. We have collected these strains over a long period and are assembling a manuscript that describes the genetic diversity of this collection. From the collection of endemic African strains, we used a carefully chosen representative subset for testing virulence on Komboka. This has now been clarified in the first section of the Results.

Supplementary Table 2 is cited for "two unprecedented outbreaks were identified, one in 2019 in Dakawa and another in 2022 in Lukenge" but this table only includes 2022 data. The sentence "We performed disease surveys in this area in 2019 and 2021 and identified two outbreaks on TXD 306 (SARO-5), a rice variety popular in irrigated ecologies in Tanzania.", has no supporting data, except that strains from 2019 are used. Finally, the sentence "More recently BB was identified on Komboka" is shown in Supplementary Table 2 after many pages of other reports, but the table isn't cited. Improving the clarity of presentation of these reports would be beneficial to the reader so that there isn't a need to synthesize data among text and supplementary tables to understand which outbreaks were sampled and how they are used in this study.

Sorry, this was a misnumbering, which has been corrected. We have clarified the text and included data for the identification of BB in Dakawa in 2019 and Lukenge in 2021. We edited also the text regarding the survey and added new information for the survey performed in 2022.

3. On page 5, the text says "Notably, CIX4457, CIX4458, and CIX4462 clustered with Asian Xoo isolates (Figure 2A)." But only 4462 is shown in the tree, the other strains shown are 4506 and 4509.

Apologies for the confusion. We had initiated WGS of all strains collected, however, the quality of some of the strain sequences was not high enough to be included. We have now included data from 5 new draft genomes demonstrating that all the newly introduced strains form a genetically homogeneous group. We cannot determine which strain was at the origin of the outbreak, however it is clear that these strains are all highly related and derive from a close common ancestor (introduction). We also show that the strains from Dakawa and Lukenge contain pthXo1-like TAL effectors that target SWEET11a, as well as iTALes. We also changed the nomenclature since the CIX codes are highly valuable on the long run, e.g. in databases, but are hard to follow for the reader. The new names are intuitive and much easier to follow.

4. There are two hyperlinks at the top of page 4 that are not working.

We tested all hyperlinks, which are all functional.

Reviewer #3 (Recommendations for the authors):

The work in the manuscript under review is technically quite sound. However, the description of the work could be improved. For example, the first paragraphs of the Results section describe exclusively published and not new data.

The Reviewer is perfectly right. We moved that section to the Introduction and revised the first part of the Results.

I suggest moving these passages to the Introduction section. Moreover, the manuscript has several tables and figures that are referenced but hardly described in the Results section. I would suggest that the authors provide at least a basic description of the contents of these Tables/Figures in the Results text. One cannot expect that the reader will go through the data to extract the essential information.

We now added sentences in Results to better include the supp data.

Author details

1. Van Schepler-Luu

   1. Institute for Molecular Physiology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
   2. International Rice Research Institute, Los Baños, Philippines

   Contribution

   Supervision, Validation, Investigation, Methodology, Writing – original draft

   Contributed equally with

   Coline Sciallano, Melissa Stiebner and Chonghui Ji

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0709-2783

2. Coline Sciallano

   Plant Health Institute of Montpellier (PHIM), Université Montpellier, IRD, CIRAD, INRAE, Institut Agro, Montpellier, France

   Contribution

   Investigation, Methodology, Writing – original draft

   Contributed equally with

   Van Schepler-Luu, Melissa Stiebner and Chonghui Ji

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8988-7733

3. Melissa Stiebner

   Institute for Molecular Physiology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

   Contribution

   Formal analysis, Validation, Investigation, Visualization, Methodology

   Contributed equally with

   Van Schepler-Luu, Coline Sciallano and Chonghui Ji

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8626-0951

4. Chonghui Ji

   Division of Plant Science and Technology, Bond Life Sciences Center, University of Missouri, Columbia, United States

   Contribution

   Investigation, Methodology

   Contributed equally with

   Van Schepler-Luu, Coline Sciallano and Melissa Stiebner

   Competing interests

   No competing interests declared

5. Gabriel Boulard

   Plant Health Institute of Montpellier (PHIM), Université Montpellier, IRD, CIRAD, INRAE, Institut Agro, Montpellier, France

   Contribution

   Formal analysis, Investigation, Methodology

   Competing interests

   No competing interests declared

6. Amadou Diallo

   Plant Health Institute of Montpellier (PHIM), Université Montpellier, IRD, CIRAD, INRAE, Institut Agro, Montpellier, France

   Contribution

   Investigation

   Competing interests

   No competing interests declared

7. Florence Auguy

   Plant Health Institute of Montpellier (PHIM), Université Montpellier, IRD, CIRAD, INRAE, Institut Agro, Montpellier, France

   Contribution

   Investigation

   Competing interests

   No competing interests declared

8. Si Nian Char

   Division of Plant Science and Technology, Bond Life Sciences Center, University of Missouri, Columbia, United States

   Contribution

   Formal analysis, Investigation, Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5759-0764

9. Yugander Arra

   Institute for Molecular Physiology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

   Contribution

   Formal analysis, Validation, Investigation, Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6778-4258

10. Kyrylo Schenstnyi

    Institute for Molecular Physiology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

    Contribution

    Formal analysis, Validation, Investigation, Methodology

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-1595-6382

11. Marcel Buchholzer

    Institute for Molecular Physiology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

    Contribution

    Formal analysis, Writing – original draft, Project administration

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-7485-6918

12. Eliza PI Loo

    Institute for Molecular Physiology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

    Contribution

    Formal analysis, Supervision, Validation, Writing – original draft

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-7622-1139

13. Atugonza L Bilaro

    Tanzania Agricultural Research Institute (TARI)-Uyole Centre, Mbeya, United Republic of Tanzania

    Contribution

    Investigation

    Competing interests

    No competing interests declared

14. David Lihepanyama

    Tanzania Agricultural Research Institute (TARI)-Uyole Centre, Mbeya, United Republic of Tanzania

    Contribution

    Resources, Investigation

    Competing interests

    No competing interests declared

15. Mohammed Mkuya

    International Rice Research Institute, Eastern and Southern Africa Region, Nairobi, Kenya

    Contribution

    Resources, Investigation

    Competing interests

    No competing interests declared

16. Rosemary Murori

    International Rice Research Institute (IRRI), Africa Regional Office, Nairobi, Kenya

    Contribution

    Resources, Data curation, Investigation, Methodology

    Competing interests

    No competing interests declared

17. Ricardo Oliva

    International Rice Research Institute, Los Baños, Philippines

    Present address

    new address: World Vegetable Center, Shanhua, Tainan, Taiwan

    Contribution

    Conceptualization, Investigation

    Competing interests

    No competing interests declared

18. Sebastien Cunnac

    Plant Health Institute of Montpellier (PHIM), Université Montpellier, IRD, CIRAD, INRAE, Institut Agro, Montpellier, France

    Contribution

    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Validation, Investigation, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

19. Bing Yang

    1. Division of Plant Science and Technology, Bond Life Sciences Center, University of Missouri, Columbia, United States
    2. Donald Danforth Plant Science Center, St. Louis, United States

    Contribution

    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-2293-3384

20. Boris Szurek

    Plant Health Institute of Montpellier (PHIM), Université Montpellier, IRD, CIRAD, INRAE, Institut Agro, Montpellier, France

    Contribution

    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

    For correspondence

    boris.szurek@ird.fr

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-1808-7082

21. Wolf B Frommer

    1. Institute for Molecular Physiology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
    2. Institute for Transformative Biomolecules, ITbM, Nagoya University, Nagoya, Japan

    Contribution

    Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

    For correspondence

    frommew@hhu.de

    Competing interests

    The Healthy Crops team has filed for patents (PCT/US20 12/071722: Genetically modified plants with resistance to Xanthomonas and other bacterial plant pathogens; PCT/US20 10/033535: Novel sugar transporters; US 2011/0201118 A1: Nuclease activity of TAL effector and Fok1 fusion protein; PCT/EP2020/059893: Diagnostic Kit and method for SWEET-based rice blight resistance and resistant breeding lines), but is charitable and non-profit and aims at helping small scale rice farmers in Asia and Africa by reducing yield losses caused by pathogens . The authors declare no competing interests

    "This ORCID iD identifies the author of this article:" 0000-0001-6465-0115

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