CAN STRESS INDUCIBLE EUL LECTINS FROM RICE HELP TO FIGHT MELOIDOGYNE GRAMINICOLA INFECTION?

Jessica Joossens Stamnummer: 00707512 Promotor: Prof. dr. Els Van Damme Tutor: Sinem Demirel Asci Masterproef voorgelegd voor het behalen van de graad in Master of Science in de industriële wetenschappen: biochemie Academiejaar: 2018 - 2019

CAN STRESS INDUCIBLE EUL LECTINS FROM RICE HELP TO FIGHT MELOIDOGYNE GRAMINICOLA INFECTION?

Jessica Joossens Stamnummer: 00707512 Promotor: Prof. dr. Els Van Damme Tutor: Sinem Demirel Asci Masterproef voorgelegd voor het behalen van de graad in Master of Science in de industriële wetenschappen: biochemie Academiejaar: 2018 - 2019

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Copyright protection and confidentiality The author and the promoter give the permission to use this thesis for consultation and to copy parts of it for personal use. Every other use is subject to the copyright laws, more specifically the source must be extensively specified when using the results from this thesis.

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Acknowledgements First of all, I would like to thank Prof. Els Van Damme for giving me the opportunity to perform my master thesis at the Lab of Glycobiology at the University of Ghent and for her guidance, support and corrections during the experimental set up and the writing of the thesis. I would also like to my tutor, Sinem Demirel Asci, for her guidance and support during the experiments. She was a great example as a researcher, setting high standards for herself and other people. I learned a lot from Sinem and I wish her all the best in her future carrier and life. I would also like to thank Isabel for helping me with the experiments, especially in the last few weeks when time was running out. Last but not least, a special thank you to Ruben, my lover, who helped me through the last intense moments of this work. I learned a lot of skills and gained a lot of knowledge during my work at the Glyco Lab. Looking back on this thesis, there are some things in the lab I would have handled differently now, which means I gained a lot of experience that I will use in my future carrier. It was a pleasure working in the Glyco group, especially with Gosia, Isabel and my fellow student Julie. We had quite some laughs, which were needed when some experiments kept on failing. Overall, I really enjoyed my time here working as a ‘real’ scientific researcher, setting up experiments and analyzing data. It has given me even more motivation to find a PhD position or a job in the research sector. Furthermore, my compliments and respect to everybody in the Glyco group for their hard work and perseverance during their research. I had a nice time working with you.

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Summary Euonymus related lectins (EULs) represent a novel family of lectins and are ubiquitous among land plants. Their expression was shown to be stress inducible and it is therefore suggested that EULs fulfil an important role in the plant defense responses against environmental stresses. Rice is an ideal model organism to unravel the physiological function of EULs since its genome is fully sequenced and easy to transform. Furthermore, rice is a major food crop and characterization of proteins contributing to rice defense responses is essential for creating varieties with increased resistance against various stresses. In this study, Meloidogyne graminicola (Mg) was used as a biotic stressor on transgenic rice plants overexpressing D-type OrysaEUL lectins. Infection assays were conducted to examine whether overexpression of D-type EULs has an effect on Mg infection. Furthermore, a quantitative reverse transcription PCR allowed to compare systemic defense responses and OsEUL gene expression in whole rice roots after Mg infection. Results revealed that overexpression of OrysaEULD1A and OrysaEULD2 lowers the susceptibility of rice plants towards Mg infection, with the lowest susceptibility in plants overexpressing OrysaEULD1A. Furthermore, root transcript levels for OsEULD1A and OsEULD1B are slightly downregulated in transgenic as well as in non-transgenic plants, with the strongest downregulation in plants from the OrysaEULD1A overexpression line. Systemic defense signaling revealed no drastic changes in ET signaling after Mg infection whereas the JA pathway was strongly downregulated in control plants and attenuated in plants from the OrysaEULD1A and OrysaEULD2 overexpression compared to control plants. These results suggest a direct or indirect interaction between OrysaEULD1A and rice defense responses against Mg infection. . Keywords: stress inducible lectins, EUL lectins, Meloidogyne graminicola, rice

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Samenvatting Euonymus gerelateerde lectines (EULs) vertegenwoordigt een nieuwe familie van lectines die alomtegenwoordig aanwezig zijn in landplanten. Onderzoek heeft aangetoond dat de expressie van deze proteïnen geïnduceerd wordt onder stress omstandigheden, daarom wordt gesuggereerd dat EULs een belangrijke rol vervullen in de verdedigingsreactie van de plant tegen verschillende stress factoren. Rijst is een ideaal modelorganisme om de fysiologisch functie van EULs te ontrafelen, omdat het rijst genoom reeds volledig is gesequeneerd en de plant gemakkelijk te transformeren is. Bovendien, rijst is een belangrijke voedselbron en karakterisatie van proteïnen die bijdragen aan de verdediging van rijst tegen abiotische en biotische stress factoren zijn essentieel om meer resistente variëteiten te creëren. In dit werk werd Meloidogyne graminicola (Mg) gebruikt als biotische stress factor in transgene rijstplanten die D-type OrysaEULs tot overexpressie brengen. Infectie analyses werden uitgevoerd om na te gaan of overexpressie van D-type OrysaEULs de rijstplant helpt zich te verdedigen tegen Mg infectie. Bovendien werd een kwantitatieve reverse transcriptie PCR uitgevoerd op rijstwortels om systemische afweerreacties en OsEUL genexpressie te vergelijken na Mg infectie. De resultaten tonen aan dat overexpressie van OrysaEULD1A en OrysaEULD2 de vatbaarheid van rijstplanten voor Mg infectie verlaagd, met de laagste vatbaarheid gezien in de OrysaD1A overexpressie lijn. Bovendien worden de transcriptie levels voor OsEULD1A en OSEULD1B licht onderdrukt in de wortels, met de grootste onderdrukking in de OrysaEULD1A overexpressie lijn. Verder lijkt het dat Mg infectie geen invloed heeft op ET signalisatie, daarentegen wordt JA biosynthese en signalisatie wel sterk onderdrukt in controle lijnen en minder onderdrukt in planten van de OrysaEULD1A en OrysaEULD2 overexpressie lijnen in vergelijking met controle planten. Deze resultaten suggereren dat er een rechtstreekse of onrechtstreekse interactie bestaat tussen OrysaEULD1A en de verdedigingsreacties in rijst tegen Mg infectie. Kernwoorden: stress geïnduceerde lectines, EUL lectines, Meloidogyne graminicola, rijst

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Table of Contents Copyright protection and confidentiality .................................................................................... i Acknowledgements .................................................................................................................... ii Summary ................................................................................................................................... iii Samenvatting ............................................................................................................................. iv Table of Contents ....................................................................................................................... 5 Introduction ................................................................................................................................ 7 1. Literature review ................................................................................................................ 9 1.1. Stress inducible EUL lectins in rice ............................................................................... 9

1.1.1. Introduction to plant lectins ............................................................................................... 9 1.1.2. The EUL lectin family ..................................................................................................... 10 1.1.3. The EUL lectin family in Oryza sativa L. ssp. japonica ................................................. 11 1.1.4. OrysaEUL proteins, their ligands and physiological role ................................................ 11 1.1.5. Stress inducible expression profile of OsEUL genes ...................................................... 13

1.2. Introduction to rice immunity ....................................................................................... 16 1.2.1. Innate immunity ............................................................................................................... 16 1.2.2. Hormones and rice immunity .......................................................................................... 19 1.2.3. Systemic immunity .......................................................................................................... 23

1.3. Biotic stress in rice: Meloidogyne graminicola infection ............................................ 24 1.3.1. The host plant - rice ......................................................................................................... 24 1.3.2. Life cycle of Meloidogyne graminicola .......................................................................... 25 1.3.3. Effectors of Meloidogyne graminicola ............................................................................ 26 1.3.4. Hormone homeostasis in rice roots after Meloidogyne graminicola infection ................ 27

2. Materials and methods ...................................................................................................... 30 2.1. Plant material and growth conditions ................................................................................... 30 2.2. Meloidogyne graminicola culture and extraction ................................................................ 31 2.3. Meloidogyne graminicola infection and development assay ............................................... 31 2.4. RNA extraction, DNAse I treatment and cDNA synthesis .................................................. 32 2.5. Primer design and Real Time Quantitative RT-PCR ........................................................... 32 2.6. Statistical analyses ............................................................................................................... 34

3. Results .............................................................................................................................. 35 3.1. Meloidogyne graminicola infection assay in rice ................................................................ 35

3.1.1. Growth parameters for infected rice plants .................................................................................... 35 3.1.2. Development of Meloidogyne graminicola on rice plants ............................................................. 37

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3.1.3. Gall formation ................................................................................................................................ 41 3.1.4. Summary: the effect of D-type OrysaEUL overexpression in rice on Mg infection and

development ................................................................................................................................... 42 3.2. RT-qPCR analysis of D-type OrysaEULs and systemic defense related gene expression .. 43

3.2.1. D-type OsEUL gene expression ..................................................................................................... 43 3.2.2. Systemic defense related gene expression ..................................................................................... 44

4. Discussion ........................................................................................................................ 46 4.1. Meloidogyne graminicola infection assay in rice ................................................................ 46

4.1.1. Root architecture: an important factor to consider when using transgenic plants ......................... 46 4.1.2. OrysaEULD1A and OrysaEULD2 help rice to cope with Mg infection ........................................ 47

4.2. Transcriptional responses of D-type OrysaEUL and systemic defense related genes towards Mg infection .............................................................................................................................. 48

5. Conclusion ........................................................................................................................ 52 6. Literature .......................................................................................................................... 53 7. Appendix .......................................................................................................................... 66

7.1. Raw data of Meloidogyne graminicola infection assay ....................................................... 66 7.2. Raw data of the qRT-PCR experiment ................................................................................ 69

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Introduction Euonymus europaeus lectins (EUL) are a novel family of lectins, first reported in 2008 by the Lab of Glycobiology at the University in Ghent. Molecular research into the EUL domain revealed its ubiquitous presence in land plants and its stress inducible expression as a response to abiotic and biotic stress factors. It is therefore suggested that this protein plays an important role in helping the plant cope with environmental stresses. To get more insight into the physiological role of EUL lectins, transgenic overexpression lines of rice cv. Nipponbare were generated by the Lab of Prof. Van Damme through Agrobacterium mediated transformation. Each transgenic line overexpresses an OrysaEUL that is under the regulation of a cauliflower mosaic virus 35S promotor, which ensures strong consecutive gene expression. These transgenic overexpression lines were used to analyze the effect of OrysaEUL overexpression on abiotic and biotic stress assays. The experiments performed in this thesis contributes to the research that is currently performed at the Lab of Prof. Van Damme to unravel the physiological function of OrysaEUL lectins. Transgenic overexpression lines were infected with Meloidogyne graminicola as a biotic stressor to analyze whether overexpression of these stress inducible proteins helps rice plants to fight off infection. Since D-type OrysaEUL proteins respond better towards biotic stress compared to S-types (unpublished data), only D-type OrysaEUL overexpression lines were used in this work and include: OrysaEULD1A, line D (D1A-D) and line F (D1A-F), OrysaEULD2, line B (D2-B) and C (D2-C) and OrysaEULD1B line D (D1B-D). A transgenic empty vector line G (EV-G) was included in the experiments to study the effect of Agrobacterium mediated vector insertion on plant physiology. After 14 days of infection with Mg, rice plants were sampled and growth parameters including shoot length, root length and root weight were recorded. Phenotypic analysis of infected plants might reveal differences between transgenic and non-transgenic control plants and these differences should be taken into account in further analysis. Once measurements were completed, the roots of the infected plants were cut and stained subsequently with acid fuchsin, to visualize the nematodes. Using a microscope, each developmental stage of Mg as well as the number of galls was recorded per root system. To gain more insight into rice defense responses and the putative interaction with OrysaEUL lectins, gene expression for D-type OsEUL and systemic related defense responses was measured at 2 and 4 dpi in whole roots by using qRT-PCR. Data was represented for each genotype as transcript levels of infected roots relative to non-infected roots. To test for systemic defense responses, marker genes for JA biosynthesis, JA signaling and ET signaling were chosen, since these pathways are known to regulate systemic immunity in rice. Furthermore, previous research already revealed OrysaEUL proteins are induced after treatment with

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hormones such as JA and ABA. These data could reveal important insights into hormonal regulation of OrysaEUL proteins. Unfortunately, no qRT-PCR data was generated on the ABA pathway because of time limitations although future research could unravel whether there is an interaction between D-type OrysaEUL lectins and the ABA pathway. In the literature review of this thesis, a general introduction is given into EUL lectins in rice and rice immunity responses as well as an introduction into the Meloidogyne graminicola – rice interaction.

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1. Literature review

1.1. Stress inducible EUL lectins in rice 1.1.1. Introduction to plant lectins

Lectins are proteins of non-immune origin which are ubiquitous among all kingdoms of life and fulfil an important role in various biological processes. Lectins consist of at least one non-catalytic domain which has the capability to recognize and reversely bind specific carbohydrate structures (Peumans and Van Damme, 1995). These carbohydrate structures exist as free sugars or glycoconjugates and are endogenous to the plant or derived from foreign organisms such as herbivores or pathogens. Based on their structure, carbohydrate specificity and sequence homology, twelve lectin families can be distinguished: Agaricus bisporus agglutinin homologs, Amaranthins, Class V chitinase homologs, Cyanovirins, Euonymus related lectins (EUL), Galanthus nivalis agglutinin related lectins, Jacalin related lectins, Hevein domain lectins, Legume lectins, LysM domain proteins, Nictaba-like lectins and Ricin-B lectins (Peumans and Van Damme, 1995; Van Damme et al., 2008). Lectins can also be divided based on their expression profile. Group one consists of ‘classical’ lectins which are expressed constitutively at high levels in seeds and storage organs. They function as nitrogen storage proteins and play a combined role in plant defense due to their toxicity towards foreign organisms such as herbivores and fungi (Peumans and Van Damme, 1995). In the second group, lectin genes are expressed at very low basal levels which are barely detectable under normal plant growth conditions. However, their expression is considerably upregulated when the plant is exposed to stress conditions such as wounding, pathogen attack, salinity, drought and treatment with plant hormones. These lectins are referred to as stress inducible lectins, or nucleocytoplasmic lectins because of their localization in the nucleus and cytoplasm of the plant. In contrast to the classical lectins, which are often synthesized with a signal peptide for vacuolar localization or extracellular secretion, most of the stress inducible lectins lack a signal peptide and are putatively synthesized on free ribosomes in cytoplasm. Because of their stress inducible profile and cytoplasmic/nuclear localization, stress inducible lectins are believed to play an important role in stress related signaling processes. So far, at least 6 different lectin domains have been shown to be stress related (Fouquaert and Van Damme, 2012; Lannoo and Van Damme, 2014; Van Damme et al., 2008). In this study we will focus on one of the stress inducible lectin domains in rice, namely the EUL lectin family. Rice is an ideal model organism for unravelling the role of this novel lectin family

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in monocots. This major food crop has a relatively small genome size of about 370 Mbp, which is spread over 12 haploid chromosomes, and is easy to transform (Kawahara et al., 2013).

1.1.2. The EUL lectin family In 2008 a new family of lectins was discovered, grouping all proteins that show homology to the Euonymus europaeus agglutinin (EEA) that is present in high concentrations in the fleshy arils of the spindle tree (Euonymus europaeus). This family is referred to as the Euonymus europaeus lectin (EUL) family. Sequencing of the EUL domain revealed its ubiquitous presence in terrestrial plants and a high conservation throughout the Embryophyta clade, suggesting an important role for this protein (Fouquaert et. al., 2008; Fouquaert et al., 2009; Petryniak et al. 1977). Based on the EUL domain architecture that is present in the different protein sequences an EUL classification system is proposed by Fouquaert et al. (2009). According to this classification, EULs are subdivided into two large groups: S-type and D-type EULs. S-type EULs contain a single EUL domain, preceded by a highly variable and unrelated N-terminal domain. In a few S-types, an additional C-terminal domain can be found, whereas in other S-types a secretion signal precedes the N-terminus suggesting vacuolar localization. D-type EULs contain double EUL domains in tandem arrayed and connected through a variable

Figure 1: Schematic representation of the twelve types of Euonymus lectin (EUL) proteins found in Embryophyta (Fouquaert and Van Damme, 2012).

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linker sequence. Most D-type EULs are preceded by an N-terminal domain which is also variable in length. The nomenclature of the EUL lectins is based on differences in protein architecture and structure. The name of the EUL protein consists of the first three letters of the genus name and first two letters of the species name, followed by EUL and the type that represents the architecture of the EUL domain. EULs belonging to the same type are further annotated with A, B, C, etc. For example, a D1A-type EUL lectin in Oryza sativa is referred to as OrysaEULD1A. Figure 1 represents a schematic overview of the 12 different EUL types (Fouquaert et al., 2009; Fouquaert and Van Damme, 2012).

1.1.3. The EUL lectin family in Oryza sativa L. ssp. japonica The Oryza sativa L spp. japonica genome encodes five EUL genes: OsEULS2, OsEULS3, OsEULD1A, OsEULD1B and OsEULD2. On top of these five EUL genes, four pseudogenes were identified for which no expression was recorded (Fouquaert et al., 2009). The functional EUL rice genes are distributed over three chromosomes, namely chromosome 1, 3 and 7, and show a high degree of sequence similarity between the different EUL domains (De Schutter et al., 2017; Fouquaert et al., 2009). This sequence similarity between OsEUL genes is the consequence of consecutive duplication events of the ancestral S-type EUL, originating from lower plants. First there were two duplication events resulting in OsEULS2 and OsEULS3, followed by domain duplication from S-type to D-type EULs. Further duplication events resulted in different D-type EULs and a higher copy number of EULs present in the japonica rice genome. These EUL duplication events are believed to increase the resistance of rice to abiotic and biotic stresses (Al Atalah, 2014a; De Schutter et al., 2017; Fouquaert et al., 2009).

1.1.4. OrysaEUL proteins, their ligands and physiological function The 3D-structure of the EUL domains in rice consists of a b-trefoil conformation made of three bundles of b-sheets, representing subdomain I, II and III (Figure 2). Subdomain III carries one functional carbohydrate binding site domain. D-type OrysaEULs consist of two b-trefoils which are connected by a proline rich linker sequence. Each b-trefoil contains one carbohydrate binding domain, which upon folding is located at the opposite ends of the polypeptide chain. The carbohydrate binding domain is promiscuous in that it binds to a diverse range of carbohydrates (De Schutter et al., 2017; Fouquaert and Van Damme, 2012). Potential targets for EULs in general are free N-glycans, originating from de novo synthesis or N-glycoconjugate degradation, as well as glycosylated proteins. In addition, EULs are also able to bind free metabolic glycans which are present in the cytosol (Fouquaert and Van Damme, 2012).

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Recent studies suggest the carbohydrate binding site of rice EUL proteins consists of four well conserved amino acid residues at the C-terminal end of each EUL domain: Asp112, Trp134, Asn139 and Gln140. However, among rice EUL proteins there are differences in the specificity of the binding site towards carbohydrates. These difference in specificity evolved from gene divergence, resulting in amino acids changes surrounding the carbohydrate binding site. To date only two EUL lectins from rice have been characterized, OrysaEULS2 and OrysaEULD1A. OrysaEULD1A preferentially binds to galactose containing N-glycans, whereas OrysaEULS2 has a high affinity towards high mannosylated and lactosamine related N-glycan structures. Furthermore, it is shown that the specificity of OrysaEULS2 to galactose containing glycans is hindered by a protruding loop that masks the Asn139 residue in the binding site. The masking of Asn139 hinders the ability of OrysaEULS2 to interact with galactose containing ligands, contributing to the promiscuity of the EUL domain (Al Atalah et al., 2012, 2014b; De Schutter et al., 2017; Fouquaert and Van Damme, 2012). Until now, not much is known on the physiological function of OrysaEUL lectins. De Schutter et al. (2017) analyzed the unrelated and unknown N-terminal domains preceding the EUL domain and the linker sequences between EUL domains in D-type OsEUL genes from rice, in search for indications of the physiological function of OrysaEUL lectins. They found no matching protein domains that are currently known for these sequences.

Figure 2: Ribbon diagram of the b-trefoil EUL domains in Oryza sativa L. ssp. japonica. a) OrysaEULS2, b) OrysaEULS3, c) OrysaEULD1A domain 1, d) OrysaEULD1A domain 2, e) OrysaEULD1B domain 1, f) OrysaEULD1B domain 2, g) OrysaEULD2 domain 1, h) OrysaEULD2 domain 2. Bundles of b-sheets, a-helixes and loops are coloured purple, red and green. The bundles of b-sheets are numbered I, II and III (De Schutter et al., 2017).

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1.1.5. Stress inducible expression profile of OsEUL genes Since EUL proteins in rice lack a signal peptide, it is presumed they are synthesized on free ribosomes and therefore reside in cytoplasmic or nuclear compartment of the plant (Van Damme et al., 2008). Under normal growth conditions, OsEUL genes are expressed at very low and almost undetectable levels. However, when plants are exposed to environmental stresses, OsEUL gene expression is upregulated. These findings suggest an important role for these protein – carbohydrate interactions to help the plant cope with environmental stresses (Al Atalah et al., 2014a; De Schutter et al., 2017). So far, few studies have been published on the expression profile of EUL genes in rice plants submitted to several stresses. To unravel the physiological function of OrysaEUL lectins, more research is needed on stress induced OsEUL gene expression. Currently, there is ongoing research at the Lab of Prof. Van Damme (University of Ghent) into OsEUL gene expression in transgenic rice plants overexpressing a D-type OrysaEUL. Hormonal treatment OsEUL gene expression is ABA responsive according to a study conducted by Al Atalah et al. (2014a). This study shows upregulation of all EUL transcript in the roots after ABA treatment, in the shoots only OsEULDS2, OsEULD1A and OsEULD2 genes were found to be ABA responsive. De Schutter et al. (2017) found similar results when searching the Transcriptome Encyclopedia of Rice (TENOR) database. The study reports ABA induced responses for all OsEUL genes, except for a slight downregulation of the OsEULS3 gene. Furthermore, unpublished data of the Lab of Prof. Van Damme also confirm the ABA induced response of OsEUL genes in roots. However, in shoots OsEULS2 and OsEULD1A do not seem to be responsive. According to De Schutter et al. (2017) JA mainly causes downregulation for all OsEUL transcripts, except for upregulation of OsEULS2 in roots and OsEULD1B in shoots. More unpublished data from the Lab of Prof. Van Damme also suggest altered OsEUL gene expression after MeJA treatment, a precursor of the plant hormone jasmonic acid. MeJA treatment upregulates OsEULS2 gene expression in the shoot, whereas it downregulates OsEULS3 and OsEULD1B in roots and shoots and OsEULD1A and OSEULD1B in roots. None of the OsEUL genes seem to be SA responsive according to ongoing experiments at the Lab of Prof. Van Damme. Abiotic stress The response of OsEUL gene expression to salt is the most studied for OrysaEUL proteins. Several studies report OsEUL genes to be salt responsive (Al Atalah et al., 2014a; De Schutter et al., 2017; Moons et al., 1997). According to Al Atalah et al. (2014a) all OsEUL transcripts were upregulated in root tissue after NaCl treatment, in shoots OsEULS2 and OsEULS3 did not respond. These results are in contrast with searches in the TENOR database. De Schutter et al. (2017) report all OsEUL genes as salt responsive either by down- or upregulation, except

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for OsEULS2 in roots. Gene expression of salt tolerance rice variety Pokkali and the salinity sensitive rice variety IR29 show a high upregulation of OsEULD1B transcript levels and to a lower extent upregulation of OsEULD1A, suggesting these proteins play an important role in salt stress signaling (De Schutter et al. 2017; Kawasaki et al., 2001). Mannitol treatment, used to mimic drought stress, shows no altered OsEUL gene expression (Al Atalah et al., 2014a). Although a study conducted in the indica rice variety shows opposite results (Babu et al., 2002). Furthermore, experiments conducted at the Lab of Prof. Van Damme show upregulation of OsEULS2, OsEULD1B and OsEULD2 transcript levels in shoots and downregulation of OsEULD1A transcripts in roots and shoots after mannitol treatment. De Schutter et al. (2017) show initial upregulation in the roots of OsEULD1A, OsEULD1B and OsEULD2 genes whereas in the shoots all OsEUL genes are initially upregulated except for OsEULD2 which is downregulated. Biotic stress According to a study by Al Atalah et al. (2014a), OsEULD1B and OsEULD2 transcript levels are upregulated and OsEULD1A downregulated at 8 days post inoculation with the biotrophic pathogen Xanthomonas oryzae pv. oryzae. In contrast, infection of rice with the biotrophic fungi Magnaporthe oryzae led to initial downregulation of OsEULS3, OsEULD1A and OsEULD2 genes. OsEULD1A seems to be the only gene which is downregulated in the latter pathogen interactions (Al Atalah et al., 2014a). Another biotic stress assay, using the root knot nematode Meloidogyne graminicola, also led to downregulation of OsEULD1A transcript levels (Kyndt et al., 2012b). These data altogether suggest a role for OrysaEULD1A in regulating the plant’s basal defense response (Al Atalah et al., 2014a). Furthermore, increased transcript levels of OsEULD2 were observed after infection with the root rot nematode Hirschmanniella oryzae and root knot nematode Meloidogyne graminicola. OsEULD1B as well as OsEULS2 genes are downregulated after Meloidogyne graminicola attack (Kyndt et al., 2012b). An overview of OsEUL gene expression is given in Table 1. In this overview, recent studies were used to summarize EUL gene expression in rice upon treatment with hormones and the application with abiotic and biotic stresses (Al Atalah et al., 2014; De Schutter et al., 2017; Kyndt et al., 2012b). Results from the Lab of Prof. Van Damme are not showed in this Table since this data is unpublished for now.

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Table 1: Overview of OsEUL gene expression following hormonal, abiotic and biotic stress treatment (Al Atalah et al., 2014; De Schutter et al., 2017; Kyndt et al., 2012b).

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1.2. Introduction to rice immunity Plants are sessile organisms that are continuously subjected to a plethora of dangers and therefore developed sophisticated surveillance mechanisms to protect themselves against various stresses. These surveillance systems recognize potential dangers and respond quickly before there is significant damage to the plant. The recognition of danger induces basal resistance mechanisms, also referred to as the innate immune system. It is the first line of defense when a plant is under stress. Basal defenses may trigger a secondary immune response in uninfected tissues, referred to as systemic immunity. Many of these immune responses are mediated by cross- communicating hormones such as salicylic acid (SA), jasmonic acid (JA) and ethylene (ET). These hormones play an important role in defense related signal-transduction pathways (Freeman and Beattie, 2008; De Vleesschauwer et al., 2013; Yang et al., 2015).

1.2.1. Innate immunity The innate immune system of plants consists of a multi layered defense response. The first layer is based on the recognition of pathogen-associated molecular patterns (PAMPs). PAMPs such as flagellin, chitin and lipopolysaccharides (LPS) are conserved microbial signatures and essential for pathogen survival. Plants are also capable of recognizing damage to oneself. These products of wounding are referred to as damage-associated patterns (DAMPs). PAMPs and DAMPs are recognized by pattern recognition receptors (PRRs) located at the plasma membrane, leading to an immune response called PAMP-triggered immunity (PTI) (Lotze et al., 2007; Saijo et al., 2018; Wu and Zhou, 2013). PRRs are transmembrane receptor-like kinases (RLKs) or proteins (RLPs) that survey the apoplast for molecular patterns. They typically consist of an extracellular domain for perceiving molecules and an intracellular serine/threonine kinase domain, which is replaced by a short non-coding region in RLPs. Because RLPs lack a cytoplasmic kinase domain for downstream signaling, they recruit proteins containing a kinase domain. RLKs and RLPs are divided into subfamilies according to their ligand binding extracellular domain, which include leucine rich repeat (LRR), lysin motif (LysM), lectin and epidermal growth factor-like (EGF) domains (Macho and Zipfel, 2014; Saijo et al., 2018; Yu et al., 2017). Instantaneously after the perception of PAMPs, PRRs recruit their coreceptor to form a PRR complex. The coreceptor is a regulatory receptor kinase which seems to be specific for the type of extracellular domain of the PRR (Couto and Zipfel, 2016; Noman et al., 2019). The rice genome contains more than 1,131 RLK and 90 RLP genes that might be involved in cellular signaling (Liu et al., 2014). So far, only a few PRRs from rice have been studied (Figure 3). For example, chitin elicitor binding protein (CEBiP), LYP4/LYP6 and XA21. CEBiP is an

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RLP that perceives chitin. It contains a transmembrane domain and two extracellular LysM motifs. CeBiP lacks a cytoplasmic kinase domain and therefore recruits chitin elicitor receptor kinase 1 (CERK1) as coreceptor for intracellular signaling. LYP4/LYP6 also contains LysM domains that bind chitin as well as peptidoglycan. Xa21 is an LRR RLK that confers broad resistance against diverse strains of Xanthomonas oryzae pv. oryzae (Xoo) by binding to the Xoo derived RaxX peptide. The coreceptor of Xa21 for intercellular signaling is somatic

embryogenesis receptor kinase 2 (SERK2). In contrast to CERK1, SERK 2 is constitutively associated with Xa21. (Couto and Zipfel, 2016; Kawano and Shimamoto, 2013; Liu and Wang, 2016). Once PRRs bind to their coreceptor, the PRR complex initiates a branched signaling cascade to activate local and systemic defense responses. Within minutes there is an influx of Ca2+ and H+ and an efflux of K+ and Cl- at the plasma membrane, which leads to plasma membrane depolarization and extracellular alkalization (Yu et al., 2017). In the apoplast there is a burst of reactive oxygen species (ROS), which acts

as a toxic barrier against pathogen invasion. The production of ROS requires the NADPH oxidase respiratory burst oxidase homolog protein D (RBOHD) that is regulated by

phosphorylated receptor-like cytoplasmic kinases (RLCKs) and calcium-dependent protein kinases (CDPKs) (Kadota et al., 2015). RLCKs associate with the intracellular kinase domain of the PRR complexes. Upon PAMP recognition,

RLCKs get activated by the PRR complex, dissociate from the complex and initiate a phosphorylation cascade of mitogen-activated protein kinases (MAPKs) (Macho and Zipfel, 2014; Yu et al., 2017). MAPK cascades are evolutionarily conserved, intracellular signaling modules and minimally consist of three kinases: a MAPK, a MAPK kinase (MAPKK) and a MAPKK kinase (MAPKKK) (Rohila and Yang, 2007; Yu et al., 2017). MAPKs and CDPKs can phosphorylate each other and transcription factors such as the WRKY family (Li et al., 2016). Transcription factors translocate the PTI signal to the nucleus, where they activate pathogenesis related (PR) gene expression and immune responses such as lignification, callose deposition, stomatal closure, production of phytohormones and phytoalexins. These immune

Figure 3: Pattern recognition receptor (PRR) signaling in rice. The PPRs chitin elicitor binding protein (CEBiP), LYP4/LYP6 and Xa21 and their coreceptors chitin elicitor receptor kinase 1 (CERK1) and somatic embryogenesis receptor kinase 2 (SERK2). The PRR complex initiates intracellular signaling through receptor-like cytoplasmic kinases (RLCK). (Couto and Zipfel, 2016).

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responses altogether lead to the establishment of PTI, which successfully restricts further colonization of most invading pathogens (Figure 4) (Hammond-Kosack and Jones, 1996; Saijo et al., 2018; Yu et al., 2017).

Figure 4: A schematic overview of pathogen associated molecular patterns (PAMP) triggered immunity

(PTI) (Saijo et al., 2017).

Successful pathogens are able to suppress PTI immunity by secreting virulence effectors into the cytoplasm, which leads to effector triggered susceptibility (ETS). In turn, plants have developed a second line of defense referred to as effector triggered immunity (ETI) (Jones and Dangl, 2006; Cook et al., 2015). ETI is activated upon recognition of highly variable effectors, also termed avirulence (Avr) proteins. Effectors are recognized by cytoplasmic immune receptors, encoded by disease resistance (R) genes. Most of these immune receptors belong to the nucleotide binding domain and leucine rich repeat (NB-LRR) family, although several atypical R proteins containing a variety of conserved protein domains are also identified (Liu and Wang, 2016). Carboxyl terminal LRRs are adaptable structural domains, specialized in protein-protein interactions. They are under diversifying selection and can evolve very different binding specificities. The central NB domain is predicted to hydrolyze ATP, necessary for ETI signal activation (Dodds and Rathjen, 2010; Noman et al., 2019). Perception of effectors by NB-LRR occurs through direct binding or by sensing the activity of an effector on nearby cell components, also known as the guard model (Figure 5). This guard model implies that crucial immune components can be guarded by NB-LRR receptors and become active when their guardee is modified by an effector. Furthermore, NB-LRRs can also guard structural mimics (or decoy’s) of a key immune component or use an accessory bait protein to facilitate binding with the effector (Dodds and Rathjen, 2010; Noman et al., 2019). According to this model, one NB-LRR in association with a guardee perceives many effectors who can alter this guardee. This abolishes the need for one R gene for each effector and broadens the plant immune

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resistance (Noman et al., 2019). It is important to note that not all effectors help to suppress PTI. Some effectors are transcription factors that manipulate plant gene expression, for example to establish feeding structures (Dodds and Rathjen, 2010). ETI activation results in similar responses as PTI but vary in magnitude. ETI responses include Ca2+ influx, secondary ROS burst, MAPK cascades, callose depositions, lignification, transcriptional reprogramming and a hypersensitivity response (HR), leading to programmed cell death of infected cells. ETI may also activate a secondary immune response in distal uninfected tissue, referred to as systemic acquired resistance (SAR) (see section 1.2.2.) (Dodds and Rathjen, 2010; Jones and Dangl, 2006). Recognition and evasion of immune receptors and PAMPS/effectors drive an evolutionary arms race and decide the compatibility of plant – pathogen interactions. The outcome of this highly coordinated PTI and ETI signaling responses ultimately determine the plant susceptibility/resistance towards invading pathogens (Cook et al., 2015).

1.2.2. Hormones and rice immunity Following PTI and ETI activation, there is an induced and coordinated expression of phytohormones which help the plant to cope with pathogen attack. Phytohormones are small molecules which are known to regulate various essential processes such as growth, development and plant defense. This interconnected and complex network of cross communicating hormones allows the plant to save energy upon pathogen attack. Hormones otherwise involved in growth and development processes are now targeted to induce a quick defense response to help the plant cope with its attacker. The classical hormones involved in plant defense are salicylic acid (SA), jasmonic acid (JA), ethylene (ET), abscisic acid (ABA), gibberellin (GA), auxin (AUX), cytokinin (CK) and brassinosteroids (BR) (De Vleesschauwer et al., 2013; Pieterse et al., 2012; Yang et al., 2015). To date, most of the knowledge on hormone biosynthesis and signaling is based on the dicot model plant

Figure 5: Model of direct and indirect recognition of effectors (green) by plant nucleotide binding (orange) – leucine rich repeat (blue) (NB-LRR) receptors in effector triggerd immunity. a) direct recognition: effector binds directly to the receptor b) In the guard/decoy model the effector modifies an accessory protein (red), which may be an effector target (guardee) or a structural mimic (decoy) of the target. The modified accessory protein is recognized by the NB-LRR receptor. c) In the bait model, interaction of the effector facilitates the direct binding of the effector (Dodds and Rathjen, 2010)

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Arabidopsis. Much less is currently known on the exact molecular mechanisms of hormone signaling upon pathogen attack in rice, although lately much effort is being made to elucidate the role of phytohormones in rice defense. In this section, we highlight the biosynthesis and signaling pathways of some rice phytohormones which are important for the experiment in this thesis: JA, ET and ABA.

Jasmonic acid

JA is an oxylipin hormone derived from a-linolenic acid, a C18 poly unsaturated fatty acid in the plant’s plasma membrane, via the octadecanoid biosynthetic pathway (Figure 6). After biosynthesis, JA can be further metabolized into methyl-jasmonate (MeJA) or conjugated

with different amino acids such as Ja-Ile, JA-Val and Ja-Phe. JA-Ile is the biologically active form of JA since it can activate genes that are suppressed by jasmonate-ZIM domains (JAZs). JAZ proteins suppress JA signaling by binding to JA responsive TF such as MYC and EIN3. When JA-Ile levels in the cell rise, JA-Ile binds to the F-box protein corona insensitive 1 (COI1) which is part of the E3 ubiquitin-ligase SCFCOI1 complex. After binding of JA-Ile to COI1, COI1 binds to the JAZ protein marking it for proteasomal degradation. Finally, degradation of JAZ proteins activates JA responsive gene expression by activation of MYC and EIN3 TFs (Pauwels and Goossens, 2011; Pieterse et al., 2012; Lyons et al., 2013). Treating rice plants with JA induces PR gene expression such as OsPR1a, OsPR1b, OsPR2 and OsPR5, suggesting an important role for JA in rice defense (Agrawal et al., 2000, 2001; Rakwal and Komatsu, 2000). Furthermore, overexpression lines of OsAOS2, allene oxide

Figure 6: The jasmonic acid biosynthesis pathway in plants (Pieterse et al., 2012).

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synthase 2 a key enzyme in JA biosynthesis pathway, upregulated endogenous JA levels, PR gene expression and increased resistance to fungal infection (Mei et al., 2006). JA also induces TFs in response to pathogen attack, such as WRKY, NAC and JAMYB TFs (Lee end Yang, 2003; Lyons et al., 2013; Uji et al., 2016). According to the classical defense model in dicots, JA is predominantly induced as defense response upon necrotrophic attack. In rice however, JA does not seem to favor pathogens with a certain lifestyle. Several studies report the JA-induced resistance against a variety of pathogens, ranging from biotrophs to necrotrophs, suggesting JA might play a role as an endogenous priming agent in rice (De Vleesschauwer et al., 2013; Riemann et al., 2013; Taheri and Tarighi, 2010; Tamaoki et al., 2013; Uji et al., 2016; Yamada et al., 2012).

Ethylene

Ethylene is a gaseous molecule which is involved in many developmental processes such as fruit ripening, germination and programmed cell death upon pathogen attack. The precursor of ethylene is the amino acid methionine. Methionine is converted into S-adenosyl-methionine (SAM) by SAM synthase. SAM is metabolized into 1-aminocyclopropane-1-carboxylic acid (ACC) by ACC synthase (ACS), which is the rate limiting step. ACC synthase levels are controlled not only at the transcriptional level but also at the translational level. This enables a quick accumulation of ethylene upon pathogen attack. 5’-methylthioadenosine is a by-product of ACS and is converted back into methionine via the Yang cycle. ACC is further metabolized into ethylene by ACC oxidase (Figure 7) (Argueso et al., 2007; Iwai et al., 2006; Rzewuski and Sauter, 2008).

Ethylene signaling starts with ethylene perception by receptor kinases, ethylene receptors (ETR) and ethylene response sensors (ERS), which are localized in the membrane of the ER. The ET receptors are active in the absence of ET and activate constitutive triple response 1

Figure 7: Schematic overview of ethylene biosynthesis. Ethylene is synthesized from methionine through the intermediates S-adenosyl methionine (SAM) and the cyclic amino acid 1-aminocyclopropane-1-carboxylic acid (ACC). The enzyme converting methionine to SAM is SAM synthetase, ACC synthase converts SAM to ACC, and ACC is oxidized to ethylene by ACC oxidase (Hegelund et al., 2017).

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(CTR1), a negative regulator of ET signaling. CTR1 phosphorylates ethylene insensitive 2 (EIN2) and marks it for degradation. Upon ethylene perception by ETR and ERS, CTR1 is inactivated and EIN2 is no longer degraded. EIN2 is now activated and translocates from the ER to the nucleus to activate EIN3 and EIL1 (EIN3-like 1). EIN3 and EIL1 are master TFs and regulate ethylene response factor (ERF) genes, which in turn activate a variety of pathogenesis related genes such as chitinase and phytoalexins (Ma et al., 2009; Jun et al., 2004; Rzewuski and Sauter, 2008; Yang et al., 2015; Yang et al., 2017). Several studies have been conducted on the role of ethylene in rice immunity (Iwai et al., 2006; Seo et al., 2011; De Vleesschauwer et al., 2014). In contrast to dicots where ET is mainly expressed upon necrotrophic attack, ET expression in rice independently of the pathogen’s lifestyle and can act as a positive or a negative regulator of rice immunity response (van Loon et al., 2006, Yang et al., 2013). For example, rice plants overexpressing OsACS2 exhibit strong disease resistance to M. oryzae and Rhizoctonia solani, which are a hemi-biotroph and necrotroph, respectively (Helliwell et al., 2013). Another example is the high levels of ET in rice which confer a higher susceptibility for X. oryzae pv. oryzae (Schen et al., 2011).

Abscisic acid

ABA is an important phytohormone that plays diverse roles in developmental and physiological processes and is differentially expressed during abiotic stresses such as high salinity, drought and cold. Lately, more and more studies suggest an additional role for ABA in rice’s immune response (Cutler et al., 2010; De Vleesschauwer et al., 2013; Ton et al., 2009; Yang et al., 2013). ABA is synthesized in plastids and derived from C40-carotenoids such as 9-cis-violaxanthin and 9-cis-neoxanthin, via oxidative cleavage by 9-cis-epoxycarotenoid dioxygenase (NCED). This oxidative cleavage results in xanthoxin, a C15 intermediate. Xanthoxin is translocated to the cytosol and further metabolized into ABA through a two-step reaction via ABA-aldehyde. NCED is a key enzyme to the ABA biosynthesis and catalyzes the regulating step in this pathway (Nambara and Marion-Poll, 2005; Xiong and Zhu, 2003; Ye et al., 2012; Zhang, 2014). Currently not much is known for ABA induced PR gene expression, although many studies suggest an important role in plant defense for this hormone. For instance, it has been shown that ABA plays a role in the closure of stomata upon early perception of bacterial leaf pathogens (Lim et al., 2015). Another study by Melotto et al. (2006) reports ABA deficient aba3-1 mutants fail to quickly induce stomatal closure upon PAMP perception, suggesting a putative role for ABA in innate immunity. However, most pathogens found a way to circumvent the ABA induced stomatal closure by secreting effectors that can reopen the stomata. ABA is also reported to induce callose deposition early upon fungal attack, although for bacterial infections callose deposition is inhibited by ABA (de Torres-Zabala et al., 2007; Flors et al., 2008; Kaliff et al, 2007; Ton and Mauch-Mani, 2004). Other studies report the inhibition of ROS and

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synergetic cross talk with JA (Asselbergh et al., 2008). Furthermore, De Vleesschauwer et al. (2010) show that ABA interacts antagonistically with ET, suppressing rice defenses against the necrotroph C. miyabeanus. On the other hand, SA is suppressed by ABA upon infection with M. oryzae and Xoo. Recently, it was shown that M. oryzae produces its own ABA in vitro and in planta, which is most likely used by the pathogen to suppress ET and SA defense responses in rice (Jiang et al., 2010; Takatsuji and Jang, 2014). Like ET, the role of ABA in rice’s defenses seems to be pathogen specific (De Vleesschauwer et al., 2014; Kyndt et al., 2017; Ton et al., 2009). Although according to Ton et al. (2009), the role of ABA mostly depends on the timing and the invasion strategy of the pathogen instead of pathogen’s lifestyle although more research is needed to confirm this assumption (Figure 8).

1.2.3. Systemic immunity In addition to local immune responses, plants developed a second type of immunity which acts in cells distant from the site of infection and is referred to as systemic immunity. In this section, two types of systemic immunity will be discussed: system acquired resistance (SAR) and induced systemic resistance (ISR). SAR is induced upon pathogen attack in distant non-infected tissue and confers long lasting resistance against a broad range of pathogens. In dicots, SAR requires the hormone signaling molecule SA (Durrant et al., 2004; Ryals et al., 1996). SA is metabolized into methyl-SA in infected cells and transported to distant tissue where it is converted back into SA to induce PR gene expression (Fu and Dong, 2013; Klessig, 2012). The expression of PR genes such as PR1a,

Figure 8: The ambiguous role of ABA during the different phases of the plant’s defense response. The positive or negative contribution of ABA depends on timing and the invasion strategy of the pathogen. Green arrows represent activation, red perpendicular lines indicate inhibition. Phase I = early pre-invasive response, Phase II = post-invasive response, Phase III = late response (Ton et al., 2009).

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chitinase and b-1,3-glucanase primes the plant for secondary pathogen attack (Fu and Dong, 2013; Van loon, 1997). SAR is not only induced upon pathogen attack, non-pathogens also have the ability to evoke SAR. In rice however, it has been suggested that JA would be an important inducer of SAR instead of SA. Transgenic OsAOS2 lines under a pathogen inducible promotor as well as exogenous treatment of JA in rice induced systemic PR gene expression, including OsPR1a and OsPR1b which are known to be SAR marker genes (Mei et al., 2016; Liu et al., 2014). Although OsPR1b is generally seen as a marker gene for JA dependent defense responses, it is also induced by SA, ET and ABA. The same pattern is observed for OsPR1a although both PR genes differ in timing and intensity depending on the (combined) hormonal treatment regulating (Agrawal et al., 2000, 2001; Luan and Zhou, 2015). ISR is another state of systemic immunity that is associated with priming of plant cells. Priming is an enhanced ability to fight off pathogen attack by a stronger activation of defense responses (Jung et al., 2012). ISR differentiates from SAR based on the inducer and the involved signaling pathways. ISR is induced by plant growth promoting rhizobacteria and fungi and unlike SAR, ISR does not lead to the accumulation of SA and PR genes in systemic tissue. Instead, ISR relies on an increased sensitivity to JA and ET by upregulating signaling proteins and TFs involved in JA and ET signaling (Choudhary et al., 2007; Pieterse et al., 2014; Vallad and Goodman, 2004). Treatment of plants with chemicals plants including vitamins, amino acids, free radicals, benzothiadiazole, glycerol-3-phosphate and azelaic acid has also been reported to induce immunity responses in rice and some of them have been shown to translocate systemically (Bahuguna et al., 2012; Kadotani et al., 2016; Schweizer et al., 1999; Shine et al., 2018).

1.3. Biotic stress in rice: Meloidogyne graminicola infection Stress inducible EUL lectins are known to be upregulated upon biotic stress (Al Atalah et al., 2014a; Kyndt et al., 2012b). In this study, Meloidogyne graminicola (Mg) will be used as biotic stress factor in rice.

1.3.1. The host plant - rice Oryza sativa is one of the most important major food crops in the world and a staple food for more than 3.5 billion people worldwide, especially in developing countries. In Asia, where 90 % of the rice is cultivated, more than 50 % of the daily calorie intake depends on rice for about 520 million people living in poverty. Not only in Asia, but also in Africa and Latin America, rice production and consumption are becoming more important both for local and global food security (Khush, 2005; Seck et al., 2012; Muthayya et al., 2014). It is estimated that an

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additional 116 million tons of rice will be needed by the year 2035 to feed growing populations worldwide (Seck et al., 2012). In sub-Saharan Africa particularly, the consumption of rice per capita has increased by more than 50 % in the past two decades. This upward trend in rice consumption will continue as more people become wealthier and their preference for rice as staple food rises (Mohanty, 2013). To meet the increased consumption of rice, intensive research is needed to produce high yield varieties that are resistant to abiotic and biotic stresses.

1.3.2. Life cycle of Meloidogyne graminicola Rice is susceptible to an array of abiotic and biotic stresses, of which root-knot nematodes are an important threat. One of the most important root-knot nematodes associated with rice is Mg (Jain et al., 2012; Mantelin et al., 2017). Infection of rice with Mg causes extensive damage to plant growth and yield losses up to 70%, particularly under water stress. Infected plants show hook-like galls in the roots, resulting in yellowing, stunting, reduction of tillering, delayed maturation and root proliferation. (Bridge et al., 2005; Cabasan et al., 2014; Kyndt et al., 2014). Mg is an obligate sedentary biotroph and has a relatively fast life cycle on rice, in comparison with other Meloidogyne species. They complete their life cycle in 19-27 days at 22-29 °C, depending mostly on soil temperature and water regime (Dutta et al., 2012; Fernandez et al.,

2014). Motile infective second stage juveniles (J2) are found in soil samples and locate the host roots by chemotaxis (Reynolds et al., 2010). Before entering the host roots, free living pre-parasitic J2s cannot feed and are dependent on their lipid reserves, established during embryonic development (Mantelin et al., 2017). J2s usually enter the plant at the root elongation zone. Subsequently, parasitic J2s migrate intercellularly in the root cortex downwards the apex and invade the young vascular cylinder moving upwards, thus bypassing the endodermis (Figure 9) (Kyndt et al., 2014; Williamson and Gleason, 2003). Once in the vascular tissue, J2s become sedentary and initiate giant feeding cells by secreting several compounds into the root cells by using a syringe like stylet. These secretions, called effectors, interfere with the host plant basal immunity and manipulate plant cell development by differentiating parenchymatic cells into giant cells (Gheysen and Mitchum, 2011; Kyndt et al., 2013). Five

to eight giant cells are formed by repeated rounds of nuclear division and cell growth in the absence of cytokinesis. This process leads to the development of multinuclear, hypertrophic

Figure 9: Infection strategy of Meloidogyne graminicola (Kyndt et al., 2014).

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and metabolically hyperactive, giant feeding cells that are up to 100 times the size of normal root vascular parenchyma cells. Cells of the pericycle surrounding the giant cells undergo hyperplasy and cause the formation of typical hook-like galls or root knots (Jaouannet et al., 2012; Kyndt et al., 2013; Cabasan et al., 2014). Once giant cells are established, J2s start feeding on them and molt to J3 and J4 juvenile stages followed by the adult stage (Figure 10). Adult females have a pear-like shape with an elongated neck and remain sedentary in the roots for their entire life cycle, protected from the environment. At the end of the life cycle, eggs are mainly laid in the root cortex in a gelatinous matrix. J1s molt to J2s inside the egg and hatch into the rhizosphere. J2s can also hatch inside the cortex and re-infect the same root by migrating intercellularly to the young vascular cylinder to establish new feeding sites. In this way, Mg can continuously reproduce inside the roots as an adaptation to flooded conditions (Abad and Williamson, 2010; Jain et al., 2012; Kyndt et al., 2014). The sex of Mg is determined by environmental conditions, more males are formed in crowded or poor nutritional conditions. Males have a filiform shape and are motile after the third molt. Amphimixis occurs when a male is in contact with a female, however mitotic parthenogenesis is encountered more often (Mantelin et al., 2017; Triantaphyllou, 1973).

1.3.3. Effectors of Meloidogyne graminicola During infection Mg secretes up to 500 proteins, so called effectors, into the host plant which are involved in processes such as establishment and maintenance of the feeding site, suppression of plant’s defense responses and intracellular migration (Haegeman et al., 2013). Effectors are mainly secreted from esophageal glands – a dorsal one and two subventral – and injected into the cytoplasm by the stylet. Effectors targeted to the apoplast are mostly cell wall degrading enzymes or have the ability to interact with receptors in the extracellular compartment. In the cytoplasm, effectors can interact with proteins or are relocated to other cell compartments such as the nucleus. Cytoplasmic effectors are mainly targeted for suppression of immunity and reprogramming of the cell to develop high metabolically active feeding structures (Abad and Williamson, 2010; Haegeman et al., 2012; Jaouannet and Rosso, 2013).

A B C D E

Figure 10: Life cycle of Meloidogyne graminicola: A: second stage juvenile in root tip, B: third stage juvenile, C: fourth stage juvenile, D: adult female, E: egg mass in gelatinous matrix (Dutta et al., 2012).

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In the last few years, quite a few effectors from Mg such as MgMO237, Mg16820, MgGGP and Mg01965 have been identified with the ability to suppress host defenses (Chen et al., 2017, 2018; Haegeman et al., 2013; Naalden et al., 2018; Petitot et al., 2016; Zhuo et al., 2019). For example, Mg16820 is secreted both in the apoplast and the cytoplasm of giant cells and has the capability to influence PTI as well as ETI by suppressing ROS signaling (Naalden et al., 2018). Recently, the newly discovered effector MgGGP was reported to recruit the post-translational machinery in rice. After secretion into the apoplast, MgGGP is targeted to the ER for post-translational modification via N-glycosylation and C-terminal proteolysis, followed by translocation to the nucleus. Only after N-glycosylation and proteolysis, MgGGP receives the ability of regulating host immunity by suppressing HR mediated cell death (Chen et al., 2017). Interestingly, a novel effector Mg01965 was recently identified belonging to the family of C-type lectins. Mg01965 accumulates in the apoplast where it can interact with free sugars and glycosylated structures. Since sugar signaling has been shown to contribute to plant immunity, it is suggested Mg01965 targets apoplastic carbohydrates to suppress defense responses (Bolouri Moghaddam et al., 2012; Zhuo et al., 2019). However, for most effectors the mode of action in suppressing plant immunity remains still unclear and more research is needed to unravel potential targets of Mg effectors.

1.3.4. Hormone homeostasis in rice roots after Meloidogyne graminicola infection

Inducible defense responses in plants are mainly regulated by hormones, making them a target for pathogens to antagonize host immunity (De Vleesschauwer et al., 2013; Pieterse et al., 2012). In this study we focus on hormones JA, ET and ABA and their interaction in regulating Mg attack in rice roots. Emphasis will be made on host hormonal responses to Mg infection in systemic root tissue although not many studies have been conducted on this subject to date. Increasing evidence is showing that JA and ET fulfill a critical role in the Mg – rice interaction. Early upon infection with Mg, the JA biosynthesis and signaling pathway is activated in systemic root tissue. OsJMT1, a jasmonate methyl transferase, is also upregulated in systemic roots. This enzyme converts JA into MeJA which acts as a mobile JA signal, priming systemic tissues and nearby plants for pathogen attack. By 7 dpi, OsJMT1 and OsJAMYB are downregulated. MeJA is known to be a strong inducer of systemic defenses in rice and therefore its biosynthesis is possibly downregulated by Mg (Kyndt et al., 2012a; Nahar et al., 2011). In young galls, there seems to be a discrepancy in JA biosynthesis related gene expression while JA signaling is initially upregulated. By day 7 however, JA defense responses are suppressed not only in young galls but also in giant cells indicating active suppression by Mg in infected and neighboring tissue (Ji et al., 2013; Kumari et al., 2016; Kyndt et al., 2012a, 2017; Nguyen et al., 2014). Early upon infection, the ET pathway in downregulated in systemic tissue and

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young galls. In systemic tissue, ET signaling is shown to modulate JA defense responses which suggests Mg might be interfering with host immunity by downregulating ET (Kyndt et al., 2012a, 2012b; Nahar et al., 2011). Foliar application of JA and ET as well as overexpression of JA and ET biosynthesis marker genes showed a lower susceptibility towards Mg. Furthermore, hebiba mutants, impaired in JA biosynthesis, and ET-insensitive mutants were more susceptible to Mg (Nahar et al., 2011; Kyndt et al. 2017; Zhan et al., 2018). A study conducted by Kumari et al. (2016) compared susceptible and resistant cultivars of rice. Results showed a constant upregulation of JA and ET biosynthesis and signaling pathways in infected root tips of the resistant cultivar compared to downregulation at 6 dpi in the susceptible cultivar. Although ABA is known to be an important regulator in drought resistance, it has been found that ABA is also able to regulate host immunity by interacting with other hormones. In the early stages of infection, ABA biosynthesis and signaling genes are downregulated in systemic root tissue whereas galls and giant cells show an upregulation. Hormone measurements also show accumulation of ABA in galls and foliar application of ABA as well as abamine, an inhibitor of ABA biosynthesis, enhances the susceptibility of rice towards Mg infection suggesting a complex role for ABA in rice immune responses. In giant cells, most upregulated genes are involved in the carotene and lycopene biosynthesis whereas genes further downstream of ABA biosynthesis are suppressed. Moreover, genes involved in ABA catabolism are upregulated in giant cells. These findings indicate that chlorophyll and carotene accumulate in giant cells rather than ABA. Carotenoids are not only an essential nutrient source for Mg, they also help the plant to cope with oxidative stress (Ji et al., 2013, 2015; Kyndt et al., 2017). Recently Kyndt et al. (2017) suggested an antagonistic interaction between JA and ABA. The study showed that foliar application of abamine, an inhibitor of ABA biosynthesis, led to increased JA levels in the roots whereas foliar application of ABA led to JA suppression. Moreover, the number of galls per root system were also lower after JA application and higher upon ABA treatment compared to control plants. Application of both ABA and JA showed an increase in gall formation although not significantly different from control plants. These findings suggest that ABA can overcome JA induced defense responses towards Mg infection. The role of ABA seems to be complex and further research is needed on this topic to unravel the contribution of ABA to the Mg – rice interaction Figure 11 shows an overview of the interaction between systemic immunity in rice roots, Mg and ABA and its carotenoid precursor.

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Figure 11: Overview of the interaction between systemic immunity in rice roots, Meloidogyne graminicola and ABA and its carotenoid precursor. Arrows indicate activation, perpendicular lines represent inhibition and dotted lines are putative interactions for which it is not proved to be influenced by Meloidogyne graminicola (adjusted from Ji et al., 2013, 2015; Kyndt et al., 2017).

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2. Materials and methods

2.1. Plant material and growth conditions Rice (Oryza sativa L. ssp. japonica cv. Nipponbare) genotypes used in this work include wild type (WT) control plants, transgenic empty vector control plants and transgenic plants overexpressing a D-type OrysaEUL. Wild type Nipponbare seeds were obtained from Dr. Fabio Fornara, University of Milan, Department of Biosciences, Italy. Transgenic rice seeds were provided by the Lab of Prof. Van Damme at Ghent University and include overexpression lines: OrysaEULD1A, line D (D1A-D) and line F (D1A-F), OrysaEULD2, line B (D2-B) and C (D2-C) and OrysaEULD1B line D (D1B-D). A transgenic empty vector line G (EV-G) was included in this experiment to study the influence of vector insertion on rice physiology. Transgenic OrysaEUL overexpression lines originate from the T2 generation whereas empty vector plants are from the T3 generation. Rice seeds were dehusked followed by surface sterilization. Surface sterilization was performed by hand shaking the seeds for five minutes in 40 mL 70% ethanol, followed by shaking at 150 rpm for 45 minutes in 40 mL sodium hypochlorite (< 5%) with a drop of Tween 20. To remove the remaining ethanol, bleach and Tween 20, seeds were washed thoroughly with autoclaved dH2O for multiple times and shaken overnight in fresh autoclaved dH2O at 150 rpm for synchronization. After surface sterilization, seeds were germinated on 4.4 g/L Murashige and Skoog (MS) basal salt medium with modified vitamins (Duchefa) complemented with 30 g/L sucrose (Duchefa) and 8 g/L agarose SPI (Duchefa). Before autoclaving the medium, the pH was adjusted to pH 5.8 using concentrated KOH. After autoclavation, 112 mg/L vitamin B5 (Duchefa) was added to the medium and in case of transgenic lines, 4 mg /L phosphinothricin as a selection marker. Plates were wrapped in aluminum foil and placed in an incubator at 28°C under a 16h/8h photoperiod and a relative humidity of 70 to 75% for 3 to 5 days. After germination, similar sized seedlings from each line were transplanted to polyvinyl chloride (PVC) tubes containing a mixture of fine sand and absorbent polymer (SAP) as a substrate (Reversat et al., 1999). The SAP tubes, each containing two rice seedlings, were put in boxes and further grown at 28°C under a 16h/8h photoperiod and a relative humidity of 70 to 75%. Each SAP tube was fertilized twice a week with 15 mL of Hoagland nutrient solution and once a week with 15 mL of tap water. The Hoagland nutrient solution was slightly modified from Hoagland and Arnon (1950), see Table 2.

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Table 2: Recipe for Hoagland nutrient solution for rice plants, modified from Hoagland and Arnon (1950).

Hoagland nutrient solution

StockNo Components Concentration mL stock per liter solution

H1 KNO3 2.5 M 2 mL

H2 KH2PO4 0.5 M 2 mL

H3 Ca(NO3)2.4H2O 2.5 M 2 mL

H4 MgSO4.7H2O 1 M 2 mL

H5 FeSO4.7H20 6.95 g/L

2 mL EDTA-Na2.2H2O 9.31 g/L

Micronutrients

H6

H3BO3 0.85 g/L

3 mL

MnSO4.H2O 0.84 g/L

ZnSO4.7H2O 44 Mg/L

(NH4)6Mo7O24.4H20 18.4 Mg/L

CuSO4.5H20 39.4 Mg/L

2.2. Meloidogyne graminicola culture and extraction Mg was originally isolated from the Philippines and kindly provided by the Nematode Research Group of Prof. Tina Kyndt (Ghent University). The cultures were maintained on susceptible grasses (Echinochloa crus-galli) grown in potting soil, under growth conditions as described above. For Mg extraction, roots of infected grasses were cut into small pieces and spread on a mesh sieve with pore size > 200 µm. The sieve was put in a tray and tap water was poured into the tray until the water touched the roots inside the sieve. Infective second stage juveniles (J2s) hatch from the eggs and migrate into the water. After approximately 48h, the nematode suspension was collected and run through a 20 µm mesh sieve to concentrate the J2 concentration. For an estimation of the J2 concentration in the nematode suspension, ten droplets of 10 – 20 µL were put under a Leica S8APO microscope and the numbers of J2s/droplet were determined and extrapolated to the total volume of the J2 containing solution.

2.3. Meloidogyne graminicola infection assay Fifteen-day-old rice plants were infected with approximately 350 infective J2s per plant. At 15 days post inoculation (dpi), 10 plants from each genotype were harvested and shoot length, root

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length and root weight were recorded for phenotypic analysis. To visualize the nematodes, infected roots were stained by boiling for three minutes in a solution containing 0.39% (w/v) acid fuchsin and 25% (v/v) acetic acid. After boiling, roots were washed with running tap water and destained in acidified glycerol (300 µL concentrated HCL/100 mL 100% glycerol). After 5-7 days of destaining, roots were ready for observation with a Leica S8APO microscope equipped with a Leica DFC400 camera. The number of nematodes and their developmental stages were recorded per plant, as well as the number of galls. The experiment was repeated twice independently.

2.4. RNA extraction, DNAse I treatment and cDNA synthesis Twenty-day-old rice plants from each genotype were infected with approximately 500 J2s per plant or mock inoculated with autoclaved dH2O. At 2 days and 4 days post inoculation, five plants from each genotype and each treatment were harvested. Immediately after harvesting, shoot and root were cut and frozen separately in liquid nitrogen. Frozen shoot and root samples were crushed into fine powder using liquid nitrogen and a mortar and pestle. After crushing, root and shoot samples were frozen at -80°C for future analysis. After finalizing both biological replicates, total shoot and root RNA from each plant was extracted using SpectrumTM Plant Total RNA Kit (Sigma-Aldrich), following manufacturer’s instructions. The extracted RNA was treated with RNAse-free DNAse I (Thermo Fisher), to remove contaminating DNA. Total RNA concentration and purity were measured with NanoDrop 2000 spectrophotometer (Thermo Fisher) and analyzed for degradation on a 1.5% agarose gel. Afterwards, reverse transcription was performed with Maxima First Strand cDNA Synthesis Kit (Thermo Fisher) using 0.5 µg RNA and the following PCR conditions: 10 min at 25oC, 20 min at 55oC and 5 min at 85oC. Finally, cDNA samples were diluted 5 times and used as a template for RT-qPCR.

2.5. Primer design and Real Time Quantitative RT-PCR Most primers were readily available in the lab, others were found in Nahar et al. (2011) and checked for specificity by performing a qRT-PCR on cDNA library from Nipponbare rice. Primer pairs with suboptimal specificity were redesigned by using Primer 3 software and ordered from Sigma, Belgium. After the specificity test, each of the primer PCR products was cloned into a pJET 1.2 vector (Thermo Fisher) and transformed into E. coli TOP 10 cells by heat shock at 42°C for 42 seconds. 120 µL of the transformed E. coli solution was inoculated on LB agar (Duchefa) plates containing 0.2 mg/mL carbenicillin and grown overnight. The next day, 5 colonies from each primer pair were picked with a sterile tip and incubated in 10 µL of sterile dH2O for 10 minutes at 95°C. After incubation, 2 µL of the solution was used as DNA template in a PCR reaction using plasmid specific primers. Afterwards, the plasmids were extracted and purified using Genejet Plasmid Miniprep Kit (Thermo Fisher) and sent for sequencing to LGC Genomics, Berlin. Sequence results were blasted in NCBI in search for

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mutations and primer efficiency was determined via qRT-PCR using a serial dilution of primer concentrations. Primer pairs used for qRT-PCR are listed in Table 3. qRT-qPCR was performed with Bio-Rad CFX ConnectTM Real-Time PCR Detection System using SYBR Green I Mix (Bio Rad) under following thermal cycling conditions: 10 min at 95°C and 45 cycles (15 sec at 95°C, 25 sec at 60°C and 20 sec at 72°C). After each run, a melting curve was generated. Gene expression levels were normalized using three reference genes, OsEXP, OsEIF5C and OsEXPNarsai, and represented as the relative expression of infected samples versus non infected control samples (Al Atalah et al., 2014a; Kyndt et al., 2012b; Narsai et al., 2010). RT-qPCR reactions for all samples were performed in duplicate. Statistical analysis of the qPCR results was performed with REST-384 software using the Pair Wise Fixed Reallocation Randomization Test © with 2000 randomizations. Table 3: Primer pairs for genes of interest and reference genes for qRT-PCR analysis in rice (Nahar et al., 2011).

Gene Gene ID Efficiency Forward primer (5' - 3') Reverse primer (5' - 3')

OsEIN2A Os07g06130 1.81 TAGGGGGACTTTGACCATTG TGGAAGGGACCAGAAGTGTT

OsJAMYB Os11g0684000 2.02 GCTCATCTTCCGATTCGTTC CACCTCCTGCATCCAGTCTT

OsAOS2 Os03g0225900 2.05 CAATACGTGTACTGGTCGAATGG AAGGTGTCGTACCGGAGGAA

OsLIP9 Os02g0669100 1.97 CCGGCTACAGAGGAAGTGAG TCTCCATGATCTTGCCCAGT

OsNCED3 Os07g0154100 2.01 CGCAACAGTAAAAAGAATTAACAGC TATACACACACGCGGTCGTT

OsPR1A Os07g0129200 2.07 CGTACGTATGCTGGTGAGAA CTAAGCAAATACGGCTGACAGT

OsEULD1A Os07g48490 2.00 AACAGTGGGTGATGTAAGTGCAGG GGGTCGAGACAAATGAGCCATTC

OsEULD1B Os03g21040 2.02 CCGTGATCTGTGGAGTTGG GCAGGACTCGAGAAAACGAC

OsEULD2 Os07g48460 2.02 TCGAGAGACCGTCAACAAAA GGACACGCAACAGTAACACG

Reference genes

OsEXP Os03g27010 2.12 TGTGAGCAGCTTCTCGTTTG TGTTGTTGCCTGTGAGATCG

OsEXPNarsai Os07g02340.1 1.98 CACGTTACGGTGACACCTTTT GACGCTCTCCTTCTTCCTCAG

OsEIF5C Os011g21990.1 2.02 AGGAACATGGAGAAGAACAAGG CAGAGGTGGTGCAGATGAAA

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2.6. Statistical analyses Data analysis was performed in SPSS. The normality of the data was checked using the Kolmogorov-Smirnov test of normality with α = 0.05. The homoscedasticity of the data was checked using the Levene test with α = 0.05. After confirming normality and homoscedasticity, an ANOVA and Duncan’s multiple range test were applied with α = 0.05. If the conditions of normality and homoscedasticity were not fulfilled, a non-parametric Kruskal-Wallis test was used with α = 0.05.

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3. Results In this work, infection assays were performed on transgenic overexpression lines to test whether D-type OrysaEUL lectins help to fight off Mg infection. In addition, a qRT-PCR was performed to study the systemic defense responses and the stress inducible expression profile of D-type OrysaEUL proteins. Transgenic overexpression lines included in this study are: OrysaEULD1A, line D (D1A-D) and line F (D1A-F), OrysaEULD2, line B (D2-B) and C (D2-C) and OrysaEULD1B line D (D1B-D). A transgenic empty vector line G (EV-G) was also included in this experiment to study the effect of Agrobacterium mediated vector insertion on rice physiology. For each experiment and biological replicate, the data obtained from transgenic overexpression lines were compared to data from WT and EV-G control plants.

3.1. Meloidogyne graminicola infection assay in rice Fifteen-day-old transgenic and non-transgenic rice plants were infected with approximately 350 infective second stage juveniles. Fourteen days after infection with Mg, ten rice plants were sampled and growth parameters including shoot length, root length and root weight were measured for each plant. Once the measurements were completed, roots were stained with acid fuchsin to visualize the nematodes. After destaining of the roots, a microscope was used to count the number of nematodes for each developmental stage as well as the number of galls. 3.1.1. Growth parameters for infected rice plants Phenotypic analysis was done on rice plants infected with Mg because it might reveal differences in development between transgenic and WT rice plants. Figure 12 summarizes the growth parameters for transgenic and non-transgenic rice plants infected with Mg. Values for shoot length, root length, total length and root weight represent average values for 10 infected plants. Data analysis was done by using Duncan’s multiple range test (a = 0.05) to compare shoot length, root length, total length and root weight among the different genotypes. For the first biological replicate, EV-G plants show a significantly shorter shoot and root length compared to WT and transgenic overexpression lines. However, most overexpression lines are not significantly different from WT plants, except for D1A-D (21.4 cm) and D1B-D (21.4 cm) plants, their root length is significantly longer than WT (19.0 cm) plants. The largest plant is D1A-D (51.7 cm), its total length is significantly higher compared to WT (46.6 cm) and EV-G (37.5 cm) plants. In terms of root weight, EV-G plants (166.5 mg) are significantly lower compared to D1A-D (254.0 mg) and D2-B (259.7 mg) lines whereas D2-C (275.0 mg) plants have a significantly higher root weight compared to WT and EV-G plants. Furthermore, it has to be noted that although D1A-D and D1B-D plants have a significantly higher root length than WT plants, no significant differences were found when comparing root weights for these genotypes.

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In the second biological replicate, EV-G plants are the smallest plants compared to other genotypes. This was also seen in the first replicate. However, growth parameters for WT plants in the second replicate are generally not similar to plants form the overexpression lines. For example, WT (40.8 cm) and EV-G (37.8 cm) plants have a significantly smaller total length compared to D1A-D (47.3 cm), D1A-F (48.2 cm), D1B-D (49.9 cm) and D2-C (46.3 cm) plants. Furthermore, both WT and EV-G plants have a significantly smaller shoot length compared to plants from D-type EUL overexpression lines, ranking WT and EV-G as similar sized plants. The root length of transgenic D1B-D plants (15.5 cm) is significantly higher compared to WT plants (13.0 cm), whereas the root length of D2-B plants (10.2 cm) is significantly smaller compared to WT plants. Transgenic D2-B plants have the smallest root length of all tested genotypes. Moreover, the root length of the D2-B overexpression line (10.2 cm) is significantly lower compared to plants from the D2-C line (13.9 cm) suggesting that the observed root length is abnormally small for this type of overexpression line and caution should be made when analyzing the D2-B line from replicate 2. The roots of EV-G plants have the lowest weight (127.8 mg) and are significantly smaller compared to the roots of plants from the D1A-F, D2-B and D2-C line (234.2 mg, 215.7 mg and 269.9 mg).

Figure 12: Growth parameters of Meloidogyne graminicola infected WT and transgenic rice plants each overexpressing an empty vector or a D-type OrysaEUL. Bars represent the average and standard error of 10 plants, sampled at 14 dpi. Different letters indicate a significant difference between groups. Data

analyzed by using Duncan’s multiple range test (a = 0.05).

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There is a difference in ranking between WT and transgenic plants when comparing the growth parameters of both biological replicates. In the first replicate, EV-G plants are smaller compared to WT plants and plants from the overexpression lines whereas in the second replicate both EV-G and WT plants are smaller compared to plants from the overexpression lines. The shoot length of all plants in the second replicate is generally higher compared to the first replicate whereas the root length of all plants is generally smaller in replicate 2 compared to replicate 1. In general, plants from the overexpression lines have a higher total length and root weight compared to WT and EV-G plants. Although only D2-C plants have a significantly higher root weight compared to WT plants in replicate 1 and EV-G plants in both replicates, it has to be noted that plants from D1A-D and D2-B overexpression lines show a remarkably higher root weight compared to WT and EV-G plants. Furthermore, the average root length of WT plants in replicate 1 is 19.0 cm with an average root weight of 183.3 mg whereas in replicate 2 the average root length of WT plants is 13.0 cm and the average root weight 201.4 mg. This disproportional trend between root length and root weight among replicates is also observed in plants from D1A-F, D1B-D and D2-C overexpression lines. To compensate for differences in root architecture between overexpression lines and WT/EV-G plants, the number of nematodes per cm root or the number of nematodes per 100 mg root can be calculated to analyze the effect of D-type OrysaEULs on Mg infection. 3.1.2. Development of Meloidogyne graminicola on rice plants After phenotypic analysis of the infected plants, the number of nematodes per developmental stages of Mg, including second stage juveniles (J2), third and fourth stage juveniles (J3 and J4) and females, were counted and the number of galls was analyzed (Figure 13). The data obtained from the first replicate revealed no significant differences in nematode development and the average number of individuals for each stage when comparing WT and EV-G plants to plants from the overexpression lines. In the second replicate however, the number of J2 is significantly lower in D1A-D, D1A-F, D1B-D and D2-B plants compared to WT plants whereas the number of J3 and J4 is significantly higher in transgenic D1B-D plants compared to WT plants. Furthermore, the number of J3 and J4 are also higher in plants from the D1A-F, D1B-D and D2-C lines compared to EV-G plants. In both replicates, no significant differences were found for the number of females, total nematodes and the number of galls. It has to be noticed that in both replicates D1A overexpression and EV-G plants have a lower number of females, total number of nematodes and number of galls compared to WT plants. However, these results do not take into account the root architecture of the plants. Considering the results of the phenotyping data, further analysis on developmental stages is done by using the number of nematodes per 100 mg root.

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OrysaEULD1A

In the first replicate, plants from the D1A overexpression lines show a significant reduction (43.73% for line D and 47.19% for line F) in the total number of nematodes per 100 mg root compared to WT plants (Figure 14). In the second replicate there is also a lower number of total nematodes per 100 mg root in D1A plants compared to WT plants, but this reduction is not statistically significant. The number of J2 per 100 mg root is lower in D1A plants compared to WT plants for both replicates, with a significant reduction of 84.83% in transgenic D1A-F plants compared to WT in replicate 2. In the second replicate, the number of females per 100 mg is significantly reduced in D1A-D plants compared to WT (44.10%) and EV-G plants (44.34%), suggesting that overexpression of OrysaEULD1A has an effect on Mg development. A different trend among replicates is observed for the number of J3 and J4 per 100 mg root. In replicate 1, the average number of J3 and J4 is higher in WT plants whereas in replicate 2 the average number is higher in D1A plants suggesting a delay in Mg development in replicate 2. Although both replicates seem to be infected to a different degree, a similar trend is observed in the average number of nematodes per 100 mg root for D1A overexpression lines compared to WT and empty vector lines. In general, the overexpression of OrysaEULD1A lowers the susceptibility of rice plants towards Mg infection since there is a significant reduction in the

Figure 13: Average number of Meloidogyne graminicola per developmental stage and the average number of galls in WT and transgenic rice plants each overexpressing an empty vector or a certain D-type OrysaEUL. Per biological replicate 10 infected plants from each genotype were sampled at 14 dpi. Asterisks indicate significant differences determined within each biological replicate by ANOVA (p < 0.05). * = significantly different from WT plants, **= significantly different from WT and EV-G plants.

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number of J2, the number of females and the total number of nematodes per 100 mg root in this transgenic line compared to WT and EV-G control plants.

OrysaEULD1B

Statistical analysis of the average number of nematodes per 100 mg root retrieved from D1B overexpression line D revealed no significant differences compared to WT and EV-G plants, except in replicate 2 which shows a significant reduction in the number of J2 per 100 mg root compared to WT plants (77.18%) (Figure 15). Further analysis of both replicates revealed differences in the number of J3 and J4 per 100 mg root in D1B-D plants. In the first replicate, the number of nematodes in D1B-D plants is for all developmental stages lower compared to the number of nematodes in WT plants. In replicate 2, a higher number of J3 and J4 and a higher number of total nematodes per 100 mg root were found in D1B-D plants compared to WT. Generally, these results suggest that overexpression of OrysaEULD1B does not affect Mg infection.

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Figure 14: Average number of Meloidogyne graminicola relative to root weight per developmental stage in WT and transgenic rice plants overexpressing an empty vector (line G) or OrysaEULD1A (line D and F) – Biological replica