Genetic Diversity of Meloidogyne graminicola on Rice in Java Indonesia Based on Ribosomal DNA Gene

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Andi Trisyono, Alan Soffan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5629720/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Rice root-knot nematode, Meloidogyne graminicola is widely distributed globally, including in Indonesia, where it may influence genetic diversity among local populations. Understanding this genetic diversity is essential for developing effective management strategies for this nematode. This study aimed to investigate the genetic diversity of M. graminicola in Java, Indonesia. Population samples were collected from West Java, Central Java, and East Java. Species identification was performed using specific primers Mg-F3/Mg-R2. All samples were sequenced and analysed for phylogenetic analyses, genetic distances, haploid diversity, and population structure. The results confirmed that all samples from Java were M. graminicola and were closely related an isolate from the Philippines. The haploid diversity (Hd) of the M. graminicola population in Java was high (Hd = 1) and the nucleotide diversity (π = 0.06357). The Fst index indicated that there was no significant genetic difference among populations in Java, categorizing the overall genetic diversity as low (Fst = -0.08370). The haplotype network analysis further revealed that the Java populations did not form a single haplogroup, suggesting that each isolate in Java possessed a unique haplotype. This research highlighted that while M. graminicola populations in Java display high genetic diversity within individual population, this could potentially impact the virulence levels of these nematodes. The insights on genetic diversity of M. graminicola in Java could inform better management practices for controlling this pest. Haplotype diversity population structure rice root-knot nematode Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Rice root-knot nematodes, specifically Meloidogyne graminicola are considered to be among the most devastating plant-parasitic nematodes affecting rice production worldwide. M. graminicola was firstly discovered in Indonesia in 1993 in Yogyakarta (Netscher and Erlan 1993 ). This nematodes infects over 100 plant species, including cereals, grasses, and dicotyledonous plants, with rice being the most severely affected. Yield losses in rice can reach up to 70% due to this nematode (Rusinque et al. 2021 ). Reports indicate that the yield loss caused by M. graminicola ranged from 16 to 73% across various crop cultivation system (Zhong-ling et al. 2018 ). One of the rotation plants, chickpea cv. Yezin 4 consider as a good host for M. graminicola (Win et al. 2016 ). The infestation by M. graminicola is characterized by the formation of hook-like galls on the roots (Jabbar et al. 2021 ; Khan and Ahamad, 2020 ). Identifying nematodes species identification is crucial for effective diagnosis and management of their population. Traditional identification methods, which rely on morphological and morphometric characteristics, require specialized expertise, are time consuming and can be subjective, especially for limited samples. In contrast, moleculr approaches for identification have proven to be more efficient and effective for analysing large number of samples, as well as forstudying phylogenetic relationship and genetic diversity (Hodda 2022 ; Zhou et al. 2017 ). Recent studies have increasingly focussed on ribosomal RNA (rRNA) genes for species identification and phylogenetic identification (Shao et al. 2020 ). rRNA genes consist of conserved coding regions, including the 28S, 18S, and 5.8S subunit genes, along with noncoding regions. As molecular markers, rRNA genes can be utilized to assess phylogenetic relationship, analyse genetic diversity and study genome evolution (Bik et al. 2013 ). The 18S gene is universally present in eukaryotes and has been shown to be an effective marker for nematode barcoding and biodiversity surveys using the Sanger sequencing technique (Floyd et al. 2005 ). The 5.8S rRNA gene is more highly conserved region than the 18S and 28S rRNA genes, making it ideal for phylogenetic studies at the species and population levels (Valadas et al. 2013 ). Genetic diversity studies can provide foundational information for further research, particularly regarding population structure. Research on entomopathogenic nematodes in Portugal demonstrated no significant genetic diversity among Heterorhabdititis bacteriophora from different geographical location when using Cytochrome c oxidase 1 (COX1) marker (Valadas et al. 2013 ). In contrast, another molecular marker, inter-simple sequence repeats (ISSR) technique, has been employed for genetic diversity studies and revealed genetic variability among Heterorhabditis species, indicating genetic polymorphism across the nematode species (Khashaba and Abd El Azim, 2021 ). The genetic diversity of Haemonchus contortus characterized using rDNA ITS marker, has identified individual haplotypes based on their nucleotide composition (Aksenov and Spiridonov, 2013 ). Variation in genetic diversity among entomopathogenic nematodes can correlate with differences in virulence (Valadas et al. 2013 ). A related study on plant-parasitic nematodes conducted by Subbotin et al. ( 2019 ) utilized mitochondrial barcodes to estimate the phylogeography of potato cyst nematodes (PCN). DNA barcoding through ITS and COI analysis of Indonesian PCN revealed no sequence variation among most PCN in the world, with COI sequences being identical to the most common and widely distributed haplotype globally. Research on molecular identification as well as genetic diversity could serve as a basis for developing effective control strategies for PCN (Handayani et al. 2020 ). Studies on the genetic diversity of M. graminicola have been conducted using several molecular barcoding techniques. A haplotype network formed from the ITS sequences of Vietnamese population of M. graminicola revealed no clear geographical pattern among the haplotypes, through three Viatnamese haplotypes did intersect with accessions from Nepal, India, the Philippines, and China (Bellafiore et al. 2015 ). Research on M. graminicola populations in the Philippines, focussing on single-nucleotide polymorphism in the ITS rDNA gene and mtDNA showed only a few instances of heteroplasmy (Cabasan et al. 2018 ). Furthermore, a population structure analysis of M. graminicola in China, based on mitochondrial COI (mtCOI) sequences revealed a significant geographical distribution in evolutionary analysis showing a spread from south to north (Liu et al. 2023 ). More recent research by Shao et al. ( 2024 ) also explored the genetic diversity of plant-parasitic nematodes, specifically M. graminicola , in rice using the mtCOI gene, revealing high differentiation among populations within their respective distributions. In contrast, studies on the genetic diversity of M. graminicola in Indonesia are lacking, even though the nematode has become increasingly widespread in the country since its first discovery in 1993. Therefore, this study aims to investigate the genetic diversity of M. graminicola in Indonesia using rDNA sequence to provide a theoretical basis for considering population management. MATERIALS AND METHODS Nematode collection Rice root-knot nematode (RKN) samples were collected from rice field in Java, Indonesia, specifically from the Province of West Java, Central Java, and East Java. The sampling locations included Cirebon District in West Java, Banyumas District in Central Java, and Tulungagung District in East Java. Samples were obtained through purposive sampling in rice field that exhibited symptoms caused by rice RKN. In each district three locations were selected as samples. Root dissections were performed to provide nematode population for DNA extraction. Nematode identification DNA extraction was performed on three J2 samples from each sampling location as described by Morindya et al. ( 2023 ) using commercial kit (GeneAidTM Tissue/Blood DNA Mini Kit). The final DNA template used for PCR amplification regarding Htay et al. ( 2016 ) with specific primer of M. graminicola Mg-F3 (5`-TTATCGCATCATTTTATTTG-3`) / Mg-R2 (5`-CGCTTTGTTAGAAAATGACCCT-3`) with an amplified target fragment 369 bp of ribosomal DNA sequence on 5.8S region. 10 µl PCR mixture comprised of 5 µl RedTaq, Nuclease-Free Water, Forward and Reverse Primer 1 µl for each, and 2 µl DNA template were incubated on PCR machine. PCR programme was set on an initial denaturation at 94°C for 2 minutes, followed by 35 cycles with the following steps: denaturation at 94°C for 15 seconds, annealing at 50°C for 30 seconds, and extension at 68°C for 60 seconds. A final synthesis step was carried out at 68°C for 5 minutes at a final temperature of 4°C. All PCR products were then separated by electrophoresis on a 2% agarose gel and 0.1% FloroSafe DNA Stain at 100 V and 25 minutes then visualized using UV transilluminator. The amplified products were sequenced using Sanger sequencing at Integrated Laboratory for Research and Testing and the sequence were submitted to Gene Bank to obtain accession numbers. Population analysis All DNA sequences were aligned and trimmed using ClustalW on BioEdit software (version 7.2). A phylogenetic tree was constructed using Molecular Evolutionary Genetic Analysis (MEGA) software (version 11). Phylogenetic analyses were performed using the Kimura 2-parameter with evolutionarily invariable component (K2 + I). Additionally, sequence data of M. graminicola isolates from China, available on Gene Bank, corresponding to the same loci as 5.8S gene, were used for comparison of population structure. Haploid diversity across three geographical distributions was analysed using DnaSP 6.0 (version 6.12.03). The index measured included the number of haplotype (Hn), haplotype diversity (Hd), and nucleotide diversity (π) index were measured. Genetic diversity data were used to assess the genetic relationship and the population structure, which could provide as a theoretical basis for managing strategy of the population. This analyses performed by calculating the population genetic differentiation index (Fst) and analyse the genetic relationship among and within populations. The Fst among the geographical distribution was calculated to know the population structure on each location (Li et al. 2021 ; Tayyrov et al. 2021 ). An analysis of Molecular Variance (AMOVA) was performed to further assess population genetic differentiation, using the Alerquin software (version 3.5.2.2). The population structure was divided into two groups. The first group consisted of population from Java, Indonesia, which included three locations: West Java, Central Java and East Java. The second group combined population from Java, Indonesia (n = 9) with those from China (n = 4), as obtained from Gene Bank. RESULTS Nucleotide sequences data of this study were identified as Meloidogyne graminicola and deposited on Gene Bank with the accession numbers for West Java samples (PP892982.1; 893008.1; PP893010.1), Central Java (PP892965.1; PP892969.1; PP892970.1), and East Java (PP893011.1; PP893015.1; PP893021.1). Phylogenetic relationship The phylogenetic tree of M. graminicola from Java indicates that they are in a one clade with all M. graminicola isolates from China, Myanmar, Bangladesh, South Korea, and the Philippines. However, most isolates from Java form a group with those from the Philippines and South Korea, while the isolates from China, Bangladesh, and Myanmar are in a separate group. Additionally, several outgroup species and genera, including Meloidogyne oryzae, Meloidogyne incognita , and Meloidogyne javanica are placed in a different clade from M. graminicola isolates due to their distinction as different species. In another clade, Globodera rostochiensis, Hirschmanniella oryzae and Hirschmanniella mucronata are classified based on their genera (Fig. 1 ). The genetic distance analysis reveals trends similar to those observed in the phylogenetic tree. Smaller genetic distance values indicate closer relationship among the isolates (Trisyani and Rahayu 2020 ). Specifically, all isolates from Java are closely related to those from the Philippines, with distances ranging from 0.00–0.33. Notably, an isolate from West Java 2 is also close to an isolate from South Korea (Table 1 ). The highest similarity observed is in the West Java 3 isolate which shares 100% homology with an isolate from the Philippines. The percentage of homology among the isolates from Java varies, however, all isolates exhibit the highest homology with the Philippines isolates. In particular, the West Java 2 isolate shows a similarity of about 96.33% to both the Philippines and South Korea isolates (Table 2 ). Haplotype diversity The haplotype diversity of M. graminicola within population in Java was found to be high, with a haploid diversity (Hd = 1). Haplotype diversity among population is categorized as high if the Hd value falls within the range of 0.5 < Hd ≤ 1, and as low if falls with the range of 0 ≤ Hd < 0.5 (Kusumaningrum et al. 2020 ). This finding aligns with the identification of haplotypes (Hn), the Java population has nine haplotypes, with three haplotypes represented from each province. Haplotype variation plays a significant role in determining genetic diversity, and a high level of genetic diversity is indicated by a greater number of diverse haplotypes (Kusumaningrum et al. 2020 ; Li et al. 2023 ). Nucleotide diversity (π) is also essential for describing genetic variability within population; it measures the degree of genetic variation within that population (Kanaka et al. 2023 ). The total π value for the Java population was 0.06357, while the values for individual provincs was 0.04381 for Central Java, 0.05238 for West Java, and 0.10667 for East Java (Table 3 ). Table 3 Haplotype diversity of Meloidogyne graminicola isolates among Java Populations Location n 1 Hn 2 Hd 3 Π 4 West Java 3 3 1 0,05238 Central Java 3 3 1 0,04381 East Java 3 3 1 0,10667 All Populations 9 9 1 0,06357 1 number of samples 2 number of haplotype 3 haplotype diversity 4 nucleotide diversity Table 4 Comparison haplotype diversity of Meloidogyne graminicola isolates from Indonesia and China Location n 1 Hn 2 Hd 3 Π 4 Java, Indonesia 9 9 1 0,05948 China 4 2 0,5 0,00144 All Populations 13 11 0,96154 0,04677 1 number of samples 2 number of haplotype 3 haplotype diversity 4 nucleotide diversity To compare the genetic diversity of M. graminicola population, four isolates from China were analysed. These isolates are available in Gene Bank under the accession number KU646999.1, MN128225.1, MN521459.1, and MW487239.1 were used to perform the analyses. They were selected because they belong to the same region of DNA amplification, specifically in the ribosomal area. We compared two datasets, one from Indonesia and the other from China. The haplotype diversity of the Indonesia population (Hd = 1) was significantly higher than that of the Chinese population (Hd = 0.05). The Indonesia isolates exhibited nine haplotypes across nine samples, whereas the Chinese isolates showed only two haplotypes from four samples. This finding is consistent with the nucleotide diversity results, which indicated that Indonesia’s diversity was greater than that of China (Table 4 ). Higher nucleotide diversity suggests that at population is more sustainable (Muliani et al. 2020 ). Population structure Population structure was analysed using the Fixation index (Fst) value to assess the genetic differentiation among populations. The pairwise Fst analysis indicated that Fst value for the Java population was − 0.08370 which was not significant (P > 0.05). The Fst values between West Java and Central Java, West Java and East Java, and Central Java and East Java were − 0.08186, -0.12926, and − 0.03636, respectively (see Table 5 ). An Fst value of 0 indicates that the compared populations share overlapping haplotype, whereas an Fst value of 1 signifies complete separation (Tayyrov et al. 2021 ). Regarding the Fst value, Java population haplotypes were overlapped each other and lack of genetic diversity. Limmon et al. ( 2024 ) exhibited that the negative Fst value disclosed that there was a gene flow and genetic connectivity among the population which have not experienced significant genetic differentiation. The Fst value of the Java population indicated negative values, suggesting that there was more variation within the population than between populations in Java. Specifically, the percentage of variation within populations was 108.37%, while the variation between populations was − 8.37%. In contrast, when comparing the populations of Indonesia and China, the Fst value revealed a significant level of differentiation at approximately 0.12805 (P < 0.05). The Fst values between the population of Indonesia and China indicated a medium level differentiation. Wright ( 1978 ) categories for Fst provides clearer definitions: Fst value less than 0.05 indicate low genetic differentiation; values between 0.05 and 0.15 indicate medium differentiation, and values of 0.15 or higher indicate high differentiation. Furthermore, the percentage of variation within populations was also higher (87.20%) compared to the variation among populations (12.80%). Table 5 Fixation index (Fst) of Meloidogyne graminicola among Java Populations Location West Java Central Java East Java West Java - - - Central Java -0,08186 - - East Java -0,12926 -0,03636 - Gene flow (Nm) among the Java population was calculated using the Fst value, with the following formula Nm = (1-Fst)/4Fst (Jin et al. 2020 ). The Nm values among West Java and Central Java, West Java and East Java, and Central Java and East Java were − 3.30399, -2.18409, and − 7.12569, respectively. All Nm values among the Java populations were less than 1, indicating that the population was vulnerable to genetic drift. Genetic drift is the primary causes of genetic differentiation within population (Jin et al. 2023 ). This finding aligns with the negative Fst values among the Java population, which suggests a lack of genetic variability among the Java population due to the high variability within population. Population connectivity A haplotype network was constructed to assess the genetic connectivity among population. The results indicated that M. graminicola from the Java population exhibited nine distinct haplotypes, meaning that each specimen was unique. This indicated three specimens from West Java (n = 3), three from Central Java (n = 3), and three from East Java (n = 3). The nine specimens from the Java population did not form a haplogroup due to their specific nucleotide sequence, indicating that there was no haplotype mixing among specimens (Fig. 2 ). In comparison with the China population, it was also found that there was no mixing between the Indonesia and Chinese populations. However, the Chinese population did display a haplogroup, where three out of four specimens form a haplogroup while one specimen exhibited a specific haplotype (Acc. No. MW487239.1) (Fig. 3 ). Overall, the nine specimens from Indonesia did not formed a haplogroup, reflecting a similar trend to that observed in the Java population. DISCUSSION The rice root-knot nematode was discovered in Indonesia in various locations, including West Java (Nurjayadi et al. 2015 ), Yogyakarta (Netscher and Erlan, 1993 ) and south Sulawesi (Mirsam and Kurniawati, 2018 ) from the previous research. This research provides an update distribution of M. graminicola in Indonesia, particularly in Central Java and East Java. Three geographical distribution of M. graminicola in Java were identified using specific primer Mg-F3/Mg-R2 refer to Htay et al. ( 2016 ). The PCR products for nine specimens varied in size, ranging from 359–375 bp. Phylogenetic analyses indicated that specimens from Cirebon District (West Java), Banyumas District (Central Java) and Tulungagung District (East Java) formed a single clade with all M. graminicola specimen worldwide. Genetic studies can effectively trace the origin and spread of the organism (Zhao et al. 2015 ). This study found that the M. graminicola in Java is closely related to populations from the Philippnes and South Korea. However, the available isolate data from the Philippines and South Koreas were insufficient for comprehensive analyses of genetic diversity using DnaSP. M. graminicola is one of the most damaging plant-parasitic nematodes affecting rice, and its distribution in Indonesia has recently expanded significantly. This nematode is not confined to a single location, rather, it has spread throughout Java, from west to east. As shown in Fig. 2 all isolates from Java exhibited a specific haplotype, whether from the same province or different ones, indicating a high level of diversity in the M. graminicola population in Java. This finding aligns with the work of (Garg and Mishra, 2018 ), who stated that haplotype polymorphism is one of the common indicators for measuring the haplotype diversity. Additionally, genetic diversity provides insights into the evolution of the species (Stewart et al. 2019 ). In a comparison of genetic diversity, the haplotypes from Java and China did not overlap and did not form a haplogroup. The diversity among the Java population was high with a haplotype diversity (Hd) of 1, whereas the combined haplotype diversity of Java and China population was 0.96. This suggests that geographic distance is not the primary factor affecting the genetic variability of M. graminicola. These findings are consistent with several studies indicating that genetic distance is not necessarily correlated with geographic distance. For example, Shao et al. ( 2024 ) revealed that genetic variability of M. graminicola may be influenced by factors such as natural irrigation and long-range seed transport. Other research on the genetic differentiation of Meloidogyne enterlobii population from mulberry in China found that variation within each group were a major influence with, no correlation to geographic distances (Shao et al. 2020 ). This study similarity illustrates that the variation of M. graminicola within the population differ across the three geographical regions of Java. M. graminicola is a facultative meiotic parthenogenesis organisms that can reproduce through amphimixis under rare condition. This reproduction strategy, particularly parthenogenesis, allows this species to have a broader host range and larger geographic distribution due to its short life cycle, enabling rapid population growth and spread (Phan et al. 2020 ). Koutsovoulos et al. ( 2019 ) reported a low Fst value among 11 population of M. incognita from Brazilian isolates, indicating a lack of genetic variability within these populations, which can be attributed to their parthenogenetic reproduction strategy. Another study on M. graminicola revealed that this species has a highly heterozygous genom, resulting in low genomic genomic diversity across global populations (Besnard et al. 2019 ). Heterozygosity reflects the degree of genetic variation within a population, and is an important measure of genetic diversity (Kanaka et al. 2023 ). Genetic diversity affects how the species respond to various conditions, such as environmental stress, natural selection, and the pathogen virulence (Asamizu et al. 2020 ; Kanaka et al. 2023 ). Several factors contribute to genetic variability, including gene flow, evolutionary history, gene mutations, breeding system, and the natural environment (Wu et al. 2020 ). Genetic diversity among species can complicate management efforts because different genotypes and pathotypes require specific measures tailored to their unique virulence. Genetic variability directly influence plant-nematode interactions, potentially linking it to the gene expression. In the case of “ Heterodera schachtii” distinct variations in biological characteristics has been observed, including egg hatching, the attraction of second stage juvenile (J2) nematodes, their penetration of plant roots, the forming the feeding sites, and the overall reproduction rate (Nuaima and Heuer, 2023 ). Research on the rice root-knot nematode in Java shows that population exhibit significant, indicates genetic variability both within and between provinces. This suggests that M. graminicola population in Java are highly adaptive to a range of conditions and may exhibit different level of pathogenicity. Furthermore, a study has indicated that genetic diversity of Meloidogyne incognita arises from alternative adaptation strategies to different cultivars. Genome-wide association analyses have shown a correlation between M. incognita genotype and phenotype, particularly regarding the nematode’s virulenc against specific the plant cultivars (Asamizu et al. 2020 ). In conclusion, the genetic diversity of M. graminicola among populations in Java is low due to high variability within the populations. The genetic variability of M. graminicola within populations in West Java, Central Java, and East Java is notably high. This is evidenced not only by haplotype diversity, but also from the Fst index. Additionally, the percentage of variation within population (108.37%) is, greater than that among populations (-8.37%). The reproductive strategy of these rice root-knot nematodes also plays a crucial role in determining the genetic variability within the populations. As a result of this genetic variability among M. graminicola within populations in Java, the species exhibit highly adaptable strategies under various conditions, which can influence its level of pathogenicity. Given the genetic variability of M. graminicola population, it is important to consider these factors in managing the population of M. graminicola. Declarations COMPETING INTERESTS On behalf of all authors, the corresponding author states that there is no conflict of interest. DATA AVAILABILITY STATEMENTS The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. ACKNOWLEDGEMENT The authors thank Universitas Gadjah Mada (UGM) for providing research funding through the Final Assignment Recognition Program, under contract No. 5286/UN1.P1/PT.01.03/2024. Also thank UGM Press as university publisher for the language editing. AUTHORS’ CONTRIBUTION All authors contributed to the study conception and design. [SI] made contribution on the research conceptualization; [MT] performed the material preparation, data collection, analysis, and drafted original manuscript; [SI], [AT], and [AS] were supervised and revised the manuscript for important content. All authors read and approved the final manuscript. 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Liu MY, Shao HD, Wu YY, Peng DL, Yu JW, Jia JP, Peng H, Li CR, Sulaiman A, Yu XY, Li CH, Huang WK (2023) Meloidogyne graminicola population structure in China suggests a south-to-north expansion. Plant Dis 107:2070–2080. https://doi.org/10.1094/PDIS-08-22-1796-RE. Mirsam H, Kurniawati F (2018) Laporan pertama di Sulawesi Selatan: Karakter morfologi dan molekuler nematoda puru akar yang berasosiasi dengan akar padi di Kabupaten Wajo, Sulawesi Selatan. JPTI 22:85-90. https://doi.org/10.22146/jpti.33108. Morindya R, Indarti S, Soffan A, Hartono S (2023) Optimization of DNA extraction methods for genomic analysis of rice root-knot nematode ( Meloidogyne graminicola ) using PCR (polymerase chain reaction) and sanger sequencing. JPPR 63:50–58. https://doi.org/10.24425/jppr.2022.144416. Muliani DR, Yulianda F, Butet NA (2020) Karakteristik gen Cytochrome Oxidase Subunit I (COI) tiram daging dari genus Crassostrea sebagai identitas jenis di Delta Cimanuk, Jawa Barat. JMI 4:8–16. 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Rusinque L, Maleita C, Abrantes I, Palomares-rius JE, Inacio M (2021) Meloidogyne graminicola -A threat to rice production: Review update on distribution, biology, identification, and management. Biol 10:1–19. Shao H, Liu MY, Huang WK, Li CH, Peng D, Peng H, Li C, Long HB, Kong LA, Liu S, Zhang P, Yu JW, Ping J (2024) Genetic diversity of the root-knot nematode Meloidogyne enterolobii in Mulberry based on the mitochondrial COI gene. Adv 10:5391-5401. https://doi.org/10.22541/au.170669376.63806985/v1. Shao H, Zhang P, You C, Li C, Feng Y, Xie Z (2020) Genetic diversity of the root-knot nematode Meloidogyne enterolobii in mulberry based on the Mitochondrial COI gene. Ecol Evol 10:5391–5401. https://doi.org/10.1002/ece3.6282. Stewart KA, Draaijer R, Kolasa MR, Smallegange IM (2019) The role of genetic diversity in the evolution and maintenance of environmentally-cued, male alternative reproductive tactics. BMC Evol Biol, 19:1–10. https://doi.org/10.1186/s12862-019-1385-4. Subbotin SA, Franco J, Knoetze R, Roubtsova TV, Bostock RM, Cid Del Prado Vera I (2019) DNA barcoding, phylogeny and phylogeography of the cyst nematode species from the genus Globodera (Tylenchida: Heteroderidae). Nematol 0:1–29. https://doi.org/10.1163/15685411-00003305. Tayyrov A, Schnetzler M, Gillis-Germitsch N, Schnyder M (2021) Genetic diversity of the cardiopulmonary canid nematode Angiostrongylus vasorum within and between rural and urban fox populations. Infect Genet Evol 87:1-11. https://doi.org/10.1016/j.meegid.2020.104618. Trisyani N, Rahayu DA (2020) DNA barcoding of razor clam solen spp. (solinidae, bivalva) in Indonesian beaches. Biodiversitas 21:478–484. https://doi.org/10.13057/biodiv/d210207. Valadas V, Laranjo M, Mota M, Oliveira S (2013) A survey of entomopathogenic nematode species in continental Portugal. J Helminthol 88:1–15. https://doi.org/10.1017/S0022149X13000217. Win PP, Kyi PP, Maung ZTZ, Myint YY, Cabasan MTN, Waele DD (2016) Host status of rotation crops in Asian rice-based cropping systems to the rice root-knot nematode Meloidogyne graminicola. Trop Plant Pathol 41:312-319. DOI 10.1007/s40858-016-0106-4. Wright S (1978) Evolution and the Genetics of Populations, Volume 1. The University of Chicago Press, US. Wu Q, Zang F, Ma Y, Zheng Y, Zang D (2020) Analysis of genetic diversity and population structure in endangered Populus wulianensis based on 18 newly developed EST-SSR markers. GECCO 24:1-13. https://doi.org/10.1016/j.gecco.2020.e01329. Zhao YB, Zhang Y, Zhang QC, Li HJ, Cui YQ, Xu Z, Jin L, Zhou H, Zhu H (2015) Ancient DNA reveals that the genetic structure of the northern Han Chinese was shaped prior to 3,000 years ago. PLoS ONE 10:1–17. https://doi.org/10.1371/journal.pone.0125676. Zhong-ling T, Maria M, Barsalote EM, Castillo P, ZHENG J-wu (2018) Morphological and molecular characterization of the rice root-knot nematode, Meloidogyne graminicola , Golden and Birchfeild, 1965 occurring in Zhejiang, China. J Integr Agric 17:2724–2733. https://doi.org/10.1016/S2095-3119(18)61971-9. Zhou S, Yan B, Li F, Zhang J, Zhang J, Ma H, Liu W, Lu Y, Yang X, Li X, Liu X, Li L (2017) RNA-Seq analysis provides the first insights into the phylogenetic relationship and interspecific variation between Agropyron cristatum and wheat. Front Plant Sci 8:1–13. https://doi.org/10.3389/fpls.2017.01644. Table 1 and 2 Table 1 and 2 are available in the Supplementary Files section. Supplementary Files Table1and2.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5629720","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":395910987,"identity":"7444a3d6-f3be-446f-95a8-bf8fa0a30c50","order_by":0,"name":"Mutala'liah Mutala'liah","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Mutala'liah","middleName":"","lastName":"Mutala'liah","suffix":""},{"id":395910988,"identity":"181e2395-af0b-40f6-b6ed-aaa89c4d2366","order_by":1,"name":"Siwi Indarti","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYDACZgaGAwwGDIwNQPaBDzDRBDaitDAzHJxBlBYoAGth5oHz8WiRb+cxPMBQcEe2f/b5g4dt22qjGdgPP2B4UIZbi8FhHgOgw54ZzziXzHA4t+14bgNPmgFDwjk8Wph5NwC1HE5sOMMM0nIst4Ehh4EhsQ2Pw5qhWuaDtFiCtPC/wa+F4TBUywaQFsa2mtwGCQK2GBzm/3AgweCw8cYzzAYHe84dyG2TeGZwAJ9f5PuPJX/48Oew7LwzjI8//Ciry+3nT3748AeeEAODBCR3gmPkAAENKKCOFMWjYBSMglEwQgAAG49XhS1u9nsAAAAASUVORK5CYII=","orcid":"","institution":"Gadjah Mada University Faculty of Agriculture: Universitas Gadjah Mada Fakultas Pertanian","correspondingAuthor":true,"prefix":"","firstName":"Siwi","middleName":"","lastName":"Indarti","suffix":""},{"id":395910989,"identity":"27b03e88-f4d5-46e8-8482-0c66a60868b4","order_by":2,"name":"Y. Andi Trisyono","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Y.","middleName":"Andi","lastName":"Trisyono","suffix":""},{"id":395910990,"identity":"6b9f78c3-688f-40d4-88ba-0328d461a3fe","order_by":3,"name":"Alan Soffan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Alan","middleName":"","lastName":"Soffan","suffix":""}],"badges":[],"createdAt":"2024-12-12 08:27:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5629720/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5629720/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":72744418,"identity":"fbc7a73c-058f-4fa5-a49a-2e64feaddecd","added_by":"auto","created_at":"2025-01-01 11:50:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":183555,"visible":true,"origin":"","legend":"\u003cp\u003eThe phylogenetic tree of \u003cem\u003eMeloidogyne graminicola\u003c/em\u003e in Java was compared to \u003cem\u003eM. graminicola\u003c/em\u003e from other countries and other species as an out group.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5629720/v1/6e29e10bbfa9ef10dceaa303.png"},{"id":72744360,"identity":"c9ab82b5-c99f-45ec-9562-2e8ae062a65c","added_by":"auto","created_at":"2025-01-01 11:42:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53608,"visible":true,"origin":"","legend":"\u003cp\u003eHaplotype networks among Java populations.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5629720/v1/9d69ea6544a1c230ba8fef7f.png"},{"id":72744362,"identity":"8a41cb79-b5f5-4654-bcea-99543b9f32d1","added_by":"auto","created_at":"2025-01-01 11:42:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":52622,"visible":true,"origin":"","legend":"\u003cp\u003eHaplotype networks from Indonesia (all Java populations) and China.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5629720/v1/f2d7f15a09d9bfdd4f3751cd.png"},{"id":77798777,"identity":"10327b99-88f3-48f0-aedb-79c35abbb108","added_by":"auto","created_at":"2025-03-05 16:06:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":847308,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5629720/v1/ae03f4c1-04a4-4af4-aaa6-f371f3ae520e.pdf"},{"id":72744359,"identity":"9774b7c4-d72b-48be-997f-bf0f1b348b96","added_by":"auto","created_at":"2025-01-01 11:42:44","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":59108,"visible":true,"origin":"","legend":"","description":"","filename":"Table1and2.docx","url":"https://assets-eu.researchsquare.com/files/rs-5629720/v1/964f92b6d0135a4f0a0db217.docx"}],"financialInterests":"","formattedTitle":"Genetic Diversity of Meloidogyne graminicola on Rice in Java Indonesia Based on Ribosomal DNA Gene","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eRice root-knot nematodes, specifically \u003cem\u003eMeloidogyne graminicola\u003c/em\u003e are considered to be among the most devastating plant-parasitic nematodes affecting rice production worldwide. \u003cem\u003eM. graminicola\u003c/em\u003e was firstly discovered in Indonesia in 1993 in Yogyakarta (Netscher and Erlan \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). This nematodes infects over 100 plant species, including cereals, grasses, and dicotyledonous plants, with rice being the most severely affected. Yield losses in rice can reach up to 70% due to this nematode (Rusinque et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Reports indicate that the yield loss caused by \u003cem\u003eM. graminicola\u003c/em\u003e ranged from 16 to 73% across various crop cultivation system (Zhong-ling et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). One of the rotation plants, chickpea cv. Yezin 4 consider as a good host for \u003cem\u003eM. graminicola\u003c/em\u003e (Win et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The infestation by \u003cem\u003eM. graminicola\u003c/em\u003e is characterized by the formation of hook-like galls on the roots (Jabbar et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Khan and Ahamad, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIdentifying nematodes species identification is crucial for effective diagnosis and management of their population. Traditional identification methods, which rely on morphological and morphometric characteristics, require specialized expertise, are time consuming and can be subjective, especially for limited samples. In contrast, moleculr approaches for identification have proven to be more efficient and effective for analysing large number of samples, as well as forstudying phylogenetic relationship and genetic diversity (Hodda \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhou et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Recent studies have increasingly focussed on ribosomal RNA (rRNA) genes for species identification and phylogenetic identification (Shao et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). rRNA genes consist of conserved coding regions, including the 28S, 18S, and 5.8S subunit genes, along with noncoding regions. As molecular markers, rRNA genes can be utilized to assess phylogenetic relationship, analyse genetic diversity and study genome evolution (Bik et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The 18S gene is universally present in eukaryotes and has been shown to be an effective marker for nematode barcoding and biodiversity surveys using the Sanger sequencing technique (Floyd et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The 5.8S rRNA gene is more highly conserved region than the 18S and 28S rRNA genes, making it ideal for phylogenetic studies at the species and population levels (Valadas et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGenetic diversity studies can provide foundational information for further research, particularly regarding population structure. Research on entomopathogenic nematodes in Portugal demonstrated no significant genetic diversity among \u003cem\u003eHeterorhabdititis bacteriophora\u003c/em\u003e from different geographical location when using Cytochrome c oxidase 1 (COX1) marker (Valadas et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In contrast, another molecular marker, inter-simple sequence repeats (ISSR) technique, has been employed for genetic diversity studies and revealed genetic variability among \u003cem\u003eHeterorhabditis\u003c/em\u003e species, indicating genetic polymorphism across the nematode species (Khashaba and Abd El Azim, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The genetic diversity of \u003cem\u003eHaemonchus contortus\u003c/em\u003e characterized using rDNA ITS marker, has identified individual haplotypes based on their nucleotide composition (Aksenov and Spiridonov, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Variation in genetic diversity among entomopathogenic nematodes can correlate with differences in virulence (Valadas et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). A related study on plant-parasitic nematodes conducted by Subbotin et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) utilized mitochondrial barcodes to estimate the phylogeography of potato cyst nematodes (PCN). DNA barcoding through ITS and COI analysis of Indonesian PCN revealed no sequence variation among most PCN in the world, with COI sequences being identical to the most common and widely distributed haplotype globally. Research on molecular identification as well as genetic diversity could serve as a basis for developing effective control strategies for PCN (Handayani et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStudies on the genetic diversity of \u003cem\u003eM. graminicola\u003c/em\u003e have been conducted using several molecular barcoding techniques. A haplotype network formed from the ITS sequences of Vietnamese population of \u003cem\u003eM. graminicola\u003c/em\u003e revealed no clear geographical pattern among the haplotypes, through three Viatnamese haplotypes did intersect with accessions from Nepal, India, the Philippines, and China (Bellafiore et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Research on \u003cem\u003eM. graminicola\u003c/em\u003e populations in the Philippines, focussing on single-nucleotide polymorphism in the ITS rDNA gene and mtDNA showed only a few instances of heteroplasmy (Cabasan et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Furthermore, a population structure analysis of \u003cem\u003eM. graminicola\u003c/em\u003e in China, based on mitochondrial COI (mtCOI) sequences revealed a significant geographical distribution in evolutionary analysis showing a spread from south to north (Liu et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). More recent research by Shao et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) also explored the genetic diversity of plant-parasitic nematodes, specifically \u003cem\u003eM. graminicola\u003c/em\u003e, in rice using the mtCOI gene, revealing high differentiation among populations within their respective distributions. In contrast, studies on the genetic diversity of \u003cem\u003eM. graminicola\u003c/em\u003e in Indonesia are lacking, even though the nematode has become increasingly widespread in the country since its first discovery in 1993. Therefore, this study aims to investigate the genetic diversity of \u003cem\u003eM. graminicola\u003c/em\u003e in Indonesia using rDNA sequence to provide a theoretical basis for considering population management.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eNematode collection\u003c/h2\u003e \u003cp\u003eRice root-knot nematode (RKN) samples were collected from rice field in Java, Indonesia, specifically from the Province of West Java, Central Java, and East Java. The sampling locations included Cirebon District in West Java, Banyumas District in Central Java, and Tulungagung District in East Java. Samples were obtained through purposive sampling in rice field that exhibited symptoms caused by rice RKN. In each district three locations were selected as samples. Root dissections were performed to provide nematode population for DNA extraction.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eNematode identification\u003c/h3\u003e\n\u003cp\u003eDNA extraction was performed on three J2 samples from each sampling location as described by Morindya et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) using commercial kit (GeneAidTM Tissue/Blood DNA Mini Kit). The final DNA template used for PCR amplification regarding Htay et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) with specific primer of \u003cem\u003eM. graminicola\u003c/em\u003e Mg-F3 (5`-TTATCGCATCATTTTATTTG-3`) / Mg-R2 (5`-CGCTTTGTTAGAAAATGACCCT-3`) with an amplified target fragment 369 bp of ribosomal DNA sequence on 5.8S region. 10 \u0026micro;l PCR mixture comprised of 5 \u0026micro;l RedTaq, Nuclease-Free Water, Forward and Reverse Primer 1 \u0026micro;l for each, and 2 \u0026micro;l DNA template were incubated on PCR machine. PCR programme was set on an initial denaturation at 94\u0026deg;C for 2 minutes, followed by 35 cycles with the following steps: denaturation at 94\u0026deg;C for 15 seconds, annealing at 50\u0026deg;C for 30 seconds, and extension at 68\u0026deg;C for 60 seconds. A final synthesis step was carried out at 68\u0026deg;C for 5 minutes at a final temperature of 4\u0026deg;C. All PCR products were then separated by electrophoresis on a 2% agarose gel and 0.1% FloroSafe DNA Stain at 100 V and 25 minutes then visualized using UV transilluminator. The amplified products were sequenced using Sanger sequencing at Integrated Laboratory for Research and Testing and the sequence were submitted to Gene Bank to obtain accession numbers.\u003c/p\u003e\n\u003ch3\u003ePopulation analysis\u003c/h3\u003e\n\u003cp\u003eAll DNA sequences were aligned and trimmed using ClustalW on BioEdit software (version 7.2). A phylogenetic tree was constructed using Molecular Evolutionary Genetic Analysis (MEGA) software (version 11). Phylogenetic analyses were performed using the Kimura 2-parameter with evolutionarily invariable component (K2\u0026thinsp;+\u0026thinsp;I). Additionally, sequence data of \u003cem\u003eM. graminicola\u003c/em\u003e isolates from China, available on Gene Bank, corresponding to the same loci as 5.8S gene, were used for comparison of population structure.\u003c/p\u003e \u003cp\u003eHaploid diversity across three geographical distributions was analysed using DnaSP 6.0 (version 6.12.03). The index measured included the number of haplotype (Hn), haplotype diversity (Hd), and nucleotide diversity (π) index were measured. Genetic diversity data were used to assess the genetic relationship and the population structure, which could provide as a theoretical basis for managing strategy of the population. This analyses performed by calculating the population genetic differentiation index (Fst) and analyse the genetic relationship among and within populations. The Fst among the geographical distribution was calculated to know the population structure on each location (Li et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tayyrov et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). An analysis of Molecular Variance (AMOVA) was performed to further assess population genetic differentiation, using the Alerquin software (version 3.5.2.2). The population structure was divided into two groups. The first group consisted of population from Java, Indonesia, which included three locations: West Java, Central Java and East Java. The second group combined population from Java, Indonesia (n\u0026thinsp;=\u0026thinsp;9) with those from China (n\u0026thinsp;=\u0026thinsp;4), as obtained from Gene Bank.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eNucleotide sequences data of this study were identified as \u003cem\u003eMeloidogyne graminicola\u003c/em\u003e and deposited on Gene Bank with the accession numbers for West Java samples (PP892982.1; 893008.1; PP893010.1), Central Java (PP892965.1; PP892969.1; PP892970.1), and East Java (PP893011.1; PP893015.1; PP893021.1).\u003c/p\u003e\n\u003ch3\u003ePhylogenetic relationship\u003c/h3\u003e\n\u003cp\u003eThe phylogenetic tree of \u003cem\u003eM. graminicola\u003c/em\u003e from Java indicates that they are in a one clade with all \u003cem\u003eM. graminicola\u003c/em\u003e isolates from China, Myanmar, Bangladesh, South Korea, and the Philippines. However, most isolates from Java form a group with those from the Philippines and South Korea, while the isolates from China, Bangladesh, and Myanmar are in a separate group. Additionally, several outgroup species and genera, including \u003cem\u003eMeloidogyne oryzae, Meloidogyne incognita\u003c/em\u003e, and \u003cem\u003eMeloidogyne javanica\u003c/em\u003e are placed in a different clade from \u003cem\u003eM. graminicola\u003c/em\u003e isolates due to their distinction as different species. In another clade, \u003cem\u003eGlobodera rostochiensis, Hirschmanniella oryzae\u003c/em\u003e and \u003cem\u003eHirschmanniella mucronata\u003c/em\u003e are classified based on their genera (Fig. \u003cspan\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe genetic distance analysis reveals trends similar to those observed in the phylogenetic tree. Smaller genetic distance values indicate closer relationship among the isolates (Trisyani and Rahayu \u003cspan\u003e2020\u003c/span\u003e). Specifically, all isolates from Java are closely related to those from the Philippines, with distances ranging from 0.00\u0026ndash;0.33. Notably, an isolate from West Java 2 is also close to an isolate from South Korea (Table \u003cspan\u003e1\u003c/span\u003e). The highest similarity observed is in the West Java 3 isolate which shares 100% homology with an isolate from the Philippines. The percentage of homology among the isolates from Java varies, however, all isolates exhibit the highest homology with the Philippines isolates. In particular, the West Java 2 isolate shows a similarity of about 96.33% to both the Philippines and South Korea isolates (Table \u003cspan\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eHaplotype diversity\u003c/h2\u003e\n \u003cp\u003eThe haplotype diversity of \u003cem\u003eM. graminicola\u003c/em\u003e within population in Java was found to be high, with a haploid diversity (Hd\u0026thinsp;=\u0026thinsp;1). Haplotype diversity among population is categorized as high if the Hd value falls within the range of 0.5\u0026thinsp;\u0026lt;\u0026thinsp;Hd\u0026thinsp;\u0026le;\u0026thinsp;1, and as low if falls with the range of 0\u0026thinsp;\u0026le;\u0026thinsp;Hd\u0026thinsp;\u0026lt;\u0026thinsp;0.5 (Kusumaningrum et al. \u003cspan\u003e2020\u003c/span\u003e). This finding aligns with the identification of haplotypes (Hn), the Java population has nine haplotypes, with three haplotypes represented from each province. Haplotype variation plays a significant role in determining genetic diversity, and a high level of genetic\u003c/p\u003e\n \u003cp\u003ediversity is indicated by a greater number of diverse haplotypes (Kusumaningrum et al. \u003cspan\u003e2020\u003c/span\u003e; Li et al. \u003cspan\u003e2023\u003c/span\u003e). Nucleotide diversity (\u0026pi;) is also essential for describing genetic variability within population; it measures the degree of genetic variation within that population (Kanaka et al. \u003cspan\u003e2023\u003c/span\u003e). The total \u0026pi; value for the Java population was 0.06357, while the values for individual provincs was 0.04381 for Central Java, 0.05238 for West Java, and 0.10667 for East Java (Table \u003cspan\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eHaplotype diversity of \u003cem\u003eMeloidogyne graminicola\u003c/em\u003e isolates among Java Populations\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLocation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHn\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHd\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026Pi;\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWest Java\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,05238\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCentral Java\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,04381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEast Java\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,10667\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll Populations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,06357\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e1\u003c/sup\u003e number of samples\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e2\u003c/sup\u003e number of haplotype\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e3\u003c/sup\u003e haplotype diversity\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e4\u003c/sup\u003e nucleotide diversity\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eComparison haplotype diversity of \u003cem\u003eMeloidogyne graminicola\u003c/em\u003e isolates from Indonesia and China\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLocation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHn\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHd\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026Pi;\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJava, Indonesia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,05948\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,00144\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll Populations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,96154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,04677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e1\u003c/sup\u003e number of samples\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e2\u003c/sup\u003e number of haplotype\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e3\u003c/sup\u003e haplotype diversity\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003csup\u003e4\u003c/sup\u003e nucleotide diversity\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTo compare the genetic diversity of \u003cem\u003eM. graminicola\u003c/em\u003e population, four isolates from China were analysed. These isolates are available in Gene Bank under the accession number KU646999.1, MN128225.1, MN521459.1, and MW487239.1 were used to perform the analyses. They were selected because they belong to the same region of DNA amplification, specifically in the ribosomal area. We compared two datasets, one from Indonesia and the other from China. The haplotype diversity of the Indonesia population (Hd\u0026thinsp;=\u0026thinsp;1) was significantly higher than that of the Chinese population (Hd\u0026thinsp;=\u0026thinsp;0.05). The Indonesia isolates exhibited nine haplotypes across nine samples, whereas the Chinese isolates showed only two haplotypes from four samples. This finding is consistent with the nucleotide diversity results, which indicated that Indonesia\u0026rsquo;s diversity was greater than that of China (Table \u003cspan\u003e4\u003c/span\u003e). Higher nucleotide diversity suggests that at population is more sustainable (Muliani et al. \u003cspan\u003e2020\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003ePopulation structure\u003c/h3\u003e\n\u003cp\u003ePopulation structure was analysed using the Fixation index (Fst) value to assess the genetic differentiation among populations. The pairwise Fst analysis indicated that Fst value for the Java population was \u0026minus;\u0026thinsp;0.08370 which was not significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The Fst values between West Java and Central Java, West Java and East Java, and Central Java and East Java were \u0026minus;\u0026thinsp;0.08186, -0.12926, and \u0026minus;\u0026thinsp;0.03636, respectively (see Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). An Fst value of 0 indicates that the compared populations share overlapping haplotype, whereas an Fst value of 1 signifies complete separation (Tayyrov et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Regarding the Fst value, Java population haplotypes were overlapped each other and lack of genetic diversity. Limmon et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) exhibited that the negative Fst value disclosed that there was a gene flow and genetic connectivity among the population which have not experienced significant genetic differentiation. The Fst value of the Java population indicated negative values, suggesting that there was more variation within the population than between populations in Java. Specifically, the percentage of variation within populations was 108.37%, while the variation between populations was \u0026minus;\u0026thinsp;8.37%. In contrast, when comparing the populations of Indonesia and China, the Fst value revealed a significant level of differentiation at approximately 0.12805 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The Fst values between the population of Indonesia and China indicated a medium level differentiation. Wright (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1978\u003c/span\u003e) categories for Fst provides clearer definitions: Fst value less than 0.05 indicate low genetic differentiation; values between 0.05 and 0.15 indicate medium differentiation, and values of 0.15 or higher indicate high differentiation. Furthermore, the percentage of variation within populations was also higher (87.20%) compared to the variation among populations (12.80%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFixation index (Fst) of \u003cem\u003eMeloidogyne graminicola\u003c/em\u003e among Java Populations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWest Java\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral Java\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEast Java\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0,08186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0,12926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0,03636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eGene flow (Nm) among the Java population was calculated using the Fst value, with the following formula Nm = (1-Fst)/4Fst (Jin et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The Nm values among West Java and Central Java, West Java and East Java, and Central Java and East Java were \u0026minus;\u0026thinsp;3.30399, -2.18409, and \u0026minus;\u0026thinsp;7.12569, respectively. All Nm values among the Java populations were less than 1, indicating that the population was vulnerable to genetic drift. Genetic drift is the primary causes of genetic differentiation within population (Jin et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This finding aligns with the negative Fst values among the Java population, which suggests a lack of genetic variability among the Java population due to the high variability within population.\u003c/p\u003e\n\u003ch3\u003ePopulation connectivity\u003c/h3\u003e\n\u003cp\u003eA haplotype network was constructed to assess the genetic connectivity among population. The results indicated that \u003cem\u003eM. graminicola\u003c/em\u003e from the Java population exhibited nine distinct haplotypes, meaning that each specimen was unique. This indicated three specimens from West Java (n\u0026thinsp;=\u0026thinsp;3), three from Central Java (n\u0026thinsp;=\u0026thinsp;3), and three from East Java (n\u0026thinsp;=\u0026thinsp;3). The nine specimens from the Java population did not form a haplogroup due to their specific nucleotide sequence, indicating that there was no haplotype mixing among specimens (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn comparison with the China population, it was also found that there was no mixing between the Indonesia and Chinese populations. However, the Chinese population did display a haplogroup, where three out of four specimens form a haplogroup while one specimen exhibited a specific haplotype (Acc. No. MW487239.1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Overall, the nine specimens from Indonesia did not formed a haplogroup, reflecting a similar trend to that observed in the Java population.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe rice root-knot nematode was discovered in Indonesia in various locations, including West Java (Nurjayadi et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Yogyakarta (Netscher and Erlan, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) and south Sulawesi (Mirsam and Kurniawati, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) from the previous research. This research provides an update distribution of \u003cem\u003eM. graminicola\u003c/em\u003e in Indonesia, particularly in Central Java and East Java. Three geographical distribution of \u003cem\u003eM. graminicola\u003c/em\u003e in Java were identified using specific primer Mg-F3/Mg-R2 refer to Htay et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The PCR products for nine specimens varied in size, ranging from 359\u0026ndash;375 bp. Phylogenetic analyses indicated that specimens from Cirebon District (West Java), Banyumas District (Central Java) and Tulungagung District (East Java) formed a single clade with all \u003cem\u003eM. graminicola\u003c/em\u003e specimen worldwide. Genetic studies can effectively trace the origin and spread of the organism (Zhao et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This study found that the \u003cem\u003eM. graminicola\u003c/em\u003e in Java is closely related to populations from the Philippnes and South Korea. However, the available isolate data from the Philippines and South Koreas were insufficient for comprehensive analyses of genetic diversity using DnaSP.\u003c/p\u003e \u003cp\u003e \u003cem\u003eM. graminicola\u003c/em\u003e is one of the most damaging plant-parasitic nematodes affecting rice, and its distribution in Indonesia has recently expanded significantly. This nematode is not confined to a single location, rather, it has spread throughout Java, from west to east. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e all isolates from Java exhibited a specific haplotype, whether from the same province or different ones, indicating a high level of diversity in the \u003cem\u003eM. graminicola\u003c/em\u003e population in Java. This finding aligns with the work of (Garg and Mishra, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), who stated that haplotype polymorphism is one of the common indicators for measuring the haplotype diversity. Additionally, genetic diversity provides insights into the evolution of the species (Stewart et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In a comparison of genetic diversity, the haplotypes from Java and China did not overlap and did not form a haplogroup. The diversity among the Java population was high with a haplotype diversity (Hd) of 1, whereas the combined haplotype diversity of Java and China population was 0.96. This suggests that geographic distance is not the primary factor affecting the genetic variability of \u003cem\u003eM. graminicola.\u003c/em\u003e These findings are consistent with several studies indicating that genetic distance is not necessarily correlated with geographic distance. For example, Shao et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) revealed that genetic variability of \u003cem\u003eM. graminicola\u003c/em\u003e may be influenced by factors such as natural irrigation and long-range seed transport. Other research on the genetic differentiation of \u003cem\u003eMeloidogyne enterlobii\u003c/em\u003e population from mulberry in China found that variation within each group were a major influence with, no correlation to geographic distances (Shao et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This study similarity illustrates that the variation of \u003cem\u003eM. graminicola\u003c/em\u003e within the population differ across the three geographical regions of Java.\u003c/p\u003e \u003cp\u003e \u003cem\u003eM. graminicola\u003c/em\u003e is a facultative meiotic parthenogenesis organisms that can reproduce through amphimixis under rare condition. This reproduction strategy, particularly parthenogenesis, allows this species to have a broader host range and larger geographic distribution due to its short life cycle, enabling rapid population growth and spread (Phan et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Koutsovoulos et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reported a low Fst value among 11 population of \u003cem\u003eM. incognita\u003c/em\u003e from Brazilian isolates, indicating a lack of genetic variability within these populations, which can be attributed to their parthenogenetic reproduction strategy. Another study on \u003cem\u003eM. graminicola\u003c/em\u003e revealed that this species has a highly heterozygous genom, resulting in low genomic genomic diversity across global populations (Besnard et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Heterozygosity reflects the degree of genetic variation within a population, and is an important measure of genetic diversity (Kanaka et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGenetic diversity affects how the species respond to various conditions, such as environmental stress, natural selection, and the pathogen virulence (Asamizu et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kanaka et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Several factors contribute to genetic variability, including gene flow, evolutionary history, gene mutations, breeding system, and the natural environment (Wu et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Genetic diversity among species can complicate management efforts because different genotypes and pathotypes require specific measures tailored to their unique virulence. Genetic variability directly influence plant-nematode interactions, potentially linking it to the gene expression. In the case of \u0026ldquo;\u003cem\u003eHeterodera schachtii\u0026rdquo;\u003c/em\u003e distinct variations in biological characteristics has been observed, including egg hatching, the attraction of second stage juvenile (J2) nematodes, their penetration of plant roots, the forming the feeding sites, and the overall reproduction rate (Nuaima and Heuer, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Research on the rice root-knot nematode in Java shows that population exhibit significant, indicates genetic variability both within and between provinces. This suggests that \u003cem\u003eM. graminicola\u003c/em\u003e population in Java are highly adaptive to a range of conditions and may exhibit different level of pathogenicity. Furthermore, a study has indicated that genetic diversity of \u003cem\u003eMeloidogyne incognita\u003c/em\u003e arises from alternative adaptation strategies to different cultivars. Genome-wide association analyses have shown a correlation between \u003cem\u003eM. incognita\u003c/em\u003e genotype and phenotype, particularly regarding the nematode\u0026rsquo;s virulenc against specific the plant cultivars (Asamizu et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, the genetic diversity of \u003cem\u003eM. graminicola\u003c/em\u003e among populations in Java is low due to high variability within the populations. The genetic variability of \u003cem\u003eM. graminicola\u003c/em\u003e within populations in West Java, Central Java, and East Java is notably high. This is evidenced not only by haplotype diversity, but also from the Fst index. Additionally, the percentage of variation within population (108.37%) is, greater than that among populations (-8.37%). The reproductive strategy of these rice root-knot nematodes also plays a crucial role in determining the genetic variability within the populations. As a result of this genetic variability among \u003cem\u003eM. graminicola\u003c/em\u003e within populations in Java, the species exhibit highly adaptable strategies under various conditions, which can influence its level of pathogenicity. Given the genetic variability of \u003cem\u003eM. graminicola\u003c/em\u003e population, it is important to consider these factors in managing the population of \u003cem\u003eM. graminicola.\u003c/em\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY STATEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank Universitas Gadjah Mada (UGM) for providing research funding through the Final Assignment Recognition Program, under contract No. 5286/UN1.P1/PT.01.03/2024. Also thank UGM Press as university publisher for the language editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHORS\u0026rsquo; CONTRIBUTION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. [SI] made contribution on the research conceptualization; [MT] performed the material preparation, data collection, analysis, and drafted original manuscript; [SI], [AT], and [AS] were supervised and revised the manuscript for important content. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAksenov AP, Spiridonov SE (2013) Diversity of the rDNA ITS haplotypes of the nematodes \u003cem\u003eHaemonchus contortus\u003c/em\u003e (Trichostrongyloidea, Rhabditida) of the same host. 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The University of Chicago Press, US.\u003c/li\u003e\n\u003cli\u003eWu Q, Zang F, Ma Y, Zheng Y, Zang D (2020) Analysis of genetic diversity and population structure in endangered \u003cem\u003ePopulus wulianensis\u003c/em\u003e based on 18 newly developed EST-SSR markers. GECCO 24:1-13. https://doi.org/10.1016/j.gecco.2020.e01329.\u003c/li\u003e\n\u003cli\u003eZhao YB, Zhang Y, Zhang QC, Li HJ, Cui YQ, Xu Z, Jin L, Zhou H, Zhu H (2015) Ancient DNA reveals that the genetic structure of the northern Han Chinese was shaped prior to 3,000 years ago. PLoS ONE 10:1\u0026ndash;17. https://doi.org/10.1371/journal.pone.0125676.\u003c/li\u003e\n\u003cli\u003eZhong-ling T, Maria M, Barsalote EM, Castillo P, ZHENG J-wu (2018) Morphological and molecular characterization of the rice root-knot nematode, \u003cem\u003eMeloidogyne graminicola\u003c/em\u003e, Golden and Birchfeild, 1965 occurring in Zhejiang, China. 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Front Plant Sci 8:1\u0026ndash;13. https://doi.org/10.3389/fpls.2017.01644.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1 and 2","content":"\u003cp\u003eTable 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Haplotype diversity, population structure, rice root-knot nematode","lastPublishedDoi":"10.21203/rs.3.rs-5629720/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5629720/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRice root-knot nematode, \u003cem\u003eMeloidogyne graminicola\u003c/em\u003e is widely distributed globally, including in Indonesia, where it may influence genetic diversity among local populations. Understanding this genetic diversity is essential for developing effective management strategies for this nematode. This study aimed to investigate the genetic diversity of \u003cem\u003eM. graminicola\u003c/em\u003e in Java, Indonesia. Population samples were collected from West Java, Central Java, and East Java. Species identification was performed using specific primers Mg-F3/Mg-R2. All samples were sequenced and analysed for phylogenetic analyses, genetic distances, haploid diversity, and population structure. The results confirmed that all samples from Java were \u003cem\u003eM. graminicola\u003c/em\u003e and were closely related an isolate from the Philippines. The haploid diversity (Hd) of the \u003cem\u003eM. graminicola\u003c/em\u003e population in Java was high (Hd\u0026thinsp;=\u0026thinsp;1) and the nucleotide diversity (π\u0026thinsp;=\u0026thinsp;0.06357). The Fst index indicated that there was no significant genetic difference among populations in Java, categorizing the overall genetic diversity as low (Fst = -0.08370). The haplotype network analysis further revealed that the Java populations did not form a single haplogroup, suggesting that each isolate in Java possessed a unique haplotype. This research highlighted that while \u003cem\u003eM. graminicola\u003c/em\u003e populations in Java display high genetic diversity within individual population, this could potentially impact the virulence levels of these nematodes. The insights on genetic diversity of \u003cem\u003eM. graminicola\u003c/em\u003e in Java could inform better management practices for controlling this pest.\u003c/p\u003e","manuscriptTitle":"Genetic Diversity of Meloidogyne graminicola on Rice in Java Indonesia Based on Ribosomal DNA Gene","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-01 11:42:39","doi":"10.21203/rs.3.rs-5629720/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"038ebfab-4ad2-42a4-bc7c-b683ec3c32ef","owner":[],"postedDate":"January 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-05T15:57:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-01 11:42:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5629720","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5629720","identity":"rs-5629720","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}