Genetic Diversity and Population Structure of Tangerine and Mandarin Citrus Accessions from Indonesia using SSR and SCoT Markers

Genetic Diversity and Population Structure of Tangerine and Mandarin Citrus Accessions from Indonesia using SSR and SCoT Markers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetic Diversity and Population Structure of Tangerine and Mandarin Citrus Accessions from Indonesia using SSR and SCoT Markers Kristianto Nugroho, Tri Joko Santoso, Mia Kosmiatin, Dewi Sukma, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4471294/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Aug, 2024 Read the published version in Genetic Resources and Crop Evolution → Version 1 posted 10 You are reading this latest preprint version Abstract Citrus is one of prominent horticultural crops that highly consumed by people around the world. Indonesia, as a country being located near the equator, has several local accessions of tangerine and mandarin citrus that remain poorly characterized. Thus, assessment of their genetic diversity will facilitate us in adequately identifying accessions conferring important traits suitable for breeding program. The objective of this study was to analyze the genetic diversity of Indonesia’s local accessions of tangerine and mandarin citrus using SSR and SCoT markers. Fifty three citrus genotypes representing 8 tangerine accessions, 28 mandarin accessions, and 17 outgroup accessions were subjected to genetic diversity analysis using 20 SSR and SCoT markers. The number of alleles detected by SCoT markers was higher than by SSR markers accounted for 137 and 107, respectively, while the number of alleles at each locus detected by ScoT and SSR markers varied from 6 to 12 and 2 to 10, respectively. Additionally, 19 SCoT and 18 SSR markers with PIC value greater than 0.5 were identified, indicating their potential as highly informative markers in citrus breeding programs. The phylogenetic tree and PCoA plot constructed from both SSR and SCoT markers revealed clearly discrimination of tangerine, mandarin, and outgroup accessions. The AMOVA results showed a higher genetic variation observed within populations in comparison to that among populations, indicating high cross-pollination in the citrus accessions used in the study. The population structure, represented by the highest delta K value of K = 2 in SSR markers and K = 3 in SCoT markers, also revealed evidence of genes flow occurred among citrus populations. The results of this study would beneficially provide an important information for citrus breeding strategies in the future. citrus germplasms cross-pollination delta K genes flow informative markers PIC Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Citrus is a valuable horticultural crop that is consumed throughout the world. Its fruits can be consumed freshly or processed into juice, jams, pastes, and sweet candy. Citrus fruit are appreciated for their attractive color, refreshing taste, and aroma (Zou et al. 2016 ). They are also highly nutritious, containing carbohydrates, protein, fiber, vitamin C, A, and E, minerals, flavonoids, hesperidin, carotenoids, and other beneficial compounds that help promote good health (Zou et al. 2016 ; Rafiq et al. 2018 ; Adenaike and Abakpa 2021 ). Citrus fruits are rich in vitamin C and fibre, which can help boost endurance, protect cells from free radicals and improve digestion (Mohanapriya et al. 2013 , Rafiq et al. 2018 ). Citrus is one of the top three fruits traded internationally, along with grapes and apples (Abobatta 2019 ). It grows well in tropical, subtropical, and temperate regions, and in different conditions such as humid, semi-arid, or arid. The annual production of citrus reaches 102 million tons leads by China, Brazil, Mexico, Spain, and United States as the main citrus-producing countries in the world (Mehl et al. 2014 ; Abobatta 2019 ; Haque et al. 2022 ). Tangerine ( Citrus nobilis L.) and mandarin ( Citrus reticulata Blanco.) are two citrus fruits that are popular in Indonesia which locally, the former known as siam citrus and the latter known as keprok citrus. It is reported that a high consumption rate of citrus in Indonesia reach 4.269 kg per capita per year in 2021 and a total production of 2,401,064 tons in the same year (Ministry of Agriculture-Republic of Indonesia 2022 ). Indonesia, being located in the equatorial zone, has many local accessions of tangerine and mandarin that possess high genetic diversity. This makes them ideal for citrus breeding program in Indonesia. The availability of citrus germplasms with high genetic diversity is essenstial in such programs (Wolter et al. 2019 ). Moreover, genetic diversity analysis is crucial in protecting and preserving plant genetic resources (Tonogbanua and Espino 2017). Analysis of the genetic diversity of citrus species can be done using morphological, biochemical, or molecular markers. The use of molecular markers have several advantages, such as early-stages testing without waiting for plants to mature, unaffected by the environmental factor, elucidating accessions with very close relationships, having high reproducibility, and having broader genome coverage (Bhandari et al. 2017 ; Nadeem et al. 2018 ). Simple Sequence Repeats (SSR) and Start Codon Targeted (SCoT) are molecular markers that can be used in genetic diversity analysis of citrus species. SSR or microsatellites are tandem repeat sequences with a length of 1–6 nucleotides, which are distributed in the genomes of eukaryotic organisms (Shahzadi et al. 2014 ). The advantages of this marker include having a high level of polymorphism, codominant, high abundance in eukaryotic genomes, and having a higher level of reproducibility compared to other markers such as Random Amplified Polymorphic DNA (RAPD) or Inter Simple Sequence Repeat (ISSR) (Woo et al. 2020 ). Previous studies have shown that SSR markers are widely used in the genetic diversity analysis of citrus germplasms around the world (Hamza 2013 ; Shahzadi et al. 2014 ; Sharma et al. 2015 ; Mahjbi et al. 2016 ; Woo et al. 2020 ; Kaur et al. 2022 ). Recently, SCoT markers are also type of molecular markers commonly used in genotyping activities that are directly related to certain functional genes and are widely used in genotyping activities and polymorphism analysis (Vanijajiva 2020 ). This marker was designed on short conserved sequences flanking the START codon (ATG) in genome of an organism (Amom and Nongdam 2017 ). SCoT markers are universal, dominant, and consists of only one primer that acts as forward and reverse. They have a length of around 18 mer and an annealing temperature of 50°C, making them more reproducible than RAPD and ISSR (Collard and Mackill 2009 ). Unlike RAPD or ISSR markers, SCoT markers have a specific gene target and a relationship with certain functional traits (Rai 2023 ). The use of the SCoT markers in analyzing the genetic diversity of citrus germplasms in the world has also been widely reported in various study (Han et al. 2011 ; Mahjbi et al. 2015 ; Wu et al. 2016 ; Juibary et al. 2021 ; and Kulyan et al. 2023 ). The objective of this study was to analyze the genetic diversity of tangerine and mandarin citrus local accessions in Indonesia using SSR and SCoT markers. The information on genetic relationship and structrure population data obtained from this study is expected to aid the maintenance of Indonesia’s citrus germplasms collection, thereby accelerating the citrus breeding program in the future. Materials and methods Genetic materials In this study, 53 citrus accessions including 8 tangerine accessions, 28 mandarin accessions, and 17 outgroup accessions i.e lemon, lime, sweet orange, and pummelo were used as plant genetic materials (Table 1 ). Most of the citrus materials used in this study were collected from the Agricultural Instrument Standardization Agency for Citrus and Subtropical Fruits (BSIP Jestro) in Malang, East Java, Indonesia while the rest were obtained from Agricultural Instrument Standardization Agency for Agricultural Biotechnology and Genetic Resources (BBPSI Biogen) in Bogor, West Java, local farmers, and local markets. Table 1 List of mandarin and tangerine citrus accessions used in this study No. Citrus accession name Species Geographical origin Collection origin Part of plant used for DNA extraction 1. Siam Pontianak Citrus nobilis Pontianak, West Kalimantan BSIP Jetsro Leaf 2. Siam Gunung Omeh C. nobilis Lima Puluh Kota, West Sumatra BSIP Jetsro Leaf 3. Siam Kintamani C. nobilis Kintamani, Bali BSIP Jetsro Leaf 4. Siam Banjar C. nobilis Banjarmasin, South Kalimantan BSIP Jetsro Leaf 5. Siam Madu C. nobilis Karo, North Sumatra BSIP Jetsro Leaf 6. Siam Banyuwangi C. nobilis Banyuwangi, East Java Local farmer Leaf 7. Sinta Ponsoe C. nobilis var Pontianak x C. Reticulata var SoE Improved variety BSIP Jestro Leaf 8. Sitaya Agrihorti C. nobilis West Kalimantan BSIP Jestro Leaf 9. Keprok Garut C. reticulata Garut, West Java BSIP Jestro Leaf 10. Keprok Borneo C. reticulata East Kalimantan BSIP Jestro Leaf 11. Keprok Tawangmangu C. reticulata Tawangmangu, Central Java BSIP Jestro Leaf 12. Keprok Pulung C. reticulata Ponorogo, East Java BSIP Jestro Leaf 13. Keprok Selayar C. reticulata Selayar Island, South Sulawesi BSIP Jestro Leaf 14. Keprok Madura C. reticulata Madura Island, East Java BSIP Jestro Leaf 15. Keprok Siompu C. reticulata Buton, South East Sulawesi BSIP Jestro Leaf 16. Keprok Tejakula C. reticulata Tejakula, North Bali BSIP Jestro Leaf 17. Keprok Kacang Solok C. reticulata Solok, West Sumatra BSIP Jestro Leaf 18. Keprok Gayo C. reticulata Gayo, Aceh BSIP Jestro Leaf 19. Keprok Brasitepu C. reticulata Karo, North Sumatra BSIP Jestro Leaf 20 Keprok Rimau Gerga Lebong (RGL) C. reticulata Lebong, Bengkulu BSIP Jestro Leaf 21. Keprok Grabag C. reticulata Magelang, Central Java BSIP Jestro Leaf 22. Keprok Wangkang C. reticulata Ketapang, West Kalimantan BSIP Jestro Leaf 23. Keprok Pulau Tengah C. reticulata Kerinci, Jambi BSIP Jestro Leaf 24. Keprok Sipirok C. reticulata Sipirok, North Sumatra BSIP Jestro Leaf 25. Keprok Batu 55 C. reticulata Malang, East Java BSIP Jestro Leaf 26. Keprok SoE C. reticulata SoE, East Nusa Tenggara Local market Leaf 27. Keprok Terigas C. reticulata Sambas, West Kalimantan BSIP Jestro Leaf 28. Kertaji C. reticulata Improved variety BSIP Jestro Leaf 29. Crifta-01 C. reticulata Improved variety BSIP Jestro Leaf 30. JRM 2012 C. reticulata Introduction BSIP Jestro Leaf 31. Krisma Agrihorti C. reticulata Bulungan, East Kalimantan BSIP Jestro Leaf 32. Monita Agrihorti C. reticulata Improved variety BSIP Jestro Leaf 33. Topazindo Agrihorti C. reticulata Improved variety BSIP Jestro Leaf 34. Keprok Selwasa C. reticulata Marantutul, Southeast Maluku BSIP Jestro Leaf 35. Keprok Maga C. reticulata Mandailing Natal, North Sumatra BSIP Jestro Leaf 36. D.N. Sabilulungan ( C. unshiu x sinensis ) x C. Poonensis Introduction BSIP Jestro Leaf 37. Proksi-1 Agrihorti Protoplast fusion between Siam Madu and Mandarin Satsuma Improved variety BBPSI Biogen Leaf 38. Japansche citroen C. limonia Introduction BSIP Jestro Leaf 39. Ponkam C. poonensis Introduction Local market Peel 40. Sunkist Valencia Egypt C. sinensis Introduction Local market Peel 41. Lemon C. limon Introduction Local market Peel 42. Nipis C. aurantifolia Local Local market Peel 43. Limau Citrus amblycarpa Local Local market Peel 44. Orange jasmine Murraya paniculata Local Local farmer Leaf 45. Carrizo-442 Citrus insitoum Introduction BSIP Jestro Leaf 46. Rough lemon Citrus jambhiri Introduction BSIP Jestro Leaf 47. Troyer-415 Poncirus trifoliata x C. sinensis Introduction BSIP Jestro Leaf 48. Pangkajene Putih C. maxima Pangkajene Kepulauan, South Sulawesi BSIP Jestro Leaf 49. Raja C. maxima Local BSIP Jestro Leaf 50. Magetan C. maxima Magetan, Central Java BSIP Jestro Leaf 51. Kunci-1 C. microcarpa Local BSIP Jestro Leaf 52. Kalamansi FR C. microcarpa Bengkulu BSIP Jestro Leaf 53. Nipis Borneo C. aurantifolia Kalimantan BSIP Jestro Leaf Genomic DNA Extraction The citrus genomic DNA extraction was performed using the modified Doyle and Doyle ( 1990 ) method. DNA quantity was measured using NanoDrop™ 2000 Spectrophotometers (ThermoScientific, USA) while DNA quality was separated using 1% (w/v) agarose gel electrophoresis. The DNA stock solutions then diluted to concentrations of 10 ng/µL and stored at − 20°C for polymerase chain reaction (PCR) activities. SSR analysis The study utilized a total of 20 SSR markers from various references as shown in Table 2 . For each sample, as many as 10 µL total reaction volume was prepared, consisting of 2 µL of 10 ng/µL DNA template, 5 µL of 2x MyTaq ™ HS Red Mix (Bioline), 0.5 µL of 10 µM forward and reverse primers, and sterile ddH 2 O. PCR analysis was performed in a T100 Thermal Cycler (Bio-Rad, USA) with the following PCR profiles: initial denaturation at 95°C for 5 minutes, followed by 35 cycles of denaturation at 94°C for 30 seconds, annealing at 55°C for 1 minute, and extension at 72°C for 1 minute. The PCR reaction was ended with a final extension at 60°C for 15 minutes. The PCR products were separated using 6% (w/v) non-denaturing polyacrylamide gel electrophoresis in 1× TBE buffer, stained with 10 mg/mL ethidium bromide solution, and visualized under UV light using a UV Transilluminator (Bio-Rad, USA). SCoT analysis In this study, a total of 20 SCoT markers designed by Collard and Mackill ( 2009 ) (Table 3 ) were also used for genotyping the 53 citrus accessions with the same PCR amplification reactions as described in SSR markers. The PCR amplification was carried out in a T100 Thermal Cycler (Bio-Rad, USA) consisting of: initial denaturation at 95°C for 5 minutes, then 40 cycles of denaturation at 94°C for 30 seconds, annealing at 50°C for 1 minute, and extension at 72°C for 1 minute, ended by a final extension at 60°C for 15 minutes. The PCR products were separated using 1.5% (w/v) agarose gel electrophoresis in 1× TAE buffer, stained with 10 mg/mL ethidium bromide solution, and visualized under UV light using a UV Transilluminator (Bio-Rad, USA). Table 2 List of SSR markers used in this study No. Marker’s name Sequence (5’-3’) Repeat motif Tm ( o C) References 1. CMS-8 F: CCAAACATCTGCGGATCC R: AGAAGAACCCAGATTCCAAATG (CT) 11 59.2 57.7 Ahmad et al. ( 2003 ) 2. CMS-21 F: TAGGCCAAATCTTATTCATGCC R: TCAGGGTCATAAGGAATGGC (CA) 10 56.6 58.3 Ahmad et al. ( 2003 ) 3. CMS-24 F: TTATTGTCCCCAATTGTGAGC R: TCCAGATTGAGGGGAAAAAG (CA) 20 (TA) 5 57.6 58.3 Ahmad et al. ( 2003 ) 4. CMS-30 F: AACACCCCTTGGAGGGAG R: GCTGTTCACACACACAACCC (CT) 9 (CA) 5 64.8 61.6 Ahmad et al. ( 2003 ) 5. CMS-34 F: GCACTAAGCAGAATGCGTGT R: GCCGTCGTTTTACATTCAAGA (CA) 39 (AT) 11 58.6 57.3 Ahmad et al. ( 2003 ) 6. CMS-45 F: CGACCACTCCACCTACGATG R: GCCGTTAATTCCTGCTTTCA (CTT) 7 63.2 57.6 Ahmad et al. ( 2003 ) 7. CCSM 06 F: ATCTGTGTGAGGACTGAA R: CCTCTATTAATGTGCCTG (AG) 21 50.0 47.0 Cristofani-Yaly et al. 2011 8. CCSM 40 F: ACAAGAGTCGCAACAATC R: GACAACAGTGGCAATACC (GCAACA) 10 50.2 51.0 Cristofani-Yaly et al. 2011 9. CCSM 68 F: ACATGGACAGGACAACTAAG R: CACTTCTGCCTTGCTATG (AG) 18 51.8 50.7 Cristofani-Yaly et al. 2011 10. CCSM 77 F: TATCCAACCATGTGTGTCCATA R: CACTAGGTCACCATTAATTG (AG) 18 53.5 48.2 Cristofani-Yaly et al. 2011 11. CCSM 95 F: AAGAAGCTCTCACCTCTC R: TAACGTCTGAACGAACTG (TC) 18 50.7 49.2 Cristofani-Yaly et al. 2011 12. CCSM 111 F: TGATACATAATATGGGATAG R: TTAGTGATTCGTGGAGC (AG)n 43.0 48.7 Cristofani-Yaly et al. 2011 13. CCSM 112 F: ATGCCATTATGTGTGTG R: CAGACCTGAACATAACTC (TC) 7 CG(TG) 4 (AG) 20 47.0 46.9 Cristofani-Yaly et al. 2011 14. CCSM 156 F: GTCTCTGTTGTGTGTCGGTT R: ACGAAGTGAAGTGTGTAATG (TC) 20 55.0 50.2 Cristofani-Yaly et al. 2011 15. BM-CiSSR-12 F: GGGCTCAGTTCTTCTCTACTC R: GCATTAGGCTTCTCTCATACC (TTA) 15 59.6 56.7 Woo et al. (2019) 16. BM-CiSSR-013 F: GGTGGCATACATACATACATACA R: GCAACATCTGGAACTACTCA (TA) 6 54.8 56.2 Woo et al. (2019) 17. BM- CiSSR-115b F: CGGTGTGTATTGGGTACACG R: GCTTTTTCGAAAGCGTCAAG (TA) 17 60.5 56.5 Woo et al. (2019) 18. BM- CiSSR-159 F: ATGACCTCAAACGGTGAGCA R: CTTCCACATCCGAACCGACA (GAGG) 5 61.3 63.1 Woo et al. (2019) 19. BM- CiSSR-162 F: GCTAGGGTTCCAGACTTCCAG R: GATTTGGCCGATCGAAAGCC (AAT) 10 (CAT) 6 63.3 61.8 Woo et al. (2019) 20. BM- CiSSR-272 F: ATAGGTCCCCACAATGGAAA R: GGGCATAAATGAATTGGGTC (GAA) 8 59.1 56.5 Woo et al. (2019) Table 3 List of SCoT markers used in this study No. Marker’s name Sequence (5’-3’) Tm ( o C) Reference 1. SCoT-1 CAACA ATG GCTACCACCA 52.6 Collard and Mackill ( 2009 ) 2. SCoT-2 CAACA ATG GCTACCACCC 53.6 Collard and Mackill ( 2009 ) 3. SCoT-3 CAACA ATG GCTACCACCG 53.9 Collard and Mackill ( 2009 ) 4. SCoT-4 CAACA ATG GCTACCACCT 52.3 Collard and Mackill ( 2009 ) 5. SCoT-7 CAACA ATG GCTACCACGG 53.9 Collard and Mackill ( 2009 ) 6. SCoT-8 CAACA ATG GCTACCACGT 52.9 Collard and Mackill ( 2009 ) 7. SCoT-13 ACGAC ATG GCGACCATCG 58.0 Collard and Mackill ( 2009 ) 8. SCoT-14 ACGAC ATG GCGACCACGC 61.3 Collard and Mackill ( 2009 ) 9. SCoT-15 ACGAC ATG GCGACCGCGA 62.6 Collard and Mackill ( 2009 ) 10. SCoT-16 ACC ATG GCTACCACCGAC 57.3 Collard and Mackill ( 2009 ) 11. SCoT-17 ACC ATG GCTACCACCGAG 57.1 Collard and Mackill ( 2009 ) 12. SCoT-18 ACC ATG GCTACCACCGCC 60.7 Collard and Mackill ( 2009 ) 13. SCoT-19 ACC ATG GCTACCACCGGC 60.7 Collard and Mackill ( 2009 ) 14. SCoT-20 ACC ATG GCTACCACCGCG 60.8 Collard and Mackill ( 2009 ) 15. SCoT-21 ACGAC ATG GCGACCCACA 59.7 Collard and Mackill ( 2009 ) 16. SCoT-22 AACC ATG GCTACCACCAC 55.0 Collard and Mackill ( 2009 ) 17. SCoT-23 CACC ATG GCTACCACCAG 55.7 Collard and Mackill ( 2009 ) 18. SCoT-24 CACC ATG GCTACCACCAT 54.8 Collard and Mackill ( 2009 ) 19. SCoT-25 ACC ATG GCTACCACCGGG 60.2 Collard and Mackill ( 2009 ) 20 SCoT-26 ACC ATG GCTACCACCGTC 57.3 Collard and Mackill ( 2009 ) Data analysis Amplification products of both the SSR and SCoT markers were scored as binary data, with each visible band being considered as one allele. A score of 1 and 0 was given for the presence and absence of a band, respectively. In order to estimate each band's size produced by each primer, GelAnalyzer (Lazar 2010 ) was applied in scoring. A phylogenetic tree was constructed using the Unweighted Pair Group Method with the Arithmetic (UPGMA) program based on Nei's genetic distance (1983), available on PowerMarker 3.25 (Liu and Muse 2005 ). The major allele frequency, gene diversity, observed heterozygosity, and Polymorphism Information Content (PIC) value were also determined using PowerMarker 3.25 (Liu and Muse 2005 ). Analysis of molecular variance (AMOVA) were perfomed using GenAlEx 6.5 (Peakall and Smouse 2012 ), while the principal coordinate analysis (PCoA) were assembled using DARwin 6 (Perrier and Jacquemoud-Collet 2006 ). The population structure model was analyzed using STRUCTURE 2.3.4 (Pritchard et al. 2000 ). The data collection involved 10,000 replications of the burn-in period, followed by 100,000 replications of the Markov Chain Monte Carlo (MCMC) along with the admixture model. Ten independent runs were conducted for each K value (ranging from 1 to 10) (Evanno et al. 2005). The results were then submitted to StructureSelector ( https://lmme.ac.cn/StructureSelector/ ) (Li and Liu 2017 ) to determine the best K value. Results SSR analysis Genetic diversity analysis was performed on 53 citrus accessions using 20 SSR markers. The analysis showed polymorphic bands, which are presented in Fig. 1 . A total of 107 alleles were identified in this study. The number of alleles per locus ranged from 2 (CCSM111) to 10 (BmCiSSR 159 and BmCiSSR 272) with average 5.35 alleles per marker (Table 4 ). The allele size varied from 70 to 488 bp. The major allele frequency value ranged from 0.077 (BmCiSSR-115b) to 0.412 (CCSM111) with an average of 0.144. Gene diversity varied from 0.752 (CCSM111) to 0.967 (BmCiSSR-159) with an average of 0.925. Observed heterozygosity values ranged from 0.075 (CMS-34) to 0.980 (BmCiSSR-162) with an average of 0.596. PIC value, which reflects the informativeness level of the markers, ranged from 0.450 (CCSM111) to 0.929 (BmCiSSR-159) with an average of 0.920. According to criteria set by Botstein et al. ( 1980 ), 18 SSR markers used in this study were highly informative, with a PIC value greater than 0.5. Table 4 Statistical summary of SSR markers polymorphism used in this study Markers Range of allele size (bp) Allele number Major allele frequency Gene diversity Observed heterozigosity PIC CMS-8 132–179 4 0.198 0.887 0.208 0.622 CMS-21 114–154 4 0.163 0.908 0.462 0.722 CMS-24 118–211 7 0.132 0.935 0.642 0.771 CMS-30 126–183 5 0.094 0.949 0.830 0.836 CMS-34 279–329 4 0.170 0.921 0.075 0.714 CMS-45 173–237 5 0.104 0.947 0.679 0.825 CCSM 06 187–210 6 0.094 0.954 0.906 0.752 CCSM 40 117–214 7 0.151 0.934 0.528 0.705 CCSM 68 84–109 3 0.179 0.893 0.566 0.450 CCSM 77 93–121 3 0.144 0.926 0.885 0.703 CCSM 95 65–148 6 0.160 0.915 0.396 0.691 CCSM 111 82–99 2 0.412 0.752 0.118 0.489 CCSM 112 70–107 4 0.100 0.946 0.520 0.800 CCSM 156 83–115 3 0.125 0.925 0.423 0.715 BM-CiSSR-12 248–325 7 0.087 0.953 0.750 0.841 BM-CiSSR-013 105–132 4 0.170 0.918 0.906 0.732 BM- CiSSR-115b 184–255 6 0.077 0.963 0.731 0.879 BM- CiSSR-159 298–488 10 0.085 0.967 0.887 0.929 BM- CiSSR-162 152–259 7 0.082 0.965 0.980 0.881 BM- CiSSR-272 245–475 10 0.144 0.949 0.423 0.812 Total 107 Mean 5.35 0.144 0.925 0.596 0.743 Phylogenetic analysis using SSR markers clearly revealed separation among tangerine, mandarin, and outgroup citrus accessions (Fig. 2 ). Since there was no clear differentiation of citrus accessions by geographic origin, the clustering pattern observed in present study was based on the genetic background variation. The analysis of Nei's genetic distance showed that mandarin and outgroup accessions had the highest genetic distance values (0.740), while tangerine and outgroup accessions had the lowest ones (0.570) (Table 5 ). It is interesting to note that five outgroup citrus accessions, including lemon, sunkist Valencia Egypt, Japansche citroen, ponkam, and Proksi-1 Agrihorti were grouped together with mandarin accessions. These findings highlight the importance of genetic background in the determination of clustering patterns among citrus accessions. Table 5 Genetic distance among three citrus populations based on SSR markers Populations Tangerine Mandarin Outgroup Tangerine 0.000 Mandarin 0.640 0.000 Outgroup 0.570 0.740 0.000 PCoA analysis showed a similar clustering pattern of citrus accessions with that previously identified by the UPGMA method in the phylogenetic tree. In Fig. 3 , all the citrus accessions were distributed in four quadrants in two major coordinates. The outgroup accessions (shown in red) were mainly distributed in quadrant 1, while the tangerine accessions (shown in yellow) were in quadrant 3. The mandarin accessions, represented by green were spread between quadrant 2 and 4. The PCoA plot also revealed that five outgroup citrus accessions including sunkist Valencia Egypt, lemon, ponkam, Japansche citroen, and Proksi-1 Agrihorti were distributed together with the mandarin accessions as previously seen in the phylogenetic tree. AMOVA over 20 SSR markers revealed that 7% of the variance was observed among the population, while 93% was within the population (Table 6 ). The analysis of population structure of SSR markers successfully classified the 53 citrus accessions into two subpopulations withthe highest delta K value at K = 2. The first and the second subpopulations each were represented by a green and a red line (Fig. 4 ). It is noted that Tangerine and outgroup accessions combined in subpopulation 1 are in accordance with both the phylogenetic and Nei's genetic distance results, whereas Mandarin accessions left in subpopulation 2. A total of 13 mandarin accessions, such as Keprok Tejakula, Keprok Rimau Gerga Lebong, Keprok Wangkang, Keprok Pulau Tengah, Keprok Batu55, Keprok SoE, Keprok Terigas, Kertaji, JRM 2012, Krisma Agrihorti, Topazindo Agrihorti, Keprok Maga, and D.N. Sabilulungan possessed mixing colors reflecting gene flow was occured between populations which lead to genetic recombination. Table 6 AMOVA among 53 citrus accessions based on SSR markers used in this study Source df Sum of squares Mean square Estimation of variance Percentage of total variance p-value Among populations 2 60.206 30.103 0.670 7 < 0.01 Within populations 103 922.191 8.953 8.953 93 < 0.01 Total 105 982.396 9.624 100 SCoT analysis The analysis of 20 SCoT markers also revealed the presence of polymorphic bands, as illustrated in Fig. 5 . The total number of alleles detected was 164, which is higher than that obtained using SSR markers. The number of alleles per locus ranged from 6 (SCoT 26) to 12 (SCoT 23), with an average of 8.20 alleles per marker (Table 7 ). The size of the alleles varied from 210 to 2050 bp. The frequency of the major allele ranged from 0.375 (SCoT 2) to 0.500 (SCoT 13, SCoT 14, SCoT 21, SCoT 22, SCoT 23, SCoT 24), with an average of 0.468. The gene diversity ranged from 0.578 (SCoT 18) to 0.791 (SCoT 26), averaging 0.723. The observed heterozygosity values ranged from 0.509 (SCoT 19) to 1.000 (SCoT 3, SCoT 16, SCoT 17, SCoT 22, and SCoT 24), averaging 0.984. The PIC values, which reflect the level of informativeness of the markers, ranged from 0.490 (SCoT 18) to 0.779 (SCoT 26), with an average of 0.698. According to the criteria established by Botstein et al. ( 1980 ), all the SCoT markers used in this study, except SCoT 18, were highly informative, as their PIC values were greater than 0.5. The analysis of the SCoT markers for phylogeny also showed that tangerine, mandarin, and outgroup citrus accessions were separated, in accordance with the cluster resulted from SSR (Fig. 6 ). However, unlike the SSR results, the tangerine accessions were found to cluster with the Mandarin accessions. Similar with SSR markers analysis, clustering of citrus accessions constructed from SCoT markers was also caused by genetic background of citrus accession and not by geographic origin. The genetic distance values from Nei's analysis of SCoT markers (Table 8 ) showed that the highest genetic distance was found between the tangerine and outgroup (0.409), while the lowest one was between the tangerine and mandarin (0.206). Interestingly, ten mandarin accessions, including Keprok Tawangmangu, Keprok Madura, Keprok Garut, Keprok Borneo, Keprok Pulung, Keprok Siompu, Keprok Selayar, Keprok Kacang Solok, Keprok Gayo, and Keprok Brasitepu, clustered together with the tangerine group. Two outgroup accessions, namely Proksi-1 Agrihorti and Japansche Citroen were clustered together with Mandarin accessions. Table 7 Statistical summary of SCoT markers polymorphism used in this study Markers Range of allele size (bp) Allele number Major allele frequency Gene diversity Observed heterozigosity PIC SCoT 1 583–1534 8 0.050 0.977 0.980 0.633 SCoT 2 445–1761 9 0.063 0.973 0.958 0.757 SCoT 3 513–1560 8 0.060 0.979 1.000 0.597 SCoT 4 610–2050 10 0.058 0.980 0.731 0.732 SCoT 7 445–1889 8 0.049 0.981 0.941 0.654 SCoT 8 367–1108 5 0.038 0.981 0.923 0.718 SCoT 13 305–1463 8 0.057 0.975 0.962 0.716 SCoT 14 187–1286 8 0.047 0.981 0.906 0.708 SCoT 15 224–1482 8 0.030 0.987 0.900 0.744 SCoT 16 469–1373 8 0.078 0.969 1.000 0.736 SCoT 17 214–1480 8 0.066 0.977 1.000 0.706 SCoT 18 278–1458 9 0.058 0.975 0.904 0.490 SCoT 19 405–1485 6 0.085 0.967 0.509 0.744 SCoT 20 210–1344 8 0.050 0.980 0.880 0.748 SCoT 21 325–1606 10 0.050 0.980 0.960 0.710 SCoT 22 340–1442 9 0.047 0.979 1.000 0.724 SCoT 23 371–1864 12 0.048 0.977 0.981 0.655 SCoT 24 380–1470 9 0.077 0.972 1.000 0.671 SCoT 25 662–1807 7 0.038 0.983 0.865 0.732 SCoT 26 387–1597 6 0.038 0.983 0.962 0.779 Total 164 Mean 8.2 0.054 0.978 0.918 0.698 Table 8 Genetic distance among tangerine, mandarin, and outgroup populations genotyped by SCoT markers based on Nei’s genetic distance (1983) Populations Tangerine Mandarin Outgroup Tangerine 0.000 Mandarin 0.206 0.000 Outgroup 0.409 0.387 0.000 The results obtained from PCoA analysis of SCoT markers showed a similar clustering pattern to the one previously identified by the UPGMA method in the phylogenetic tree. The citrus accessions used in this study were distributed across four quadrants in two main coordinates, as shown in Fig. 7 . The tangerine and mandarin accessions were overlapped in quadrant 1 and 2, respectively, in line with the phylogenetic tree and Nei's genetic distance results. On the other hand, the outgroup accessions, represented by red color, were mostly distributed in quadrants 3 and 4, except for Proksi-1 Agrihorti and Japansche citroen, which existed in quadrant 2 with Mandarin accessions. AMOVA based on SCoT markers performed in this study revealed that 2% of the genetic variance was presence among populations, while 98% was found within the population (Table 9 ). This result is consistent with previous findings from SSR markers, suggesting that the genetic variation within a population is more significant than that among populations. Population structure analysis from SCoT markers indicated that the citrus accessions used in this study could be best classified into three subpopulations, as demonstrated by the highest delta K value at K = 3 (Fig. 8 ). The three subpopulations are represented by the colors red, green, and blue. All of the tangerine accessions and ten mandarin accessions combined in subpopulation 1 in accordance to phylogenetic tree and Nei’s genetic distance result. However, two Mandarin accessions (Siam Pontianak and Siam Gunung Omeh), and four Mandarin accessions (Keprok Brasitepu, Keprok Rimau Gerga Lebong, Keprok Grabag, and Keprok Terigas accessions) displayed mixing blue color, indicating their recombination with outgroup citrus accessions. Table 9 AMOVA result from SCoT analysis showed variance among 53 citrus accessions used in this study Source df Sum of squares Mean square Estimation of variance Percentage of total variance p-value Among populations 2 31.537 15.768 0.191 2% < 0.01 Within populations 103 1004.511 9.753 9.753 98% < 0.01 Total 105 1036.047 9.943 100% Discussion The genetic diversity analysis of citrus accessions based on molecular markers as revealed in this study could provide fundamental information in directing citrus breeding strategy and improvement. Present study compared the effectiveness of SCoT and SSR markers in identifying alleles and gene diversity in 53 citrus accessions. The use of SCoT markers could identify more alleles (137) than SSR markers (107). Additionally, SCoT markers could detect alleles with a higher maximum size of 2050 bp, while SSR markers could only detect alleles with a maximum size of 488 bp. Previous studies from Han et al. ( 2011 ) and Mahjbi et al. (2019), have also shown that SCoT markers can detect alleles with even larger sizes than those observed in this study. However, the SSR markers used in this study showed a greater average PIC value than SCoT markers. PIC value is a useful tool in determining the effectiveness of polymorphic loci in distinguishing genetic diversity among the genotypes (Ikten et al. 2023). Both SSR and SCoT markers used in this study showed an average PIC value of greater than 0.5, indicating their potential as highly informative markers in citrus breeding programs (Eltaher et al. 2018 ). Overall, the study suggests that genetic variation analysisi using a combination of SCoT and SSR markers can be useful in breeding and improving citrus fruit related traits. SSR and SCoT markers target a different portions of the plant genome. SSR markers target a flanking region of repeat sequence that highly abundant in plant genome, while SCoT markers target a flanking region of START codon (ATG) that highly conserved in related plant genes (Zhang et al. 2015 ; Jian et al. 2021 ). SSR is a codominant marker and can be used to distinguished between heterozygotes and homozygotes genotypes (Jian et al. 2021 ). This makes SSR markers are useful for highly heterozygous plant such as citrus. On the other hand, SCoT markers are dominant markers, and they cannot distinguish heterozygote genotypes. However, converting SCoT markers to codominant SCAR markers can solve this problem (Rai 2023 ). Both SSR and SCoT markers are highly polymorphic and reproducible, making them suitable for genetic diversity analysis, fingerprinting construction, sex determination, and the construction of linkage or assosiation maps (Vierira et al. 2016; Rai 2023 ). All of the SSR and SCoT markers utilized in this study demonstrated their robustness in identifying the genetic relationship from citrus accessions. The phylogenetic tree and PCoA plot clearly distinguished tangerine, mandarin, and outgroup citrus accessions. The SSR markers revealed a separation between tangerine and mandarin, while SCoT markers showed a mixture between mandarin and tangerine accessions. Based on SCoT markers, eleven mandarin accessions were grouped together with tangerine as presented in Figs. 7 and 8 . In accordance to this study, Martasari et al. ( 2023 ) previously reported about the mixing among mandarin and tangerine accessions in the similar cluster based on ISSR and SSR markers. This study also found that both SSR and SCoT markers could distinguished the accessions with similar name, between Nipis ( C. aurantifolia ) accession that collected from local market in Bogor, West Java with Nipis Borneo ( C. aurantifolia var. Borneo) accession that originated from Kalimantan island. The phylogenetic tree from SSR analysis also showed a separation from Kalamansi FR ( C. microcarpa ) with outgroup cluster, in line with previous study from Wu et al. ( 2018 ) that showed a separation of calamondin ( C. microcarpa ) from orange, lemon, pummelos, and lime group based on chloroplast genome. However, the study found that neither the SSR nor SCoT markers could separate orange jasmine ( M. paniculata ) accession from outgroup cluster. Orange jasmine is an ornamental plant commonly grown in home gardens. In contrast to our study, Penjor et al. ( 2013 ) and Nagano et al. ( 2018 ) reported separation of orange jasmine from true citrus cluster consisted of C. reticulata , C. maxima , and C. medica by using matK gene and RAD-seq respectively. The SSR and SCoT markers used in this study could also classified two accessions, namely Sinta Ponsoe and Proksi-1 Agrihorti, derived from breeding activities using mandarin and tangerine as their parentals. Sinta Ponsoe was created by hybridizing Siam Pontianak (tangerine group) and Keprok SoE (mandarin group) and it was clustered with the tangerine group in the phylogenetic tree and PCoA plot. Proksi-1 Agrihorti, on the other hand, was formed from protoplast fusion between Siam Madu (tangerine group) and Satsuma mandarin (mandarin group) and was classified as an outgroup accession. In the phylogenetic tree and PCoA plot, this accession clustered in the mandarin group. In contrast to those results, SSR and SCoT markers used in this study showed a different robustness in ponkam accession clustering, of which SSR markers classified ponkam in a mandarin group along with Proksi-1 Agrihorti and Japansche citroen ( C. limonia ), while SCoT markers classified it in an outgroup with sunkist valencia Egypt ( C. sinensis ), lemon ( C. limon ), and nipis ( C. aurantifolia ). According to Velasco and Licciardello ( 2014 ), ponkam is a hybrid derived from hybridization between mandarin ( C. reticulata ) and pummelo ( C. maxima ). In this case, SSR markers showed a better robustness in distinguishing citrus accessions used in this study. Furthermore, SSR and SCoT markers yielded different results in Nei’s genetic distance (1983). The genetic distance between tangerine and outgroup accessions was found to be close (0.570) using SSR markers, while SCoT markers revealed a closer genetic relationship between tangerine and mandarin accessions (0.206). According to Nicolosi et al. ( 2000 ), citrus taxonomy and phylogeny are still a very complex, disputable, and confusing problem, because of their cross compatibility between citrus species and related genera, high rate of bud mutations, the long history of cultivation, and wide dispersion. The taxonomy of citrus has gone through numerous system. The citrus taxonomy proposed by Scora ( 1975 ) and Barrett and Rhodes ( 1976 ) revealed that there were only three species constituted citrus ancestral, namely citron ( C. medica L.), mandarin ( C. reticulata Blanco), and pummelo ( C. grandis (L.) Osb.). The hybridization among these three species inherited other genotypes including commercial citrus found today. Previous molecular analysis using RAPD and SCAR markers reported by Nicolosi et al. ( 2000 ) successfully clustered eight citrus group consisting of citron, mandarin, pummelo, ichang, fortunella, and micrantha clusters. The mandarin cluster consisted of all mandarin ( C. reticulata ) and mandarin-like accessions such as C. tachibana , C. paradisi , C. aurantium , C. sinensis , C. junos , including C. nobilis (tangerine citrus). The result obtained from this study and Martasari et al. ( 2023 ) support the previous study by Nicolosi et al. ( 2000 ) that tangerine citrus is the member of mandarin group. The AMOVA from both SSR and SCoT markers showed that there was a higher variance within population than among population. This suggests that cross-pollination occured mostly in the citrus accessions used in this study. However, the results are contrary to those found by Barbhuiya et al. ( 2015 ) who discovered a higher variance among populations than within populations in C. medica populations from the Eastern Himalayan. This different of result could be due to the clonal propagation system by grafting, which may have increased the homogenity level at those populations. Citrus plants have unique reproduction systems. Some genotypes, such as Valencia orange, are capable of self-pollination, while other like mandarin and mandarin-hybrid require cross-pollination (Halder et al. 2019 ). Since, citrus pollen is heavy and sticky, it cannot be carried by wind, making the presence of insect pollinators crucial for pollination (Chacoff and Aizen 2007 ). However, whether insect pollinators play a significant rolein citrus pollination still a matter of debate. Certain genotypes, such as tangelos and tangerines, are known to require pollinator for better fruit sets (Halder et al. 2019 ). Interestingly, citrus plants can also reproduce clonally through apomixis, a natural process that result in a polyembryony phenomenon (Zhang et al., 2018 ), or artificially by human through grafting (Warschefsky et al. 2016 ). This leads to high heterozigosity in citrus species, which makes their taxonomy and phylogeny challenging to determine. The analysis of population structure from SSR markers demonstrated that the highest delta K value was obtained when K value was equal 2, indicating that all citrus accessions used in this study were best classified into two subpopulations. This result showed that tangerine and outgroup were classified in the same subpopulations, whereas the mandarin group was separated. Among these, 13 mandarin showed mixing color, which indicated gene flow between populations, leading to genetic recombination. On the other hand, SCoT markers showed that the highest delta K value was achieved when K was equal to3, indicating that three subpopulations were best classified for all of citrus accessions used in this study. The first subpopulation consisted of a mix of all Tangerine and ten Mandarin accessions. The second subpopulation consisted of 18 mandarin accessions including Proksi-1 Agrihorti and Japansche citroen from outgroup, while the third subpopulations consited of 15 outgroup accessions. According to this result, two tangerine accessions, namely Siam Pontianak and Siam Gunung Omeh, and also four Mandarin accessions namely Keprok Brasitepu, Keprok Rimau Gerga Lebong, Keprok Grabag, and Keprok Terigas showing mixing color representing their recombination with outgroup citrus accessions. The population structure obtained in this study corroborated with with AMOVA results, which showed that citrus accessions mostly underwent cross-polinaton between species and related genera, resulting in their heterogenity. Mandarin citrus is believed to have originated from the east coast of China and then spread to Formosa Island (now Taiwan) and Japan (Krueger and Navarro 2007 ). Many mandarin landraces and wild mandarins have been found in China, supporting the hypothesis that China is the center of origin of this species (Li et al., 2007 ). However, based on genomic analysis, proposed by Wu et al. ( 2018 ) revealed that the Southeast Himalaya region, which includes the Eastern part of Assam, Northern Myanmar, and Western China, are the center of origin of citrus species. The process by which mandarin and tangerine citrus were disseminated to Southeast Asia, especially to Indonesia, still needs to be clarified. In contrast to mandarin, tangerine ( C. nobilis ) is thought to have originated from a hybrid between mandarin ( C. reticulata ) and sweet orange ( C. sinensis ) (Krueger and Navarro 2007 ). This finding is supported by the population structure from SCoT analysis, which showed an admixture between mandarin and tangerine accessions in one subpopulation. The mandarin and tangerine accessions used in this study are probably came from a similar ancestral or shared partial ancestral. This hypothesis is supported by the results of the phylogenetic tree, both from SSR and SCoT analysis, which showed that the clustering of tangerine and mandarin accessions did not depend on geographical origins, but rather on their genetic background. This suggests that similarities still exist between tangerine or mandarin accessions, even if they originated from different islands and have been separated geographically for an extended period. Citrus genetic relationships are closely related to the dissemination pattern of citrus mother trees and seedlings, which has occurred for a long time, according to Agisimanto et al. ( 2007 ). Three locations in East Java Province, such as Tlekung-Batu, Purworejo, and Tulungagung have become the source of mother trees and scions for both distribution and production centers of citrus plants in Indonesia. Both tangerine and mandarin accessions used in this study might have undergone genetic improvement from their origin, either by hybridization, spontaneous mutations, adaptation to their geographical conditions, or human domestication, creating their new genetic diversity. The information on genetic diversity obtained from this study could be highly useful in managing, utilizing, and breeding citrus germplasm. It could also help in resolving the complexity of their taxonomy and phylogeny. The SSR and SCoT markers applied in present study have shown a high level of polymorphism and reproducibility, thus they are recommended as promising tools to be used for future genetic diversity analyses of citrus species. Performing a combination analysis of data obtained from molecular markers with those from morphological and biochemical markers in future studies will lead to gain more comprehensive results. Conclusion In this study, SSR and SCoT markers could reveal the genetic diversity among the tangerine, mandarin, and outgroup accessions. The phylogenetic tree and PCoA plot constructed from SSR and SCoT markers could distinguish among those three citrus populations. AMOVA resulted from both SSR and SCoT markers revealed a higher citrus variance within the population than among the population, reflecting the high frequency of cross-pollination in the citrus accessions observed in present study. The population structure also revealed gene flow among citrus populations that allegedly occurred due to the transfer of material genetics across the region in Indonesia. The result of this study could provide essential information for future citrus germplasm management, utilization, and breeding strategy. Declarations Author contributions Conceptualization and designing the work: KN, TJS, MK, DS, and AP. Formal analysis, investigation, and wrote original draft: KN. Supervision: TJS, MK, DS, and AP. Reviewed the draft and editing: TJS, MK, DS, AP, AH, R, and PL. Resources: MK, AH, TJS, and R. Funding acquisition: MK and PL. Funding This study was supported by Riset dan Inovasi untuk Indonesia Maju (RIIM) project, Badan Riset dan Inovasi Nasional (BRIN), second wave budget in the year of 2022-2023. Acknowledgements Authors gratefully acknowledged BSIP Jestro for supplying citrus genetic materials for this study and BBPSI Biogen for providing laboratory facilities. Conflict of interest The authors declare that they have no any conflict of interest References Abobatta WF (2019) Influence of climate change on citrus growth and productivity (effect of temperature). Adv Agricultural Technol Plant Sci 2:180036. https://doi.org/10.15406/mojes.2019.04.00168. Adenaike O, Abakpa GO (2021) Antioxidant compounds and health benefits of citrus fruits. European J Nutr Food Saf 13:65–74. https://doi.org/10.9734/ejnfs/2021/v13i230376. Agisimanto D, Martasari C, Supriyanto A (2007) Perbedaan primer RAPD dan ISSR dalam identifikasi hubungan kekerabatan genetik jeruk siam ( Citrus suhuniensis L. Tan) Indonesia. J Hortikultura 17:101–110. https://doi.org/10.21082/jhort.v17n2.2007. Ahmad R, Struss D, Southwick SM (2003) Development and characterization of microsatellite markers in Citrus . J Am Soc Hortic Sci 128: 584–590. https://doi.org/10.21273/JASHS.128.4.0584. Amom T, Nongdam P (2017) The use of molecular marker methods in plants: a review Int J Curr Res Rev 9:1–7. https://doi.org/10.7324/IJCRR.2017.9171. Barbhuiya AR, Khan ML, Dayanandan S (2015) Genetic structure and diversity of natural and domesticated populations of Citrus medica L. in the Eastern Himalayan region of Northeast India. Ecol Evol 6: 3898–3911. https://doi.org /10.1002/ece3.2174. Barrett HC, Rhodes AM (1976) A numerical taxonomic study of affinity relationships in cultivated Citrus and its close relatives. Syst Bot: 105–136. Bhandari HR, Bhanu AN, Srivastava K, Singh MN, Shreya, Hemantaranjan A (2017) Assessment of genetic diversity in crop plants-an overview. Adv Plants Agric Res 7:279–286. https://doi.org/ 10.15406/apar.2017.07.00255. Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet 32: 314–332. Chacoff NP, Aizen MA (2007) Pollination requirements of pigmented grapefruit ( Citrus paradisi Macf.) from Northwestern Argentina. Crop Sci 47:1143–1150. https://doi.org/10.2135/cropsci2006.09.0586. Cristofani-Yaly M, Novelli VM, Bastianel M, Machado MA (2011) Transferability and level of heterozygosity of microsatellite markers in citrus species. Plant Mol Biol Rep 29:418–423. https://doi.org/10.1007/s11105-010-0241-x. Collard BCY, Mackill DJ (2009). Start codon targeted (SCoT) polymorphism: a simple, novel DNA marker technique for generating gene-targeted markers in plants. Plant Mol Biol Rep 27:86–93. https://doi.org/10.1007/s11105-008-0060-5. Doyle JJ, Doyle JL (1990) Isolation of plant DNA from fresh tissue. Focus 12:13–15. Eltaher S, Sallam A, Belamkar V, Emara HA, Nower AA, Salem KFM, Poland J, Baenziger PS (2018) Genetic diversity and population structure of F3:6 Nebraska winter wheat genotypes using genotyping-by-sequencing. Front Genet 9:76. https://doi.org/10.3389/fgene.2018.00076. Evanno G, Regnaut S, Goudet J (2000) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x. Halder S, Ghosh S, Khan R, Khan AA, Perween T, Hasan MA (2019) Role of pollination in fruit crops: a review. The Pharma Innovation Journal 8: 695–702. Hamza EM (2013) Genetic diversity of some Citrus varieties based on microsatellite and RAPD molecular markers in Egypt. World J Agric Sci 9:316–324. https://doi.org/10.5829/idosi.wjas.2013.9.4.1753. Han GH, Su Q, Wang WS, Jia ZG, Hong QB, Liang GL (2011) Establishment and application of SCoT molecular marker system for citrus. Acta Hortic Sin 38:1243–1250. Haque EU, Hayat A, Asim M, Afzaal S, Hanif MS, Murtaza MA, Din A, Sabir S, Ahmad S (2022) The supply and value chain of citrus fruit producer to consumer. In: Hussain S, Khalid MF, Ali MA, Ahmed N, Hasanuzzaman M, Ahmad S (eds) Citrus production technological advancements and adaptation to changing climate. CRC Press LLC, Florida, pp 405–1420. https://doi.org/10.1201/9781003119852-26. Jian Y, Yan W, Xu J, Duan S, Li G, Jin L (2021) Genome-wide simple sequence repeat markers in potato: abundance, distribution, composition, and polymorphism. DNA Res 28:1–9. https://doi.org/10.1093/dnares/dsab020. Juibary PL, Seyedmehdi FS, Sheidai M, Noormohammadi Z, Koohdar F (2021) Genetic structure analysis and genetic finger printing of sweet orange cultivars ( Citrus sinensis (L.) Osbeck) by using SCoT molecular markers. Genet Resour Crop Evol 68: 1645–1654. https://doi.org/10.1007/s10722-020-01092-2. Kaur H, Sidhu GS, Sarao NK, Singh R, Singh G (2022) Assessment of genetic diversity of mandarin cultivars grown in major citrus regions of world using morphological and microsatellite markers. Hortic Environ Biotechnol 63:425–437. https://doi.org/10.1007/s13580-021-00404-4. Krueger RR, Navarro L (2007) Citrus germplasm resources. In: Khan I (ed) Citrus genetics, breeding, and biotechnology. CAB International, Oxford, pp 45–140. Kulyan R, Samarina L, Shkhalakhova R, Kuleshov A, Ukhatova Y, Antonova O, Koninskaya N, Matskiv A, Malyarovskaya V, Ryndin A (2023) InDel and SCoT markers for genetic diversity analysis in a Citrus collection from the Western Caucasus. Int J Mol Sci 24:8276. https://doi.org/10.3390/ijms24098276. Lazar I (2010) GelAnalyzer software. http://www.gelanalyzer.com. Accessed 17 April 2024. Li Y, Cheng Y, Tao N, Deng X (2007) Phylogenetic analysis of mandarin landraces, wild mandarins, and related species in China using nuclear LEAFY second intron and plastid trnL-trnF sequence. J Am Soc Hortic Sci 132:796–806. http://dx.doi.org/10.21273/JASHS.132.6.796. Li YL, Liu JX (2017) STRUCTURESELECTOR: A web-based software to select and visualize the optimal number of clusters using multiple methods. Mol Ecol Res 18:176–177. https://doi.org/10.1111/1755-0998.12719. Liu K, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics Research Center, North Carolina State University, North Carolina, USA. Mahjbi A, Baraket G, Oueslati A, Salhi-Hannachi A (2015) Start Codon Targeted (SCoT) markers provide new insights into the genetic diversity analysis and characterization of Tunisian Citrus species. Biochem Syst Ecol 61:390–398. https://doi.org/10.1016/j.bse.2015.07.017. Mahjbi A, Oueslati A, Baraket G, Salhi-Hannachi A, Azouzi SZ (2016) Assessment of genetic diversity of Tunisian orange, Citrus sinensis (L.) Osbeck using microsatellite (SSR) markers. Genet Mol Res 15:1–12. https://doi.org/10.4238/gmr.15026564. Martasari C, Yulianti F, Widyaningsih S, Budiyati E, Hardiyanto, Budiarto K, Yusuf HM (2023) Genetic diversity assessment of citrus accessions grown in Indonesia using molecular markers. Agrivita J Agric Sci 45: 419–429. http://doi.org/10.17503/agrivita.v41i0.4165. Mohanapriya M, Ramaswamy L, Rajendran R (2013) Health and medicinal properties of lemon ( Citrus limonum ) . Int J Ayurvedic Herb Med 3: 1095–1100. Mehl F, Marti G, Boccard J, Debrus B, Merle P, Delort E, Baroux L, Raymo V, Velazco MI, Sommer H, Wolfender JL, Rudaz S (2014) Differentiation of lemon essential oil based on volatile and non-volatile fractions with various analytical techniques: a metabolomic approach. Food Chem 143:325–335. https://doi.org/10.1016/j.foodchem.2013.07.125. Ministry of Agriculture-Republic of Indonesia (2022) Statistik Pertanian 2022. Center for Agricultural Data and Information System, Ministry of Agriculture Republic of Indonesia, Jakarta, Indonesia. Nadeem MA, Nawaz MA, Shahid MQ, Doğan Y, Comertpay G, Yıldız M, Hatipoğlu R, Ahmad F, Alsaleh A, Labhane N, Özkan H, Chung G, Baloch FS (2018) DNA molecular markers in plant breeding: current status and recent advancements in genomic selection and genome editing. Biotechnol Biotechnol Equip 32: 261–285. https://doi.org/10.1080/13102818.2017.1400401. Nagano Y, Mimura T, Kotoda N, Matsumoto R, Nagano AJ, Honjo MN, Kudoh H, Yamamoto M (2018) Phylogenetic relationships of Aurantioideae (Rutaceae) based on RAD-seq. Tree Genet Genomes 14:6. https://doi.org/10.1007/s11295-017-1223-z. Nei M, Tajima F, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. J Mol Evol 19: 153–170. Nicolosi E, Deng ZN, Gentile A, La Malfa S, Continella G, Tribulato E (2000) Citrus phylogeny and genetic origin of important species as investigated by molecular markers. Theor Appl Genet 100:1155–1166. Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update. Bioinformatics 28:2537–2539. http://dx.doi.org/10.1093/bioinformatics/bts460. Penjor T, Yamamoto M, Uehara M, Ide M, Matsumoto N, Matsumoto R, Nagano Y (2013) Phylogenetic relationships of citrus and its relatives based on matK gene sequences. PLoS One 8:e62574. https://doi.org/10.1371/journal.pone.0062574. Perrier X, Jacquemoud-Collet JP (2006) DARwin software. https://darwin.cirad.fr/. Accessed 20 April 2024. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959. https://doi.org/10.1093/genetics/155.2.945. Rafiq S, Kaul R, Sofi SA, Bashir N, Nazir F, Nayik GA (2018) Citrus peel as a source of functional ingredient: a review. J Saudi Soc Agric Sci 17:351–358. https://doi.org/10.1016/j.jssas.2016.07.006. Rai MK (2023) Start codon targeted (SCoT) polymorphism marker in plant genome analysis: current status and prospects. Planta 257:34. https://doi.org/10.1007/s00425-023-04067-6. Scora RW (1975) On the history and origin of Citrus. Bulletin of the Torrey Botanical Club 369–375. Shahzadi K, Naz S, Riaz S (2014) Assessing genetic diversity of Pakistani Citrus varieties using microsatellite markers. J Anim Plant Sci 24:1752–1757. Sharma N, Dubey AK, Srivastav M, Singh BP, Singh AK, Singh NK (2015) Assessment of genetic diversity in grapefruit ( 'Citrus paradisi ' Macf) cultivars using physico-chemical parameters and microsatellite markers. Aust J Crop Sci 9:62–68. Vanijajiva O (2020) Start codon targeted (SCoT) polymorphism reveals genetic diversity of Manilkara in Thailand. Biodiversitas 21: 666–673. https://doi.org/10.13057/biodiv/d210232. Velasco R, Licciardello C (2014) A genealogy of the citrus family. Nat Biotechnol 32:640–642. https://doi.org/10.1038/nbt.2954. Vieira MLC, Santini L, Diniz AL, de Freitas Munhoz C (2016) Microsatellite markers: what they mean and why they are so useful. Genet Mol Biol 39:312–328. https://doi.org/10.1590/1678-4685-GMB-2016-0027. Warschefsky EJ, Klein LL, Frank MH, Chitwood DH, Londo JP, von Wettberg EJB, Miller AJ (2016) Rootstocks: diversity, domestication, and impacts on shoot phenotypes. Trends Plant Sci 21: 418–437. http://dx.doi.org/10.1016/j.tplants.2015.11.008. Wolter F, Schindele P, Puchta H (2019) Plant breeding at the speed of light: the power of CRISPR/Cas to generate directed genetic diversity at multiple sites. BMC Plant Biol 19:176. https://doi.org/10.1186/s12870-019-1775-1. Woo JK, Yun SH, Yi KU, Park YC, Lee HY, Kim M, Lee Y, Song KJ, Kim HB (2020) Identification of citrus varieties bred in Korea using microsatellite markers. Hortic Sci Technol 38: 374–384. https://doi.org/10.7235/HORT.20200036. Wu X, Zheng F, Xu C, Tang W (2016) Genetic diversity analysis of Shatangju mandarin ( Citrus reticulata ) by SCoT-PCR. Agric Sci Technol 17:34. Wu GA, Terol J, Ibanez V, López-García A, Pérez-Román E, Borredá C, Domingo C, Tadeo FR, Carbonell-Caballero J, Alonso R, Curk F, Du D, Ollitrault P, Roose ML, Dopazo J, Gmitter FG, Rokhsar DS, Talon M (2018) Genomics of the origin and evolution of Citrus. Nature 554:311–316. https://doi.org/10.1038/nature25447. Zou Z, Xi W, Hu Y, Nie C, Zhou Z (2016) Antioxidant activity of Citrus fruits. Food Chem 196:885–896. https://doi.org/10.1016/j.foodchem.2015.09.072. Zhang SW, Huang GX, He XH, Pan JC, Ding F (2015) Study on genetic diversity of 39 lemon, lime, and Rangpur germplasm resources with SCoT and ISSR markers. Acta Hortic 1065:97–104. https://doi.org/10.17660/ActaHortic.2015.1065.9. Zhang S, Liang M, Wang N, Xu Q, Deng X, Chai L (2018) Reproduction in woody perennial citrus: an update on nucellar embryony and self‑incompatibility. Plant Reprod 31:43–57. https://doi.org/10.1007/s00497-018-0327-4. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Aug, 2024 Read the published version in Genetic Resources and Crop Evolution → Version 1 posted Editorial decision: Revision requested 08 Jul, 2024 Reviews received at journal 08 Jul, 2024 Reviewers agreed at journal 26 Jun, 2024 Reviews received at journal 25 Jun, 2024 Reviewers agreed at journal 24 Jun, 2024 Reviewers agreed at journal 24 Jun, 2024 Reviewers invited by journal 22 Jun, 2024 Submission checks completed at journal 24 May, 2024 Editor assigned by journal 24 May, 2024 First submitted to journal 24 May, 2024 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-4471294","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":308007058,"identity":"df99230c-b5b1-470b-833a-f005c7cef940","order_by":0,"name":"Kristianto Nugroho","email":"","orcid":"","institution":"IPB University","correspondingAuthor":false,"prefix":"","firstName":"Kristianto","middleName":"","lastName":"Nugroho","suffix":""},{"id":308007059,"identity":"2be1d8a7-e808-4961-9f2f-72d25471f78d","order_by":1,"name":"Tri Joko Santoso","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYFACxgaDBAMbOQMgA8xnY0jAr4EHpOVDRZoxKVqA9sw4czhxA0KMgBZ76cMNxbxtzOnbpQ+3PWD4ZcPAx07IFr7EBmPeNrbcnX2J7QaMfWkMbDwPCGjhYQRp4cndcIaxTYKx5zADmwQhWyBaJNINSNJiOOMMMJxBWhh+EKPlDDiQEwx39gC1JDak8RD0C3sP+zOgFf/lzXnYn0l8+GMjJ99OwBYgYDOAMxPbwBFFEDAjOeQPMRpGwSgYBaNgpAEA5LU8mZv1pdAAAAAASUVORK5CYII=","orcid":"","institution":"National Research and Innovation Agency","correspondingAuthor":true,"prefix":"","firstName":"Tri","middleName":"Joko","lastName":"Santoso","suffix":""},{"id":308007060,"identity":"a1793849-4728-4145-881b-b9d3dd8217ef","order_by":2,"name":"Mia Kosmiatin","email":"","orcid":"","institution":"National Research and Innovation Agency","correspondingAuthor":false,"prefix":"","firstName":"Mia","middleName":"","lastName":"Kosmiatin","suffix":""},{"id":308007061,"identity":"7328b7ca-5f1c-4cd6-9dd4-c460271e770e","order_by":3,"name":"Dewi Sukma","email":"","orcid":"","institution":"IPB University","correspondingAuthor":false,"prefix":"","firstName":"Dewi","middleName":"","lastName":"Sukma","suffix":""},{"id":308007062,"identity":"bc28d53c-8da8-48c9-86c0-bf59feb8cee3","order_by":4,"name":"Agus Purwito","email":"","orcid":"","institution":"IPB University","correspondingAuthor":false,"prefix":"","firstName":"Agus","middleName":"","lastName":"Purwito","suffix":""},{"id":308007063,"identity":"393a285c-b114-49ea-a6eb-983d8013e681","order_by":5,"name":"Ali Husni","email":"","orcid":"","institution":"National Research and Innovation Agency","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Husni","suffix":""},{"id":308007064,"identity":"57f6ba0f-b347-4001-b88c-2089a5abde75","order_by":6,"name":"Reflinur Reflinur","email":"","orcid":"","institution":"National Research and Innovation Agency","correspondingAuthor":false,"prefix":"","firstName":"Reflinur","middleName":"","lastName":"Reflinur","suffix":""},{"id":308007065,"identity":"bee3d784-1296-4863-904f-6a65aaf22d14","order_by":7,"name":"Puji Lestari","email":"","orcid":"","institution":"National Research and Innovation Agency","correspondingAuthor":false,"prefix":"","firstName":"Puji","middleName":"","lastName":"Lestari","suffix":""}],"badges":[],"createdAt":"2024-05-24 09:01:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4471294/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4471294/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10722-024-02130-z","type":"published","date":"2024-08-24T15:57:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57849327,"identity":"e50bed1e-696f-4899-85dc-c1a83a177b81","added_by":"auto","created_at":"2024-06-06 11:31:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":181238,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Visualization of amplicon band amplified by CCSM40 across 53 citrus accessions. \u003cstrong\u003eB\u003c/strong\u003e Visualization of amplicon band amplified by CCSM06 markers across 53 citrus accessions. Information: M: 100 bp DNA ladder (Geneaid Biotech, Ltd), Lane 1-53: list of citrus accessions with sample arrangement as presented in \u003cstrong\u003eTable 1\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4471294/v1/01a4164e76403f0139b77d39.png"},{"id":57850814,"identity":"b97f8c16-b7c5-4a35-b60e-dfa99950849a","added_by":"auto","created_at":"2024-06-06 11:47:43","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":204065,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree of 53 citrus accessions based on SSR markers constructed by Nei’s genetic distance (1983) using UPGMA method. Information: green color refer to mandarin group, yellow color refer to tangerine group, and red color refer to outgroup\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4471294/v1/e24c8192344b328228b8b84e.jpeg"},{"id":57849328,"identity":"5c8c444a-89d4-4e04-a7e3-42cb4fce4da5","added_by":"auto","created_at":"2024-06-06 11:31:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":100995,"visible":true,"origin":"","legend":"\u003cp\u003ePCoA plot constructed from SSR markers showing the spatial distribution of 53 citrus accessions used in this study. Tangerine group represented by yellow color, mandarin group represented by green color, and outgroup represented by red color\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4471294/v1/b5286df1c25d3e2f90d01b52.png"},{"id":57849963,"identity":"e65e4b2e-6f51-4d13-a507-41704361c602","added_by":"auto","created_at":"2024-06-06 11:39:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":77313,"visible":true,"origin":"","legend":"\u003cp\u003ePopulation structure of 53 citrus accessions constructed from SSR analysis at K = 2 based on Bayesian approach. Lane 1-53: list of citrus accessions with sample arrangement as presented in Table 1\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4471294/v1/f6c2cc01091c100c8a3e2e94.png"},{"id":57849965,"identity":"a26c113b-b88b-422b-a034-728b119a3d72","added_by":"auto","created_at":"2024-06-06 11:39:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":117232,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Visualization of amplicon band from 53 citrus accessions amplified by SCoT 13. \u003cstrong\u003eB\u003c/strong\u003eVisualization of amplicon band from 53 citrus accessions amplified by SCoT 14 markers. Information: M: 100 bp DNA ladder (Geneaid Biotech, Ltd), Lane 1-53: list of citrus accessions with sample arrangement as presented in Table 1.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4471294/v1/c3f9be751eec684ec576f7ef.png"},{"id":57849333,"identity":"0e8b0570-6563-42ad-b474-0ce39c4d29e0","added_by":"auto","created_at":"2024-06-06 11:31:43","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":200736,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree of 53 citrus accessions genotyped by SCoT markers based on Nei’s genetic distance (1983) using UPGMA method. Green color represented mandarin group, yellow color represented tangerine group, and red color represented the outgroup\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4471294/v1/55b95084f840d1e285efdc2c.jpeg"},{"id":57849331,"identity":"4b27a7ac-e9b3-4699-a68d-27a12c0adb9a","added_by":"auto","created_at":"2024-06-06 11:31:43","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":105975,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal coordinate analysis constructed from SCoT markers across 53 citrus accessions. Tangerine group represented by yellow color, mandarin group represented by green color, and outgroup represented by red color\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4471294/v1/fcbfa938042e47381e931b1e.png"},{"id":57849334,"identity":"f49613f5-991d-4d60-bc05-7e3cc99a84cb","added_by":"auto","created_at":"2024-06-06 11:31:43","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":72596,"visible":true,"origin":"","legend":"\u003cp\u003ePopulation structure of 53 citrus accessions from SCoT analysis at K = 3 based on Bayesian approach. Lane 1-53: list of citrus accessions with sample arrangement as presented in Table 1.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-4471294/v1/bce64ee4d1e1f3bea713b6b5.png"},{"id":63300091,"identity":"75a4a540-7db8-4475-a09e-127b554343f5","added_by":"auto","created_at":"2024-08-26 16:10:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2444879,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4471294/v1/4542365b-e731-4a98-820c-75c31a356731.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genetic Diversity and Population Structure of Tangerine and Mandarin Citrus Accessions from Indonesia using SSR and SCoT Markers","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCitrus is a valuable horticultural crop that is consumed throughout the world. Its fruits can be consumed freshly or processed into juice, jams, pastes, and sweet candy. Citrus fruit are appreciated for their attractive color, refreshing taste, and aroma (Zou et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). They are also highly nutritious, containing carbohydrates, protein, fiber, vitamin C, A, and E, minerals, flavonoids, hesperidin, carotenoids, and other beneficial compounds that help promote good health (Zou et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Rafiq et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Adenaike and Abakpa \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Citrus fruits are rich in vitamin C and fibre, which can help boost endurance, protect cells from free radicals and improve digestion (Mohanapriya et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, Rafiq et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Citrus is one of the top three fruits traded internationally, along with grapes and apples (Abobatta \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It grows well in tropical, subtropical, and temperate regions, and in different conditions such as humid, semi-arid, or arid. The annual production of citrus reaches 102\u0026nbsp;million tons leads by China, Brazil, Mexico, Spain, and United States as the main citrus-producing countries in the world (Mehl et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Abobatta \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Haque et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTangerine (\u003cem\u003eCitrus nobilis\u003c/em\u003e L.) and mandarin (\u003cem\u003eCitrus reticulata\u003c/em\u003e Blanco.) are two citrus fruits that are popular in Indonesia which locally, the former known as \u003cem\u003esiam\u003c/em\u003e citrus and the latter known as \u003cem\u003ekeprok\u003c/em\u003e citrus. It is reported that a high consumption rate of citrus in Indonesia reach 4.269 kg per capita per year in 2021 and a total production of 2,401,064 tons in the same year (Ministry of Agriculture-Republic of Indonesia \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Indonesia, being located in the equatorial zone, has many local accessions of tangerine and mandarin that possess high genetic diversity. This makes them ideal for citrus breeding program in Indonesia. The availability of citrus germplasms with high genetic diversity is essenstial in such programs (Wolter et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Moreover, genetic diversity analysis is crucial in protecting and preserving plant genetic resources (Tonogbanua and Espino 2017). Analysis of the genetic diversity of citrus species can be done using morphological, biochemical, or molecular markers. The use of molecular markers have several advantages, such as early-stages testing without waiting for plants to mature, unaffected by the environmental factor, elucidating accessions with very close relationships, having high reproducibility, and having broader genome coverage (Bhandari et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nadeem et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Simple Sequence Repeats (SSR) and Start Codon Targeted (SCoT) are molecular markers that can be used in genetic diversity analysis of citrus species.\u003c/p\u003e \u003cp\u003eSSR or microsatellites are tandem repeat sequences with a length of 1\u0026ndash;6 nucleotides, which are distributed in the genomes of eukaryotic organisms (Shahzadi et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The advantages of this marker include having a high level of polymorphism, codominant, high abundance in eukaryotic genomes, and having a higher level of reproducibility compared to other markers such as Random Amplified Polymorphic DNA (RAPD) or Inter Simple Sequence Repeat (ISSR) (Woo et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Previous studies have shown that SSR markers are widely used in the genetic diversity analysis of citrus germplasms around the world (Hamza \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Shahzadi et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sharma et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Mahjbi et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Woo et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kaur et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Recently, SCoT markers are also type of molecular markers commonly used in genotyping activities that are directly related to certain functional genes and are widely used in genotyping activities and polymorphism analysis (Vanijajiva \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This marker was designed on short conserved sequences flanking the START codon (ATG) in genome of an organism (Amom and Nongdam \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). SCoT markers are universal, dominant, and consists of only one primer that acts as forward and reverse. They have a length of around 18 mer and an annealing temperature of 50\u0026deg;C, making them more reproducible than RAPD and ISSR (Collard and Mackill \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Unlike RAPD or ISSR markers, SCoT markers have a specific gene target and a relationship with certain functional traits (Rai \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The use of the SCoT markers in analyzing the genetic diversity of citrus germplasms in the world has also been widely reported in various study (Han et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Mahjbi et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wu et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Juibary et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; and Kulyan et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe objective of this study was to analyze the genetic diversity of tangerine and mandarin citrus local accessions in Indonesia using SSR and SCoT markers. The information on genetic relationship and structrure population data obtained from this study is expected to aid the maintenance of Indonesia\u0026rsquo;s citrus germplasms collection, thereby accelerating the citrus breeding program in the future.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eGenetic materials\u003c/p\u003e \u003cp\u003eIn this study, 53 citrus accessions including 8 tangerine accessions, 28 mandarin accessions, and 17 outgroup accessions i.e lemon, lime, sweet orange, and pummelo were used as plant genetic materials (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Most of the citrus materials used in this study were collected from the Agricultural Instrument Standardization Agency for Citrus and Subtropical Fruits (BSIP Jestro) in Malang, East Java, Indonesia while the rest were obtained from Agricultural Instrument Standardization Agency for Agricultural Biotechnology and Genetic Resources (BBPSI Biogen) in Bogor, West Java, local farmers, and local markets.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of mandarin and tangerine citrus accessions used in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCitrus accession name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGeographical origin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollection origin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePart of plant used for DNA extraction\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiam Pontianak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCitrus nobilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePontianak, West Kalimantan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jetsro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiam Gunung Omeh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. nobilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLima Puluh Kota, West Sumatra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jetsro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiam Kintamani\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. nobilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKintamani, Bali\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jetsro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiam Banjar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. nobilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBanjarmasin, South Kalimantan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jetsro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiam Madu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. nobilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKaro, North Sumatra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jetsro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiam Banyuwangi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. nobilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBanyuwangi, East Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLocal farmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSinta Ponsoe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. nobilis\u003c/em\u003e var Pontianak x \u003cem\u003eC. Reticulata\u003c/em\u003e var SoE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eImproved variety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSitaya Agrihorti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. nobilis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWest Kalimantan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Garut\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGarut, West Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Borneo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEast Kalimantan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Tawangmangu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTawangmangu, Central Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Pulung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePonorogo, East Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Selayar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSelayar Island, South Sulawesi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Madura\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMadura Island, East Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Siompu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eButon, South East Sulawesi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Tejakula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTejakula, North Bali\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Kacang Solok\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSolok, West Sumatra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Gayo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGayo, Aceh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Brasitepu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKaro, North Sumatra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Rimau Gerga Lebong (RGL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLebong, Bengkulu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Grabag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMagelang, Central Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Wangkang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKetapang, West Kalimantan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Pulau Tengah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKerinci, Jambi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Sipirok\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSipirok, North Sumatra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Batu 55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMalang, East Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok SoE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSoE, East Nusa Tenggara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLocal market\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Terigas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSambas, West Kalimantan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKertaji\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eImproved variety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrifta-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eImproved variety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJRM 2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntroduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKrisma Agrihorti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBulungan, East Kalimantan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMonita Agrihorti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eImproved variety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTopazindo Agrihorti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eImproved variety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Selwasa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMarantutul, Southeast Maluku\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKeprok Maga\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. reticulata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMandailing Natal, North Sumatra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD.N. Sabilulungan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(\u003cem\u003eC. unshiu\u003c/em\u003e x \u003cem\u003esinensis\u003c/em\u003e) x \u003cem\u003eC. Poonensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntroduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProksi-1 Agrihorti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProtoplast fusion between Siam Madu and Mandarin Satsuma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eImproved variety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBBPSI Biogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJapansche citroen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. limonia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntroduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e39.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePonkam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. poonensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntroduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLocal market\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePeel\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSunkist Valencia Egypt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. sinensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntroduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLocal market\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePeel\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLemon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. limon\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntroduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLocal market\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePeel\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e42.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNipis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. aurantifolia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLocal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLocal market\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePeel\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e43.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLimau\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCitrus amblycarpa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLocal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLocal market\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePeel\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e44.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrange jasmine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eMurraya paniculata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLocal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLocal farmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarrizo-442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCitrus insitoum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntroduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e46.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRough lemon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCitrus jambhiri\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntroduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e47.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTroyer-415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ePoncirus trifoliata x C. sinensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntroduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e48.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePangkajene Putih\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. maxima\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePangkajene Kepulauan, South Sulawesi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e49.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRaja\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. maxima\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLocal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMagetan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. maxima\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMagetan, Central Java\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKunci-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. microcarpa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLocal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e52.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKalamansi FR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. microcarpa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBengkulu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e53.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNipis Borneo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eC. aurantifolia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKalimantan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBSIP Jestro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLeaf\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\u003eGenomic DNA Extraction\u003c/p\u003e \u003cp\u003eThe citrus genomic DNA extraction was performed using the modified Doyle and Doyle (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1990\u003c/span\u003e) method. DNA quantity was measured using NanoDrop\u0026trade; 2000 Spectrophotometers (ThermoScientific, USA) while DNA quality was separated using 1% (w/v) agarose gel electrophoresis. The DNA stock solutions then diluted to concentrations of 10 ng/\u0026micro;L and stored at \u0026minus;\u0026thinsp;20\u0026deg;C for polymerase chain reaction (PCR) activities.\u003c/p\u003e \u003cp\u003eSSR analysis\u003c/p\u003e \u003cp\u003eThe study utilized a total of 20 SSR markers from various references as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. For each sample, as many as 10 \u0026micro;L total reaction volume was prepared, consisting of 2 \u0026micro;L of 10 ng/\u0026micro;L DNA template, 5 \u0026micro;L of 2x MyTaq\u003csup\u003e\u0026trade;\u003c/sup\u003e HS Red Mix (Bioline), 0.5 \u0026micro;L of 10 \u0026micro;M forward and reverse primers, and sterile ddH\u003csub\u003e2\u003c/sub\u003eO. PCR analysis was performed in a T100 Thermal Cycler (Bio-Rad, USA) with the following PCR profiles: initial denaturation at 95\u0026deg;C for 5 minutes, followed by 35 cycles of denaturation at 94\u0026deg;C for 30 seconds, annealing at 55\u0026deg;C for 1 minute, and extension at 72\u0026deg;C for 1 minute. The PCR reaction was ended with a final extension at 60\u0026deg;C for 15 minutes. The PCR products were separated using 6% (w/v) non-denaturing polyacrylamide gel electrophoresis in 1\u0026times; TBE buffer, stained with 10 mg/mL ethidium bromide solution, and visualized under UV light using a UV Transilluminator (Bio-Rad, USA).\u003c/p\u003e \u003cp\u003eSCoT analysis\u003c/p\u003e \u003cp\u003eIn this study, a total of 20 SCoT markers designed by Collard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) were also used for genotyping the 53 citrus accessions with the same PCR amplification reactions as described in SSR markers. The PCR amplification was carried out in a T100 Thermal Cycler (Bio-Rad, USA) consisting of: initial denaturation at 95\u0026deg;C for 5 minutes, then 40 cycles of denaturation at 94\u0026deg;C for 30 seconds, annealing at 50\u0026deg;C for 1 minute, and extension at 72\u0026deg;C for 1 minute, ended by a final extension at 60\u0026deg;C for 15 minutes. The PCR products were separated using 1.5% (w/v) agarose gel electrophoresis in 1\u0026times; TAE buffer, stained with 10 mg/mL ethidium bromide solution, and visualized under UV light using a UV Transilluminator (Bio-Rad, USA).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of SSR markers used in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarker\u0026rsquo;s name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequence (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRepeat motif\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTm ( \u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCMS-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: CCAAACATCTGCGGATCC\u003c/p\u003e \u003cp\u003eR: AGAAGAACCCAGATTCCAAATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CT)\u003csub\u003e11\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.2\u003c/p\u003e \u003cp\u003e57.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAhmad et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCMS-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: TAGGCCAAATCTTATTCATGCC\u003c/p\u003e \u003cp\u003eR: TCAGGGTCATAAGGAATGGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CA)\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56.6\u003c/p\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAhmad et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCMS-24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: TTATTGTCCCCAATTGTGAGC\u003c/p\u003e \u003cp\u003eR: TCCAGATTGAGGGGAAAAAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CA)\u003csub\u003e20\u003c/sub\u003e(TA)\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57.6\u003c/p\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAhmad et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCMS-30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: AACACCCCTTGGAGGGAG\u003c/p\u003e \u003cp\u003eR: GCTGTTCACACACACAACCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CT)\u003csub\u003e9\u003c/sub\u003e(CA)\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.8\u003c/p\u003e \u003cp\u003e61.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAhmad et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCMS-34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: GCACTAAGCAGAATGCGTGT\u003c/p\u003e \u003cp\u003eR: GCCGTCGTTTTACATTCAAGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CA)\u003csub\u003e39\u003c/sub\u003e (AT)\u003csub\u003e11\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.6\u003c/p\u003e \u003cp\u003e57.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAhmad et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCMS-45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: CGACCACTCCACCTACGATG\u003c/p\u003e \u003cp\u003eR: GCCGTTAATTCCTGCTTTCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(CTT)\u003csub\u003e7\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.2\u003c/p\u003e \u003cp\u003e57.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAhmad et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2003\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCSM 06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: ATCTGTGTGAGGACTGAA\u003c/p\u003e \u003cp\u003eR: CCTCTATTAATGTGCCTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AG)\u003csub\u003e21\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003cp\u003e47.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCristofani-Yaly et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCSM 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: ACAAGAGTCGCAACAATC\u003c/p\u003e \u003cp\u003eR: GACAACAGTGGCAATACC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(GCAACA)\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.2\u003c/p\u003e \u003cp\u003e51.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCristofani-Yaly et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCSM 68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: ACATGGACAGGACAACTAAG\u003c/p\u003e \u003cp\u003eR: CACTTCTGCCTTGCTATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AG)\u003csub\u003e18\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.8\u003c/p\u003e \u003cp\u003e50.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCristofani-Yaly et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCSM 77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: TATCCAACCATGTGTGTCCATA\u003c/p\u003e \u003cp\u003eR: CACTAGGTCACCATTAATTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AG)\u003csub\u003e18\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.5\u003c/p\u003e \u003cp\u003e48.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCristofani-Yaly et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCSM 95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: AAGAAGCTCTCACCTCTC\u003c/p\u003e \u003cp\u003eR: TAACGTCTGAACGAACTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(TC)\u003csub\u003e18\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.7\u003c/p\u003e \u003cp\u003e49.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCristofani-Yaly et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCSM 111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: TGATACATAATATGGGATAG\u003c/p\u003e \u003cp\u003eR: TTAGTGATTCGTGGAGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AG)n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.0\u003c/p\u003e \u003cp\u003e48.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCristofani-Yaly et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCSM 112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: ATGCCATTATGTGTGTG\u003c/p\u003e \u003cp\u003eR: CAGACCTGAACATAACTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(TC)\u003csub\u003e7\u003c/sub\u003eCG(TG)\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(AG)\u003csub\u003e20\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.0\u003c/p\u003e \u003cp\u003e46.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCristofani-Yaly et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCSM 156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: GTCTCTGTTGTGTGTCGGTT\u003c/p\u003e \u003cp\u003eR: ACGAAGTGAAGTGTGTAATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(TC)\u003csub\u003e20\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.0\u003c/p\u003e \u003cp\u003e50.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCristofani-Yaly et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM-CiSSR-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: GGGCTCAGTTCTTCTCTACTC\u003c/p\u003e \u003cp\u003eR: GCATTAGGCTTCTCTCATACC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(TTA)\u003csub\u003e15\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.6\u003c/p\u003e \u003cp\u003e56.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWoo \u003cem\u003eet al.\u003c/em\u003e (2019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM-CiSSR-013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: GGTGGCATACATACATACATACA\u003c/p\u003e \u003cp\u003eR: GCAACATCTGGAACTACTCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(TA)\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.8\u003c/p\u003e \u003cp\u003e56.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWoo \u003cem\u003eet al.\u003c/em\u003e (2019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM- CiSSR-115b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: CGGTGTGTATTGGGTACACG\u003c/p\u003e \u003cp\u003eR: GCTTTTTCGAAAGCGTCAAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(TA)\u003csub\u003e17\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.5\u003c/p\u003e \u003cp\u003e56.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWoo \u003cem\u003eet al.\u003c/em\u003e (2019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM- CiSSR-159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: ATGACCTCAAACGGTGAGCA\u003c/p\u003e \u003cp\u003eR: CTTCCACATCCGAACCGACA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(GAGG)\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.3\u003c/p\u003e \u003cp\u003e63.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWoo \u003cem\u003eet al.\u003c/em\u003e (2019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM- CiSSR-162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: GCTAGGGTTCCAGACTTCCAG\u003c/p\u003e \u003cp\u003eR: GATTTGGCCGATCGAAAGCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(AAT)\u003csub\u003e10\u003c/sub\u003e(CAT)\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.3\u003c/p\u003e \u003cp\u003e61.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWoo \u003cem\u003eet al.\u003c/em\u003e (2019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM- CiSSR-272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: ATAGGTCCCCACAATGGAAA\u003c/p\u003e \u003cp\u003eR: GGGCATAAATGAATTGGGTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(GAA)\u003csub\u003e8\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.1\u003c/p\u003e \u003cp\u003e56.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWoo \u003cem\u003eet al.\u003c/em\u003e (2019)\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\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of SCoT markers used in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarker\u0026rsquo;s name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequence (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTm ( \u003csup\u003eo\u003c/sup\u003eC)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAACA\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAACA\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAACA\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAACA\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAACA\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAACA\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACGAC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCGACCATCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACGAC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCGACCACGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACGAC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCGACCGCGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCGAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCGAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCGCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCGGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCGCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACGAC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCGACCCACA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAACC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCACC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCACC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCGGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCoT-26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eACC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eATG\u003c/span\u003eGCTACCACCGTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCollard and Mackill (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\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 \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eAmplification products of both the SSR and SCoT markers were scored as binary data, with each visible band being considered as one allele. A score of 1 and 0 was given for the presence and absence of a band, respectively. In order to estimate each band's size produced by each primer, GelAnalyzer (Lazar \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) was applied in scoring. A phylogenetic tree was constructed using the Unweighted Pair Group Method with the Arithmetic (UPGMA) program based on Nei's genetic distance (1983), available on PowerMarker 3.25 (Liu and Muse \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The major allele frequency, gene diversity, observed heterozygosity, and Polymorphism Information Content (PIC) value were also determined using PowerMarker 3.25 (Liu and Muse \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnalysis of molecular variance (AMOVA) were perfomed using GenAlEx 6.5 (Peakall and Smouse \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), while the principal coordinate analysis (PCoA) were assembled using DARwin 6 (Perrier and Jacquemoud-Collet \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The population structure model was analyzed using STRUCTURE 2.3.4 (Pritchard et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The data collection involved 10,000 replications of the burn-in period, followed by 100,000 replications of the Markov Chain Monte Carlo (MCMC) along with the admixture model. Ten independent runs were conducted for each K value (ranging from 1 to 10) (Evanno et al. 2005). The results were then submitted to StructureSelector (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://lmme.ac.cn/StructureSelector/\u003c/span\u003e\u003cspan address=\"https://lmme.ac.cn/StructureSelector/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e (Li and Liu \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) to determine the best K value.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eSSR analysis\u003c/p\u003e \u003cp\u003eGenetic diversity analysis was performed on 53 citrus accessions using 20 SSR markers. The analysis showed polymorphic bands, which are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 107 alleles were identified in this study. The number of alleles per locus ranged from 2 (CCSM111) to 10 (BmCiSSR 159 and BmCiSSR 272) with average 5.35 alleles per marker (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The allele size varied from 70 to 488 bp. The major allele frequency value ranged from 0.077 (BmCiSSR-115b) to 0.412 (CCSM111) with an average of 0.144. Gene diversity varied from 0.752 (CCSM111) to 0.967 (BmCiSSR-159) with an average of 0.925. Observed heterozygosity values ranged from 0.075 (CMS-34) to 0.980 (BmCiSSR-162) with an average of 0.596. PIC value, which reflects the informativeness level of the markers, ranged from 0.450 (CCSM111) to 0.929 (BmCiSSR-159) with an average of 0.920. According to criteria set by Botstein et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1980\u003c/span\u003e), 18 SSR markers used in this study were highly informative, with a PIC value greater than 0.5.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical summary of SSR markers polymorphism used in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarkers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange of allele size (bp)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAllele number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMajor allele frequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGene diversity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eObserved heterozigosity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePIC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMS-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132\u0026ndash;179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMS-21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114\u0026ndash;154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMS-24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118\u0026ndash;211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMS-30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126\u0026ndash;183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMS-34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e279\u0026ndash;329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCMS-45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e173\u0026ndash;237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCSM 06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e187\u0026ndash;210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCSM 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117\u0026ndash;214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCSM 68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84\u0026ndash;109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.450\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCSM 77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93\u0026ndash;121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCSM 95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.691\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCSM 111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82\u0026ndash;99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCSM 112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u0026ndash;107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCSM 156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83\u0026ndash;115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM-CiSSR-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e248\u0026ndash;325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM-CiSSR-013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105\u0026ndash;132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM- CiSSR-115b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e184\u0026ndash;255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM- CiSSR-159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e298\u0026ndash;488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM- CiSSR-162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e152\u0026ndash;259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.881\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM- CiSSR-272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e245\u0026ndash;475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.743\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\u003ePhylogenetic analysis using SSR markers clearly revealed separation among tangerine, mandarin, and outgroup citrus accessions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Since there was no clear differentiation of citrus accessions by geographic origin, the clustering pattern observed in present study was based on the genetic background variation. The analysis of Nei's genetic distance showed that mandarin and outgroup accessions had the highest genetic distance values (0.740), while tangerine and outgroup accessions had the lowest ones (0.570) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). It is interesting to note that five outgroup citrus accessions, including lemon, sunkist Valencia Egypt, Japansche citroen, ponkam, and Proksi-1 Agrihorti were grouped together with mandarin accessions. These findings highlight the importance of genetic background in the determination of clustering patterns among citrus accessions.\u003c/p\u003e \u003cp\u003e \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\u003eGenetic distance among three citrus populations based on SSR markers\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTangerine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMandarin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOutgroup\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTangerine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMandarin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutgroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\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\u003ePCoA analysis showed a similar clustering pattern of citrus accessions with that previously identified by the UPGMA method in the phylogenetic tree. In Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, all the citrus accessions were distributed in four quadrants in two major coordinates. The outgroup accessions (shown in red) were mainly distributed in quadrant 1, while the tangerine accessions (shown in yellow) were in quadrant 3. The mandarin accessions, represented by green were spread between quadrant 2 and 4. The PCoA plot also revealed that five outgroup citrus accessions including sunkist Valencia Egypt, lemon, ponkam, Japansche citroen, and Proksi-1 Agrihorti were distributed together with the mandarin accessions as previously seen in the phylogenetic tree.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAMOVA over 20 SSR markers revealed that 7% of the variance was observed among the population, while 93% was within the population (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The analysis of population structure of SSR markers successfully classified the 53 citrus accessions into two subpopulations withthe highest delta K value at K\u0026thinsp;=\u0026thinsp;2. The first and the second subpopulations each were represented by a green and a red line (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). It is noted that Tangerine and outgroup accessions combined in subpopulation 1 are in accordance with both the phylogenetic and Nei's genetic distance results, whereas Mandarin accessions left in subpopulation 2. A total of 13 mandarin accessions, such as Keprok Tejakula, Keprok Rimau Gerga Lebong, Keprok Wangkang, Keprok Pulau Tengah, Keprok Batu55, Keprok SoE, Keprok Terigas, Kertaji, JRM 2012, Krisma Agrihorti, Topazindo Agrihorti, Keprok Maga, and D.N. Sabilulungan possessed mixing colors reflecting gene flow was occured between populations which lead to genetic recombination.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAMOVA among 53 citrus accessions based on SSR markers used in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSum of squares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEstimation of variance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePercentage of total variance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmong populations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithin populations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e922.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e982.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSCoT analysis\u003c/p\u003e \u003cp\u003eThe analysis of 20 SCoT markers also revealed the presence of polymorphic bands, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The total number of alleles detected was 164, which is higher than that obtained using SSR markers. The number of alleles per locus ranged from 6 (SCoT 26) to 12 (SCoT 23), with an average of 8.20 alleles per marker (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The size of the alleles varied from 210 to 2050 bp. The frequency of the major allele ranged from 0.375 (SCoT 2) to 0.500 (SCoT 13, SCoT 14, SCoT 21, SCoT 22, SCoT 23, SCoT 24), with an average of 0.468. The gene diversity ranged from 0.578 (SCoT 18) to 0.791 (SCoT 26), averaging 0.723. The observed heterozygosity values ranged from 0.509 (SCoT 19) to 1.000 (SCoT 3, SCoT 16, SCoT 17, SCoT 22, and SCoT 24), averaging 0.984. The PIC values, which reflect the level of informativeness of the markers, ranged from 0.490 (SCoT 18) to 0.779 (SCoT 26), with an average of 0.698. According to the criteria established by Botstein et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1980\u003c/span\u003e), all the SCoT markers used in this study, except SCoT 18, were highly informative, as their PIC values were greater than 0.5.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe analysis of the SCoT markers for phylogeny also showed that tangerine, mandarin, and outgroup citrus accessions were separated, in accordance with the cluster resulted from SSR (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). However, unlike the SSR results, the tangerine accessions were found to cluster with the Mandarin accessions. Similar with SSR markers analysis, clustering of citrus accessions constructed from SCoT markers was also caused by genetic background of citrus accession and not by geographic origin. The genetic distance values from Nei's analysis of SCoT markers (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) showed that the highest genetic distance was found between the tangerine and outgroup (0.409), while the lowest one was between the tangerine and mandarin (0.206). Interestingly, ten mandarin accessions, including Keprok Tawangmangu, Keprok Madura, Keprok Garut, Keprok Borneo, Keprok Pulung, Keprok Siompu, Keprok Selayar, Keprok Kacang Solok, Keprok Gayo, and Keprok Brasitepu, clustered together with the tangerine group. Two outgroup accessions, namely Proksi-1 Agrihorti and Japansche Citroen were clustered together with Mandarin accessions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical summary of SCoT markers polymorphism used in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarkers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange of allele size (bp)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAllele number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMajor allele frequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGene diversity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eObserved heterozigosity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePIC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e583\u0026ndash;1534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e445\u0026ndash;1761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.757\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e513\u0026ndash;1560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e610\u0026ndash;2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e445\u0026ndash;1889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e367\u0026ndash;1108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.718\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e305\u0026ndash;1463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.716\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e187\u0026ndash;1286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.708\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e224\u0026ndash;1482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e469\u0026ndash;1373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214\u0026ndash;1480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e278\u0026ndash;1458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e405\u0026ndash;1485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e210\u0026ndash;1344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e325\u0026ndash;1606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e340\u0026ndash;1442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.724\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e371\u0026ndash;1864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e380\u0026ndash;1470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e662\u0026ndash;1807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCoT 26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e387\u0026ndash;1597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.698\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\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGenetic distance among tangerine, mandarin, and outgroup populations genotyped by SCoT markers based on Nei\u0026rsquo;s genetic distance (1983)\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTangerine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMandarin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOutgroup\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTangerine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMandarin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutgroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\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\u003eThe results obtained from PCoA analysis of SCoT markers showed a similar clustering pattern to the one previously identified by the UPGMA method in the phylogenetic tree. The citrus accessions used in this study were distributed across four quadrants in two main coordinates, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. The tangerine and mandarin accessions were overlapped in quadrant 1 and 2, respectively, in line with the phylogenetic tree and Nei's genetic distance results. On the other hand, the outgroup accessions, represented by red color, were mostly distributed in quadrants 3 and 4, except for Proksi-1 Agrihorti and Japansche citroen, which existed in quadrant 2 with Mandarin accessions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAMOVA based on SCoT markers performed in this study revealed that 2% of the genetic variance was presence among populations, while 98% was found within the population (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). This result is consistent with previous findings from SSR markers, suggesting that the genetic variation within a population is more significant than that among populations. Population structure analysis from SCoT markers indicated that the citrus accessions used in this study could be best classified into three subpopulations, as demonstrated by the highest delta K value at K\u0026thinsp;=\u0026thinsp;3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The three subpopulations are represented by the colors red, green, and blue. All of the tangerine accessions and ten mandarin accessions combined in subpopulation 1 in accordance to phylogenetic tree and Nei\u0026rsquo;s genetic distance result. However, two Mandarin accessions (Siam Pontianak and Siam Gunung Omeh), and four Mandarin accessions (Keprok Brasitepu, Keprok Rimau Gerga Lebong, Keprok Grabag, and Keprok Terigas accessions) displayed mixing blue color, indicating their recombination with outgroup citrus accessions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAMOVA result from SCoT analysis showed variance among 53 citrus accessions used in this study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSum of squares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEstimation of variance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePercentage of total variance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmong populations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithin populations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1004.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1036.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe genetic diversity analysis of citrus accessions based on molecular markers as revealed in this study could provide fundamental information in directing citrus breeding strategy and improvement. Present study compared the effectiveness of SCoT and SSR markers in identifying alleles and gene diversity in 53 citrus accessions. The use of SCoT markers could identify more alleles (137) than SSR markers (107). Additionally, SCoT markers could detect alleles with a higher maximum size of 2050 bp, while SSR markers could only detect alleles with a maximum size of 488 bp. Previous studies from Han et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and Mahjbi et al. (2019), have also shown that SCoT markers can detect alleles with even larger sizes than those observed in this study. However, the SSR markers used in this study showed a greater average PIC value than SCoT markers. PIC value is a useful tool in determining the effectiveness of polymorphic loci in distinguishing genetic diversity among the genotypes (Ikten et al. 2023). Both SSR and SCoT markers used in this study showed an average PIC value of greater than 0.5, indicating their potential as highly informative markers in citrus breeding programs (Eltaher et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Overall, the study suggests that genetic variation analysisi using a combination of SCoT and SSR markers can be useful in breeding and improving citrus fruit related traits.\u003c/p\u003e \u003cp\u003eSSR and SCoT markers target a different portions of the plant genome. SSR markers target a flanking region of repeat sequence that highly abundant in plant genome, while SCoT markers target a flanking region of START codon (ATG) that highly conserved in related plant genes (Zhang et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Jian et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). SSR is a codominant marker and can be used to distinguished between heterozygotes and homozygotes genotypes (Jian et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This makes SSR markers are useful for highly heterozygous plant such as citrus. On the other hand, SCoT markers are dominant markers, and they cannot distinguish heterozygote genotypes. However, converting SCoT markers to codominant SCAR markers can solve this problem (Rai \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Both SSR and SCoT markers are highly polymorphic and reproducible, making them suitable for genetic diversity analysis, fingerprinting construction, sex determination, and the construction of linkage or assosiation maps (Vierira et al. 2016; Rai \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAll of the SSR and SCoT markers utilized in this study demonstrated their robustness in identifying the genetic relationship from citrus accessions. The phylogenetic tree and PCoA plot clearly distinguished tangerine, mandarin, and outgroup citrus accessions. The SSR markers revealed a separation between tangerine and mandarin, while SCoT markers showed a mixture between mandarin and tangerine accessions. Based on SCoT markers, eleven mandarin accessions were grouped together with tangerine as presented in Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. In accordance to this study, Martasari et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) previously reported about the mixing among mandarin and tangerine accessions in the similar cluster based on ISSR and SSR markers. This study also found that both SSR and SCoT markers could distinguished the accessions with similar name, between Nipis (\u003cem\u003eC. aurantifolia\u003c/em\u003e) accession that collected from local market in Bogor, West Java with Nipis Borneo (\u003cem\u003eC. aurantifolia\u003c/em\u003e var. Borneo) accession that originated from Kalimantan island. The phylogenetic tree from SSR analysis also showed a separation from Kalamansi FR (\u003cem\u003eC. microcarpa\u003c/em\u003e) with outgroup cluster, in line with previous study from Wu et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) that showed a separation of calamondin (\u003cem\u003eC. microcarpa\u003c/em\u003e) from orange, lemon, pummelos, and lime group based on chloroplast genome. However, the study found that neither the SSR nor SCoT markers could separate orange jasmine (\u003cem\u003eM. paniculata\u003c/em\u003e) accession from outgroup cluster. Orange jasmine is an ornamental plant commonly grown in home gardens. In contrast to our study, Penjor et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and Nagano et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) reported separation of orange jasmine from true citrus cluster consisted of \u003cem\u003eC. reticulata\u003c/em\u003e, \u003cem\u003eC. maxima\u003c/em\u003e, and \u003cem\u003eC. medica\u003c/em\u003e by using matK gene and RAD-seq respectively.\u003c/p\u003e \u003cp\u003eThe SSR and SCoT markers used in this study could also classified two accessions, namely Sinta Ponsoe and Proksi-1 Agrihorti, derived from breeding activities using mandarin and tangerine as their parentals. Sinta Ponsoe was created by hybridizing Siam Pontianak (tangerine group) and Keprok SoE (mandarin group) and it was clustered with the tangerine group in the phylogenetic tree and PCoA plot. Proksi-1 Agrihorti, on the other hand, was formed from protoplast fusion between Siam Madu (tangerine group) and Satsuma mandarin (mandarin group) and was classified as an outgroup accession. In the phylogenetic tree and PCoA plot, this accession clustered in the mandarin group. In contrast to those results, SSR and SCoT markers used in this study showed a different robustness in ponkam accession clustering, of which SSR markers classified ponkam in a mandarin group along with Proksi-1 Agrihorti and Japansche citroen (\u003cem\u003eC. limonia\u003c/em\u003e), while SCoT markers classified it in an outgroup with sunkist valencia Egypt (\u003cem\u003eC. sinensis\u003c/em\u003e), lemon (\u003cem\u003eC. limon\u003c/em\u003e), and nipis (\u003cem\u003eC. aurantifolia\u003c/em\u003e). According to Velasco and Licciardello (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), ponkam is a hybrid derived from hybridization between mandarin (\u003cem\u003eC. reticulata\u003c/em\u003e) and pummelo (\u003cem\u003eC. maxima\u003c/em\u003e). In this case, SSR markers showed a better robustness in distinguishing citrus accessions used in this study.\u003c/p\u003e \u003cp\u003eFurthermore, SSR and SCoT markers yielded different results in Nei\u0026rsquo;s genetic distance (1983). The genetic distance between tangerine and outgroup accessions was found to be close (0.570) using SSR markers, while SCoT markers revealed a closer genetic relationship between tangerine and mandarin accessions (0.206). According to Nicolosi et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), citrus taxonomy and phylogeny are still a very complex, disputable, and confusing problem, because of their cross compatibility between citrus species and related genera, high rate of bud mutations, the long history of cultivation, and wide dispersion. The taxonomy of citrus has gone through numerous system. The citrus taxonomy proposed by Scora (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1975\u003c/span\u003e) and Barrett and Rhodes (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1976\u003c/span\u003e) revealed that there were only three species constituted citrus ancestral, namely citron (\u003cem\u003eC. medica\u003c/em\u003e L.), mandarin (\u003cem\u003eC. reticulata\u003c/em\u003e Blanco), and pummelo (\u003cem\u003eC. grandis\u003c/em\u003e (L.) Osb.). The hybridization among these three species inherited other genotypes including commercial citrus found today. Previous molecular analysis using RAPD and SCAR markers reported by Nicolosi et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) successfully clustered eight citrus group consisting of citron, mandarin, pummelo, ichang, fortunella, and micrantha clusters. The mandarin cluster consisted of all mandarin (\u003cem\u003eC. reticulata\u003c/em\u003e) and mandarin-like accessions such as \u003cem\u003eC. tachibana\u003c/em\u003e, \u003cem\u003eC. paradisi\u003c/em\u003e, \u003cem\u003eC. aurantium\u003c/em\u003e, \u003cem\u003eC. sinensis\u003c/em\u003e, \u003cem\u003eC. junos\u003c/em\u003e, including \u003cem\u003eC. nobilis\u003c/em\u003e (tangerine citrus). The result obtained from this study and Martasari et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) support the previous study by Nicolosi et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) that tangerine citrus is the member of mandarin group.\u003c/p\u003e \u003cp\u003eThe AMOVA from both SSR and SCoT markers showed that there was a higher variance within population than among population. This suggests that cross-pollination occured mostly in the citrus accessions used in this study. However, the results are contrary to those found by Barbhuiya et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) who discovered a higher variance among populations than within populations in \u003cem\u003eC. medica\u003c/em\u003e populations from the Eastern Himalayan. This different of result could be due to the clonal propagation system by grafting, which may have increased the homogenity level at those populations.\u003c/p\u003e \u003cp\u003eCitrus plants have unique reproduction systems. Some genotypes, such as Valencia orange, are capable of self-pollination, while other like mandarin and mandarin-hybrid require cross-pollination (Halder et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Since, citrus pollen is heavy and sticky, it cannot be carried by wind, making the presence of insect pollinators crucial for pollination (Chacoff and Aizen \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). However, whether insect pollinators play a significant rolein citrus pollination still a matter of debate. Certain genotypes, such as tangelos and tangerines, are known to require pollinator for better fruit sets (Halder et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Interestingly, citrus plants can also reproduce clonally through apomixis, a natural process that result in a polyembryony phenomenon (Zhang et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), or artificially by human through grafting (Warschefsky et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This leads to high heterozigosity in citrus species, which makes their taxonomy and phylogeny challenging to determine.\u003c/p\u003e \u003cp\u003eThe analysis of population structure from SSR markers demonstrated that the highest delta K value was obtained when K value was equal 2, indicating that all citrus accessions used in this study were best classified into two subpopulations. This result showed that tangerine and outgroup were classified in the same subpopulations, whereas the mandarin group was separated. Among these, 13 mandarin showed mixing color, which indicated gene flow between populations, leading to genetic recombination. On the other hand, SCoT markers showed that the highest delta K value was achieved when K was equal to3, indicating that three subpopulations were best classified for all of citrus accessions used in this study. The first subpopulation consisted of a mix of all Tangerine and ten Mandarin accessions. The second subpopulation consisted of 18 mandarin accessions including Proksi-1 Agrihorti and Japansche citroen from outgroup, while the third subpopulations consited of 15 outgroup accessions. According to this result, two tangerine accessions, namely Siam Pontianak and Siam Gunung Omeh, and also four Mandarin accessions namely Keprok Brasitepu, Keprok Rimau Gerga Lebong, Keprok Grabag, and Keprok Terigas showing mixing color representing their recombination with outgroup citrus accessions. The population structure obtained in this study corroborated with with AMOVA results, which showed that citrus accessions mostly underwent cross-polinaton between species and related genera, resulting in their heterogenity.\u003c/p\u003e \u003cp\u003eMandarin citrus is believed to have originated from the east coast of China and then spread to Formosa Island (now Taiwan) and Japan (Krueger and Navarro \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Many mandarin landraces and wild mandarins have been found in China, supporting the hypothesis that China is the center of origin of this species (Li et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). However, based on genomic analysis, proposed by Wu et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) revealed that the Southeast Himalaya region, which includes the Eastern part of Assam, Northern Myanmar, and Western China, are the center of origin of citrus species. The process by which mandarin and tangerine citrus were disseminated to Southeast Asia, especially to Indonesia, still needs to be clarified. In contrast to mandarin, tangerine (\u003cem\u003eC. nobilis\u003c/em\u003e) is thought to have originated from a hybrid between mandarin (\u003cem\u003eC. reticulata\u003c/em\u003e) and sweet orange (\u003cem\u003eC. sinensis\u003c/em\u003e) (Krueger and Navarro \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This finding is supported by the population structure from SCoT analysis, which showed an admixture between mandarin and tangerine accessions in one subpopulation. The mandarin and tangerine accessions used in this study are probably came from a similar ancestral or shared partial ancestral. This hypothesis is supported by the results of the phylogenetic tree, both from SSR and SCoT analysis, which showed that the clustering of tangerine and mandarin accessions did not depend on geographical origins, but rather on their genetic background. This suggests that similarities still exist between tangerine or mandarin accessions, even if they originated from different islands and have been separated geographically for an extended period.\u003c/p\u003e \u003cp\u003e Citrus genetic relationships are closely related to the dissemination pattern of citrus mother trees and seedlings, which has occurred for a long time, according to Agisimanto et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Three locations in East Java Province, such as Tlekung-Batu, Purworejo, and Tulungagung have become the source of mother trees and scions for both distribution and production centers of citrus plants in Indonesia. Both tangerine and mandarin accessions used in this study might have undergone genetic improvement from their origin, either by hybridization, spontaneous mutations, adaptation to their geographical conditions, or human domestication, creating their new genetic diversity.\u003c/p\u003e \u003cp\u003eThe information on genetic diversity obtained from this study could be highly useful in managing, utilizing, and breeding citrus germplasm. It could also help in resolving the complexity of their taxonomy and phylogeny. The SSR and SCoT markers applied in present study have shown a high level of polymorphism and reproducibility, thus they are recommended as promising tools to be used for future genetic diversity analyses of citrus species. Performing a combination analysis of data obtained from molecular markers with those from morphological and biochemical markers in future studies will lead to gain more comprehensive results.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, SSR and SCoT markers could reveal the genetic diversity among the tangerine, mandarin, and outgroup accessions. The phylogenetic tree and PCoA plot constructed from SSR and SCoT markers could distinguish among those three citrus populations. AMOVA resulted from both SSR and SCoT markers revealed a higher citrus variance within the population than among the population, reflecting the high frequency of cross-pollination in the citrus accessions observed in present study. The population structure also revealed gene flow among citrus populations that allegedly occurred due to the transfer of material genetics across the region in Indonesia. The result of this study could provide essential information for future citrus germplasm management, utilization, and breeding strategy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization and designing the work: KN, TJS, MK, DS, and AP. Formal analysis, investigation, and wrote original draft: KN. Supervision: TJS, MK, DS, and AP. Reviewed the draft and editing: TJS, MK, DS, AP, AH, R, and PL. Resources: MK, AH, TJS, and R. Funding acquisition: MK and PL.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Riset dan Inovasi untuk Indonesia Maju (RIIM) project, Badan Riset dan Inovasi Nasional (BRIN), second wave budget in the year of 2022-2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors gratefully acknowledged BSIP Jestro for supplying citrus genetic materials for this study and BBPSI Biogen for providing laboratory facilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no any conflict of interest\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbobatta WF (2019) Influence of climate change on citrus growth and productivity (effect of temperature). Adv Agricultural Technol Plant Sci 2:180036. https://doi.org/10.15406/mojes.2019.04.00168.\u003c/li\u003e\n\u003cli\u003eAdenaike O, Abakpa GO (2021) Antioxidant compounds and health benefits of citrus fruits. European J Nutr Food Saf 13:65\u0026ndash;74. https://doi.org/10.9734/ejnfs/2021/v13i230376.\u003c/li\u003e\n\u003cli\u003eAgisimanto D, Martasari C, Supriyanto A (2007) Perbedaan primer RAPD dan ISSR dalam identifikasi hubungan kekerabatan genetik jeruk siam (\u003cem\u003eCitrus suhuniensis\u003c/em\u003e L. Tan) Indonesia. J Hortikultura 17:101\u0026ndash;110. https://doi.org/10.21082/jhort.v17n2.2007.\u003c/li\u003e\n\u003cli\u003eAhmad R, Struss D, Southwick SM (2003) Development and characterization of microsatellite markers in \u003cem\u003eCitrus\u003c/em\u003e. J Am Soc Hortic Sci 128: 584\u0026ndash;590. https://doi.org/10.21273/JASHS.128.4.0584.\u003c/li\u003e\n\u003cli\u003eAmom T, Nongdam P (2017) The use of molecular marker methods in plants: a review Int J Curr Res Rev 9:1\u0026ndash;7. https://doi.org/10.7324/IJCRR.2017.9171.\u003c/li\u003e\n\u003cli\u003eBarbhuiya AR, Khan ML, Dayanandan S (2015) Genetic structure and diversity of natural and domesticated populations of \u003cem\u003eCitrus medica\u003c/em\u003e L. in the Eastern Himalayan region of Northeast India. Ecol Evol 6: 3898\u0026ndash;3911. https://doi.org /10.1002/ece3.2174.\u003c/li\u003e\n\u003cli\u003eBarrett HC, Rhodes AM (1976) A numerical taxonomic study of affinity relationships in cultivated Citrus and its close relatives. Syst Bot: 105\u0026ndash;136.\u003c/li\u003e\n\u003cli\u003eBhandari HR, Bhanu AN, Srivastava K, Singh MN, Shreya, Hemantaranjan A (2017) Assessment of genetic diversity in crop plants-an overview. Adv Plants Agric Res 7:279\u0026ndash;286. https://doi.org/ 10.15406/apar.2017.07.00255.\u003c/li\u003e\n\u003cli\u003eBotstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet 32: 314\u0026ndash;332.\u003c/li\u003e\n\u003cli\u003eChacoff NP, Aizen MA (2007) Pollination requirements of pigmented grapefruit (\u003cem\u003eCitrus paradisi\u003c/em\u003e Macf.) from Northwestern Argentina. Crop Sci 47:1143\u0026ndash;1150. https://doi.org/10.2135/cropsci2006.09.0586.\u003c/li\u003e\n\u003cli\u003eCristofani-Yaly M, Novelli VM, Bastianel M, Machado MA (2011) Transferability and level of heterozygosity of microsatellite markers in citrus species. Plant Mol Biol Rep 29:418\u0026ndash;423. https://doi.org/10.1007/s11105-010-0241-x.\u003c/li\u003e\n\u003cli\u003eCollard BCY, Mackill DJ (2009). Start codon targeted (SCoT) polymorphism: a simple, novel DNA marker technique for generating gene-targeted markers in plants. Plant Mol Biol Rep 27:86\u0026ndash;93. https://doi.org/10.1007/s11105-008-0060-5.\u003c/li\u003e\n\u003cli\u003eDoyle JJ, Doyle JL (1990) Isolation of plant DNA from fresh tissue. Focus 12:13\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eEltaher S, Sallam A, Belamkar V, Emara HA, Nower AA, Salem KFM, Poland J, Baenziger PS (2018) Genetic diversity and population structure of F3:6 Nebraska winter wheat genotypes using genotyping-by-sequencing. Front Genet 9:76. https://doi.org/10.3389/fgene.2018.00076.\u003c/li\u003e\n\u003cli\u003eEvanno G, Regnaut S, Goudet J (2000) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611\u0026ndash;2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x.\u003c/li\u003e\n\u003cli\u003eHalder S, Ghosh S, Khan R, Khan AA, Perween T, Hasan MA (2019) Role of pollination in fruit crops: a review. The Pharma Innovation Journal 8: 695\u0026ndash;702. \u003c/li\u003e\n\u003cli\u003eHamza EM (2013) Genetic diversity of some Citrus varieties based on microsatellite and RAPD molecular markers in Egypt. World J Agric Sci 9:316\u0026ndash;324. https://doi.org/10.5829/idosi.wjas.2013.9.4.1753.\u003c/li\u003e\n\u003cli\u003eHan GH, Su Q, Wang WS, Jia ZG, Hong QB, Liang GL (2011) Establishment and application of SCoT molecular marker system for citrus. Acta Hortic Sin 38:1243\u0026ndash;1250.\u003c/li\u003e\n\u003cli\u003eHaque EU, Hayat A, Asim M, Afzaal S, Hanif MS, Murtaza MA, Din A, Sabir S, Ahmad S (2022) The supply and value chain of citrus fruit producer to consumer. In: Hussain S, Khalid MF, Ali MA, Ahmed N, Hasanuzzaman M, Ahmad S (eds) Citrus production technological advancements and adaptation to changing climate. CRC Press LLC, Florida, pp 405\u0026ndash;1420. https://doi.org/10.1201/9781003119852-26.\u003c/li\u003e\n\u003cli\u003eJian Y, Yan W, Xu J, Duan S, Li G, Jin L (2021) Genome-wide simple sequence repeat markers in potato: abundance, distribution, composition, and polymorphism. DNA Res 28:1\u0026ndash;9. https://doi.org/10.1093/dnares/dsab020.\u003c/li\u003e\n\u003cli\u003eJuibary PL, Seyedmehdi FS, Sheidai M, Noormohammadi Z, Koohdar F (2021) Genetic structure analysis and genetic finger printing of sweet orange cultivars (\u003cem\u003eCitrus sinensis\u003c/em\u003e (L.) Osbeck) by using SCoT molecular markers. Genet Resour Crop Evol 68: 1645\u0026ndash;1654. https://doi.org/10.1007/s10722-020-01092-2.\u003c/li\u003e\n\u003cli\u003eKaur H, Sidhu GS, Sarao NK, Singh R, Singh G (2022) Assessment of genetic diversity of mandarin cultivars grown in major citrus regions of world using morphological and microsatellite markers. Hortic Environ Biotechnol 63:425\u0026ndash;437. https://doi.org/10.1007/s13580-021-00404-4.\u003c/li\u003e\n\u003cli\u003eKrueger RR, Navarro L (2007) Citrus germplasm resources. In: Khan I (ed) Citrus genetics, breeding, and biotechnology. CAB International, Oxford, pp 45\u0026ndash;140.\u003c/li\u003e\n\u003cli\u003eKulyan R, Samarina L, Shkhalakhova R, Kuleshov A, Ukhatova Y, Antonova O, Koninskaya N, Matskiv A, Malyarovskaya V, Ryndin A (2023) InDel and SCoT markers for genetic diversity analysis in a \u003cem\u003eCitrus\u003c/em\u003e collection from the Western Caucasus. Int J Mol Sci 24:8276. https://doi.org/10.3390/ijms24098276.\u003c/li\u003e\n\u003cli\u003eLazar I (2010) GelAnalyzer software. http://www.gelanalyzer.com. Accessed 17 April 2024.\u003c/li\u003e\n\u003cli\u003eLi Y, Cheng Y, Tao N, Deng X (2007) Phylogenetic analysis of mandarin landraces, wild mandarins, and related species in China using nuclear LEAFY second intron and plastid trnL-trnF sequence. J Am Soc Hortic Sci 132:796\u0026ndash;806. http://dx.doi.org/10.21273/JASHS.132.6.796.\u003c/li\u003e\n\u003cli\u003eLi YL, Liu JX (2017) STRUCTURESELECTOR: A web-based software to select and visualize the optimal number of clusters using multiple methods. Mol Ecol Res 18:176\u0026ndash;177. https://doi.org/10.1111/1755-0998.12719.\u003c/li\u003e\n\u003cli\u003eLiu K, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics Research Center, North Carolina State University, North Carolina, USA.\u003c/li\u003e\n\u003cli\u003eMahjbi A, Baraket G, Oueslati A, Salhi-Hannachi A (2015) Start Codon Targeted (SCoT) markers provide new insights into the genetic diversity analysis and characterization of Tunisian \u003cem\u003eCitrus\u003c/em\u003e species. Biochem Syst Ecol 61:390\u0026ndash;398. https://doi.org/10.1016/j.bse.2015.07.017.\u003c/li\u003e\n\u003cli\u003eMahjbi A, Oueslati A, Baraket G, Salhi-Hannachi A, Azouzi SZ (2016) Assessment of genetic diversity of Tunisian orange, \u003cem\u003eCitrus sinensis\u003c/em\u003e (L.) Osbeck using microsatellite (SSR) markers. Genet Mol Res 15:1\u0026ndash;12. https://doi.org/10.4238/gmr.15026564.\u003c/li\u003e\n\u003cli\u003eMartasari C, Yulianti F, Widyaningsih S, Budiyati E, Hardiyanto, Budiarto K, Yusuf HM (2023) Genetic diversity assessment of citrus accessions grown in Indonesia using molecular markers. Agrivita J Agric Sci 45: 419\u0026ndash;429. http://doi.org/10.17503/agrivita.v41i0.4165.\u003c/li\u003e\n\u003cli\u003eMohanapriya M, Ramaswamy L, Rajendran R (2013) Health and medicinal properties of lemon (\u003cem\u003eCitrus\u003c/em\u003e\u003cem\u003elimonum\u003c/em\u003e)\u003cem\u003e.\u003c/em\u003e Int J Ayurvedic Herb Med 3: 1095\u0026ndash;1100.\u003c/li\u003e\n\u003cli\u003eMehl F, Marti G, Boccard J, Debrus B, Merle P, Delort E, Baroux L, Raymo V, Velazco MI, Sommer H, Wolfender JL, Rudaz S (2014) Differentiation of lemon essential oil based on volatile and non-volatile fractions with various analytical techniques: a metabolomic approach. Food Chem 143:325\u0026ndash;335. https://doi.org/10.1016/j.foodchem.2013.07.125.\u003c/li\u003e\n\u003cli\u003eMinistry of Agriculture-Republic of Indonesia (2022) Statistik Pertanian 2022. Center for Agricultural Data and Information System, Ministry of Agriculture Republic of Indonesia, Jakarta, Indonesia.\u003c/li\u003e\n\u003cli\u003eNadeem MA, Nawaz MA, Shahid MQ, Doğan Y, Comertpay G, Yıldız M, Hatipoğlu R, Ahmad F, Alsaleh A, Labhane N, \u0026Ouml;zkan H, Chung G, Baloch FS (2018) DNA molecular markers in plant breeding: current status and recent advancements in genomic selection and genome editing. Biotechnol Biotechnol Equip 32: 261\u0026ndash;285. https://doi.org/10.1080/13102818.2017.1400401.\u003c/li\u003e\n\u003cli\u003eNagano Y, Mimura T, Kotoda N, Matsumoto R, Nagano AJ, Honjo MN, Kudoh H, Yamamoto M (2018) Phylogenetic relationships of Aurantioideae (Rutaceae) based on RAD-seq. Tree Genet Genomes 14:6. https://doi.org/10.1007/s11295-017-1223-z.\u003c/li\u003e\n\u003cli\u003eNei M, Tajima F, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. J Mol Evol 19: 153\u0026ndash;170.\u003c/li\u003e\n\u003cli\u003eNicolosi E, Deng ZN, Gentile A, La Malfa S, Continella G, Tribulato E (2000) Citrus phylogeny and genetic origin of important species as investigated by molecular markers. Theor Appl Genet 100:1155\u0026ndash;1166.\u003c/li\u003e\n\u003cli\u003ePeakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research\u0026mdash;an update. Bioinformatics 28:2537\u0026ndash;2539. http://dx.doi.org/10.1093/bioinformatics/bts460.\u003c/li\u003e\n\u003cli\u003ePenjor T, Yamamoto M, Uehara M, Ide M, Matsumoto N, Matsumoto R, Nagano Y (2013) Phylogenetic relationships of citrus and its relatives based on \u003cem\u003ematK \u003c/em\u003egene sequences. PLoS One 8:e62574. https://doi.org/10.1371/journal.pone.0062574.\u003c/li\u003e\n\u003cli\u003ePerrier X, Jacquemoud-Collet JP (2006) DARwin software. https://darwin.cirad.fr/. Accessed 20 April 2024.\u003c/li\u003e\n\u003cli\u003ePritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945\u0026ndash;959. https://doi.org/10.1093/genetics/155.2.945.\u003c/li\u003e\n\u003cli\u003eRafiq S, Kaul R, Sofi SA, Bashir N, Nazir F, Nayik GA (2018) Citrus peel as a source of functional ingredient: a review. J Saudi Soc Agric Sci 17:351\u0026ndash;358. https://doi.org/10.1016/j.jssas.2016.07.006.\u003c/li\u003e\n\u003cli\u003eRai MK (2023) Start codon targeted (SCoT) polymorphism marker in plant genome analysis: current status and prospects. Planta 257:34. https://doi.org/10.1007/s00425-023-04067-6.\u003c/li\u003e\n\u003cli\u003eScora RW (1975) On the history and origin of Citrus. Bulletin of the Torrey Botanical Club 369\u0026ndash;375.\u003c/li\u003e\n\u003cli\u003eShahzadi K, Naz S, Riaz S (2014) Assessing genetic diversity of Pakistani \u003cem\u003eCitrus\u003c/em\u003e varieties using microsatellite markers. J Anim Plant Sci 24:1752\u0026ndash;1757.\u003c/li\u003e\n\u003cli\u003eSharma N, Dubey AK, Srivastav M, Singh BP, Singh AK, Singh NK (2015) Assessment of genetic diversity in grapefruit (\u003cem\u003e\u0026apos;Citrus paradisi\u003c/em\u003e\u0026apos; Macf) cultivars using physico-chemical parameters and microsatellite markers. Aust J Crop Sci 9:62\u0026ndash;68.\u003c/li\u003e\n\u003cli\u003eVanijajiva O (2020) Start codon targeted (SCoT) polymorphism reveals genetic diversity of \u003cem\u003eManilkara\u003c/em\u003e in Thailand. Biodiversitas 21: 666\u0026ndash;673. https://doi.org/10.13057/biodiv/d210232.\u003c/li\u003e\n\u003cli\u003eVelasco R, Licciardello C (2014) A genealogy of the citrus family. Nat Biotechnol 32:640\u0026ndash;642. https://doi.org/10.1038/nbt.2954.\u003c/li\u003e\n\u003cli\u003eVieira MLC, Santini L, Diniz AL, de Freitas Munhoz C (2016) Microsatellite markers: what they mean and why they are so useful. Genet Mol Biol 39:312\u0026ndash;328. https://doi.org/10.1590/1678-4685-GMB-2016-0027.\u003c/li\u003e\n\u003cli\u003eWarschefsky EJ, Klein LL, Frank MH, Chitwood DH, Londo JP, von Wettberg EJB, Miller AJ (2016) Rootstocks: diversity, domestication, and impacts on shoot phenotypes. Trends Plant Sci 21: 418\u0026ndash;437. http://dx.doi.org/10.1016/j.tplants.2015.11.008.\u003c/li\u003e\n\u003cli\u003eWolter F, Schindele P, Puchta H (2019) Plant breeding at the speed of light: the power of CRISPR/Cas to generate directed genetic diversity at multiple sites. BMC Plant Biol 19:176. https://doi.org/10.1186/s12870-019-1775-1.\u003c/li\u003e\n\u003cli\u003eWoo JK, Yun SH, Yi KU, Park YC, Lee HY, Kim M, Lee Y, Song KJ, Kim HB (2020) Identification of citrus varieties bred in Korea using microsatellite markers. Hortic Sci Technol 38: 374\u0026ndash;384. https://doi.org/10.7235/HORT.20200036.\u003c/li\u003e\n\u003cli\u003eWu X, Zheng F, Xu C, Tang W (2016) Genetic diversity analysis of Shatangju mandarin (\u003cem\u003eCitrus reticulata\u003c/em\u003e) by SCoT-PCR. Agric Sci Technol 17:34.\u003c/li\u003e\n\u003cli\u003eWu GA, Terol J, Ibanez V, L\u0026oacute;pez-Garc\u0026iacute;a A, P\u0026eacute;rez-Rom\u0026aacute;n E, Borred\u0026aacute; C, Domingo C, Tadeo FR, Carbonell-Caballero J, Alonso R, Curk F, Du D, Ollitrault P, Roose ML, Dopazo J, Gmitter FG, Rokhsar DS, Talon M (2018) Genomics of the origin and evolution of Citrus. Nature 554:311\u0026ndash;316. https://doi.org/10.1038/nature25447.\u003c/li\u003e\n\u003cli\u003eZou Z, Xi W, Hu Y, Nie C, Zhou Z (2016) Antioxidant activity of Citrus fruits. Food Chem 196:885\u0026ndash;896. https://doi.org/10.1016/j.foodchem.2015.09.072.\u003c/li\u003e\n\u003cli\u003eZhang SW, Huang GX, He XH, Pan JC, Ding F (2015) Study on genetic diversity of 39 lemon, lime, and Rangpur germplasm resources with SCoT and ISSR markers. Acta Hortic 1065:97\u0026ndash;104. https://doi.org/10.17660/ActaHortic.2015.1065.9.\u003c/li\u003e\n\u003cli\u003eZhang S, Liang M, Wang N, Xu Q, Deng X, Chai L (2018) Reproduction in woody perennial citrus: an update on nucellar embryony and self‑incompatibility. Plant Reprod 31:43\u0026ndash;57. https://doi.org/10.1007/s00497-018-0327-4.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"genetic-resources-and-crop-evolution","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gres","sideBox":"Learn more about [Genetic Resources and Crop Evolution](https://www.springer.com/journal/10722)","snPcode":"10722","submissionUrl":"https://submission.nature.com/new-submission/10722/3","title":"Genetic Resources and Crop Evolution","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"citrus germplasms, cross-pollination, delta K, genes flow, informative markers, PIC","lastPublishedDoi":"10.21203/rs.3.rs-4471294/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4471294/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCitrus is one of prominent horticultural crops that highly consumed by people around the world. Indonesia, as a country being located near the equator, has several local accessions of tangerine and mandarin citrus that remain poorly characterized. Thus, assessment of their genetic diversity will facilitate us in adequately identifying accessions conferring important traits suitable for breeding program. The objective of this study was to analyze the genetic diversity of Indonesia\u0026rsquo;s local accessions of tangerine and mandarin citrus using SSR and SCoT markers. Fifty three citrus genotypes representing 8 tangerine accessions, 28 mandarin accessions, and 17 outgroup accessions were subjected to genetic diversity analysis using 20 SSR and SCoT markers. The number of alleles detected by SCoT markers was higher than by SSR markers accounted for 137 and 107, respectively, while the number of alleles at each locus detected by ScoT and SSR markers varied from 6 to 12 and 2 to 10, respectively. Additionally, 19 SCoT and 18 SSR markers with PIC value greater than 0.5 were identified, indicating their potential as highly informative markers in citrus breeding programs. The phylogenetic tree and PCoA plot constructed from both SSR and SCoT markers revealed clearly discrimination of tangerine, mandarin, and outgroup accessions. The AMOVA results showed a higher genetic variation observed within populations in comparison to that among populations, indicating high cross-pollination in the citrus accessions used in the study. The population structure, represented by the highest delta K value of K\u0026thinsp;=\u0026thinsp;2 in SSR markers and K\u0026thinsp;=\u0026thinsp;3 in SCoT markers, also revealed evidence of genes flow occurred among citrus populations. The results of this study would beneficially provide an important information for citrus breeding strategies in the future.\u003c/p\u003e","manuscriptTitle":"Genetic Diversity and Population Structure of Tangerine and Mandarin Citrus Accessions from Indonesia using SSR and SCoT Markers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-06 11:31:38","doi":"10.21203/rs.3.rs-4471294/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-08T17:42:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-08T17:24:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"288395793855413137951006812546336676760","date":"2024-06-26T17:11:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-25T13:46:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199659954555449221757698554403885338905","date":"2024-06-24T12:50:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"39590436642616716187243519350520259573","date":"2024-06-24T07:32:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-22T05:07:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-24T10:39:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-24T10:39:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Genetic Resources and Crop Evolution","date":"2024-05-24T08:59:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"genetic-resources-and-crop-evolution","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gres","sideBox":"Learn more about [Genetic Resources and Crop Evolution](https://www.springer.com/journal/10722)","snPcode":"10722","submissionUrl":"https://submission.nature.com/new-submission/10722/3","title":"Genetic Resources and Crop Evolution","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c0b0de88-dcf8-4c70-a966-4dceeed0e280","owner":[],"postedDate":"June 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-26T15:59:50+00:00","versionOfRecord":{"articleIdentity":"rs-4471294","link":"https://doi.org/10.1007/s10722-024-02130-z","journal":{"identity":"genetic-resources-and-crop-evolution","isVorOnly":false,"title":"Genetic Resources and Crop Evolution"},"publishedOn":"2024-08-24 15:57:03","publishedOnDateReadable":"August 24th, 2024"},"versionCreatedAt":"2024-06-06 11:31:38","video":"","vorDoi":"10.1007/s10722-024-02130-z","vorDoiUrl":"https://doi.org/10.1007/s10722-024-02130-z","workflowStages":[]},"version":"v1","identity":"rs-4471294","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4471294","identity":"rs-4471294","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}