Dissection of Race 1 Anthracnose Resistance in a Watermelon (Citrullus lanatus var. lanatus) Biparental Mapping Population

Dissection of Race 1 Anthracnose Resistance in a Watermelon (Citrullus lanatus var. lanatus) Biparental Mapping Population | 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 Dissection of Race 1 Anthracnose Resistance in a Watermelon (Citrullus lanatus var. lanatus) Biparental Mapping Population Bed Prakash Bhatta, Takshay Patel, Edgar Correa, Todd C. Wehner, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1710183/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Oct, 2022 Read the published version in Euphytica → Version 1 posted 4 You are reading this latest preprint version Abstract Anthracnose, caused by the fungal pathogen Colletotrichum orbiculare (Berk. & Mont.) Arx syn. lagenaria , is one of the most important diseases of watermelon in the United States and worldwide. The study was conducted to identify C . orbiculare race 1 resistance quantitative trait loci (QTL) in a ‘Charleston Gray’, resistant parent, and ‘New Hampshire Midget’, susceptible parent, biparental mapping population. The mapping population consisted of 228 F 2 and the validation population consisted of 60 individuals each in BC 1 P 1 and BC 1 P 2 . The disease severity was rated using a disease index comprising a rating scale of 0 to 100%. IciMapping was used to draw the linkage map and R/qtl non-parametric method (‘model = np’) was used to identity QTL. We identified a major disease resistance QTL, Qar1-8 , on chromosome 8. The significant SNP marker S8_5149002, part of a putative coiled-coil (CC)–nucleotide-binding site (NBS)–leucine-rich repeat (LRR) (CC-NBS-LRR or CNL; ClCG08G002410 ), had a LOD of 14.06. The significant marker was validated on mapping populations using R package functions ‘chisq.test’, ‘wilcox.test’, ‘kruskal.test’, and ‘dunn.test’. The significant marker S8_5149002 was also tested for its ability to differentiate race 1 anthracnose resistance on 61 watermelon germplasm including 41 plant introduction (PI) lines. Hence, the diagnostic SNP marker S8_5149002 could be used for marker assisted selection (MAS) for race 1 anthracnose resistance in watermelon breeding programs. watermelon Colletotrichum orbiculare race 1 anthracnose QTL PACE SNP marker Qar1-8 Figures Figure 1 Figure 2 Figure 3 Introduction Watermelon ( Citrullus lanatus var. lanatus ) occupies 7% of global vegetable production acreage and is among the top five most consumed fresh fruits in the world (Yong and Guo 2017). In 2020, watermelon was grown on 100,000 acres and worth $ 574 million in the U.S. (USDA-NASS 2021). The major watermelon growing states in the U.S. are Florida, Texas, Georgia, and California. Anthracnose is one of the major diseases of watermelon and other cucurbits and is caused by the fungal pathogen Colletotrichum orbiculare (Berk. & Mont.) Arx syn. lagenaria . The fungus is a hemibiotroph ascomycete that occurs intracellularly in the plant hosts (Perfect et al. 1999 ; Dickman 2000 ; Xuei et al. 1988). Though seven races of C. orbiculare have been described (Wasilwa et al. 1993; Sitterly 1972 ), only three races of the fungus (races 1, 2, and 3) are of importance in watermelon (Boyhan et al. 1994 ). A large number of watermelon germplasm are resistant to Colletotrichum orbiculare race 1 and 3, while others are susceptible (Maynard and Hopkins 1999 ; Wasilwa et al. 1993). The disease affects all above ground parts and symptoms include angular, brown to black leaf spots; tan, oval-shaped lesions in stems; sunken, and water-soaked spots on fruits (Elwakil et al. 2013 ; Dutta 1958 ; Layton 1937 ). Wet weather conditions such as rain and high humidity provide a favorable environment for dispersion and germination of conidia, and subsequent infection in plant (Maynard and Hopkins 1999 ). Several accounts of anthracnose as a major disease in cucurbits can be traced back to the late 19th century and early 20th century (Gardner 1918 ; Parris 1949 ). The most severe reports of this disease was mainly in south, southeast, northeast, and mid-west regions of the U.S. (Wasilwa et al. 1993), with up to 30% yield loss reported in watermelon (Parris 1949 ) and 60% yield loss reported in other cucurbits (Thompson and Jenkins 1985 ). A significant negative impact on plants due to anthracnose is on fruit quality, as this disease influences grading standards of watermelon outlined by the United States Department of Agriculture (USDA-AMS 2021 ). Research on anthracnose disease management in watermelon has been prioritized in the past (King and Davis 2007 ), and is still considered a major research priority (Kousik et al. 2016 ). Several efforts focused on breeding watermelon varieties for anthracnose resistance have been reported (Huh et al. 2010a , b ; Crall et al. 1994 ; Norton et al. 1993 ; Crall 1990 ). Resistance to race 1 anthracnose in watermelons has been shown to be governed by a single dominant locus, Ar-1 , and resistance was dominant to susceptibility (Layton 1937 ; Wehner 2012). Utilizing molecular markers closely associated with underlying genes can increase efficiency of the breeding programs (Xu and Crouch 2008). Single nucleotide polymorphism (SNP) markers are the latest of the molecular markers, succeeding restriction fragment length polymorphisms (RFLP) markers (Beckmann and Soller 1986 ), random amplified polymorphic DNA (RAPD) markers (Williams et al. 1990), simple sequence repeats (SSRs) or microsatellite markers (Litt and Luty 1989 ; Akkaya et al. 1992 ), and amplified fragment length polymorphisms (AFLP) markers (Vos et al. 1995 ). The popularity of SNP markers stems from the fact that they are commonly occurring DNA sequence variations, the basis of most genetic variation (Ganal and Röder 2007 ; Chagné et al. 2008 ), high density, cost effective and efficient compared to previous types of markers (Xu and Crouch 2008), and may affect protein function if present in the coding sequences (Yuan et al. 2006). In the current study, we identified a major quantitative trait loci (QTL) for C . orbiculare race 1 resistance from ‘Charleston Gray’ in a F 2 population and validated on BC 1 populations. We further delineated a putative race 1 anthracnose resistant gene in the QTL region and used a previously reported SNP marker (Jang et al. 2019 ) to differentiate race 1 anthracnose resistant and susceptible individuals from the mapping population, as well as the broader watermelon germplasm pool. Materials And Methods Developing biparental mapping populations The watermelon mapping populations were developed at North Carolina State University. Two parental lines, ‘Charleston Gray’(resistant, female parent, P 1 ) developed by C. F. Andrus in 1954 (Andrus 1955 ), and ‘New Hampshire Midget’ (susceptible, male parent, P 2 ) were used to generate F 1 , F 2 , BC 1 P 1 , and BC 1 P 2 mapping populations. The mapping populations consisted of 228 F 2 individuals as well as 60 individuals each in BC 1 P 1 and BC 1 P 2 . Inoculum preparation and pathogen inoculation Colletotrichum orbiculare race 1, collected in North Carolina in 1998, was used to inoculate seedlings. The inoculum preparation and inoculation were conducted as described by Patel ( 2019 ). In brief, the fungus was grown on green bean agar (GBA) media for three-weeks. Spores were harvested by adding 10 to 15 mL distilled water to each agar plate, rubbing the surface of the agar with a sterile metal spreader, pouring the spore suspension into a sterile conical flask, and passing it through four layers of cheesecloth. Concentration of the inoculum was measured using a hemocytometer and adjusted to 100,000 spores mL − 1 prior to inoculation. One drop of Tween-20 was added to every 500 mL of the spore inoculum. The three-week-old watermelon seedlings grown in the greenhouse were inoculated with the spore inoculum. After inoculation, seedlings were kept in a humidity chamber, in the greenhouse, for 48 h in darkness at 80–100% relative humidity, and at a temperature of 22 to 24°C. Then, seedlings were moved to the natural light, and rated at 8, 11, and 14 days post inoculation (dpi). Disease rating The disease index was rated on a scale of 0 to 100%, with an interval of 5%, with weightage on different parts of the plants - true leaves (50% total: yellowing- 5%, complete necrotic leaf- 40%, petiole-10%), meristem (25% total: necrosis spots-10%, mostly necrotic- 20%, dead-25%), hypocotyl (20% total: 1–2 brown patches-5%, many brown patches-15%, completely brown-20%), cotyledons (5% total: little to complete necrosis: 5%). Individuals were designated as resistant and susceptible when the overall rating score was ≤ 40%, and ≥ 41%, respectively (Patel 2019 ). DNA isolation, ddRADseq library construction, and genotyping by sequencing A total of 360 watermelon leaf samples (three P 1 , three P 2 , six F 1 , 60 BC 1 P 1 , 60 BC 1 P 2 , and 228 F 2 individuals) were collected from three-week-old seedlings. Samples were freeze-dried immediately, and genomic DNA was extracted from lyophilized samples using E.Z.N.A. Plant DNA Kit (Omega Bio-tek, GA, USA) following manufacturer’s protocol. The DNA were quantified using Quant-iT-PicoGreen (Invitrogen, Thermo Fisher Scientific, USA) following the manufacturer’s instructions. Due to some samples yielding low amounts of DNA, a total of 188 watermelon samples (three P 1 , two P 2 , six F 1 , 48 BC 1 P 1 and 129 F 2 individuals) were sent to Texas A&M AgriLife Genomics and Bioinformatics Service, College Station, TX ( https://www.txgen.tamu.edu/ ) for double digest restriction-site associated DNA sequencing (ddRADseq) as described previously (Yang et al. 2020) with the following changes. The restriction enzymes EcoR I and Nla III were used for library prep and inserts from 400 to 600 bp were selected on a Pippin prep (Sage Science, Boston, MA, USA). The ddRADseq libraries were sequenced using 40% of a NovaSeq S4 X lane (2 x150 bp paired-end run; Illumina, Inc., San Diego, CA, USA). Raw sequences were demultiplexed using Illumina bcl2fastq, allowing for 1 base error in the barcode sequences. Sequences were first quality-filtered using the program FASTX-Toolkit ( http://hannonlab.cshl.edu/fastx-toolkit ). Raw sequencing reads were first trimmed to remove low quality bases with quality score less than 20 on the ends of reads and reads with 30% or more bases showing low quality score (Q < 15) were removed. The reference genome for watermelon was downloaded from NCBI website (GCA_000238415.2). Bowtie2 [ http://bowtie-bio.sourceforge.net/bowtie2/index.shtml ] was used to align quality-filtered reads to the reference with the default parameters. Aligned reads were then processed with SAMtools v1.19 to generate coordinate sorted binary SAM files (BAM). Reads with mapping quality (MQ) less than 5 were removed. The local re-alignment tool in the Genome Analysis Toolkit (GATK, https://software.broadinstitute.org/gatk/ ) was used to perform re-alignment in Insertion/Deletion regions as previously described. Finally, the processed alignment files were fed to the tool HaplotypeCaller, which is part of the GATK, to call variations and perform genotyping for each sample. Once the SNP calling process was completed, individual SNPs with more than 20% missing data and Minor Allele Frequency (MAF) less than 0.05 in each population group were removed. QTL mapping Genotypic data were assigned to A (P 1 type, homozygous resistant), B (P 2 type, homozygous susceptible), H (heterozygous), and X (missing) types. Since the phenotypic disease rating data for F 2 population were found to be in a non-normal distribution, QTL analysis was done on ‘qtl’ package (Broman et al. 2003 ) with a non-parametric method (‘model = np’) on R software (R Core Team 2014; version 3.6.2) with RStudio GUI (RStudio-Team 2021 ). The logarithm of odds (LOD) threshold of 4.11 for QTL detection was estimated with 1,000 permutations. As genotyping-by-sequencing (GBS) genotypic data had higher missing values, QTL analysis was also performed after imputing missing genotypic data using a multiple imputation method (‘method = imp’) (Sen and Churchill 2001 ) on R ‘qtl’. A graphical display of allele effects was done using “Effect Plot” function on R ‘qtl’. A genetic linkage map was constructed using IciMapping V4.1 (Meng et al., 2014), whereas the linkage map was displayed using MapChart version 2.32 (Voorrips 2002 ). PACE-based SNP genotyping and non-parametric analysis Allele-specific primers were designed for 34 SNP markers in and around the QTL region using PrimerQuest™ Tool (IDT, Coralville, IA, USA) and confirmed manually. Polymerase chain reaction (PCR) allelic competitive extension (PACE) genotyping chemistry constituting FAM, HEX, and ROX fluorophores was used to analyze the SNPs (3CR Bioscience, Essex, UK). The polymorphic PACE SNP markers ( Supplementary Table S1 ) were used to genotype the mapping populations ( N = 360 ) as well as watermelon germplasm ( N = 61 ). The PACE SNP marker was also designed for a previously reported high resolution melting SNP marker, CL14-27-9 ( Supplementary Fig. S1 ), for CC-NBS-LRR gene (CNL; Cla001017 or ClCG08G002410 ) (Jang et al. 2019 ), and designated as S8_5149002 to match the physical coordinates of the Charleston Gray genome. The PACE PCR components included 4 µL of PACE Genotyping Master Mix (2X) (3CR Bioscience, Essex, UK), 0.11 µL primer assay mix (72X), 2 µL template DNA and 2 µL of molecular biology grade water. The PCR was carried out in the Eppendorf flexlid nexus gradient Mastercycler (Eppendorf, Hamburg, Germany). The PCR conditions included one cycle of enzyme activation (94℃, 15 min), followed by 10 cycles each of template denaturation (94℃, 20 s) and annealing/extension with drop of 0.8℃ per cycle (65 to 57℃, 60 s), and 27 cycles each of denaturation (94℃, 20 s), and annealing/extension (57℃, 60 s) (3crBioscience 2018 ). KlusterCaller software version 3.4.1.36 (LGC Genomics, Herts, UK) was used to cluster genotypes using BMG Labtech Omega machine (BMG Labtech, Ortenberg, Germany). An additional 3 to 9 cycles of final denaturation and annealing/extension was done to improve the amplification, as well as to obtain tight and well separated clusters. Several non-parametric analysis - Chi-Square, Mann-Whitney-Wilcoxon test (Wilcoxon 1945; Mann and Whitney 1947 ), Kruskal-Wallis test (Kruskal and Wallis 1952 ), and Dunn’s test (Dunn 1964 ) were conducted on data on R software (R Core Team 2014; version 3.6.2) with RStudio GUI (RStudio-Team 2021 ) using functions ‘chisq.test’, ‘wilcox.test’, ‘kruskal.test’, and ‘dunn.test’, respectively. Results Disease response of the mapping population Phenotypic disease response of race 1 anthracnose inoculated mapping populations ( N = 360 ) resulted in Mendelian ratios for a single gene ( Supplementary Table S2 ). All 60 BC 1 P 1 individuals showed no segregation and had 100% resistance phenotype. The 60 BC 1 P 2 individuals (χ 2 1:1 = 0.26, P = 0.60) failed to reject the null hypothesis of 1:1::resistant:susceptible segregation ratio. The 228 F 2 individuals (χ 2 3:1 = 2.33, P = 0.12) also failed to reject the null hypothesis of 3:1::resistant:susceptible segregation ratio. The histograms of the BC 1 P 1 , BC 1 P 2 , and F 2 population (Fig. 1 ) indicated a non-normal phenotypic distribution. Analysis of ddRADseq data Generated DNA fragments (400–600 bp inserts) were selected on the Pippin Prep platform. After construction of ddRADseq libraries, they were sequenced using 40% of a NovaSeq S4 X lane (2x150 bp paired-end run), and an average of 4.79 million (M) reads/sample or 1.44 giga base (Gb) per sample were generated. A 4X genome coverage (depth) was obtained on average. Approximately 50% of reads were chloroplast or mitochondria based on the basic local alignment search tool (BLAST). However, upon manually checking several reads to the reference genome ( https:/www.ncbi.nlm.nih.gov/assembly/GCA_000238415.2 ), samples aligned from 89.06 to 99.45% to the reference genome. This attests to a recent finding that there is exchange of genetic material between nuclear and organelle genome, and the mitochondrial and chloroplast genomes in watermelon share about 33% and 47% homology, respectively with the nuclear genome (Cui et al. 2021 ). The reference genome obtained from the National Center for Biotechnology Information (NCBI) website (GenBank assembly accession: GCA_000238415.2) corresponds to the watermelon cultivar ‘97103’ v2 Genome in the Cucurbit Genetics Database ( http://cucurbitgenomics.org/ftp/genome/watermelon/97103/v2/ ). At median 3 and mean 11 coverage depth, a total of 147,600 raw, unfiltered single nucleotide polymorphisms (SNPs) were obtained. After removing SNPs with depth > 20, a total of 134,136 SNPs were remaining. After filtering SNPs with minor allele frequency (MAF) < 0.05 and more than 20% missing data, a total of 653 SNP markers were left. QTL mapping, genetic linkage map and resistant gene After aligning the SNP regions between ‘97103’ and ‘Charleston Gray’ genomes, the physical coordinates of markers were updated to represent ‘Charleston Gray’ and used in the linkage map construction (Fig. 2 ). The rank based non-parametric QTL analysis was done on R ‘qtl’ and a significant SNP marker S8_5149002 was observed in the major QTL region (LOD = 14.06) (Table 1 and Fig. 2 ). The effect plot for the marker showed that the disease index was low and similar for the homozygous resistant ( Ar-1Ar-1 ) and heterozygous individuals ( Ar-1ar-1 ) as compared to the homozygous susceptible ( ar-1ar-1 ) (Fig. 3 ). Since GBS genotypic data resulted in higher missing value, QTL analysis was re-analyzed after multiple imputation in R/qtl. The LOD score for the significant marker increased from 14.06 to 44.42 after imputation. The QTL was validated on BC 1 P 1 and BC 1 P 2 populations, where only the latter population showed a significant QTL with S8_5149002 being the significant marker (LOD = 8.32; Supplementary Fig. S2 ). The physical coordinate of S8_5149002 marker did not align with the physical positions of adjacent markers on F 2 population probably due to inversion or crossover in this genome segment on the mapping population or due to the small population size of the mapping population. Such discrepancy in the order of marker locations was also observed earlier in the same region of Chromosome 8 in watermelon (Shang et al. 2016 ; Jang et al. 2019 ). The results from this study showed that a significant QTL, Qar1-8 , from Charleston Gray contributed to race 1 anthracnose resistance. Table 1 Quantitative trait loci (QTL) for race 1 anthracnose (ANTR_R1) resistance on chromosome 8 in ‘Charleston Gray’ X ‘New Hampshire Midget’ F 2 population. QTLs Marker Trait Chr Position (cM) LOD Qar1-8 S8_5149002 ANTR_R1 8 285.18 14.06 PACE based SNP genotyping and significant marker validation Out of 34 PACE markers designed, only three markers (S8_4483489, S8_4714069, and S8_5149002) were found to be polymorphic and clustered populations into three distinct groups - homozygous resistant, heterozygous, and homozygous susceptible. The proportion of individuals into different groups based on the PACE SNP genotyping and their Chi-square values are presented in Supplementary Table S3 . Non-parametric tests (Chi-Square, Mann-Whitney, and Kruskal-Wallis) using PACE-based genotypic data of three markers (S8_4483489, S8_4714069 and S8_5149002) showed varying results (Table 2 ). For Marker S8_4483489 and S8_4714069, the observed segregation ratios significantly deviated from expected Mendelian ratios ( P < 0.05) in the backcross population [BC 1 P 2 , expected 1( Ar-1ar-1 ):1( ar-1ar-1 )]. However, the Mann-Whitney test failed to reject the null hypothesis ( P = 0.12) for 1:1 ratio. The Chi-Square test for markers S8_4483489 and S8_4714069 on the F 2 population failed to reject ( P = 0.06) and rejected ( P < 0.001), respectively, the null hypothesis for expected ratios − 1( Ar-1Ar-1 ):2( Ar-1ar-1 ):1( ar-1ar-1 ). Furthermore, the Kruskal-Wallis test in F 2 population resulted in a significant difference ( P < 0.001) among Ar-1Ar-1 (homozygous resistant), ar-1ar-1 (homozygous susceptible), and Ar-1ar-1 (heterozygous) groups. Since the Kruskal-Wallis test in F 2 population was significant for the marker, a post-hoc analysis using Dunn’s test was done to compare how the three groups ( Ar-1Ar-1 , ar-1ar-1 , and Ar-1ar-1 ) differed from each other. There was significant difference between all groups: ( Ar-1Ar-1 vs ar-1ar-1 ), ( Ar-1Ar-1 vs Ar-1ar-1 ), and ( ar-1ar-1 vs Ar-1ar-1 ) ( P < 0.001), indicating that markers categorized homozygous dominant ( Ar-1Ar-1 ), heterozygous ( Ar-1ar-1 ), and homozygous recessive ( ar-1ar-1 ) into three separate groups based on phenotype. Results indicated that markers failed to correctly assign individuals into resistant and susceptible groups based on the single dominant gene. Thus, markers S8_4483489 and S8_4714069 were not diagnostic markers for Qar1-8 . Table 2 Results of non-parametric tests (Chi-Square, Mann-Whitney = MW, Kruskal-Wallis = KW, Dunn’s Test = DT) in BC 1 P 2 and F 2 population using information obtained from PACE-based genotyping. Marker BC1P2 F2 χ2 P MW ( P ) χ2 P KW: χ2 P DT: z ( Ar-1Ar-1 vs ar-1ar-1 ), ( Ar-1Ar-1 vs Ar-1ar-1 ) ( ar-1ar-1 vs Ar-1ar-1 ) P § S8_ 4483489 5.5 0.02 0.12 5.6 0.06 78.2 < 0.001 -8.69 -2.85 6.91 < 0.001 0.002 < 0.001 S8_ 4714069 3.9 0.04 0.12 11 < 0.001 67.7 < 0.001 -8.21 -3.62 6.17 < 0.001 < 0.001 < 0.001 S8_ 5149002 0.2 0.69 0.09 3.4 0.18 124.3 < 0.001 -9.46 -1.02 9.93 < 0.001 0.1523 < 0.001 § P ≥ 0.05 indicates there is no significant difference between observed and expected Mendelian ratios, or there is no significant difference between groups Ar-1Ar-1 , ar-1ar -1, and Ar-1ar-1 . P < 0.05 indicates there is significant difference between observed and expected Mendelian ratios or between groups Ar-1Ar-1 , ar-1ar-1 , and Ar-1ar-1 ; Ar-1Ar-1 = homozygous resistant parent alleles, ar-1ar-1 = homozygous susceptible parent alleles, and Ar-1ar-1 = heterozygous. Contrastingly, the marker S8_5149002 did not show deviation between the observed and expected Mendelian ratios in the BC 1 P 2 population for both the Chi-Square and Mann-Whitney test ( P = 0.09). The Chi-Square test in the F 2 population showed that there was no deviation ( P = 0.69) from expected Mendelian ratios − 1( Ar-1Ar-1 ):2( Ar-1ar-1 ):1( ar-1ar-1 ). The Kruskal-Wallis test in F 2 population showed that there was significant difference ( P < 0.05) among Ar-1Ar-1 , ar-1ar-1 , and Ar-1ar-1 groups. The post-hoc Dunn’s test showed significant difference between only the two groups ( Ar-1Ar-1 vs ar-1ar-1 ) and ( ar-1ar-1 vs Ar-1ar-1 ) ( P < 0.001) but not for the ( Ar-1Ar-1 vs Ar-1ar-1 ) group ( P = 0.1523). Results indicated that the marker, S8_5149002, was able to distinguish phenotypes, resistant ( Ar-1Ar-1 and Ar-1ar-1 ) versus susceptible ( ar-1ar-1 ) and agrees with earlier genetic studies that a single dominant gene controls race 1 anthracnose resistance. Results showed that S8_5149002 marker is the diagnostic marker located in the Qar1-8 region. The SNP marker S8_5149002 was used to discriminate the watermelon germplasm ( N = 61 ) for Colletotrichum orbiculare race 1 resistance. There were 19, 12, and 30 germplasm showing homozygous resistant, heterozygous, and homozygous susceptible alleles, respectively ( Supplementary Table S4 ). Discussion Phenotypic and genotypic ratios Colletotrichum orbiculare race 1 affects watermelon and cucumber in which a single dominant resistance gene was reported. In this study, the Chi-square analysis showed a goodness of fit for a single dominant gene controlling race 1 anthracnose resistance both phenotypically and genotypically. Similar Mendelian phenotypic segregation ratios were reported and suggested that a single dominant gene was involved for race 1 anthracnose resistance in watermelon – ‘Africa 8’ (Layton 1937 ), and ‘Charleston Gray’, ‘Congo’ and ‘Fairfax’ (Hall et al. 1960 ; Table 3 ). Resistance to anthracnose in beans was also found to be dominant in crosses of resistant x tolerant and resistant x susceptible varieties (Andrus and Wade 1942 ). A single dominant gene for anthracnose resistance was also reported in cucumber (Barnes and Epps 1952 ). Robinson et al. ( 1976 ) assigned Ar gene symbol for the anthracnose resistance gene in watermelon and cucumber. Winstead et al. (1959) also reported that race 1 anthracnose resistance gene also conferred race 3 anthracnose resistance in watermelon by superimposing race 3 inoculum on race 1 inoculated plants and vice-versa. The pedigree of ‘Charleston Gray’ had ‘Africa 8’, whereas the pedigree of ‘Congo’ and ‘Fairfax’ had ‘African’ (Table 3 ). It is most likely that Ar-1 in ‘Charleston Gray’ might had been inherited from ‘Africa 8’, a race 1 anthracnose resistance founder parent. Table 3 Pedigrees of race 1 anthracnose resistant ( R ) and susceptible ( S ) watermelon cultivars. Genotype Pedigree Race 1 Anthracnose response References Charleston Gray [{(Africa 8 x Iowa Belle) x Garrison} x Garrison] x [(Hawkesbury x Leesburg) x Garrison] R (Hall et al. 1960 ; Levi et al. 2001b ) Congo (African x Iowa Belle) x Garrison R (Hall et al. 1960 ; Levi et al. 2001b ) Fairfax [Garrison x (African x Iowa Belle)] x [(Leesburg x Hawkesbury)] R (Hall et al. 1960 ; Levi et al. 2001b ) New Hampshire Midget (Favorite Honey x Dakota Sweet) S (Yeager 1950; Rhodes et al. 1992 ) Resistance QTL and putative genes In the study, the preliminary analysis using GBS markers identified race 1 anthracnose resistance QTL on chromosome 8 (in between coordinates 4,847,957 and 6,294,791). The QTL on chromosome 8 was on the similar region to the previous study (Jang et al. 2019 ). One of the genes, CC-NBS-LRR (CNL; Cla001017 or ClCG08G002410 ), in the QTL region was reported for race 1 anthracnose resistance on breeding line ‘DrHS7250’ (Jang et al. 2019 ). We converted the high-resolution melting (HRM) SNP marker, CL14-27-9, for ClCG08G002410 onto the PACE marker and designated it as S8_5149002. We reanalyzed F 2 mapping population data by including genotypic data for marker S8_5149002. The result showed that S8_5149002 was the significant marker with LOD up to 44 (with imputation) and could indicate that ClCG08G002410 could also be the race 1 anthracnose resistance gene in ‘Charleston Gray’. Variable genotype of watermelon germplasm The significant SNP marker S8_5149002 clearly differentiated the disease response of the individuals of the mapping population as well as the germplasm present in the watermelon breeding program. Genotype of several watermelon germplasm and hybrids showed homozygous resistance to race 1 anthracnose. These include ‘Crimson Sweet’, ‘TASTIGOLD’, ‘AU-Sweet Scarlet’, ‘AU-Golden Producer’, ‘Perola’, ‘Crimson Diamond’, ‘Graybelle’, ‘Verona’, ‘SUNSHADE’, ‘Sugarlee’, ‘Dixielee’, ‘Jubilee’, ‘Big Stripe’, ‘Pronto’, ‘Pathfinder F 1 ’, and ‘Fascination’. For most of them the source of race 1 anthracnose resistance might had inherited from the founder parent – ‘Africa 8’. It is intriguing that the Ar-1 gene is exhibiting resistance for more than 50 years. Interestingly, the germplasm PI 189225 which is resistant to race 2 anthracnose (Levi et al. 2001a ), showed susceptible genotype ( ar-1ar-1 ) for race 1 anthracnose suggesting race-specific resistance provided by the R -genes. Conclusion The study delineates a major QTL region on chromosome 8 governing race 1 anthracnose resistance and putative CC-NBS-LRR (CNL; ClCG08G002410 ) could be a potential resistance gene in Charleston Gray. Further study is needed to validate that the CNL is the Ar-1 gene. The S8_5149002 is a diagnostic marker for race 1 anthracnose resistance and could be used in MAS in watermelon breeding programs. Declarations Acknowledgments We thank Jared Smith, USDA-ARS, NC and Dr. Robert Vaughn, TAMU for assistance on PACE primer design. We would also like to thank Drs. Nithya Subramanian and Madhumita Joshi for testing DNA quantity and quality. Funding This research was supported by USDA Hatch Project TEX09665, Texas A&M AgriLife Vegetable Seed Grant, Texas A&M University Excellence Fellowship, and Texas A&M AgriLife Research Strategic Initiative Assistantship. Author Contributions Conceptualization: T.C.W., T.P., and S.M.; Methodology: T.P., B.P.B, E.C., R.M., S.W., M.B., C.D.J., and S.M.; Software: S.W., M.B., B.P.B., and S.M.; Validation: S.M.; Formal analysis: B.P.B. and S.M.; Investigation : T.P., B.P.B., E.C., and S.M.; Resources : T.C.W. and S.M.; Data curation: B.P.B. and S.M.; Writing —original draft preparation, B.P.B.; Writing—review and editing: T.C.W, K.M.C., M.J.T., R.M., M.B., C.D.J., S.M.; Visualization: B.P.B. and S.M.; Supervision: T.C.W., C.D.J. and S.M.; Funding acquisition: T.C.W. and S.M. Conflicts of Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Ethical approval Not applicable. Consent to participate Not applicable. Consent for publication Not applicable. 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Genetics 159:371-387. https://doi.org/10.1093/genetics/159.1.371 Shang J, Li N, Li N, Xu Y, Ma S, Wang J (2016) Construction of a high-density genetic map for watermelon ( Citrullus lanatus L.) based on large-scale SNP discovery by specific length amplified fragment sequencing (SLAF-seq). Scientia Hort 203:38-46. https://doi.org/10.1016/j.scienta.2016.03.007 Sitterly WR (1972) Breeding for disease resistance in cucurbits. Annu Rev Phytopathol 10:471-490. https://doi.org/10.1146/annurev.py.10.090172.002351 Thompson D, Jenkins S (1985) Influence of cultivar resistance, initial disease, environment, and fungicide concentration and timing on anthracnose development and yield loss in pickling cucumbers. Phytopathology 75:1422-1427 USDA-AMS (2021) United States Standards for Grades of Watermelons. United States Department of Agriculture (Agricultural Marketing Service, Specialty Crops Program, Specialty Crops Inspection Division), Washington, D.C. https://www.ams.usda.gov/sites/default/files/media/WatermelonStandards.pdf (Accessed on 03/23/2022). USDA-NASS (2021) Vegetables 2020 Summary. United States Department of Agriculture (National Agricultural Statistics Service). https://downloads.usda.library.cornell.edu/usda-esmis/files/02870v86p/j6731x86f/9306tr664/vegean21.pdf (Accessed on 03/23/2022). Voorrips R (2002) MapChart: software for the graphical presentation of linkage maps and QTLs. J Hered 93:77-78. https://doi.org/10.1093/jhered/93.1.77 Vos P, Hogers R, Bleeker M, Reijans M, Lee Tvd, Hornes M, Friters A, Pot J, Paleman J, Kuiper M (1995) AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res 23:4407-4414. https://doi.org/10.1093/nar/23.21.4407 Wasilwa L, Correll J, Morelock T, McNew R (1993) Reexamination of races of the cucurbit anthracnose pathogen Colletotrichum orbiculare . Phytopathology 83:1190-1198 Wehner TC (2012) Gene List for Watermelon; https://cucurbit.info/2012/07/2012-gene-list-for-watermelon/ (Accessed on 03/23/2022). Wilcoxon F (1945) Individual Comparisons by Ranking Methods. Biometrics Bul 1:80-83 Williams JG, Kubelik AR, Livak KJ, Rafalski JA, Tingey SV (1990) DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Res 18:6531-6535. https://doi.org/10.1093/nar/18.22.6531 Winstead N, Goode M, Barham W (1959) Resistance in watermelon to Colletotrichum lagenarium races 1, 2, and 3. Plant Dis Rptr 43:570-577 Xu Y, Crouch JH (2008) Marker‐assisted selection in plant breeding: From publications to practice. Crop Sci 48:391-407. https://doi.org/10.2135/cropsci2007.04.0191 Xuei X, Järlfors U, Kuć J (1988) Ultrastructural changes associated with induced systemic resistance of cucumber to disease: host response and development of Colletotrichum lagenarium in systemically protected leaves. Can J of Bot 66:1028-1038. https://doi.org/10.1139/b88-148 Yang Y, Dhakal S, Chu C, Wang S, Xue Q, Rudd JC, Ibrahim AMH, Jessup K, Baker J, Fuentealba MP, Devkota R, Baker S, Johnson CD, Metz R, Liu S (2020) Genome wide identification of QTL associated with yield and yield components in two popular wheat cultivars TAM 111 and TAM 112. PLOS ONE 15:e0237293. https://doi.org/10.1371/journal.pone.0237293 Yeager AF (1950) Breeding improved horticultural plants. I. Vegetables. The University of New Hampshire. https://scholars.unh.edu/cgi/viewcontent.cgi?article=1341&context=agbulletin (Accessed on 03/23/2022). Yong X, Guo S (2017) The Watermelon Genome. In: R. Grumet NK, & J. Garcia-Mas (ed) Genetics and Genomics of Cucurbitaceae. Springer International Publishing., pp 199-210 Yuan H-Y, Chiou J-J, Tseng W-H, Liu C-H, Liu C-K, Lin Y-J, Wang H-H, Yao A, Chen Y-T, Hsu C-N (2006) FASTSNP: an always up-to-date and extendable service for SNP function analysis and prioritization. Nucleic Acids Res 34:W635-W641. https://doi.org/10.1093/nar/gkl236 Supplementary Files FigS1.tif FigS2.tif Cite Share Download PDF Status: Published Journal Publication published 17 Oct, 2022 Read the published version in Euphytica → Version 1 posted Editorial decision: Major revisions 16 Jul, 2022 Reviewers agreed at journal 08 Jun, 2022 Editor assigned by journal 03 Jun, 2022 First submitted to journal 30 May, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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The arrows mark the average disease rating (%) for the resistant and susceptible parents in the F\u003csub\u003e2\u003c/sub\u003e population.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1710183/v1/024a8c7439ca908520d3b9e9.png"},{"id":22420630,"identity":"9738d4cb-8ca5-46ba-b5b1-84d9e6152f16","added_by":"auto","created_at":"2022-06-08 16:12:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":112900,"visible":true,"origin":"","legend":"\u003cp\u003eGenetic linkage map showing the significant QTL for race 1 anthracnose resistance, \u003cem\u003eQar1-8\u003c/em\u003e, on Chromosome 8.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1710183/v1/dcd522893c3bc298845e9672.png"},{"id":22420099,"identity":"473e09f5-319c-46c6-83a4-69efd74d0277","added_by":"auto","created_at":"2022-06-08 16:07:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":10103,"visible":true,"origin":"","legend":"\u003cp\u003eEffect plot for the significant marker, S8_5149002, on \u003cem\u003eQar1-8\u003c/em\u003e showing the mean and standard error for each genotypic class: \u003cem\u003eAr-1Ar-1\u003c/em\u003e = homozygous resistant parent alleles, \u003cem\u003ear-1ar-1\u003c/em\u003e = homozygous susceptible parent alleles, and \u003cem\u003eAr-1ar-1\u003c/em\u003e = heterozygous.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1710183/v1/ce4e9b323bd81a0d0c514ac4.png"},{"id":29971420,"identity":"dddb72b5-90a5-4c60-8afc-2f74900cf84e","added_by":"auto","created_at":"2022-12-06 15:49:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":602314,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1710183/v1/84e7498d-0f1b-4e1c-a6c9-e6ca5d5aa863.pdf"},{"id":22420102,"identity":"9c06a1cc-ca13-4cc4-867d-842042bca45d","added_by":"auto","created_at":"2022-06-08 16:07:46","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1543772,"visible":true,"origin":"","legend":"","description":"","filename":"FigS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-1710183/v1/0454745b19bc222751a2d985.tif"},{"id":22420101,"identity":"85302392-a252-46de-9323-0f73fdc6b688","added_by":"auto","created_at":"2022-06-08 16:07:46","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1020348,"visible":true,"origin":"","legend":"","description":"","filename":"FigS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-1710183/v1/37446e5fc2eca6d3d7cdd43d.tif"}],"financialInterests":"","formattedTitle":"Dissection of Race 1 Anthracnose Resistance in a Watermelon (Citrullus lanatus var. lanatus) Biparental Mapping Population","fulltext":[{"header":"Introduction","content":"\u003cp\u003e Watermelon (\u003cem\u003eCitrullus lanatus\u003c/em\u003e var. \u003cem\u003elanatus\u003c/em\u003e) occupies 7% of global vegetable production acreage and is among the top five most consumed fresh fruits in the world (Yong and Guo 2017). In 2020, watermelon was grown on 100,000 acres and worth \u003cspan\u003e$\u003c/span\u003e574\u0026nbsp;million in the U.S. (USDA-NASS 2021). The major watermelon growing states in the U.S. are Florida, Texas, Georgia, and California. Anthracnose is one of the major diseases of watermelon and other cucurbits and is caused by the fungal pathogen \u003cem\u003eColletotrichum orbiculare\u003c/em\u003e (Berk. \u0026amp; Mont.) Arx syn. \u003cem\u003elagenaria\u003c/em\u003e. The fungus is a hemibiotroph ascomycete that occurs intracellularly in the plant hosts (Perfect et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Dickman \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Xuei et al. 1988). Though seven races of \u003cem\u003eC. orbiculare\u003c/em\u003e have been described (Wasilwa et al. 1993; Sitterly \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1972\u003c/span\u003e), only three races of the fungus (races 1, 2, and 3) are of importance in watermelon (Boyhan et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). A large number of watermelon germplasm are resistant to \u003cem\u003eColletotrichum orbiculare\u003c/em\u003e race 1 and 3, while others are susceptible (Maynard and Hopkins \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Wasilwa et al. 1993). The disease affects all above ground parts and symptoms include angular, brown to black leaf spots; tan, oval-shaped lesions in stems; sunken, and water-soaked spots on fruits (Elwakil et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Dutta \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1958\u003c/span\u003e; Layton \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1937\u003c/span\u003e). Wet weather conditions such as rain and high humidity provide a favorable environment for dispersion and germination of conidia, and subsequent infection in plant (Maynard and Hopkins \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral accounts of anthracnose as a major disease in cucurbits can be traced back to the late 19th century and early 20th century (Gardner \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1918\u003c/span\u003e; Parris \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1949\u003c/span\u003e). The most severe reports of this disease was mainly in south, southeast, northeast, and mid-west regions of the U.S. (Wasilwa et al. 1993), with up to 30% yield loss reported in watermelon (Parris \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1949\u003c/span\u003e) and 60% yield loss reported in other cucurbits (Thompson and Jenkins \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). A significant negative impact on plants due to anthracnose is on fruit quality, as this disease influences grading standards of watermelon outlined by the United States Department of Agriculture (USDA-AMS \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Research on anthracnose disease management in watermelon has been prioritized in the past (King and Davis \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), and is still considered a major research priority (Kousik et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral efforts focused on breeding watermelon varieties for anthracnose resistance have been reported (Huh et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010a\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003eb\u003c/span\u003e; Crall et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Norton et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Crall \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). Resistance to race 1 anthracnose in watermelons has been shown to be governed by a single dominant locus, \u003cem\u003eAr-1\u003c/em\u003e, and resistance was dominant to susceptibility (Layton \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1937\u003c/span\u003e; Wehner 2012). Utilizing molecular markers closely associated with underlying genes can increase efficiency of the breeding programs (Xu and Crouch 2008). Single nucleotide polymorphism (SNP) markers are the latest of the molecular markers, succeeding restriction fragment length polymorphisms (RFLP) markers (Beckmann and Soller \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1986\u003c/span\u003e), random amplified polymorphic DNA (RAPD) markers (Williams et al. 1990), simple sequence repeats (SSRs) or microsatellite markers (Litt and Luty \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Akkaya et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1992\u003c/span\u003e), and amplified fragment length polymorphisms (AFLP) markers (Vos et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). The popularity of SNP markers stems from the fact that they are commonly occurring DNA sequence variations, the basis of most genetic variation (Ganal and R\u0026ouml;der \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Chagn\u0026eacute; et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), high density, cost effective and efficient compared to previous types of markers (Xu and Crouch 2008), and may affect protein function if present in the coding sequences (Yuan et al. 2006).\u003c/p\u003e \u003cp\u003eIn the current study, we identified a major quantitative trait loci (QTL) for \u003cem\u003eC\u003c/em\u003e. \u003cem\u003eorbiculare\u003c/em\u003e race 1 resistance from \u0026lsquo;Charleston Gray\u0026rsquo; in a F\u003csub\u003e2\u003c/sub\u003e population and validated on BC\u003csub\u003e1\u003c/sub\u003e populations. We further delineated a putative race 1 anthracnose resistant gene in the QTL region and used a previously reported SNP marker (Jang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) to differentiate race 1 anthracnose resistant and susceptible individuals from the mapping population, as well as the broader watermelon germplasm pool.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDeveloping biparental mapping populations\u003c/h2\u003e \u003cp\u003eThe watermelon mapping populations were developed at North Carolina State University. Two parental lines, \u0026lsquo;Charleston Gray\u0026rsquo;(resistant, female parent, P\u003csub\u003e1\u003c/sub\u003e) developed by C. F. Andrus in 1954 (Andrus \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1955\u003c/span\u003e), and \u0026lsquo;New Hampshire Midget\u0026rsquo; (susceptible, male parent, P\u003csub\u003e2\u003c/sub\u003e) were used to generate F\u003csub\u003e1\u003c/sub\u003e, F\u003csub\u003e2\u003c/sub\u003e, BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e1\u003c/sub\u003e, and BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003e mapping populations. The mapping populations consisted of 228 F\u003csub\u003e2\u003c/sub\u003e individuals as well as 60 individuals each in BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e1\u003c/sub\u003e and BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eInoculum preparation and pathogen inoculation\u003c/h2\u003e \u003cp\u003e \u003cem\u003eColletotrichum orbiculare\u003c/em\u003e race 1, collected in North Carolina in 1998, was used to inoculate seedlings. The inoculum preparation and inoculation were conducted as described by Patel (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In brief, the fungus was grown on green bean agar (GBA) media for three-weeks. Spores were harvested by adding 10 to 15 mL distilled water to each agar plate, rubbing the surface of the agar with a sterile metal spreader, pouring the spore suspension into a sterile conical flask, and passing it through four layers of cheesecloth. Concentration of the inoculum was measured using a hemocytometer and adjusted to 100,000 spores mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e prior to inoculation. One drop of Tween-20 was added to every 500 mL of the spore inoculum. The three-week-old watermelon seedlings grown in the greenhouse were inoculated with the spore inoculum. After inoculation, seedlings were kept in a humidity chamber, in the greenhouse, for 48 h in darkness at 80\u0026ndash;100% relative humidity, and at a temperature of 22 to 24\u0026deg;C. Then, seedlings were moved to the natural light, and rated at 8, 11, and 14 days post inoculation (dpi).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDisease rating\u003c/h2\u003e \u003cp\u003eThe disease index was rated on a scale of 0 to 100%, with an interval of 5%, with weightage on different parts of the plants - true leaves (50% total: yellowing- 5%, complete necrotic leaf- 40%, petiole-10%), meristem (25% total: necrosis spots-10%, mostly necrotic- 20%, dead-25%), hypocotyl (20% total: 1\u0026ndash;2 brown patches-5%, many brown patches-15%, completely brown-20%), cotyledons (5% total: little to complete necrosis: 5%). Individuals were designated as resistant and susceptible when the overall rating score was \u0026le;\u0026thinsp;40%, and \u0026ge;\u0026thinsp;41%, respectively (Patel \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDNA isolation, ddRADseq library construction, and genotyping by sequencing\u003c/h2\u003e \u003cp\u003eA total of 360 watermelon leaf samples (three P\u003csub\u003e1\u003c/sub\u003e, three P\u003csub\u003e2\u003c/sub\u003e, six F\u003csub\u003e1\u003c/sub\u003e, 60 BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e1\u003c/sub\u003e, 60 BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003e, and 228 F\u003csub\u003e2\u003c/sub\u003e individuals) were collected from three-week-old seedlings. Samples were freeze-dried immediately, and genomic DNA was extracted from lyophilized samples using E.Z.N.A. Plant DNA Kit (Omega Bio-tek, GA, USA) following manufacturer\u0026rsquo;s protocol. The DNA were quantified using Quant-iT-PicoGreen (Invitrogen, Thermo Fisher Scientific, USA) following the manufacturer\u0026rsquo;s instructions. Due to some samples yielding low amounts of DNA, a total of 188 watermelon samples (three P\u003csub\u003e1\u003c/sub\u003e, two P\u003csub\u003e2\u003c/sub\u003e, six F\u003csub\u003e1\u003c/sub\u003e, 48 BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e1\u003c/sub\u003e and 129 F\u003csub\u003e2\u003c/sub\u003e individuals) were sent to Texas A\u0026amp;M AgriLife Genomics and Bioinformatics Service, College Station, TX (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.txgen.tamu.edu/\u003c/span\u003e\u003cspan address=\"https://www.txgen.tamu.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for double digest restriction-site associated DNA sequencing (ddRADseq) as described previously (Yang et al. 2020) with the following changes. The restriction enzymes \u003cem\u003eEcoR\u003c/em\u003eI and \u003cem\u003eNla\u003c/em\u003eIII were used for library prep and inserts from 400 to 600 bp were selected on a Pippin prep (Sage Science, Boston, MA, USA). The ddRADseq libraries were sequenced using 40% of a NovaSeq S4 X lane (2 x150 bp paired-end run; Illumina, Inc., San Diego, CA, USA).\u003c/p\u003e \u003cp\u003eRaw sequences were demultiplexed using Illumina bcl2fastq, allowing for 1 base error in the barcode sequences. Sequences were first quality-filtered using the program FASTX-Toolkit (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://hannonlab.cshl.edu/fastx-toolkit\u003c/span\u003e\u003cspan address=\"http://hannonlab.cshl.edu/fastx-toolkit\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Raw sequencing reads were first trimmed to remove low quality bases with quality score less than 20 on the ends of reads and reads with 30% or more bases showing low quality score (Q\u0026thinsp;\u0026lt;\u0026thinsp;15) were removed. The reference genome for watermelon was downloaded from NCBI website (GCA_000238415.2). Bowtie2 [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bowtie-bio.sourceforge.net/bowtie2/index.shtml\u003c/span\u003e\u003cspan address=\"http://bowtie-bio.sourceforge.net/bowtie2/index.shtml\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e] was used to align quality-filtered reads to the reference with the default parameters. Aligned reads were then processed with SAMtools v1.19 to generate coordinate sorted binary SAM files (BAM). Reads with mapping quality (MQ) less than 5 were removed. The local re-alignment tool in the Genome Analysis Toolkit (GATK, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://software.broadinstitute.org/gatk/\u003c/span\u003e\u003cspan address=\"https://software.broadinstitute.org/gatk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to perform re-alignment in Insertion/Deletion regions as previously described. Finally, the processed alignment files were fed to the tool HaplotypeCaller, which is part of the GATK, to call variations and perform genotyping for each sample. Once the SNP calling process was completed, individual SNPs with more than 20% missing data and Minor Allele Frequency (MAF) less than 0.05 in each population group were removed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eQTL mapping\u003c/h2\u003e \u003cp\u003eGenotypic data were assigned to A (P\u003csub\u003e1\u003c/sub\u003e type, homozygous resistant), B (P\u003csub\u003e2\u003c/sub\u003e type, homozygous susceptible), H (heterozygous), and X (missing) types. Since the phenotypic disease rating data for F\u003csub\u003e2\u003c/sub\u003e population were found to be in a non-normal distribution, QTL analysis was done on \u0026lsquo;qtl\u0026rsquo; package (Broman et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) with a non-parametric method (\u0026lsquo;model\u0026thinsp;=\u0026thinsp;np\u0026rsquo;) on R software (R Core Team 2014; version 3.6.2) with RStudio GUI (RStudio-Team \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The logarithm of odds (LOD) threshold of 4.11 for QTL detection was estimated with 1,000 permutations. As genotyping-by-sequencing (GBS) genotypic data had higher missing values, QTL analysis was also performed after imputing missing genotypic data using a multiple imputation method (\u0026lsquo;method\u0026thinsp;=\u0026thinsp;imp\u0026rsquo;) (Sen and Churchill \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) on R \u0026lsquo;qtl\u0026rsquo;. A graphical display of allele effects was done using \u0026ldquo;Effect Plot\u0026rdquo; function on R \u0026lsquo;qtl\u0026rsquo;. A genetic linkage map was constructed using IciMapping V4.1 (Meng et al., 2014), whereas the linkage map was displayed using MapChart version 2.32 (Voorrips \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePACE-based SNP genotyping and non-parametric analysis\u003c/h2\u003e \u003cp\u003eAllele-specific primers were designed for 34 SNP markers in and around the QTL region using PrimerQuest\u0026trade; Tool (IDT, Coralville, IA, USA) and confirmed manually. Polymerase chain reaction (PCR) allelic competitive extension (PACE) genotyping chemistry constituting FAM, HEX, and ROX fluorophores was used to analyze the SNPs (3CR Bioscience, Essex, UK). The polymorphic PACE SNP markers (\u003cem\u003eSupplementary Table S1\u003c/em\u003e) were used to genotype the mapping populations (\u003cem\u003eN\u0026thinsp;=\u0026thinsp;360\u003c/em\u003e) as well as watermelon germplasm (\u003cem\u003eN\u0026thinsp;=\u0026thinsp;61\u003c/em\u003e). The PACE SNP marker was also designed for a previously reported high resolution melting SNP marker, CL14-27-9 (\u003cem\u003eSupplementary Fig. S1\u003c/em\u003e), for CC-NBS-LRR gene (CNL; \u003cem\u003eCla001017\u003c/em\u003e or \u003cem\u003eClCG08G002410\u003c/em\u003e) (Jang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and designated as S8_5149002 to match the physical coordinates of the Charleston Gray genome. The PACE PCR components included 4 \u0026micro;L of PACE Genotyping Master Mix (2X) (3CR Bioscience, Essex, UK), 0.11 \u0026micro;L primer assay mix (72X), 2 \u0026micro;L template DNA and 2 \u0026micro;L of molecular biology grade water. The PCR was carried out in the Eppendorf flexlid nexus gradient Mastercycler (Eppendorf, Hamburg, Germany). The PCR conditions included one cycle of enzyme activation (94℃, 15 min), followed by 10 cycles each of template denaturation (94℃, 20 s) and annealing/extension with drop of 0.8℃ per cycle (65 to 57℃, 60 s), and 27 cycles each of denaturation (94℃, 20 s), and annealing/extension (57℃, 60 s) (3crBioscience \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). KlusterCaller software version 3.4.1.36 (LGC Genomics, Herts, UK) was used to cluster genotypes using BMG Labtech Omega machine (BMG Labtech, Ortenberg, Germany). An additional 3 to 9 cycles of final denaturation and annealing/extension was done to improve the amplification, as well as to obtain tight and well separated clusters. Several non-parametric analysis - Chi-Square, Mann-Whitney-Wilcoxon test (Wilcoxon 1945; Mann and Whitney \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1947\u003c/span\u003e), Kruskal-Wallis test (Kruskal and Wallis \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1952\u003c/span\u003e), and Dunn\u0026rsquo;s test (Dunn \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1964\u003c/span\u003e) were conducted on data on R software (R Core Team 2014; version 3.6.2) with RStudio GUI (RStudio-Team \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) using functions \u0026lsquo;chisq.test\u0026rsquo;, \u0026lsquo;wilcox.test\u0026rsquo;, \u0026lsquo;kruskal.test\u0026rsquo;, and \u0026lsquo;dunn.test\u0026rsquo;, respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDisease response of the mapping population\u003c/h2\u003e \u003cp\u003ePhenotypic disease response of race 1 anthracnose inoculated mapping populations (\u003cem\u003eN\u0026thinsp;=\u0026thinsp;360\u003c/em\u003e) resulted in Mendelian ratios for a single gene (\u003cem\u003eSupplementary Table S2\u003c/em\u003e). All 60 BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e1\u003c/sub\u003e individuals showed no segregation and had 100% resistance phenotype. The 60 BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003e individuals (χ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e1:1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.26, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.60) failed to reject the null hypothesis of 1:1::resistant:susceptible segregation ratio. The 228 F\u003csub\u003e2\u003c/sub\u003e individuals (χ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003e3:1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;2.33, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12) also failed to reject the null hypothesis of 3:1::resistant:susceptible segregation ratio. The histograms of the BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e1\u003c/sub\u003e, BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003e, and F\u003csub\u003e2\u003c/sub\u003e population (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) indicated a non-normal phenotypic distribution.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of ddRADseq data\u003c/h2\u003e \u003cp\u003eGenerated DNA fragments (400\u0026ndash;600 bp inserts) were selected on the Pippin Prep platform. After construction of ddRADseq libraries, they were sequenced using 40% of a NovaSeq S4 X lane (2x150 bp paired-end run), and an average of 4.79\u0026nbsp;million (M) reads/sample or 1.44 giga base (Gb) per sample were generated. A 4X genome coverage (depth) was obtained on average. Approximately 50% of reads were chloroplast or mitochondria based on the basic local alignment search tool (BLAST). However, upon manually checking several reads to the reference genome (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps:/www.ncbi.nlm.nih.gov/assembly/GCA_000238415.2\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/assembly/GCA_000238415.2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), samples aligned from 89.06 to 99.45% to the reference genome. This attests to a recent finding that there is exchange of genetic material between nuclear and organelle genome, and the mitochondrial and chloroplast genomes in watermelon share about 33% and 47% homology, respectively with the nuclear genome (Cui et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The reference genome obtained from the National Center for Biotechnology Information (NCBI) website (GenBank assembly accession: GCA_000238415.2) corresponds to the watermelon cultivar \u0026lsquo;97103\u0026rsquo; v2 Genome in the Cucurbit Genetics Database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cucurbitgenomics.org/ftp/genome/watermelon/97103/v2/\u003c/span\u003e\u003cspan address=\"http://cucurbitgenomics.org/ftp/genome/watermelon/97103/v2/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). At median 3 and mean 11 coverage depth, a total of 147,600 raw, unfiltered single nucleotide polymorphisms (SNPs) were obtained. After removing SNPs with depth\u0026thinsp;\u0026gt;\u0026thinsp;20, a total of 134,136 SNPs were remaining. After filtering SNPs with minor allele frequency (MAF)\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and more than 20% missing data, a total of 653 SNP markers were left.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eQTL mapping, genetic linkage map and resistant gene\u003c/h2\u003e \u003cp\u003eAfter aligning the SNP regions between \u0026lsquo;97103\u0026rsquo; and \u0026lsquo;Charleston Gray\u0026rsquo; genomes, the physical coordinates of markers were updated to represent \u0026lsquo;Charleston Gray\u0026rsquo; and used in the linkage map construction (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The rank based non-parametric QTL analysis was done on R \u0026lsquo;qtl\u0026rsquo; and a significant SNP marker S8_5149002 was observed in the major QTL region (LOD\u0026thinsp;=\u0026thinsp;14.06) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The effect plot for the marker showed that the disease index was low and similar for the homozygous resistant (\u003cem\u003eAr-1Ar-1\u003c/em\u003e) and heterozygous individuals (\u003cem\u003eAr-1ar-1\u003c/em\u003e) as compared to the homozygous susceptible (\u003cem\u003ear-1ar-1\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Since GBS genotypic data resulted in higher missing value, QTL analysis was re-analyzed after multiple imputation in R/qtl. The LOD score for the significant marker increased from 14.06 to 44.42 after imputation. The QTL was validated on BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e1\u003c/sub\u003e and BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003e populations, where only the latter population showed a significant QTL with S8_5149002 being the significant marker (LOD\u0026thinsp;=\u0026thinsp;8.32; \u003cem\u003eSupplementary Fig. S2\u003c/em\u003e). The physical coordinate of S8_5149002 marker did not align with the physical positions of adjacent markers on F\u003csub\u003e2\u003c/sub\u003e population probably due to inversion or crossover in this genome segment on the mapping population or due to the small population size of the mapping population. Such discrepancy in the order of marker locations was also observed earlier in the same region of Chromosome 8 in watermelon (Shang et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Jang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The results from this study showed that a significant QTL, \u003cem\u003eQar1-8\u003c/em\u003e, from Charleston Gray contributed to race 1 anthracnose resistance.\u003c/p\u003e \u003cp\u003e \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\u003eQuantitative trait loci (QTL) for race 1 anthracnose (ANTR_R1) resistance on chromosome 8 in \u0026lsquo;Charleston Gray\u0026rsquo; X \u0026lsquo;New Hampshire Midget\u0026rsquo; F\u003csub\u003e2\u003c/sub\u003e population.\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\u003eQTLs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePosition (cM)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLOD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eQar1-8\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS8_5149002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eANTR_R1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e285.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.06\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 \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePACE based SNP genotyping and significant marker validation\u003c/h2\u003e \u003cp\u003eOut of 34 PACE markers designed, only three markers (S8_4483489, S8_4714069, and S8_5149002) were found to be polymorphic and clustered populations into three distinct groups - homozygous resistant, heterozygous, and homozygous susceptible. The proportion of individuals into different groups based on the PACE SNP genotyping and their Chi-square values are presented in \u003cem\u003eSupplementary Table S3\u003c/em\u003e. Non-parametric tests (Chi-Square, Mann-Whitney, and Kruskal-Wallis) using PACE-based genotypic data of three markers (S8_4483489, S8_4714069 and S8_5149002) showed varying results (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). For Marker S8_4483489 and S8_4714069, the observed segregation ratios significantly deviated from expected Mendelian ratios (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the backcross population [BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003e, expected 1(\u003cem\u003eAr-1ar-1\u003c/em\u003e):1(\u003cem\u003ear-1ar-1\u003c/em\u003e)]. However, the Mann-Whitney test failed to reject the null hypothesis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12) for 1:1 ratio. The Chi-Square test for markers S8_4483489 and S8_4714069 on the F\u003csub\u003e2\u003c/sub\u003e population failed to reject (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.06) and rejected (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respectively, the null hypothesis for expected ratios\u0026thinsp;\u0026minus;\u0026thinsp;1(\u003cem\u003eAr-1Ar-1\u003c/em\u003e):2(\u003cem\u003eAr-1ar-1\u003c/em\u003e):1(\u003cem\u003ear-1ar-1\u003c/em\u003e). Furthermore, the Kruskal-Wallis test in F\u003csub\u003e2\u003c/sub\u003e population resulted in a significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) among \u003cem\u003eAr-1Ar-1\u003c/em\u003e (homozygous resistant), \u003cem\u003ear-1ar-1\u003c/em\u003e (homozygous susceptible), and \u003cem\u003eAr-1ar-1\u003c/em\u003e (heterozygous) groups. Since the Kruskal-Wallis test in F\u003csub\u003e2\u003c/sub\u003e population was significant for the marker, a \u003cem\u003epost-hoc\u003c/em\u003e analysis using Dunn\u0026rsquo;s test was done to compare how the three groups (\u003cem\u003eAr-1Ar-1\u003c/em\u003e, \u003cem\u003ear-1ar-1\u003c/em\u003e, and \u003cem\u003eAr-1ar-1\u003c/em\u003e) differed from each other. There was significant difference between all groups: (\u003cem\u003eAr-1Ar-1\u003c/em\u003e vs \u003cem\u003ear-1ar-1\u003c/em\u003e), (\u003cem\u003eAr-1Ar-1\u003c/em\u003e vs \u003cem\u003eAr-1ar-1\u003c/em\u003e), and (\u003cem\u003ear-1ar-1\u003c/em\u003e vs \u003cem\u003eAr-1ar-1\u003c/em\u003e) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that markers categorized homozygous dominant (\u003cem\u003eAr-1Ar-1\u003c/em\u003e), heterozygous (\u003cem\u003eAr-1ar-1\u003c/em\u003e), and homozygous recessive (\u003cem\u003ear-1ar-1\u003c/em\u003e) into three separate groups based on phenotype. Results indicated that markers failed to correctly assign individuals into resistant and susceptible groups based on the single dominant gene. Thus, markers S8_4483489 and S8_4714069 were not diagnostic markers for \u003cem\u003eQar1-8\u003c/em\u003e.\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\u003eResults of non-parametric tests (Chi-Square, Mann-Whitney\u0026thinsp;=\u0026thinsp;MW, Kruskal-Wallis\u0026thinsp;=\u0026thinsp;KW, Dunn\u0026rsquo;s Test\u0026thinsp;=\u0026thinsp;DT) in BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003e and F\u003csub\u003e2\u003c/sub\u003e population using information obtained from PACE-based genotyping.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBC1P2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c11\" namest=\"c7\"\u003e \u003cp\u003eF2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW (\u003cem\u003eP\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eKW: χ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDT: z\u003c/p\u003e \u003cp\u003e(\u003cem\u003eAr-1Ar-1\u003c/em\u003e vs \u003cem\u003ear-1ar-1\u003c/em\u003e),\u003c/p\u003e \u003cp\u003e(\u003cem\u003eAr-1Ar-1\u003c/em\u003e vs \u003cem\u003eAr-1ar-1\u003c/em\u003e) (\u003cem\u003ear-1ar-1\u003c/em\u003e vs \u003cem\u003eAr-1ar-1\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS8_\u003c/p\u003e \u003cp\u003e4483489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e78.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-8.69\u003c/p\u003e \u003cp\u003e-2.85\u003c/p\u003e \u003cp\u003e 6.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003e0.002\u003c/p\u003e \u003cp\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS8_\u003c/p\u003e \u003cp\u003e4714069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e67.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-8.21\u003c/p\u003e \u003cp\u003e-3.62\u003c/p\u003e \u003cp\u003e6.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS8_\u003c/p\u003e \u003cp\u003e5149002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e124.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-9.46\u003c/p\u003e \u003cp\u003e-1.02\u003c/p\u003e \u003cp\u003e 9.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003e0.1523 \u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003csup\u003e\u003cem\u003e\u0026sect;\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026ge;\u0026thinsp;0.05 indicates there is no significant difference between observed and expected Mendelian ratios, or there is no significant difference between groups \u003cem\u003eAr-1Ar-1\u003c/em\u003e, \u003cem\u003ear-1ar\u003c/em\u003e-1, and \u003cem\u003eAr-1ar-1\u003c/em\u003e. \u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e indicates there is significant difference between observed and expected Mendelian ratios or between groups \u003cem\u003eAr-1Ar-1\u003c/em\u003e, \u003cem\u003ear-1ar-1\u003c/em\u003e, and \u003cem\u003eAr-1ar-1\u003c/em\u003e; \u003cem\u003eAr-1Ar-1\u003c/em\u003e\u0026thinsp;=\u0026thinsp;homozygous resistant parent alleles, \u003cem\u003ear-1ar-1\u003c/em\u003e\u0026thinsp;=\u0026thinsp;homozygous susceptible parent alleles, and \u003cem\u003eAr-1ar-1\u003c/em\u003e\u0026thinsp;=\u0026thinsp;heterozygous.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eContrastingly, the marker S8_5149002 did not show deviation between the observed and expected Mendelian ratios in the BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003e population for both the Chi-Square and Mann-Whitney test (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.09). The Chi-Square test in the F\u003csub\u003e2\u003c/sub\u003e population showed that there was no deviation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.69) from expected Mendelian ratios\u0026thinsp;\u0026minus;\u0026thinsp;1(\u003cem\u003eAr-1Ar-1\u003c/em\u003e):2(\u003cem\u003eAr-1ar-1\u003c/em\u003e):1(\u003cem\u003ear-1ar-1\u003c/em\u003e). The Kruskal-Wallis test in F\u003csub\u003e2\u003c/sub\u003e population showed that there was significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) among \u003cem\u003eAr-1Ar-1\u003c/em\u003e, \u003cem\u003ear-1ar-1\u003c/em\u003e, and \u003cem\u003eAr-1ar-1\u003c/em\u003e groups. The \u003cem\u003epost-hoc\u003c/em\u003e Dunn\u0026rsquo;s test showed significant difference between only the two groups (\u003cem\u003eAr-1Ar-1\u003c/em\u003e vs \u003cem\u003ear-1ar-1\u003c/em\u003e) and (\u003cem\u003ear-1ar-1\u003c/em\u003e vs \u003cem\u003eAr-1ar-1\u003c/em\u003e) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but not for the (\u003cem\u003eAr-1Ar-1\u003c/em\u003e vs \u003cem\u003eAr-1ar-1\u003c/em\u003e) group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.1523). Results indicated that the marker, S8_5149002, was able to distinguish phenotypes, resistant (\u003cem\u003eAr-1Ar-1\u003c/em\u003e and \u003cem\u003eAr-1ar-1\u003c/em\u003e) versus susceptible (\u003cem\u003ear-1ar-1\u003c/em\u003e) and agrees with earlier genetic studies that a single dominant gene controls race 1 anthracnose resistance. Results showed that S8_5149002 marker is the diagnostic marker located in the \u003cem\u003eQar1-8\u003c/em\u003e region.\u003c/p\u003e \u003cp\u003eThe SNP marker S8_5149002 was used to discriminate the watermelon germplasm (\u003cem\u003eN\u0026thinsp;=\u0026thinsp;61\u003c/em\u003e) for \u003cem\u003eColletotrichum orbiculare\u003c/em\u003e race 1 resistance. There were 19, 12, and 30 germplasm showing homozygous resistant, heterozygous, and homozygous susceptible alleles, respectively (\u003cem\u003eSupplementary Table S4\u003c/em\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePhenotypic and genotypic ratios\u003c/h2\u003e \u003cp\u003e \u003cem\u003eColletotrichum orbiculare\u003c/em\u003e race 1 affects watermelon and cucumber in which a single dominant resistance gene was reported. In this study, the Chi-square analysis showed a goodness of fit for a single dominant gene controlling race 1 anthracnose resistance both phenotypically and genotypically. Similar Mendelian phenotypic segregation ratios were reported and suggested that a single dominant gene was involved for race 1 anthracnose resistance in watermelon \u0026ndash; \u0026lsquo;Africa 8\u0026rsquo; (Layton \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1937\u003c/span\u003e), and \u0026lsquo;Charleston Gray\u0026rsquo;, \u0026lsquo;Congo\u0026rsquo; and \u0026lsquo;Fairfax\u0026rsquo; (Hall et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1960\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Resistance to anthracnose in beans was also found to be dominant in crosses of resistant x tolerant and resistant x susceptible varieties (Andrus and Wade \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1942\u003c/span\u003e). A single dominant gene for anthracnose resistance was also reported in cucumber (Barnes and Epps \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1952\u003c/span\u003e). Robinson et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1976\u003c/span\u003e) assigned \u003cem\u003eAr\u003c/em\u003e gene symbol for the anthracnose resistance gene in watermelon and cucumber. Winstead et al. (1959) also reported that race 1 anthracnose resistance gene also conferred race 3 anthracnose resistance in watermelon by superimposing race 3 inoculum on race 1 inoculated plants and vice-versa. The pedigree of \u0026lsquo;Charleston Gray\u0026rsquo; had \u0026lsquo;Africa 8\u0026rsquo;, whereas the pedigree of \u0026lsquo;Congo\u0026rsquo; and \u0026lsquo;Fairfax\u0026rsquo; had \u0026lsquo;African\u0026rsquo; (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). It is most likely that \u003cem\u003eAr-1\u003c/em\u003e in \u0026lsquo;Charleston Gray\u0026rsquo; might had been inherited from \u0026lsquo;Africa 8\u0026rsquo;, a race 1 anthracnose resistance founder parent.\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\u003ePedigrees of race 1 anthracnose resistant (\u003cem\u003eR\u003c/em\u003e) and susceptible (\u003cem\u003eS\u003c/em\u003e) watermelon cultivars.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePedigree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRace 1\u003c/p\u003e \u003cp\u003eAnthracnose response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\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\u003eCharleston Gray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[{(Africa 8 x Iowa Belle) x Garrison} x Garrison] x [(Hawkesbury x Leesburg) x Garrison]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Hall et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1960\u003c/span\u003e; Levi et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2001b\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(African x Iowa Belle) x Garrison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Hall et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1960\u003c/span\u003e; Levi et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2001b\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFairfax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e[Garrison x (African x Iowa Belle)] x [(Leesburg x Hawkesbury)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Hall et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1960\u003c/span\u003e; Levi et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2001b\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNew Hampshire Midget\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Favorite Honey\u003c/p\u003e \u003cp\u003ex Dakota Sweet)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Yeager 1950; Rhodes et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1992\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 \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eResistance QTL and putative genes\u003c/h2\u003e \u003cp\u003eIn the study, the preliminary analysis using GBS markers identified race 1 anthracnose resistance QTL on chromosome 8 (in between coordinates 4,847,957 and 6,294,791). The QTL on chromosome 8 was on the similar region to the previous study (Jang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). One of the genes, CC-NBS-LRR (CNL; \u003cem\u003eCla001017\u003c/em\u003e or \u003cem\u003eClCG08G002410\u003c/em\u003e), in the QTL region was reported for race 1 anthracnose resistance on breeding line \u0026lsquo;DrHS7250\u0026rsquo; (Jang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). We converted the high-resolution melting (HRM) SNP marker, CL14-27-9, for \u003cem\u003eClCG08G002410\u003c/em\u003e onto the PACE marker and designated it as S8_5149002. We reanalyzed F\u003csub\u003e2\u003c/sub\u003e mapping population data by including genotypic data for marker S8_5149002. The result showed that S8_5149002 was the significant marker with LOD up to 44 (with imputation) and could indicate that \u003cem\u003eClCG08G002410\u003c/em\u003e could also be the race 1 anthracnose resistance gene in \u0026lsquo;Charleston Gray\u0026rsquo;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eVariable genotype of watermelon germplasm\u003c/h2\u003e \u003cp\u003eThe significant SNP marker S8_5149002 clearly differentiated the disease response of the individuals of the mapping population as well as the germplasm present in the watermelon breeding program. Genotype of several watermelon germplasm and hybrids showed homozygous resistance to race 1 anthracnose. These include \u0026lsquo;Crimson Sweet\u0026rsquo;, \u0026lsquo;TASTIGOLD\u0026rsquo;, \u0026lsquo;AU-Sweet Scarlet\u0026rsquo;, \u0026lsquo;AU-Golden Producer\u0026rsquo;, \u0026lsquo;Perola\u0026rsquo;, \u0026lsquo;Crimson Diamond\u0026rsquo;, \u0026lsquo;Graybelle\u0026rsquo;, \u0026lsquo;Verona\u0026rsquo;, \u0026lsquo;SUNSHADE\u0026rsquo;, \u0026lsquo;Sugarlee\u0026rsquo;, \u0026lsquo;Dixielee\u0026rsquo;, \u0026lsquo;Jubilee\u0026rsquo;, \u0026lsquo;Big Stripe\u0026rsquo;, \u0026lsquo;Pronto\u0026rsquo;, \u0026lsquo;Pathfinder F\u003csub\u003e1\u003c/sub\u003e\u0026rsquo;, and \u0026lsquo;Fascination\u0026rsquo;. For most of them the source of race 1 anthracnose resistance might had inherited from the founder parent \u0026ndash; \u0026lsquo;Africa 8\u0026rsquo;. It is intriguing that the \u003cem\u003eAr-1\u003c/em\u003e gene is exhibiting resistance for more than 50 years. Interestingly, the germplasm PI 189225 which is resistant to race 2 anthracnose (Levi et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2001a\u003c/span\u003e), showed susceptible genotype (\u003cem\u003ear-1ar-1\u003c/em\u003e) for race 1 anthracnose suggesting race-specific resistance provided by the \u003cem\u003eR\u003c/em\u003e-genes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study delineates a major QTL region on chromosome 8 governing race 1 anthracnose resistance and putative CC-NBS-LRR (CNL; \u003cem\u003eClCG08G002410\u003c/em\u003e) could be a potential resistance gene in Charleston Gray. Further study is needed to validate that the CNL is the \u003cem\u003eAr-1\u003c/em\u003e gene. The S8_5149002 is a diagnostic marker for race 1 anthracnose resistance and could be used in MAS in watermelon breeding programs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Jared Smith, USDA-ARS, NC and Dr. Robert Vaughn, TAMU for assistance on PACE primer design. We would also like to thank Drs. Nithya Subramanian and Madhumita Joshi for testing DNA quantity and quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by USDA Hatch Project TEX09665, Texas A\u0026amp;M AgriLife Vegetable Seed Grant, Texas A\u0026amp;M University Excellence Fellowship, and Texas A\u0026amp;M AgriLife Research Strategic Initiative Assistantship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConceptualization:\u003c/em\u003e\u0026nbsp; T.C.W., T.P., and S.M.; \u003cem\u003eMethodology:\u003c/em\u003e T.P., B.P.B, E.C., R.M., S.W., M.B., C.D.J., and S.M.; \u003cem\u003eSoftware:\u003c/em\u003e S.W., M.B., B.P.B., and S.M.; \u003cem\u003eValidation:\u003c/em\u003e S.M.; \u003cem\u003eFormal analysis:\u003c/em\u003e B.P.B. and S.M.; \u003cem\u003eInvestigation\u003c/em\u003e: T.P., B.P.B., E.C., and S.M.; \u003cem\u003eResources\u003c/em\u003e: T.C.W. and S.M.; \u003cem\u003eData curation:\u003c/em\u003e B.P.B. and S.M.; \u003cem\u003eWriting\u003c/em\u003e\u0026mdash;original draft preparation, B.P.B.; \u003cem\u003eWriting\u0026mdash;review and editing:\u003c/em\u003e T.C.W, K.M.C., M.J.T., R.M., M.B., C.D.J., S.M.; \u003cem\u003eVisualization:\u003c/em\u003e B.P.B. and S.M.; \u003cem\u003eSupervision:\u003c/em\u003e T.C.W., C.D.J. and S.M.; \u003cem\u003eFunding acquisition:\u003c/em\u003e T.C.W. and S.M.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e3crBioscience (2018) PACE Genotyping Master Mix User Guide. https://3crbio.com/wp-content/uploads/2019/01/PACE-IR-User-Guide-v1.5.pdf (Accessed on 07/18/2021).\u003c/li\u003e\n \u003cli\u003eAkkaya MS, Bhagwat AA, Cregan PB (1992) Length polymorphisms of simple sequence repeat DNA in soybean. Genetics 132:1131-1139. https://doi.org/10.1093/genetics/132.4.1131\u003c/li\u003e\n \u003cli\u003eAndrus CF (1955) New watermelon varieties: Bring new life to that industry. Seed World 4:36-40\u003c/li\u003e\n \u003cli\u003eAndrus CF, Wade BL (1942) The factorial interpretation of anthracnose resistance in beans. U.S. Department of Agriculture, Washington D.C., vol. 810, pp 1-29,\u003c/li\u003e\n \u003cli\u003eBarnes W, Epps W (1952) Two types of anthracnose resistance in cucumbers. Plant Dis Rptr 36:479-480\u003c/li\u003e\n \u003cli\u003eBeckmann J, Soller M (1986) Restriction fragment length polymorphisms in plant genetic improvement. Oxford Surveys of Plant Mol and Cell Biol 3:196-250\u003c/li\u003e\n \u003cli\u003eBoyhan G, Norton J, Abrahams B, Wen H (1994) A new source of resistance to anthracnose (Race 2) in watermelon. 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Nucleic Acids Res 34:W635-W641. https://doi.org/10.1093/nar/gkl236\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":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"euphytica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"euph","sideBox":"Learn more about [Euphytica](https://www.springer.com/journal/10681)","snPcode":"10681","submissionUrl":"https://submission.springernature.com/new-submission/10681/3","title":"Euphytica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"watermelon, Colletotrichum orbiculare, race 1 anthracnose, QTL, PACE SNP marker, Qar1-8","lastPublishedDoi":"10.21203/rs.3.rs-1710183/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1710183/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAnthracnose, caused by the fungal pathogen \u003cem\u003eColletotrichum orbiculare\u003c/em\u003e (Berk. \u0026amp; Mont.) Arx syn. \u003cem\u003elagenaria\u003c/em\u003e, is one of the most important diseases of watermelon in the United States and worldwide. The study was conducted to identify \u003cem\u003eC\u003c/em\u003e. \u003cem\u003eorbiculare\u003c/em\u003e race 1 resistance quantitative trait loci (QTL) in a ‘Charleston Gray’, resistant parent, and ‘New Hampshire Midget’, susceptible parent, biparental mapping population. The mapping population consisted of 228 F\u003csub\u003e2\u003c/sub\u003e and the validation population consisted of 60 individuals each in BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e1\u003c/sub\u003e and BC\u003csub\u003e1\u003c/sub\u003eP\u003csub\u003e2\u003c/sub\u003e. The disease severity was rated using a disease index comprising a rating scale of 0 to 100%. IciMapping was used to draw the linkage map and R/qtl non-parametric method (‘model = np’) was used to identity QTL. We identified a major disease resistance QTL, \u003cem\u003eQar1-8\u003c/em\u003e, on chromosome 8. \u0026nbsp;The significant SNP marker S8_5149002, part of a putative coiled-coil (CC)–nucleotide-binding site (NBS)–leucine-rich repeat (LRR) (CC-NBS-LRR or CNL; \u003cem\u003eClCG08G002410\u003c/em\u003e), had a LOD of 14.06. \u0026nbsp;The significant marker was validated on mapping populations using R package functions ‘chisq.test’, ‘wilcox.test’, ‘kruskal.test’, and ‘dunn.test’. The significant marker S8_5149002 was also tested for its ability to differentiate race 1 anthracnose resistance on 61 watermelon germplasm including 41 plant introduction (PI) lines. \u0026nbsp;Hence, the diagnostic SNP marker S8_5149002 could be used for marker assisted selection (MAS) for race 1 anthracnose resistance in watermelon breeding programs.\u003c/p\u003e","manuscriptTitle":"Dissection of Race 1 Anthracnose Resistance in a Watermelon (Citrullus lanatus var. lanatus) Biparental Mapping Population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-06-08 16:07:44","doi":"10.21203/rs.3.rs-1710183/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2022-07-16T05:12:17+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2022-06-08T12:49:03+00:00","index":0,"fulltext":""},{"type":"editorAssigned","content":"","date":"2022-06-03T05:47:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Euphytica","date":"2022-05-31T01:21:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"euphytica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"euph","sideBox":"Learn more about [Euphytica](https://www.springer.com/journal/10681)","snPcode":"10681","submissionUrl":"https://submission.springernature.com/new-submission/10681/3","title":"Euphytica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"145dbe87-31a5-4550-adfe-603c0d1287d9","owner":[],"postedDate":"June 8th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2022-12-06T15:49:01+00:00","versionOfRecord":{"articleIdentity":"rs-1710183","link":"https://doi.org/10.1007/s10681-022-03108-7","journal":{"identity":"euphytica","isVorOnly":false,"title":"Euphytica"},"publishedOn":"2022-10-18 00:00:00","publishedOnDateReadable":"October 18th, 2022"},"versionCreatedAt":"2022-06-08 16:07:44","video":"","vorDoi":"10.1007/s10681-022-03108-7","vorDoiUrl":"https://doi.org/10.1007/s10681-022-03108-7","workflowStages":[]},"version":"v1","identity":"rs-1710183","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1710183","identity":"rs-1710183","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}