Identification of a Novel Slow-Gray STX17 Lineage in Japanese Thoroughbreds via a Multi-Tiered Copy Number Analysis Workflow

Identification of a Novel Slow-Gray STX17 Lineage in Japanese Thoroughbreds via a Multi-Tiered Copy Number Analysis Workflow | 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 Identification of a Novel Slow-Gray STX17 Lineage in Japanese Thoroughbreds via a Multi-Tiered Copy Number Analysis Workflow Koki Kawate, Risako Furukawa, Mio Kikuchi, Taichiro Ishige, Kazuhiro Seki, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9164835/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 14 You are reading this latest preprint version Abstract Gray is a dominant coat color phenotype in horses caused by a ~4.6 kb tandem duplication within intron 6 of syntaxin 17 ( STX17 ). The copy number variation (CNV) of the duplicated segment influences the graying rate. The rare G2 allele (CNV=2) is associated with a slower graying rate compared to the common G3 allele (CNV=3), and is also relevant to melanoma risk. Current assays are limited because long and accurate PCR (LA-PCR) detects only the presence or absence of duplications, while droplet digital PCR (ddPCR) cannot reliably distinguish certain genotypes such as G3/g and G2/G2 . We constructed a stepwise workflow combining (i) multiplex real-time PCR targeting the duplication junction for rapid gray/non-gray screening, (ii) ddPCR for CN estimation, and (iii) LA-PCR for confirmatory genotyping of ambiguous copy-number classes. Using real-time PCR, we screened 4,596 Japanese Thoroughbreds aged 2–7 years, of which 4,374 were classified as non-gray and 222 as gray. Based on age and coat appearance, 23 gray candidates were prioritized for slow-gray evaluation and analyzed by ddPCR; one was classified as G2/g and 22 as G3/g or G2/G2 . LA-PCR detected a g-derived band in all 22 cases, confirming that it was G3/g . Pedigree analysis indicated that the G2 allele was maternally inherited and originated from a lineage distinct from a previously reported Japanese slow-gray family. This workflow enables practical molecular discrimination among non-gray, common gray, and slow-gray genotypes, supporting the surveillance of rare G2 alleles in the Japanese Thoroughbred population. deletion insertion STX17 slow-gray structure variation Figures Figure 1 Figure 2 Figure 3 Figure 4 1 Introduction Gray is a dominant coat color phenotype in horses, in which foals are born with their base coat color but progressively lose hair pigmentation with age, ultimately becoming almost completely white. The causal mutation for graying has been identified as an approximately 4,600-bp tandem duplication within intron 6 of the syntaxin 17 ( STX17 ) gene on equine chromosome 25 (Rosengren Pielberg et al., 2008 ; Sundström et al., 2012a ).The rate of graying varies among individuals, and recent studies have shown that copy number variation (CNV) in the duplicated segment of STX17 intron 6 contributes to this variation (Rubin et al., 2024 ). Specifically, horses homozygous for the g allele with CNV = 1 were non-gray, whereas horses carrying the G2 allele with CNV = 2 showed significantly slower graying than those carrying the G3 allele with CNV = 3. Gray horses carrying the G2 allele are defined as slow-gray horses, and we investigated the prevalence of slow-gray horses in the Japanese Thoroughbred population. Our previous survey identified a single slow-gray lineage in Japanese Thoroughbreds (Rubin et al., 2024 ). While graying in Thoroughbreds typically progresses between 3 and 5 years of age, individuals of this lineage can remain largely non-white, even after 10 years of age. As a potential mechanism by which the STX17 intron 6 CNV affects the graying rate, the duplicated segment is hypothesized to function as a melanocyte-specific enhancer with binding activity for the transcription factor MITF, which elevates STX17 and NR4A3 expression, thereby increasing enhancer activity and causing dose-dependent acceleration of graying through the early depletion of melanin in hair follicle cells (Sundström et al., 2012b ). In other model organisms, STX17 has been identified as a membrane protein that forms part of a soluble N-ethylmaleimide-sensitive-factor attachment protein receptor (SNARE) complex involved in autophagy and plays an important role in autophagy pathways that are targeted in human melanoma therapy (Viret & Faure 2019 ). In contrast, an epidemiological survey of gray Camargue horses reported a higher occurrence of melanoma in shaded body sites with limited sun exposure, suggesting that melanocytic tumors frequently observed in gray horses may involve risk factors distinct from ultraviolet (UV) exposure, which is one of the major risk factors for human melanoma(Fleury et al., 2000 ; Green et al., 2010 ; Walter et al., 1999 ). In addition to these observations, expansion of the CNV at STX17 intron 6 in equine melanoma cells, together with increased expression of STX17 and the neighboring gene NR4A3 , indicates that the STX17 intron 6 CNV contributes to melanoma development via transcriptional regulation that is independent of the canonical protein function of STX17 (Rosengren Pielberg et al., 2008 ; Sundström et al., 2012a ). Consistent with this, although the prevalence varies by breed, 50%–80% of gray horses aged ≥ 15 years develop melanoma (Curik et al., 2013 ; Hofmanová et al., 2015 ; Rubin et al., 2024 ; Seltenhammer et al., 2003 ). Moreover, G3/G3 homozygotes exhibit a higher incidence of melanoma than G3/g heterozygotes. (Sundström et al., 2012b ). In Connemara ponies, gray horses carrying the G2 allele (slow- gray) have a significantly lower melanoma incidence of melanoma than age-matched common-gray horses (Rubin et al., 2024 ). Thus, determining STX17 genotypes in a population is important not only for understanding coat color phenotypes but also for the epidemiological evaluation of melanoma and genotype-based risk stratification. Currently, STX17 genotyping is performed by long and accuracy PCR (LA-PCR) or droplet digital PCR (ddPCR). LA-PCR is a method for high-fidelity amplification of long DNA fragments and has been used to detect duplicated segments in STX17 intron 6 (Barnes 1994 ; Rosengren Pielberg et al., 2008 ). However, LA-PCR evaluates only the presence or absence of STX17 intron 6 duplication by agarose gel electrophoresis and therefore cannot distinguish common gray from slow-gray (Rosengren Pielberg et al., 2008 ). Moreover, the prolonged PCR cycling and gel electrophoresis required for LA-PCR (e.g., 2 h at 100 V) can constrain its use in routine screening. ddPCR-based CNV analysis is used to detect slow-gray horses, but it has a limited ability to discriminate between genotypes with similar copy numbers, particularly G3/g heterozygotes and G2/G2 homozygotes (Nowacka-Woszuk et al., 2021a ; Nowacka-Woszuk et al., 2021b ; Rubin et al., 2024 ). Therefore, this study aimed to establish a detection strategy capable of distinguishing non-gray, common gray, and slow-gray horses and to survey the current Japanese Thoroughbred population for potentially undetected slow-gray individuals, thereby clarifying their frequency and pedigree background. 2 Materials and Methods 2.1 Animal samples Residual DNA extracts from 4,596 Thoroughbreds that used for routine genetic testing at the Laboratory of Racing Chemistry (LRC) were repurposed for the screening of slow-gray. For confirmatory testing, whole blood samples were collected from the identified slow-gray individuals and their parents. Blood samples were collected by a veterinarian with extensive clinical equine experience. Blood was drawn from the jugular vein and collected in BD Vacutainer® K2EDTA Blood Collection Tubes (Becton Dickinson and Company, Franklin Lakes, NJ, USA). The Animal Care Committee of the LRC approved the blood collection protocol (approval number: 20 − 4), and was performed in accordance with the ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines. 2.2 DNA extraction Distinct DNA extraction methods were used for each downstream application. Plasma-derived cell-free DNA (cfDNA) was used for real-time PCR for initial screening, and genomic DNA (gDNA) from whole blood was used for ddPCR and LA-PCR for confirmatory analysis because it provides a more stable and higher-quality template for precise genotype assessment. For cfDNA extraction, whole blood collected in 6 mL EDTA tubes was centrifuged at 3,000 rpm for 10 min to separate the plasma and cellular fractions. cfDNA was extracted from 1.5 mL of plasma using a Custom NEXTprep cfDNA Auto (1.5 mL) kit (Revvity Inc., Waltham, MA, USA) according to the manufacturer’s instructions. The extracted cfDNA was stored at 4 ℃ until real-time PCR was performed. For gDNA extraction from whole blood, gDNA was isolated using a DNeasy Blood & Tissue Kit (QIAGEN, Venlo, Netherlands) according to the manufacturer’s protocol. 2.3 Real-time PCR assay For multiplex real-time PCR, hydrolysis probe–based real-time PCR reactions contained 2× TaqMan Fast Universal PCR Master Mix (Thermo Fisher Scientific, Waltham, MA, USA), specific primers and fluorescently labeled probes, and template DNA, in a final reaction volume of 10 µL. The final concentrations of the primers and probes were 100 nM and 300 nM, respectively. For the multiplex assay, primers and probes were designed to target the junction of the STX17 intron 6 duplicated segments, and an internal sequence within MSTN exon 4 was simultaneously amplified in the same reaction as an internal reference. Targets were distinguished using probes labeled with different fluorophores (FAM and VIC). The primer and probe sequences are listed in Table S1. Cycling conditions were as follows: initial denaturation at 95 ℃ for 1 min, followed by 40 cycles of 95 ℃ for 15 s and 60 ℃ for 1 min. Fluorescence signals were acquired at the end of each annealing/extension step of PCR. Data were analyzed using QuantStudio Design and Analysis Software (Thermo Fisher Scientific).The amplification curves and baselines were automatically set using the software and manually adjusted when required. Ct values were calculated based on an automatically determined threshold. 2.4 ddPCR assay ddPCR was performed following a previously reported method (Rubin et al., 2024 ), with redesigned primer sequences for CNV analysis of STX17 . The target assay amplified the internal region of STX17 intron 6 and was run as a multiplex ddPCR with a reference assay targeting MSTN exon 4. The primer and probe sequences are listed in Table S2. The copy number was calculated from the ratio of target to reference copies, and genotypes were assigned according to the calculated copy numbers (expected diploid copy numbers: G3/G3 : 6, G3/G2 : 5, G3/g or G2/G2 : 4, G2/g : 3, and g/g : 2). ddPCR data were analyzed using QuantaSoft Analysis Pro Software (Bio-Rad Laboratories Inc., Hercules, CA, USA). Absolute target concentrations (copies/µL) and 95% confidence intervals (CIs) were calculated using Poisson statistics. For each ddPCR reaction, we confirmed that ≥ 10,000 droplets were accepted for analysis and that no non-specific amplification was observed in the negative controls. 2.5 LA-PCR assay LA-PCR was performed accoding to the method reported by Rosengren Pielberg et al ( 2008 ). The primer sequences are listed in Table S3. The PCR reactions included each primer, reagents supplied with the Expand Long Range Enzyme mix (Roche Diagnostics, Mannheim, Germany), and DNA extracted from whole blood. The PCR products were separated by electrophoresis on a 0.7% agarose gel at 100 V for 2 h, stained with ethidium bromide, and visualized under UV illumination. 3 Results 3.1 Real-time PCR–based screening for Gray To screen for STX17 genotypes in the population, we established a workflow consisting of (i) rapid gray/non-gray screening by real-time PCR, (ii) CN analysis of STX17 intron 6 by ddPCR, and (iii) confirmatory genotyping of G3/g versus G2/G2 by LA-PCR (Fig. 1). Although real-time PCR could not accurately discriminate the small copy number difference between the G3 and G2 alleles, assessing the presence or absence of amplification from the STX17 intron 6 duplication junction enabled more efficient discrimination between gray and non-gray horses than LA-PCR alone (Fig. 2). Using this workflow, we screened 4,596 Japanese Thoroughbreds aged 2–7 years, of which 4,374 were classified as non-gray and 222 as gray. 3.2 Discrimination between G3/g and G2/G2 using ddPCR and LA-PCR Among the horses classified as gray by real-time PCR, age and coat appearance were reviewed, and 23 horses were selected as candidates for slow-gray based on delayed depigmentation at age 2–3 years. These horses were analyzed by ddPCR. Consequently, one horse was classified as G2/g, and the remaining 22 were classified as either G3/g or G2/G2. No G3/G3 or G3/G2 horses were included among the 22 horses. These were subsequently analyzed by LA-PCR, and a g-derived band (~5.6 kbp) was detected in all samples, confirming that all 22 horses were G3/g; the detection of the wild-type g-allele-specific band (~5.6 kb) in all samples confirmed the G3/g genotype (Fig. 3). 3.3 Emergence of the G2 allele The G2/g individuals identified in this study belong to a lineage distinct from the previously reported Japanese slow-gray family. Using samples from this pedigree and applying the established workflow, we found that the sire was G3/g , whereas the dam and the full sibling (sister) were G2/g, confirming maternal inheritance of the G2 allele. Pedigree investigation further suggested a slow-gray like coat appearance in the great-granddam generation, whereas earlier generations showed a common gray phenotype. These observations suggest that a reduction in the copy number of the STX17 intron 6 duplicated segment (including a deletion-type event) occurred in the great-granddam generation and that the resulting G2 allele subsequently segregated within the lineage (Fig. 4). 4 Discussion In this study, we proposed a detection strategy for the Japanese Thoroughbred population by combining real-time PCR, ddPCR, and LA-PCR. This workflow enabled discrimination between common gray and slow-gray and facilitated the search for potentially undetected slow-gray individuals. The newly developed real-time PCR–based screening assay was completed within approximately 2 h, including the reaction time. Compared with conventional workflows that rely solely on LA-PCR and gel electrophoresis, this approach substantially reduces laboratory handling steps and turnaround time while enabling robust and consistent classification of gray and non-gray samples. CNV estimation using real-time PCR is sensitive to differences in amplification efficiency between target and reference assays, inhibitory substances, and assay specificity, making accurate quantitative discrimination of small copy-number differences challenging(Aldhous et al., 2010). Additional optimization and condition testing are necessary to infer STX17 CNV solely using real-time PCR. However, from an operational perspective eliminating gel electrophoresis is expected to reduce hands-on time, contamination risk, and operator-dependent interpretation. In this study, plasma-derived cfDNA was used for analysis, and when applying the assay to other sample types, differences in DNA extraction conditions may affect PCR inhibition and copy-number variance, potentially influencing the interpretation. Thus, an implementation plan with clearly defined negative/positive controls and retesting criteria (e.g., Ct thresholds and re-extraction rules) is required. ddPCR is intrinsically well-suited for distinguishing G2 from G3 because it enables copy number estimation from the target/reference ratio based on absolute quantification. (Hindson et al., 2011). In this study, 23 horses suspected of the slow-gray phenotype based on age and appearance were examined in detail: one horse was classified as G2 / g , whereas the remaining 22 were inferred by ddPCR as having four copies of the duplicated segment. However, g -derived electrophoretic bands were detected in all 22 by LA-PCR, confirming that they were G3 / g . Only one out of 4,596 horses carried the G2 allele, which is consistent with observations in many other breeds that the G2 allele is significantly less frequent than the G3 allele (Rubin et al., 2024). Therefore, the presence of G2 / G2 individuals in the current Japanese Thoroughbred population is likely extremely rare. Nevertheless, when pedigree information suggests segregation of the G2 allele, a two-step confirmation scheme—(i) narrowing genotype candidates using ddPCR and (ii) confirming heterozygosity ( g -carrier status) using LA-PCR—can reliably determine STX17 genotype. The G2/g individuals detected in this study belong to a lineage distinct from the previously reported slow-gray family. Pedigree investigation and relatedness analysis indicated that the dam and sibling were also G2/g , demonstrating the inheritance of the G2 allele within the lineage. Because a slow-gray like appearance was suspected in the great-granddam generation, it is plausible that a copy number contraction in the duplicated segment of STX17 intron 6 (e.g., a contraction corresponding to a decrease from G3 ) arose at the origin of this pedigree and subsequently segregated. This suggests that slow-gray individuals are not restricted to a single founder lineage and could have multiple origins within the population, implying that continued monitoring and screening will likely identify additional slow-gray families. Previous work has suggested that although the founder of G2 in the domestic horse population is unknown, an insertion event from g to G2 followed by a further insertion generating the G3 allele may have occurred because horses carrying the G3 allele gray earlier; breeding preferences for sires and dams with the G3 allele could have driven the much higher frequency of G3 relative to G2 (Rubin et al., 2024). In contrast, slow-gray which is currently confirmed in the Japanese Thoroughbred population, appears to involve only copy number contraction from G3 to G2 . The Gray founder in Thoroughbreds is thought to be traced back to a single Arabian horse; in the Japanese Thoroughbred population the founder’s G3 allele likely disseminated broadly, with slow- gray arising via copy-number contraction from G3 to G2 (Binns & Swinburne 2004; Swinburne et al., 2002). In this study, the detection of slow-gray was based on pre-selection criteria such as “gray horses that have not depigmented relative to age,” and thus selection bias remains in estimating the frequency of undetected slow-gray. The absence of early-whitening G3 / G3 horses among the 23 selected individuals is likely attributable to this bias. Moreover, graying progression may be influenced not only by STX17 genotype, but also by base coat color, age, sex, modifier genes, and environmental factors (Curik et al., 2013; Hofmanová et al., 2015; Teixeira et al., 2013). Therefore, rather than inferring slow-gray horses from non-genetic information, applying this detection strategy to all gray horses based on genotype would enable a more precise estimation of the slow-gray frequency in the Japanese Thoroughbred population. As the STX17 intron 6 CNV is associated with melanoma risk, characterizing genotype distributions may provide a foundation for future clinical and epidemiological studies(Curik et al., 2013; Teixeira et al., 2013). As research linking genotypes and clinical phenotypes advances, meaningful insights may be gained for risk stratification and early detection. In conclusion, the proposed strategy—real-time PCR as a primary screen, ddPCR as a secondary assessment, and LA-PCR as confirmatory testing—enables molecular discrimination among non-gray, common gray, and slow-gray. Although slow-gray appears rare in the Japanese Thoroughbred population, our findings indicate that it may have multiple origins. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9164835","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":625763974,"identity":"3f1145a7-4285-474d-a07e-462e99cb21cd","order_by":0,"name":"Koki Kawate","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBACCQY2CIOfHSrC2ECcFgMGyWaStRgcJtZhkg1siZ95av7IGR/mffiBoeIeA/NsAtZIM7AdluY5ZmBsdpjdWILhTDED45wD+LXIyT9vkM5hM0jcdpiNjYGxLYGBcUYCAS0M7M2/c/4Z1G9uJlYL0GHHpHPbDBIMmInVAvR+mvXfPmPDGYfZmCUSziTwEPSLxAE245szvsnJ87e3MX74UJEgZ0goxFAB0Ek8hjNI0QEG8hIkaxkFo2AUjIJhDgDAezYD63UoIgAAAABJRU5ErkJggg==","orcid":"","institution":"Laboratory of Racing Chemistry","correspondingAuthor":true,"prefix":"","firstName":"Koki","middleName":"","lastName":"Kawate","suffix":""},{"id":625763975,"identity":"6c402dbb-22dd-4ef3-96cf-06fac9d0120d","order_by":1,"name":"Risako Furukawa","email":"","orcid":"","institution":"Laboratory of Racing Chemistry","correspondingAuthor":false,"prefix":"","firstName":"Risako","middleName":"","lastName":"Furukawa","suffix":""},{"id":625763977,"identity":"53597d76-313b-47b8-8009-e9496ea1503a","order_by":2,"name":"Mio Kikuchi","email":"","orcid":"","institution":"Laboratory of Racing Chemistry","correspondingAuthor":false,"prefix":"","firstName":"Mio","middleName":"","lastName":"Kikuchi","suffix":""},{"id":625763980,"identity":"ccefe567-cee7-4d4f-9ad5-04741ccf1b18","order_by":3,"name":"Taichiro Ishige","email":"","orcid":"","institution":"Laboratory of Racing Chemistry","correspondingAuthor":false,"prefix":"","firstName":"Taichiro","middleName":"","lastName":"Ishige","suffix":""},{"id":625763981,"identity":"1b4e61a6-b78e-4ab9-aecc-cc9a0e3a946e","order_by":4,"name":"Kazuhiro Seki","email":"","orcid":"","institution":"Japan Racing Association","correspondingAuthor":false,"prefix":"","firstName":"Kazuhiro","middleName":"","lastName":"Seki","suffix":""},{"id":625763982,"identity":"12869b3e-8d3c-4286-8aa6-317c3fa5a43d","order_by":5,"name":"Teruaki Tozaki","email":"","orcid":"","institution":"Laboratory of Racing Chemistry","correspondingAuthor":false,"prefix":"","firstName":"Teruaki","middleName":"","lastName":"Tozaki","suffix":""},{"id":625763983,"identity":"5a13b5be-365d-4dc0-9075-9f7368320ac9","order_by":6,"name":"Hironaga Kakoi","email":"","orcid":"","institution":"Laboratory of Racing Chemistry","correspondingAuthor":false,"prefix":"","firstName":"Hironaga","middleName":"","lastName":"Kakoi","suffix":""}],"badges":[],"createdAt":"2026-03-19 04:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9164835/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9164835/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107317635,"identity":"8b617a6e-f164-477c-a9ab-431eb1b30d6c","added_by":"auto","created_at":"2026-04-20 09:58:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35427,"visible":true,"origin":"","legend":"\u003cp\u003eWorkflow for discrimination of \u003cem\u003eSTX17\u003c/em\u003e genotypes\u003c/p\u003e\n\u003cp\u003e(i) Gray and non-gray horses were initially screened using real-time PCR. (ii) Copy number variation (CNV) analysis by ddPCR was used to distinguish \u003cem\u003eG3\u003c/em\u003e/\u003cem\u003eG3\u003c/em\u003e, \u003cem\u003eG3\u003c/em\u003e/\u003cem\u003eG2\u003c/em\u003e, and \u003cem\u003eG2\u003c/em\u003e/\u003cem\u003eg\u003c/em\u003e(note that \u003cem\u003eG3\u003c/em\u003e/\u003cem\u003eg\u003c/em\u003e and \u003cem\u003eG2\u003c/em\u003e/\u003cem\u003eG2\u003c/em\u003e cannot be discriminated at this step). (iii) LA-PCR was subsequently performed to detect the \u003cem\u003eg\u003c/em\u003e-derived band, thereby distinguishing \u003cem\u003eG3\u003c/em\u003e/\u003cem\u003eg\u003c/em\u003e from \u003cem\u003eG2\u003c/em\u003e/\u003cem\u003eG2\u003c/em\u003e. To search for slow-gray individuals in this study, 222 samples classified as gray in step (i) were further prioritized based on age and coat appearance, yielding 23 candidates for downstream analyses in steps (ii) and (iii).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9164835/v1/e2659267ea06f8d651581fc7.png"},{"id":107317594,"identity":"90d153cc-6b32-407b-991c-f525ff2d1466","added_by":"auto","created_at":"2026-04-20 09:58:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":87880,"visible":true,"origin":"","legend":"\u003cp\u003eDetection of \u003cem\u003eSTX17\u003c/em\u003e genotypes using real-time PCR\u003cbr\u003e\n Panels (a) and (b) show the amplification curves for each gene obtained from multiplex real-time PCR targeting the \u003cem\u003eMSTN\u003c/em\u003e and \u003cem\u003eSTX17\u003c/em\u003egenes. (a) When a sample carries the \u003cem\u003eG3\u003c/em\u003e or \u003cem\u003eG2\u003c/em\u003e allele, amplification is observed with primers designed for the \u003cem\u003eSTX17\u003c/em\u003eduplication junction. (b) In \u003cem\u003eg/g\u003c/em\u003e samples, no \u003cem\u003eSTX17\u003c/em\u003e amplification is detected, and only the \u003cem\u003eMSTN\u003c/em\u003e gene is amplified.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9164835/v1/5de2ee20ca310ef464d02164.png"},{"id":107317595,"identity":"2d268504-797f-4881-acaa-7f5e4c61f376","added_by":"auto","created_at":"2026-04-20 09:58:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":167715,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAgarose gel electrophoresis of LA-PCR amplicons\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter LA-PCR, 5 µL of loading buffer was added to each sample, and 1 µL of the resulting mixture was loaded per lane. As a DNA size marker, 1 µL of HyperLadder 1 kb DNA size marker (BIOLINE, London, United Kingdom) was used. Gels were stained with ethidium bromide (EtBr) for at least 15 min and imaged using a WSE-5200UV Printgraph 2M UV Model (ATTO, Tokyo, Japan) with a 2.0-s UV exposure. In LA-PCR, a 4.9-kbp amplicon was detected when a sample carried the \u003cem\u003eG3\u003c/em\u003eor \u003cem\u003eG2\u003c/em\u003e allele. When a sample carries only the \u003cem\u003eg\u003c/em\u003e allele, only a 5.6-kbp amplicon was detected. In addition to the expected amplicons, weak non-specific bands were observed in a subset of samples. These minor bands were of low intensity and did not affect the genotype calling based on the expected product size.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9164835/v1/88238df9e8ddcce9d4330796.png"},{"id":107486238,"identity":"9ebe1829-e6b2-4afb-aefa-bff1def56497","added_by":"auto","created_at":"2026-04-22 02:37:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":84432,"visible":true,"origin":"","legend":"\u003cp\u003ePedigree of a newly identified late-gray family\u003cbr\u003e\n Squares and circles indicate males and females, respectively. Diagonal slashes indicate deceased or missing individuals. Arrows indicate the slow-gray individuals identified in this study. Filled black symbols represent non-gray, open symbols represent gray, and half-filled symbols represent slow-gray. Individuals marked with an asterisk (*) are those whose \u003cem\u003eSTX17\u003c/em\u003e genotype was determined in this study, whereas individuals shown with dotted outlines are those whose gray phenotype was inferred from age, external appearance, and/or the phenotype of their offspring. For all other individuals, coat-color information follows the studbook records. Stars (★) indicate the position at which a change in the \u003cem\u003eSTX17\u003c/em\u003e genotype is inferred to have occurred.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9164835/v1/e843cfc75651df6248127746.png"},{"id":107488067,"identity":"48138bee-2bc8-4890-9415-33d1a55d799b","added_by":"auto","created_at":"2026-04-22 02:43:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":656095,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9164835/v1/ddd1f89e-be1f-4286-9de2-a3200aba2b5d.pdf"},{"id":107317590,"identity":"6cfbcf39-7eb2-481d-adc8-250427a0b034","added_by":"auto","created_at":"2026-04-20 09:58:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":97301,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.docx","url":"https://assets-eu.researchsquare.com/files/rs-9164835/v1/ead5316fe0a377b6c748f9e3.docx"},{"id":107317638,"identity":"858d1176-374a-40b0-a0ae-1eb0d9f1abe7","added_by":"auto","created_at":"2026-04-20 09:58:52","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17979,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-9164835/v1/6b6ffe1bdf45fc7056ac8a0c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Identification of a Novel Slow-Gray STX17 Lineage in Japanese Thoroughbreds via a Multi-Tiered Copy Number Analysis Workflow","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eGray is a dominant coat color phenotype in horses, in which foals are born with their base coat color but progressively lose hair pigmentation with age, ultimately becoming almost completely white. The causal mutation for graying has been identified as an approximately 4,600-bp tandem duplication within intron 6 of the \u003cem\u003esyntaxin 17\u003c/em\u003e (\u003cem\u003eSTX17\u003c/em\u003e) gene on equine chromosome 25 (Rosengren Pielberg et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Sundstr\u0026ouml;m et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e).The rate of graying varies among individuals, and recent studies have shown that copy number variation (CNV) in the duplicated segment of \u003cem\u003eSTX17\u003c/em\u003e intron 6 contributes to this variation (Rubin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Specifically, horses homozygous for the g allele with CNV\u0026thinsp;=\u0026thinsp;1 were non-gray, whereas horses carrying the \u003cem\u003eG2\u003c/em\u003e allele with CNV\u0026thinsp;=\u0026thinsp;2 showed significantly slower graying than those carrying the \u003cem\u003eG3\u003c/em\u003e allele with CNV\u0026thinsp;=\u0026thinsp;3. Gray horses carrying the \u003cem\u003eG2\u003c/em\u003e allele are defined as slow-gray horses, and we investigated the prevalence of slow-gray horses in the Japanese Thoroughbred population. Our previous survey identified a single slow-gray lineage in Japanese Thoroughbreds (Rubin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). While graying in Thoroughbreds typically progresses between 3 and 5 years of age, individuals of this lineage can remain largely non-white, even after 10 years of age. As a potential mechanism by which the \u003cem\u003eSTX17\u003c/em\u003e intron 6 CNV affects the graying rate, the duplicated segment is hypothesized to function as a melanocyte-specific enhancer with binding activity for the transcription factor MITF, which elevates \u003cem\u003eSTX17\u003c/em\u003e and \u003cem\u003eNR4A3\u003c/em\u003e expression, thereby increasing enhancer activity and causing dose-dependent acceleration of graying through the early depletion of melanin in hair follicle cells (Sundstr\u0026ouml;m et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn other model organisms, STX17 has been identified as a membrane protein that forms part of a soluble N-ethylmaleimide-sensitive-factor attachment protein receptor (SNARE) complex involved in autophagy and plays an important role in autophagy pathways that are targeted in human melanoma therapy (Viret \u0026amp; Faure \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In contrast, an epidemiological survey of gray Camargue horses reported a higher occurrence of melanoma in shaded body sites with limited sun exposure, suggesting that melanocytic tumors frequently observed in gray horses may involve risk factors distinct from ultraviolet (UV) exposure, which is one of the major risk factors for human melanoma(Fleury et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Green et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Walter et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). In addition to these observations, expansion of the CNV at \u003cem\u003eSTX17\u003c/em\u003e intron 6 in equine melanoma cells, together with increased expression of \u003cem\u003eSTX17\u003c/em\u003e and the neighboring gene \u003cem\u003eNR4A3\u003c/em\u003e, indicates that the \u003cem\u003eSTX17\u003c/em\u003e intron 6 CNV contributes to melanoma development via transcriptional regulation that is independent of the canonical protein function of \u003cem\u003eSTX17\u003c/em\u003e (Rosengren Pielberg et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Sundstr\u0026ouml;m et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e). Consistent with this, although the prevalence varies by breed, 50%\u0026ndash;80% of gray horses aged\u0026thinsp;\u0026ge;\u0026thinsp;15 years develop melanoma (Curik et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Hofmanov\u0026aacute; et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rubin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Seltenhammer et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Moreover, \u003cem\u003eG3/G3\u003c/em\u003e homozygotes exhibit a higher incidence of melanoma than \u003cem\u003eG3/g\u003c/em\u003e heterozygotes. (Sundstr\u0026ouml;m et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012b\u003c/span\u003e). In Connemara ponies, gray horses carrying the \u003cem\u003eG2\u003c/em\u003e allele (slow- gray) have a significantly lower melanoma incidence of melanoma than age-matched common-gray horses (Rubin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Thus, determining \u003cem\u003eSTX17\u003c/em\u003e genotypes in a population is important not only for understanding coat color phenotypes but also for the epidemiological evaluation of melanoma and genotype-based risk stratification.\u003c/p\u003e \u003cp\u003eCurrently, \u003cem\u003eSTX17\u003c/em\u003e genotyping is performed by long and accuracy PCR (LA-PCR) or droplet digital PCR (ddPCR). LA-PCR is a method for high-fidelity amplification of long DNA fragments and has been used to detect duplicated segments in \u003cem\u003eSTX17\u003c/em\u003e intron 6 (Barnes \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Rosengren Pielberg et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). However, LA-PCR evaluates only the presence or absence of \u003cem\u003eSTX17\u003c/em\u003e intron 6 duplication by agarose gel electrophoresis and therefore cannot distinguish common gray from slow-gray (Rosengren Pielberg et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Moreover, the prolonged PCR cycling and gel electrophoresis required for LA-PCR (e.g., 2 h at 100 V) can constrain its use in routine screening. ddPCR-based CNV analysis is used to detect slow-gray horses, but it has a limited ability to discriminate between genotypes with similar copy numbers, particularly \u003cem\u003eG3/g\u003c/em\u003e heterozygotes and \u003cem\u003eG2/G2\u003c/em\u003e homozygotes (Nowacka-Woszuk et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e; Nowacka-Woszuk et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e; Rubin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to establish a detection strategy capable of distinguishing non-gray, common gray, and slow-gray horses and to survey the current Japanese Thoroughbred population for potentially undetected slow-gray individuals, thereby clarifying their frequency and pedigree background.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Animal samples\u003c/h2\u003e \u003cp\u003eResidual DNA extracts from 4,596 Thoroughbreds that used for routine genetic testing at the Laboratory of Racing Chemistry (LRC) were repurposed for the screening of slow-gray. For confirmatory testing, whole blood samples were collected from the identified slow-gray individuals and their parents. Blood samples were collected by a veterinarian with extensive clinical equine experience. Blood was drawn from the jugular vein and collected in BD Vacutainer\u0026reg; K2EDTA Blood Collection Tubes (Becton Dickinson and Company, Franklin Lakes, NJ, USA). The Animal Care Committee of the LRC approved the blood collection protocol (approval number: 20\u0026thinsp;\u0026minus;\u0026thinsp;4), and was performed in accordance with the ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 DNA extraction\u003c/h2\u003e \u003cp\u003eDistinct DNA extraction methods were used for each downstream application. Plasma-derived cell-free DNA (cfDNA) was used for real-time PCR for initial screening, and genomic DNA (gDNA) from whole blood was used for ddPCR and LA-PCR for confirmatory analysis because it provides a more stable and higher-quality template for precise genotype assessment. For cfDNA extraction, whole blood collected in 6 mL EDTA tubes was centrifuged at 3,000 rpm for 10 min to separate the plasma and cellular fractions. cfDNA was extracted from 1.5 mL of plasma using a Custom NEXTprep cfDNA Auto (1.5 mL) kit (Revvity Inc., Waltham, MA, USA) according to the manufacturer\u0026rsquo;s instructions. The extracted cfDNA was stored at 4 ℃ until real-time PCR was performed. For gDNA extraction from whole blood, gDNA was isolated using a DNeasy Blood \u0026amp; Tissue Kit (QIAGEN, Venlo, Netherlands) according to the manufacturer\u0026rsquo;s protocol.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Real-time PCR assay\u003c/h2\u003e \u003cp\u003eFor multiplex real-time PCR, hydrolysis probe\u0026ndash;based real-time PCR reactions contained 2\u0026times; TaqMan Fast Universal PCR Master Mix (Thermo Fisher Scientific, Waltham, MA, USA), specific primers and fluorescently labeled probes, and template DNA, in a final reaction volume of 10 \u0026micro;L. The final concentrations of the primers and probes were 100 nM and 300 nM, respectively. For the multiplex assay, primers and probes were designed to target the junction of the \u003cem\u003eSTX17\u003c/em\u003e intron 6 duplicated segments, and an internal sequence within \u003cem\u003eMSTN\u003c/em\u003e exon 4 was simultaneously amplified in the same reaction as an internal reference. Targets were distinguished using probes labeled with different fluorophores (FAM and VIC). The primer and probe sequences are listed in Table S1. Cycling conditions were as follows: initial denaturation at 95 ℃ for 1 min, followed by 40 cycles of 95 ℃ for 15 s and 60 ℃ for 1 min. Fluorescence signals were acquired at the end of each annealing/extension step of PCR. Data were analyzed using QuantStudio Design and Analysis Software (Thermo Fisher Scientific).The amplification curves and baselines were automatically set using the software and manually adjusted when required. Ct values were calculated based on an automatically determined threshold.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 ddPCR assay\u003c/h2\u003e \u003cp\u003eddPCR was performed following a previously reported method (Rubin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), with redesigned primer sequences for CNV analysis of \u003cem\u003eSTX17\u003c/em\u003e. The target assay amplified the internal region of \u003cem\u003eSTX17\u003c/em\u003e intron 6 and was run as a multiplex ddPCR with a reference assay targeting \u003cem\u003eMSTN\u003c/em\u003e exon 4. The primer and probe sequences are listed in Table S2. The copy number was calculated from the ratio of target to reference copies, and genotypes were assigned according to the calculated copy numbers (expected diploid copy numbers: \u003cem\u003eG3/G3\u003c/em\u003e: 6, \u003cem\u003eG3/G2\u003c/em\u003e: 5, \u003cem\u003eG3/g\u003c/em\u003e or \u003cem\u003eG2/G2\u003c/em\u003e: 4, \u003cem\u003eG2/g\u003c/em\u003e: 3, and \u003cem\u003eg/g\u003c/em\u003e: 2). ddPCR data were analyzed using QuantaSoft Analysis Pro Software (Bio-Rad Laboratories Inc., Hercules, CA, USA). Absolute target concentrations (copies/\u0026micro;L) and 95% confidence intervals (CIs) were calculated using Poisson statistics. For each ddPCR reaction, we confirmed that \u0026ge;\u0026thinsp;10,000 droplets were accepted for analysis and that no non-specific amplification was observed in the negative controls.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 LA-PCR assay\u003c/h2\u003e \u003cp\u003eLA-PCR was performed accoding to the method reported by Rosengren Pielberg et al (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The primer sequences are listed in Table S3. The PCR reactions included each primer, reagents supplied with the Expand Long Range Enzyme mix (Roche Diagnostics, Mannheim, Germany), and DNA extracted from whole blood. The PCR products were separated by electrophoresis on a 0.7% agarose gel at 100 V for 2 h, stained with ethidium bromide, and visualized under UV illumination.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Real-time PCR\u0026ndash;based screening for Gray\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo screen for \u003cem\u003eSTX17\u003c/em\u003e genotypes in the population, we established a workflow consisting of (i) rapid gray/non-gray screening by real-time PCR, (ii) CN analysis of \u003cem\u003eSTX17\u003c/em\u003e intron 6 by ddPCR, and (iii) confirmatory genotyping of \u003cem\u003eG3/g\u003c/em\u003e versus \u003cem\u003eG2/G2\u003c/em\u003e by LA-PCR (Fig. 1). Although real-time PCR could not accurately discriminate the small copy number difference between the \u003cem\u003eG3\u003c/em\u003e and \u003cem\u003eG2\u003c/em\u003e alleles, assessing the presence or absence of amplification from the \u003cem\u003eSTX17\u003c/em\u003e intron 6 duplication junction enabled more efficient discrimination between gray and non-gray horses than LA-PCR alone (Fig. 2). Using this workflow, we screened 4,596 Japanese Thoroughbreds aged 2\u0026ndash;7 years, of which 4,374 were classified as non-gray and 222 as gray.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Discrimination between G3/g and G2/G2 using ddPCR and LA-PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the horses classified as gray by real-time PCR, age and coat appearance were reviewed, and 23 horses were selected as candidates for slow-gray based on delayed depigmentation at age 2\u0026ndash;3 years. These horses were analyzed by ddPCR. Consequently, one horse was classified as G2/g, and the remaining 22 were classified as either G3/g or G2/G2. No G3/G3 or G3/G2 horses were included among the 22 horses. These were subsequently analyzed by LA-PCR, and a g-derived band (~5.6 kbp) was detected in all samples, confirming that all 22 horses were G3/g; the detection of the wild-type g-allele-specific band (~5.6 kb) in all samples confirmed the G3/g genotype (Fig. 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Emergence of the G2 allele\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eG2/g\u003c/em\u003e individuals identified in this study belong to a lineage distinct from the previously reported Japanese slow-gray family. Using samples from this pedigree and applying the established workflow, we found that the sire was \u003cem\u003eG3/g\u003c/em\u003e, whereas the dam and the full sibling (sister) were \u003cem\u003eG2/g,\u003c/em\u003e confirming maternal inheritance of the \u003cem\u003eG2\u003c/em\u003e allele. Pedigree investigation further suggested a slow-gray like coat appearance in the great-granddam generation, whereas earlier generations showed a common gray phenotype. These observations suggest that a reduction in the copy number of the \u003cem\u003eSTX17\u003c/em\u003e intron 6 duplicated segment (including a deletion-type event) occurred in the great-granddam generation and that the resulting \u003cem\u003eG2\u003c/em\u003e allele subsequently segregated within the lineage (Fig. 4).\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eIn this study, we proposed a detection strategy for the Japanese Thoroughbred population by combining real-time PCR, ddPCR, and LA-PCR. This workflow enabled discrimination between common gray and slow-gray and facilitated the search for potentially undetected slow-gray individuals. The newly developed real-time PCR–based screening assay was completed within approximately 2 h, including the reaction time. Compared with conventional workflows that rely solely on LA-PCR and gel electrophoresis, this approach substantially reduces laboratory handling steps and turnaround time while enabling robust and consistent classification of gray and non-gray samples.\u003c/p\u003e\n\u003cp\u003eCNV estimation using real-time PCR is sensitive to differences in amplification efficiency between target and reference assays, inhibitory substances, and assay specificity, making accurate quantitative discrimination of small copy-number differences challenging(Aldhous et al., 2010). Additional optimization and condition testing are necessary to infer \u003cem\u003eSTX17\u003c/em\u003e CNV solely using real-time PCR. However, from an operational perspective eliminating gel electrophoresis is expected to reduce hands-on time, contamination risk, and operator-dependent interpretation. In this study, plasma-derived cfDNA was used for analysis, and when applying the assay to other sample types, differences in DNA extraction conditions may affect PCR inhibition and copy-number variance, potentially influencing the interpretation. Thus, an implementation plan with clearly defined negative/positive controls and retesting criteria (e.g., Ct thresholds and re-extraction rules) is required.\u003c/p\u003e\n\u003cp\u003eddPCR is intrinsically well-suited for distinguishing \u003cem\u003eG2\u003c/em\u003e from \u003cem\u003eG3\u003c/em\u003e because it enables copy number estimation from the target/reference ratio based on absolute quantification.\u0026nbsp;(Hindson et al., 2011). In this study, 23 horses suspected of the slow-gray phenotype based on age and appearance were examined in detail: one horse was classified as \u003cem\u003eG2\u003c/em\u003e/\u003cem\u003eg\u003c/em\u003e, whereas the remaining 22 were inferred by ddPCR as having four copies of the duplicated segment. However, \u003cem\u003eg\u003c/em\u003e-derived electrophoretic bands were detected in all 22 by LA-PCR, confirming that they were \u003cem\u003eG3\u003c/em\u003e/\u003cem\u003eg\u003c/em\u003e. Only one out of 4,596 horses carried the \u003cem\u003eG2\u003c/em\u003e allele, which is consistent with observations in many other breeds that the \u003cem\u003eG2\u003c/em\u003e allele is significantly less frequent than the \u003cem\u003eG3\u003c/em\u003e allele\u0026nbsp;(Rubin et al., 2024). Therefore, the presence of \u003cem\u003eG2\u003c/em\u003e/\u003cem\u003eG2\u003c/em\u003e individuals in the current Japanese Thoroughbred population is likely extremely rare. Nevertheless, when pedigree information suggests segregation of the \u003cem\u003eG2\u003c/em\u003e allele, a two-step confirmation scheme—(i) narrowing genotype candidates using ddPCR and (ii) confirming heterozygosity (\u003cem\u003eg\u003c/em\u003e-carrier status) using LA-PCR—can reliably determine \u003cem\u003eSTX17\u003c/em\u003e genotype.\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eG2/g\u003c/em\u003e individuals detected in this study belong to a lineage distinct from the previously reported slow-gray family. Pedigree investigation and relatedness analysis indicated that the dam and sibling were also \u003cem\u003eG2/g\u003c/em\u003e, demonstrating the inheritance of the \u003cem\u003eG2\u003c/em\u003e allele within the lineage. Because a slow-gray like appearance was suspected in the great-granddam generation, it is plausible that a copy number contraction in the duplicated segment of \u003cem\u003eSTX17\u003c/em\u003e intron 6 (e.g., a contraction corresponding to a decrease from \u003cem\u003eG3\u003c/em\u003e) arose at the origin of this pedigree and subsequently segregated. This suggests that slow-gray individuals are not restricted to a single founder lineage and could have multiple origins within the population, implying that continued monitoring and screening will likely identify additional slow-gray families.\u003c/p\u003e\n\u003cp\u003ePrevious work has suggested that although the founder of \u003cem\u003eG2\u003c/em\u003e in the domestic horse population is unknown, an insertion event from \u003cem\u003eg\u003c/em\u003e to \u003cem\u003eG2\u003c/em\u003e followed by a further insertion generating the \u003cem\u003eG3\u003c/em\u003e allele may have occurred because horses carrying the \u003cem\u003eG3\u003c/em\u003e allele gray earlier; breeding preferences for sires and dams with the \u003cem\u003eG3\u003c/em\u003e allele could have driven the much higher frequency of \u003cem\u003eG3\u003c/em\u003e relative to \u003cem\u003eG2\u003c/em\u003e (Rubin et al., 2024). In contrast, slow-gray which is currently confirmed in the Japanese Thoroughbred population, appears to involve only copy number contraction from \u003cem\u003eG3\u003c/em\u003e to \u003cem\u003eG2\u003c/em\u003e. The Gray founder in Thoroughbreds is thought to be traced back to a single Arabian horse; in the Japanese Thoroughbred population the founder’s \u003cem\u003eG3\u003c/em\u003e allele likely disseminated broadly, with slow- gray arising via copy-number contraction from \u003cem\u003eG3\u003c/em\u003e to \u003cem\u003eG2\u003c/em\u003e(Binns \u0026amp; Swinburne 2004; Swinburne et al., 2002).\u003c/p\u003e\n\u003cp\u003eIn this study, the detection of slow-gray was based on pre-selection criteria such as “gray horses that have not depigmented relative to age,” and thus selection bias remains in estimating the frequency of undetected slow-gray. The absence of early-whitening \u003cem\u003eG3\u003c/em\u003e/\u003cem\u003eG3\u003c/em\u003e horses among the 23 selected individuals is likely attributable to this bias. Moreover, graying progression may be influenced not only by \u003cem\u003eSTX17\u003c/em\u003e genotype, but also by base coat color, age, sex, modifier genes, and environmental factors\u0026nbsp;(Curik et al., 2013; Hofmanová et al., 2015; Teixeira et al., 2013). Therefore, rather than inferring slow-gray horses from non-genetic information, applying this detection strategy to all gray horses based on genotype would enable a more precise estimation of the slow-gray frequency in the Japanese Thoroughbred population. As the \u003cem\u003eSTX17\u003c/em\u003e intron 6 CNV is associated with melanoma risk, characterizing genotype distributions may provide a foundation for future clinical and epidemiological studies(Curik et al., 2013; Teixeira et al., 2013). As research linking genotypes and clinical phenotypes advances, meaningful insights may be gained for risk stratification and early detection.\u003c/p\u003e\n\u003cp\u003eIn conclusion, the proposed strategy—real-time PCR as a primary screen, ddPCR as a secondary assessment, and LA-PCR as confirmatory testing—enables molecular discrimination among non-gray, common gray, and slow-gray. Although slow-gray appears rare in the Japanese Thoroughbred population, our findings indicate that it may have multiple origins. This detection strategy should be useful for the screening and surveillance of potentially undetected slow-gray individuals within the population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the horse owners who kindly provided samples for this research. The authors thank Ms. Tanaka, Ms. Endo and Ms. Sato for their technical assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the experimental protocols were approved by the Animal Care Committee of the Laboratory of Racing Chemistry (approval number: 20-4) and was performed in accordance with the ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAldhous, M. C., Bakar, S. A., Prescott, N. J., Palla, R., Soo, K., Mansfield, J. C., Mathew, C. G., Satsangi, J., \u0026amp; Armour, J. A. L. (2010). 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Identification of a melanocyte-specific, microphthalmia-associated transcription factor-dependent regulatory element in the intronic duplication causing hair Graying and melanoma in horses. \u003cem\u003ePigment Cell and Melanoma Research\u003c/em\u003e,\u0026nbsp;\u003cem\u003e25\u003c/em\u003e(1), 28\u0026ndash;36.\u0026nbsp;\u003cbr\u003e\u0026nbsp;https://doi.org/10.1111/j.1755-148X.2011.00902.x\u003c/li\u003e\n \u003cli\u003eSwinburne, J. E., Hopkins, A., \u0026amp; Binns, M. M. (2002). Assignment of the horse Gray coat colour gene to ECA25 using whole genome scanning. \u003cem\u003eAnimal Genetics\u003c/em\u003e,\u0026nbsp;\u003cem\u003e33\u003c/em\u003e(5), 338\u0026ndash;342.\u0026nbsp;\u003cbr\u003e\u0026nbsp;https://doi.org/https://doi.org/10.1046/j.1365-2052.2002.00895.x\u003c/li\u003e\n \u003cli\u003eTeixeira, R. B. C., Rendahl, A. K., Anderson, S. M., Mickelson, J. R., Sigler, D., Buchanan, B. R., Coleman, R. J., \u0026amp; Mccue, M. E. (2013). Coat color genotypes and risk and severity of melanoma in gray quarter horses. \u003cem\u003eJournal of Veterinary Internal Medicine\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(5), 1201\u0026ndash;1208. https://doi.org/10.1111/jvim.12133\u003c/li\u003e\n \u003cli\u003eViret, C., \u0026amp; Faure, M. (2019). Regulation of Syntaxin 17 during Autophagosome Maturation. \u003cem\u003eTrends in Cell Biology\u003c/em\u003e,\u0026nbsp;\u003cem\u003e29\u003c/em\u003e(1), 1\u0026ndash;3.\u0026nbsp;\u003cbr\u003e\u0026nbsp;https://doi.org/https://doi.org/10.1016/j.tcb.2018.10.003\u003c/li\u003e\n \u003cli\u003eWalter, S. D., King, W. D., \u0026amp; Marrett, L. D. (1999). Association of cutaneous malignant melanoma with intermittent exposure to ultraviolet radiation: results of a case-control study in Ontario, Canada. \u003cem\u003eInternational Journal of Epidemiology\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(3), 418\u0026ndash;427. https://doi.org/10.1093/ije/28.3.418\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biochemical-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bigi","sideBox":"Learn more about [Biochemical Genetics](http://link.springer.com/journal/10528)","snPcode":"10528","submissionUrl":"https://submission.nature.com/new-submission/10528/3","title":"Biochemical Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"deletion, insertion, STX17, slow-gray, structure variation","lastPublishedDoi":"10.21203/rs.3.rs-9164835/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9164835/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGray is a dominant coat color phenotype in horses caused by a ~4.6 kb tandem duplication within intron 6 of syntaxin 17 (\u003cem\u003eSTX17\u003c/em\u003e). The copy number variation (CNV) of the duplicated segment influences the graying rate. The rare \u003cem\u003eG2 \u003c/em\u003eallele (CNV=2) is associated with a slower graying rate compared to the common\u003cem\u003e G3\u003c/em\u003eallele (CNV=3), and is also relevant to melanoma risk. Current assays are limited because long and accurate PCR (LA-PCR) detects only the presence or absence of duplications, while droplet digital PCR (ddPCR) cannot reliably distinguish certain genotypes such as \u003cem\u003eG3/g\u003c/em\u003e and \u003cem\u003eG2/G2\u003c/em\u003e. We constructed a stepwise workflow combining (i) multiplex real-time PCR targeting the duplication junction for rapid gray/non-gray screening, (ii) ddPCR for CN estimation, and (iii) LA-PCR for confirmatory genotyping of ambiguous copy-number classes. Using real-time PCR, we screened 4,596 Japanese Thoroughbreds aged 2–7 years, of which 4,374 were classified as non-gray and 222 as gray. Based on age and coat appearance, 23 gray candidates were prioritized for slow-gray evaluation and analyzed by ddPCR; one was classified as \u003cem\u003eG2/g\u003c/em\u003e and 22 as \u003cem\u003eG3/g\u003c/em\u003eor \u003cem\u003eG2/G2\u003c/em\u003e. LA-PCR detected a g-derived band in all 22 cases, confirming that it was \u003cem\u003eG3/g\u003c/em\u003e. Pedigree analysis indicated that the \u003cem\u003eG2 \u003c/em\u003eallele was maternally inherited and originated from a lineage distinct from a previously reported Japanese slow-gray family. This workflow enables practical molecular discrimination among non-gray, common gray, and slow-gray genotypes, supporting the surveillance of rare \u003cem\u003eG2\u003c/em\u003e alleles in the Japanese Thoroughbred population.\u003c/p\u003e","manuscriptTitle":"Identification of a Novel Slow-Gray STX17 Lineage in Japanese Thoroughbreds via a Multi-Tiered Copy Number Analysis Workflow","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-20 09:57:59","doi":"10.21203/rs.3.rs-9164835/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-09T11:27:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-08T22:06:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-28T13:42:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-24T17:55:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-19T15:58:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"260563047017125640598560458398517620826","date":"2026-04-15T14:13:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"19179050524074335033097279762751145217","date":"2026-04-13T10:56:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"198690081462259577974385716772654886526","date":"2026-04-10T17:39:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"239244520673422846919050384164463302508","date":"2026-04-10T15:12:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"236540575075428749962237012673363889061","date":"2026-04-10T13:21:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-10T12:40:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-20T10:34:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-20T10:34:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biochemical Genetics","date":"2026-03-19T04:23:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biochemical-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bigi","sideBox":"Learn more about [Biochemical Genetics](http://link.springer.com/journal/10528)","snPcode":"10528","submissionUrl":"https://submission.nature.com/new-submission/10528/3","title":"Biochemical Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"59cc2dcd-8245-4c30-bd52-81d7ba2bb987","owner":[],"postedDate":"April 20th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-09T11:27:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-08T22:06:33+00:00","index":41,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-09T11:39:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-20 09:57:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9164835","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9164835","identity":"rs-9164835","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}