Identification and Validation of Microsatellite Markers for Acer rubrum

  • Arboriculture & Urban Forestry (AUF)
  • March 2026,
  • 52
  • (2)
  • 159-168;
  • DOI: https://doi.org/10.48044/jauf.2026.004

Abstract

Red maple (Acer rubrum) is one of the most commonly cultivated tree species and is often used in urban settings, as it is resilient, fast-growing, and tolerant of a wide variety of conditions. This study sought to understand the genetic variation between A. rubrum cultivars using microsatellites. Since A. rubrum is an autopolyploid that is often either hexaploid or octoploid, but can also be tetraploid, this species presents unique challenges for understanding population genetics, as many statistical tests assume diploidy. For these reasons, we cross referenced and verified genetic relationships with information regarding the development of the cultivars. We tested a total of 34 microsatellite loci that had been previously developed for closely related Acer spp. until we were able to validate 12 microsatellite loci that were consistently present in our A. rubrum samples, which included both wild-type and cultivated trees. Following validation, we then looked at the genetic relationships between 16 cultivars. These cultivars included some of the most popularly available, including Armstrong, Franks Jr.TM (Redpointe), Franks RedTM (Red Sunset), and October Glory. We found that our genetic results from the microsatellite analysis were consistent with the histories of the developments of the various cultivars and therefore have confidence in using these microsatellite markers for analysis of A. rubrum.

Keywords

Introduction

Red maple, Acer rubrum, is one of the most cultivated trees in the nursery industry and is a highly popular choice for urban tree planting schemes. Its native range spans much of the Eastern coast of the United States, from as far north as Quebec, Canada, to as far south as Florida in the United States, and as far west as Texas and Minnesota in the United States (Santamour 1965). However, it is readily available for purchase in nurseries across North America and even in Europe. Acer rubrum is consistently popular because it tolerates a wide variety of soil and moisture conditions, as well as being fast growing and deer resistant (Abrams 1998). Due to these traits, this hardy and versatile tree has been in cultivation since the 19th century.

The term cultivar refers specifically to plants that are selectively bred to maintain certain desired traits. In the case of A. rubrum, there are currently over 50 cultivated varieties available (van Gelderen et al. 1994), with varieties that have been bred for various features including pest resistance, vibrant fall foliage, or specific crown and branching structures. While the popularity of some cultivars is dictated by geography, with varieties bred for success in colder or warmer climates, many cultivars are favored for consistency in growth pattern and robustness. Additionally, there are a variety of cultivars such as “Northwood”, developed by Frank Schmidt Arboretum (J. Frank Schmidt & Son Co., Boring, OR, USA), and “Karpick”, developed by Femrite Nursery (Aurora, OR, USA), where there is too much variation in the cultivar and not enough consistency of traits (Townsend and Douglass 1998). The development of these types of cultivars is usually abandoned in favor of lineages with more dependable and homogenous qualities. Another key feature of many preferred cultivars is relatively quick growth. Nurseries prioritize fast growing lineages, as they are able to profit from them more quickly, and purchasers often want a tree that will get to a large size in a shorter period of time (van Nocker and Gardiner 2014). For this reason, some cultivars that have similar aesthetic features but don’t develop as rapidly are not as popular. This is the case with the cultivar “Columnare” and “Armstrong”; while both have an upright, narrow branching structure, Armstrong reaches a larger size more promptly (Sydnor 1980). Due to preferences for faster growing trees, often only a few cultivars dominate in a given region.

Despite the preponderance of this tree in arboriculture, there have not been extensive studies on the population genetics of A. rubrum. This maple species is a variable autopolyploid, and individuals within this species can range anywhere from 4x to 8x, with 6x and 8x being the most common (Santamour 1965; Contreras and Shearer 2018). In addition, this tree species is polygamodioecious, meaning it is capable of hermaphroditic changes from year to year, and in some cases, it can be monoecious, with both sex characteristics being found on the same tree concurrently (Sakai 1990). However, it is most often dioecious, with distinct male and female sex characteristics on different trees. The complicated nature of both the variable ploidy and polygamodioecious potential present challenges for analyzing A. rubrum population genetics. Fortunately, microsatellites have been successfully used in other polyploid species and are known to be capable of detecting differences among multiple alleles within an organism’s genome (Vieira et al. 2016). As microsatellites are highly polymorphic, they are ideal for analyzing complex polyploid genetics and are a useful tool for population genetics. This paper will serve as a foundation for further population genetic studies of A. rubrum. It is possible that the decreased genetic diversity of cultivars could have an impact on the genetic diversity of local wildtype populations, and further studies on urban tree populations will be vital to understanding urban ecosystems (Ingvarsson and Dahlberg 2019; Avolio 2023). We therefore sought to establish a verified set of microsatellite regions specific for use in A. rubrum. We then use these microsatellite markers to inform on the relationships among common A. rubrum cultivars.

Methods

Sample Collection

In the summer of 2021, we collected leaf samples from 20 trees in various locations around Baltimore (MD, USA) with the intention of collecting samples of varied genetic backgrounds. We expected to capture wildtype lineages in rural and suburban forests and therefore sampled from state parks and nature preserves. We used a database of trees maintained by TreeBaltimore (Baltimore, MD, USA) to locate street and park trees that were planted and assumed to be cultivars. We also sampled from urban forest patches to capture potential hybrids of wild-type and cultivars. We used these 20 samples to test for the presence of microsatellite regions that had been developed for other closely related Acer spp. Once an appropriate number of microsatellite regions were confirmed to be present in A. rubrum, we visited several nurseries throughout the Baltimore region in the summer of 2023. Although there are over 50 developed cultivars, most commercial retailers sold only 2 or 3 of the most popular cultivars. The most commonly sold cultivars were October Glory, Franks RedTM, and Franks Jr.TM. In order to obtain less popular cultivars, we also collected additional cultivar tissue from the National Arboretum in Washington, DC (USA). The National Arboretum had 14 unique cultivars (Table 1) with several specimens of certain cultivars that were different ages. To collect samples, we took 3 leaves from the tree and recorded the cultivar name. A total of 38 samples of various cultivars from the nurseries and the Arboretum were analyzed to assess the genetic diversity within cultivar lineages.

View this table:
Table 1.

List of cultivars including brand name and generic name (if there is one), the year that the cultivar was developed, the nursery or organization that originally developed it, the geographical region of the original provenance of the cultivar, and key features maintained in the cultivar’s lineage.

DNA Extraction

We stored leaf samples in paper coin envelopes within a sealed plastic bag filled with silica desiccant prior to proceeding. After samples were dried, we ground leaf fragments in a bead mill for 90 seconds at 30Hz using 24-mm metal beads (Fisherbrand™ Bead Mill 24 Homogenizer; Thermo Fisher Scientific, Waltham, MA, USA). Following pulverization, we extracted DNA using the E.Z.N.A. Plant DNA DS Mini Kit (Omega Bio-Tek, Norcross, GA, USA). Quality and quantity checks were rendered using gel electrophoresis on a 1% gel agarose stained with gel-red and compared against a DNA ladder (1kb)(New England Biolabs, Ipswich, MA, USA). We stored extracted DNA at −30 °C.

Primer Testing

We selected primers that had been successfully identified in closely related species to test for consistent presence in the A. rubrum population. We referenced primers from Pandey et al. (2004), who originally looked at A. pseudoplatanus and which were successfully used by Motahari et al. (2021) for A. monspessulanum. Harmon et al. (2017) and Graignic et al. (2013) both developed primers for A. saccharum. Lastly, primers developed for A. miyebei by Saeki et al. (2015) were tested. We tested a total of 34 potential microsatellites on the genetically diverse sample of 20 individuals. Microsatellite regions that were present in at least 80% of the samples were included in future analysis. We verified presence or absence of nucleotide repeats using Sanger sequencing at the Johns Hopkins Genetics Resources Core Facility (Baltimore, MD, USA). Based on literature reviews of using microsatellites to inform genetic relationships, a goal of 12 microsatellite regions was set for comparison rigor (Koskinen et al. 2004; Hale et al. 2012). The following 12 microsatellite loci were found to be present in the sample of the A. rubrum populations and were then used in the later analysis of all 38 cultivars (Table 2). We ordered primers corresponding to those microsatellite regions with fluorescent dyes 6-FAM, MAX, Atto565, or Atto550 affixed to the forward primers (Table 3).

View this table:
Table 2.

Primers tested and rates of detection in our samples. Those that are highlighted were detected and used for further analysis.

View this table:
Table 3.

Microsatellite regions with allele size, base pairs, and dyes used.

We performed PCRs with 15 μl total volume comprised of 2-μl template DNA, 0.20-μl M of each forward primer with fluorescent dye, 0.15 μl of each reverse primer, and 7.5 μl of UCP Multiplex Mix (QIAGEN, Venlo, Netherlands) with a 4× concentration of Taq. Samples were run using the following protocols:

  • Primer pairs developed by Graignic (Tables 2, 3) consisted of an initial denaturation period at 94 °C for 15 minutes. This was followed by 35 cycles of 94 °C for 60 seconds, 54 °C for 90 seconds, and 72 °C for 60 seconds. A final extension was run at 72 °C for 45 minutes.

  • Primer pairs developed by Pandey (Tables 2, 3) were referenced and consisted of an initial denaturation period at 95 °C for 15 minutes. This was followed by 35 cycles of 94 °C for 45 seconds, 45 °C for 60 seconds, and 72 °C for 120 seconds. A final extension was run at 72 °C for 8 minutes.

  • Primer pairs developed by Harmon (Tables 2, 3) were referenced with the modified PCR protocol used by Motahari, which consisted of an initial denaturation period at 94 °C for 5 minutes. This was followed by 36 cycles of 94 °C for 60 seconds, 64 °C for 60 seconds, and 72 °C for 45 seconds. A final extension was run at 72 °C for 10 minutes.

  • Primer pairs developed by Saeki (Tables 2, 3) were referenced and consisted of an initial denaturation period at 95 °C for 5 minutes. This was followed by 35 cycles of 95 °C for 30 seconds, 60 °C for 90 seconds, and 72 °C for 30 seconds. A final extension was run at 72 °C for 30 minutes.

PCR product was sent to the University of Arizona Genetics Core (Tucson, AZ, USA). The PCR product was diluted 1:20 and fragment analysis was performed on an ABI3730 DNA Analyzer (Applied Biosystems, Waltham, MA, USA).

Allele Scoring

We analyzed the fragment analysis files using Gene-Marker software version 3.0.1 (SoftGenetics LLC, State College, PA, USA). All results were scored twice by two independent scorers, and results were combined to verify consistency between calls. We used the Polysat package in R (R Foundation, Vienna, Austria) to calculate distance matrices using Bruvo distance (Clark and Jasieniuk 2011). As Polysat is specifically designed for use on microsatellite data in polyploid organisms, it was used for the bulk of the analyses. Since A. rubrum has unknown copies of alleles, Bruvo distance is the most appropriate measure, as it accounts for mutational distance between alleles (Bruvo et al. 2004). We had technical (DNA extracted from the same leaf) and biological (DNA extracted from multiple specimens of the same cultivar) replicates. We found technical replicates had up to 96% similarity, and biological replicates had 88% similarity. This low degree of similarity within cultivars could be due to the presence of null alleles, which could cause heterozygous loci to be incorrectly scored as homozygous (Kanaka et al. 2023). The potential for null alleles is even greater in polyploids, and therefore allele frequencies were estimated using the method developed by De Silva et al. (2005) for use with polyploids. Alternatively, these differences in similarity could also be accounted for by genetic drift in older cultivars that have been propagated for a longer period of time. Additionally, it is possible that there were somatic mutations occurring in the leaves of different individuals, even when propagated from the same parent stock (Bairu et al. 2011). We then generated cladograms (Figure 1A) to display genetic groups in R using the packages ggtree2 and ape (Wickham 2007; Paradis and Schliep 2019).

(A) Cladogram of A. rubrum cultivars. Cultivars that have been hybridized with A. saccharinum have an * after the cultivar name. Colors correspond to the state of origin of the trees used in the cultivar’s development. (B) Map of Cultivar origins that correspond to Figure 1A. Each color represents a different state, and circles reflect the locations where nurseries obtained trees used in the development of the cultivar.
Figure 1.

(A) Cladogram of A. rubrum cultivars. Cultivars that have been hybridized with A. saccharinum have an * after the cultivar name. Colors correspond to the state of origin of the trees used in the cultivar’s development. (B) Map of Cultivar origins that correspond to Figure 1A. Each color represents a different state, and circles reflect the locations where nurseries obtained trees used in the development of the cultivar.

In order to determine the level of genetic diversity between different cultivar lineages, we used the Polysat package to determine ploidy levels, calculate allele frequencies, detect genotypic distributions, and to create distance matrices (Clark and Jasieniuk 2011). We also used the program GenoDive (Patrick Meirmans, Amsterdam, Netherlands), which can be used with polyploids, to calculate observed heterozygosity (HO), heterozygosity within populations (HS), and total heterozygosity (HT)(Meirmans 2020).

Investigation of Cultivar Sources

Genetic relationships were also cross-referenced with known history of the cultivars. Several cultivars go by different names depending on if they are sold under the original patented name or a generic name; e.g., Franks RedTM is the trademarked name for the generic “Red Sunset”. We used various publications, including academic journals, grey literature from governmental agencies, horticultural texts, and patents to determine the origin, key features, and general history of A. rubrum cultivars. The following patent numbers were referenced: PP25301, PP04864, PP16769, PP02116, and PP02377.

Results and Discussion

Within forestry and arboriculture, A. rubrum is a widely propagated and distributed commodity. Having a method for describing genetic diversity and genetic structure will be beneficial for future studies that involve this species. Using microsatellites allows for cost-effective ways to detect relationships, inbreeding coefficients, and trends in gene flow. Here, we describe 12 microsatellite loci that can be used to study A. rubrum.

Using these new microsatellite loci, we found evidence of very little genetic diversity between the cultivars. The lack of diversity between the cultivars is expected, as several cultivars were developed by hybridizing two previously developed cultivars (e.g., Sun Valley is a cross of Red Sunset and Autumn Flame, and Somerset is a cross of October Glory and Autumn Flame). Alleles per locus ranged from 12 to 34. The observed heterozygosity (HO) for the cultivars was 0.772, while the expected heterozygosity (HE) was 0.638 (Table 4). Increased levels of heterozygosity are indicative of more movement between populations, whereas decreased levels indicate a more isolated population with greater likelihood of homozygotes (Fridman 2015). We are likely seeing higher than expected heterozygosity among cultivars as cultivar stock can be sourced from the entire native range of A. rubrum, rather than from one distinct population.

View this table:
Table 4.

Summary of population statistics for A. rubrum.

The results of our genetic analysis were largely in line with the findings of our research on the history of the cultivars. Cultivars with origins from similar geographic locations tend to be more closely related (Figure 1B). Armstrong and Autumn Blaze were developed with trees from Ohio and are found on the same branch of the cladogram. Documentation of these cultivars also indicates that hybridization with silver maple (A. saccharinum) was used in the development of these lineages as well as in Freemanii (Sibley et al. 1995). Indeed, we find that Armstrong, Autumn Blaze, and Freemanii are closely related. Freemanii and Schlesingeri were both sourced from trees originating from Massachusetts and are likewise closely associated. These relationships suggest that there are regional differences found in A. rubrum that are being propagated through artificial selection and maintained within cultivar stock. The National Arboretum (Washington, DC, USA) developed several cultivars specifically bred for pest resistance from crossing previously developed cultivars, and these relationships are confirmed by the genetic analysis. The cultivars Somerset and Brandywine were developed by the National Arboretum from crossing October Glory with Autumn Flame and are very closely related both to each other and to the parent stock. Sun Valley was also developed by the National Arboretum and is a cross between Autumn Flame and Franks RedTM and is also closely clustered with the declared parent stock. While we expected a closer relationship between Franks RedTM and Franks Jr.TM, the genetic results indicate that the trees originating from New York are more prominent in Franks Jr.TM genetics than are the stock from Franks RedTM. Publications of the development of Franks Jr.TM are not clear as to how many different trees were used to develop Franks Jr.TM, but genetic results indicate that it was likely a few different trees crossed with Franks RedTM.

Many A. rubrum cultivars are developed in Oregon and Washington, DC, but their genetic provenances are typically from Northern areas. In the face of consistent warming trends due to climate change, it is unknown if cultivars that were sourced from colder regions will be able to survive in warmer regions of the continental United States. With investment in urban greening initiatives becoming increasingly popular (Doroski et al. 2020), it would be economical to match the most appropriate cultivar for particular environmental conditions to guarantee success and lasting survival of trees.

One of the main selling features of A. rubrum is that it is native to many parts of the Eastern and middle United States. If planters are choosing this species to foster biodiversity, but are only able to obtain cultivars, it is possible that these cultivars may not be as valuable to the broader ecosystem as their wildtype counterparts. For example, many cultivars were developed to be resistant to pest damage; however, it is unknown if this resistance will affect interactions with other organisms. Clearly, cultivars have advantages for city planners, as many were developed to withstand harsh urban conditions, such as compacted soils and limited access to water and nutrients. However, for those who are planting in more hospitable conditions or who are looking for trees for the purposes of ecosystem restoration, relying on cultivars may be inadequate in these settings. Additional research is needed on the broader impacts of cultivars on the surrounding ecosystems, both from an inter and intra species perspective. To date, the impact of planting cultivars on the resilience and diversity of urban forests is understudied (Avolio 2023). This could potentially result in decreased biodiversity among wild-type trees and could thereby impact the long-term health and ecosystem services of urban forests.

Conflicts of Interest

The authors reported no conflicts of interest.

Acknowledgements

We thank Nancy Sonti, Dexter Locke, Morgan Grove, Eva Perry, and Karin Burghardt for helping to conceptualize this study. We thank Ava Hoffman and Ester Rozenblum for guidance on understanding population genetics and polyploids. We also thank Ayla Frost and Olivia Arbogast for assistance in the field and in the lab. Lastly, this research was funded by the USDA NIFA AFRI Award Number #: 2021-67013-33619.

Literature Cited

  1. ↵
    Abrams MD. 1998. The red maple paradox: What explains the widespread expansion of red maple in eastern forests? Bio-Science. 48(5):355-364. https://doi.org/10.2307/1313374
    Google ScholarCrossRefWeb of Science
  2. ↵
    Avolio ML. 2023. The unexplored effects of artificial selection on urban tree populations. American Journal of Botany. 110(7):e16187. https://doi.org/10.1002/ajb2.16187
    Google ScholarPubMed
  3. ↵
    Bairu MW, Aremu AO, Van Staden J. 2011. Somaclonal variation in plants: Causes and detection methods. Plant Growth Regulation. 63:147-173. https://doi.org/10.1007/s10725-010-9554-x
    Google Scholar
  4. ↵
    Bruvo R, Michiels NK, D’souza TG, Schulenburg H. 2004. A simple method for the calculation of microsatellite genotype distances irrespective of ploidy level. Molecular Ecology. 13(7):2101-2106. https://doi.org/10.1111/j.1365-294X.2004.02209.x
    Google ScholarCrossRefPubMedWeb of Science
  5. ↵
    Clark LV, Jasieniuk M. 2011. polysat: An R package for polyploid microsatellite analysis. Molecular Ecology Resources. 11(3):562-566. https://doi.org/10.1111/j.1755-0998.2011.02985.x
    Google ScholarPubMed
  6. ↵
    Contreras RN, Shearer K. 2018. Genome size, ploidy, and base composition of wild and cultivated Acer. Journal of the American Society for Horticultural Science. 143(6):470-485. https://doi.org/10.21273/JASHS04541-18
    Google ScholarCrossRefAbstract/Full Text
  7. ↵
    De Silva HN, Hall AJ, Rikkerink E, McNeilage MA, Fraser LG. 2005. Estimation of allele frequencies in polyploids under certain patterns of inheritance. Heredity. 95:327-334. https://doi.org/10.1038/sj.hdy.6800728
    Google ScholarCrossRefPubMedWeb of Science
  8. ↵
    Doroski DA, Ashton MS, Duguid MC. 2020. The future urban forest—A survey of tree planting programs in the Northeastern United States. Urban Forestry & Urban Greening. 55:126816. https://doi.org/10.1016/j.ufug.2020.126816
    Google Scholar
  9. ↵
    Fridman E. 2015. Consequences of hybridization and heterozygosity on plant vigor and phenotypic stability. Plant Science. 232:35-40. https://doi.org/10.1016/j.plantsci.2014.11.014
    Google ScholarCrossRefPubMed
  10. ↵
    Graignic N, Tremblay F, Bergeron Y. 2013. Development of polymorphic nuclear microsatellite markers in sugar maple (Acer saccharum Marsh.) using cross-species transfer and SSR-enriched shotgun pyrosequencing. Conservation Genetics Resources. 5:845-848. https://doi.org/10.1007/s12686-013-9923-7
    Google Scholar
  11. ↵
    Hale ML, Burg TM, Steeves TE. 2012. Sampling for microsatellite-based population genetic studies: 25 to 30 individuals per population is enough to accurately estimate allele frequencies. PLoS ONE. 7(9):e45170. https://doi.org/10.1371/journal.pone.0045170
    Google ScholarCrossRefPubMed
  12. ↵
    Harmon M, Lane T, Staton M, Coggeshall MV, Best T, Chen CC, Liang H, Zembower N, Drautz-Moses DI, Hwee YZ, Schuster SC, Schlarbaum SE, Carlson JE, Gailing O. 2017. Development of novel genic microsatellite markers from transcriptome sequencing in sugar maple (Acer saccharum Marsh.). BMC Research Notes. 10:369. https://doi.org/10.1186/s13104-017-2653-2
    Google ScholarPubMed
  13. ↵
    Ingvarsson PK, Dahlberg H. 2019. The effects of clonal forestry on genetic diversity in wild and domesticated stands of forest trees. Scandinavian Journal of Forest Research. 34(5): 370-379. https://doi.org/10.1080/02827581.2018.1469665
    Google ScholarCrossRef
  14. ↵
    Kanaka KK, Sukhija N, Goli RC, Singh S, Ganguly I, Dixit SP, Dash A, Malik AA. 2023. On the concepts and measures of diversity in the genomics era. Current Plant Biology. 33:100278. https://doi.org/10.1016/j.cpb.2023.100278
    Google Scholar
  15. ↵
    Koskinen MT, Hirvonen H, Landry PA, Primmer CR. 2004. The benefits of increasing the number of microsatellites utilized in genetic population studies: An empirical perspective. Hereditas. 141(1):61-67. https://doi.org/10.1111/j.1601-5223.2004.01804.x
    Google ScholarCrossRefPubMedWeb of Science
  16. ↵
    Meirmans PG. 2020. genodive version 3.0: Easy-to-use software for the analysis of genetic data of diploids and polyploids. Molecular Ecology Resources. 20(4):1126-1131. https://doi.org/10.1111/1755-0998.13145
    Google ScholarPubMed
  17. ↵
    Motahari B, Shabanian N, Rahmani MS, Mohammad-Hasani F. 2021. Genetic diversity and genetic structure of Acer monspessulanum L. across Zagros forests of Iran using molecular markers. Gene. 769:145245. https://doi.org/10.1016/j.gene.2020.145245
    Google ScholarPubMed
  18. ↵
    Pandey M, Gailing O, Fischer D, Hattemer HH, Finkeldey R. 2004. Characterization of microsatellite markers in sycamore (Acer pseudoplatanus L.). Molecular Ecology Notes. 4(2):253-255. https://doi.org/10.1111/j.1471-8286.2004.00633.x
    Google ScholarCrossRefWeb of Science
  19. ↵
    Paradis E, Schliep K. 2019. ape 5.0: An environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics. 35(3):526-528. https://doi.org/10.1093/bioinformatics/bty633
    Google ScholarCrossRefPubMed
  20. ↵
    Saeki I, Hirao AS, Kenta T. 2015. Development and evaluation of microsatellite markers for Acer miyabei (Sapindaceae), a threatened maple species in East Asia. Applications in Plant Sciences. 3(6):1500020. https://doi.org/10.3732/apps.1500020
    Google Scholar
  21. ↵
    Sakai AK. 1990. Sex ratios of red maple (Acer rubrum) populations in Northern lower Michigan. Ecology. 71(2):571-580. https://doi.org/10.2307/1940310
    Google ScholarCrossRefWeb of Science
  22. ↵
    Santamour FS Jr. 1965. Cytological studies in red and silver maples and their hybrids. Bulletin of the Torrey Botanical Club. 92(2):127-134. https://doi.org/10.2307/2483933
    Google ScholarCrossRef
  23. ↵
    Sibley JL, Eakes DJ, Gilliam CH, Keever GJ, Dozier WA Jr, Peterson CM. 1995. Anatomy and morphology of select red maple cultivars. Journal of Arboriculture. 21(3):136-144. https://doi.org/10.48044/jauf.1995.023
    Google Scholar
  24. ↵
    Sydnor TD. 1980. Evaluation of the growth and development of thirteen cultivars of Acer rubrum L. HortScience. 15(3):436. https://eurekamag.com/research/000/883/000883329.php
    Google Scholar
  25. ↵
    Townsend AM, Douglass LW. 1998. Evaluation of various traits of 40 selections and cultivars of red maple and Freeman maple growing in Maryland. Journal of Environmental Horticulture. 16(4):189-194. https://doi.org/10.24266/0738-2898-16.4.189
    Google Scholar
  26. ↵
    van Gelderen DM, de Jong PC, Oterdoom HJ. 1994. Maples of the world. Portland (OR, USA): Timber Press. 478 p.
    Google Scholar
  27. ↵
    van Nocker S, Gardiner SE. 2014. Breeding better cultivars, faster: Applications of new technologies for the rapid deployment of superior horticultural tree crops. Horticulture Research. 1:14022. https://doi.org/10.1038/hortres.2014.22
    Google ScholarPubMed
  28. ↵
    Vieira MLC, Santini L, Diniz AL, Munhoz CDF. 2016. Microsatellite markers: What they mean and why they are so useful. Genetics and Molecular Biology. 39(3):312-328. https://doi.org/10.1590/1678-4685-GMB-2016-0027
    Google Scholar
  29. ↵
    Wickham H. 2007. Reshaping data with the reshape package. Journal of Statistical Software. 21(12):1-20. https://doi.org/10.18637/jss.v021.i12
    Google Scholar
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Vol. 52, Issue 2

March 2026

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    Identification and Validation of Microsatellite Markers for Acer rubrum
    • Arboriculture & Urban Forestry (AUF)
    • Mar 2026,
    • 52
    • (2)
    • 159-
    • 168;
    • DOI: 10.48044/jauf.2026.004
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Keywords

Acer rubrum, Cultivar, Genetic Diversity, Microsatellites, Polyploid