# Overview

#### Statistical Genetics Lab
Department of Genetics
Luiz de Queiroz College of Agriculture
University of São Paulo

#### 2026-01-12

OneMap is an environment for constructing linkage maps in several experimental crosses, including outcrossing (full-sib families derived from two non-homozygous parents), RILs, F\(_2\), and backcrosses.

It is implemented as a package to be used under the freely distributed R software, which is a language and environment for statistical computing (www.r-project.org). It is designed to be fully integrated with the R/qtl package (Broman and Sen, 2009) and Windows QTL Cartographer (Wang et al., 2010) in order to do QTL mapping for RILs, F\(_2\), and backcrosses. New functions for doing QTL mapping in outcrossing species (e. g. using models from Gazaffi et al. 2014) are under development and will be included in the near future.

Wu et al. (2002a) proposed a methodology to construct genetic maps in outcrossing species, which allows the analysis of a mixed set of different marker types containing various segregation patterns. It also allows the simultaneous estimation of linkage and linkage phases between markers. Combined with ideas from Wu et al. (2002b) for doing multipoint analysis based on hidden Markov models (HMMs), provides an excellent framework for genetic mapping in outcrossing species, in a similar way as for inbred-based populations, commonly analyzed by packages such as MAPMAKER/EXP (Lander et al., 1987).

This method was implemented in OneMap and was tested through extensive simulations. It was also successfully applied by the author(s) of the packages and their collaborators in the construction of genetic maps of sugarcane (Garcia et al., 2006; Oliveira et al., 2007; Palhares et al. 2013), Passiflora (Oliveira et al., 2008; Pereira et al., 2013), rubber tree (Souza et al., 2013) and Acca sellowiana (Quezada et al., 2014). Actually, the analysis of these data sets motivated the implementation of the first release of OneMap (Margarido et al., 2007) and all its subsequent updates.

In version 2.0-0, we included several major modifications to take advantage of the fact that some segregation patterns that occur in outcrossing populations can also occur in populations derived from inbred lines (i.e. RILs, F\(_2\), and backcrosses). For example, a marker that segregates in a 1:2:1 fashion in the outcrossing context can be viewed as a co-dominant marker in F\(_2\) populations. The main difference is that, for the latter, there is no need to estimate linkage phases.

Using these ideas, we adapted OneMap to also construct genetic maps for RILs, F\(_2\), and backcross populations, all incorporating the advantages of the HMMs. Moreover, we also implemented three new ordering algorithms. Version 1.0-0 had Rapid Chain Delineation - RCD (Doerge, 1996) and TRY (Lander et al., 1987); starting in version 2.0-0, the new ones available are Seriation - SER (Buetow and Chakravarti, 1987), recombination counting and ordering - RECORD (Van Os et al., 2005) and unidirectional growth - UG (Tan and Fu, 2006). They can be used for all experimental crosses included in OneMap, and can be chosen to give the best result for any situation faced by the user (Mollinari et al., 2009).

OneMap is available as source code for Windows, Linux, and Mac OS. It is released under the GNU General Public License, is open-source and the code can be changed freely. It comes with no warranty.

No advanced knowledge in R is required to use OneMap. Several researchers around the world had contacted us to provide feedback and suggestions. If you do not know R, we wrote a short vignette with an introduction to R, where we address the basic knowledge required to start using OneMap. People with some knowledge of R may just skip this part.

We also wrote a chapter with information about OneMap installation, as well as sections showing the usage of OneMap to build linkage maps for outcrossing (non-inbred) populations, as well as F\(_2\) populations (which can also be applied to backcrosses and RILs). All sections may be read independently. So, you can just move to the part you are interested in.

The software has been available on CRAN since 2007 (OneMap on CRAN) and has undergone several updates, adding new features and optimization up to version 3.2.0 in 2024. Future updates will focus solely on maintaining accessibility and functionality. New feature development and optimization efforts are now being directed toward the MAPpoly and MAPpoly2 packages.

MAPpoly is a more robust package designed for constructing linkage maps in polyploid species. Its optimized algorithms also provide improved efficiency for diploid species compared to OneMap. Therefore, we recommend using MAPpoly instead of OneMap in the following scenarios for diploid species:

- When working with only biallelic markers (e.g., SNPs).
- For outcrossing full-sib (F1), F2, or backcross populations.
- For datasets with a large number of markers (>5,000).
- For multi-population datasets (e.g., progeny from multiple parents; see MAPpoly2).

However, OneMap remains the best choice if you have:

- Populations derived from recombinant inbred lines (RILs).
- Datasets with multiallelic or dominant markers.

For guidance on best practices in building linkage maps while accounting for genotyping errors, please refer to Taniguti et. al 2023.

# How to Cite

Margarido, G. R. A., Souza, A. P., &38; Garcia, A. A. F. (2007). OneMap: software for genetic mapping in outcrossing species. Hereditas, 144(3), 78–79. https://doi.org/10.1111/j.2007.0018-0661.02000.x

- If you are using OneMap versions > 2.0, please cite also:

Taniguti, C. H.; Taniguti, L. M.; Amadeu, R. R.; Lau, J.; de Siqueira Gesteira, G.; Oliveira, T. de P.; Ferreira, G. C.; Pereira, G. da S.; Byrne, D.; Mollinari, M.; Riera-Lizarazu, O.; Garcia, A. A. F. Developing best practices for genotyping-by-sequencing analysis in the construction of linkage maps. 2023. GigaScience, 12, giad092. https://doi.org/10.1093/gigascience/giad092

- If you used the HMM parallelization, please cite BatchMap paper too:

Schiffthaler, B., Bernhardsson, C., Ingvarsson, P. K., &; Street, N. R. (2017). BatchMap: A parallel implementation of the OneMap R package for fast computation of F1 linkage maps in outcrossing species. PLoS ONE, 12(12), 1–12. https://doi.org/10.1371/journal.pone.0189256

# References

Broman K. W., Sen S., 2009. A Guide to QTL Mapping with R/qtl. Springer, New York.

Wang S., Basten, C. J. and Zeng Z.-B. Windows QTL Cartographer 2.5. Department of Statistics, North Carolina State University, Raleigh, NC, 2010.

Wu, R., Ma, C.X., Painter, I. and Zeng, Z.-B. 2002a. Simultaneous maximum likelihood estimation of linkage and linkage phases in outcrossing species. Theoretical Population Biology 61: 349-363.

Wu, R., Ma, C.-X., Wu, S. S. and Zeng, Z.-B. 2002b. Linkage mapping of sex-specific differences. Genetical Research 79: 85-96.

Gazaffi R., Margarido G. R. A., Pastina M. M., Mollinari M., Garcia A. A. F., 2014. A model for quantitative trait loci mapping, linkage phase, and segregation pattern estimation for a full-sib progeny. Tree Genet. Genomes 10: 791–801.

Lander, E.S., Green, P., Abrahanson, J., Barlow, A., Daly, M.J., Lincoln, S.E. and Newburg, L. 1987. MAPMAKER, An interactive computing package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1: 174-181.

Garcia A. A. F., Kido E. A., Meza A. N., Souza H. M. B., Pinto L. R., Pastina M. M., Leite C. S., Silva J. A. G. da, Ulian E. C., Figueira A. V, Souza A. P., 2006. Development of an integrated genetic map of a sugarcane (Saccharum spp.) commercial cross, based on a maximum-likelihood approach for estimation of linkage and linkage phases. Theor. Appl. Genet. 112: 298–314.

Oliveira K. M., Pinto L. R., Marconi T. G., Margarido G. R. A., Pastina M. M., Teixeira L. H. M., Figueira A. V, Ulian E. C., Garcia A. A. F., Souza A. P., 2007. Functional integrated genetic linkage map based on EST-markers for a sugarcane (Saccharum spp.) commercial cross. Mol. Breed. 20: 189–208.

Palhares A. C., Rodrigues-Morais T. B., Sluys M.-A. Van, Domingues D. S., Maccheroni W., Jordão H., Souza A. P., Marconi T. G., Mollinari M., Gazaffi R., Garcia A. A. F., Vieira M. L. C., 2012. A novel linkage map of sugarcane with evidence for clustering of retrotransposon-based markers. BMC Genet. 13: 51.

Oliveira E. J., Vieira M. L. C., Garcia A. A. F., Munhoz C. F., Margarido G. R. A., Consoli L., Matta F. P., Moraes M. C., Zucchi M. I., Fungaro M. H. P., 2008. An Integrated Molecular Map of Yellow Passion Fruit Based on Simultaneous Maximum-Likehood Estimation of Linkage and Linkage Phases. J. Am. Soc. Hortic. Sci. 133: 35–41.

Pereira G. S., Nunes E. S., Laperuta L. D. C., Braga M. F., Penha H. a., Diniz A. L., Munhoz C. F., Gazaffi R., Garcia A. a. F., Vieira M. L. C., 2013. Molecular polymorphism and linkage analysis in sweet passion fruit, an outcrossing species. Ann. Appl. Biol. 162: 347–361.

Souza L. M., Gazaffi R., Mantello C. C., Silva C. C., Garcia D., Guen V. Le, Cardoso S. E. A., Garcia A. A. F., Souza A. P., 2013. QTL Mapping of Growth-Related Traits in a Full-Sib Family of Rubber Tree (Hevea brasiliensis) Evaluated in a Sub-Tropical Climate. PLoS One 8: e61238.

Quezada M., Pastina M. M., Ravest G., Silva P., Vignale B., Cabrera D., Hinrichsen P., Garcia A. A. F., Pritsch C., 2014. A first genetic map of Acca sellowiana based on ISSR, AFLP and SSR markers. Sci. Hortic. 169: 138–146.

Doerge, R.W. 1996. Constructing genetic maps by rapid chain delineation. Journal of Agricultural Genomics 2.

Buetow, K. H., Chakravarti, A. 1987. Multipoint gene mapping using seriation. I. General methods. American Journal of Human Genetics 41: 180-188.

Van Os H, Stam P, Visser R.G.F., Van Eck H.J. 2005. RECORD: a novel method for ordering loci on a genetic linkage map. Theor. Appl. Genet. 112: 30-40.

Tan, Y., Fu, Y. 2006. A novel method for estimating linkage maps. Genetics 173: 2383-2390.

Mollinari, M., Margarido, G. R. A., Vencovsky, R. and Garcia, A. A. F. 2009. Evaluation of algorithms used to order markers on genetics maps. Heredity 103: 494-502.