Evidence map›Paper›PMID 42316312›Full record

ArticleGenome biology2026

Deciphering the mosaic genome of sugarcane cultivars through polyploid admixture inference with AdmixPoly.

Simon Rio, Franck Gauthier, Olivier Garsmeur, George Piperidis, Jean-Yves Hoarau, German Serino, Raul Castillo Torres, Shailesh Vinay Joshi, Yoshifumi Terajima, Jershon Lopez-Gerena and 8 more

Abstract read
In one paragraph

Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Simon RioCIRAD, UMR AGAP Institut, Montpellier, F-34398, France. simon.rio@cirad.fr.ORCID https://orcid.org/0000-0001-7014-8789
Franck GauthierUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, Gif-sur-Yvette, 91190, France.
Olivier GarsmeurCIRAD, UMR AGAP Institut, Montpellier, F-34398, France.
George PiperidisSugar Research Australia, Brisbane, QLD 4000, Australia.
Jean-Yves HoarauUMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, F-34398, France.
German SerinoChacra Experimental Agrícola Santa Rosa, Camino Vecinal No. 8 Km 6, Colonia Santa Rosa, 4531, Argentina.
Raul Castillo TorresCentro de Investigación de la Caña de Azúcar del Ecuador - CINCAE, Guayaquil, Ecuador.
Shailesh Vinay JoshiSouth African Sugarcane Research Institute, Private Bag X02, Mount Edgecombe, 4300, Durban, KwaZulu-Natal, South Africa.
Yoshifumi TerajimaTropical Agriculture Research Front, JIRCAS, 1091-1 Maezato-Kawarabaru, Ishigaki, 907-0002, Japan.
Jershon Lopez-GerenaCentro de Investigación de la Caña de Azúcar de Colombia (CENICAÑA), Cali, Colombia.
María Francisca PereraInstituto de Tecnología Agroindustrial del Noroeste Argentino (ITANOA), Estación Experimental Agroindustrial Obispo Colombres (EEAOC) - Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Las Talitas, Argentina.
Andrew StouteWest Indies Central Sugar Cane Breeding Station, Groves, St. George, Barbados.
Goolam BadalooMauritius Sugarcane Industry Research Institute, Mauritius Cane Industry Authority, 1 Moka Road, Réduit, Mauritius.
Dongliang HuangSugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, China.
Kerrie BarryDOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, 94720, CA, USA.
Jeremy SchmutzDOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, 94720, CA, USA.
Tristan Mary-Huard *Université Paris-Saclay, INRAE, CNRS, AgroParisTech, UMR GQE-Le Moulon, Gif-sur-Yvette, 91190, France.
Angélique D'Hont *CIRAD, UMR AGAP Institut, Montpellier, F-34398, France.

Funding

International Consortium for Sugarcane Biotechnology ICSB37U.S. Department of Energy Joint Genome Institute 10.46936/10.25585/60001194
6 · The paper itself

Abstract

backgroundCharacterizing population structure and admixture events between ancestral groups plays a key role in understanding the evolutionary history of species and crops. Most tools for inferring admixture have been developed for diploids and are not suitable for polyploids, in particular those with high and mixed ploidy such as Saccharum.

resultsHere we present AdmixPoly, an R-package designed to infer admixture in polyploid species both at the genome-wide scale and locally along chromosomes. We compare AdmixPoly with state-of-the-art methods using simulations, demonstrating its precision and computational efficiency. Notably, local admixture inference in complex scenarios, such as high ploidy levels, large numbers of ancestral groups and alleles per marker is enabled through efficient approximations of emission and transition probabilities within a hidden Markov model framework. We apply this approach to characterize the contributions of wild Saccharum species to the complex polyploid genome of modern sugarcane cultivars. A panel of wild and cultivated Saccharum accessions is genotyped for 80K genomic regions, each revealing approximately 50 read-scale haplotypes.

conclusionsThe results reveal that most of the approximately 12 copies of each basic chromosome in modern cultivars are derived from the domesticated species Saccharum officinarum, with one to four copies typically contributed by distinct subgroups of the wild species Saccharum spontaneum. In addition, contributions from an unknown wild Saccharum group originating from the Pacific were identified in most cultivars. The conserved pattern of these introgressions suggests that they can be traced back to the early stages of sugarcane breeding approximately a century ago.

Indexed as

Genome, PlantPolyploidySaccharumChromosomes, PlantHaplotypesAdmixtureCrop evolutionPolyploidyPopulation structureSaccharum sppSugarcane

Identifiers

PMID42316312
PMCPMC13531838

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.