Evidence map›Paper›PMID 42698130›Full record

ArticleThe New phytologist2026

The MexMAGIC population reveals the genetic architecture of traits exhibiting clinal variation in Mexican native maize.

Sergio Perez-Limón, Ana Laura Alonso-Nieves, M Rosario Ramírez-Flores, G Carolina Cintora-Martínez, M Nancy Salazar-Vidal, Jorge Vladimir Torres-Rodriguez, Jessica Carcaño-Macías, Melanie G Perryman, Oliver H S Paulson, Jagdeep S Sidhu and 9 more

Abstract read
In one paragraph

Article in The New phytologist, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

19 authors.

Sergio Perez-LimónDepartment of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA.ORCID https://orcid.org/0000-0002-1893-4325
Ana Laura Alonso-NievesUnidad de Genómica Avanzada, Cinvestav, Irapuato, Guanajuato, 36824, México.ORCID https://orcid.org/0000-0001-7312-4897
M Rosario Ramírez-FloresDepartamento de Biotecnología y Bioquímica, Centro de Investigación y de Estudios Avanzados (CINVESTAV-IPN), Irapuato, Guanajuato, 36821, México.ORCID https://orcid.org/0000-0003-2561-0086
G Carolina Cintora-MartínezUnidad de Genómica Avanzada, Cinvestav, Irapuato, Guanajuato, 36824, México.ORCID https://orcid.org/0000-0002-7646-5977
M Nancy Salazar-VidalUnidad de Genómica Avanzada, Cinvestav, Irapuato, Guanajuato, 36824, México.ORCID https://orcid.org/0000-0003-4894-9795
Jorge Vladimir Torres-RodriguezUnidad de Genómica Avanzada, Cinvestav, Irapuato, Guanajuato, 36824, México.ORCID https://orcid.org/0000-0001-6056-3452
Jessica Carcaño-MacíasUnidad de Genómica Avanzada, Cinvestav, Irapuato, Guanajuato, 36824, México.ORCID https://orcid.org/0000-0002-4950-0642
Melanie G PerrymanDepartment of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA.ORCID https://orcid.org/0009-0008-1046-0453
Oliver H S PaulsonDepartment of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA.
Jagdeep S SidhuDepartment of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA.ORCID https://orcid.org/0000-0002-4672-3701
Peng YuDepartment of Plant Genetics, TUM School of Life Sciences, Technical University of Munich, Freising, 85354, Germany.ORCID https://orcid.org/0000-0003-1670-8428
Victor LlacaGenome Center of Excellence, Corteva Agriscience, Johnston, 50131, IA, USA.ORCID https://orcid.org/0000-0003-4822-2924
Kevin A FenglerGenome Center of Excellence, Corteva Agriscience, Johnston, 50131, IA, USA.ORCID https://orcid.org/0000-0003-0010-2093
Forrest LiDepartment of Evolution and Ecology, University of California, Davis, CA, 95616, USA.ORCID https://orcid.org/0000-0003-2965-2494
Daniel E RuncieDepartment of Evolution and Ecology, University of California, Davis, CA, 95616, USA.ORCID https://orcid.org/0000-0002-3008-9312
Jeffrey Ross-IbarraDepartment of Evolution and Ecology, University of California, Davis, CA, 95616, USA.ORCID https://orcid.org/0000-0003-1656-4954
C Stewart GillmorUnidad de Genómica Avanzada, Cinvestav, Irapuato, Guanajuato, 36824, México.ORCID https://orcid.org/0000-0003-1009-2167
Rubén Rellán-ÁlvarezDepartment of Molecular and Structural Biochemistry, N.C. Plant Sciences Initiative, North Carolina State University, Raleigh, NC, 27695, USA.ORCID https://orcid.org/0000-0001-6843-3716
Ruairidh J H SawersDepartment of Plant Science, The Pennsylvania State University, University Park, PA, 16802, USA.ORCID https://orcid.org/0000-0002-8945-3078

Funding

Agricultural Research Service 7008935Agricultural Research Service PEN05039Division of Integrative Organismal Systems 1546719Secretaría de Ciencia, Humanidades, Tecnología e Innovación CB-2015-01 254012Secretaría de Ciencia, Humanidades, Tecnología e Innovación FOINS-2016-01
6 · The paper itself

Abstract

Defining the genetic basis of local adaptation is a key goal of evolutionary biology and crop improvement. Theory predicts that when selective pressures follow differences in the environment, a cline will be established. Clines can be exploited to uncover adaptive variation by association of alleles with the environment. However, monotonic phenotypic change over a cline is not necessarily mirrored in the behavior of genetic variants and population structure can further complicate analysis. To study genetic and phenotypic variation across the environment, we developed a multi-parent advanced generation inter-cross (MAGIC) population using eight Mexican native maize (Zea mays L. ssp. mays) varieties sourced from distinct agroecological zones. We evaluated the population in a common garden in Mexico and mapped tassel branching and flowering time, two traits that exhibit clinal variation. Variation in tassel branching was dominated by a single QTL with allele effects aligning to a negative elevational cline. By contrast, allele effects associated with 11 identified flowering time QTL were not consistently correlated with any one source environmental factor. Our observations support the prediction that genotype-environment association will be strongest under simple genetic architecture, although, even then, analysis in native populations may be confounded by population structure.

Indexed as

Genetic VariationQuantitative Trait, HeritableZea maysAllelesChromosome MappingCrosses, GeneticFlowersGene-Environment InteractionGenetics, PopulationGenotypeMexicoPhenotypeQuantitative Trait Lociclineflowering timegenetic architectureMAGICMexican maizetassel branch number

Identifiers

PMID42698130
PMCPMC13628542

What OpenQuestion holds

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Registered trials

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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.