Leveraging Knowledge of Traditional Italian Maize Landrace Diversity to Identify Signals of Local Adaptation

Climate change is the greatest challenge to modern agriculture. It significantly impacts agricultural systems through an increased frequency and intensity of extreme environmental events. Maize, a vital crop for global food security, is particularly vulnerable to these changes, highlighting the urgent need to develop resilient varieties. This study aims to identify significant genes for adaptation to environmental conditions in 140 individuals derived from 28 Italian maize landraces using a landscape genomics approach to support the development of resilient maize genotypes. Landraces were genotyped using genotyping-by-sequencing, and the resulting genetic matrix was used to characterize the collection's diversity. Population genetic studies were conducted to investigate the genetic diversity and structure of the collection. Partial redundancy analysis (pRDA) was subsequently employed to analyze the relationship between climate variables and genetic variation of the materials. Among the 12 ancestral populations identified, both well-defined populations and highly admixed groups were observed. This degree of admixture was reflected in the clustering analysis and principal component analysis (PCA), although clear differentiation of individual populations was still apparent. pRDA revealed that 30% of the genetic variance in the collection was explained together by climate (45%), geography (11%), and genetic structure (31%). Three potential genomic signals of adaptation were identified in relation to the environmental variability across the sampling sites. The results highlight significant intra-landrace variability within the examined germplasm and reveal unique landraces tied to ancestral lineages. Notably, we identify distinct genetic markers strongly correlated with environmental factors. This discovery opens new avenues for potential genetic improvement in maize cultivation. Landraces preserve vital traits for the adaptation of maize to environmental stresses, thereby serving as key sources for breeding programs aimed at improving stress tolerance and yield stability under climate change.

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Publication Details

Journal
Evolutionary Applications
Published
2026-02-01
DOI
https://doi.org/10.1111/eva.70186
Primary Topic
Genetic Mapping and Diversity in Plants and Animals
Type
article
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article

Leveraging Knowledge of Traditional Italian Maize Landrace Diversity to Identify Signals of Local Adaptation

Leonardo Caproni, D M Di Matteo, Alessandra Lezzi, Lorenzo Stagnati et al.
Evolutionary Applications
Genetic Mapping and Diversity in Plants and Animals
article

Leveraging Knowledge of Traditional Italian Maize Landrace Diversity to Identify Signals of Local Adaptation

Leonardo Caproni, D M Di Matteo, Alessandra Lezzi, Lorenzo Stagnati, Adriano Marocco, Alessandra Lanubile, Matteo Busconi
article en

Abstract

Climate change is the greatest challenge to modern agriculture. It significantly impacts agricultural systems through an increased frequency and intensity of extreme environmental events. Maize, a vital crop for global food security, is particularly vulnerable to these changes, highlighting the urgent need to develop resilient varieties. This study aims to identify significant genes for adaptation to environmental conditions in 140 individuals derived from 28 Italian maize landraces using a landscape genomics approach to support the development of resilient maize genotypes. Landraces were genotyped using genotyping-by-sequencing, and the resulting genetic matrix was used to characterize the collection's diversity. Population genetic studies were conducted to investigate the genetic diversity and structure of the collection. Partial redundancy analysis (pRDA) was subsequently employed to analyze the relationship between climate variables and genetic variation of the materials. Among the 12 ancestral populations identified, both well-defined populations and highly admixed groups were observed. This degree of admixture was reflected in the clustering analysis and principal component analysis (PCA), although clear differentiation of individual populations was still apparent. pRDA revealed that 30% of the genetic variance in the collection was explained together by climate (45%), geography (11%), and genetic structure (31%). Three potential genomic signals of adaptation were identified in relation to the environmental variability across the sampling sites. The results highlight significant intra-landrace variability within the examined germplasm and reveal unique landraces tied to ancestral lineages. Notably, we identify distinct genetic markers strongly correlated with environmental factors. This discovery opens new avenues for potential genetic improvement in maize cultivation. Landraces preserve vital traits for the adaptation of maize to environmental stresses, thereby serving as key sources for breeding programs aimed at improving stress tolerance and yield stability under climate change.

Evolutionary ApplicationsVol. 19(2)
Università Cattolica del Sacro Cuore (IT), Scuola Superiore Sant'Anna (IT)
Climate action
Openalex Percentile: Top 53%
Genetic Mapping and Diversity in Plants and Animals
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