Artículo
Geographical patterns of genetic variation in locoto chile (Capsicum pubescens) in the Americas inferred by genome-wide data analysis
Fecha de publicación:
29/10/2022
Editorial:
MDPI
Revista:
Plants
e-ISSN:
2223-7747
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The locoto chile (Capsicum pubescens) is a regionally important food crop grown and marketed throughout the mid-highlands of South andCentral America, but little is known about its evolution and the diversity it harbours. An initial scan of genetic diversity and structure across its cultivation range was conducted, the first one using a genomic approach. The RAD-sequencing methodology was applied to a sampling of C. pubescens germplasm consisting of 67 accessions from different American countries, covering its range of distribution/cultivation on the continent. The RAD-seq SNP data obtained clustered the accessions into three major groups, with a high degree of admixture/reticulation among them. Moderate but significant differentiation and geographic structuration were found, depicting a south–north pattern in the distribution of genetic variation. The highest levels of diversity were found among central-western Bolivian individuals, while the lowest was found across Central America-Mexican germplasm. This study provides new genome-wide supported insights into the diversity and differentiation of C. pubescens, as well as a starting point for more efficient use of its genetic variation and germplasm conservation efforts. The findings also contribute to understanding the evolutionary history of C. pubescens, but further investigation is needed to disentangle its origin and diversification under domestication.
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Articulos(IMBIV)
Articulos de INST.MULTIDISCIPL.DE BIOLOGIA VEGETAL (P)
Articulos de INST.MULTIDISCIPL.DE BIOLOGIA VEGETAL (P)
Citación
Palombo, Nahuel Ezequiel; Carrizo Garcia, Carolina; Geographical patterns of genetic variation in locoto chile (Capsicum pubescens) in the Americas inferred by genome-wide data analysis; MDPI; Plants; 11; 21; 29-10-2022; 1-16
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