Nonparametric approaches for population structure analysis using CIPs wild potato germplasm collection

• Autor: Ortiz Ruiz, Tamara Fátima
• Formato: tesis de grado
• Fecha de Publicación: 2023
• Institución: Universidad de Ingeniería y tecnología
• Repositorio: UTEC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.utec.edu.pe:20.500.12815/370
• Enlace del recurso: https://hdl.handle.net/20.500.12815/370
• Nivel de acceso: acceso abierto
• Materia: Diversidad genética - Papa; Análisis estadísticos; Datos estadísticos; Genetic diversity - Potato; Statistical analysis; Statistical data; https://purl.org/pe-repo/ocde/ford#2.11.00

Wild potato species hold important genes related to disease resistance, tolerance to abiotic stress, and other traits of agronomic interest; however, they remain being the least explored. This study aimed to develop an accessible and replicable R analysis workflow to explore the genetic diversity and population structure of the International Potato Center’s (CIP) wild potato germplasm collection through nonparametric approaches. We worked with single nucleotide polymorphism (SNP) data from 1248 wild potato accessions, most of which had been genotyped for the first time. Genetic diversity parameters were calculated prior to structure analysis. Population structure was analyzed through parametric methods such as variational Bayesian inference, and nonparametric methods, such as dimensionalityreduction and distance-based techniques. Distance-based analysis revealed clustering based on ploidy level, taxonomic clade, and region of origin. Population structure results from different methods revealed significant gene flow between subpopulations, and confirmed similarities in the genetic makeup of individuals from similar geographical regions and with associated taxonomic characteristics. The analysis was programmed such that it can be replicated and scaled according to the researcher’s requirements. Nonparametric methods produced comparable results to those produced through parametric methods, requiring a lower computational cost, and establishing themselves as a practical alternative for population genetics studies. The results of this study provide new insights into the diversity and population architecture of CIPs wild potato collection, allowing researchers to understand the inter and intraspecific genetic relationships between species and broaden the genetic base of potato germplasm. The produced R analysis workflow will allow other crop population genetics studies using SNP data to be carried out in a quicker and more efficient manner, promoting their use in genetic improvement programs.