Affiliation:
1. Instituto Nacional de Investigación Agropecuaria (INIA) Estación Experimental Las Brujas Ruta 48 km 10 Rincón del Colorado Canelones 90200 Uruguay
2. Department of Statistics College of Agriculture | Universidad de la República Garzón 780 Montevideo Montevideo 12900 Uruguay
3. Instituto Nacional de Investigación Agropecuaria (INIA) Estación Experimental INIA Treinta y Tres Ruta 8 km 281 Treinta y Tres Treinta y Tres 33000 Uruguay
4. Instituto Nacional de Investigación Agropecuaria (INIA) Estación Experimental Tacuarembó Ruta 5 km 386 Tacuarembó Tacuarembó 45000 Uruguay
Abstract
AbstractBreeding programs generate vast amount of data which are often scattered in separate files. This hinders the application of modern breeding tools such as multi‐environment analyses and genomic selection. This research work describes the process of consolidating 23 years of phenotypic, pedigree, and genomic records from the Uruguayan national rice (Oryza sativa L.) breeding program, and the features and structure of the resulting database. Using a custom‐made R code, we gathered all the available data from 1997 to 2020 corresponding to field trials, blast disease evaluation nurseries, laboratory analyses of milling and cooking quality, pedigree information, and genomic information for selected advanced breeding lines, and organized it into a relational database. Records of 996 trials in 12 locations over a span of 23 years, 91,636 field plots with information on 14 phenotypic variables, pedigree for 19,447 genotypes, and genomic information regarding 61,260 single nucleotide polymorphism (SNP) markers for 965 genotypes were recovered. The dataset is structured in trials, phenotypes, lines, genomic information, and SNP tables in an easy‐to‐access relational database, which will be a valuable resource for rice breeding.
Funder
Instituto Nacional de Investigación Agropecuaria
Agencia Nacional de Investigación e Innovación
Subject
Agronomy and Crop Science
Reference68 articles.
1. Aguilar I. Misztal I. Tsututa S. Legarra A. &Wang H.(2014).PREGSF90–POSTGSF90: Computational tools for the implementation of single‐step genomic selection and genome‐wide association with ungenotyped individuals in BLUPF90 programs.Proceedings of the World Congress on Genetics Applied to Livestock Production Canada.
2. Combining Partially Overlapping Multi-Omics Data in Databases Using Relationship Matrices
3. Fitting Linear Mixed-Effects Models Usinglme4
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献