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Autor: Juan Burgueño
Significant SNPs from SeeD GWAS Analysis of Flowering Time
Jorge Alberto Romero Navarro Martha Willcox Juan Burgueño Cinta Romay Kelly Swarts Samuel Trachsel Iván Ortíz-Monasterios Felix San Vicente Garcia Gary Atlin Peter Wenzl Sarah Hearne Edward Buckler (2017)
The files included in this study provide significant SNPs from the gene-level analysis for days to anthesis, days to silking, altitude, and latitude within the SeeD GWAS panel. Markers shown are only those found outside high LD regions as defined in the paper: A study of allelic diversity underlying flowering-time adaptation in maize landraces. Nature Genetics. 2017: 49, 476–480. doi:10.1038/ng.3784, and included in the file: HighLD ranges.txt.
Dataset
Significant SNPs from SeeD GWAS Analysis of Flowering Time
Jorge Alberto Romero Navarro Martha Willcox Juan Burgueño Cinta Romay Kelly Swarts Samuel Trachsel Iván Ortíz-Monasterios Felix San Vicente Garcia Gary Atlin Peter Wenzl Sarah Hearne Edward Buckler (2017)
The files included in this study provide significant SNPs from the gene-level analysis for days to anthesis, days to silking, altitude, and latitude within the SeeD GWAS panel. Markers shown are only those found outside high LD regions as defined in the paper: A study of allelic diversity underlying flowering-time adaptation in maize landraces. Nature Genetics. 2017: 49, 476–480. doi:10.1038/ng.3784, and included in the file: HighLD ranges.txt.
Dataset
Replication Data for: Genomic Prediction of Gene Bank Wheat Landraces
Jose Crossa DIEGO JARQUIN Jorge Franco Paulino Pérez-Rodríguez Juan Burgueño Carolina Saint Pierre Prashant Vikram Carolina Sansaloni Cesar Petroli Deniz Akdemir Clay Sneller Matthew Paul Reynolds Thomas Payne Carlos Guzman Roberto Peña Peter Wenzl Sukhwinder Singh (2023)
Genomic prediction methods may be used to enhance efforts to rapidly introgress traits of interest from exotic germplasm into elite materials. This study examined the performance of different genomic prediction models using genotypic and phenotypic data related to 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in germplasm banks. The Mexican and Iranian collections were evaluated under optimal, drought, and heat conditions for several traits including the highly heritable traits, days to heading (DTH), and days to maturity (DTM). The results of the different analyses are reported in the accompanying journal article.
Dataset
Berhanu Tadesse Ertiro Yoseph Beyene Dan Makumbi Suresh L.M. Manje Gowda Anani Bruce Vijay Chaikam Fidelis Owino Walter Chivasa Aparna Das Nicholas J. Davis Pieter Rutsaert Juan Burgueño Prasanna Boddupalli (2023)
New and improved maize hybrids, developed by the CIMMYT Global Maize Program, are available for uptake by public and private sector partners, especially those interested in marketing or disseminating hybrid maize seed across Eastern Africa and similar agro-ecological zones. Following rigorous trialing and a stage-gate advancement process and culminating in the 2022 Eastern Africa Regional On-Farm Trials, CIMMYT has advanced a total of 6 new elite maize hybrids, each of which met the stringent performance criteria for CIMMYT’s eastern Africa early (EAPP1B), intermediate (EAPP1A) or late (EAPP2) maize breeding pipelines. Phenotypic data collected in Stage 4 and Stage 5 trials for the selected hybrids as well as information about the trial sites are provided in this dataset. These trials were conducted through a network of partners, including NARES and private seed companies, in Eastern Africa under various management and environmental conditions.
Dataset
Carolina Sansaloni Jorge Franco Bruno Santos Lawrence Percival-Alwyn Cesar Petroli Jaime Campos Kate Dreher Thomas Payne David Marshall Benjamin Kilian Iain Milne Sebastian Raubach Paul Shaw Gordon Stephen Carolina Saint Pierre Juan Burgueño Jose Crossa Huihui Li Andrzej Kilian Peter Wenzl Ahmed Amri Cristobal Uauy Marianne Bänziger Mario Caccamo Kevin Pixley (2020)
A diverse panel of domesticated hexaploid and tetraploid wheat lines and their tetraploid and diploid wild relatives were genotyped using the DArtSeq technology and characterized in a global wheat diversity analysis.
Dataset