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Identifying genetically redundant accessions in the world’s largest cassava collection

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Identifying genetically redundant accessions in the world’s largest cassava collection
 
Identifier https://doi.org/10.7910/DVN/JWNYFA
 
Creator Carvajal-Yepes, Monica
Ospina Colorado, Jessica Alejandra
Aranzales Rondon, Ericson
Velez Tobon, Monica Lorena
Correa Abondano, Miguel Angel
Barbosa Torres, Norma Constanza
Wenzl, Peter
 
Publisher Harvard Dataverse
 
Description A diverse panel of cultivated cassava landraces and improved lines were genotyped using DArTSeq Technology to identify genetic redundancy within the genebank collection.

Metodology:Leaf samples were collected from in vitro plants for DNA extraction. The extracted DNA samples were subsequently sent to DArT P/L and genotyped using the DArTseq platform and sequencing, resulting in approximately 2.5 million reads per sample. Libraries were generated using the PstI and MseI restriction enzymes. To call SNPs and SilicoDArT genomic variants, the DS14 software was implemented. Genomic variants were reported in .csv files. SilicoDArT Format: SilicoDArTs are scored in a binary fashion, representing genetically 'dominant' markers, with '1' indicating the presence and '0' indicating the absence of a restriction fragment with the marker sequence in the genomic representation of the sample. 'NA' is used for missing data. SNP Format: '0' represents a reference allele homozygote, '2' represents an SNP allele homozygote, '1' represents a heterozygote, and 'NA' represents a double null/null allele homozygote (absence of a fragment with SNP in the genomic representation).
 
Subject Agricultural Sciences
Earth and Environmental Sciences
Cassava
Americas
Crops for Nutrition and Health
CGIAR Genebank Platform
 
Language English
 
Date 2023-12-21
 
Contributor Alliance Data Management
 
Type Experimental Data
Genomic Data