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
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Identifier |
https://doi.org/10.7910/DVN/JWNYFA
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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 |
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Publisher |
Harvard Dataverse
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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). |
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Subject |
Agricultural Sciences
Earth and Environmental Sciences Cassava Americas Crops for Nutrition and Health CGIAR Genebank Platform |
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Language |
English
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Date |
2023-12-21
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Contributor |
Alliance Data Management
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Type |
Experimental Data
Genomic Data |
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