Gene Expression Datasets for Two Versions of the Saccharum spontaneum AP85-441 Genome

Nicolás López-Rozo, Mauricio Ramirez-Castrillon, Miguel Romero, Jorge Finke and Camilo Rocha ()
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Nicolás López-Rozo: Department of Electronics and Computer Science, Pontificia Universidad Javeriana, Cali 760031, Colombia
Mauricio Ramirez-Castrillon: OMICAS Program, Pontificia Universidad Javeriana, Cali 760031, Colombia
Miguel Romero: Department of Electronics and Computer Science, Pontificia Universidad Javeriana, Cali 760031, Colombia
Jorge Finke: Department of Electronics and Computer Science, Pontificia Universidad Javeriana, Cali 760031, Colombia
Camilo Rocha: Department of Electronics and Computer Science, Pontificia Universidad Javeriana, Cali 760031, Colombia

Data, 2022, vol. 8, issue 1, 1-9

Abstract: Sugarcane is a species of tall grass with high biomass and sucrose production, and the world’s largest crop by production quantity. Its evolutionary environment adaptation and anthropogenic breeding response have resulted in a complex autopolyploid genome. Few efforts have been reported in the literature to document this organism’s gene co-expression and annotation, and, when available, use different gene identifiers that cannot be easily associated across studies. This data descriptor paper presents a dataset that consolidates expression matrices of two Saccharum spontaneum AP85-441 genome versions and an algorithm implemented in Python to mechanically obtain this dataset. The data are processed from the allele-level information of the two sources, with BLASTn used bidirectionally to suggest feasible mappings between the two sets of alleles, and a graph-matching optimization algorithm to maximize global identity and uniqueness of genes. Association tables are used to consolidate the expression values from alleles to genes. The contributed expression matrices comprise 96 experiments and 109,050 and 35,516 from the two genome versions. They can represent significant computational cost reduction for further research on, e.g., sugarcane co-expression network generation, functional annotation prediction, and stress-specific gene identification.

Keywords: sugarcane; expression matrix; allele expression; graph flow (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2022
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