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Dataset for transcriptome and physiological response of mature tomato seed tissues to light and heat during fruit ripening

Seed vigor is an estimate of how successfully a seed lot will establish seedlings under a wide range of environmental conditions, with both the embryo and the surrounding endosperm playing distinct roles in the germination behaviour. Germination and seedling establishment are essential for crop prod...

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Detalles Bibliográficos
Autores principales: Bizouerne, Elise, Ly Vu, Benoit, Ly Vu, Joseph, Verdier, Jerome, Buitink, Julia, Leprince, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773857/
https://www.ncbi.nlm.nih.gov/pubmed/33409343
http://dx.doi.org/10.1016/j.dib.2020.106671
Descripción
Sumario:Seed vigor is an estimate of how successfully a seed lot will establish seedlings under a wide range of environmental conditions, with both the embryo and the surrounding endosperm playing distinct roles in the germination behaviour. Germination and seedling establishment are essential for crop production to be both sustainable and profitable. Seed vigor traits are sequentially acquired during development via genetic programs that are poorly understood, but known to be under the strong influence of environmental conditions. To investigate how light and temperature have an impact on the molecular mechanisms governing seed vigor at harvest, RNA sequencing was performed on Solanum lycopersicum cv. Moneymaker seed tissues (i.e. embryo and endosperm) that were dissected from fruits that were submitted to standard or high temperature and/or standard or dim light. The dataset encompassed a total of 26.5 Gb raw data from mature embryo and endosperm tissues transcriptomes. The raw and mapped reads data on build SL4.0 and annotation ITAG4.0 are available under accession GSE158641 at NCBI Gene Expression Omnibus (GEO) database. Data on seed vigor characteristics are presented together with the differentially expressed gene transcripts. GO and Mapman annotations were generated on ITAG4.0 to analyse this dataset and are provided for datamining future datasets.