Abstract
The Chinese chestnut (Castanea mollissima) stands out as a plant with significant ecological and economic value, excellent nutritional quality and natural resistance to pests and diseases. Recent strides in high-throughput techniques have enabled the continuous accumulation of genomic data on chestnuts, presenting a promising future for genetic research and advancing traits in this species. To facilitate the accessibility and utility of this data, we have curated and analyzed a collection of genomic datasets for eight Castanea species, including functional annotations, 213 RNA-Seq samples, and 330 resequencing samples. These datasets are publicly available on Figshare and are also available through other platforms such as GEO and EVA, providing a valuable resource for researchers studying Castanea genetics, functional genomics, and evolutionary biology. Furthermore, the datasets are integrated into the Castanea Genome Database (CGD, http://castaneadb.net ), which serves as a complementary platform, offering advanced data mining and analysis tools, including BLAST, Batch Query, GO/KEGG Enrichment Analysis, and Synteny Viewer, to enhance the usability of the curated datasets.
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Claims 2
Claim · model-written summary
Curated genomic data for eight Castanea species include RNA sequencing and resequencing samples.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Verbatim
e0“curated and analyzed a collection of genomic datasets for eight Castanea species, including functional annotations, 213 RNA-Seq samples, and 330 resequencing samples”
Claim · model-written summary
The datasets are integrated into the Castanea Genome Database with analysis tools.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Verbatim
e0“datasets are integrated into the Castanea Genome Database (CGD, http://castaneadb.net ), which serves as a complementary platform, offering advanced data mining and analysis tools, including BLAST, Batch Query, GO/KEGG Enrichment Analysis, and Synteny Viewer”