Comprehensive expression data for two honey bee species, Apis mellifera and Apis cerana japonica

Comprehensive expression datasets were constructed for Apis mellifera and Apis cerana japonica. Firstly, we obtained RNA-Seq data of the samples prepared: post-oviposition day 6 to day 58 samples of A. mellifera workers (larva to adult), and day 9, 10, 12, and 13 samples of A. mellifera queen (larva to pupa), and day 9 to day 18 samples of A. cerana japonica workers (larva to adult). For A. cerana japonica, reference transcript sequence, predicted amino acid sequence, and functional annotation data were generated based on the genome sequence and RNA-Seq data. Using the transcript sequence and RNA-Seq data, comprehensive expression data for all transcripts of A. mellifera and A. cerana japonica were prepared. Hierarchical clustering analyses, the used sample preparation method, and other evaluation results ensured that both sets of expression data were reliable for use as comprehensive reference expression datasets. Therefore, these data can be used for honey bee research or comparative or evolutionary studies on insect species or social insect species at the genetic and molecular levels.

Authors

Institutions

Publication Details

Journal
Scientific Data
Published
2025-06-02
DOI
https://doi.org/10.1038/s41597-025-05279-z
Citations
1
Primary Topic
Insect and Arachnid Ecology and Behavior
Type
article
Field-Weighted Citation Impact
1.82

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comprehensive expression data for two honey bee species, Apis mellifera and Apis cerana japonica

Kakeru Yokoi, Masatsugu Hatakeyama, Taro Maeda, Mikio Yoshiyama et al.
1 citations
Scientific Data
Insect and Arachnid Ecology and Behavior
1.82
article

Comprehensive expression data for two honey bee species, Apis mellifera and Apis cerana japonica

Kakeru Yokoi, Masatsugu Hatakeyama, Taro Maeda, Mikio Yoshiyama, Hidemasa U. Bono, Shigeru Matsuyama, Akiya Jouraku, Mari Horigane-Ogihara, Kiyoshi Kimura, Seigo Kuwazaki
article en
1 citations

Abstract

Comprehensive expression datasets were constructed for Apis mellifera and Apis cerana japonica. Firstly, we obtained RNA-Seq data of the samples prepared: post-oviposition day 6 to day 58 samples of A. mellifera workers (larva to adult), and day 9, 10, 12, and 13 samples of A. mellifera queen (larva to pupa), and day 9 to day 18 samples of A. cerana japonica workers (larva to adult). For A. cerana japonica, reference transcript sequence, predicted amino acid sequence, and functional annotation data were generated based on the genome sequence and RNA-Seq data. Using the transcript sequence and RNA-Seq data, comprehensive expression data for all transcripts of A. mellifera and A. cerana japonica were prepared. Hierarchical clustering analyses, the used sample preparation method, and other evaluation results ensured that both sets of expression data were reliable for use as comprehensive reference expression datasets. Therefore, these data can be used for honey bee research or comparative or evolutionary studies on insect species or social insect species at the genetic and molecular levels.

Scientific DataVol. 12(1)
Hiroshima University (JP), National Agriculture and Food Research Organization (JP), University of Tsukuba (JP), Institute of Agrobiological Sciences (JP), Institute of Livestock and Grassland Science (JP), National Institute for Agro-Environmental Sciences (JP), PhoenixBio (Japan) (JP)
Japan Science and Technology Agency, Co-creation place formation support program
Life in Land
Openalex Percentile: Top 15%
Insect and Arachnid Ecology and Behavior
1.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.