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Related Experiment Video

Updated: May 21, 2026

Non-destructive SPE-UPLC-based Quantification of Aflatoxins and Stilbenoid Phytoalexins in Single Peanut (Arachis spp.) Seeds

Non-destructive SPE-UPLC-based Quantification of Aflatoxins and Stilbenoid Phytoalexins in Single Peanut (Arachis spp.) Seeds

Published on: April 19, 2024

PeanutDB: an integrated bioinformatics web portal for Arachis hypogaea transcriptomics.

Xiaohong Duan¹, Emily Schmidt, Pei Li

¹State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China.

BMC Plant Biology

|June 21, 2012

Summary

PeanutDB is a new database integrating peanut transcriptome data to aid researchers. This resource facilitates genomics and breeding for this important, yet understudied, crop.

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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

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Non-destructive SPE-UPLC-based Quantification of Aflatoxins and Stilbenoid Phytoalexins in Single Peanut (Arachis spp.) Seeds

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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Published on: June 17, 2012

Area of Science:

Genomics
Bioinformatics
Plant Science

Background:

Peanut (Arachis hypogaea) is a globally important crop for food and oil.
Its complex, tetraploid genome (AABB, 2n=40) poses challenges for sequencing.
Limited genomic resources make transcriptome sequencing crucial for understanding gene expression.

Purpose of the Study:

To develop a comprehensive, publicly accessible database for peanut transcriptome data.
To facilitate genomics research and molecular breeding in peanut.
To provide integrated tools for analyzing peanut genetic information.

Main Methods:

Integrated large-scale transcriptomic datasets from Sanger, Roche 454, and Illumina sequencing.
Generated a de novo peanut transcriptome assembly of 32,619 contigs.
Performed functional annotation (EC, KEGG, GO) and identified genetic polymorphisms (SSRs, SNPs).

Main Results:

Developed PeanutDB, a web portal for accessing and visualizing peanut transcriptome assembly and annotations.
Included tools for searching, filtering, and navigating assembled transcripts.
Highlighted sequence alignments with detailed views of polymorphisms and repeats.

Conclusions:

PeanutDB serves as a vital public resource for the peanut research community.
The database simplifies access to integrated genomic data for this understudied crop.
Facilitates advancements in peanut genomics research and accelerates molecular breeding efforts.