Araport

Araport provides integrated genomic annotations and RNA-Seq–based expression resources for Arabidopsis thaliana to support analysis of gene models, non-coding RNAs, orthology, interaction networks, and transcriptomic regulation.

Key Features:

• Comprehensive annotation: Updated annotation of the Arabidopsis thaliana genome including protein-coding genes and non-coding RNA classes such as microRNA, long intergenic RNA, small nucleolar RNA, natural antisense transcripts, small nuclear RNA, and small RNA derived from an integrative annotation pipeline using tissue-specific RNA-Seq libraries constructed from 113 datasets.
• Novel gene and transcript discoveries: Identification of 635 novel protein-coding genes, 508 new transcribed regions, 5,178 non-coding RNAs, and 35,846 small RNA loci, improving resolution of gene structures, untranslated regions, and splicing activities.
• Expression profiles and splicing events: RNA-Seq–based expression profiles and splicing event data across eleven tissues to characterize tissue-specific transcriptomics.
• Housekeeping genes: A curated set of 692 uniformly expressed housekeeping genes, with 43% of their human orthologs also annotated as housekeeping genes.
• Orthology and interaction networks: Inclusion of orthology data and interaction networks to support comparative genomics and network analyses.

Scientific Applications:

• Functional genomics: Elucidation of gene and non-coding RNA functions in Arabidopsis thaliana using detailed gene models and expression data.
• Comparative genomics: Comparative analyses between Arabidopsis and other species using orthology data.
• Transcriptomics: Analysis of transcript dynamics and splicing using RNA-Seq–based expression profiles across tissues.
• Gene regulation studies: Investigation of splicing events and untranslated regions to study molecular mechanisms of gene regulation.

Methodology:

Annotations were generated by an integrative annotation pipeline that assembled tissue-specific RNA-Seq libraries from 113 datasets, constructed transcript models, and annotated protein-coding genes and diverse classes of non-coding RNAs using published datasets and proprietary analytic results.