qTeller

qTeller enables comparative analysis of gene-level expression from RNA-Seq data across multiple genomes and experimental conditions to support transcriptome-level and cross-genome expression studies.

Key Features:

• Comparative analysis across multiple genomes: Performs intergenomic gene expression comparisons within defined genomic intervals across multiple genomes and conditions using RNA-Seq data.
• Two-gene comparisons: Produces pairwise comparisons of expression levels between two genes across selected tissues or conditions.
• Support for mRNA and protein abundance: Integrates mRNA expression and protein abundance datasets alongside RNA-Seq data for multi-level expression analysis.
• Integration with public RNA-Seq datasets: Incorporates public RNA-Seq datasets to enable cross-study comparative analyses and meta-analysis.
• GenBank dataset mapping: Maps and integrates datasets from GenBank, including over 200 unique datasets covering 27 maize genomes.
• Optimized database framework: Uses an optimized back-end database framework for storage and querying of multi-genome expression data.

Scientific Applications:

• Comparative genomics: Identifies and compares gene expression patterns across species or genomes.
• Transcriptome analysis: Supports transcriptome-level differential expression analyses across tissues, conditions, or genotypes using RNA-Seq.
• Meta-analysis: Facilitates aggregation and comparative analysis of expression datasets from public RNA-Seq and GenBank sources.
• Plant genetics: Applies to plant genetics studies, including multi-genome analyses in maize.
• Evolutionary biology: Enables evolutionary and cross-species expression studies by comparing orthologous or homologous genomic intervals.
• Systems biology: Integrates transcriptomic, mRNA, and protein abundance data to support systems-level investigations of gene regulation.

Methodology:

Performs gene-level comparative analyses of RNA-Seq-derived expression across defined genomic intervals and conditions, supports pairwise gene comparisons, and integrates mRNA, protein abundance, public RNA-Seq and GenBank datasets into an optimized database.