The Effect of Human Genome Annotation Complexity on RNA-Seq Gene Expression Quantification

Area of Science:

• Genomics
• Transcriptomics
• Bioinformatics

Background:

• Next-generation sequencing (NGS) revolutionized human genomic research.
• RNA-Seq quantifies gene expression, relying on accurate human genome annotation.
• Existing genome annotations vary in complexity, creating uncertainty.

Purpose of the Study:

• To evaluate the influence of different human genome annotations on RNA-Seq gene expression quantification.
• To assess the impact on mapping quality, quantification variation, and accuracy.

Main Methods:

• Compared multiple human genome annotations for RNA-Seq analysis.
• Assessed mapping quality and quantification variation.
• Validated quantification accuracy using quantitative reverse transcription PCR (qRT-PCR) data.
• Evaluated concordance in detecting differentially expressed genes.

Main Results:

• Different genome annotations led to variations in mapping quality and gene expression quantification.
• External validation with qRT-PCR indicated that more complex genome annotations correlate with higher quantification variation.
• The choice of annotation influenced the detection of differentially expressed genes.

Conclusions:

• Genome annotation is a critical factor influencing RNA-Seq-based gene expression studies.
• Researchers must carefully consider the chosen genome annotation for accurate and reproducible RNA-Seq results.
• Further investigation into annotation-specific biases is warranted.