The quantitative impact of read mapping to non-native reference genomes in comparative RNA-Seq studies

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Sequence read alignment to a reference genome is critical for genomics studies.
• Using a common reference genome for multiple bacterial strains is a frequent practice for ease of comparison.
• The accuracy of reference genome choice impacts the interpretation of biological data, especially in differential expression analysis.

Purpose of the Study:

• To investigate the impact of using a common reference genome in multi-strain transcriptomic analysis.
• To identify regions affected by non-native alignments that cause false positives in differential expression.
• To determine the extent of expression loss due to reference choice and simulate data for best practices.

Main Methods:

• Analysis of two multi-strain transcriptomic datasets with closed genomic sequences for all strains.
• Development of a method to identify regions susceptible to false positives from non-native alignments.
• Data simulation to evaluate best practices for using non-native references.

Main Results:

• Non-native alignments can introduce false positives in differential expression analysis.
• Significant expression loss can occur when using an inappropriate common reference genome.
• Identification of specific genomic regions most affected by reference choice.

Conclusions:

• The choice of reference genome significantly impacts the accuracy of transcriptomic analysis in multi-strain bacterial studies.
• A common reference genome approach can lead to erroneous conclusions in differential expression.
• Best practices are needed to mitigate biases and ensure reliable results in comparative genomics.