Pairagon: a highly accurate, HMM-based cDNA-to-genome aligner

Area of Science:

• Bioinformatics
• Genomics
• Computational Biology

Background:

• Accurate intron-exon structure determination is crucial for genome annotation.
• cDNA-to-genome alignment programs are essential components of annotation pipelines.
• Scoring systems significantly impact alignment accuracy but are less studied than heuristics.

Purpose of the Study:

• To introduce Pairagon, a novel pair hidden Markov model-based cDNA-to-genome alignment program.
• To evaluate Pairagon's accuracy compared to existing aligners across diverse sequence identities.
• To highlight the importance of scoring systems in alignment accuracy.

Main Methods:

• Development of Pairagon, a pair hidden Markov model-based alignment program.
• Simulation of cDNA sequences and mutation of reference genomes (fly, human) to test alignment accuracy.
• Cross-species alignment of orthologous transcripts (human, mouse, rat) to validate results with natural sequences.

Main Results:

• Pairagon demonstrates superior accuracy in cDNA-to-genome alignment, particularly at high and low sequence identities.
• At 100% identity, Pairagon achieved >99.6% accuracy with significantly fewer errors than other aligners.
• For human/mouse alignments (85% identity), Pairagon achieved 87% accuracy, outperforming all other tested aligners.

Conclusions:

• Pairagon is the most accurate cDNA-to-genome aligner available, offering significant improvements for gene annotation.
• Aligner performance is highly dependent on sequence identity, with Pairagon excelling in both high and low identity scenarios.
• The Pairagon software is freely available for research use.