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Related Experiment Video

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Ultra-long Read Sequencing for Whole Genomic DNA Analysis

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Hardness of Covering Alignment: Phase Transition in Post-Sequence Genomics.

Romeo Rizzi, Massimo Cairo, Veli Makinen

IEEE/ACM Transactions on Computational Biology and Bioinformatics

|July 12, 2018

Summary

Extending sequence alignment to pan-genome graphs and diploid genomes presents new computational challenges. Finding covering alignments for labeled directed acyclic graphs (DAGs) is NP-hard, impacting genomic sequence analysis.

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Area of Science:

Computational Biology
Genomics
Bioinformatics

Background:

Genomic analysis is shifting from reference genomes to pan-genome graphs.
Haplotyping advances allow for the use of complete diploid genome content in sequence analysis.
Traditional sequence alignment methods face challenges with these new genomic representations.

Purpose of the Study:

To investigate the computational complexity of sequence alignment extensions for pan-genome graphs and diploid genomes.
To analyze the complexity of covering alignments on labeled directed acyclic graphs (DAGs).
To model the similarity of two diploids over arbitrary recombinations using covering alignments.

Main Methods:

Formulating sequence alignment as a covering alignment problem on labeled DAGs.
Proving the NP-hardness of finding covering alignments for two labeled DAGs, even on binary alphabets.
Reducing diploid genome alignment to a two-path coverable labeled DAG problem.

Main Results:

Finding a covering alignment of two labeled DAGs is NP-hard.
The problem remains NP-hard even for binary alphabets.
Recombination-oblivious diploid alignment is NP-hard on alphabets of size 3.

Conclusions:

Extending sequence alignment to pan-genome graphs and diploid genomes significantly increases computational complexity.
The covering alignment framework provides a model for analyzing diploid genome similarity under recombination.
New algorithmic approaches are needed to address these NP-hard problems in genomics.