Minimap2: pairwise alignment for nucleotide sequences.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Sequencing technologies now produce ultra-long reads (∼100 kb mRNA/cDNA, 100 Mb genomic contigs).
• Existing alignment programs struggle to efficiently process these large-scale sequencing datasets.

Purpose of the Study:

• To develop a novel, general-purpose alignment program optimized for ultra-long sequencing reads.
• To address the limitations of current alignment tools in handling high-throughput, long-read data.

Main Methods:

• Minimap2 is a versatile alignment program for DNA and long mRNA sequences.
• It supports accurate mapping of short reads (≥100 bp), long genomic reads (≥1 kb, ~15% error rate), full-length noisy RNA/cDNA reads, and large genomic contigs/chromosomes.
• The algorithm incorporates split-read alignment, concave gap costs for indels, and novel heuristics to minimize spurious alignments.

Main Results:

• Minimap2 achieves 3-4x speed improvement over short-read mappers with comparable accuracy.
• It is ≥30x faster than existing long-read mappers, offering higher accuracy.
• The tool surpasses specialized aligners in performance across various alignment tasks.

Conclusions:

• Minimap2 provides a highly efficient and accurate solution for aligning ultra-long sequencing reads.
• It represents a significant advancement in bioinformatics tools for large-scale genomic and transcriptomic data analysis.
• The program's versatility and performance make it suitable for diverse applications involving long-read sequencing data.