sgcocaller and comapr: personalised haplotype assembly and comparative crossover map analysis using single-gamete...

Area of Science:

• Genomics
• Computational Biology
• Reproductive Biology

Background:

• High-throughput single-cell sequencing enables large-scale gamete profiling for personalized haplotypes and meiotic crossover landscapes.
• Low coverage depth in high-throughput single-gamete data challenges existing haplotype phasing methods.
• Current methods for haplotyping and crossover profiling are computationally intensive.

Purpose of the Study:

• Introduce efficient software tools for personalized haplotype generation and meiotic crossover calling from single-gamete DNA sequencing data (sgcocaller).
• Develop tools for constructing, visualizing, and comparing individualized crossover landscapes from single gametes (comapr).
• Address computational challenges and low-coverage limitations in gamete-based genomic analysis.

Main Methods:

• Development of sgcocaller for haplotype phasing and crossover calling in gametes.
• Development of comapr for constructing and comparing crossover landscapes.
• Application of tools to single-gamete DNA sequencing data, with adaptability for bulk-sequenced samples via pre-processing.

Main Results:

• sgcocaller achieves accurate phasing on high-coverage datasets, outperforming existing methods in accuracy and stability.
• sgcocaller performs well on low-coverage single-gamete data where current methods fail.
• The developed tools offer user-friendly installation, comprehensive documentation, efficient computation, and minimal memory usage.

Conclusions:

• The introduced software tools provide efficient and accurate solutions for personalized haplotype and meiotic crossover landscape analysis.
• These tools overcome critical limitations of low-coverage data in high-throughput single-gamete sequencing.
• The software facilitates advanced genomic research in reproductive biology and personalized medicine.