QTLseqr: An R Package for Bulk Segregant Analysis with Next-Generation Sequencing.

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Next-Generation Sequencing Bulk Segregant Analysis (NGS-BSA) is a powerful technique for identifying quantitative trait loci (QTL).
• The R statistical platform is widely used in genetic research, but lacks a dedicated package for NGS-BSA.
• Existing methods for QTL detection can be computationally intensive or lack specific statistical rigor.

Purpose of the Study:

• To introduce QTLseqr, a novel R package designed to facilitate NGS-BSA.
• To provide two robust statistical approaches, QTL-seq and G', for QTL identification and significance assessment within the R environment.
• To offer a user-friendly tool for importing, filtering, and analyzing SNP data for QTL mapping.

Main Methods:

• Development of the QTLseqr R package, integrating simulation-based (QTL-seq) and statistic-based (G') methods.
• Implementation of functions for SNP data import, quality filtering, and distribution analysis.
• Calculation of relative allele frequencies, G' statistics, and log (-values) for QTL detection and visualization.

Main Results:

• QTLseqr successfully implements two distinct statistical approaches for QTL detection in NGS-BSA data.
• The package provides comprehensive tools for data processing, including SNP filtering and frequency calculations.
• QTLseqr enables the identification and plotting of significant quantitative trait loci, streamlining genetic analysis.

Conclusions:

• QTLseqr addresses the need for a dedicated R package for NGS-BSA, enhancing accessibility and efficiency.
• The package offers reliable methods for QTL identification and statistical validation.
• QTLseqr is a valuable resource for researchers aiming to map QTL using NGS-BSA data within the R statistical platform.