MCPtaggR

MCPtaggR improves genotype calling accuracy in reduced representation sequencing (RRS) data by identifying and filtering mismapping- and bias-prone markers using collinearity information between parental genomes within the mappable collinear polymorphic tag genotyping (MCPtagg) pipeline.

Key Features:

• Elimination of error-prone markers: Filters markers that produce mismapping or biased mapping when RRS reads with mismatches are mapped onto a reference genome.
• Collinearity-based filtering: Leverages marker collinearity information derived from genome sequence comparisons of parent organisms in biparental cross populations to identify and exclude problematic markers prior to genotype calling.
• Sequencing technology compatibility: Designed for reduced representation sequencing approaches including genotyping-by-sequencing (GBS).
• Assembly compatibility: Demonstrated performance with polished genome assemblies and does not require de novo assembly for accurate genotype calling.
• Implementation: Distributed as an R package that implements the MCPtagg pipeline for marker filtering and genotype calling workflows.
• Evaluation on empirical data: Validated using real GBS data from a rice F2 population to assess genotyping accuracy.

Scientific Applications:

• Plant and animal breeding: Improves genotype accuracy for mapping traits and informing genetic selection in breeding programs.
• Population genetics: Reduces genotyping errors in studies of allele frequencies, linkage, and population structure using RRS data.
• Evolutionary biology: Enhances reliability of genotype data for analyses of genetic diversity and evolutionary inference.

Methodology:

Maps RRS reads to a reference genome, filters markers with mismapping- or bias-associated signals, uses marker collinearity from parental genome sequence comparisons in biparental crosses to exclude error-prone markers prior to genotype calling, and was evaluated on GBS data from a rice F2 population and on polished genome assemblies without de novo assembly.