A fully automated pipeline for quantitative genotype calling from next generation sequencing data in autopolyploids

Area of Science:

• Plant genetics
• Genomics
• Bioinformatics

Background:

• Genotyping-by-sequencing (GBS) is widely used in genetic studies, particularly for agriculturally important species.
• Current genotype calling software faces limitations in accurately distinguishing heterozygous classes in autopolyploid species due to allele dosage complexities.

Purpose of the Study:

• To develop and validate a computational approach for accurate genotype calling in autopolyploid species using GBS data.
• To overcome the limitations of existing software in handling allele dosage variations in polyploids.

Main Methods:

• Development of VCF2SM, a Python script integrating sequencing depth information from variant call format (VCF) files with SUPERMASSA software.
• Utilizing VCF files generated from GBS data, including a modified TASSEL-GBS pipeline for precise allele sequencing depth output.
• Application of the VCF2SM script to analyze GBS data from diverse polyploid panels and populations.

Main Results:

• VCF2SM successfully performed quantitative genotype calling by integrating sequencing depth and allele dosage information.
• The script was effectively applied to analyze GBS data from various polyploid species, including alfalfa, potato, and switchgrass.
• Demonstrated accurate differentiation of heterozygous classes based on allele dosage in autopolyploid GBS datasets.

Conclusions:

• The developed VCF2SM approach enables accurate genotype calling from GBS data in autopolyploid species.
• This method assists plant geneticists in advancing studies involving polyploid species by resolving allele dosage ambiguities.
• Facilitates more robust genetic analyses and breeding applications in polyploid crops and plants.