Fine-tuning GBS data with comparison of reference and mock genome approaches for advancing genomic selection in less studied farmed species.

ABSTRACT:

Background

Diversifying animal cultivation demands efficient genotyping for enabling genomic selection, but non-model species lack efficient genotyping solutions. The aim of this study was to optimize a genotyping-by-sequencing (GBS) double-digest RAD-sequencing (ddRAD) pipeline. Bovine data was used to automate the bioinformatic analysis. The application of the optimization was demonstrated on non-model European whitefish data.

Results

DdRAD data generation was designed for a reliable estimation of relatedness and is scalable to up to 384 samples. The GBS sequencing yielded approximately one million reads for each of the around 100 assessed samples. Optimizing various strategies to create a de-novo reference genome for variant calling (mock reference) showed that using thre

SUBMITTER: Fischer D 

PROVIDER: S-EPMC11796084 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature