Multi-omics analysis

Comparison of strategies for incorporating functional annotation in genomic prediction

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Abstract

The increasing availability of functional annotations has created opportunities to incorporate biological knowledge into genomic prediction of quantitative traits. This study aims to demonstrate how prioritizing SNPs based on prior biological knowledge across different annotation strategies affects genomic prediction. We presented two strategies for prioritizing SNPs for genomic prediction: SNPs prioritized from genomic regions associated with related phenotypic traits in other populations, and SNPs prioritized within the genic region of the genome. These approaches were illustrated using Landrace x Yorkshire pigs from a natural disease challenge study on two carcass traits, lean yield (LYD) and backfat (BF). Our results showed higher prediction accuracy (up to 4.23% gain) for LYD and provided insights into estimates of the proportion of total genetic variance captured by SNPs prioritized across strategies and traits evaluated.

Keywords: 2026

How to Cite:

Olabosoye, B., Dekkers, J. & Steibel, J., (2026) “Comparison of strategies for incorporating functional annotation in genomic prediction”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2284887. doi: https://doi.org/10.31274/wcgalp.23620

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