A1254
Title: Trait measurement error and its impact on genetic analysis of computer vision-based phenotypes
Authors: Gota Morota - The University of Tokyo (Japan) [presenting]
Abstract: Quantitative genetic analysis of image- or video-derived phenotypes is increasingly being performed for a wide range of traits. Pig body weight estimated by a conventional approach or a computer vision system can be considered as two different measurements of the same trait, but with different sources of phenotyping error. Previous studies have shown that trait measurement error, defined as the difference between manually collected phenotypes and image-derived phenotypes, can be influenced by genetics, suggesting that the error is systematic rather than random and is more likely to lead to misleading quantitative genetic analysis results. We investigated the effect of trait measurement error on genetic analysis of pig body weight (BW). Genomic heritability estimates for scale-based and image-based BW were mostly identical across growth periods. Genomic heritability estimates for trait measurement error were consistently negligible, regardless of the choice of computer vision algorithm. In addition, genome-wide association analysis revealed no overlap between the top markers identified for scale-based BW and those associated with trait measurement error. This study showed that manually measured scale-based and image-based BW phenotypes yielded the same quantitative genetic results. We found no evidence that BW trait measurement error could be influenced, at least in part, by genetic factors.
