Effects of known functional alleles of agronomically important genes on yield-related traits estimated by historical rice breeding data in Japan

Abstract

Utilizing genetic information is a promising strategy to accelerate crop breeding. The identification of many causative genes in rice, even for polygenic traits, enables us to take on the challenge of predicting yield-related traits by using allele information. However, phenotyping has been a bottleneck in such analyses. Historical breeding data constitute a valuable source of yield-related phenotypic data. Here, we used a subset of 19,218 records drawn from 225,163 records in the rice historical phenotype dataset maintained by the National Agriculture and Food Research Organization. We evaluated the heritability of seven yield-related traits explained by 26 agronomically important genes and the accuracies of the models’ predictions. These genes constituted a portion of the total genetic effect, but the effects of the genetic background were also significant. In some traits, the model based on the agronomically important genes proved more accurate than that based on whole-genome polymorphisms. We also estimated the effects of genes that contribute to yield. This paper presents the possibilities and challenges of utilizing historical breeding data, and important information on how to utilize allele information in future breeding.