Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

Abstract

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.

Plant phenotyping relevance

圃場ハイスループット表現型解析を大規模イネ集団に適用し、従来測定との精度・有効性を比較してQTL検出に利用しており、表現型取得法が研究の中心である。

Code and data availability

The paper's QTL/phenotyping analysis code is publicly hosted on Bitbucket, and the authors state that the code and original phenotyping data files are deposited in Dryad under a DOI. Both are paper-specific, public, and actionable.