Combining high-throughput micro-CT-RGB phenotyping and genome-wide association study to dissect the genetic architecture of tiller growth in rice.

Abstract

Manual phenotyping of rice tillers is time consuming and labor intensive, and lags behind the rapid development of rice functional genomics. Thus, automated, non-destructive methods of phenotyping rice tiller traits at a high spatial resolution and high throughput for large-scale assessment of rice accessions are urgently needed. In this study, we developed a high-throughput micro-CT-RGB imaging system to non-destructively extract 739 traits from 234 rice accessions at nine time points. We could explain 30% of the grain yield variance from two tiller traits assessed in the early growth stages. A total of 402 significantly associated loci were identified by genome-wide association study, and dynamic and static genetic components were found across the nine time points. A major locus associated with tiller angle was detected at time point 9, which contained a major gene, TAC1. Significant variants associated with tiller angle were enriched in the 3'-untranslated region of TAC1. Three haplotypes for the gene were found, and rice accessions containing haplotype H3 displayed much smaller tiller angles. Further, we found two loci containing associations with both vigor-related traits identified by high-throughput micro-CT-RGB imaging and yield. The superior alleles would be beneficial for breeding for high yield and dense planting.

Plant phenotyping relevance

高スループットなmicro-CT-RGB画像システムを開発し、イネの形態形質を多数・経時的に非破壊抽出することが研究の中心であるため、GWAS応用を含む植物フェノタイピング手法研究として含める。

Code and data availability

The paper deposits its rice tiller phenotyping datasets, images, and analysis source code at Dryad (doi:10.5061/dryad.gm18v5f), and makes the raw phenotypic data and CT/RGB images publicly downloadable via the HZAU plant phenomics database. Both are paper-specific, public, and actionable.