Raw genotype and imputed genotype of 422 rice hybrid cultivars

Accurate prediction of flowering time across diverse environments is crucial for effective crop management and breeding. While the accumulated temperature index (ATI) is widely used as an indicator for estimating flowering time, its traditional definition lacks systematic evaluation and genetic basis understanding. Here, using data from 422 rice hybrids across 47 locations, we identified the optimal ATI calculation window as 1 day after sowing to 26 days before flowering. Based on this redefined ATI, we developed a single-parameter model that outperforms the state-of-the-art reaction norm index model in both accuracy and stability, especially with limited data. We identified 10 loci significantly associated with ATI variation, including three near known flowering time genes and four linked to ecotype differentiation. To enhance practical utility, we developed an efficient flowering time prediction kit using 28 functionally relevant markers, complemented by a user-friendly online tool (http://xielab.hzau.edu.cn/ATI). Our approach can be easily applied to other crops, as ATI is commonly used across various agricultural systems.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-16
DOI
https://doi.org/10.5281/zenodo.13766912
Primary Topic
Genetic Mapping and Diversity in Plants and Animals
Type
article
Field-Weighted Citation Impact
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article

Raw genotype and imputed genotype of 422 rice hybrid cultivars

Zenodo (CERN European Organization for Nuclear Research)
Genetic Mapping and Diversity in Plants and Animals
article

Raw genotype and imputed genotype of 422 rice hybrid cultivars

article en

Abstract

Accurate prediction of flowering time across diverse environments is crucial for effective crop management and breeding. While the accumulated temperature index (ATI) is widely used as an indicator for estimating flowering time, its traditional definition lacks systematic evaluation and genetic basis understanding. Here, using data from 422 rice hybrids across 47 locations, we identified the optimal ATI calculation window as 1 day after sowing to 26 days before flowering. Based on this redefined ATI, we developed a single-parameter model that outperforms the state-of-the-art reaction norm index model in both accuracy and stability, especially with limited data. We identified 10 loci significantly associated with ATI variation, including three near known flowering time genes and four linked to ecotype differentiation. To enhance practical utility, we developed an efficient flowering time prediction kit using 28 functionally relevant markers, complemented by a user-friendly online tool (http://xielab.hzau.edu.cn/ATI). Our approach can be easily applied to other crops, as ATI is commonly used across various agricultural systems.

Zenodo (CERN European Organization for Nuclear Research)
Zero hunger
Openalex Percentile: Top 53%
Genetic Mapping and Diversity in Plants and Animals
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