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Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice.

Yang W, Guo Z, Huang C, Duan L, Chen G, Jiang N, Fang W, Feng H, Xie W, Lian X, Wang G, Luo Q, Zhang Q, Liu Q, Xiong L - Nat Commun (2014)

Bottom Line: Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1.Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information.The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.

View Article: PubMed Central - PubMed

Affiliation: 1] Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China [2] National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China [3] MoE Key Laboratory for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China [4] College of Engineering, Huazhong Agricultural University, Wuhan 430070, China.

ABSTRACT
Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.

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Combination of the HRPF (RAP and YTS) and genome-wide association study (GWAS).To automatically screen the rice-core germplasm resource throughout the growth period (a), the entire HRPF was designed with two main elements: a rice automatic plant phenotyping device (RAP, b) and a YTS (c). These novel phenotyping tools were able to extract not only the traditional agronomic traits but also several novel phenotypic traits (such as plant compactness and grain-projected area). After the rice phenotypic traits (d) were extracted with the RAP and YTS, new loci were dissected using GWAS (e). *New traits are those that cannot be defined and extracted using traditional measurement techniques.
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f1: Combination of the HRPF (RAP and YTS) and genome-wide association study (GWAS).To automatically screen the rice-core germplasm resource throughout the growth period (a), the entire HRPF was designed with two main elements: a rice automatic plant phenotyping device (RAP, b) and a YTS (c). These novel phenotyping tools were able to extract not only the traditional agronomic traits but also several novel phenotypic traits (such as plant compactness and grain-projected area). After the rice phenotypic traits (d) were extracted with the RAP and YTS, new loci were dissected using GWAS (e). *New traits are those that cannot be defined and extracted using traditional measurement techniques.

Mentions: To enable high-throughput and automatic phenotypic screening of rice germplasm resources and populations throughout the growth period and after harvest (Fig. 1a), a phenotyping facility was designed with two main sections: a rice automatic phenotyping platform (RAP; Fig. 1b) and a yield traits scorer (YTS; Fig. 1c). The RAP, which included greenhouse, transportation and inspection units, was a highly integrated facility that could achieve high-throughput screening of rice plants. The inspection unit of the RAP included two devices: a colour-imaging device and a linear X-ray computed tomography (CT). The colour imaging (also called optical imaging) was designed to non-destructively extract morphology-related traits (plant height, green leaf area and plant compactness; Fig. 1d) and biomass-related traits (shoot fresh weight and shoot dry weight; Fig. 1d). After colour image acquisition and two-dimensional (2D) image processing, 32 features, including plant height, plant compactness and other morphological and texture features, were extracted for each plant. The features were then combined with the manual measurements of shoot fresh weight, shoot dry weight and green leaf area of the same rice accessions to generate the best model for predicting these three traits using feature grouping and all-subset regression. The linear X-ray CT was used to automatically measure the tiller number as described in our previous study14.


Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice.

Yang W, Guo Z, Huang C, Duan L, Chen G, Jiang N, Fang W, Feng H, Xie W, Lian X, Wang G, Luo Q, Zhang Q, Liu Q, Xiong L - Nat Commun (2014)

Combination of the HRPF (RAP and YTS) and genome-wide association study (GWAS).To automatically screen the rice-core germplasm resource throughout the growth period (a), the entire HRPF was designed with two main elements: a rice automatic plant phenotyping device (RAP, b) and a YTS (c). These novel phenotyping tools were able to extract not only the traditional agronomic traits but also several novel phenotypic traits (such as plant compactness and grain-projected area). After the rice phenotypic traits (d) were extracted with the RAP and YTS, new loci were dissected using GWAS (e). *New traits are those that cannot be defined and extracted using traditional measurement techniques.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4214417&req=5

f1: Combination of the HRPF (RAP and YTS) and genome-wide association study (GWAS).To automatically screen the rice-core germplasm resource throughout the growth period (a), the entire HRPF was designed with two main elements: a rice automatic plant phenotyping device (RAP, b) and a YTS (c). These novel phenotyping tools were able to extract not only the traditional agronomic traits but also several novel phenotypic traits (such as plant compactness and grain-projected area). After the rice phenotypic traits (d) were extracted with the RAP and YTS, new loci were dissected using GWAS (e). *New traits are those that cannot be defined and extracted using traditional measurement techniques.
Mentions: To enable high-throughput and automatic phenotypic screening of rice germplasm resources and populations throughout the growth period and after harvest (Fig. 1a), a phenotyping facility was designed with two main sections: a rice automatic phenotyping platform (RAP; Fig. 1b) and a yield traits scorer (YTS; Fig. 1c). The RAP, which included greenhouse, transportation and inspection units, was a highly integrated facility that could achieve high-throughput screening of rice plants. The inspection unit of the RAP included two devices: a colour-imaging device and a linear X-ray computed tomography (CT). The colour imaging (also called optical imaging) was designed to non-destructively extract morphology-related traits (plant height, green leaf area and plant compactness; Fig. 1d) and biomass-related traits (shoot fresh weight and shoot dry weight; Fig. 1d). After colour image acquisition and two-dimensional (2D) image processing, 32 features, including plant height, plant compactness and other morphological and texture features, were extracted for each plant. The features were then combined with the manual measurements of shoot fresh weight, shoot dry weight and green leaf area of the same rice accessions to generate the best model for predicting these three traits using feature grouping and all-subset regression. The linear X-ray CT was used to automatically measure the tiller number as described in our previous study14.

Bottom Line: Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1.Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information.The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.

View Article: PubMed Central - PubMed

Affiliation: 1] Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China [2] National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China [3] MoE Key Laboratory for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China [4] College of Engineering, Huazhong Agricultural University, Wuhan 430070, China.

ABSTRACT
Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.

Show MeSH