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Genome-wide association study of rice (Oryza sativa L.) leaf traits with a high-throughput leaf scorer.

Yang W, Guo Z, Huang C, Wang K, Jiang N, Feng H, Chen G, Liu Q, Xiong L - J. Exp. Bot. (2015)

Bottom Line: Nine associated loci contained known leaf-related genes, such as Nal1 for controlling the leaf width.In addition, a total of 73, 123, and 177 new loci were detected for traits associated with leaf size, colour, and shape, respectively.In summary, after evaluating the performance with a large number of rice accessions, the combination of GWAS and high-throughput leaf phenotyping (HLS) has proven a valuable strategy to identify the genetic loci controlling rice leaf traits.

View Article: PubMed Central - PubMed

Affiliation: National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, PR China College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China Agricultural Bioinformatics Key Laboratory of Hubei Province, Huazhong Agricultural University, Wuhan 430070, PR China.

No MeSH data available.


The performance evaluation of the LN and leaf area extraction. The scatter plots of the HLS measurement versus the DS measurement for the (a) GLA, (b) TLA, and (c) LN.
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Figure 3: The performance evaluation of the LN and leaf area extraction. The scatter plots of the HLS measurement versus the DS measurement for the (a) GLA, (b) TLA, and (c) LN.

Mentions: To test the HLS performance, 163 rice accessions from germplasm resources were randomly selected to measure the GLA, TLA, and LN. After the leaves of an individual rice plant were measured with the HLS, a DS (BenQ 8800) was used to obtain the actual GLA and TLA (Caldas et al., 1992), and the LNs were counted manually. A comparison between the DS measurements and the HLS measurements for GLA are illustrated in Fig. 3a and TLA in Fig. 3b. The manual measurement versus the HLS measurement for LN is shown in Fig. 3c. The mean absolute per cent errors (MAPE, defined by Eq. 1) were 3.20% for GLA, 4.14% for TLA, and 0.95% for LN. The standard deviation of the absolute per cent error values for GLA was 2.51%, for TLA was 2.81%, and for LN was 1.82%. The coefficients of determination (R2) of the DS (or manual) measurements versus HLS measurements for GLA, TLA, and LN were all 0.99.


Genome-wide association study of rice (Oryza sativa L.) leaf traits with a high-throughput leaf scorer.

Yang W, Guo Z, Huang C, Wang K, Jiang N, Feng H, Chen G, Liu Q, Xiong L - J. Exp. Bot. (2015)

The performance evaluation of the LN and leaf area extraction. The scatter plots of the HLS measurement versus the DS measurement for the (a) GLA, (b) TLA, and (c) LN.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4585412&req=5

Figure 3: The performance evaluation of the LN and leaf area extraction. The scatter plots of the HLS measurement versus the DS measurement for the (a) GLA, (b) TLA, and (c) LN.
Mentions: To test the HLS performance, 163 rice accessions from germplasm resources were randomly selected to measure the GLA, TLA, and LN. After the leaves of an individual rice plant were measured with the HLS, a DS (BenQ 8800) was used to obtain the actual GLA and TLA (Caldas et al., 1992), and the LNs were counted manually. A comparison between the DS measurements and the HLS measurements for GLA are illustrated in Fig. 3a and TLA in Fig. 3b. The manual measurement versus the HLS measurement for LN is shown in Fig. 3c. The mean absolute per cent errors (MAPE, defined by Eq. 1) were 3.20% for GLA, 4.14% for TLA, and 0.95% for LN. The standard deviation of the absolute per cent error values for GLA was 2.51%, for TLA was 2.81%, and for LN was 1.82%. The coefficients of determination (R2) of the DS (or manual) measurements versus HLS measurements for GLA, TLA, and LN were all 0.99.

Bottom Line: Nine associated loci contained known leaf-related genes, such as Nal1 for controlling the leaf width.In addition, a total of 73, 123, and 177 new loci were detected for traits associated with leaf size, colour, and shape, respectively.In summary, after evaluating the performance with a large number of rice accessions, the combination of GWAS and high-throughput leaf phenotyping (HLS) has proven a valuable strategy to identify the genetic loci controlling rice leaf traits.

View Article: PubMed Central - PubMed

Affiliation: National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, PR China College of Engineering, Huazhong Agricultural University, Wuhan 430070, PR China Agricultural Bioinformatics Key Laboratory of Hubei Province, Huazhong Agricultural University, Wuhan 430070, PR China.

No MeSH data available.