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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 leaf colour and leaf shape extraction. (a) The green colour ratio distribution of each batch (50 rice leaves) belonging to group 2 (light green), group 3 (green), and group 4 (dark green). The scatter plots of the HLS measurement versus the DS measurement for the (b) LL and (c) LW.
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Figure 4: The performance evaluation of the leaf colour and leaf shape extraction. (a) The green colour ratio distribution of each batch (50 rice leaves) belonging to group 2 (light green), group 3 (green), and group 4 (dark green). The scatter plots of the HLS measurement versus the DS measurement for the (b) LL and (c) LW.

Mentions: To evaluate the green leaf colour discrimination of the HLS, three batches of rice leaves (50 leaves for each batch) that belong to green-2 (light green), green-3 (green), and green-4 (dark green) were manually selected using the leaf colour chart developed by IRRI. Afterwards, each batch was measured using the HLS, and the results are shown in Fig. 4a and Supplementary Fig. S4. The discrimination errors for green-2, green-3, and green-4 were 0%, 0%, and 2%, respectively, demonstrating that the HLS is highly accurate in discriminating green leaf colours in rice.


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 leaf colour and leaf shape extraction. (a) The green colour ratio distribution of each batch (50 rice leaves) belonging to group 2 (light green), group 3 (green), and group 4 (dark green). The scatter plots of the HLS measurement versus the DS measurement for the (b) LL and (c) LW.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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

Figure 4: The performance evaluation of the leaf colour and leaf shape extraction. (a) The green colour ratio distribution of each batch (50 rice leaves) belonging to group 2 (light green), group 3 (green), and group 4 (dark green). The scatter plots of the HLS measurement versus the DS measurement for the (b) LL and (c) LW.
Mentions: To evaluate the green leaf colour discrimination of the HLS, three batches of rice leaves (50 leaves for each batch) that belong to green-2 (light green), green-3 (green), and green-4 (dark green) were manually selected using the leaf colour chart developed by IRRI. Afterwards, each batch was measured using the HLS, and the results are shown in Fig. 4a and Supplementary Fig. S4. The discrimination errors for green-2, green-3, and green-4 were 0%, 0%, and 2%, respectively, demonstrating that the HLS is highly accurate in discriminating green leaf colours in rice.

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.