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A DNA-based method for studying root responses to drought in field-grown wheat genotypes.

Huang CY, Kuchel H, Edwards J, Hall S, Parent B, Eckermann P - Sci Rep (2013)

Bottom Line: Root systems are critical for water and nutrient acquisition by crops.Current methods measuring root biomass and length are slow and labour-intensive for studying root responses to environmental stresses in the field.The new method eliminates the need for separation of roots from soil and permits large-scale phenotyping of root responses to drought or other environmental and disease stresses in the field.

View Article: PubMed Central - PubMed

Affiliation: Australian Centre for Plant Functional Genomics, The University of Adelaide, Waite Campus, Glen Osmond, South Australia, 5064, Australia.

ABSTRACT
Root systems are critical for water and nutrient acquisition by crops. Current methods measuring root biomass and length are slow and labour-intensive for studying root responses to environmental stresses in the field. Here, we report the development of a method that measures changes in the root DNA concentration in soil and detects root responses to drought in controlled environment and field trials. To allow comparison of soil DNA concentrations from different wheat genotypes, we also developed a procedure for correcting genotypic differences in the copy number of the target DNA sequence. The new method eliminates the need for separation of roots from soil and permits large-scale phenotyping of root responses to drought or other environmental and disease stresses in the field.

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Genetic variation of root DNA density (RDD) in field-grown wheat genotypes.(a) Genetic variation of RDD in top 10-cm soil among 20 wheat genotypes at five field sites. Ten representative soil cores (one cm in diameter × 10 cm in depth) from between rows were collected at flowering for each plot. Predicted means of four replicates are presented for RDD. (b) Genotypic variation of RRD in soil profile among seven wheat genotypes. Five representative soil cores (2.5 cm in diameter and 45 cm in depth) were collected at flowering from between rows for each plot at one field site, Karoonda. The 45-cm soil cores were separated into three 15-cm sections (0–15 cm, 15–30 cm and 30–45 cm), and the corresponding sections of five soil cores were combined for root DNA analysis. Natural logarithm transformed data were used for statistical analysis and means (n = 3) are presented for RDD. There are significant differences in RDD for genotype and depth (P < 0.001), and for interactions of genotype × depth (P < 0.034). Vertical lines indicate the least significant difference (LSD0.05) for interactions of genotype × depth. Ct values of TaITS2 were determined for all soil samples using quantitative real-time PCR with ARMS primers and the TaITS2 probe. RDD was standardised with the scaling factor for each genotype.
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f4: Genetic variation of root DNA density (RDD) in field-grown wheat genotypes.(a) Genetic variation of RDD in top 10-cm soil among 20 wheat genotypes at five field sites. Ten representative soil cores (one cm in diameter × 10 cm in depth) from between rows were collected at flowering for each plot. Predicted means of four replicates are presented for RDD. (b) Genotypic variation of RRD in soil profile among seven wheat genotypes. Five representative soil cores (2.5 cm in diameter and 45 cm in depth) were collected at flowering from between rows for each plot at one field site, Karoonda. The 45-cm soil cores were separated into three 15-cm sections (0–15 cm, 15–30 cm and 30–45 cm), and the corresponding sections of five soil cores were combined for root DNA analysis. Natural logarithm transformed data were used for statistical analysis and means (n = 3) are presented for RDD. There are significant differences in RDD for genotype and depth (P < 0.001), and for interactions of genotype × depth (P < 0.034). Vertical lines indicate the least significant difference (LSD0.05) for interactions of genotype × depth. Ct values of TaITS2 were determined for all soil samples using quantitative real-time PCR with ARMS primers and the TaITS2 probe. RDD was standardised with the scaling factor for each genotype.

Mentions: To test whether the DNA-based method is suitable for studying genetic variation in root response to drought, a large trial consisting of twenty modern wheat genotypes with diverse genetic background was conducted at five locations in South Australia in 2008. The growing-season rainfall in 2008 was well below the yearly average and each location varied in accumulated rainfall of the growing season (Supplementary Table 2). On average, there was an approximately two-fold variation of RDD in the top 10-cm soil at flowering across the 20 genotypes for the five locations (Fig. 4a). Genetic variance at each location was highly significant, and the heritability at each site was greater than 0.5 (Supplementary Table 3), indicating a strong genetic component underlying RDD. The genetic correlations between sites were also highly significant (Supplementary Table 3).


A DNA-based method for studying root responses to drought in field-grown wheat genotypes.

Huang CY, Kuchel H, Edwards J, Hall S, Parent B, Eckermann P - Sci Rep (2013)

Genetic variation of root DNA density (RDD) in field-grown wheat genotypes.(a) Genetic variation of RDD in top 10-cm soil among 20 wheat genotypes at five field sites. Ten representative soil cores (one cm in diameter × 10 cm in depth) from between rows were collected at flowering for each plot. Predicted means of four replicates are presented for RDD. (b) Genotypic variation of RRD in soil profile among seven wheat genotypes. Five representative soil cores (2.5 cm in diameter and 45 cm in depth) were collected at flowering from between rows for each plot at one field site, Karoonda. The 45-cm soil cores were separated into three 15-cm sections (0–15 cm, 15–30 cm and 30–45 cm), and the corresponding sections of five soil cores were combined for root DNA analysis. Natural logarithm transformed data were used for statistical analysis and means (n = 3) are presented for RDD. There are significant differences in RDD for genotype and depth (P < 0.001), and for interactions of genotype × depth (P < 0.034). Vertical lines indicate the least significant difference (LSD0.05) for interactions of genotype × depth. Ct values of TaITS2 were determined for all soil samples using quantitative real-time PCR with ARMS primers and the TaITS2 probe. RDD was standardised with the scaling factor for each genotype.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3824167&req=5

f4: Genetic variation of root DNA density (RDD) in field-grown wheat genotypes.(a) Genetic variation of RDD in top 10-cm soil among 20 wheat genotypes at five field sites. Ten representative soil cores (one cm in diameter × 10 cm in depth) from between rows were collected at flowering for each plot. Predicted means of four replicates are presented for RDD. (b) Genotypic variation of RRD in soil profile among seven wheat genotypes. Five representative soil cores (2.5 cm in diameter and 45 cm in depth) were collected at flowering from between rows for each plot at one field site, Karoonda. The 45-cm soil cores were separated into three 15-cm sections (0–15 cm, 15–30 cm and 30–45 cm), and the corresponding sections of five soil cores were combined for root DNA analysis. Natural logarithm transformed data were used for statistical analysis and means (n = 3) are presented for RDD. There are significant differences in RDD for genotype and depth (P < 0.001), and for interactions of genotype × depth (P < 0.034). Vertical lines indicate the least significant difference (LSD0.05) for interactions of genotype × depth. Ct values of TaITS2 were determined for all soil samples using quantitative real-time PCR with ARMS primers and the TaITS2 probe. RDD was standardised with the scaling factor for each genotype.
Mentions: To test whether the DNA-based method is suitable for studying genetic variation in root response to drought, a large trial consisting of twenty modern wheat genotypes with diverse genetic background was conducted at five locations in South Australia in 2008. The growing-season rainfall in 2008 was well below the yearly average and each location varied in accumulated rainfall of the growing season (Supplementary Table 2). On average, there was an approximately two-fold variation of RDD in the top 10-cm soil at flowering across the 20 genotypes for the five locations (Fig. 4a). Genetic variance at each location was highly significant, and the heritability at each site was greater than 0.5 (Supplementary Table 3), indicating a strong genetic component underlying RDD. The genetic correlations between sites were also highly significant (Supplementary Table 3).

Bottom Line: Root systems are critical for water and nutrient acquisition by crops.Current methods measuring root biomass and length are slow and labour-intensive for studying root responses to environmental stresses in the field.The new method eliminates the need for separation of roots from soil and permits large-scale phenotyping of root responses to drought or other environmental and disease stresses in the field.

View Article: PubMed Central - PubMed

Affiliation: Australian Centre for Plant Functional Genomics, The University of Adelaide, Waite Campus, Glen Osmond, South Australia, 5064, Australia.

ABSTRACT
Root systems are critical for water and nutrient acquisition by crops. Current methods measuring root biomass and length are slow and labour-intensive for studying root responses to environmental stresses in the field. Here, we report the development of a method that measures changes in the root DNA concentration in soil and detects root responses to drought in controlled environment and field trials. To allow comparison of soil DNA concentrations from different wheat genotypes, we also developed a procedure for correcting genotypic differences in the copy number of the target DNA sequence. The new method eliminates the need for separation of roots from soil and permits large-scale phenotyping of root responses to drought or other environmental and disease stresses in the field.

Show MeSH
Related in: MedlinePlus