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Combining field performance with controlled environment plant imaging to identify the genetic control of growth and transpiration underlying yield response to water-deficit stress in wheat.

Parent B, Shahinnia F, Maphosa L, Berger B, Rabie H, Chalmers K, Kovalchuk A, Langridge P, Fleury D - J. Exp. Bot. (2015)

Bottom Line: From the 20 quantitative trait loci (QTLs) found for several traits in the platform, some showed strong effects, accounting for between 26 and 43% of the variation on chromosomes 1A and 1B, indicating that the G×E interaction could be reduced in a controlled environment and by using dynamic variables.Co-located QTLs were found for average growth rate, leaf expansion rate, transpiration rate, and water-use efficiency from the platform with yield, spike number, grain weight, grain number, and harvest index in the field.These results demonstrated that imaging platforms are a suitable alternative to field-based screening and may be used to phenotype recombinant lines for positional cloning.

View Article: PubMed Central - PubMed

Affiliation: Australian Centre for Plant Functional Genomics (ACPFG), University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia.

No MeSH data available.


Difference between lines with the Drysdale or Gladius alleles at marker wsnp_CAP11_c1902_1022590 (position 74.3 on chromosome 1B) for their growth curve and Average transpiration rate (TR) in the well-watered treatment of the experiment in the imaging platform. The graphs show growth curves for lines with the Gladius allele (lower curve) or the Drysdale allele (upper curve) at this locus. Curves are the logistic inference±standard deviation obtained with 1000 bootstrap replicates (function boot in R) on all lines having the considered allele at this locus. Insets show boxplots of TR per unit leaf area for lines with the Gladius (G) or Drysdale (D) allele at this locus. (This figure is available in colour at JXB online.)
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Figure 3: Difference between lines with the Drysdale or Gladius alleles at marker wsnp_CAP11_c1902_1022590 (position 74.3 on chromosome 1B) for their growth curve and Average transpiration rate (TR) in the well-watered treatment of the experiment in the imaging platform. The graphs show growth curves for lines with the Gladius allele (lower curve) or the Drysdale allele (upper curve) at this locus. Curves are the logistic inference±standard deviation obtained with 1000 bootstrap replicates (function boot in R) on all lines having the considered allele at this locus. Insets show boxplots of TR per unit leaf area for lines with the Gladius (G) or Drysdale (D) allele at this locus. (This figure is available in colour at JXB online.)

Mentions: We found overlaps between QTLs for different variables measured in the platform on three regions of chromosomes 1B, 2A, and 5B (Table 4). On chromosome 1B, the QTL QGRO.atw-1B for GrowthAVE and QLERAVE.atw-1B.1 for Average leaf expansion rate coincided with the QTL peak of QTR.atw-1B for Average transpiration rate. These three QTLs carried Drysdale as a positive allele. When looking at pools of RILs carrying Gladius or Drysdale alleles at the marker wsnp_CAP11_c1902_1022590 (Fig. 3), it appeared that the higher transpiration rate and higher growth rate for plants carrying the Drysdale allele were observed in both treatments. This QTL effect seemed intrinsic rather than specific to well-watered conditions.


Combining field performance with controlled environment plant imaging to identify the genetic control of growth and transpiration underlying yield response to water-deficit stress in wheat.

Parent B, Shahinnia F, Maphosa L, Berger B, Rabie H, Chalmers K, Kovalchuk A, Langridge P, Fleury D - J. Exp. Bot. (2015)

Difference between lines with the Drysdale or Gladius alleles at marker wsnp_CAP11_c1902_1022590 (position 74.3 on chromosome 1B) for their growth curve and Average transpiration rate (TR) in the well-watered treatment of the experiment in the imaging platform. The graphs show growth curves for lines with the Gladius allele (lower curve) or the Drysdale allele (upper curve) at this locus. Curves are the logistic inference±standard deviation obtained with 1000 bootstrap replicates (function boot in R) on all lines having the considered allele at this locus. Insets show boxplots of TR per unit leaf area for lines with the Gladius (G) or Drysdale (D) allele at this locus. (This figure is available in colour at JXB online.)
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4585424&req=5

Figure 3: Difference between lines with the Drysdale or Gladius alleles at marker wsnp_CAP11_c1902_1022590 (position 74.3 on chromosome 1B) for their growth curve and Average transpiration rate (TR) in the well-watered treatment of the experiment in the imaging platform. The graphs show growth curves for lines with the Gladius allele (lower curve) or the Drysdale allele (upper curve) at this locus. Curves are the logistic inference±standard deviation obtained with 1000 bootstrap replicates (function boot in R) on all lines having the considered allele at this locus. Insets show boxplots of TR per unit leaf area for lines with the Gladius (G) or Drysdale (D) allele at this locus. (This figure is available in colour at JXB online.)
Mentions: We found overlaps between QTLs for different variables measured in the platform on three regions of chromosomes 1B, 2A, and 5B (Table 4). On chromosome 1B, the QTL QGRO.atw-1B for GrowthAVE and QLERAVE.atw-1B.1 for Average leaf expansion rate coincided with the QTL peak of QTR.atw-1B for Average transpiration rate. These three QTLs carried Drysdale as a positive allele. When looking at pools of RILs carrying Gladius or Drysdale alleles at the marker wsnp_CAP11_c1902_1022590 (Fig. 3), it appeared that the higher transpiration rate and higher growth rate for plants carrying the Drysdale allele were observed in both treatments. This QTL effect seemed intrinsic rather than specific to well-watered conditions.

Bottom Line: From the 20 quantitative trait loci (QTLs) found for several traits in the platform, some showed strong effects, accounting for between 26 and 43% of the variation on chromosomes 1A and 1B, indicating that the G×E interaction could be reduced in a controlled environment and by using dynamic variables.Co-located QTLs were found for average growth rate, leaf expansion rate, transpiration rate, and water-use efficiency from the platform with yield, spike number, grain weight, grain number, and harvest index in the field.These results demonstrated that imaging platforms are a suitable alternative to field-based screening and may be used to phenotype recombinant lines for positional cloning.

View Article: PubMed Central - PubMed

Affiliation: Australian Centre for Plant Functional Genomics (ACPFG), University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia.

No MeSH data available.