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Genome-wide association mapping of growth dynamics detects time-specific and general quantitative trait loci.

Bac-Molenaar JA, Vreugdenhil D, Granier C, Keurentjes JJ - J. Exp. Bot. (2015)

Bottom Line: Genome-wide association (GWA) mapping of the temporal growth data resulted in the detection of time-specific quantitative trait loci (QTLs), whereas mapping of model parameters resulted in another set of QTLs related to the whole growth curve.The positive correlation between projected leaf area (PLA) at different time points during the course of the experiment suggested the existence of general growth factors with a function in multiple developmental stages or with prolonged downstream effects.In addition, the detection of QTLs without obvious candidate genes implies the annotation of novel functions for underlying genes.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Plant Physiology, Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands Laboratory of Genetics, Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands.

No MeSH data available.


(A) Images of one of the replicates of CS28014 (Amel-1), a representative accession, at all time points included in the analyses. (B) Pictures processed by ImageJ to determine the projected leaf area (PLA). Pictures were segmented based on colour, saturation, and brightness, and thereafter made binary. Particles which were too small (<120 pixels) were excluded from the analysis. In the images of days 8, 11, and 14, more than one plant is present, but only the remaining one (days 16 and onwards) is taken into account for PLA determinations.
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Figure 1: (A) Images of one of the replicates of CS28014 (Amel-1), a representative accession, at all time points included in the analyses. (B) Pictures processed by ImageJ to determine the projected leaf area (PLA). Pictures were segmented based on colour, saturation, and brightness, and thereafter made binary. Particles which were too small (<120 pixels) were excluded from the analysis. In the images of days 8, 11, and 14, more than one plant is present, but only the remaining one (days 16 and onwards) is taken into account for PLA determinations.

Mentions: A large-scale experiment was performed in the plant phenotyping platform PHENOPSIS (Granier et al., 2006). A total of 324 natural accessions of A. thaliana were grown and their rosette sizes were monitored over time by capturing top-view pictures daily (Supplementary Table S1 at JXB online). The plant architecture of the vegetative stage of Arabidopsis makes this species very suitable for top-view imaging. Because the rosette grows in a horizontal plane, it can be approached as a 2D structure the size of which can be determined accurately from top-view images. Top-view imaging of Arabidopsis rosettes was first reported in the 1990s (Leister et al., 1999), but became suitable for large populations only recently due to advances in the automation of image analysis (Berger et al., 2010; Arvidsson et al., 2011; Tessmer et al., 2013). Although at the moment low-cost, high-throughput methods are available to determine the genome of an organism and genetic information is available for many species and for many mutants and natural accessions, the plant science community lags behind in the high-throughput measurements of phenotypes (Houle et al., 2010). In this experiment, top-view imaging in combination with high-throughput image analysis allowed the determination of the rosette size of plants of 324 accessions in triplicate at 11 time points during growth. PLA was determined from day 8 onwards and the experiment was ended before too many leaves were overlapping (Fig. 1). On day 8, all seeds had germinated, the cotyledons were unfolded, but the first true leaves were not yet visible. As the growth rate increased during the course of the experiment, the interval between the time points of PLA determination was decreased, from a 3 d interval in the second week to a 1 d interval in the fourth week, to ensure that dynamics in growth were accurately captured. Because diurnal leaf movement was observed, PLA was always determined within 2h after the start of the light period. This analysis is one of the first steps in the detailed characterization of the phenomes of these natural accessions (Furbank and Tester, 2011). Similar approaches can also be used in the future to characterize further the phenomes of these natural accessions by performing similar experiments when plants are grown in different and possibly less favourable conditions, such as short days or under abiotic or biotic stress. For much smaller sets of accessions, similar experiments have previously been performed, but to be able to use the phenotypes in mapping studies much larger populations need to be screened (El-Lithy et al., 2004; Granier et al., 2006). Growth was determined not only by differences in PLA over time, but also at the end of the experiment by measuring the FW of the rosettes.


Genome-wide association mapping of growth dynamics detects time-specific and general quantitative trait loci.

Bac-Molenaar JA, Vreugdenhil D, Granier C, Keurentjes JJ - J. Exp. Bot. (2015)

(A) Images of one of the replicates of CS28014 (Amel-1), a representative accession, at all time points included in the analyses. (B) Pictures processed by ImageJ to determine the projected leaf area (PLA). Pictures were segmented based on colour, saturation, and brightness, and thereafter made binary. Particles which were too small (<120 pixels) were excluded from the analysis. In the images of days 8, 11, and 14, more than one plant is present, but only the remaining one (days 16 and onwards) is taken into account for PLA determinations.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4585414&req=5

Figure 1: (A) Images of one of the replicates of CS28014 (Amel-1), a representative accession, at all time points included in the analyses. (B) Pictures processed by ImageJ to determine the projected leaf area (PLA). Pictures were segmented based on colour, saturation, and brightness, and thereafter made binary. Particles which were too small (<120 pixels) were excluded from the analysis. In the images of days 8, 11, and 14, more than one plant is present, but only the remaining one (days 16 and onwards) is taken into account for PLA determinations.
Mentions: A large-scale experiment was performed in the plant phenotyping platform PHENOPSIS (Granier et al., 2006). A total of 324 natural accessions of A. thaliana were grown and their rosette sizes were monitored over time by capturing top-view pictures daily (Supplementary Table S1 at JXB online). The plant architecture of the vegetative stage of Arabidopsis makes this species very suitable for top-view imaging. Because the rosette grows in a horizontal plane, it can be approached as a 2D structure the size of which can be determined accurately from top-view images. Top-view imaging of Arabidopsis rosettes was first reported in the 1990s (Leister et al., 1999), but became suitable for large populations only recently due to advances in the automation of image analysis (Berger et al., 2010; Arvidsson et al., 2011; Tessmer et al., 2013). Although at the moment low-cost, high-throughput methods are available to determine the genome of an organism and genetic information is available for many species and for many mutants and natural accessions, the plant science community lags behind in the high-throughput measurements of phenotypes (Houle et al., 2010). In this experiment, top-view imaging in combination with high-throughput image analysis allowed the determination of the rosette size of plants of 324 accessions in triplicate at 11 time points during growth. PLA was determined from day 8 onwards and the experiment was ended before too many leaves were overlapping (Fig. 1). On day 8, all seeds had germinated, the cotyledons were unfolded, but the first true leaves were not yet visible. As the growth rate increased during the course of the experiment, the interval between the time points of PLA determination was decreased, from a 3 d interval in the second week to a 1 d interval in the fourth week, to ensure that dynamics in growth were accurately captured. Because diurnal leaf movement was observed, PLA was always determined within 2h after the start of the light period. This analysis is one of the first steps in the detailed characterization of the phenomes of these natural accessions (Furbank and Tester, 2011). Similar approaches can also be used in the future to characterize further the phenomes of these natural accessions by performing similar experiments when plants are grown in different and possibly less favourable conditions, such as short days or under abiotic or biotic stress. For much smaller sets of accessions, similar experiments have previously been performed, but to be able to use the phenotypes in mapping studies much larger populations need to be screened (El-Lithy et al., 2004; Granier et al., 2006). Growth was determined not only by differences in PLA over time, but also at the end of the experiment by measuring the FW of the rosettes.

Bottom Line: Genome-wide association (GWA) mapping of the temporal growth data resulted in the detection of time-specific quantitative trait loci (QTLs), whereas mapping of model parameters resulted in another set of QTLs related to the whole growth curve.The positive correlation between projected leaf area (PLA) at different time points during the course of the experiment suggested the existence of general growth factors with a function in multiple developmental stages or with prolonged downstream effects.In addition, the detection of QTLs without obvious candidate genes implies the annotation of novel functions for underlying genes.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Plant Physiology, Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands Laboratory of Genetics, Wageningen University, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands.

No MeSH data available.