a. Explain how figures 3 and 5 are connected. Does this support the hypothesis proposed by Parent and colleagues (2015)? b. What is the main goal of the study? State using the if-then format.    c. What are the two substances that confer resistance to the white spruces? d. What stage of the spruce budworm is most susceptible to the bioactive substances of white spruce?

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Chapter37: Plant Signals And Responses To The Environment
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ANSWER THE FOLLOWING QUESTIONS USING THE GIVEN SCIENTIFIC PAPER.

a. Explain how figures 3 and 5 are connected. Does this support the hypothesis proposed by Parent and colleagues (2015)?

b. What is the main goal of the study? State using the if-then format. 
 
c. What are the two substances that confer resistance to the white spruces?

d. What stage of the spruce budworm is most susceptible to the bioactive substances of white spruce?

 

Microevolutionary
patterns of a
resistance mechanism in white spruce
G. J. Parent¹, I. Giguère¹*, J. J. MacKay²
¹ Institut de biologie intégrative et des systèmes, Centre d'étude de la forêt, Département des sciences du bois et de la forêt, Université Laval,
Québec, Canada (genevieve.parent.5@ulaval.ca) 2 Department of Plant Sciences, University of Oxford, Oxford, UK
Resistance mechanism
Results: distribution of resistant trees
linked to insect development
* White spruces (Picea glauca) resistant against spruce budworm
(Choristoneura fumiferana) contain two aglycon acetophenones,
piceol and pungenol, that reduce by half the survival rate of SBW
when added to artificial diet. (Delvas and coll. 2011)
Geographic variation
Low values
O Normal values
●High values
Area 2
The enzyme PgBGLU-1 catalyzes the synthesis of aglycon
acetophenones from picein and pungenin (Fig. 1). (Mageroy and coll. 2015)
Area 1
This resistance mechanism is genetically transmissible; progeny
from resistant trees have more transcripts of PgBglu-1 gene than
those from non-resistant trees. (Mageroy and coll. 2015)
Figure 3. Non
random
distribution of
resistant trees. Blue
or red dots identify
provenances of low
or high abundance
of resistant trees,
respectively.
Area 3
68
Insect fitness is lower on resistant trees than on non-resistant trees.
(results not shown)
sol
Sites within areas 1 and 2 identified as high or low values in two
different trials.
picein
pungenin
piceol
pungenol
* Resistant trees more frequent in the center of study area (area 2).
Non resistant trees more frequent in the south-west (area 1) and east
(area 3) regions.
enzyme
PgBGLU-1
Explanatory variables
Valcartier Mastigouche Sussex
X
X
X
X
Figure 1.
Resistance mechanism.
Table 2. Summary of exploratory
regression results.
L2+ timing
Precipitation
Forest type
Elevation
R²
0.36
0.19
0.19
Random distribution of
resistant trees?
Timing of L2+ (Fig. 4) and precipitation
as significant explanatory variables in at least two trials (Table 2). Timing
of L2+ is the greatest explanatory variable across the study area (Fig. 5).
* Medium to low regression coefficients.
This project aims to determine if trees using this
resistance mechanism have different fitness across
the eastern distribution of white spruce.
L2 to L6
Adults-Eggs-L1+-L2+
L2
Diapause
Figure 4.
Univoltine
SBW life
cycle.
Material and methods
Fall-Winter
Spring
Summer
Sampling: year foliage of white spruces in 3 provenance (p.)
trials (Fig. 2 Valcartier 25 p., Mastigouche 42 p., Sussex 32 p.);
Figure 5. Variation in
SBW development
O
O
8
* Lab analyses: quantification of transcripts by RTqPCR and of
phenolic compounds with liquid chromatography coupled with
UV detector (LCUV) or mass spectrometry;
duration. Average
julian day of
appearance of 50% of
SBW L2+ stage during
summer from 1900 to
Table 1. Summary of Traits/Phenotypes
trait values associated Pg8glu-1 expression
Non-resistant Resistant
Low
68 2014.
High
with resistance Piceol
phenotypes. Pungenol
Low
High
Low
High
* Early appearance of L2+ stage (Fig. 5) linked to low survival of SBW.
In silico analyses: simulations of the average timing of life
cycle of SBW and annual water precipitation (BIOSIM v10);
forest type from raster LandCoverCanada 2005 (ArcGIS v10.2.2);
Conclusion and perspective
Geographic statistical analyses (ArcGIS v10.2.2): hot spot
analyses (Getis-Ord), exploratory regressions (4 variables).
The selection pressure exerted by SBW on white spruce could
explain the distribution of resistant trees.
Sampling during summer 2015 of areas recently affected by SBW to
test the following hypothesis: resistant trees have greater survival
than non resistant trees in areas affected by SBW.
Acknowledgements
O
É. Bauce, J. Bohlmann, and M. Mageroy for their constructive
comments.
M. Charest, G. Germanos, G. Piette Lauzière, J. Piette and D.
Vigneault Roussy for their help in the field and lab work.
Figure 2.
Provenances in
3 trials.
●Valcartier 2013
Mastigouche 2014
Sussex 2014
New Phytologist
Symposium!
+ MFFP: A. Rainville, G. Gagnon, L. Morneau for sampling and
helpful discussions.
Delvas et al. (2011). Entomologia Exp. Et App. 141: 35-44.
Mageroy et al. (2015). The Plant Journal 81: 68-80.
+ CFS-Station de recherche forestière de Valcartier: D. Plourde,
Rémi St-Amant.
References
0-227
O228-232
O 233-238
O 239-244
245-248
UNIVERSITÉ
LAVAL
NSERC
CRSNG
Transcribed Image Text:Microevolutionary patterns of a resistance mechanism in white spruce G. J. Parent¹, I. Giguère¹*, J. J. MacKay² ¹ Institut de biologie intégrative et des systèmes, Centre d'étude de la forêt, Département des sciences du bois et de la forêt, Université Laval, Québec, Canada (genevieve.parent.5@ulaval.ca) 2 Department of Plant Sciences, University of Oxford, Oxford, UK Resistance mechanism Results: distribution of resistant trees linked to insect development * White spruces (Picea glauca) resistant against spruce budworm (Choristoneura fumiferana) contain two aglycon acetophenones, piceol and pungenol, that reduce by half the survival rate of SBW when added to artificial diet. (Delvas and coll. 2011) Geographic variation Low values O Normal values ●High values Area 2 The enzyme PgBGLU-1 catalyzes the synthesis of aglycon acetophenones from picein and pungenin (Fig. 1). (Mageroy and coll. 2015) Area 1 This resistance mechanism is genetically transmissible; progeny from resistant trees have more transcripts of PgBglu-1 gene than those from non-resistant trees. (Mageroy and coll. 2015) Figure 3. Non random distribution of resistant trees. Blue or red dots identify provenances of low or high abundance of resistant trees, respectively. Area 3 68 Insect fitness is lower on resistant trees than on non-resistant trees. (results not shown) sol Sites within areas 1 and 2 identified as high or low values in two different trials. picein pungenin piceol pungenol * Resistant trees more frequent in the center of study area (area 2). Non resistant trees more frequent in the south-west (area 1) and east (area 3) regions. enzyme PgBGLU-1 Explanatory variables Valcartier Mastigouche Sussex X X X X Figure 1. Resistance mechanism. Table 2. Summary of exploratory regression results. L2+ timing Precipitation Forest type Elevation R² 0.36 0.19 0.19 Random distribution of resistant trees? Timing of L2+ (Fig. 4) and precipitation as significant explanatory variables in at least two trials (Table 2). Timing of L2+ is the greatest explanatory variable across the study area (Fig. 5). * Medium to low regression coefficients. This project aims to determine if trees using this resistance mechanism have different fitness across the eastern distribution of white spruce. L2 to L6 Adults-Eggs-L1+-L2+ L2 Diapause Figure 4. Univoltine SBW life cycle. Material and methods Fall-Winter Spring Summer Sampling: year foliage of white spruces in 3 provenance (p.) trials (Fig. 2 Valcartier 25 p., Mastigouche 42 p., Sussex 32 p.); Figure 5. Variation in SBW development O O 8 * Lab analyses: quantification of transcripts by RTqPCR and of phenolic compounds with liquid chromatography coupled with UV detector (LCUV) or mass spectrometry; duration. Average julian day of appearance of 50% of SBW L2+ stage during summer from 1900 to Table 1. Summary of Traits/Phenotypes trait values associated Pg8glu-1 expression Non-resistant Resistant Low 68 2014. High with resistance Piceol phenotypes. Pungenol Low High Low High * Early appearance of L2+ stage (Fig. 5) linked to low survival of SBW. In silico analyses: simulations of the average timing of life cycle of SBW and annual water precipitation (BIOSIM v10); forest type from raster LandCoverCanada 2005 (ArcGIS v10.2.2); Conclusion and perspective Geographic statistical analyses (ArcGIS v10.2.2): hot spot analyses (Getis-Ord), exploratory regressions (4 variables). The selection pressure exerted by SBW on white spruce could explain the distribution of resistant trees. Sampling during summer 2015 of areas recently affected by SBW to test the following hypothesis: resistant trees have greater survival than non resistant trees in areas affected by SBW. Acknowledgements O É. Bauce, J. Bohlmann, and M. Mageroy for their constructive comments. M. Charest, G. Germanos, G. Piette Lauzière, J. Piette and D. Vigneault Roussy for their help in the field and lab work. Figure 2. Provenances in 3 trials. ●Valcartier 2013 Mastigouche 2014 Sussex 2014 New Phytologist Symposium! + MFFP: A. Rainville, G. Gagnon, L. Morneau for sampling and helpful discussions. Delvas et al. (2011). Entomologia Exp. Et App. 141: 35-44. Mageroy et al. (2015). The Plant Journal 81: 68-80. + CFS-Station de recherche forestière de Valcartier: D. Plourde, Rémi St-Amant. References 0-227 O228-232 O 233-238 O 239-244 245-248 UNIVERSITÉ LAVAL NSERC CRSNG
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