Flow Cytometry Training : Introduction day 1 session 1
Thesis DEFENSE
1. Density and flow effects on benthic black fly
larvae
and
Identifying genomic regions responsible for
altered reproductive traits of Arabidopsis
thaliana grown at an elevated carbon dioxide
concentration
Briena E. Healy
Advisor: Dr. Jonathan T. Fingerut
Dr. Clint J. Springer
Thursday, July 12, 2012
Thesis Presentation
3. Black Flies, Family Simuliidae
• Order Diptera, Family Simuliidae,
sp. Simulium tribulatum.
•Common, usually a biting pest.
4. Hill, Catherine, and John MacDonald. Resources: Public Health and Medical Department at Purdue University,
2008. Web. Aug. 2011. <http://extension.entm.purdue.edu/publichealth/resources.html>.
Life cycle of the Black fly
5. Black Fly Larvae
• Found on solid substrates within
streambeds.
• Heavily reliant upon flow at
different scales
– Distribution
– Protection
– Food
FLOW
7. Objectives of the study
• Density effects on distribution.
– What are the effects of neighboring larvae on distribution?
• Past experiences effecting behavior.
– How do starting conditions effect final settlement location?
11. Determining effects of Density
• Graphed the last known position for
– Individual Neonate (N) = low density
– Individual Late-Instar (LI)= low density
– Mass Addition Late-Instar (MA)= high density
-50
-45
-40
-35
-30
-25
-20
-15
-10
-5
0
-15 -10 -5 0 5 10 15 20 25 30
Individual Neonate positions under
Medium (26 cm/s) Flow
Individual Neonate positional
data under Medium Flow
5 10 15 20 25 30 35 40 45
0
1
2
3
4
5
6
7
8
9
10
Frequency
Distance on the hemi-cylinder (mm)
Last position of Individual Neonates
under Medium (26 cm/s ) flow
13. Density Effects Results
• Definite preference by larvae for fastest
available flow
• Distributional spread differs with high
density populations shifting towards
suboptimal flows
• While distributions were not statistically
different, descriptive statistics support the
expected trend of distribution into faster
flow
14. Determining effects of past experiences
• Calculated and compared the starting and
ending flow conditions.
• Tortuosity of paths travelled in respect to
starting velocity
15. Tortuosity: a winding or twisting path.
How twisty or circuitous is the path travelled
http://www.sciencedirect.com/science/article/pii/S0264817210001170
Straight Medium Curvy
1-2 3-5 6-10
Ratio of Linear Distance:
Path shape
16. Flow effects on Late-Instar destination
• Larvae relocate themselves
from an area of slower flow
to an area of higher flow.
• Though larvae may start in
the highest available flow,
they don’t necessarily
remain there due to
turbulence.
0
2
4
6
8
10
12
0 2 4 6 8 10 12
EndingVelocity(cm/s)
Starting Velocity (cm/s)
Late-Instar larvae In Low speed flow (12 cm/s)
-4
-2
0
2
4
6
8
10
0 2 4 6 8 10 12
DifferencebetweenEnding-Starting
velocity(cm/s)
Starting velocity (cm/s)
Difference in velocity for Late-Instar larvae
under Low speed flow (12 cm/s)
17. Flow effects on Neonate destination
• No matter where they
landed, they remained
there.
• The majority have a
difference in almost zero
between their starting and
ending velocities
0
2
4
6
8
10
12
0 2 4 6 8 10 12
Endingvelocity(cm/s)
Starting velocity (cm/s)
Neonate larvae in Low speed flow (12 cm/s)
-2
-1
0
1
2
3
0 2 4 6 8 10 12
DifferencebetweenEnding-
Startingvelocity(cm/s)
Starting velocity (cm/s)
Difference in velocity for Neonate larvae under
Low speed flow (12 cm/s)
18. Conclusions and possibilities for future
endeavors
• High density flow has some effect on where
within a current a larva ends
• Conditions of starting flow matter, but
ontogeny can effect larval distribution
• Data remains unexamined in the database
19. Isolating genomic regions in Arabidopsis
responsible for changes…
Briena Healy
Advisor: Dr. Clint Springer
26. t
Goal= to identify regions of an organism’s genome that controls for a quantitative trait
Quantitative Trait Loci Analysis
Quantitative Trait = Characteristic of an organism that can be attributed to it’s
genetic background
27. Mapping QTL Requires
• An organism with a mapped genome.
• Genetic markers distributed throughout the
genome
– Must be polymorphic markers
• Individuals homozygous at identified markers.
– Back-crossed populations
– Recombinant Inbred Lines
28.
29. Objectives
• Identifying the significant QTLs controlling the
flowering time in both CO2 concentrations.
• Identifying the significant QTLs controlling plant
reproductive architecture in both CO2
concentrations.
30. Methods
• Grew 98 RILs of the cross Columbia (Col) ×
Landsberg erecta (Ler)
• Used two [CO2]
– e[CO2]: 1000 ppm
– a[CO2]: 400 ppm
• Recorded time to flowering
• Counted resulting architecture
• Calculated means for individual lines at both
[CO2] Ungerer et al. 2003
31. Averages days until Flowering
0
10
20
30
40
50
60
70
5 10 15 20 25 30 35 40 45
Frequency
Average days
a[CO2] e[CO2]
32. Average Total Silique number
0
1
2
3
4
5
6
7
8
9
50
100
150
200
250
300
350
400
450
500
550
600
650
700
750
800
850
900
950
1000
1050
1100
1150
1200
1250
Frequency
Average number of siliques
a[CO2] e[CO2]
33. 0
5
10
15
20
25
50 100 150 200 250 300 350 400
Frequency
Average number of Primary Siliques
Primary Siliques a[CO2]
e[CO2]
0
2
4
6
8
10
12
14
16
5 10 15 20 25 30 35 40 45 50 55 60 65
Frequency
Proportion of Primary Silique number: Primary Axes number
Primary Siliques/Primary Axes
a[CO2]
e[CO2]
0
5
10
15
20
25
30
2 4 6 8 10
Frequency
Average number of Primary Axes
Primary Axes
a[CO2]
e[CO2]
34. 0
2
4
6
8
10
12
14
16
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80
Frequency
Average number of Secondary Axes number
Secondary Axes a[CO2]
e[CO2]
0
1
2
3
4
5
6
7
8
9
10
50
100
150
200
250
300
350
400
450
500
550
600
650
700
750
800
850
900
950
1000
Frequency
Average number of Secondary Silique number
Secondary Siliques a[CO2]
e[CO2]
0
5
10
15
20
25
30
5 10 15 20 25 30 35 40 45
Frequency
Proportion of Secondary Silique number: Secondary Axes number
Secondary Siliques/Secondary Axes a[CO2]
e[CO2]
38. Interaction ANOVA table
Characteristic Chromosome Marker Significance
Primary Axes 1 CO2 * jcc3 0.04
Primary Axes 1 CO2 * R64 0.04
Primary Siliques/Primary Axes 3 CO2 * ATA1 0.02
Primary Siliques/Primary Axes 3 CO2 * atts3983 0.058
Secondary Siliques/Secondary Axes 2 CO2 * BIO2b 0.002
Two-way ANOVA results indicating significant CO2 x genomic marker interaction for measured A.
thaliana architectural traits (p <0.05)
• Looked at the nature of the effect of the marker on CO2 response
• These markers showed significant marker x CO2 interactions
39. Conclusions
• Plant reproduction increases as [CO2]
increases
– Driven by meristematic activity
• Growth at e[CO2] alters the number and
location of regions of control within the
genome
• Effect of [CO2] on traits will depend on the
genetic background present at loci.
40. Implications
• QTL identified represent portions of the genome
that are most likely to undergo selection in
future conditions
• The identified genomic regions can also
be used as targets for crop breeding programs.
41. Acknowledgements
• Dr. Jonathan Fingerut
• Dr. Clint Springer
• Dr. Scott McRobert
• SJU Department of Biology
• Dana Semos, Sabrina Fecher, Holly Clark
• Dr. Nick Nicolaides
• My Family & Friends
• Fellow graduate students
• Kristina Orbe
BIOLOGY
