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. HealyAdvisor: Dr. Jonathan T. Fingerut

Dr. Clint J. Springer

Thursday, July 12, 2012

Thesis Presentation

Briena Healy

Advisor: Dr. Jonathan Fingerut

Black Flies, Family Simuliidae

• Order Diptera, Family Simuliidae, sp. Simulium tribulatum.

•Common, usually a biting pest.

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

Black Fly Larvae

• Found on solid substrates within streambeds.

• Heavily reliant upon flow at different scales

– Distribution

– Protection

– Food

FLOW

Research question

What effects distribution on the scale of a

single bed element?

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?

The one-stone model

Hemi-cylinder placed perpendicular to the flow

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Distance from Top (cm)

Relative Flow Speed by Position at Different Settings

Slow Flow

Medium Flow

High Flow

Flow data

(12 cm/s)

(26 cm/s)

(56 cm/s)

The Database

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

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Individual Neonate positions under Medium (26 cm/s) Flow

Individual Neonate positionaldata under Medium Flow

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Distance on the hemi-cylinder (mm)

Last position of Individual Neonates under Medium (26 cm/s ) flow

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Distance on hemi-cylinder in cm

Mass Addition Late Instar

Individual Late Instar

Slow (12 cm/s) flow

Density on distribution

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

Determining effects of past experiences

• Calculated and compared the starting and ending flow conditions.

• Tortuosity of paths travelled in respect to starting velocity

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 6-10Ratio of Linear Distance:

Path shape

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.

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Starting Velocity (cm/s)

Late-Instar larvae In Low speed flow (12 cm/s)

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Difference in velocity for Late-Instar larvae under Low speed flow (12 cm/s)

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

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Neonate larvae in Low speed flow (12 cm/s)

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Difference in velocity for Neonate larvae under Low speed flow (12 cm/s)

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

Isolating genomic regions in Arabidopsis responsible for changes…

Briena Healy

Advisor: Dr. Clint Springer

Rising Atmospheric CO2

Photosynthesis +40%

Carbohydrates +45%

Total Mass +35%

Seed Yield +25%

Ainsworth et al. 2002

Plant LevelResponses

Ambient [CO2] = 350-370 ppm

Elevated [CO2] = 650-700 ppm

150 ppm

270 ppm350 ppm

700 ppm

Flowering Time and Elevated [CO2]

Springer & Ward, 2007

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28

32Ireland

Norway

Sweden

Portugal

Austria

BC, Canada

Cape Verdi

Tadjikistan

Ukraine

Belgium

380 700

Tim

e o

f F

low

ering

(d

)

[CO2] (ppm)

Genetic Variation in Flowering Time

Springer & Ward. 2007 New Phytol.

What are the molecular and physiological mechanisms controlling reproductive responses to elevated atmospheric CO2 in Arabidopsis thaliana?

Research Question

© European Communities, 1995-2009

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

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

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.

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

Averages days until Flowering

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Average days

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Average Total Silique number

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Average number of Primary Siliques

Primary Siliques a[CO2]e[CO2]

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Proportion of Primary Silique number: Primary Axes number

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e[CO2]

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Average number of Primary Axes

Primary Axesa[CO2]e[CO2]

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Average number of Secondary Axes number

Secondary Axes a[CO2]e[CO2]

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Proportion of Secondary Silique number: Secondary Axes number

Secondary Siliques/Secondary Axes a[CO2]e[CO2]

The existence of a significant QTL varying by CO2 concentration

Summary QTL table slideTrait CO2 concentration Number of sig. QTL Chromosome

Flowering Time Elevated 1 2

Ambient 4 1, 4, 5, 6

Total Siliques Elevated 2 5

Ambient 2 1

Primary Axes Elevated 1 5

Ambient - -

Primary Siliques Elevated 1 1, 5, 5

Ambient 3 5

Primary Siliques/ Primary Axes

Elevated3

4, 5, 5

Ambient - -

Secondary Axes Elevated 7 1, 1, 2, 3, 3, 5, 5

Ambient 8 1, 1, 1, 2, 3, 3, 4, 5

Secondary Siliques Elevated 3 2, 5, 5

Ambient 1 4

Secondary Siliques/ Secondary Axes

Elevated - -

Ambient 1 4

Number of QTL by Trait

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Interaction ANOVA table

Characteristic Chromosome Marker Significance

Primary Axes 1 CO2 * jcc3 0.04Primary Axes 1 CO2 * R64 0.04Primary Siliques/Primary Axes 3 CO2 * ATA1 0.02

Primary Siliques/Primary Axes 3 CO2 * atts3983 0.058Secondary 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

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.

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.

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