M. cinxia image

Functional genomics of a metapopulation: population dynamics, life history traits, and genetic mechanisms in time and space

We are in the midst of a collaborative project (supported by a NSF Biocomplexity grant) with Dr. Ilkka Hanski, University of Helsinki, to examine relationships between metapopulation dynamics and the dispersal ability and fecundity of female Glanville fritillary butterflies.  Like most species, these butterflies exist as small populations at scattered habitat patches.


    
Center: Map of occupied and unoccupied habitat patches suitable for Glanville Fritillary butterflies in the Aland islands during 2002.  Hanski's team has surveyed this patch network every year since 1993. This long-term data set provides a wealth of data and infrastructure for studies of metapopulation processes. Right: A granite outcrop in the Aland islands.  Plants used by Glanville Fritilllaries for oviposition and larval feeding grow in the thin soil that border these outcrops.  Areas between such habitat patches are predominately agricultural fields and forests, unsuitable for host plants or fritillaries.

    Individual Glanville Fritillary populations frequently go extinct, but local extinctions are balanced, on average, by the founding of new populations by individual females that have dispersed away from their natal patch. Using a spatially realistic model of the evolution of dispersal rate in this metapopulation, Hanski et al. (2004) predicted that females that disperse successfully and establish a new local population have a higher dispersal ability than the average female in the metapopulation.  Furthermore, this difference should increase with patch isolation, because the most isolated patches should be especially difficult to reach for females with poor flight capacity.   Empirical studies that we began in 2004 have shown that the F1 female offspring of new population founders do indeed have a higher flight metabolic capacity and increased fecundity compared to females in old populations (those that have persisted for > 5 years), particularly when the new populations are poorly connected in the population network. 

 Haag et al. 2005 figure

Figure legend:  Left panel -Theoretical predictions for the distribution of average female dispersal ability of Glanville fritillary butterflies from old and newly founded populations, in habitat patches that vary in their connectivity (inverse of isolation) within a metapopulation.  Right panel – Mass-adjusted flight metabolic capacity of female butterflies that we measured from this metapopulation.

Quicktime movie of open-flow respirometry measurement of Glanville fritillary flight metabolic rate


What are the mechanistic bases for differences in dispersal ability and flight metabolism?

    During the summer of 2006, we measured peak flight metabolic rate for 2-day old lab-reared F2 female offspring of mothers that were new population founders or from old populations.  The data shown below represent 67 butterflies from 25 families and 22 populations.  A general linear model that includes body mass, population age, and family nested within population age (a random effect) showed a significant effect of population age on peak metabolic rate (p = 0.017; 3.46 vs 3.00 ml CO2 hr-1, a 15% difference).  This result  shows that there is a lasting and probably heritable effect of population history on a major physiological trait of butterflies.  Thoraces of these butterflies have been flash-frozen and saved for RNA extraction for use in microarray analyses that will determine the global gene expression differences that underlie these differences in metabolism.  A graduate student, Kristjan Niitepõld, is using mark recapture and telemetry studies to determine how variation in flight metabolic rate affects movement behavior of females in the field.
plot of metabolic rate within families Marden et al., in prep.



    We have successfully used a next-generation sequencing technology (454 pyrosequencing performed in Stephan Schuster's lab) to characterize a large portion of the M. cinxia transcriptome (expressed genes; cDNA).  Our paper reporting this work is:
 J. C. Vera, C.W. Wheat, H.W. Fescemyer, M.J. Frilander, D.L. Crawford, I. Hanski, J.H. Marden.  2008. Rapid transcriptome characterization for a non-model organism using 454 pyrosequencing.  In press, Molecular Ecology 17: 1636–1647

Flowchart diagram of this portion of the work

        M. cinxia sequence database search tool

Using those sequence data, we constructed a 44K feature Agilent microarray containing 3x replication of about 13,500 gene probes (representing 9.3K genes with unique annotation).  We are presently using this microarray to test the hypothesis that there are significant differences in gene expression between 2-day old female butterflies from old versus new popoulations (the same individuals represented in the figure above).  Because we also know the flight metabolic rate of these females, we will be able to also determine the relationship between expression level of individual genes and metabolism.

Here is one of our arrays hybridized with labeled RNA from the abdomen of two 2-day old female butterflies, where yellow spots represent equal expression levels, and red or green represent expression of that gene primarily in one of the two butterflies.  Our overall experiment involves comparisons of 20 heads, 40 thoraces, and 20 abdomens.
microarray image


From the assembled 454 sequences, we have also identifed thousands of SNPs, including 149 at first and second codon position sites (i.e. likely to cause amino acid polymorphisms).  These are candidate loci to examine for association with dispersal, flight metabolism, and sorting of genotypes by metapopulation dynamics.


Identification of a polymorphic locus with these traits:

    We have identified allelic variation in one candidate gene (Pgi) that is significantly associated with the behavioral and physiological phenotypes of interest.

pgi effects plot
   

Haag, C.R., Saastamoinen, M., Marden, J.H., and Hanski, I. 2005.  A candidate locus for variation in dispersal rate in a butterfly metapopulation.  Proceedings of the Royal Society of London B 272, 2449–2456. (full text)

This result (similar to what Ward Watt has found in Colias butterflies) stimulated Ilkka Hanski and his former student, Ilik Saccheri, to rexamine their old survey data in which Pgi had been used as a marker for polymorphism and inbreeding.  They discovered that Pgi allele frequency has surprisingly strong effects on year-to-year population growth, in a context-dependent manner. In isolated patches where immigration has little effect, a high frequency of one Pgi allele is favorable for population (deme) growth in small patches, whereas a high frequency of the other most common Pgi allele is favorable for population growth in large patches.  Allelic variation at six other polymorphic loci showed no associations with population growth. 


Hanski, I. and Sacherri, I.  2006.  Molecular-level variation affects population growth in a butterfly metapopulation.  PLoS Biology 4 (5): e29.  (full text link)



In an effort led by our post-doc Christ Wheat, we are presently performing evolutionary genetic analyses of the Pgi gene in this species.  Chris has previously published a similar analysis for the Pgi gene in Colias butterflies.

Work in progress indicates that alternative splicing of the muscle gene troponin-t also plays interesting roles, apparently by adjusting muscle performance in a phenotypically plastic manner in response to individual condition.  We have recently published a short review of some of the ways that alternative splicing affects whole organism-level traits.

Ultimately, we will use the genetic information we are collecting to inform models and make predictions about the spatial dynamics of particular alleles and metabolic and life history traits.  Overall results from this project will provide an unusually detailed level of understanding of how and why genetic variation is maintained in nature, and how genetic variation is affected by habitat fragmentation and population turnover. 



Publications arising from this NSF grant, as of 7/08 (list includes projects that this grant supported in full or only partially):

Bejan, A. and Marden, J.H.  2006.  Constructal theory of running, swimming, and flying.  Chapter 13.8, pp. 805-815, in Advanced Engineering Thermodynamics, 3rd Edition, John Wiley & Sons.

Bejan, A. and Marden, J.H.  2006.  Constructing animal locomotion from new thermodynamics theory.  American Scientist 94, 342-349. (A translated version appears in the French popular science magazine, Pour la Science 346, 68-73)

Bejan, A. and Marden, J.H.  2006.  Unifying constructal theory for scale effects in running, swimming, and flying. Journal of Experimental Biology 209, 238-248.

Fischer, H. M., C. W. Wheat, D. G. Heckel and H. Vogel, 2008  Evolutionary origins of a novel host plant detoxification gene in butterflies.  Molecular Biology and Evolution 25(5):809-820.

Haag, C.R., Saastamoinen, M., Marden, J.H., and Hanski, I. 2005.  A candidate locus for variation in dispersal rate in a butterfly metapopulation.  Proceedings of the Royal Society of London B, 272, 2449-2456.

Hagner-Holler, S., Pick, C., Girgenrath,S., Marden, J.H., and Burmester, T. 2007.  Diversity of stonefly hexamerins and implication for the evolution of insect storage proteins. Insect Biochem. Mol. Biol. 37:1064-74.

Hanski, I. & Saccheri, I. 2006. Molecular-level variation affects population growth in a butterfly metapopulation. PLoS Biology 4:719-726.

Marden, J.H.  2005. Scaling of maximum net force output by motors used for locomotion. Journal of Experimental Biology 208, 1653-64.

Marden, J.H.  2008.  Quantitative and evolutionary biology of alternative splicing: how changing the mix of alternative transcripts affects phenotypic plasticity and reaction norms.  Heredity, 100, 111–120.

Marden, J.H.  2008. Dragonfly flight performance: a model system for biomechanics, physiological genetics, and animal competitive behavior.  In: Dragonflies: Model Organisms for Ecological and Evolutionary Research, ed. A. Córdoba-Aguilar.  Oxford University Press. In press.

Marden, J.H.  2008. Evolution and physiology of flight in aquatic insects.  In: Aquatic Insects: Challenges to Populations, ed. J. Lancaster.  CABI Press. In press.

Marden, J.H., Fescemyer, H.W., Saastamoinen, M., MacFarland, S.P., Vera, J.C., Frilander, M.J., and Hanski, I.  Weight and nutrition affect pre-mRNA splicing of a muscle gene associated with performance, energetics and life history.  J. Exp. Biol, submitted.

Niitepõld, K., Smith, A.D. , Osborne, J.L., Reynolds, D.R., Carreck, N.L., Martin, A.P., Marden, J.H., Ovaskainen, O. and Hanski,  I.  Flight metabolic rate and Pgi genotype influence butterfly dispersal rate in the field.  Submitted, Ecology.

Orsini, L., C. W. Wheat, C. R. Haag, J. Kvist, M. J. Frilander, and I. Hanski Large-scale SNP genotyping of the Pgi gene in the Glanville fritillary butterfly reveals reduced fitness of homozygous individuals. Molecular Ecology, submitted.

Ovaskainen, O., A. D. Smith, J. L. Osborne, D. R. Reynolds, N. L. Carreck, A. P. Martin, K. Niitepõld, and I. Hanski. Tracking butterfly movements with harmonic radar reveals an effect of population age on movement frequency.  PNAS, in press.

Saastamoinen, M. & Hanski, I. Genotypic and environmental effects on flight activity and oviposition in the Glanville fritillary butterfly. American Naturalist, in press.

Schilder, R.J. and Marden, J.H.  2006.  Metabolic syndrome and obesity in an insect. Proceedings of the National Academy of Science 103, 18805-18809.

Schilder, R.J. and Marden, J.H.  2007.  Metabolic syndrome in insects triggered by gut microbes.  Journal of Diabetes Science and Technology 1(5): 794-796. (Invited commentary)

Schilder, R.J. and Marden, J.H.  2007. Parasites, performance and proteomics: effects of gregarine gut parasites on dragonfly flight muscle composition and function.  Journal of Experimental Biology, 210: 4298-4306.

Vera* J. C., Wheat* C.W., Fescemyer H.W., Frilander M.J., Crawford D.L., Hanski I., Marden J.H..  2008. Rapid transcriptome characterization for a non-model organism using 454 pyrosequencing. Molecular Ecology 17: 1636–1647. (cover)
            *shared first authorship

Wheat, C. W. Rapidly developing functional genomics in ecological model systems via 454 transcriptome sequencing. Genetica, accpeted pending minor revision.

Wahlberg, N. and C. W. Wheat, 2008. Genomic outposts serve the phylogenomic pioneers: designing novel nuclear markers for genomic dna extractions of Lepidoptera.  Systematic Biology 57(2):231-42.

Wheat, C. W., H. Vogel, U. Wittstock, M. F. Braby, D. Underwood et al., 2007 The genetic basis of a coevolutionary key innovation. Proc Natl Acad Sci U S A. 104(51):20427-31.

Wheat, C.W., and Watt, W.B.  2008. A mitochondrial-DNA-based phylogeny for some evolutionary-genetic model species of Colias butterflies (Lepidoptera, Pieridae).  Molecular Phylogenetics and Evolution, in press.

Wheat, C. W., C. R. Haag, J. H. Marden, I. Hanski, M. J. Frilander Evidence for balancing selection at a candidate gene (Pgi) influencing ecological dynamics in a butterfly metapopulation. In prep for submission to Molecular Biology and Evolution.


                                                           PLoS cover      MolEcol cover

    Stayed tuned; there is more interesting stuff still to come.
This material is based upon work supported by the National Science Foundation under Grant No. 0412651
and the Finnish Center of Excellence Program