The evolution of a disease resistance pathway in tomato [Elektronische Ressource] / vorgelegt von Lukasz Grzeskowiak

Lukasz Grzeskowiak

Sujets

• Biologie

Informations

• Publié par: ludwig-maximilians-universitat_munchen
• Publié le: 01 janvier 2009
• Nombre de lectures: 20
• Langue: English
• Poids de l'ouvrage: 4 Mo

Extrait

The evolution of a disease
resistance pathway in tomato


Lukasz Grzeskowiak






























München 2009


























































The evolution of a disease
resistance pathway in tomato












Dissertation
an der Fakultät für Biologie
der Ludwig-Maximilians-Universität
München






vorgelegt von
Lukasz Grzeskowiak







München, den 01. Oktober 2009





























Erstgutachter: Prof. Dr. Wolfgang Stephan
Zweitgutachter: Prof. Dr. John Parsch
Tag der mündlichen Prüfung: 07. Dezember 2009



Summary



In this dissertation research I describe natural variation of five genes at different points
in a signaling pathway controlling disease resistance to a bacterial pathogen of tomato,
Pseudomonas syringae. Since these genes are involved in defense response to the same
pathogen, I evaluate how position in the genetic network influences the selective
constraint acting on these molecules. Three components of the pathway are encoded by
resistance genes that are tightly linked in the tomato genome. Pto and Fen kinases, in
complex with the Prf NBS-LRR protein, bind bacterial pathogen effectors and trigger a
specific recognition event which initiates a signal leading to an immune response.
Furthermore, these host proteins have multiple downstream interaction partners and
experience posttranslational regulation such as phosphorylation and ubiquitination.
Genes throughout signaling pathways controlling these different processes can be
subject to natural selection. I use this system to address specific questions about
evolution of a resistance gene complex. I analyze sequences of three resistance genes in
natural populations of wild tomato species Solanum peruvianum, collected in South
America at different altitudes and habitats. This outcrossing species shows the highest
level of polymorphism among tomatoes. The patterns of nucleotide diversity and levels
of genetic differentiation between populations suggest that these resistance genes have
experienced a mixture of natural selection including not only purifying, but also
balancing and positive selection. In addition to standard population genetic analyses, I
evaluated the statistical associations between polymorphisms of the interacting proteins
to determine whether epistatic selection has contributed to the observed patterns of
balancing selection through the maintenance of particular combination of alleles. Using
bioinformatic analyses of protein sequences, I found a set of significant associations,
which could be due to the structural or functional coadaptation and accommodation
between these interacting protein partners. I mapped these sites onto known and
predicted structures of Pto, Fen and Prf to visualize putative coevolving regions
between proteins. These specific positions are candidates for future functional studies.




Contents




CHAPTER 1: INTRODUCTION .................................................................................. 1
1. Selective constraint and coevolution in protein pathways ...........................................1
2. Epistatic selection ........................................................................................................3
3. Linkage disequilibrium ................................................................................................5
4. Case studies of epistatic selection................................................................................6
5. Disease resistance in plants and animals....................................................................10
6. Tomato as a model system to study evolution of disease and stress resistance.........14
7. Solanum peruvianum .................................................................................................16
8. The Pto signaling pathway.........................................................................................17
9. This research ..............................................................................................................21
CHAPTER 2: MATERIALS AND METHODS ......................................................... 25
1. Plant materials............................................................................................................25
2. Gene amplification and sequencing ...........................................................................26
3. DNA sequence analyses.............................................................................................29
4. Protein sequence analyses..........................................................................................31
CHAPTER 3: RESULTS .............................................................................................. 35
1. Nucleotide diversity in five genes from the Pto signaling pathway ..........................35
2. Population differentiation in Pto, Fen and Prf ...........................................................45
3. Linkage disequilibrium between Pto/Fen and Prf......................................................52
4. Partitioning of LD variance components ...................................................................57
5. Correlated substitutions in proteins ...........................................................................60
6. Candidate sites in Pto.................................................................................................62
7. Candidate sites in Fen ................................................................................................66
8. Candidate sites in Prf68
CHAPTER 4: DISCUSSION...................................................................................... 83
1. Evolution of genes at different points in a signaling pathway in tomatoes ...............83
2. Detecting epistatic selection between interacting proteins ........................................87
3. Distribution of natural selection across genes in the Prf complex.............................92
4. Future directions ........................................................................................................95
Appendix: Polymorphic amino acid sites at Pto, Fen and Prf ..................................................98
Abbreviations ......................................................................................................................102
References ...........................................................................................................................104











































CHAPTER 1

INTRODUCTION










1. Selective constraint and coevolution in protein pathways

The rate of evolution can differ radically among proteins (GILLESPIE 1991; LI 1997).
This rate variation can be attributed to differences in selective constraint. Proteins
subject to greater constraint should show lower rates of amino acid substitution while
those that are less constrained should show higher rates. Some of the most variable
proteins are those involved in pathogen resistance and self/non-self recognition
(HUGHES and NEI 1989; TAKAHATA et al. 1992; HEDRICK 1999; CHARLESWORTH 2002;
ROSE et al. 2004). This cannot be explained by lack of evolutionary constraint, but
instead by natural selection maintaining variation. Understanding these differences in
constraints and the forces determining them is one of the major challenges of modern
biology.
Many proteins do not operate alone, but as components of complex pathways or
metabolic networks. The protein connectivity (i.e. the number of protein interactions
with the other components of a network) is determined by structural and physico-
chemical properties of interacting partners. Thus, the specificity of interactions may
determine the level of constraint and hence the rate of molecular evolution. Indeed, in
yeast the connectivity of well-conserved proteins in the network is negatively correlated
with their rate of evolution. Proteins that have many interactors generally evolve slowly
as a great