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Genome evolution There are both proximate and ultimate explanations in molecular biology Mutation continually generates variation in genome content and.

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Presentation on theme: "Genome evolution There are both proximate and ultimate explanations in molecular biology Mutation continually generates variation in genome content and."— Presentation transcript:

1 Genome evolution There are both proximate and ultimate explanations in molecular biology Mutation continually generates variation in genome content and structure Raw material for natural selection Potential for non-adaptive evolution Function is too blunt a concept for genome evolution

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3 The genome as phenotype
Evolutionary biologists study both pattern and process, or mechanism What unexpected patterns do we see Within genomes? By comparisons among them? What can we infer about proximal and ultimate mechanisms by Catching evolution red-handed? Testing genome evolutionary models?

4 Three open questions How rapidly do the expression profiles of duplicated genes diverge? What is the extent of polymorphism in gene order within species? What is responsible for physical clusters of co-expressed genes?

5 Three open questions How rapidly do the expression profiles of duplicated genes diverge? What is the extent of polymorphism in gene order within species? What is responsible for physical clusters of co-expressed genes?

6 Arabidopsis MPSS With Blake Meyers and Barry Kesner
Massively parallel signature sequencing Bead based expression monitoring Estimates for nearly all genes Estimates are good even at low expression Sample eight tissues from Arabidopsis thaliana Couple with genome-wide phylogenetic analysis of duplicated genes

7 Measuring expression distance
Tissue 2 Tissue 1 Tissue 3

8 Measuring duplication age
Rice Athal1 Athal2 T1 T2

9 Divergence between duplicates
Expression distance Age of duplication

10 Does the pattern differ for
Tandem duplicates? Transposed duplicates? Polyploidy remnants?

11 Three open questions How rapidly do the expression profiles of duplicated genes diverge? What is the extent of polymorphism in gene order within species? What is responsible for physical clusters of co-expressed genes?

12 Gene order polymorphism
With Jason Lieb and Jennifer Kriss Using high-throughput methods to compare gene order in two yeast strains One strain known to lack 7 ORFs present in the reference genome The key ingredients Comparative genomic hybridization to a whole-genome chip Whole-genome genotyping in multiple haploid recombinants from a cross between the two strains

13 Comparative genomic hybridization on a chip

14 Detecting gene transposition
Genes that are in different chromosomal positions in the two strains will appear as deletions and amplifications in the recombinant progeny

15 Stay tuned!

16 Three open questions How rapidly do the expression profiles of duplicated genes diverge? What is the extent of polymorphism in gene order within species? What is responsible for physical clusters of co-expressed genes?

17 Natural selection and clusters of co-expressed genes
With Jianhua Hu Neighboring genes with similar expression profiles are more common than expected in C. elegans Two classes of explanation Adaptive: more efficient, less error-prone Maladaptive: due to recent transpositions

18 Selection and recombination
In regions of low recombination deleterious mutations can hitch-hike to high frequency along with favorable ones favorable mutations are kept at low frequency by linkage to deleterious ones The effectiveness of natural selection is directly related to recombination rate Are clusters found in regions of high recombination (adaptive) or low (maladaptive)?

19 Measuring the co-expression of neighboring genes
Measure the distance in expression space from central gene to each neighbor If neighboring genes are co-expressed, the average of these distances will be smaller than for non-neighboring genes d1 d2 d3 d4 X

20 Sizes of co-expressed clusters

21 Measuring recombination rate

22 Expression distance and recombination rate
data:  expdis2 and recrate normal-z = , p-value = alternative hypothesis: true rho is less than 0 sample estimates:         rho   Spearman = -0.07 p =

23 Opportunities abound! The field of genome evolution is a vast and open playing field Gads of genome data Some seriously cool experimental techniques A golden age in bioinformatics and molecular evolution


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