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 transcript:

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

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?

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?

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?

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

Measuring expression distance Tissue 2 Tissue 1 Tissue 3

Measuring duplication age Rice Athal1 Athal2 T1 T2

Divergence between duplicates Expression distance Age of duplication

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

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?

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

Comparative genomic hybridization on a chip

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

Stay tuned!

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?

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

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)?

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

Sizes of co-expressed clusters

Measuring recombination rate

Expression distance and recombination rate data:  expdis2 and recrate normal-z = -3.2743, p-value = 0.0005 alternative hypothesis: true rho is less than 0 sample estimates:         rho  -0.0671727 Spearman = -0.07 p = 0.0005

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