Presentation is loading. Please wait.

Presentation is loading. Please wait.

Genome Evolution. Amos Tanay 2009 Genome evolution Lecture 10: Comparative genomics, non coding sequences.

Similar presentations


Presentation on theme: "Genome Evolution. Amos Tanay 2009 Genome evolution Lecture 10: Comparative genomics, non coding sequences."— Presentation transcript:

1 Genome Evolution. Amos Tanay 2009 Genome evolution Lecture 10: Comparative genomics, non coding sequences

2 Genome Evolution. Amos Tanay 2009 Why larger genomes? Ameobe dubia – 670Gb! S. cerevisae is 0.3% of human, D. melanogaster is 3% Selflish DNA – –larger genomes are a result of the proliferation of selfish DNA –Proliferation stops only when it is becoming too deleterious Bulk DNA –Genome content is a consequence of natural selection –Larger genome is needed to allow larger cell size, larger nuclear membrane etc.

3 Genome Evolution. Amos Tanay 2009 Why smaller genomes? Metabolic cost: maybe cells lose excess DNA for energetic efficiency –But DNA is only 2-5% of the dry mass –No genome size – replication time correlation in prokaryotes –Replication is much faster than transcription (10-20 times in E. coli)

4 Genome Evolution. Amos Tanay 2009 Mutational balance Balance between deletions and insertions –May be different between species –Different balances may have been evolved In flies, yeast laboratory evolution –4-fold more 4kb spontaneous insertions In mammals –More small deletions than insertions Mutational hazard No loss of function for inert DNA –But is it truly not functional? Gain of function mutations are still possible: –Transcription –Regulation Differences in population size may make DNA purging more effective for prokaryotes, small eukaryotes Differences in regulatory sophistication may make DNA mutational hazard less of a problem for metazoan

5 Genome Evolution. Amos Tanay 2009 Repeats: selfish DNA

6 Genome Evolution. Amos Tanay 2009 Retrotransposition via RNA Genome Fraction CopiesClass 20.4%868,000 (only ~100 active!!) LINEs 13.1%1,558,000 (70% Alu) SINEs 8.3%443,000LTR elements 2.8%294,000Transposons Repetitive elements in the human genome

7 Genome Evolution. Amos Tanay 2009 Burst of repeats activity Han et al. 2005

8 Genome Evolution. Amos Tanay 2009 Age of repeats in the human genome

9 Genome Evolution. Amos Tanay 2009 DNA and gene distribution in the isochore families of the human genome Bernardi G. PNAS 2007;104:8385-8390 These trends are quite clear. But the existence of distinct isochore classes can be questioned

10 Genome Evolution. Amos Tanay 2009 Bernardi G. PNAS 2007;104:8385-8390 The selection hypotheses on the origin of G+C content heterogeneity

11 Genome Evolution. Amos Tanay 2009 Genomic information: Protein coding genes

12 Genome Evolution. Amos Tanay 2009 Genome information: RNA genes mRNA – messenger RNA. Mature gene transcripts after introns have been processed out of the mRNA precursor miRNA – micro-RNA. 20-30bp in length, processed from transcribed “hair-pin” precursors RNAs. Regulate gene expression by binding nearly perfect matches in the 3’ UTR of transcripts siRNA – small interfering RNAs. 20-30bp in length, processed from double stranded RNA by the RNAi machinary. Used for posttranscriptional silencing rRNA – ribosomal RNA, part of the ribosome machine (with proteins) snRNA – small nuclear RNAs. Heterogeneous set with function confined to the nucleus. Including RNAs involved in the Splicesome machinery. snoRNA – small nucleolar RNA. Involved in the chemical modifications made in the construction of ribosomes. Often encode within the introns of ribosomal proteins genes tRNA – transfer RNA. Delivering amino-acid to the ribosome. piRNA – silencing repeats in the germline

13 Genome Evolution. Amos Tanay 2009 Gene content in the genome M. Lynch

14 Genome Evolution. Amos Tanay 2009 Genome information: Introns/Exons

15 Genome Evolution. Amos Tanay 2009 Pseudogenes Genes that are becoming inactive due to mutations are called pseudogenes mRNAs that jump back into the genome are called processed pseudogenes (they therefore lack introns) M. Lynch

16 Genome Evolution. Amos Tanay 2009 Adaptive evolution of non-coding DNA in Drosophila (P. Andolfatto, 2005) 12 D. melanogaster collected in Zimbabwe 188 regions of ~800bp, surveyed for polymorphisms compared to sequences of D. simulans to measure divergence Classified loci according to genomic context

17 Genome Evolution. Amos Tanay 2009 Estimating  Theorem: Let u be the mutation rate for a locus under consideration, and set  =4Nu. Under the infinite sites model, the expected number of segregating sites is: The Waterston estimator for theta is: Definition: Let  ij count the number of differences between two sequences. The average number of pairwise difference in a sample of n individuals is: Theorem: as always,  =4Nu. We have:

18 Genome Evolution. Amos Tanay 2009 Tajima’s D Theorem: as always,  =4Nu. We have: Proof: Going backwards. Coalescent is occuring before mutation in a rate of: After one mutation occurred, we again have the same rate so overall: The expected value of this geometric series is  and so is the average of all pairs. Definition: Tajima’s D is the difference between two estimators of  :

19 Genome Evolution. Amos Tanay 2009 Tajima’s D for classes of drosophila sequence Definition: Tajima’s D is the difference between two estimators of  : High D values: allele multiplicities are spread more evenly than expected – (why?) Low D values: More rare alleles are present (Why?)

20 Genome Evolution. Amos Tanay 2009 Adaptive evolution of non-coding DNA in Drosophila (P. Andolfatto) The proportion of divergence driven by positive selection:  = 1–(D S P X /D X P S )

21 Genome Evolution. Amos Tanay 2009 Phastcons (A. Siepel) Siepel A. et.al. Genome Res. 2005;15:1034-1050 Each model is context-less Transition parameters are kept fixed – this determine the fraction of conserved sequence Inference on the phyloHMM -> inferred conserved model posteriors Use threshold to detect contiguous regions of high conservation posterior Learning the branch lengths

22 Genome Evolution. Amos Tanay 2009 Siepel A. et.al. Genome Res. 2005;15:1034-1050 Phastcons parameters

23 Genome Evolution. Amos Tanay 2009 Fixation probabilities and population size: what selection coefficient can drive a 70% decrease in substitution rate (if N_e = 10,000)?

24 Genome Evolution. Amos Tanay 2009 ENCODE

25 Genome Evolution. Amos Tanay 2009 481 segment longer than 200bp that are absolutely conserved between human, mouse and rat (Bejerano et al 2005) What are these elements doing? Why they are completely conserved? 4 Knockouts are not revealing significant phenotypes.. Ahituv et al. PloS Biolg 2007 Ultra-conserved elements

26 Genome Evolution. Amos Tanay 2009 Katzman et al., Science 2007 Population genetics do suggest ultraconserved elements are under selection Separating mutational effects from selective effect is still a challenge… Ultra-conserved elements


Download ppt "Genome Evolution. Amos Tanay 2009 Genome evolution Lecture 10: Comparative genomics, non coding sequences."

Similar presentations


Ads by Google