1. Genome evolution: a sequence-centric approach Lecture 7: Brief evolutionary history of everything

2. Probabilistic models Inference Parameter estimation Genome structure Mutations Population Inferring Selection (Probability, Calculus/Matrix theory, some graph theory, some statistics) Simple Tree Models HMMs and variants PhyloHMM,DBN Context-aware MM Factor Graphs DP Sampling Variational apx. LBP EM Generalized EM (optimize free energy)

3. Genome Structure, Genome Information Genome structure Genomic information Selection Mutation

4. Diversity: Brief description of the tree of life Genome structure: Size, Key features, Mobile elements Genome information: Proteins/RNA genes, regulatory elements Today: A lot of terminology, basic overview

5. RNA Based Genomes Ribosome Proteins Genetic Code DNA Based Genomes Membranes Diversity! ? ? 3.4 – 3.8 BYA – fossils?? 3.2 BYA – good fossils 3 BYA – metanogenesis 2.8 BYA – photosynthesis.. 1.7-1.5 BYA – eukaryotes.. 0.55 BYA – camberian explosion 0.44 BYA – jawed vertebrates 0.4 – land plants 0.14 – flowering plants 0.10 - mammals

7. Curated set of universal proteins Eliminating Lateral transfer Multiple alignment and removal of bad domains Maximum likelihood inference, with 4 classes of rate and a fixed matrix Bootstrap Validation Ciccarelli et al 2005

8. PROKARYOTESEUKARYOTES (Also present in the Planktomycetes)Presence of a nuclear membrane (also in b-protebacteria)Organelles derived from endosymbionts Tubulin-related protein, no microtubulesCytoskeleton and vesicle transport -Trans-splicing Rare – almost never in codingIntrons in protein coding genes, spliceosome Short UTRsExpansion of untranslated regions of transcripts Ribosome binds directly to a Shine-Delgrano sequence Translation initiation by scanning for start Nonsense mediated decay pathway is absentmRNA surveillance Single linear chromosomes in a few eubacteriaMultiple linear chromosomes, telomeres AbsentMitosis, Meiosis -Gene number expansion Some exceptions, but cells are smallExpansion of cell size

10. Biknots Uniknots Eukaryotes

11. Uniknots – one flagela at some developmental stage Fungi Animals Animal parasites Amoebas Biknots – ancestrally two flagellas Green plants Red algea Ciliates, plasmoudium Brown algea More amobea Strange biology! A big bang phylogeny: speciations across a short time span? Ambiguity – and not much hope for really resolving it

12. Vertebrates Sequenced Genomes phylogeny Fossil based, large scale phylogeny

13. Marmoset Macaque Orangutan Chimp Human Baboon Gibbon Gorilla 0.5% 0.8% 1.5% 3% 9% 1.2% Primates

14. Flies

15. Yeasts

16. Genome Size

17. Why larger genomes? 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.

18. 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)

19. 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 Can we model genome size evolution in a quantitative way?

20. Genome Structural features: centromeres/telomeres Rat – Partly acrocentric Human Centromeres are essential and universally important for proper cell division, but are highly diverging among species Sattelites and repeats Pericentromeric regions – more repeats Telomeres are critical for genome maintenance Sub telomeric regions – also repetitive May be key to nuclear structure?

21. Genome Structural features: nuclear organization The nucleus must be organized to allow functional transcription and replication Incredibly dense mesh of chromosomes, cytoskeleton, membranes Transcription factories / chromosomal territories “spacer DNA” may affect physical organization in unexpected ways Inter- and Intra- chromosomal interactions Entire genome may participate in regulating interactions

22. Genomic information: Protein coding genes

23. Modeling protein coding genes Modeling protein structure/function Structure is complex Dependencies are not confined by gene linear coding http://predictioncenter.org/

24. Genomic information: the gene repertoire is evolving by duplication and loss

25. Genome information: Introns/Exons

26. 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 - ???

27. miRNA clusters

28. snRNA works by binding other RNAs RNA structure affects function

29. Computational perspective: finding and understanding RNAs and their evolution

30. Ultra-high throughput sequencing is transforming all aspects of biology

32. Genome information: regulatory elements Computational perspective: finding and understanding TFBSs Specialized proteins can bind DNA in a sequence specific fashion Genomes can therefore control the level of affinity of each region to a large set of DNA binding proteins DNA binding sites are typically short (<20bp) Multiple binding sites at different affinities participate in regulation

33. The regulatory process is likely to less deterministic and discrete the this beautiful idealized sea urchin regulatory network Each regulatory interaction is parameterized and many additional weak interaction participate in the Process Evolution of regulatory regions involve more than a small set of discrete 20bp sites

34. Chromatin Immunoprecipitation is mapping DNA binding sites

35. Structure meets information: packaging and chromosomal interactions are critical for proper genome function

36. Structure meets information: HOX clusters as an example Hox genes are important developmental regulators Present in linear clusters, preserving order Their expression is frequently coordinate with the gene order 4 HOX clusters are present in the human genome Additional gene clusters: Protocadherins, Olfactory receptors, MAGE genes, Zinc fingers Additional smaller groups of related regulators are co-located

37. Mapping chromosomal interactions: 4C

38. Repeats: selfish DNA Genome FractionCopiesClass 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

39. Retrotransposition via RNA

40. Repeats: short tandems, satellites DNA-based transposons do not involve an RNA intermediate, and are quite rare. Satellite DNA duplicate by Replication slippages which is enhanced for specific sequences. Abundant near telomeres and centromeres. Some of these are still a mystery. Retrotransposition is generally sloppy and noisy – so elements die out quickly Element proliferation appears in evolutionary bursts.

41. 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)

42. Summary – History/Phylogeny: –Early phylogenetics can be inferred using genome sequences, but conclusions are not always reliable –Maximum likelihood models sometime depends on the gene/genomic region analyzed, genome is highly heterogeneous at all levels. –The major clades, phylogeny of model organisms and sequenced genomes Genome structure –Size and its consequences –Packaging and nuclear organization –Mutational effects and differences –Selfish DNA Genome information –Protein coding genes –RNA genes –Transcription factor binding sites –Chromosomal organization and DNA codes that affect it