1 / 94

Orthology predictions for whole mammalian genomes

Orthology predictions for whole mammalian genomes. Leo Goodstadt MRC Functional Genomics Unit Oxford University. Mammalian Genomes. How does our genome, and how do our genes, differ from those of other mammals and other vertebrates?. Great Expectations.

hayley
Download Presentation

Orthology predictions for whole mammalian genomes

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Orthology predictions for whole mammalian genomes Leo Goodstadt MRC Functional Genomics Unit Oxford University

  2. Mammalian Genomes How does our genome, and how do our genes, differ from those of other mammals and other vertebrates?

  3. Great Expectations

  4. We did not appreciate how much functional sequence there would be. We did not appreciate how hard it would be to ‘read off’ functions from the human genome. We had no idea that individual human genomes can differ so much! So why is it taking so long to understand a simple genome • How much? • Species-specific genes? • Human genomes

  5. How do we find function in the genome? • Nothing in Biology Makes Sense Except in the Light of Evolution. Theodosius Dobzhansky (1900-1975).

  6. The dawn of mammalian comparative genomics Sanity checks for all mammalian projects:Lessons from the mouse genome (2002)

  7. Domain-regions are more conserved

  8. Because they are under higher purifying selection

  9. Because they are under higher purifying selection

  10. Secreted proteins evolve faster

  11. Rapid duplicators are rapid evolvers

  12. Higher purifying pressures in enzymes

  13. Mouse-Human Orthologues % Identity • sites not in domains: 64.4% • cSNP sites: 67.1% • all sites: 70.1% • sites in domains: 88.9% • disease sites: 90.3%

  14. Which genes have lineage specific duplicates?

  15. Large number of lineage specific duplications 10 – 20% of genes are lineage specific depending on comparisons

  16. 20% of human genes have been duplicated or do not have a rodent orthologue Family trees for genes: Human specific genes missing from mouse.(In many cases, more distantly related mouse gene (homologues) can be found. (8%) 1 to 1 (80%) Gene families shared with mouse but which have expanded in human (9%) Shared Orthologues (present as a single gene in the common ancestor to human and mouse)

  17. Where do new genes come from? • De novo (from non-coding) • Rapid sequence change • Gene duplication M. Lynch and A. Force , The probability of duplicate gene preservation by subfunctionalisation. Genetics 154 (2000), pp. 459–473 y • Pseudogenisation • Missing: Horizontal Gene transfer

  18. Inparalogues Chemosensation(OR, V1R and V2R ) Reproduction(Vomeronasal Receptors, lipocalins, b-microseminoprotein (12:1)) Immunity(IG chains, butyrophilins, leukocyte IG-like receptors, T-cell receptor chains and carcinoembryonic antigen-related cell adhesion molecules )pancreatic RNAses Detoxification(hypoxanthine phosphoribosyltransferase homologues nitrogen poor diets) KRAB ZnFingers

  19. No. in cluster Reproduction Clusters

  20. Weaker purifying selection for duplicate genes

  21. Rapid evolvers in protein coding genes Reproduction Chemosensation KRAB Zn Fingers Immunity TOXIN DEGRADATION

  22. Hypothesis: Darwinian evolution Competition: • Inter-specific (pathogens, predators) • Intra-specific • mating • sub-speciation / kin-selection • gender conflict • clonal expansions in sperm

  23. Immunity genes evolve the fastest

  24. KRAB-zinc finger genes Cancer-testis antigen genes (e.g. PRAMEs) Regulate chromatin structure and therefore the timing of transcription. Rapidly-changing developmental or transcriptional regulatory genes?

  25. Detecting biological signals among inparalogues Correlations with known annotations • Biological Annotations (gene descriptions / Gene Ontology) • Tissue specificity • Comparative changes across lineages (dating) • Chromosomal Distribution • Positive selection • Genomic environment

  26. Different genes duplicate at different times LeoGoodstadt et al. Genome Res. 2007; 17: 969-981

  27. Look for differential evolution

  28. GO-analysis of innovations

  29. Trends - Functions Human - Chicken GCSC (2005)‏

  30. Trends - Tissues Chicken - Human CGSC (2005)‏

  31. Exploring rapid evolutionary with protein structure GENE FAMILIES

  32. Independent expansions in the PRAME gene family

  33. Positive selection: PRAME genes Amino acid sites under positive selection in human (red), mouse (blue) and rat (purple) [or multiple species (yellow)] PRAME genes.

  34. Gene Duplication Remodels Genome Androgen-binding proteins. produced by sertoli cells in testes seminiferous tubulesEmes et al. (2004) Genome Res. 14(8):1516-29

  35. Lipocalins:Mouse Major Urinary ProteinsRat 2u-globulin genes sites subject to positive selection

  36. VR2 olfactory receptor N-terminal domain:  sites: dark blue, ligand (glutamate) pink (other monomer)

  37. MHC class1b, M10s  sites : in blue, peptide ligand in MHC structure in green

  38. Finding disease candidates within model organisms ORTHOLOGY AND DISEASE

  39. Few Mendelian disease genes lack mouse orthologues • Kallmann syndrome geneC. elegans orthologue. • CETP - cholesteryl ester transfer proteinRabbit and Hamster • Glycophorin EPrimate specificMN and Ss blood types

  40. Mouse equivalents of human disease variants Hs normal: MAETLFWTPLLVVLLAGLGDTEAQQTTLHPLVGRVFVHTLDHETFLSLPEHVAVPPAVHI Hs variant: MAETLFWTPLLVVLLAGLGDTEAQQTTLHLLVGRVFVHTLDHETFLSLPEHVAVPPAVHI Mm normal: MAAAVTWIPLLAGLLAGLRDTKAQQTTLHLLVGRVFVHPLEHATFLRLPEHVAVPPTVRL Nick Dickens & Jörg Schultz

  41. Disease mutations do not always lead to pathological phenotypes in mouse! 7293 SwissProt disease-associated variants • 90.3% mouse residue = human wild-type residue • 7.5% mouse residue ≠ human wild-type residue • 2.2%mouse residue = human disease residue

  42. Genomes are not a bag of genes GENOMIC CONTEXT IS IMPORTANT:LESSONS FROM THE MONODELPHIS

  43. Mutation rate is higher on the X chromosome

  44. Human X has separate synteny with MDOX/4/7

  45. Only Marsupial X show an increase in dS

  46. Comparisons with a third genome • Australian marsupial silver-gray bushtail possumTrichosurus vulpecula • 8,237 orthologues from 111,634 ESTs • More closely related to Monodelphis Median dS:

  47. X chromosome increased mutation rate is marsupial specific

  48. Homo Monodelphis 1:1 orthologues / d d N S 0.086 1.02 d S Amino acid sequence identity 81.0% 94.2% Pairwise alignment coverage Homo sapiens Monodelphis domestica Number of exons 9 9 Sequence length (codons) 471 445 Unspliced transcript length (bp) 27 , 241 25 , 365 G+C content at 4D sites 56.9% 48.7%

  49. Higher G+C in Monodelphis X Increased G+C

More Related