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Homologs, Orthologs and Paralogs

Homologs, Orthologs and Paralogs. Identifying changes in the genome requires resolving evolutionary relationships for all bases. Homologues : Common descent from an ancestral sequence Paralogues : Homologues in the same genome which are the result of gene duplication; Often short hand for:

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Homologs, Orthologs and Paralogs

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  1. Homologs, Orthologs and Paralogs Identifying changes in the genome requires resolving evolutionary relationships for all bases. Homologues: Common descent from an ancestral sequence Paralogues: Homologues in the same genome which are the result of gene duplication; Often short hand for: In-paralogues: Genes which have arisen from duplications in one lineage (E.g. mouse- or human- specific gene duplications) Orthologues: Corresponding genes in two species which were derived from a single gene in the last common ancestor Cenancestor SP1 SP2 DP2 A1 C1 C2 B1 C1 and C2 are paralogues A1 and B1 and (C1 and C2) are orthologues

  2. Orthologs

  3. Orthologs 1:1 orthologues are most likely to retain the common ancestral function Human and mouse c-kit mutations show similar phenotypes. The utility of mouse as a biomedical model for human disease is enhanced when mutations in orthologous genes give similar phenotypes in both organisms. In a visually striking example of this, the same pattern of hypopigmentation is seen in (a) a patient with the piebald trait and (b) a mouse with dominant spotting, both resulting from heterozygous mutations of the c-kit proto-oncogene.

  4. Measuring evolutionary rates on protein coding genes There are 2 type of mutations: synonymous - don’t change the encode aa. non-synonymous-change aa.

  5. Measuring evolutionary rates on protein coding genes

  6. Measuring evolutionary rates on protein coding genes

  7. Measuring evolutionary rates on protein coding genes

  8. Measuring evolutionary rates on protein coding genes

  9. Measuring evolutionary rates on protein coding genes

  10. Measuring evolutionary rates on protein coding genes

  11. Measuring evolutionary rates on protein coding genes

  12. Measuring evolutionary rates on protein coding genes

  13. Measuring evolutionary rates on protein coding genes

  14. Measuring evolutionary rates on protein-coding genes dN/dS Neutral Conserving / purifying Diversifying / positive  1.0 0.0 << 1 purifying selection = 1 neutral >> 1 positive diversifying selection N.B: dNnon-synonymous substitution rate dssynonymous rate

  15. Slow evolvers enzymes Non-enzymatic

  16. Fast evolvers

  17. Origin of new elements in the genome

  18. Gene duplication Proportion of (paralogous) genes in gene families Saccharomyces (yeast): 30% C. elegans: 48% Arabidopsis: 60% Drosophila: 40% Humans: 40%

  19. Evolutionary fate of gene duplicates 1. Duplication occurs butdoes not reach fixationin the population Chr. 3 Chr. 10 Chr. 10 Chr. 10 Chr. 10 Chr. 10 Chr. 10

  20. Duplication of protein coding genes 2. Duplication occursand fixes in the population butdegenerates becoming apseudogene: deletions, insertions and stop codons STOP STOP STOP STOP STOP STOP STOP STOP Chr. 3 Chr. 10 Chr. 10 Chr. 10 Chr. 10 Chr. 10 Chr. 10

  21. Duplication of protein coding genes ! 3. Duplication occursand fixes in the population –new geneis kept in the genomewith function Chr. 3 Chr. 10 Chr. 10 Chr. 10 Chr. 10 Chr. 10 Chr. 10

  22. Duplication of protein coding genes • Evolutionary fate/role of new functional gene • Duplication for the sake of producing more of the same.

  23. Duplication of protein coding genes

  24. Duplication of protein coding genes • Evolutionary fate/role of new functional gene • Duplication for the sake of producing more of the same. • Subfunctionalization

  25. MTS positive selection accelerated evolution of GLUD2 MTS (P < 0.001) • Subfunctionalization Mitochondrial targeting sequence (MTS) evolution of GLUDs GLUD MTS GLUD enzyme

  26. MitoTracker Merge MTS+GFP MTS Human GLUD2 MTS GLUD2 Node B MTS GLUD2 Node A MTS Human GLUD1 Mitochondrial targeting capacity of GLUD MTSs • Subfunctionalization

  27. Subfunctionalization GLUD2 sites under positive selection MTS alignment:

  28. Subfunctionalization

  29. Duplication of protein coding genes • Evolutionary fate/role of new functional gene • Duplication for the sake of producing more of the same. • Subfunctionalization • Creation of a new gene function from a duplicate of an existing gene

  30. Duplication of protein coding genes

  31. Duplication of protein coding genes

  32. Gene Loss Gene loss is also associated with the origin of new traits. Loss of egg yolk genes in mammals Loss of olfactory receptors Brawand D. et al. (2006) Hayden S et al. (2010)

  33. How is this important ?

  34. Challenges ahead • How are the apparent differences in species “complexity” encoded? • Are the ~19,000 genes in the genome the “important” bits? • How much genetic variation is determined epigenetically? • What is the function of the thousands of non-protein coding transcripts we find within the cell? • Which genes are switched on in which tissues and at what developmental time-points? • How much somatic variation is there? • Currently, we can only explain <20% of the causes underlying many important diseases. How do we identify the cause of the rest?

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