Comparative genomics of the fungal kingdom

Slideshow Transcript

1. Slide 1: Comparative genomics of the fungal kingdom: a view from the chytrids Jason Stajich University of California, Berkeley
2. Slide 2: Comparative Genomics • Tools for studying evolution at level of genomic blueprints. • Identifying shared, unique, loss and gains of genes. • Signatures of adaptation • Identify genes that are under positive directional selection - changing faster at the amino acid level than expected given neutral rate • Identification of gene families that expand or contract by unexpected amounts • Contrasting genome organization and evolution of genomic clusters of genes
3. Slide 3: Fantastic Fungi • Evolution of modern fungal forms and lifestyles • Evolution of Multicellularity - independent transitions in Metazoa and Plants. • Reversions to unicellularity • Evolution of development; early genes involved in fruiting body development • Plants and Fungi have cell walls; animals lack cell walls; what were fungal ancestor’s cell walls like? Fungal-animal ancestor? • What genes were in the ancestral fungus? Which genes have newly evolved and are contribute to new morphologies or life stages?
4. Slide 4: Fantastic opportunities in fungal comparative genomics • More than 65 available genomes - dozens more in pipeline at sequencing centers • http://fungalgenomes.org/wiki/Fungal_Genome_Links • 1(2) Chytrid, 2 Zygomycetes, 8 (12) Basidiomycetes, 3-4 Taphrinomycotina, • ~30 (+15 strains Coccidoidioides, 3 strains of Histoplasma) Pezizomycotina • ~22(+20-100 strains S. cerevisiae & S. paradoxus) Saccharomycotina • Broad Institute & Fungal Genome Initiative, Joint Genome Institute, Stanford Genome Technology Center, Sanger Centre, Génolevures project & CNRS, BC Genome Sequencing Center, others. • US genome sequencing funding: NSF, DOE, NIH
5. Slide 5: Genome annotation • Train ab initio gene predictors • Build good models from protein to genome alignments of take set of curated genes. Build full-length models from cDNA or assembled ESTs • Trains on exon-intron, intron length, exon length, and codon/nt biases • Refine parameters using iterative manner with some gene models held out to assess improvements • Generate and combine Annotations • Take ab initio, homology based, and EST tracks • Combine into consensus gene models • GLEAN or Jigsaw (GAZE also) • Assess performance of different datasets, leave out some models if necessary
6. Slide 6: Combined predictions perform better scaffold_5 1219k 1220k 1221k % gc 58% 17% GLEAN BDEN_JAM81_00470 BDEN_JAM81_00471 probability 0.765437 probability 0.981985 SNAP genes lenx_scaffold_5-snap.460 lenx_scaffold_5-snap.461 Twinscan genes TS.scaffold_5.413 Genewise genes dhan_DEHA0E17479g__scaffold_5__1216332__1226931 egos_AGR101C__scaffold_5__1216332__1226940 klac_KLLA0F11957g__scaffold_5__1216332__1226931 ctro_CTRT_03542__scaffold_5__1216332 lelo_LELT_03523__scaffold_5__1216332 AUGUSTUS genes scaffold_5-augustus-g372.t1 PASA EST genes Model.asmbl_4025 Model.asmbl_4026
7. Slide 7: Combined predictions perform better scaffold_5 1219k 1220k 1221k % gc 58% 17% GLEAN BDEN_JAM81_00470 BDEN_JAM81_00471 probability 0.765437 probability 0.981985 SNAP genes lenx_scaffold_5-snap.460 lenx_scaffold_5-snap.461 Twinscan genes TS.scaffold_5.413 Genewise genes dhan_DEHA0E17479g__scaffold_5__1216332__1226931 egos_AGR101C__scaffold_5__1216332__1226940 klac_KLLA0F11957g__scaffold_5__1216332__1226931 ctro_CTRT_03542__scaffold_5__1216332 lelo_LELT_03523__scaffold_5__1216332 AUGUSTUS genes scaffold_5-augustus-g372.t1 PASA EST genes Model.asmbl_4025 Model.asmbl_4026
8. Slide 8: Combined predictions perform better scaffold_5 1219k 1220k 1221k % gc 58% 17% GLEAN BDEN_JAM81_00470 BDEN_JAM81_00471 probability 0.765437 probability 0.981985 SNAP genes lenx_scaffold_5-snap.460 lenx_scaffold_5-snap.461 Twinscan genes TS.scaffold_5.413 Genewise genes dhan_DEHA0E17479g__scaffold_5__1216332__1226931 egos_AGR101C__scaffold_5__1216332__1226940 klac_KLLA0F11957g__scaffold_5__1216332__1226931 ctro_CTRT_03542__scaffold_5__1216332 lelo_LELT_03523__scaffold_5__1216332 AUGUSTUS genes scaffold_5-augustus-g372.t1 PASA EST genes Model.asmbl_4025 Model.asmbl_4026
9. Slide 9: Combined predictions perform better scaffold_5 1219k 1220k 1221k % gc 58% 17% GLEAN BDEN_JAM81_00470 BDEN_JAM81_00471 probability 0.765437 probability 0.981985 SNAP genes lenx_scaffold_5-snap.460 lenx_scaffold_5-snap.461 Twinscan genes TS.scaffold_5.413 Genewise genes dhan_DEHA0E17479g__scaffold_5__1216332__1226931 egos_AGR101C__scaffold_5__1216332__1226940 klac_KLLA0F11957g__scaffold_5__1216332__1226931 ctro_CTRT_03542__scaffold_5__1216332 lelo_LELT_03523__scaffold_5__1216332 AUGUSTUS genes scaffold_5-augustus-g372.t1 PASA EST genes Model.asmbl_4025 Model.asmbl_4026
10. Slide 10: Combined predictions perform better scaffold_5 1219k 1220k 1221k % gc 58% 17% GLEAN BDEN_JAM81_00470 BDEN_JAM81_00471 probability 0.765437 probability 0.981985 SNAP genes lenx_scaffold_5-snap.460 lenx_scaffold_5-snap.461 Twinscan genes TS.scaffold_5.413 Genewise genes dhan_DEHA0E17479g__scaffold_5__1216332__1226931 egos_AGR101C__scaffold_5__1216332__1226940 klac_KLLA0F11957g__scaffold_5__1216332__1226931 ctro_CTRT_03542__scaffold_5__1216332 lelo_LELT_03523__scaffold_5__1216332 AUGUSTUS genes scaffold_5-augustus-g372.t1 PASA EST genes Model.asmbl_4025 Model.asmbl_4026
11. Slide 11: • Consensus tree of 42 fungal genomes based on many thousands of orthologous genes • Not perfect, but automated reconstruction can be powerful tool • Conflicts in topology can identify genes with interesting history Fitzpatrick DA, Logue ME, Stajich JE, Butler G. BMC Genomics 2006
12. Slide 12: Complex fungal genes • Modern fungi have complex gene structures. How complex were gene structures in the fungal ancestor? • Many introns are present in fungal genes • Intron poor Saccharomyces, U.maydis, and S.pombe are derived • Evolution of introns in fungi has seen many losses, few gains
13. Slide 13: Fungal intron size and frequency evolution 500 Hemiascomycota C. glabrata Median intron length (bp) 400 300 K. lactis U. maydis B.dendrobatidis Y. lipolytica 200 Euascomycota Basidiomycota S.cerevisiae Zygomycota 100 C. cinerea P. chrysosporium R. oryzae C. neoformans S. pombe 0 0 1 2 3 4 5 6 7 Stajich JE, Dietrich FS, and Roy SW. Mean number of introns per kb of coding sequence Genome Biology In revision
14. Slide 14: Podospora anserina (359) Euascomycota Chaetomium globosum (463) Neurospora crassa (336) Magnaporthe grisea (368) Fusarium graminearum (372) Aspergillus fumigatus (481) Aspergillus terreus (474) Aspergillus nidulans (469) Stagonospora nodorum (403) Hemiascomycota Ashbya gossypii (7) Kluyveromyces lactis (6) Saccharomyces cerevisiae (7) Dikarya Candida glabrata (6) Debaryomyces hansenii (5) Yarrowia lipolytica (30) Schizosaccharomyces pombe (214) Basidiomycota Coprinopsis cinerea (1621) Opisthokont Phanerochaete chrysosporium (1615) Cryptococcus neoformans (1578) Ustilago maydis (86) Zygomycota Rhizopus oryzae (947) Vertebrates Homo sapiens (2737) Mus musculus (2656) Takifugu rubripes (2685) Plants Stajich JE, Dietrich FS, and Roy SW. Arabidopsis thaliana (2290) Genome Biology In revision 0.1
15. Slide 15: Intron loss predominates in fungal lineages Saccharomycetes P. chrysosporium Sordariomycetes Eurotiomycetes C. neoformans A S. nodorum Vertebrates Y. lipolytica A. thaliana C. cinerea U. maydis S. pombe R. oryzae 5.51 6.62 2.28 0.21 3.80 3.89 3.90 0.52 0.88 1.16 0.97 0.07 0.02 4.03 1.20 0.07 3.59 2.36 2.77 3.59 3.59 3.87 4.98 Stajich JE, Dietrich FS, and Roy SW. Genome Biology In revision
16. Slide 16: Intron loss in C. neoformans through mRNA intermediete C A C. gattii, strain WM276 JEC21 BT-100 BT-157 WM276 BT-63 R265 H99 35-23 2462 C. gattii, strain R265 C. neoformans var. neoformans, strain JEC21 C. neoformans var. grubii, strain H99 1.0 B 1kb 5 kb 2 kb 3 kb 4 kb 6 kb 1 2 3 4 5 6 78 9 10 11 12 13 14 15 16 17 18 19 20 21 22 1 2 3 4 5 6 78 9-19 20 21 22 Stajich JE, Dietrich FS. Euk Cell 2006
17. Slide 17: Intron gain is rare • Two studies looked at intron loss and gain in 4 closely related C. neoformans (Sharpton et al, submitted; Stajich and Dietrich 2006) and found little or no intron gain. • Nielsen et al, Plos Biology 2004 found moderate amount of intron gain among Pezizomycota • Intron gain IS happening in lineages but among sampled closely related genomes there are few examples of intron gains... • ... and little convincing evidence of the molecular mechanism of this gain (duplication, self- splicing, de-novo intron creation) • More work needed to understand dynamics and mechanisms of gene structure change
18. Slide 18: B. dendrobatidis genomics • Amphibian pathogen killing frogs worldwide • Chytrid fungus with motile zoospore and zoosporangia stage • Genome sequencing of 2 strains • JEL423 (Joyce Longcore; Panama) motile and JAM81 (Jess Morgan; Sierras, zoospore California) • 24 Mb genome; ~8,000 genes • Tiling genomic microarray and exon array in development (Eisen lab) zoosporangia
19. Slide 19: B. dendrobatidis genomics • Amphibian pathogen killing frogs worldwide • Chytrid fungus with motile zoospore and zoosporangia stage • Genome sequencing of 2 strains • JEL423 (Joyce Longcore; Panama) motile C. neoformans ~7,000 and JAM81 (Jess Morgan; Sierras, zoospore C. cinereus ~10,000 California) U. maydis ~7,000 S. cerevisiae ~6,000 • 24 Mb genome; ~8,000 genes A. fumigatus ~10,000 • Tiling genomic microarray and exon array in development (Eisen lab) zoosporangia
20. Slide 20: Gene structure evolution: B.dendrobatidis genes are intron rich B.dendrobatidis BDEN_JAM81_01417 U.maydis UM03290.1 P.chrysosporium GLEAN_01130 S.pombe SPAC644.14c N.crassa NCU02741.1 S. cerevisiae YER095W Strand exchange protein, forms a helical filament with DNA that searches for homology; involved in the recombinational repair of double-strand breaks in DNA during vegetative growth and meiosis; homolog of Dmc1p and bacterial RecA protein
21. Slide 21: Phylogenetic profiling • Classify a genes as to which phylogenetic clades it shares homologs with. • Can be simply a similarity search (BLAST) to representatives genomes. • Summarize the number of shared genes by different patterns • Using Chytrid genes to identify genes present in ancestor, shared with animal outgroup. • Find genes lost at different part of tree • By comparing all genes in lineages back to Chytrid can identify potential gene gains
22. Slide 22: Phylogenetic profile of B.dendrobatidis genes Fungi Basidiomycota 122 262 63 606 556 123 4685 3732 119 395 168 Zygomycota Ascomycota Animal Plant 1550 (19.2%) Chytrid specific genes 8068 B. dendrobatidis genes
23. Slide 23: Phylogenetic profile of B.dendrobatidis genes Fungi Basidiomycota 1.5% 3.3% .7% 7.5% 6.9% 1.5% 58% 46% 1.5% 4.9% 2% Zygomycota Ascomycota Animal Plant 1550 (19.2%) Chytrid specific genes
24. Slide 24: Fungal cell wall Latgé JP
25. Slide 25: Evolution of cell walls • Fungal cell wall are made of • Chitin, Beta-glucans, Mannin, other sugars • Animals lack cell walls • Plants have rigid cell walls • Can learn about opisthokont ancestor from learning about the ancestral fungus Baldauf SL. Science 2003
26. Slide 26: Evolution of cell wall: 1,3 Beta-glucan synthesis Genes C Z B A ✘ ✔ ✔ ✔ 1,3-beta-D-glucan synthase (FKS1) 1,6 β-glucan 1,3 β-glucan ✘ ✘ ✘ ✔ Cell surface reg kinase (HKR1) ✘ ✘ ✔ ✔ Regulator (SMI1) ✘ ✔ ✔ ✔ 1,3-beta-glucanase (EXG1) ✔ ✔ ✔ ✔ Glucosidase (GTB1) ✘ ✘ ✘ ✔ 1,6-beta-glucan biosynthesis (KNH1) ✔ ✔ ✔ ✔ glucosyltransferase (KRE5) ✘ ✘ ✔ ✔ Glucosidase activity (KRE6) ✘ ✘ ✔ ✔ Glucosidase activity (SKN1) ✔ ✔ ✔ ✔ uridylyltransferase (UGP1)
27. Slide 27: Evolution of cell wall: 1,3 Beta-glucan synthesis Genes C Z B A ✘ ✔ ✔ ✔ 1,3-beta-D-glucan synthase (FKS1) 1,6 β-glucan 1,3 β-glucan ✘ ✘ ✘ ✔ Cell surface reg kinase (HKR1) ✘ ✘ ✔ ✔ Regulator (SMI1) ✘ ✔ ✔ ✔ 1,3-beta-glucanase (EXG1) ✔ ✔ ✔ ✔ Glucosidase (GTB1) ✘ ✘ ✘ ✔ 1,6-beta-glucan biosynthesis (KNH1) ✔ ✔ ✔ ✔ glucosyltransferase (KRE5) ✘ ✘ ✔ ✔ Glucosidase activity (KRE6) ✘ ✘ ✔ ✔ Glucosidase activity (SKN1) ✔ ✔ ✔ ✔ uridylyltransferase (UGP1)
28. Slide 28: Flagella in fungi • Loss of flagella was a one or a few events • Find shared genes in animal and Chytrid genomes but missing fungi • Many of these genes are even shared with cillia & flagellar genes with Chlamydomonas. • Microarray expression data differences between zoospore and sporangia • Flagella Dynein 64x up regulated in zoospores.
29. Slide 29: Hypothesis for new cell wall genes and transition to terrestrial life • Cell wall of ancestral fungus adapted for aquatic fungus which had flagella. • Loss of flagella as part of adaptation to terrestrial life. • Additional gene family duplication and specialization. • Chitin synthase expansions • FKS1 1,3-Beta-glucan pathway evolution • Substrate for complex multicellular evolution and morphological elaboration.
30. Slide 30: Collaboration • Erica Rosenblum, Michael Eisen, John Taylor; University of California, Berkeley • Igor Grigoriev, Alan Kuo; DOE Joint Genome Institute • Christina Cuomo, Antonis Rokas; Broad Institute of MIT and Harvard • Tim James; Uppsala University • http://fungal.genome.duke.edu - genome browser and annotations • http://fungalgenomes.org • Blog & Wiki for Genome data • Coming soon: Genome Browser and comparative resources