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Comparative genomics
in eukaryotes
Genome analysis



  Klaas Vandepoele, PhD


Professor Ghent University
Comparative & Integrative Genomics
VIB – Ghent University, Belgium
I. Genome conservation & genomic
        homology
       Alignment of homologous regions
            Inter-genomic: aligning genomic sequences from different
             species
            Intra-genomic aligning genomic sequences from the same
             species

       Different levels of resolution
          Comparative mapping (markers)
          Synteny (~ gene content)
          Colinearity (gene content + order conservation)
          DNA-based alignments (base-to-base mapping)




2
Human – Mouse - Rat
                          resolution




3
Human – Mouse orthologous
                   regions                                     resolution


                                      Genome translocations associated
    Comparative
                                      with human-mouse speciation
    mapping




               Human




Mouse chr IV




4                                                       www.ensembl.org
Human genome browser
                                                                      resolution


Conserved gene      Human chr I
content & order     Mouse chr IV

                                     Gene loss and insertions in orthologous
                                   segments since human-mouse speciation




EST/cDNA
similarities




Genome
similarities



5                                                      Human gene model
Human – Mouse base-to-base
       mapping                                                 resolution


                                                 Functional sequences
                                                (e.g. exons) evolve slower
                                                than non-functional ones
                                                (e.g. introns) due to
                                                natural selection against
                                                mutations in these regions


                                                 Consequently,
                                                functional elements, both
                                                coding and non-coding,
                                                are unusually well
                                                conserved in orthologous
                                                regions




    Blue: coding exons   GT donor AG acceptor
6
DNA substitution rates for different
    gene/genome regions




7                                Molecular Evolution, Li WH
Multiple species comparisons
             (gene-based)




8   Hedges, 2002                            PhIGs
Genome size variation in the grasses:
       the use of model systems



        BEP                           Rice 450Mb
             46 MYA


    55 MYA                            Barley ~5000Mb




             28 MYA

       PACC                           Sorghum ~750Mb
                                      Maize ~2400Mb




9                                          Gaut 2002
Grass genomes: a single genetic
     system?
                               Gale and Devos, 1998




10
Micro-colinearity within the grasses




11                                  Bennetzen lab
Yeast Gene Order Browser (YGOB)




12
II. Computational detection of
         genomic homology
        Synteny
         ~ conservation of gene content
        Colinearity
         ~ conservation of (gene) content & order

        Macro-colinearity
            Marker-based
        Micro-colinearity
            DNA based or gene-based
13
How to find evidence for gene
          colinearity?
     A    1   2    3      4       5        6   7   8     9    10    11

                              speciation

     S1   1   2    3      4       5        6   7   8     9    10    11

     S2   1   2    3      4       5        6   7   8     9    10    11
                                                                         Time
                  Gene loss, insertions,
                  rearrangements,
                  translocation, etc …
              2

     S1   1        3      4                6   7              10    11

     S2   1   2           4                6   7   8     9          11




                               retained orthologs (anchor points)
14
Matrix representation

     S1   1                             3       4               6       7                   10   11

     S2   1                2                    4               6       7       8       9        11


                                                        segment S1
                                    1       -       3   4   -   6   7   X   X       10 11
                               1

                               2

                               -
              segment S2




                               4
                               X

                               6

                               7

                               8

                               9
                               -

15                             11
Map-based approach
                        Chromosome 1

                                            • Represent chromosomes
                                              as sorted gene lists
                                            • Identify all homologous
     Chromosome 2




                                              gene pairs between
                                              chromosomes (all-
                                              against-all BLASTP*).
                                            • Score pairs of
                                              homologues in matrix


     Identifying homologous regions = identifying diagonal series of
     elements in the gene homology matrix (GHM).
16                                            Vandepoele et al., Genome Research 2002
The map-based approach: terminology


                      Chromosome 1

                                     Colinear segment
                                     Tandem duplication
     Chromosome 2




                                     Homologous gene
                                     Inverted colinear segment


                                                                 1


                                                                 2


     Gene Homology Matrix (GHM)
17
Detection of colinear homologous
             regions


                   Human-mouse    Chicken-human




     MmuC4
                                                  HsaC1




                     HsaC1           GgaC23
18
Detection of colinear homologous
             regions


                   Human-mouse    Human-tetraodon




     MmuC4
                                                    TviC1




                     HsaC1             HsaC1
19
MUMmer
     NUCmer   PROmer




20
And what about synteny?
                                                  HsaC1




                                                          • Application of 2-
                                                          dimensional sliding-
     HsaC9
                                                          window approach to
                                                          score regions with a high
                                                          density of homologous
                                                          genes between 2
                                                          chromosomes



              ancient duplication

        Identifying syntenic regions = identifying high homolog-density
        regions in the gene homology matrix (GHM).
21                                                   DeSyRe, Vandepoele et al. unpublished
Detection of recent and ancient large-
            scale duplications

          recent duplication                ancient duplication




                               C2                                 HsaC1




     C4                             HsaC9




22          colinearity                            synteny
III. Whole-genome alignments

        Evolutionary constrained sequences are a
         good indicator of functional genome regions

        Basic protocol
         1.   Sequence generation
         2.   Reconstructing homologous colinearity across
              related genomes
         3.   Multi-sequence alignment
         4.   Detection sequences under purifying selection.



23                                             Margulies & Birney, NRG 2008
Reconstructing homologous
     colinearity




     • Segmental duplication and other species-specific
     rearrangements (e.g. inversions, insertions, deletions)
     interfere with the accurate detection of orthologous
     genomic regions


24
Tools

        Mercator (Ensembl)
            coding exons as anchor points
            graph of colinearity information
            travel through graph to generate homologous
             regions
        chains-and-nets (UCSC)
            reference-based local alignments different
             genomes (BLASTZ)
            filtering highest-scoring chains
            net together chains from same locus

25
Sequence alignment & constraint
     detection




                               PhastCons
                               BinCons
                               GERP
                               Siphy




26
Whole-genome base-pair
         alignment

        Challenges
            multi-species alignment
            long DNA sequences (reflecting homologous
             colinear regions)
            one-to-one mapping (with reference genome)
            various levels of sequence divergence




27
Whole-genome base-pair
         alignment toolbox
        MLAGAN
            CHAOS seeding algorithm (k-mer anchors)
            Dynamic programming (pairwise)
            Multiple alignment using progressive strategy
            Shuffle-LAGAN (incl. rearrangement map); VISTA
        TBA / MultiZ; UCSC
            Pairwise BLASTZ alignments (local blocks)
            Merging joining blocks using MultiZ
            Complex ordering of blocks using Threaded Blockset Aligner
        PECAN (Ensembl)
            Consistency alignment based on pairwise alignments (incl. outgroup
             information)
        MAVID




28
From gene to DNA-based
                  colinearity…

Pairwise approach:
 Human segment as
          reference




29                                                    VISTA
                                           http://genome.lbl.gov/vista
From gene to DNA-based
     colinearity…




30
Input and output files




                              PIP- maker




31                                Frazer et al., 2003
Conserved Non-coding Sequences or
              Elements (CNS/CNE)

Human/dog

Human/mouse

 Mouse/dog




                                                           VISTA plot
                                          Blue: exons
                                          Turquoise: UTR
32
Exercise

        Explore the genome organization and
         conservation of your favorite locus in a set of
         related species.

        Plants
           http://bioinformatics.psb.ugent.be/plaza/


        Vertebrates
           http://teleost.cs.uoregon.edu/synteny_db/


        Yeast
           http://wolfe.gen.tcd.ie/ygob/


33
34

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BITS - Comparative genomics on the genome level

  • 1. Comparative genomics in eukaryotes Genome analysis Klaas Vandepoele, PhD Professor Ghent University Comparative & Integrative Genomics VIB – Ghent University, Belgium
  • 2. I. Genome conservation & genomic homology  Alignment of homologous regions  Inter-genomic: aligning genomic sequences from different species  Intra-genomic aligning genomic sequences from the same species  Different levels of resolution  Comparative mapping (markers)  Synteny (~ gene content)  Colinearity (gene content + order conservation)  DNA-based alignments (base-to-base mapping) 2
  • 3. Human – Mouse - Rat resolution 3
  • 4. Human – Mouse orthologous regions resolution Genome translocations associated Comparative with human-mouse speciation mapping Human Mouse chr IV 4 www.ensembl.org
  • 5. Human genome browser resolution Conserved gene Human chr I content & order Mouse chr IV Gene loss and insertions in orthologous segments since human-mouse speciation EST/cDNA similarities Genome similarities 5 Human gene model
  • 6. Human – Mouse base-to-base mapping resolution  Functional sequences (e.g. exons) evolve slower than non-functional ones (e.g. introns) due to natural selection against mutations in these regions  Consequently, functional elements, both coding and non-coding, are unusually well conserved in orthologous regions Blue: coding exons GT donor AG acceptor 6
  • 7. DNA substitution rates for different gene/genome regions 7 Molecular Evolution, Li WH
  • 8. Multiple species comparisons (gene-based) 8 Hedges, 2002 PhIGs
  • 9. Genome size variation in the grasses: the use of model systems BEP Rice 450Mb 46 MYA 55 MYA Barley ~5000Mb 28 MYA PACC Sorghum ~750Mb Maize ~2400Mb 9 Gaut 2002
  • 10. Grass genomes: a single genetic system? Gale and Devos, 1998 10
  • 11. Micro-colinearity within the grasses 11 Bennetzen lab
  • 12. Yeast Gene Order Browser (YGOB) 12
  • 13. II. Computational detection of genomic homology  Synteny ~ conservation of gene content  Colinearity ~ conservation of (gene) content & order  Macro-colinearity  Marker-based  Micro-colinearity  DNA based or gene-based 13
  • 14. How to find evidence for gene colinearity? A 1 2 3 4 5 6 7 8 9 10 11 speciation S1 1 2 3 4 5 6 7 8 9 10 11 S2 1 2 3 4 5 6 7 8 9 10 11 Time Gene loss, insertions, rearrangements, translocation, etc … 2 S1 1 3 4 6 7 10 11 S2 1 2 4 6 7 8 9 11 retained orthologs (anchor points) 14
  • 15. Matrix representation S1 1 3 4 6 7 10 11 S2 1 2 4 6 7 8 9 11 segment S1 1 - 3 4 - 6 7 X X 10 11 1 2 - segment S2 4 X 6 7 8 9 - 15 11
  • 16. Map-based approach Chromosome 1 • Represent chromosomes as sorted gene lists • Identify all homologous Chromosome 2 gene pairs between chromosomes (all- against-all BLASTP*). • Score pairs of homologues in matrix Identifying homologous regions = identifying diagonal series of elements in the gene homology matrix (GHM). 16 Vandepoele et al., Genome Research 2002
  • 17. The map-based approach: terminology Chromosome 1 Colinear segment Tandem duplication Chromosome 2 Homologous gene Inverted colinear segment 1 2 Gene Homology Matrix (GHM) 17
  • 18. Detection of colinear homologous regions Human-mouse Chicken-human MmuC4 HsaC1 HsaC1 GgaC23 18
  • 19. Detection of colinear homologous regions Human-mouse Human-tetraodon MmuC4 TviC1 HsaC1 HsaC1 19
  • 20. MUMmer NUCmer PROmer 20
  • 21. And what about synteny? HsaC1 • Application of 2- dimensional sliding- HsaC9 window approach to score regions with a high density of homologous genes between 2 chromosomes ancient duplication Identifying syntenic regions = identifying high homolog-density regions in the gene homology matrix (GHM). 21 DeSyRe, Vandepoele et al. unpublished
  • 22. Detection of recent and ancient large- scale duplications recent duplication ancient duplication C2 HsaC1 C4 HsaC9 22 colinearity synteny
  • 23. III. Whole-genome alignments  Evolutionary constrained sequences are a good indicator of functional genome regions  Basic protocol 1. Sequence generation 2. Reconstructing homologous colinearity across related genomes 3. Multi-sequence alignment 4. Detection sequences under purifying selection. 23 Margulies & Birney, NRG 2008
  • 24. Reconstructing homologous colinearity • Segmental duplication and other species-specific rearrangements (e.g. inversions, insertions, deletions) interfere with the accurate detection of orthologous genomic regions 24
  • 25. Tools  Mercator (Ensembl)  coding exons as anchor points  graph of colinearity information  travel through graph to generate homologous regions  chains-and-nets (UCSC)  reference-based local alignments different genomes (BLASTZ)  filtering highest-scoring chains  net together chains from same locus 25
  • 26. Sequence alignment & constraint detection PhastCons BinCons GERP Siphy 26
  • 27. Whole-genome base-pair alignment  Challenges  multi-species alignment  long DNA sequences (reflecting homologous colinear regions)  one-to-one mapping (with reference genome)  various levels of sequence divergence 27
  • 28. Whole-genome base-pair alignment toolbox  MLAGAN  CHAOS seeding algorithm (k-mer anchors)  Dynamic programming (pairwise)  Multiple alignment using progressive strategy  Shuffle-LAGAN (incl. rearrangement map); VISTA  TBA / MultiZ; UCSC  Pairwise BLASTZ alignments (local blocks)  Merging joining blocks using MultiZ  Complex ordering of blocks using Threaded Blockset Aligner  PECAN (Ensembl)  Consistency alignment based on pairwise alignments (incl. outgroup information)  MAVID 28
  • 29. From gene to DNA-based colinearity… Pairwise approach: Human segment as reference 29 VISTA http://genome.lbl.gov/vista
  • 30. From gene to DNA-based colinearity… 30
  • 31. Input and output files PIP- maker 31 Frazer et al., 2003
  • 32. Conserved Non-coding Sequences or Elements (CNS/CNE) Human/dog Human/mouse Mouse/dog VISTA plot Blue: exons Turquoise: UTR 32
  • 33. Exercise  Explore the genome organization and conservation of your favorite locus in a set of related species.  Plants  http://bioinformatics.psb.ugent.be/plaza/  Vertebrates  http://teleost.cs.uoregon.edu/synteny_db/  Yeast  http://wolfe.gen.tcd.ie/ygob/ 33
  • 34. 34