Comparative%20Genomics%20Comparative%20Gene%20Prediction%20in%20the%20Human%20Genome

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Comparative GenomicsComparative Gene Prediction
in the Human Genome

• Maribel Hernandez Rosales

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What is Comparative Genomics?

• Comparative genomics is the analysis and
  comparison of genomes from different species.
• The purpose is to gain a better understanding of
  how species have evolved and to determine the
  function of genes and noncoding regions of the
  genome.
• Researchers have learned a great deal about the
  function of human genes by examining their
  counterparts in simpler model organisms such as
  the mouse.
• Genome researchers look at many different
  features when comparing genomes sequence
  similarity, gene location, the length and number
  of coding regions (called exons) within genes,
  the amount of noncoding DNA in each genome, and
  highly conserved regions maintained in organisms
  as simple as bacteria and as complex as humans.
• Comparative genomics involves the use of computer
  programs that can line up multiple genomes and
  look for regions of similarity among them.

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What are the comparative genome sizes of humans
and other organisms being studied?
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Eukaryotic Gene Finding
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Comparative Gene Prediction

• GenScan ab initio gene prediction.
• GeneWise, Procrustes homology guided.
• Rosseta, SGP1 (Syntetic Gene Prediction), CEM
  (Conserved Exon Method) gene prediction and
  sequence alignment are clearly separated.
• GenomeScan Ab Initio modified by BLAST
  homologies.
• SGP-2, TwinScan, SLAM, DoubleScan modification
  of GenScan scoring schema to incorporate
  similarity to known proteins.

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GeneScan

• A general probabilistic model for the gene
  structure of human genomic sequences.
• Gene identification by identifying complete
  exon/intron structures of genes in genomic DNA.
• Include de capacity to predict multiple genes in
  a sequence, to deal with partial as well as
  complete genes, and to predict consistent sets of
  genes occurring on either or both DNA strands.
• Markov Model of coding regions predictions do
  not depend on presence of a similar gene in the
  protein sequence databases and complement the
  information provided by homology-based gene
  identification methods (BLASTX).
• Maximal Dependence Decomposition (MDD) new
  statistical model of donor and acceptor splice
  sites which capture important dependencies
  between signal positions.

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Pre-mRNA Splicing
exon definition
intron definition
...
(assembly of
spliceosome,
catalysis)
...
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Hidden semi-Markov Model (HMM)
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GenScan HMM

• N - intergenic region
• P - promoter
• F - 5 untranslated region
• Esngl single exon (intronless) (translation
  start -gt stop codon)
• Einit initial exon (translation start -gt donor
  splice site)
• Ek phase k internal exon (acceptor splice site
  -gt donor splice site)
• Eterm terminal exon (acceptor splice site -gt
  stop codon)
• Ik phase k intron 0 between codons 1
  after the first base of a codon 2 after the
  second base of a codon

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GenScan Features

• Model both strands at once
• Each state may output a string of symbols
  (according to some probability distribution).
• Explicit intron/exon length modeling
• Advanced splice site modeling
• Parameters learned from annotated genes
• Prediction of multiple genes in a sequence
  (partial or complete).

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GenomeScan

• We can enhance our gene prediction by using
  external information DNA regions with homology
  to known proteins are more likely to be coding
  exons.
• Combine probabilistic extrinsic information
  (BLAST hits) with a probabilistic model of gene
  structure/composition (GenScan).
• Focus on typical case when homologous but not
  identical proteins are available.

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Ab Initio modified by BLAST homologies
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Ab Initio modified by BLAST homologies
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GeneWise

• Motivation Use good DB of protein world (PFAM)
  to help us annotate genomic DNA
• GeneWise algorithm aligns a profile HMM directly
  to the DNA

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GeneWise

• Start with a PFAM domain HMM
• Replace AA emissions with codon emissions

• Allow for sequencing errors (deletions/
  insertions)
• Add a 3-state intron model

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GeneWise Model
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GeneWise Intron Model
5 site
3 site
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GeneWise Features Problems

• Best alignment of DNA to protein domain
• Alignment gives exact exon-intron boundaries
• Parameters learned from species-specific
  statistics
• Only provides partial prediction, and only where
  the homology lies
• Does not find more genes
• Pseudogenes, Retrotransposons picked up
• CPU intensive
• Solution Pre-filter with BLAST

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Rosetta

• Gene prediction is separated from sequence
  alignment.
• First, the alignment is obtained between two
  homologous genomic sequences using sequence
  global alignment Glass. Then, gene structures
  (splice sites, exon number and length, etc.) are
  predicted that are compatible with this
  alignment, meaning that predicted exons fall in
  the aligned regions.

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Syntenic Gene Prediction

• This approach does not require the comparison of
  two homologous genomic sequences.
• A query sequence from a target genome is
  compared against a collection of sequence from a
  second (informant, reference) genome and the
  results of the comparison are used to modify the
  scores of the exons produced by underlying ab
  initio'' gene prediction algorithms.
• Gene prediction and sequence alignment are
  separated.

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SGP-2
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Gene predicition programs predict a large number
of genes

• almost every mouse gene has
• the human orthologue counterpart

TwinScan SGP
48462 total 47055
17562 novel 21942
10987 3171 multiexonic long no low complexity 12158 4543
954 human ts 2983 human sgp
317 637 1931 1052
intron aligned human ts human sgp intron aligned



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Orthologous human mouse genes have conserved
exonic structure.

• 85 of the orhologous pairs have identical
  number of exons
• 91 of the orthologous exons have identical
  length
• 99.5 of the orthologous exons have identical
  phase
• there are a few cases of intron
  insertion/deletion (22)

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Summary

• Genes are complex structures which are difficult
  to predict with the required level of accuracy/
  confidence
• Different approaches to gene finding improve
  accuracy/confidence of the predictions
• Ab Initio GenScan
• Ab Initio modified by BLAST homologies
  GenomeScan
• Homology guided GeneWise
• Gene prediction and sequence alignment
  separately Rosseta
• Ab initio with similarity in known proteins SGP-2

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Merci pour votre attention!