Genome Analysis

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Genome Analysis
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• Gene catalogues
• Data retrieval
• Comparative Genome Analysis

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Sequencing large genomes
The hybrid approach
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The evidence for a gene
mRNA
reverse transcription
cDNA
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Ensembl Gene catalogue

• Gene view exon info

Supporting evidence (exon)
Protein alignment
DNA alignment
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Gene catalogues - information hubs
Ensembl UCSC NCBI
entry points for interrogation
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Reference Sequences
Goal One sequence entry for each naturally
occurring DNA, RNA and protein molecule
chromosome
gene
NC_000000
NG_000000
Key curated calculated
mRNA
protein
contig
NM_000000
NP_000000
NT_000000
predictedmRNA
predictedprotein
XM_000000
XP_000000
Multiple products for one gene are instantiated
as separate RefSeqs with the same GeneID.
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General Gene classification
Known genes as catalogued by the reference
sequence project Ensembl known genes (red
genes) NCBI known genes Novel genes (1)
based on similarity to known genes, or cDNAs
these need not have 100 matching supporting
evidence Ensembl novel genes (black) NCBI Loc
genes (locus)
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General Gene classification
Novel genes (2) based on the presence of
ESTs resource of alternative splicing EST genes
in Ensembl (purple) Database of transcribed
sequences (DOTs) www.allgenes.org Acembly
(assembly) Gene prediction Single organism
Genscan Comparative information
Twinscan commonalities and differences Pseudog
enes - matches a known gene but with a disrupted
ORF Gene prediction with NO prior expressed
sequence as evidence
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Ensembl entry points

• Home page

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Ensembl entry points

• Genetic interval

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• Gene catalogues
• Data retrieval
• Comparative Genome Analysis

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Data Retrieval

• Biomart

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• Gene catalogues
• Data retrieval
• Comparative Genome Analysis

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The perfect model?
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Mouse genes and MGI
http//www.informatics.jax.org/
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And the list goes on.
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Comparative Genome Analysis

• Functionally conserved units may be conserved
  at the sequence level
• Evolutionary conserved regions

functional units
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• Why Comparative Genome Analysis?
• allows us to achieve a greater understanding of
  vertebrate evolution
• tells us what is common and what is unique
  between different species at the genome level
• the function of human genes and other regions
  may be revealed by studying their counterparts in
  lower organisms
• helps identify both coding and non-coding genes
  and regulatory elements
• Genome browsers have done some work, we can do
  more

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Compare Genome Sequences-Multicontigview in
Ensembl
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Compare Genome Sequences- UCSC
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Identify Evolutionary Conserved Regions yourself

• To identify ECRs, you must
• Identify (if necessary extract) the relevant
  genome sequences
• Annotate the genome sequences
• Mask out repetitive sequences

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Programmes for identifying ECRs

• Pipmaker http//bio.cse.psu.edu/cgi-bin/pipmaker
  
• requires repeatmasked and annotation
  files
• Vista http//www-gsd.lbl.gov/vista
• requires annotation files, repeat masks
  for you
• zPicture - http//www.dcode.org

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PIP - http//bio.cse.psu.edu/cgi-bin/pipmaker/
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VISTA - http//www-gsd.lbl.gov/vista/
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zPicture
Uploads sequence and annotation files directly
from UCSC Allows regulatory elements to be added
to the alignment via link to rVista
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Visualisation of ECRs