Bioinformatics Workshops 1 & 21. use of public database/search sites
- range of data and access methods - interpretation of search results
- understanding the meaning & effect of search (e.g. BLAST) parameters
2. functional analysis of single sequences- i.e. how to work out what your unknown
protein might be doing- complex searches for (e.g.) patterns of
motifs & secondary structure elements
Workshop 1.overall survey of data
Mutation between species -> orthologs
Mutation between duplications -> domains
Search methods – 2D vs. 3D
Search methods – similarity vs. models vs. comparative
Main data axes
Main Portals
Database searches vs. genome browsers
Finding similar sequences
BLAST, et al
E-values!
Biological origin of sequences
Genes vs.loci
Random sequences
Using Public Data Resources
• There is (are!) data out there• There are methods out there• Quite often they are combined
– BLAST searches of sequence databases
Notes…
• Sequence databases– Entrez queries…
• Genome browsers/databases• Regulatory Elements• SNPs• Functional Sequence Models (PFam domains,
etc.)• Expression Data
– Array data– in situ data
Notes II
• Blast parameters– Low complexity: frameshifted cDNA– miRNAs vs genome– morpholinos for other genes– -q-2 for EST vs EST alignments– Entrez queries
What have we got…gene model
locus
~ gene
mRNA
protein
genomeprimary transcript
Derivative Sequences
mRNA
clone into cDNA library
3’ EST
5’ EST
cDNA sequence
Single pass sequence from each end of the clone
Multiple pass sequencing over whole length of the clone
Initial Growth of Databases
• Lots of ESTs were generated
• Some clones were selected for full-insert sequencing -> cDNAs
• cDNAs were translated to yield presumed protein sequences
Then Came Genomes
• With increasing larger fragments of genomic sequence came the ability to align cDNAs to create gene models
• And then to apply our understanding of exon/intron structure to predict theoretical genes…
Introns and Exons
gene model
genome
CTACCATCCATGCTAACCATTCTACCATTTTATACTCATGCAACGGACCGTAGCGTAGTCGCTTAGCATCCTTTATAACTGGCTA
CTACCATCCATGCTAACCATTCTAC CATTTTATACTCATGCAACGGACCGT AGCGTAGTCGCTTAGCATCCTTTATAACTGGCTA
CTACCATCCATGCTAACCATTCTACGTAAGTCATCTATATCAATATTATTTCAGCATTTTATACTCATGCAACGGACCGTGTCAGTATTACAGAGCGTAGTCGCTTAGCATCCTTTATAACTGGCTA
GTAAG.donor
.TTTCAG acceptor
mRNA
exon intron exon intron exon
splice sites
Gene PredictionsGiven:- coding sequence must run from ATG – STOP codon in-frame- introns GT. . . . . . AG can be spliced out
Also take a statistical approach:- coding and non-coding sequence are slightly different in composition- some ‘possible’ splice sites are more likely than others
. . .CGTCGTATGGCTTCGATGTAGTACATCGGATCGGTATGGAATCATTTCAGTCGCTAGCTAGCCTAACGTATATAGCTAGGTAAGACTA. .
. . .CGTCGTATGGCTTCGATGTAGTACATCGGATCGGTATGGAATCATTTCAGTCGCTAGCTAGCCTAACGTATATAGCTAGGTAAGACTA. .. . .CGTCGTATGGCTTCGATGTAGTACATCGGATCGGTATGGAATCATTTCAGTCGCTAGCTAGCCTAACGTATATAGCTAGGTAAGACTA. .
. . .CGTCGTATGGCTTCGATGTAGTACATCGGATCGGTATGGAATCATTTCAGTCGCTAGCTAGCCTAACGTATATAGCTAGGTAAGACTA. .
. . .CGTCGTATGGCTTCGATTCGCTAGCTAGCCTAACGTATATAGCTAGGTAAGACTA. . .
. . .CGTCGTATGGCTTCGATGTAGTACATCGGATCGTCGCTAGCTAGCCTAACGTATATAGCTAGGTAAGACTA. . . . . .CGTCGTATGGCTTCGATGTAGTACATCGGATCGGTATGGAATCATTTCAGTCGCTAGCTAGCCTAACGTATATAGCTAGGTAAGACTA. .
. . .CGTCGTATGGCTTCGATTCGCTAGCTAGCCTAACGTATATAGCTAGGTAAGACTA. . .
. . .CGTCGTATGGCTTCGATGTAGTACATCGGATCGTCGCTAGCTAGCCTAACGTATATAGCTAGGTAAGACTA. . .
scan genomic sequence …
. . .CGTCGTATGGCTTCGATGTAGTACATCGGATCGGTATGGAATCATTTCAGTCGCTAGCTAGCCTAACGTATATAGCTAGGTAAGACTA. .
most likely gene model
Supporting Evidence!
EST evidence
genome
gene model
We note that even though there is good evidence for the existence of all four exons, there is no evidence that all the exons would appear on a real transcript. An alternative transcript, skipping exon 3, would be plausible, if a little unlikely.
This gets less ambiguous as more ESTs are available, and clones are sequenced at both ends (which helps put distant exons into the same transcripts), and eventually full-length transcript sequences are available.
exons: 1 2 3 4
So What’s in the Databases Now?
• At NCBI– 15,000,000 EST sequences– 3,329,110 non-redundant DNA sequences (excluding
ESTs, etc.)– 2,693,904 non-redundant translated coding
sequences – 954,378 Protein Reference Sequences sequences
(RefSeq)• But the majority of RefSeq may be translations
of theoretical transcripts…
Main Data Axes
• Europe: EBI/EMBL– Swiss-Prot/Trembl/Ensembl/UniProt
• US: NIH/NCBI– GenBank/UniGene/RefSeq/Entrez
• Japan: DNA Data Bank of Japan – National Institute of Genetics
Synchronisation…
GenBank
DDBJ
EMBL
ATCGATCGATCATAGTATGCTAGCTGCTA
BC009638.1
ATCGATCGATCATAGTATGCTAGCTGCTA
BC009638.1
ATCGATCGATCATAGTATGCTAGCTGCTA
You submit a sequence
BC009638.1
ATCGATCGATCATAGTATGCTAGCTGCTA
Sequences, Accession Numbers and Genes
NM_001015922.1 gi=62860271
GATCGTTCGATTAGCTAGGGACACCACCGATCGATATGACCACAAAAA
BC009638.1 gi=16307106
GTTCGATTAGCTAGGGACACCACCGATCGATATGACCACAAAA
NM_001015922.2 gi=62860589
GACCGTTCGATTAGCTAGGGACACCACCGATCGATATGACCACAAAAA
Main Data Portals
• NCBI Entrez Databases• ExPASy Proteomics Server• DNA Data Bank of Japan DDBJ• EBI Ensembl Genome Browser• Santa Cruz Genome Browser