Genomics:
READING genome sequences
ASSEMBLY of the sequence
ANNOTATION of the sequence
carry out dideoxy sequencing
connect seqs. to make whole chromosomes
find the genes!
For Bioinformatics, Start with:
Genomics:
READING genome sequences
ASSEMBLY of the sequence
ANNOTATION of the sequence
carry out dideoxy sequencing
connect seqs. to make whole chromosomes
find the genes!
For Bioinformatics, Start with:
2 ways to annotate eukaryotic genomes:
-ab initio gene finders:
-Genes based on previous knowledge….EVIDENCE of message
2 ways to annotate eukaryotic genomes:
-ab initio gene finders:Work on basic biological principles:
Open reading framesConsensus splice sitesMet start codons…..
-Genes based on previous knowledge….EVIDENCE of message
2 ways to annotate eukaryotic genomes:
-ab initio gene finders:Work on basic biological principles:
Open reading framesConsensus splice sitesMet start codons…..
-Genes based on previous knowledge….EVIDENCE of message cDNA sequence of the gene’s message
cDNA of a closely related gene’ message sequenceProtein sequence of the known geneSame gene’sSame gene’s from another speciesRelated gene’s protein…….
Homology based exon predictions
Consensus genestructure (both strands)
start and stop site
predictions
Splice site predictions
computational exon
predictions
Tracking information
Unique identifiers
Information for Ab initiogene finding
Automaticallygeneratedannotation
A zebrafish hit shows a gene model protein encoded by a 6 exon gene.
This gene structure (intron/exon) is seen in other species, as is the protein size.
The proteins, if corresponding to MSP in S. gal., must be heavily glycosylated (likely). At least some have a signal peptide.
The zebrafish hit can be viewed at higher resolution, and…
The zebrafish hit can be viewed down to nucleotide resolution
GO LIVE!
Sarin et al
Sarin et al
Is there linkage between a mutant gene/phenotype and a SNP?
USE standard genetic mapping technique, with SNP alternative sequences as “phenotype”
B= bad hair, DominantSNP1 ..ACGTC..SNP1’ ..ACGCC..
SNP2 ..GCTAA..SNP2’ ..GCAAA..
SNP3 ..GTAAC..SNP3’ ..GTCAC..
X
XSNP1’ ..ACGCC..SNP1’ ..ACGCC..
SNP2’ ..GCAAA..SNP2’ ..GCAAA..
SNP3’ ..GTCAC..SNP3’ ..GTCAC..
SNP1 ..ACGTC..SNP1 ..ACGTC..
SNP2 ..GCTAA..SNP2 ..GCTAA..
SNP3 ..GTAAC..SNP3 ..GTAAC..
F1
START with Inbred lines-
SNPs are homozygosed
B
Is there linkage between a mutant gene/phenotype and a SNP?
USE standard genetic mapping technique, with SNP alternative sequences as “phenotype”
B= bad hair, Dominant
X
B/b b/b
B/b
B/b
b/b
b/b
1’/1 25%
1/1 25%
1’/1 25%
1/1 25%
1’/1 1/1
SNP1 ..ACGTC..SNP1’ ..ACGCC..
SNP2 ..GCTAA..SNP2’ ..GCAAA..
SNP3 ..GTAAC..SNP3’ ..GTCAC..
2’/2 47%
2/2 3%
2’/2 3%
2/2 47%
2’/2 2/2
3’/3 25%
3/3 25%
3’/3 25%
3/3 25%
3’/3 3/3
SO…B is 6 cM from SNP2, and is unlinked to SNP 1 or 3
B 2’ / b 2
Is there linkage between a mutant gene/phenotype and a SNP?
USE standard genetic mapping technique, with SNP alternative sequences as “phenotype”
B= bad hair, Dominant
X
B/b b/b 1/1’ 1/1
SNP1 ..ACGTC..SNP1’ ..ACGCC..
SNP2 ..GCTAA..SNP2’ ..GCAAA..
SNP3 ..GTAAC..SNP3’ ..GTCAC.. 2/2’ 2/2 3/3’ 3/3
SO…B is 6 cM from SNP2, and is unlinked to SNP 1 or 3
We have the ENTIRE genome sequence of mouse, so we know where the SNPs are
Now-do this while checking the sequence of THOUSANDS of SNPs
Genomics:
READING genome sequences
ASSEMBLY of the sequence
ANNOTATION of the sequence
carry out dideoxy sequencing
connect seqs. to make whole chromosomes
find the genes!
But Bioinformatics is more…
TRANSCRIPTOMICS: cDNAs
RNA target sampleRNA target sample
End Reads (Mates)End Reads (Mates)
SEQUENCESEQUENCE
PrimerPrimer
cDNA Library
Each cDNA provides sequence from the two ends – two ESTs
& ESTs: Expressed Sequence Tags
!!AA_SEQUENCE 1.0ab025413 peptide tenm4.pep Length: 2771 May 12, 1999 09:34 Type: P Check: 2254 ..
1 MDVKERKPYR SLTRRRDAER RYTSSSADSE EGKGPQKSYS SSETLKAYDQ
51 DARLAYGSRV KDMVPQEAEE FCRTGTNFTL RELGLGEMTP PHGTLYRTDI
101 GLPHCGYSMG ASSDADLEAD TVLSPEHPVR LWGRSTRSGR SSCLSSRANS
151 NLTLTDTEHE NTETDHPSSL QNHPRLRTPP PPLPHAHTPN QHHAASINSL
201 NRGNFTPRSN PSPAPTDHSL SGEPPAGSAQ EPTHAQDNWL LNSNIPLETR
251 NLGKQPFLGT LQDNLIEMDI LSASRHDGAY SDGHFLFKPG GTSPLFCTTS
301 PGYPLTSSTV YSPPPRPLPR STFSRPAFNL KKPSKYCNWK CAALSAILIS
351 ATLVILLAYF VAMHLFGLNW HLQPMEGQMQ MYEITEDTAS SWPVPTDVSL
401 YPSGGTGLET PDRKGKGAAE GKPSSLFPED SFIDSGEIDV GRRASQKIPP
Protein sequence: from peptide sequencing, or from translation of sequenced nucleic acids
Structural proteomics:Coordinates, rather than 1D sequence, Saved
/TRANSCRIPTOMICS (Arrays)
RNA for ALL C. elegans genesWhere? When? Who? are the RNAs
Where? When? Who? are the RNAs
Where? When? Who? are the RNAs
MICROARRAY ANALYSIS
Where? When? Who? are the RNAs
/TRANSCRIPTOMICS (Arrays)
Figure 4.15 Microarray TechniqueWhere? When? Who? are the RNAs
Figure 4.15 Microarray TechniqueWhere? When? Who? are the RNAs
Array analysis: see animation from Griffiths
Where? When? Who? are the RNAs
Figure 4.16(1) Microarray Analysis of Those Genes Whose Expression in the Early Xenopus Embryo Is Caused by the Activin-Like Protein Nodal-Related 1
(Xnr1)
Where? When? Who? are the RNAs
Figure 4.16(2) Microarray Analysis of Those Genes Whose Expression in the Early Xenopus Embryo Is Caused by the Activin-Like Protein Nodal-Related 1
(Xnr1)
Where? When? Who? are the RNAs
Where? When? Who? are the RNAs
Where? When? Who? are the RNAs
RNAi for every C. elegans gene too!
-results on the webProjects to systematically Knock-out (or pseudo-knockout)every gene, in order to establish phenotype of each gene -> function of each gene
Figure 4.23(1) Use of Antisense RNA to Examine the Roles of Genes in Development (here fly)
Figure 4.23(2) Use of Antisense RNA to Examine the Roles of Genes in Development (here fly)
RNAi for ALL C. elegans genes
Figure 4.24 Injection of dsRNA for E-Cadherin into the Mouse ZygoteBlocks E-Cadherin Expression
MODENCODE
MODENCODE
MODENCODE
MODENCODE
MODENCODE
MODENCODE
MODENCODE
MODENCODE
MODENCODE
MODENCODE was from the Drosophila paper:
Nature. 2011 Mar 24;471(7339):527-31. doi: 10.1038/nature09990.
A cis-regulatory map of the Drosophila genome.Nègre N et al.
Followed by INVERSE PCR to recover seqeunce adjacent to insertion.Then compare to the complete Drosophila genome sequence to know which ORF “Hit”
KNOCK-OUTS OF ALL ESSENTIAL GENES – RANDOM MUTAGENESIS ATTEMPT – using transposon mobilization
About 10% of All Assumed genes “Hit” (~10/100 per interval) on Drosophila X chromosome. 1 series of random insertion experiments.
ALL inset sites know, thanks to INVERSE PCR
Figure 1 The two-hybrid assay carried out by screening a protein array. a, The array of 6,000 haploid yeast transformants plated on medium lacking leucine, which allows growth of all transformants. Each transformant expresses one of the yeast ORFs expressed as a fusion to the Gal4 activation domain. b, Two-hybrid positives from
a screen of the array with a Gal4 DNA-binding domain fusion of the Pcf11 protein, a component of the pre-mRNA cleavage and
polyadenylation factor IA, which also consists of four other polypeptides36. Diploid colonies are shown after two weeks of
growth on medium lacking tryptophan, leucine and histidine and supplemented with 3 mM 3-amino-1,2,4-triazole, thus allowing growth only of cells that express the HIS3 two-hybrid reporter gene. Three other components of factor IA, Rna14, Rna15 and Clp1, were identified as Pcf11 interactors. Positives that do not
appear in Table 2 were either not reproducible or are false positives that occurred in many screens.
2-hybrid reaction between one protein and all 6000+ potential interactors in Yeast Genome
Figure 2 Visualization of combined, large-scale interaction data sets in yeast. A total of 14,000 physical interactions obtained from the GRID database were represented with the Osprey network visualization system (see http://biodata.mshri.on.ca/grid). Each edge in the graph represents an interaction between nodes, which are coloured according to Gene Ontology (GO) functional annotation. Highly connected complexes within the data set, shown at the perimeter of the central mass, are built from nodes that share at least three interactions within other complex members. The complete graph contains 4,543 nodes of 6,000 proteins encoded by the yeast genome, 12,843 interactions and an average connectivity of 2.82 per node. The 20 highly connected complexes contain 340 genes, 1,835 connections and an average connectivity of 5.39
Osprey: integrate all 2-hybrid interactions between all 6000+ proteinsin Yeast Genome (Proteome)
a