Difference between revisions of "Wikiomics:Cloning in silico"
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Latest revision as of 02:52, 4 March 2008
Cloning in silico proceduro of obtaining full or partial cDNA sequence of a gene by using computer only.
There are several variants:
- discovery of new splice forms of a known gene
- cloning a novel orthologue gene in new species
- cloning a new gene(s) using ESTs database alone (ESTs clustering)
databases of pre-clustered ESTs
A shortcut to obtain either consensus sequence (TIGR) or a set of ESTs (Unigene) derived from a gene of interest.
- STACKdb (limited access, tissue specific splice forms) 
- Unigene (no consensus sequence) 
- TIGR 
Search of ESTs databases using BLAST
- Depending on a level of homology we can use:
- blastn program, cDNA sequence as query, EST DB from the same species (== novel splice forms discovery in the same species)
- tblastn program, protein sequence as query, EST DB from the same (==paralogue discovery) or other species (== cloning any homologues)
If possible, use protein sequence from related species i.e zebrafish protein when looking for a homologue in salmon), but for a large number number of proteins one can detect homology between human and C.elegans.
- Restrict blast output with species, i.e search only porcine ESTs to simplify the output
- On the BLAST output page select reasonable hits by checking box on the left in the alignment section.
- Retrieve all checked results as FASTA file (i.e. pig_Xgene_ESTs_date_round1.fasta
- check how many sensible hits you got, i.e. using grep on Unix/Linux
grep '>' pig_Xgene_ESTs_date_round1.fasta | wc
- assembly all your EST sequences using phrap (on Unix command line):
you should get file: pig_Xgene_ESTs_date_round1.fasta.contigs
If you do not have phrap you may use:
You may download sequences of human SYNGR4 [ESTs http://www.ncbi.nlm.nih.gov/UniGene/clust.cgi?UGID=221005&TAXID=9606&SEARCH= here], save it as FASTA file and then feed CAP3 or ESSEM with it to check how it works. Use Suggested assembly sequence:
>assembly: gnl|UG|Hs# -> gnl|UG|Hs# (R) TTTTTTTTTTTTTTTGTTTTTAGAAACCCTTCTGGAGGGAGGATTCTCTCTTTATTGATTTGGATAAGGATATTTAGTTG TCAGGCATCATAGCAAGCCGGGGGGACTTTGGAGCGGTCAGACAGGGGGACAGGGCAGAGCTAGCATAACTCAGGCTGTT GGGGCCAGTGGTGGGCATGTTCACAGGGCTGTTGGCAGAGGGCAAGGGGAGGGTGGTCAGCACCATGCCACCCTCATCCA GGAAGCGCTTGTAAGGGACTGGAGCATCATTTCGGAGGTCCTGGAATGCCAGGTAGGCCTGGAATATCCAGACAAGGATG GAGAAGAAGGTGAAGGCGATGGCTGCCTGGCACTGCTGCTCCCCAGGAGGAACTCTTTGGGCGGCGAATGCTGCCATTGG TTGGCCAGGAAGCAGAAACCCATGAACCAGACAACTGCCCAGAGAACAGCCAGGATGAAGTCCAGGAGCTGGAAGGCTGT CTTGAAGCGGGTGCCGGCAATGCGGGTCTCCTGTGTGTCCAGGACGAGGAAGGCCAGCCACGCTGAGGAAGGCCAGGAAG CCGGCTCCCACGGCAAAGCTGCAGGCCACGCTGTTGCTGTTGAGAATGCAGTGGAGCTGCGGAGACTCCATCTTGTTCTG GTAGCCGTCGGTCAGCAGGGAGGAGAAGACGATCAGGGAGAAGACCCCTGCCTCCCCCACACTCTCCTTCTGCCACCAAA CC
- mask possible repeats using RepeatMasker server. ESTs libraries are notorious for containing non-spliced ESTs/containations.
- use masked consensus sequence (MCS) from step above in next round of BLAST search:
in blastn program, MCS as query, EST DB from the same species
check how many sensible hits you got.
- repeat ESTs assembly, repeat masking, compare new ESTs contigs with contigs from the previous step until you got no new hits in ESTs database.
- after every assembly step make sure that the contig you use contains sequence of interest (== compare it with the first cDNA or protein sequence)
Genome annotation using ESTs assembly
importing human, mouse and zebrafish EST trace files
For a significant subset of human, mouse and zebrafish ESTs there are available trace and even experiment files. For a sane gene cloning we need them because:
- sequences in GeneBank are usually shorter than original trace files
- there is no way you can detect a sequencing error in plain text/fasta file without looking at trace file
In order to get them one can search for relevant trace files using Sanger's Trace server:
After blsting one can retrieve trace files as compressed tar in SCF or RCF. RCF is encoded & shrinked SCF: obtain and compile rcf2scf program here if you plan to get large number of trace files for speeding up transfer times.
- based on homology
- de novo
This will be covered in genome annotation guide.