Presentation on theme: "An Introduction to Bioinformatics Finding genes in prokaryotes."— Presentation transcript:
An Introduction to Bioinformatics Finding genes in prokaryotes
AIMS To establish the concept of ORFs and their relationship to genes To describe the features used by software to find ORFs/genes To become familiar with Web-based programmes used to find ORFs/genes OBJECTIVES To be able to distinguish between the concepts of ORF and gene Use ORF Finder to find ORFs in prokaryotic nucleotide sequences
Usually the primary challenge that follows the sequencing of anything from a small segment of DNA to a complete genome is to establish where the location functional elements such as: genes (intron/exon boundaries) promoters, terminators etc DNA sequences that may potentially encode proteins are called Open Reading Frames (ORFs) The situation in prokaryotes is relatively straightforward since scarcely any eubacterial and archaeal genes contain introns
FINDING ORFs The simplest method in prokaryotes is to scan the DNA for start and stop codons The DNA is double stranded and each strand has three potential reading frames (codons are groups of 3 bases) THE CAT ATE THE RAT Frame 1 T HEC ATA TET HER AT Frame 2 TH ECA TAT ETH ERA T Frame 3 The scan must look at all 6 reading frames
Any region of DNA between a start codon and a stop codon in the same reading frame could potentially code for a polypeptide and is therefore an ORF Start AUG (methionine)Stop UAA UAG UGA small potential coding sequences like this will occur frequently by chance, and therefore the longer they are the more likely they are to represent real coding regions, genes Problems Small genes may be missed The actual start codon may be internal to the ORF There may be overlapping genes
The simplest tool for finding ORFs is ORF Finder at NCBI It simply scans all 6 reading frames and shows the position of the ORFs which are greater than a user defined minimum size The genetic code used for the analysis can be altered by the user This would be important if e.g. mitochondrial or ciliate nuclear DNA were being analysed
To overcome the limitations of ORF finder, more sophisticated programmes detect compositional biases and increase the reliability of gene detection These compositional biases are regular, though very diffuse, And arise for a variety of reasons: many organisms there is a detectable preference for G or C over A and T in the third ("wobble") position in a codon all organisms do not utilize synonymous codons with the same frequency - consequently there is a codon bias there is an unequal usage of amino acids in proteins sufficient to cause a bias in all three positions of codons and increase the overall codon bias
the %GC content of the first two codon positions of the universal genetic code is approximately 50%, therefore, organisms which have a low or high %GC content will exhibit a marked bias at the third position of codons to achieve their overall %GC content The most recent approaches to using compositional features to distinguish coding from non-coding regions employ ‘Markov models’ such approaches include the popular GENEMARK and GLIMMER programs
Finding Genes in Eukaryotes An Introduction to Bioinformatics
AIMS To establish the concept of ORFs and their relationship to genes To describe the features used by software to find ORFs/genes To become familiar with Web-based programmes used to find ORFs/genes OBJECTIVES To be able to distinguish between the concepts of ORF and gene Use ORF Finder to find ORFs in prokaryotic nucleotide sequences To describe the complications of the eukaryote “signals” To be aware of the Web-based programmes To be able to use the eukaryote programmes for a number of organisms
Organisms whose cells have a membrane-bound nucleus and many specialised structures located within their cell boundary. In these organisms, genetic material is organized into chromosomes that reside in the nucleus.
Principles Content - codon usage – often species or class specific Signals - PWMs – principle is the same, signals are different – Complication of introns/exons
Eukaryotic promoter TATA boxGC boxCAAT box 5’ 3’ -110 -40 -25 +1 mRNA In addition - transcription factor binding sites Genes can be enormous! Controlled by “distant” enhancers
AAUAA ~ 12bp polyA AAAAA…... Kozak sequence At translational start Polyadenylation sequence AUG Signals on the mRNA STOP
Introns and Exons Chicken 1 2 collagen gene has - 38 kb > 50 Introns Muscular Dystrophy gene is 2.5 Mb and has ? Exons!
Splicing signals C A T C A G C T AGGT AGT N AGG () >11 5’Exon 3’Exon GT-AG rule
Exon finding Initial exons, from the initiation codon to the first splice site; Internal exons from splice site to splice site; Terminal exons from splice site to stop codon; Single introns corresponding to uninterrupted, intronless genes, i.e., running from initiation codon to stop codon.
Intergrated Gene Parsing Search for signals Perform a content analysis Define the intron/exon boundaries