Gene prediction

A blog by Darshan Patil

Gene prediction refers to the process of identifying the regions of genomic DNA that encode genes.This includes protein coding genes, RNA genes and other functional elements such as the regulatory genes.It has vast application in structural genomics ,functional genomics , metabolomics, transcriptomics, proteomics, genome studies and other genetic related studies including genetics disorders detection, treatment and prevention.

Importance of Gene Prediction are:

• Recognize coding and non-coding locales of a genome.
• Predict complete exon — intron structures of protein coding regions.
• Describe individual genes in terms of their function.

Bioinformatics and the Prediction of Genes:

• With databases of human and model living being DNA groupings expanding rapidly with time, it has gotten practically difficult to complete the regular meticulous experimentation on living cells and life forms to foresee qualities.
• Formerly, statistical analysis of the rates of homologous recombination of several different genes could determine their order on a certain chromosome, and information from many such experiments could be combined to create a genetic map specifying the rough location of known genes relative to each other.
• However, today, the frontiers of bioinformatics research are making it increasingly possible to predict the function of such a deluge of genes based on its sequence alone.

Methods of Gene Prediction:

Similarity Based Searches:

• It is an comparatively basic methodology that depends on discovering closeness in quality successions between ESTs (communicated arrangement labels), proteins or different genomes to the input genome.
• Once there is similarity between a certain genomic region and an EST, DNA or protein, the similarity information can be used to infer gene structure or function of that region.
• Local alignment and global alignment are two methods based on similarity searches. The most common local alignment tool is the BLAST family of programs, which detects sequence similarity to known genes, proteins, or ESTs.
• Two more types of software, GeneWise and Procrustes and use global alignment of a homologous protein to translated ORFs in a genomic sequence for gene prediction.

Ab- initio Prediction:

• It uses gene structure as a template to detect genes.
• Ab initio gene predictions rely on two types of sequence information: signal sensors and content sensors.
• Signal sensors refer to short sequence motifs, such as splice sites, branch points, polypyrimidine tracts, start codons and stop codons.
• While content sensors refer to the patterns of codon usage that are unique to a species and allow coding sequences to be distinguished from the surrounding non-coding sequences by statistical detection algorithms.
• Exon detection must rely on the content sensors.

Original link- https://darshan-bioinformatics.tumblr.com/post/626768737905917952/gene