Genomic analysis is the identification, measurement or comparison of genomic features such as DNA sequence, structural variation, gene expression, or regulatory and functional element annotation at a genomic scale. Methods for genomic analysis require high throughput sequencing or microarray hybridization and bioinformatics.
However, the pace of genome annotation is not matching the pace of genome sequencing. Experimental genome annotation is slow and time consuming. The demand is to be able to develop computational tools for gene prediction.
Working of analysis of Genome
Given a DNA sequence, what part of it codes for a protein and what part of it is junk DNA.
Classify the junk DNA as intron, untranslated region, transposons, dead genes, regulatory elements etc.
Divide a newly sequenced genome into the genes (coding) and the non-coding regions.
Computational Gene prediction is relatively simple for the prokaryotes where all the genes are converted into the corresponding mRNA and then into proteins. The process is more complex for eukaryotic cells where the coding DNA sequence is interrupted by random sequences called introns.
The importance of genome analysis can be understood by comparing the human and chimpanzee genomes. The chimp and human genomes vary by an average of just 2% i.e. just about 160 enzymes. A complete genome analysis of the two genomes would give a strong insight into the various mechanisms responsible for the differences.
DNA annotation is the process of identifying the locations of genes and coding regions in a genome to create ideas about the possible functions of the genes. There are three main steps to annotate the genome, which include to:
Identify the portions of the genome that are not involved in coding proteins
Identify the main elements of the genome (gene prediction)
Connect the main elements of the genome with biological information
It is important to consider how the genome is similar to other genomes that are already known, as this can help when establishing the role of the gene. Additionally, the plasmids, phages and resistance genes of the genome can reveal information about the nature of the genome. The traditional method of curation method uses the Basic Local Alignment Search Tool (BLAST) algorithm to find similarities to annotate the genome. However, this approach involves expert knowledge and experimental verification to be carried out.
There are also certain tools that can automatically annotate the genome in silico, which tend to be more efficient than the curation method and can provide additional information. Both curation and technological automation tools are often used together to complement each other in the provision of results.
The recent advances in technology that allow high throughput genomic sequencing to be undertaken quickly and relatively cheaply has propelled the work of genome analysis forward. However, this progression also places a large demand for efficient and robust tools of analysis to interpret the data into a form that can be utilized in practice. The massive sets of data that have been produced by projects, such as the Human Genome Project, remain largely under-utilized, despite the fact that the project concluded more than a decade ago.
There are several important functions of the tools used in the process to analyze genomes. The tools should have capabilities to:
Compare variant calls between genomes
Export data into convenient formats for analysis
Filter and annotate results to increase ease of analysis
Create a reference genome for successive analyses
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We are providing “Genome Analysis” service to our customers to study, identify or measure certain features of DNA at genomic level and to strive high quality research and will advance science in the domain of Genome Analysis.