Question

1. With the rise of functional genomic approaches, large amounts of data can be generated in a relatively short amount of time. What are some pros and cons of this development? Do you think traditional forward genetics still has a role to play in research?

Answer 1

During the era of genomics, scientists studied the genome of (Total Genetic Content) and accumulated the whole knowledge of the genes, DNA sequences, their counterparts in the proteins, regulatory genes, etc. Many hypothetical proteins are identified with unknown functions.

Functional genomics is the research domain that assigned a function to a given gene product has then been developed. But even in this high-technological research, the genomic study is depending on the bio-informatics on one hand but experimentation is equally important to study the effect of proteins and their application on life. When the mad-cow disease took human infections, study of prions needs experimentation on animals to human beings.

One major disadvantage of micro-array analysis is results may be different than results contained at proteomic level due to post-transcriptional levels.

In case of pathogenic bacteria, they exhibit special peculiarities due to their interaction with the host cells and due to the contamination of the experiments. They also exhibit sudden and new development which is very difficult to study and apply available knowledge and further experimentation is needed, At levels we have to depend on bio-informatics to study and identify virulence factors.

The use of hetrologous expression, to study its effects is a common approach. Sequence-based functional genome, relies mainly on similarities of sequence at various levels such as nucleotide or protein level, i.e., structural level. But when we study functional level, various unknown factors still needs experimental verification.  

Experiment-based functional genomics performed to study at different levels - pre-transcriptional level, transcriptional level and translational level, random meta-genesis, RNA micro-arrays and RNA sequences and proteins. Using 2D gel followed mass-spectometry, all this needs experimentation.

Adaptation - Depending on the functional genomics, when the forecast, apply our knowledge and establish experiments, but 100% exact is not matching as there are some new developments takes place where we find there is a knowledge-gap and further experimentation is required. For example, human genome is composed of 46 chromosomes, 23 pairs. Each chromosome contains hundreds of genes which are separated by intergenic regions.

The intergenic regions contain gene related sequences and extragenic DNA. 70% of DNA is extragenic DNA. Of this, 20% is moderately or highly repetitive DNA. Remaining 80% is unique or single copy sequences. Repetitive DNA includes dispersed and clustered repeats.

The repetitive sequences are used to identify parental conformation (paternal identification) and forensic studies. But these sequences, as we dont code for any proteins, how to study their function needs experimentation. As per the human genomic studies, the protein encoding genes are 2% of the human genome. Out of total genes discovered, 50% genes functions are not known. So this needs large amount of higher-technology as well as classical experimentation. This information promises to revolutionize processes of finding chromosomal locations for disease-associated sequences and tracing human history.

Due to various applications, adaptations are developed by various organisms, general adversity is increasing, organisms are developing resistance where new corners are opening where experimentation is very much required.

Unknown end-points, which are unable to clear the present situations, needs experimentation and higher technology as all are life-related processes.

When we cross the plants and variations develop, these are not predictable or known variations. So applying higher technology without experimentation, probably is impossible.