Human genome sequencing is the technique through which the exact order of nucleic acid base pairs in 24 chromosomes of human has been determined. It has constituted a major portion of our translational research since the completion of Human Genome Project in 2003. Scientists are working on this to understand and improve human health and disease.
The major aims of researchers in this technique are to improve the sequencing speed, its reliability and to decrease the cost.
Genomic sequencing technologies are used in three most important categories i.e. blood/lymph, cancers/neoplasms and immune system disorders.
There are four important sequencing technologies i.e. Sanger Sequencing, which is first generation sequencing, and Roche 454, Illumina Genome Analyzer (GA), and Applied Biosystems (ABI) SOLiD, which are second generation sequencing technologies.
None of these platforms are ideal for every application, so the scientists use every platform at different times and places. As for example, Illumina and SOLiD platforms, have lower cost and rapid turnover but their capacity for read length is limited. How we can merge the different qualities of these technologies, such as lower cost with improved read length and accuracy, can be an important research project in the field of genome sequencing. An important example in this regard is that of the first “third generation” sequencer released by Pacific Biosciences, last year. This system has a read length of greater than 1000 bases on average delivering results in less than a day.
Whole genome sequencing i.e. sequencing of entire genome is a costly hard work, requiring the more expensive Sanger sequencing due to the capacity for longer read lengths. Although, it is costly but scientists have used whole genomic sequencing for the development of targeted chemotherapies for lung adenocarcinoma, detection of BRCA1 and MYO1E mutations
Exome sequencing, in which only the transcribed regions of the genome are sequenced, can potentially be used to determine the genetic abnormalities in congenital defects. Moreover, this has been used more favorably in identification of specific mutations in more common complex disorders such as breast cancer, Parkinson’s disease and familial lipid disorders.
Another sequencing i.e. transcriptome sequencing can be used in the detection of changes in gene expression, in patients who were healthy a small time ago or within diseases such as breast cancer and malignant metastasis, and to identify the effects of drugs on patients.
As there is a huge amount of complex data obtained through sequencing technologies, so the researchers are now considering the point that there must be a good and reliable dealing with the computational complexities for analyzing the data as the genomic sequencing technologies are advanced than the computational complexities. In this regard, researchers of bioinformatics and translational medicine must collaborate with each other. Text mining algorithms focusing the field of biology and medical, and the integration of the electronic medical records (EMR) can help in combining the genomics with computational capabilities as these both may speed up the process of collection and analysis of structured data.
It must be considered that still there is a problem that sequencing technologies can miss parts of the genome that may be clinically important as it focuses on small polymorphisms. Research can also be done in developing and designing the multiple comparisons and sample size analysis.
Karen K Mestan, Leonard Ilkhanoff, Samdeep Mouli, and Simon Lin, (2011). Genomic Sequencing in Clinical Trials. Journal of Translational Medicine, doi:10.1186/1479-5876-9-222