Genes for everybody
The “-omics” field is exploding. Technology in proteomics, transcriptomics, metabolomics and interactomics is becoming increasingly more efficient and accurate. The implications are profound, particularly in medicine, where disease diagnosis can be done hastily, treatments can be tailored to specific forms of a disease and drug targets can be identified easily in a laboratory.
The trendsetter is genomics, of which the technology has advanced rapidly. Nature has just published the results of the 1000 Genomes Project. In the five-year $120 million project, researchers were able to sequence the genomes of 1092 people from 14 populations in Europe, East Asia, sub-Saharan Africa, North America and South America. These figures are even more impressive by the fact that the bulk of the sequencing was completed within a year, using the latest and most efficient technologies available.
The director of the Wellcome Trust (a co-financer of the project), Sir Mark Walport commented in the Guardian on how remarkable it that the first human genome that was published in 2003 took ten years to sequence, compared to volume sequenced in this study.
“This study is an important contribution to our understanding of human genetic variation in health and disease and the DNA sequences are freely available for analysis and use by researchers” says Walport.
Genetic sequencing technology is evidently getting very efficient. Following the completion of the Human Genome Project, which cost over $US 2.7 billion over the 13 years or so of the project, the new goal was to sequence an entire human genome for under $US 1000. Earlier this year Ion Torrent have released the $100,000 Ion Proton machine, which is able to sequence each individual genome for $1000.
The 1000 Genomes Project will allow for geneticists to identify the variants associated different diseases in different populations. It is foreseeable that a doctor will be able to diagnose a patient by cheaply sequencing their genome and identifying genetic variants, which were first found in the 1000 Genomes Project, and then subsequently associated with diseases.
All we hope now is that there is enough space on the computers to store all this information.