Written by Ummulwara Qasim
Our genome is the hard drive of our genetic material. Not only can it tell us about our physical characteristics and what has been passed on to us from our parents, but it can be an indicator of what is to become of our body in the future. Analyzing an individual’s genome can determine the gene expressions of different genetic diseases, thus allowing for future methods of predicting the likelihood of the person developing the disease. But how can we reach that option of genome analysis?
The central dogma in molecular biology describes the method of information flow within our genes which starts from DNA that is transcribed to RNA and then translated to protein. During transcription, mRNA, which is a key component in relaying the genetic information to proteins for gene expression, is formed. The variations in gene expression can be further studied by analyzing mRNA which can help to explain the transcriptional machinery in our genome. Transcripts are composed of mRNA and are a part of gene expression and are part of the transcriptome which is the total sum of all mRNA components that takes part in gene expression [1]. Transcripts and gene expression provide vital information about the possible function of the gene. How can this be studied? Scientists have been using a recently discovered approach called RNA-sequencing that uses deep-sequencing methods to perform transcriptome profiling [2]. There is a whole area of research dedicated to studying the whole set of transcripts in our genes to understand gene development, function, translation, and expression.
The technique of RNA-sequencing is based on using RNA components as a whole to be fractionated and then sequenced to analyze each segment [4]. These segments can be mapped out and scaled for different expression levels in various regions. RNA-sequencing has been shown to be highly accurate in quantifying levels of gene expression [4]. These quantified levels of gene expression and mapped regions can be seen as indicators for specific genes that may represent a genetic disease. Analyzing the genetic material in a transcript-level basis can also allow for detection of polymorphisms, which are variations that occur in the genes that contribute to genetic variations of different characteristics that a gene may express, that have occurred in the genome [3]. These polymorphisms can occur not just from random mutations within our DNA, but can also have mutations influenced from environmental factors. These polymorphisms can be associated to different diseases that may result due to these changes in the genome. Knowing these analyzed components in the genome can allow for personalizing treatment methods for these diseases according to an individual’s genetic makeup.
The area of RNA-sequencing and other genetic sequencing methods is still further developing. At the University of California, Irvine, Dr. Ali Mortazavi and his lab study transcriptional regulation and use many genomic techniques, such as RNA-sequencing, in their projects. Dr. Mortazavi was one of the primary scientists in pioneering the development of RNA-sequencing. During his time in graduate school years in California Institute of Technology, he had the landmark paper regarding the the topics of RNA-sequencing which has now been cited over 6,000 times over the course of years. Dr. Mortazavi is also a part of the ENCODE (Encyclopedia of DNA Elements) project with the interest of annotating all of the functional elements in the human genome. His lab aims to build global models for gene regulation and apply these techniques to study animal developments, and ultimately the human genome. RNA-sequencing is one of the many sequencing techniques the lab uses to understand the outputs of gene expression and analyze it comparatively among different evolutionary species. Future directions the lab will take is to focus on understanding everything at a single-cell level and to try to use newer sequencing technologies to be able to analyze larger sequences as compared to RNA-sequencing which works with smaller segments. Dr. Mortazavi is also interested in developing techniques for reprogramming cells by taking a cell and adopting it to a different fate. “Many of these techniques can be applicable in advancing medicine,” Dr. Mortazavi mentioned, “I’m interested in characterizing the functional genome and the techniques that are used in characterizing the functional genome are ultimately going to be useful in personalized medicine.” These findings can result in new methods to be used in the field of medicine for different treatment options that can be used for our current genetic diseases. Dr. Mortazavi remarked, “Understanding the underlying laws of nature is what I hope to do, and if one day someone comes by to do the translational work to apply it to personalizing medicine, then that would be even better for the field of science.”
References:
- Genome: Transcriptome. 27 August 2015. Bethesda (MD): National Human Genome Research Institute; [accessed 2016 October 27]. http://www.genome.gov
- Conesa A., Madrigal P., Tarazona S., Gomez-Cabrero D., Cervera A., McPherson A., Szcześniak M.W., Gaffney D.J., Elo L.L., Zhang X., Mortazavi A. 2016. “A survey of best practices for RNA-seq data analysis.” Genome biology. 17:13
- Zeng W., Jiang S., Kong X., El-Ali N., Ball A.R. Jr., Ma C.I., Hashimoto N., Yokomori K., Mortazavi A. 2016. “Single-nucleus RNA-seq of differentiating human myoblasts reveals the extent of fate heterogeneity.” Nucleic Acids Research. 19: gkw739
- Wang Z., Gerstein M., Snyder M. 2009. “RNA-seq: a revolutionary tool for transcriptomics.” Nature Reviews Genetics. 10: 57-63