Tuuli Lappalainen is an Assistant Professor in the Department of Systems Biology at Columbia University and a Junior Investigator and Core Member at the New York Genome Center. Her research focuses on functional genetic variation in human populations and its contribution to traits and diseases. The work of her research group, physically located at New York Genome Center in lower Manhattan, links computational and population genomics to experimental molecular biology. While their individual projects may focus on specific diseases, the overall goal is to uncover general rules of the genomic sources of human variation. She also seeks to push the discoveries and methods from her research projects further towards clinical applications. (Source: Columbia)
The following has been paraphrased from an interview with Prof. Tuuli Lappalainen on July 20th, 2018.
(Click above to listen to the full audio version or click here for a downloadable version)
How do you define transcriptomics to a lay audience?
In transcription, a gene is expressed or activated by copying the information contained in DNA into RNA, which then gets translated into a protein. In transcriptomics, we analyze the information in these transcripts that are present throughout a cell or tissue sample. This allows us to understand all the RNA and all the products of gene expression in that sample.
When and how did the field begin?
About 20 years ago, the first transcriptomic type of analysis started when expression micro-arrays were developed. This technology allows us to measure the expression of specific genes. In many ways, this was one of the first ‘big data’ approaches to genomics. The next big wave started about 10 years ago when high-throughput sequencing technologies (an automated process that can quickly read the nucleotide sequence of DNA, or RNA) were developed that allowed us to sequence RNA. This really pushed the field forward and gave us a lot of new insights into cellular biology.
Compared to how much we know about the genome, how much do we know about the transcriptome?
It is hard to say if we know more about the genome or the transcriptome. Genomes of complex species are very large, but only 3% of them are genes. The transcriptome are the functional sites of the genome, and in some ways it is a little bit easier to analyze because it is just a part of the genome. But the two fields have evolved together; nothing on the genome makes sense except in the light of the transcriptome. A genome without a functional interpretation of what it actually does (the transcriptome), doesn’t tell us very much.
How much further does an understanding of our transcriptome get us to a complete understanding of our biology?
When we think about the study of genetic diseases and trying to understand genetic variants that contribute to disease, a lot of it is done through genome and exome (all of the protein-coding genes in a genome) sequencing. But now we are also starting to analyze the transcriptome of patients to help us interpret their genome. We know the genetic code and how it is translated into proteins, but when it comes to gene regulation (how genes are switched on and off, and understanding when the genes are expressed and active), that is a really hard problem to understand. Transcriptomics is enabling us to solve this problem.
Are there ‘transcriptic’ diseases as there are genetic diseases?
A ‘transcriptic’ disease would I guess be one that is not caused by a mutation but somehow by gene regulation. The transcriptome captures many aspects of the functional state of cells, including how the cells are functioning and how their molecular networks come together. Disruptions in that process can be caused by genetic mutations, or by environmental effects. I’m not sure I would call any disease ‘transcriptic’, but in most diseases there are things going wrong at the cellular level that the transcriptome can help capture.
Do you see any new tools or techniques coming that might help push the field forward?
One very exciting technology is called long-read sequencing from Oxford Nanopore that allows us to sequence full transcripts. The current technologies just read short fragments of the genome or the transcriptome and can be difficult to put together. Emerging technologies will allow us to take the full transcript, which is the functional unit in the cell, and read it as is, giving us a more thorough understanding of the transcriptome.
What excites you most about the future of this field?
Many things. One thing I should mention is the All of Us project launched by the Obama administration that is collecting a large amount of genomic and lifestyle data from a huge cohort of people. It would be very interesting to add transcriptome readouts to the databases being created from this and other similar projects. That would allow us to better integrate the fundamental information from the genome and apply it to clinical practices.