A few posts ago, I wrote about a couple of grant proposals that we were preparing on methods to detect rare variants in cancer and improve the tools and methods to validate datasets from quantitative assays that utilize Next Gen data, like RNA-Seq, ChIP-Seq, or Other-Seq experiments. Besides the normal challenges of getting two proposals written and uploaded to the NIH, there was an additional challenge. Nearly everyday, we opened the tables-of-contents in our e-mail and found a new papers highlighting Next Gen Sequencing techniques, applications, or biological discoveries made through Next Gen techniques. To date, over 200 Next Gen publications have been produced. During the last two months alone more than 30 papers have been published. Some of these (listed in the figure below) were relevant to the proposals we were drafting.
The papers highlighted many of the themes we've touched on here, including the advantages of Next Gen sequencing and challenges with dealing with the data. As we are learning, these technologies allow us to explore the genome and genomics of systems biology at significantly higher resolutions than previously imagined. In one of the higher profile efforts, teams at the Washington University School of Medical and Genome Center compared a leukemia genome to a normal genome using cells from the same patient. This first intra-person whole genome analysis identified acquired mutations in ten genes, eight of which were new. Interestingly, the eight genes have unknown functions and might be important some day for new therapies.
Next Gen technologies are also confirming that molecular biology is more complicated than we thought. For example, the four most recent papers in Science show us that not only is 90% of the genome actively transcribed, but many genes have both sense and anti-sense RNA expressed. It is speculated that the anti-sense transcripts have a role in regulating gene expression. Also, we are seeing that nearly every gene produces alternatively spiced transcripts. The most recent papers indicate that between 92% and 97% of transcripts are alternatively spliced. My guess is that the only genes, not alternatively spliced are those lacking introns, like olfactory receptors. Although, when alternative transcription starts and alternative polyadenylation sites are considered, we may see that all genes are processed in multiple ways. It will be interesting to see how the products of alternative splicing and anti-sense transcription might interact.
This work has a number of take home messages.
- Like astronomy, when we can see deeper we see more. Next Gen technologies are giving us the means to interrogate large collections of individual RNA or DNA molecules and speculate more on functional consequences.
- Our limits are our imaginations. The reported experiments have used a variety of creative approaches to study genomic variation, sample expressed molecules from different strands of DNA, and measure protein DNA/RNA interaction.
- Good hands do good science. As pointed out in the paper from the Sanger Center on their implementation of Next Gen sequencing, the processes are complex and technically demanding. You need to have good laboratory practices with strong informatics support for all phases (laboratory, data management, and data analysis) of the Next Gen sequencing processes.
To see how, join us for a webinar next Wednesday, Dec. 17 at 10 am PDT, for RNA Expression Analysis with Geospiza.
Click on the figure to enlarge the text.