One of the things that I’ve been working a lot on over the last year is setting up pipelines to analyze whole genome sequencing data from human samples. This work is now coming to fruition and one part of that is that we (at the SNP&SEQ Technology Platform) have now released data for our users and others to see. It’s still a work in progress, but most of the pieces are in place at this stage.
The data is being release under a Creative Commons Attribution-NonCommercial 4.0 International License, so as long as you attribute the work to the SNP&SEQ Technology Platform you can use it for non-commercial purposes. You’ll find the data here:
Being a fan of open science working for an employer that will release data for the benefit of the community makes me jump with joy!
P.S. Like to have a look at the code that makes it all happen, checkout the National Genomics Infrastructure github repo.
Not that long ago I wrote about the use of CRISPR-CAS9 systems and the ongoing ethical debate on their use in humans. As it turns out this future is even closer that I might initially have thought. This week a Chinese group published a paper where they used these systems to do genome editing in non-viable human embryos.
The original paper is available here: http://link.springer.com/article/10.1007%2Fs13238-015-0153-5 And nature news piece on the topic can be found her: http://www.nature.com/news/chinese-scientists-genetically-modify-human-embryos-1.17378 Finally the findings were also covered in Swedish mainstream press (in Swedish) here: http://www.dn.se/ekonomi/forsta-manskliga-genmanipulationen-genomford/
The study itself draws attention to some problems related to genome editing using these techniques. The poor success rates (28 out of 86 embryos tested were successfully spliced) and problems with off-target mutations hinder the immediate clinical use of the technique. These are however problems that I’m sure will be addressed by technology development.
More importantly I think that this highlights the importance of establishing ethical frameworks for the use of gene-editing. Interestingly the paper was rejected both by Nature and Science “in part because of ethical objections” – it remains to be seen if such objections will hold in the future.
Personally I’m as of yet undecided on the morality of carrying out gene editing in embryos. While the promise of cures to heritable disease is wonderful, it’s easy to see a slippery slope from there into more dubious uses. Also it warrants the questions of what is to be considered a disease/disability.
Today at the SciLifeLab Large Scale Human Genome Sequencing Symposium Dr. Anna Lindstrand spoke about a study indicating CTNND2 as a candidate gene for reading problems. Are such mild disabilities to be considered for gene editing? Maybe not – but where do we draw the line? Once the technology is available I have little doubts that some will want to use it produce “genetically enhanced” humans.
The Nature news article referenced above ends of with the somewhat ominous quote: “A Chinese source familiar with developments in the field said that at least four groups in China are pursuing gene editing in human embryos.” Certainly we are going to hear more on this topic in the future.
Last week I came across a comment article in Nature by Jeffery Chang titled “Core services: Reward bioinformaticians”. I found it highly interesting, but I’m not sure I agree with the conclusions draw by the author.
Chang argues that “biologists are increasingly finding that questions that are initially based on a single protein or gene quickly expand to require large-scale experiments” and thus the need for bioinformaticians increase. His answer to this is that the scientific community should invest in alternate career paths for bioinformaticians. And while I believe that the analysis of the situation is spot on – I think that there is a different solution to the problem. I think that rather than to to create a separate structure where bioinformaticians act as support to biologists, we should include more applied bioinformatics in basic training for biologists.
I do think that anyone would argue that having a career in physics means having a firm understanding of math. The reason for this is of course that math is an essential tool for a physicist. In the same way I believe that a firm understanding of applied bioinformatics is crucial to the work of a biologist in a high-throughput assay world.
“To give greater support to researchers, our centre set out to develop a series of standardized services. We documented the projects that we took on over 18 months. Forty-six of them required 151 data-analysis tasks. No project was identical, and we were surprised at how common one-off requests were (see ‘Routinely unique’). There were a few routine procedures that many people wanted, such as finding genes expressed in a disease. But 79% of techniques applied to fewer than 20% of the projects. In other words, most researchers came to the bioinformatics core seeking customized analysis, not a standardized package.”
I think this “routinely unique” situation only strengthens the arguments that the researches asking the questions also need to be able to answer those questions themselves. The view that I’ve sometimes come across, that bioinformatics is “just a support thing” which should be provided be somebody else bothers me. It purports the false image that one can work in an informatics rich area without investing in the know-how.
To some extent bioinformatics is already included in biology programs, but not to the extent that I think that it needs to be. The tools of the trade in bioinformatics need to be in there. Skills such as scripting, working with high-performance computing systems, etc all need to be taught. In the long run making the bioinformaticians of today redundant.
Of course there will always be a need for specialisation (and I don’t want to loose my job), but to argue that bioinformatics is a thing separate from biology I think misses the point. Rather than to make ourselves indispensable we should strive to provide biologists with the tools and the knowledge they need to answer the biological questions of tomorrow. That way we will be able to say – the bioinformatician is dead, long live bioinformatics!