In my new role at TGAC I will be leading the group of computational biologists working on plant and animal genome analyses within the Genome Analysis Team. Our aims will include the organization of the analysis of sequence generated at TGAC, engaging with internal and external collaborators, nationally and internationally. A lot of the work will focus on (but will not solely be restricted to) the analysis of RNA-seq, ChIP-seq and Bisulphite sequencing data for the purposes of understanding how genes are regulated.

Coming Opportunities

I will be expecting to have openings in my group in the near future for student projects (Masters and PhD) as well as research associates and technicians. Meanwhile, if you are interested in joining or simply discussing ideas or potential projects in the the broad areas of transcriptomics, epigenomics and gene regulation, you are always welcome to drop me a line.

In order to have the most up-to-date version for the Human Genome set of genes and features sometimes it is necessary to convert from one assembly to another. In the past I have written a tutorial on how to remap from NCBI36 to GRCh37 human assemblies using liftOver. In this tutorial I present a simple step-by-step guide for feature remapping using NCBI’s remapping tool.

Important:

Please make sure you know in advance the assembly to which your aberration data is currently mapped to. If by mistake you remap an aberration already in GRCh37 to GRCh37 you will get new coordinates for the region mapped to the wrong coordinates.

The NCBI provides a web facility to convert coordinates from one assembly into another. To convert coordinates using their genome remapping service do the following:

1. Make sure that your data is in BED format,  e.g. “chr3            100000 999990 myId0000123” -> CNV aberration in NCBI36/hg18

• Please note that each field is separated by a tab and each line by a character return. Please follow this strictly or the remapping tool may throw an error.
• Add as many lines as aberrations you would like to remap

1. Go to the NCBI Remap page:

• http://www.ncbi.nlm.nih.gov/genome/tools/remap/

1. Select “Organism for source data” Homo Sapiens, “Source Assembly” NCBI36 (hg18) and “Target Assembly” GRCh37 (hg19)
2. Please leave all “Remapping Options” (Minimum ratio of bases that must remap, etc) with default values
3. Select for “Input format” BED, “Output format” Same as input
4. Paste your aberration in the input box where it says “Paste data here” and hit submit at the bottom of the page
5. Wait until results are returned
6. To retrieve results download “Mapping Report”, which is in excel format or alternatively Mapping report Sample in the results page

Please note that your aberration may remap to more than one location. I recommend that you manually check the coordinates and select the most appropriate of the doubly remapped aberration in the new assembly. Please also note that your aberration may not remap because the region is partially or entirely deleted in the new assembly or split in GRCh37. In this case I recommend that you use another start or end point position, maybe use the start/end of alternative probes until you find a region where it maps.

Another possibility could be to look at the genes for the region in the old assembly and select a region in GRCh37 that includes the same genes as in NCBI36. Each of these solutions requires careful deliberation and may not be applicable to your particular case (e.g. genes in different chromosomes would not allow remapping based on genes).

Unfortunately, people around the world are still trapped in the paper-based office paradigm when wanting to disseminate announcement information. Again and again they post their announcement to different places knowing that it will only reach a partial share of all potentially interested readers. They add data and clog online databases as no centralized repository is available for posting or getting information. Despite the great number of hours of work lost by millions of people trying to post, scientific organizations have been extremely slow to embrace community-shared announcement curation.

We (Rafael Jimenez and I) are promoting the creation of a community of organizations and people to lead iAnn, a centralized collaboration platform that coordinates curation efforts among scientific organizations. iAnn increases access to announcements through its dissemination tools, which have been designed specifically to integrate posts across many different websites with minimal effort. iAnn allows you to post your event, course, piece of news only once to a central repository, which is then disseminated seamlessly to relevant scientific organizations or websites according to keywords, dates or geographical location.

If you think iAnn is of interest to you please contact me (see contact information on the right) or wait for future developments that are about to come in Manuel Corpas’ Blog. Currently we are in a development phase for the project and would like to hear from potential users or scientific organizations if they have any thoughts or suggestions on the matter. Our aim is to change the way anyone posts and finds relevant information about any given professional field. iAnn promises to help many users keep up-to-date with relevant announcements more effortlessly. Perhaps from now on websites will be better able to have most of the events, courses, seminars, news, etc. that users would expect to find in them.

Beware of pasting gene names in an Excel spreadsheet with a default format, as these may be changed into dates.

From my current list of 19,026 genes that I have compiled as of now, here are the names of the genes that have been automatically changed by Excel into dates. In the table below, the first column denotes the date the gene name is changed to, the middle column the Ensembl ID of the gene and the right column the actual name that was changed by Excel into a date.

Sep-01    ENSG00000180096        SEPT1    
Sep-02    ENSG00000168385        SEPT2
Sep-03    ENSG00000100167        SEPT3
Sep-04    ENSG00000108387        SEPT4
Sep-05    ENSG00000184702        SEPT5
Sep-06    ENSG00000125354        SEPT6
Sep-07    ENSG00000122545        SEPT7
Sep-08    ENSG00000164402        SEPT8
Sep-09    ENSG00000184640        SEPT9
Sep-10    ENSG00000186522        SEPT10
Sep-11    ENSG00000138758        SEPT11
Sep-12    ENSG00000140623        SEPT12
Sep-14    ENSG00000154997        SEPT14

Mar-01    ENSG00000145416        MARCH1
Mar-02    ENSG00000099785        MARCH2
Mar-03    ENSG00000173926        MARCH3
Mar-04    ENSG00000144583        MARCH4
Mar-05    ENSG00000198060        MARCH5
Mar-06    ENSG00000145495        MARCH6
Mar-07    ENSG00000136536        MARCH7
Mar-08    ENSG00000165406        MARCH8
Mar-09    ENSG00000139266        MARCH9
Mar-10    ENSG00000173838        MARCH10
Mar-11    ENSG00000183654        MARCH11

Dec-01    ENSG00000173077        DEC1

The paper is freely available and open access.

Citation: Jimenez RC, Salazar GA, Gel B, Dopazo J, Mulder N, et al. (2011) myKaryoView: A Light-Weight Client for Visualization of Genomic Data. PLoS ONE 6(10): e26345. doi:10.1371/journal.pone.0026345

Sharing and comparing one’s genome with other personal genomes is a matter of necessity if one is to shed light on the meaning of one’s personal DNA.

This is why I became a genome blogger myself. Why one should be constrained by the information that genomic test reports provide? No personal genome analysis report can ever be complete, they will always be influenced by the biases of whomever is providing such a report.

*   *   *

Although no formal document seems to have been produced on what the core values for genome blogging should be yet, core beliefs driving personal genome-sharing should be made explicit. Here I present an initial and inherently imperfect first attempt to put in writing of what I believe genome blogger values could be. I do not expect every fellow blogger to agree with them, but I hope that at least they inspire some debate. These are not a fixed set of rules; on the contrary, I expect this thinking to evolve with the genomics technology itself. I base some of the ideas below on Marcus Wohlsen’s ‘Biopunk’ book, Meredith Patterson’s ‘biopunk manifesto’, Misha Angrist’s ‘Here is a human being’ book and Pekka Himanen’s ‘Hacker’s ethics’ book.

Core Values for Genome Blogging

1. Intelligent exploration, experimentation and trial to push the boundaries of knowledge are a right for ordinary people. The days in which genetic science was only done by university professors or people working in corporate labs are now over. Now everyone should have the power and legitimacy to be able to discover, develop and find new things about their own genome data.
2. Sharing with the world is more useful than keeping the data to oneself. Whether one wants to share genome data or keep it private it should be a matter personal choice. I have my own right to do what I want with my genome, learn from it, share it with the world or keep it private. Sharing personal experiences about personal genomics findings is a way of creative self-expression and a channel for curiosity to find its way to better self-awareness. Freedom to be open about one’s genome information and the ability to have accessibility to one’s own information is of paramount importance to every human being.
3. Whatever attitude a person has towards personal genome privacy, it should be utterly respected. Knowledge of genetics is not as important for informed consent as the personal/psychological attitude of the person. The decision of openness of personal genome data completely resides in the individual and although openness is the better default option, privacy must be utterly respected and not judged.
4. Personal genome data access should be affordable to all irrespective of nationality, gender, social background or any other circumstance. Whole genome sequencing and tools for its interpretation should become accessible to everyone, not just the realm of those who can pay for it. Genome interpretation tools should be accessible and free for all. Not having access to a personal genetic test is in itself a new kind of discrimination.
5. Stating that genetic tests merely provide non-clinical information misses the point of what personal genomics is all about. Genetic risks tests do tell something about one’s health, one’s ability to respond to certain drugs and one’s ethnic ancestry. Trying to downplay the importance of these predictions because we do not have enough statistical discrimination power does not take away the effect such predictions may cause in the recipient regardless of whether they right or wrong.
6. Genes affect one’s present but they do not determine one’s future. One’s genetic data is just one more factor among many others in predispositions, risks and behavioural reactions. Genes are affected by the environment as much as the environment is affected by my genes. Although some dramatic genetic diseases can significantly alter one’s life style, genes can never determine the decisions that make us the way we are.
7. Education in risks and opportunities for personal genetic testing should be the primary aim of policy makers. Restricting access to interested people makes no sense and it is virtually impossible to ensure. The power of Internet allows anyone to order a test with no need to physically be in any particular location.  
8. Corporate interest can never compromise any human right. Laws must fully protect individual human rights of equality for every person, irrespective of whatever risks are predicted from genetic data.
9. Privacy does not have to be incompatible with openness. Knowing one’s bank account movements are probably a better reflection of oneself than a personal genome.

Conclusion

Genome blogging is about sharing the thrill of discovering uncharted territory. Sharing one’s experiences on the Internet may help start answering personal questions without having to wait for others to find out. The challenge of personal genomics does not lie in the sequencing itself but in the interpretation of results. The wide access to the technology to the public is driving some policy makers to exert a “protective” approach to keep users away from unpredictable or undesirable “potential” consequences. However, legal and health systems seem hardly suited to keep up with advancements. It is pointless to restrict access to genetic testing: education in risks and opportunities seem a more reasonable approach. Despite the ease with which it is now possible to access one’s genome data, the personal genomics field is still inaccessible to most people.

After doing our whole genome genotypes, the next obvious step is to have our whole genomes sequenced. There is quite a lot of debate at the moment as to whether genome sequencing should be accessible to the general public and if so, to what extent. But I figured out that if “the rich and famous” can have their genome sequenced, perhaps with a bit of luck, the “ordinary and poor” (among which I include myself), could have a chance, even with zero budget. Zero budget for this exercise was an essential point of principle, given that we really would not be able to afford even a 10th of the price a genome currently costs (around $9,500; probably cheaper than this price by the time you are reading this).

I wasn’t sure how to do this, but I know that this might be possible and that we would get it done if we could. So I went onto the Internet and searched for whole genome sequencing. I found three potential good candidates that could do it on demand: Complete Genomics, the Illumina personal sequencing services and the Beijin Genomics Institute (BGI).  So the first thing I did, I sent them an email. Given that we had no money to spend and that there is no such a thing as free lunch, we thought that we needed to offer something substantial in return since we were asking them to waive us the fee of ~$50,000. The only substantial thing we could really offer was publicity, so the following proposal was sent to those three companies via their websites:

Dear Sir/Madam: I would like to offer you a deal/proposal. My family would like to have their whole genome sequenced with your company. In exchange for releasing to the public openly and freely on the Internet our genomes we thought you could sponsor us. This action could attract *a lot of attention* to [company name], as this is a pioneering move. Currently a very limited set of people are actually interested in sequencing their genomes. The only way you can reach the ordinary citizen (sooner rather than later) is if ordinary people, like my family publish their experiences and pave the way. My family, an ordinary family, constitutes an example of what this technology could do for any ordinary person, not just a scientist, etc. In addition to this, I want to fully research all of the social/ethical implications that publishing this information can bring. We also hope to share this information with the world. Currently all my family has genotyped their genomes with 23andMe and put all this data in the Internet for free download: http://manuelcorpas.com/five-family-relatives-genome-download/ To our knowledge, this is the first time that anything like that has been done. In barely a month since this information has been published, four different analyses from specialists/hobbyists have reached us, making us learn that dad, for example, is lactose intolerant [1]. Our point is that now, with DNA sequence providers, the door opens for DIY genome mining. The power of the Internet and computers may bring this technology to computer savvy people. For example, our 23andMe genomes are now been taken by SNPedia and several other ancestry projects such as Eurogenes and Artemis: http://www.snpedia.com/index.php/User:Manuelcorpas http://bga101.blogspot.com/2011/03/mds-analysis-of-southern-europe.html http://dioegenesartemis.blogspot.com/2011/04/first-results.html Although up to date the information provided by 23andMe has not revealed any nasty surprises about our genomes, we are aware that now anyone can report new findings that were not initially discovered in our genomes. We believe, however, that as a family we can gain a lot more than lose by sharing our genome data with the world. I believe my proposal could bring a lot of exposure to [company name] and therefore would request whether you could consider this offer. Best wishes, Manuel

Illumina never got back to us. Looking around we learned that their policy is that sequencing should be done with medical prescription. Fair enough.

I couldn’t wait long so I continued researching the matter and found Complete’s contact phone number on their website, so I rang them. To my surprise I was put through and the person was very polite with me and keen to listen to what I had to say. Since I have learned that Complete had already sequenced and published 69 genomes, available via this website:

http://www.completegenomics.com/sequence-data/download-data/

Among these genomes there is a multigenerational family with a bigger pedigree than the one I was proposing. This obviously meant that our offer wasn’t as innovative as we initially thought of. It seems that Complete Genomics will not do (at least for the time being) “Direct-to-consumer” business, but that still, their goal is to become the “Intel Inside” for human genome sequencing efforts, the technology underlying most human genome analyses. I thought that that was a cool objective if attainable.

I still didn’t give up. I tried to see whether there was a chance that Complete might change their mind, so I wrote to them about our incredibly interesting experience of family dynamics and family communication issues while discussing our personal genomes. So far we have not been lucky enough to get our genomes sequenced for free. Despite not achieving our outcome, there is a lot we have learned on the way though. What an interesting experience.

This is the end of part one on Getting My Genome Sequencing Done.

[1] This information was actually available in our 23andMe reports, but we missed it initially. We learned about this condition with the SNPedia tool Promethease

This is an unanticipated benefit we have experienced as a family for publishing our genomes on the Internet. Using Promethease’s report we were able to learn that dad is lactose intolerant. The fact that he did not like milk and had not taken milk in years kind of made sense when we discovered that his two SNPs rs4988235(C;C) and rs182549(C;C) make him unlikely to digest lactose with 70% probability. This result regarding lactose intolerance was in fact in the 23andMe report but we missed it.

It is clear that Direct-to-consumer genetic companies do try to cater to the non-expert, i.e. the majority of its customer base. The novel SNPedia visualization tool will be an useful addition to those of us who strive to DIY our own discoveries about our personal genomes data.

Using his visualization tool, when I compare all my SNPs with those of my sister’s, I find that 68% of mine are identical to hers, a total of 389,250 (see below).

SNP comparison between my sister and myself

Note that the graph is using a logarithmic scale. Of all our analyzed SNPs, 25% are halfmatch (i.e. one of the alleles is common to both of us) and about 2% are conflicts. Example of conflicts may include different SNPs with the same position. This, according to Mike, may not be an accident. Because I know that we were analyzed in two different array platforms, version 2 and version 3 respectively, I can now tell the number of SNPs that are different between both of us, i.e. not present in either genotype.  Of the total 0.5 Million plus SNPs in my genome about 29,082 do not match hers.

The other nice feature this tool provides is an actual graphical representation of chromosomal SNPs in a map of pixels, colored consistently with the above notations: light blue means match, dark blue halfmatch, red conflict and grey different SNPs:

Pixelated map of chromosome 1/chromosome 1 comparison between me and sister

The above figure shows two representations for chromsome/chromosome comparison between my chromosome 1 and my sister’s. Clearly most of the area is light blue, indicating complete match. Also the number of differences, halfmatches and conflicts are reported. Clicking on any of these links, one can find the actual SNPs in conflict, getting an output that looks like this:

1	rs9729550	1	1125105	CC	AA
2	rs12142199	1	1239050	GG	AA
3	rs7531583	1	1696020	GG	AA
4	rs6681938	1	1771080	CC	TT
5	rs41307846	1	1949559	GG	--
6	rs3128296	1	2058766	TT	GG
7	rs262654	1	2079386	AA	GG
8	rs262688	1	2103425	GG	TT
9	rs6659405	1	2362949	TT	GG
10	rs4648482	1	2739781	CC	TT
11	rs2483266	1	3225901	CC	TT
12	rs868688	1	3290667	TT	CC
13	rs10492939	1	3292731	AA	GG
14	rs2493268	1	3298358	TT	CC
15	rs871822	1	3302774	GG	TT
16	rs12024847	1	3310659	TT	CC
17	rs2821017	1	3510731	GG	AA
18	rs3765761	1	3620336	CC	TT
19	rs3765766	1	3624520	TT	CC
20	rs4233262	1	4136842	CC	TT
21	rs966321	1	4215064	GG	TT
22	rs964715	1	4216644	TT	CC
23	rs1390136	1	4241703	CC	TT
24	rs4654545	1	4425464	TT	CC
25	rs446529	1	4695274	CC	TT

This table shows that for the first SNP, rs9729550, I have CC while my sister has AA.

In conclusion, Promethease and the SNPedia visualization tool is helping me learn more about my SNP genotype results, complementing the information that I initially got from my Direct-to-consumer provider. Hopefully I will be able to do some additional research based on the results hereby obtained.

If you want to see my family’s genomes with Mike Cariaso’s tool you can find it here:

http://files.snpedia.org/reports/promethease_data/promethease_corpas_family_comparison_newfamily.html

Don’t forget to send me any exciting findings that you might encounter!

The flip side of this is the nascent trend to outsource database annotation to the general public. Databases like Rfam [3] or Pfam [4], two popular RNA and protein family databases, have adopted the strategy of outsourcing their annotation to Wikipedia. Realizing that it is impossible to keep up with the literature, an attempt was made by Rfam to seed Wikipedia with database-specific information. They then developed a system to collect Wikipedia text from created entries periodically to repopulate back the corresponding RNA entry. The price they had to pay was losing control on what gets entered into the Wikipedia entry. However, benefits seem to outstrip this loss of control, including ready access to an army of casual annotators and a dramatically increased exposure of the database itself (Wikipedia consistently ranks top of the list for most RNA family searches in Google). This means that their chances of having up-to-date content is increased, as well as better awareness of the resource, justifying future cycles of funding.

Something that started as an experiment in Rfam seems to be spreading to other databases as they begin to assess how to address their annotation bottleneck. It seems that outsourcing annotation of Biomedical databases to Wikipedia is a solution worth considering as curation practices continue evolving to cope with current fund shortages. Generalized lack of funding for research and the establishment of community wiki-style annotation practices may mean that funding agencies may be ever more reluctant to provide funding for database curation. Perhaps this is the time to start rethinking future plans for those of us who care about biological databases and their contents. Is now the time ripe for embracing Wikipedia to the full?

[1] http://www.ncbi.nlm.nih.gov/omim

[2] http://www.ncbi.nlm.nih.gov/

[3] http://rfam.sanger.ac.uk/

[4] http://pfam.sanger.ac.uk/

[5] http://www.wikipedia.org/